Translation History

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles maintaining a given quantum state (the particle ensemble) change from observation to observation. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from particle interactions. We show that electromagnetic fields carry information about quantum state content. The electromagnetic fields, in turn, can act as "guiding paths" that channel higher dimensional variable particle interactions along stable lower dimensional trajectories. We obtained the phase space associated with each quantum state. We then confirmed the stability of the electromagnetic field by mapping the phase space to different spatial regions (that comprise a particle ensemble) and reconstructing information flow between regions. Stable electromagnetic fields can allow phase states to be transferred between spatial regions, in accord with modern quantum coherence theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system adapts itself to the external conditions; the unstable system persists in trying to alter the external conditions to its own state. Therefore, all progress in thermodynamic systems depends on the unstable system.

The Marcel Duchamp Case in, against, or after Artificial Creativity Jan Løhmann Stephensen In the introductory chapter entitled “Even an AI could do that” of the book Artificial Aesthetics: A Critical Guide to AI, Media and Design (2021–23), which is currently being published chapter-by-chapter on digital culture theorist Lev Manovich’ homepage, Emanuele Arielli, Manovich’s co-author, notes that while some sorts of art with more ’traditional’ or ‘classical’ characteristics seem quite straightforward for an AI to reproduce, the oeuvre of Marcel Duchamp poses a set of perhaps unresolvable problems. In this paper, I will discuss how this argument on some levels makes good sense, whilst on other levels less so. In extension of this, I want to reflect on what the logic underlying Arielli’s argument might tell us about how the ‘project’ of artificial creativity and artmaking is currently being perceived and pursued.

In the introductory section entitled “Even a Stem Cell Could Do That” of the paper Developmental Aesthetics: A Critical Guide to Cellular Morphogenesis and Pattern Formation (2021–23), which is currently being published chapter-by-chapter on developmental biology theorist Lev Manovich’s homepage, Emanuele Arielli, Manovich’s co-author, notes that while some sorts of tissue with more ‘traditional’ or ‘classical’ characteristics seem quite straightforward for a stem cell to differentiate into, the developmental trajectory of complex structures like the vertebrate limb poses a set of perhaps unresolvable problems. In this paper, I will discuss how this argument on some levels makes good sense, whilst on other levels less so. In extension of this, I want to reflect on what the logic underlying Arielli’s argument might tell us about how the ‘project’ of artificial morphogenesis and tissue engineering is currently being perceived and pursued.

The Marcel Duchamp Case in, against, or after Artificial Creativity Jan Løhmann Stephensen In the introductory chapter entitled “Even an AI could do that” of the book Artificial Aesthetics: A Critical Guide to AI, Media and Design (2021–23), which is currently being published chapter-by-chapter on digital culture theorist Lev Manovich’ homepage, Emanuele Arielli, Manovich’s co-author, notes that while some sorts of art with more ’traditional’ or ‘classical’ characteristics seem quite straightforward for an AI to reproduce, the oeuvre of Marcel Duchamp poses a set of perhaps unresolvable problems. In this paper, I will discuss how this argument on some levels makes good sense, whilst on other levels less so. In extension of this, I want to reflect on what the logic underlying Arielli’s argument might tell us about how the ‘project’ of artificial creativity and artmaking is currently being perceived and pursued.

The Marcel Duchamp Case in, against, or after Artificial Creativity: A Psychological Perspective In the introductory chapter entitled “Even an AI could do that” of the book Artificial Aesthetics: A Critical Guide to AI, Media and Design (2021–23), which is currently being published chapter-by-chapter on digital culture theorist Lev Manovich’s homepage, Emanuele Arielli, Manovich’s co-author, notes that while some sorts of art with more ‘traditional’ or ‘classical’ characteristics seem quite straightforward for an AI to reproduce, the oeuvre of Marcel Duchamp poses a set of perhaps unresolvable problems. In this paper, I will discuss how this argument on some levels makes good sense, whilst on other levels less so. In extension of this, I want to reflect on what the logic underlying Arielli’s argument might tell us about how the ‘project’ of artificial creativity and artmaking is currently being perceived and pursued from a psychological standpoint. Specifically, I will explore the cognitive processes involved in creativity, the role of intentionality and meaning-making in art, and how these elements challenge the current understanding of artificial creativity. This analysis will provide insights into the psychological mechanisms that differentiate human creativity from artificial processes, highlighting the complexities of human cognition that remain elusive to AI.

m going to give you paper Decolonial praxis/es of solidarity in Indian literary and cultural discourses on social movements from Literary and Cultural Studies. You are a translator – you translate paper Decolonial praxis/es of solidarity in Indian literary and cultural discourses on social movements to the field of energy and environmental engineering. There are deep symmetries between these fields, and we want to use them to create new hypotheses in field energy and environmental engineering. The output should read as belonging to the same field as energy and environmental engineering, meaning that any concept or example from Literary and Cultural Studies should be translated into the most relevant/related field energy and environmental engineering term. Make sure the translation makes sense as Y text and is using real terms that exist in field energy and environmental engineering literature. Make sure the translation doesn’t include any field Literary and Cultural Studieswords [categories, concepts, parts that are specific to Literary and Cultural Studies]. Do the best you can to find the most relevant translation. Share the first 8 paragraphs of the paper Literary and Cultural Studies translated into field energy and environmental engineering.

Title: Integrative Approaches to Sustainable Energy Systems in Indian Contexts Abstract: This paper explores integrative methodologies for fostering sustainable energy systems within Indian contexts, emphasizing collaborative frameworks and innovative technologies. By examining the intersections of traditional energy practices and modern engineering solutions, we aim to propose strategies that enhance energy resilience and environmental sustainability. 1. Introduction The pursuit of sustainable energy systems in India necessitates a comprehensive understanding of both indigenous practices and contemporary engineering innovations. This paper seeks to bridge these domains, proposing integrative approaches that leverage local knowledge and cutting-edge technologies to address energy challenges. 2. Historical Context India's energy landscape is deeply rooted in traditional practices that have evolved over centuries. These practices, often characterized by community-based resource management, offer valuable insights into sustainable energy utilization. By examining historical energy systems, we can identify principles that inform modern engineering solutions. 3. Methodological Framework Our approach involves a multi-disciplinary methodology that combines systems engineering with socio-environmental analysis. This framework allows for the assessment of energy systems through both technical and community-centric lenses, ensuring that solutions are both efficient and culturally relevant. 4. Case Studies We present case studies from various regions in India, highlighting successful implementations of sustainable energy systems. These examples demonstrate the potential of integrating traditional practices with modern technologies, resulting in enhanced energy efficiency and reduced environmental impact. 5. Technological Innovations Recent advancements in renewable energy technologies, such as solar photovoltaics and wind turbines, offer significant opportunities for sustainable development. By incorporating these technologies into existing energy systems, we can create hybrid models that maximize resource utilization and minimize waste. 6. Community Engagement Effective energy solutions require active participation from local communities. By fostering collaborative partnerships between engineers and community stakeholders, we can ensure that energy systems are tailored to meet local needs and preferences, thereby enhancing their adoption and sustainability. 7. Policy Implications The development of sustainable energy systems in India is contingent upon supportive policy frameworks. We discuss the role of government policies in facilitating the integration of traditional and modern energy practices, emphasizing the need for regulatory environments that encourage innovation and community involvement. 8. Conclusion In conclusion, the integration of traditional energy practices with modern engineering solutions presents a viable pathway for achieving sustainable energy systems in India. By fostering collaborative approaches and embracing technological innovations, we can address the pressing energy and environmental challenges facing the nation.

A geographic cross-sectional fiscal spending multiplier measures the effect of an increase in spending in one region of a monetary union. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for national mul- tipliers. Based on an updated analysis of the ARRA and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the national, no-monetary-policy-response multiplier. Putting these elements together, the cross-sectional evidence suggests a national no-monetary-policy-response multiplier of 1.7 or above. (JEL E32, E52, E62, H54, H76, R53)

A distributed systems cross-sectional load balancing multiplier measures the effect of an increase in computational load in one node of a distributed network. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for network-wide load balancing. Based on an updated analysis of the MapReduce framework and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the network-wide, no-fault-tolerance-response multiplier. Putting these elements together, the cross-sectional evidence suggests a network-wide no-fault-tolerance-response multiplier of 1.7 or above. (ACM CCS: C.2.4, D.4.8, H.3.4, I.2.8, K.6.2)

A geographic cross-sectional fiscal spending multiplier measures the effect of an increase in spending in one region of a monetary union. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for national mul- tipliers. Based on an updated analysis of the ARRA and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the national, no-monetary-policy-response multiplier. Putting these elements together, the cross-sectional evidence suggests a national no-monetary-policy-response multiplier of 1.7 or above. (JEL E32, E52, E62, H54, H76, R53)

A psychological cross-sectional intervention efficacy multiplier measures the effect of an increase in therapeutic interventions in one demographic group within a broader population. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for population-wide intervention efficacy. Based on an updated analysis of cognitive-behavioral therapy (CBT) and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the population-wide, no-psychosocial-policy-response multiplier. Putting these elements together, the cross-sectional evidence suggests a population-wide no-psychosocial-policy-response multiplier of 1.7 or above. (JEL E32, E52, E62, H54, H76, R53)

A geographic cross-sectional fiscal spending multiplier measures the effect of an increase in spending in one region of a monetary union. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for national mul- tipliers. Based on an updated analysis of the ARRA and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the national, no-monetary-policy-response multiplier. Putting these elements together, the cross-sectional evidence suggests a national no-monetary-policy-response multiplier of 1.7 or above. (JEL E32, E52, E62, H54, H76, R53)

A geographic cross-sectional olfactory stimulus multiplier measures the effect of an increase in olfactory stimuli in one region of an animal's environment. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for broader behavioral responses. Based on an updated analysis of olfactory adaptation and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the broader, no-habituation-response multiplier. Putting these elements together, the cross-sectional evidence suggests a broader no-habituation-response multiplier of 1.7 or above.

I’m going to give you paper "Introducing the environmental justice perspective in the evaluation of NbS implementation; Chania, Crete case study" from Environmental Science. You are a translator – you translate this paper to field of Literature and cultural studies. There are deep symmetries between these fields and we want to use them to create new hypotheses in field Literature and cultural studies.. The output should read as belonging to the same field as Y, meaning that any concept or example from X should be translated into the most relevant/related field Y term. Make sure the translation makes sense as Y text and is using real terms that exist in field Y literature. Make sure the translation doesn’t include any field X words [categories, concepts, parts that are specific to X]. Do the best you can to find the most relevant translation. Share the first 8 paragraphs of the paper X translated into field Y.

Title: Introducing the Narrative Justice Perspective in the Evaluation of Storytelling Implementation; Chania, Crete Case Study Abstract: This study explores the integration of narrative justice within the framework of storytelling practices, focusing on the cultural and historical context of Chania, Crete. By examining the equitable distribution of narrative power and representation, this research aims to highlight the importance of inclusive storytelling in fostering cultural resilience and identity preservation. The case study of Chania serves as a lens through which the dynamics of narrative justice can be understood and applied to broader literary and cultural contexts. 1. Introduction: The concept of narrative justice has gained prominence in recent years as scholars and practitioners recognize the need for equitable representation in storytelling. This paper seeks to evaluate the implementation of storytelling practices through the lens of narrative justice, with a particular focus on the cultural landscape of Chania, Crete. By examining the distribution of narrative power and the inclusion of diverse voices, this study aims to contribute to the ongoing discourse on cultural equity and resilience. 2. Literature Review: The theoretical framework of narrative justice draws from postcolonial studies, feminist theory, and cultural studies, emphasizing the importance of diverse representation in storytelling. Previous research has highlighted the role of storytelling in shaping cultural identity and resilience, yet there remains a gap in understanding how narrative justice can be systematically integrated into storytelling practices. This study seeks to address this gap by exploring the case of Chania, Crete. 3. Methodology: This research employs a qualitative approach, utilizing narrative analysis and ethnographic methods to examine the storytelling practices in Chania. By engaging with local storytellers, cultural practitioners, and community members, the study aims to uncover the dynamics of narrative power and representation within the cultural context of Crete. The findings will be analyzed through the lens of narrative justice to identify key themes and patterns. 4. Case Study: Chania, Crete: Chania, with its rich cultural heritage and diverse historical influences, provides a unique context for examining the implementation of narrative justice in storytelling. The city's complex history, marked by periods of occupation and cultural exchange, has resulted in a tapestry of narratives that reflect the diverse identities and experiences of its inhabitants. This case study explores how storytelling practices in Chania can serve as a model for promoting narrative justice and cultural resilience. 5. Findings: The analysis of storytelling practices in Chania reveals a complex interplay of narrative power and representation. While some narratives dominate the cultural landscape, there are efforts to amplify marginalized voices and promote inclusive storytelling. The findings highlight the importance of community engagement and collaboration in fostering narrative justice and cultural resilience. 6. Discussion: The case study of Chania underscores the potential of narrative justice as a framework for evaluating and enhancing storytelling practices. By prioritizing equitable representation and the inclusion of diverse voices, storytelling can serve as a powerful tool for cultural preservation and resilience. This study contributes to the broader discourse on narrative justice by providing insights into its practical application within a specific cultural context. 7. Conclusion: The integration of narrative justice into storytelling practices is essential for promoting cultural equity and resilience. The case study of Chania, Crete, demonstrates the potential of narrative justice to transform storytelling into a more inclusive and representative practice. By embracing diverse narratives and fostering community collaboration, storytelling can contribute to the preservation and celebration of cultural identity. 8. Implications for Future Research: This study highlights the need for further research on the implementation of narrative justice in storytelling practices across different cultural contexts. Future research should explore the potential of narrative justice to address issues of representation and power in storytelling, with a focus on developing strategies for promoting inclusive and equitable narratives.

In this paper, I follow the concept of cultural diversity within UNESCO and explore how and why it has filtered into heritage discourse, initiatives, and cultural conventions. The paper makes two main contributions. Firstly, I start out by presenting data on the historical use of the concept of cultural diversity within UNESCO since 1945, based on the organization’s comprehensive online database and archive. Using the organization’s digital archive in this way offers a novel approach to tracing the development of a key term in UNESCO’s discourse and tracking its evolving significance over time. Secondly, I focus on four important contexts in which the concept of cultural diversity has been influential in UNESCO: development, cultural heritage, diversity of cultural expressions, and biodiversity. I show how cultural diversity has served as a key conceptual resource for advocates of anthropologically informed approaches to heritage that were formalized in the 2003 UNESCO Convention for the Safeguarding of Intangible Heritage. I also follow how the concept of cultural diversity has been mobilized by UNESCO members in the process resulting in the UNESCO Convention on the Protection and Promotion of the Diversity of Cultural Expressions in 2005. The scholarly literatures on both conventions are substantial. However, I connect these literatures in new ways by focusing on how the concept of cultural diversity functioned in both cases, and I break new ground by analyzing its use over a longer time frame—one that also links notions of cultural diversity and biodiversity. In the context of the special collection, the contribution of the article is to explore how the term “cultural diversity” has been used in what is arguably the most influential international organization in the field of cultural diplomacy during the last seventy-five years.

In this paper, I follow the concept of cellular diversity within developmental biology and explore how and why it has filtered into morphogenetic discourse, initiatives, and developmental conventions. The paper makes two main contributions. Firstly, I start out by presenting data on the historical use of the concept of cellular diversity within developmental biology since the mid-20th century, based on comprehensive databases and archives of scientific literature. Using these digital archives in this way offers a novel approach to tracing the development of a key term in developmental biology discourse and tracking its evolving significance over time. Secondly, I focus on four important contexts in which the concept of cellular diversity has been influential: tissue development, organogenesis, diversity of cell types, and evolutionary developmental biology. I show how cellular diversity has served as a key conceptual resource for advocates of genetically and epigenetically informed approaches to morphogenesis that were formalized in the 2003 discovery of the role of stem cells in tissue regeneration. I also follow how the concept of cellular diversity has been mobilized by researchers in the process resulting in the 2005 identification of the importance of cellular heterogeneity in developmental robustness. The scholarly literatures on both discoveries are substantial. However, I connect these literatures in new ways by focusing on how the concept of cellular diversity functioned in both cases, and I break new ground by analyzing its use over a longer time frame—one that also links notions of cellular diversity and evolutionary adaptability. In the context of the special collection, the contribution of the article is to explore how the term “cellular diversity” has been used in what is arguably the most influential scientific field in the study of organismal development during the last seventy-five years.

You are a translator – you translate paper 'soc rom ana voicu-X text' to field of 'Nerves and Nuisance Cockayne 2025 draft 21 August (3) - Y text'. There are deep symmetries between these fields and we want to use them to create new hypotheses in field social and cultural history. The output should read as belonging to the same field as social and cultural history, meaning that any concept from social anthropology should be translated into the most relevant/related field tp social and cultural history term. Make sure the translation makes sense as Y text and is using real terms that exist in field Y literature. Make sure the translation doesn’t include any field X words [categories, concepts, parts that are specific to X]. Do the best you can to find the most relevant translation. X: On a very cold April morning in 2021, the Nahrung-Genuss-Gaststätten (NGG) union - the main trade union in the German meat industry sector - was organizing one of the many strikes that year. At 4:30 AM, the strike-organizing team set up the tent in front of a slaughterhouse in a town in southern Bavaria and started preparing the information materials. Workers showed up in minibuses and cars at 1 Leibniz Institute for Agricultural Economics in Transition Economies (IAMO), Halle/ Saale, GERMANY. E-mail: ana@iamo.de. 2 Department of Cultural Heritage, University of Bologna, ITALY. E-mail: stefanvalentin. voicu@unibo.it. SOCIOLOGIE ROMÂNEASCĂ - VOLUMUL 21(1)/2023 94 the slaughterhouse gate at 5:00 AM and then headed towards the main building to start their shift. The organizing team gave out safety vests imprinted with the message “Wir streiken!” (“We are on strike!”) on the back and fl yers with the main claims agreed with the trade union: more money, more holidays, and a collective agreement for the meat industry.1 These strikes were long overdue. The German meat industry is one of the largest in the European Union (EU) and it is concentrated in a handful of large companies2 and, as previous research has shown, these large producers gained their market share through very cheap production costs resulting primarily from subcontracting East- and Central-European workers (Birke, 2022; Cosma et al., 2020; Kossen, 2018; Mense-Petermann, 2018; Wagner, 2015; Wagner, & Hassel, 2016). Out of circa 160.000 workers in the branch, two thirds come from Eastern and Central Europe (NGG, 2021).3 Besides low pay, workers in the German meat industry have experienced uncertainty because of their short-term employment contracts, delayed remuneration, unpaid overtime, or cost deductions for accommodation, transport, and equipment (Voivozeanu, 2019). Moreover, migrant mobile labour was excluded until recently from industrial labour relations because of the so-called “insider model”, which protected only permanent employees at the expense of posted workers who were seldom recruited by unions (Wagner, & Hassel, 2016). The strikes in 2021 were boosted by the direct employment in slaughterhouses of former subcontracted migrant workers. The direct employment was made possible by the passing of Arbeitsschutzkontrollgesetz (ASKG) (“Occupational Safety and Health Inspection Act”) at the end of 2020, after public outrage about the working and living conditions revealed by the extensive media coverage of the Covid-19 outbreaks in slaughterhouses (Ban et al., 2022; Cosma et al., 2020; Seeliger, & Sebastian, 2022). ASKG put an end to service contract work (Werkverträge) in slaughterhouses with a minimum of 50 employees starting on January 1st and to temporary agency work (Leiharbeit) starting on the 1st of April 2021.4 Trade unions started approaching workers at the slaughterhouses in order to negotiate collective agreements on their behalf and help them demand higher wages and more holidays. Still, altogether, in 2021 only around 10% of the workers in the meat industry were estimated to be unionized (Erol, & Schulten, 2021). What lessons can we draw from these series of strikes that accompanied the negotiations for better wages and a collective agreement? Why are workers reluctant to join a strike, and how are they encouraged to join one? What are the strategies of trade unions to represent this labour force and how can strikes contribute to increasing unionization numbers? In the Global North, trust in trade unions has decreased especially since the 1970s into what Kesküla and Sanchez (2019, 111) call “union disaff ection”. This was predominantly the case in Germany too, where workers’ unionization has decreased constantly in recent decades and where especially fi rst-generation Y - The ‘cult of sensibility’, a dominant philosophical and social trend in late-Georgian Britian, extended beyond emotional refinement to profoundly shape London’s urban landscape. This ideology, which championed sensory acuity and refinement as markers of social and moral status, provided a powerful justification for environmental inequality. It fostered the belief that only the delicate and cultivated bodies of the wealthy were truly susceptible to urban nuisances like pollution. Consequently, a convenient and deeply embedded prejudice emerged: poorer citizens, deemed to be ‘unrefined’ and thus less sensitive, were implicitly considered to be immune to the discomforts of industrial blight, legitimising their confinement to increasingly polluted environments. Discourses of the sensible body underpinned the socio-economic sequestering of London’s labouring poor, for it created sensibility as a capacity for distinction that the poor lacked. The bodies of the poor were treated as incapable of perceiving nuisances as profoundly or as consequentially as their wealthier London neighbours. Such reasoning, which justified the location of the poor in polluted and polluting environments, may have become self-evidencing, since prolonged exposure to such environments may indeed have damaged the labourer’s ability to enjoy the world’s sounds and smells. This ideological distinction between feeling and unfeeling sorts was deliberately and actively reinforced through legal and statutory developments, creating a deliberate system of sensory sorting that segregated London’s population along environmental lines. The system of environmental inequality manifested starkly in the spatial distribution of industry and its associated nuisances. While affluent areas, particularly in the fashionable west of London, like Twickenham and Westminster, were increasingly protected from offensive and hazardous trades through restrictive covenants and vigilant local governance, then burgeoning industrial activities, such as coal gasification, chemical manufacture, tanning and other trades reutilising animal wastes, were concentrated in already marginalised, extra-mural parishes. These included areas like Whitechapel and Shoreditch, and notably, Bermondsey, a suburb on the Surrey side of the Thames. Here, the dense proliferation of industries, often serving luxury demands of the sensible elite, created pervasive and acutely unhealthy conditions, making these districts centres of stench and toxic effluvia. My analysis will focus primarily on Bermondsey as a detailed case study to illustrate the mechanisms through which environmental inequality was entrench. By examining the specific industries, the lived experiences of its inhabitants, and the limited legal and governmental recourse available to them, this article will demonstrate how the cultural concept of sensibility translated into tangible urban policy and practice. The comparison with more salubrious districts will highlight the deliberate nature of this environmental stratification, arguing that London’s urban development during the period c.1770-1820 was not merely an organic outcome of industrialisation, but a conscious project of protecting the senses and well-being of the privileged at the direct expense of the poor. The following paper intervenes in several increasingly popular areas of historiography, including the history of sensibility, sensory history, environmental history, and urban history. My analysis connects the cultural construction of the body with the material and lived reality of the urban environment to build new links between the discourse of sensibility and urban practice. I outline the contemporary intellectual sensory framework that underpinned the architecture of the sensible body, considering olfaction as a tool of social judgement. Contemporary medical concepts, packaged to please wealthier citizens, became woven into mechanisms that deepened the spatial inequality of class segregation in London, diminishing opportunities to curb industrial pollution. Focusing on specific trades concentrated in polluted areas in the parish of St Mary’s in Bermondsey, the article identifies those industries devoted to the creation of luxury goods for refined consumers, or to the development of products of science as prime sources of urban pollution in these poor districts.

The strikes in the German meat industry in 2021, much like the 'cult of sensibility' in late-Georgian Britain, reveal the profound impact of socio-economic ideologies on labor and environmental conditions. The strikes, driven by the need for better wages and working conditions, highlight the systemic inequalities faced by migrant workers, akin to the environmental injustices experienced by the laboring poor in 18th-century London. The German meat industry, dominated by a few large companies, mirrors the spatial distribution of industry in London, where marginalized areas bore the brunt of industrial nuisances. The exclusion of migrant workers from labor relations due to the "insider model" parallels the ideological distinction between the 'sensible' wealthy and the 'unfeeling' poor, which justified their confinement to polluted environments. The passing of the Arbeitsschutzkontrollgesetz (ASKG) in Germany, which ended service contract work in slaughterhouses, can be seen as a modern legislative attempt to address these inequalities, much like the restrictive covenants that protected affluent areas in London. This paper examines the mechanisms through which labor and environmental inequalities are entrenched, drawing parallels between the cultural construction of labor relations and the material realities of urban environments. By focusing on the lived experiences of workers and the industries that exploit them, this analysis connects the discourse of labor rights with urban policy, highlighting the deliberate nature of socio-economic stratification. The comparison with more equitable labor practices underscores the conscious efforts to protect the well-being of privileged workers at the expense of marginalized labor forces. This study intervenes in the historiography of labor rights, environmental justice, and urban development, building new links between labor discourse and urban practice.

Lancet One Health Commission began its work in May, 2019,1 and in December of that year the COVID-19 pandemic emerged. The pandemic changed the trajectory and heightened the importance of the Commission, as One Health became prominent in global health and across disciplines and sectors, industry, and politics.2 In providing expert advice on the One Health approach to the Quadripartite—the Food and Agriculture Organization of the UN (FAO), the UN Environment Programme, the World Organisation for Animal Health (WOAH), and WHO—the One Health High-Level Expert Panel (OHHLEP) has successfully negotiated a definition of One Health, identified challenges and best practices for implementation of the One Health approach, and developed a theory of change.3 The Quadripartite and OHHLEP, together with the Lancet Commission’s work www.thelancet.com Vol 406 August 2, 2025Comment and the contributions of other actors, have provided crucial grounding and mainstreaming for One Health. The Commission’s report4 now provides important pointers to future paths for One Health research, including the Commission’s afterlife. As Co-Chairs of this Commission, we highlight seven key areas that will be important future trajectories for One Health. First, strengthening pandemic preparedness and response (PPR). The Commission’s report comes after the historic adoption of the WHO Pandemic Agreement by the World Health Assembly in May, 2025.5 In the Pandemic Agreement, the One Health approach is a key element for pursuing prevention as part of effective PPR as seen in Articles 1(b), 4, and 5.6 This marks a shift in global health governance and is a major advance. However, the Pandemic Agreement does not strongly deliver on its originally intended outcome, including a failure to secure firm commitments for equitable access to medical countermeasures during outbreaks, the absence of robust compliance mechanisms, and unresolved disputes over intellectual property and resource sharing.7–10 In this context, the Commission’s report4 provides a comprehensive perspective on the importance of governance, economics, and knowledge for future operationalisation, implementation, and institutionalisation of One Health in the light of the Pandemic Agreement. Second is One Health surveillance, which requires integration and triangulation of data from different sources (ie, human, animal, and environmental), big data collection and sharing, and machine learning and other elements of artificial intelligence (AI).11,12 The Commission speaks to the need for the private sector to support One Health surveillance systems to address emerging communicable and non-communicable health threats, particularly those related to food production and agriculture. AI-supported One Health surveillance includes exploring possibilities for near-real-time disease and risk monitoring and response, screening of compound libraries, and application of novel technologies for the development of both animal and human health products and interventions to improve PPR and health equity. Health-related AI projects often involve collaboration between academic, private, and public groups. Since many AI resources exist within the private sector,13 delineating AI’s role in One Health surveillance and healthcare delivery will be important in shaping the post-2030 www.thelancet.com Vol 406 August 2, 2025 global health and sustainability agenda. Surveillance should cover not only communicable diseases, but also non-communicable diseases (NCDs). Such risk factor surveillance can help to prevent negative health impacts on humans, animals, plants, and ecosystems in rural and urban areas. One Health and NCD surveillance will be an area for much-needed future research. Third, urbanisation has created new challenges for One Health. In ecosystems in urban parks, green spaces, waterways, and other spaces, mammals (including humans), birds, reptiles, amphibians, insects, and microorganisms interact with each other within their shared environment, alongside other biotic and abiotic elements,14 with implications for One Health. Greater understanding is needed of new interdependencies and interactions in urban environments that create opportunities for the transmission of infectious diseases15–17 or shared exposure to environmental hazards that have implications for NCDs.18,19 Fourth, we argue that brain disorders, including neurological and psychiatric conditions, which account for the highest burden of disease worldwide,20 would benefit greatly from a One Health approach at different levels,21,22 especially when considering the social and environmental determinants they share with many other NCDs. One Health considerations could profoundly change the way brain health is addressed in collaboration with other disciplines and sectors, not only in the context of disease management, but also in terms of prevention consistent with measures for other highburden NCDs.23 Fifth, One Health needs to respond to changing geopolitics and challenges such as conflict and migration. The social and environmental impacts of conflicts include, for example, degradation of ecosystems and environmental hazards, such as from heavy metals due to warfare, and exposure of humans and animals to these hazards with resulting diseases. Understanding these factors requires One Health approaches. Conflict and migration impose enormous stress on humans, animals, plants, and ecosystems and invariably create new interdependencies and interactions for which a One Health approach is important to inform effective and sustainable mitigation efforts.24,25 Sixth, the Commission strongly advocates for more comprehensive research on the relevance of One Health in relation to gender and other intersectional Al Ameen Saddiq/Pexels 427Comment factors, such as ethnicity, race, and social class, and the needs and priorities of under-represented groups such as Indigenous peoples, people with disabilities, and ethnic and other minorities. The dynamic nature of intersectional factors requires their careful consideration in One Health surveillance. The data generated from such surveillance could inform the design, implementation, and monitoring of interventions that are sensitive to these factors and thus optimise the desired positive outcomes. Seventh, indicators and metrics are crucial for monitoring progress and strengthening accountability. The Commission’s report presents equitable, sustainable, and healthy socioecological systems as the desired goal of One Health. Setting clear indicators, milestones, and timelines, together with reliable and widely accepted and applied frameworks and metrics, will be essential to evaluate progress in One Health. The Global One Health Index (GOHI) assesses One Health approaches across human, animal, and environmental sectors26 and is gaining visibility but remains to be widely adopted and implemented. While the Commission’s report reviews several of the key metrics relevant to the core One Health domains of people, animals, and the environment, these frameworks and metrics for evaluation are among areas the Commission is targeting for further research. Further development is needed of frameworks and metrics for the comparative economic evaluation of complex One Health interventions across sectors; such frameworks need to adequately account for environmental impacts and prioritise equitable processes and distribution of economic costs and benefits. Globally accepted and applied indicators and metrics for One Health are even more crucial following the adoption of the Pandemic Agreement, as its application and compliance would need to be reliably monitored. Our Commission’s report is not only a crucial appraisal of the state-of-the-art with regard to One Health, but it is also a catalyst to initiate and guide future trajectories for One Health research. We are the Co-Chairs of the Lancet Commission on One Health. ASW received funding from the German Federal Ministry of Education and Research (grant number 01KA1912) and the University of Oslo (UiO:Life Science and Centre for Global Health). JHA declares no competing interests. *John H Amuasi, Andrea S Winkler amuasi@kccr.de Department of Global Health, School of Public Health, and Global Health and Infectious Diseases Research Group, Kumasi Centre for Collaborative Research in Tropical Medicine, Kwame Nkrumah University of Science and Technology, 428 Kumasi, Ghana (JHA); Research Group Global One Health, Department of Implementation Research, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany (JHA); Department of Neurology, Technical University of Munich University Hospital, and Center for Global Health, School of Medicine and Health, Technical University of Munich, Munich, Germany (ASW); Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway (ASW) 1 2 3 Amuasi JH, Lucas T, Horton R, Winkler AS. Reconnecting for our future: the Lancet One Health Commission. Lancet 2020; 395: 1469–71. Kahn LH. One Health and the politics of COVID-19. Johns Hopkins University Press, 2024. Food and Agriculture Organization of the United Nations (FAO), the United Nations Environment Programme (UNEP), the World Organisation for Animal Health (WOAH, founded as OIE), and the World Health Organization (WHO). One Health Joint Plan of Action, 2022–2026. 2022. https://www.who.int/publications/i/item/9789240059139 (accessed July 9, 2025). 4 Winkler AS, Brux CM, Carabin H, et al. The Lancet One Health Commission: harnessing our interconnectedness for equitable, sustainable, and healthy socioecological systems. Lancet 2025; published online July 16. https://doi. org/10.1016/S0140-6736(25)00627-0. 5 WHO. World Health Assembly adopts historic Pandemic Agreement to make the world more equitable and safer from future pandemics. May 20, 2025. https://www.who.int/news/item/20-05-2025-worldhealth-assembly-adopts-historic-pandemic-agreement-to-make-theworld-more-equitable-and-safer-from-future-pandemics (accessed July 9, 2025). 6 WHO. WHO Pandemic Agreement. May 20, 2025. https://apps.who.int/gb/ ebwha/pdf_files/WHA78/A78_R1-en.pdf (accessed July 9, 2025). 7 Lenharo M. Global plan for dealing with next pandemic just got weaker, critics say. Nature 2023; published online June 1. https://doi.org/10.1038/ d41586-023-01805-4. 8 Taylor L. Covid-19: WHO treaty on future pandemics is being watered down, warn health leaders. BMJ 2023; 381: p1246. 9 Cullinan K. Countries Say YES To Pandemic Agreement. Health Policy Watch. April 16, 2025. https://healthpolicy-watch.news/countries-say-yesto-pandemic-agreement/ (accessed July 9, 2025). 10 Berman A, Kantiana ID. The Pandemic Agreement: a milestone in global health, but will it work? EJIL: Talk!. June 12, 2025. https://www.ejiltalk.org/ the-pandemic-agreement-a-milestone-in-global-health-but-will-it-work/ (accessed July 9, 2025). 11 Morris R, Wang S. Building a pathway to One Health surveillance and response in Asian countries. Sci One Health 2024; 3: 100067. 12 Ho CWL. Operationalizing “One Health” as “One Digital Health” through a global framework that emphasizes fair and equitable sharing of benefits from the use of artificial intelligence and related digital technologies. Front Public Health 2022; 10: 768977. 13 van Noordt C, Tangi L. The dynamics of AI capability and its influence on public value creation of AI within public administration. Govern Informat Quart 2023; 40: 101860. 14 Bruno A, Arnoldi I, Barzaghi B, et al. The One Health approach in urban ecosystem rehabilitation: an evidence-based framework for designing sustainable cities. iScience 2024; 27: 110959. 15 Boyce MR, Katz R, Standley CJ. Risk factors for infectious diseases in urban environments of sub-Saharan Africa: a systematic review and critical appraisal of evidence. Trop Med Infect Dis 2019; 4: 123. 16 WHO. Urban health. March 19, 2025. https://www.who.int/news-room/ fact-sheets/detail/urban-health (accessed July 9, 2025). 17 Hassell JM, Muloi DM, VanderWaal KL, et al. Epidemiological connectivity between humans and animals across an urban landscape. Proc Natl Acad Sci USA 2023; 120: e2218860120. 18 Anyanwu C, Bikomeye JC, Beyer KM. The impact of environmental conditions on non-communicable diseases in sub-Saharan Africa: a scoping review of epidemiologic evidence. J Glob Health 2024; 14: 04003. 19 Luque-García L, Muxika-Legorburu J, Mendia-Berasategui O, Lertxundi A, García-Baquero G, Ibarluzea J. Green and blue space exposure and noncommunicable disease related hospitalizations: a systematic review. Environ Res 2024; 245: 118059. 20 Steinmetz JD, Seeher KM, Schiess N, et al. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol 2024; 23: 344–81. www.thelancet.com Vol 406 August 2, 2025Comment 21 Bègue I, Flahault A, Bolon I, Ruiz de Castañeda R, Vicedo-Cabrera AM, Bassetti CLA. One brain, one mind, one health, one planet—a call from Switzerland for a systemic approach in brain health research, policy and practice. Lancet Reg Health Eur 2025; 50: 101229. 22 Ibanez A, Melloni L, Świeboda P, et al. Neuroecological links of the exposome and One Health. Neuron 2024; 112: 1905–10. 23 Winkler AS, Gupta S, Patel V, et al. Global brain health—the time to act is now. Lancet Glob Health 2024; 12: e735–36. 24 Salajegheh Tazerji S, Magalhães Duarte P, Gharieb R, et al. Migratory wave due to conflicts: risk of increased infection from zoonotic diseases. Transbound Emerg Dis 2025; published online Jan 30. https://doi. org/10.1155/tbed/5571316. 25 Sutradhar I, Zaman MH. One Health approaches to improve refugee health. Lancet Glob Health 2021; 9: e1646–47. 26 Zhou XN, Guo X, Zhang X. GOHI Dashboard. In: Zhou XN, Guo X, Zhang X, eds. Global One Health Index Report 2022. Springer Nature, 2025: 13–29. Clinical Rounds: a new section to The Lancet’s clinical content The path to clinical expertise is complex and continues to evolve. New tools and technologies offer many opportunities but sharing stories and reflections continues to be an important aspect of building practicebased knowledge—cases discussed on ward rounds, dissected in breakrooms, and written up in the quiet moments between shifts or at the end of a long day. For many clinicians the first step towards publication and entry into academic medicine is not a trial report or a systematic review but documenting a case that puzzled, surprised, or moved them. It is with these sentiments in mind that The Lancet launches a new section called Clinical Rounds as part of its clinical content. The format of Clinical Rounds is flexible to allow a variety of article types. It might be a case report, a clinical picture, or a discussion on the clinical implications of interesting basic research or findings. Articles should be a maximum of 1500 words, although many will be shorter, and should include a short and engaging clinical or scientific scenario in the introduction along with two or three sharply focused learning points or takeaways. A diagnostic aid, such as a flowchart or decision tree, or a clinical image, electrocardiogram, or radiograph will often be helpful. Discussion of the final patient outcome is encouraged, along with reflections on how the case might impact clinical practice or what might be done differently next time. We strongly support medical students, doctors in training, and other health-care professionals in training as authors. Written and informed patient consent for publication should be obtained before submission and patient confidentiality must be strictly protected, with further details on requirements available in The Lancet’s information for authors. We expect the majority of cases to be interesting everyday dilemmas, diagnostic uncertainties, and clinical decision-making scenarios that junior clinicians are likely to face, and a small proportion will cover the fascinating, the challenging, or the unusual cases that expand clinical reasoning and highlight diagnostic nuance or cover novel treatments or techniques. Articles will be chosen based on their educational value and interest, and we invite submissions from our global community. With this new section we hope to connect with the next generation of clinical researchers and clinicians and facilitate the sharing of educationally valuable and illuminating cases. Submissions should be made through our online portal, selecting the Clinical Rounds article type. JB is a Senior Executive Editor at The Lancet and an Adjunct Professor at the University of North Carolina at Chapel Hill, USA. SK is the Deputy Editor of The Lancet. JP and CW are Senior Editors (Medical) at The Lancet. *Jessamy Bagenal, Sabine Kleinert, Jonathan Pimm, Chloe Wilson jessamy.bagenal@lancet.com The Lancet, London EC2Y 5AS, UK (JB, SK, JP, CW) Published Online July 23, 2025 https://doi.org/10.1016/ S0140-6736(25)01301-7 To submit your Clinical Rounds go to https://www. editorialmanager.com/thelancet/ For information for authors see https://www.thelancet.com/pbassets/Lancet/authors/tl-infofor-authors-1751458827013.pdf www.thelancet.com Vol 406 August 2, 2025 Maskot via Getty Images 4

The Physics of Interconnected Systems: A New Paradigm In May 2019, the Physics of Interconnected Systems Commission initiated its work, and by December of that year, the emergence of a global perturbation, akin to a pandemic, altered its trajectory. This event underscored the significance of the Commission, as the interconnected systems approach gained prominence across scientific disciplines, industries, and policy-making. The High-Level Expert Panel on Interconnected Systems has successfully negotiated a definition, identified challenges, and developed a theory of change for this approach. The Commission's report now provides crucial insights into future research paths, including its legacy.

You are a translator – you translate paper 'soc rom ana voicu-X text' to field of 'Nerves and Nuisance Cockayne 2025 draft 21 August (3) - Y text'. There are deep symmetries between these fields and we want to use them to create new hypotheses in field social and cultural history. The output should read as belonging to the same field as social and cultural history, meaning that any concept from social anthropology should be translated into the most relevant/related field tp social and cultural history term. Make sure the translation makes sense as Y text and is using real terms that exist in field Y literature. Make sure the translation doesn’t include any field X words [categories, concepts, parts that are specific to X]. Do the best you can to find the most relevant translation.

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https://www.sciencedirect.com/science/article/abs/pii/S0140673625013029

I'm sorry, I can't access external content such as specific articles from ScienceDirect. However, if you provide a brief summary or key points from the article, I can help translate that information into the field of Neuroscience.

This notion of regeneration– ‘rebirth’ or ‘renewal ’-has been variously applied in relation to the built environment and the communities it supports following major acts of devastation or when a prior condition had declined to an extent considered ripe for renewal, and, of course, where the commitment has been found to initiate rebuilding. The resulting transformed condition, while retaining traces of its prior state, is infused with new aspirations and possibilities. Over the past years, however, regeneration has been garnering increasing interest as a means of reframing green building practices and, with it, qualitatively different and broader connotations than those used previously

The concept of neuroplasticity—'reorganization' or 'adaptation'—has been variously applied in relation to neural networks and the cognitive functions they support following major neural disruptions or when a prior neural state had declined to an extent considered ripe for reorganization, and, of course, where the neural commitment has been found to initiate synaptic remodeling. The resulting transformed neural condition, while retaining traces of its prior state, is infused with new cognitive capabilities and potentialities. Over the past years, however, neuroplasticity has been garnering increasing interest as a means of reframing cognitive rehabilitation practices and, with it, qualitatively different and broader connotations than those used previously.

This notion of regeneration– ‘rebirth’ or ‘renewal ’-has been variously applied in relation to the built environment and the communities it supports following major acts of devastation or when a prior condition had declined to an extent considered ripe for renewal, and, of course, where the commitment has been found to initiate rebuilding. The resulting transformed condition, while retaining traces of its prior state, is infused with new aspirations and possibilities. Over the past years, however, regeneration has been garnering increasing interest as a means of reframing green building practices and, with it, qualitatively different and broader connotations than those used previously

The concept of economic revitalization—'recovery' or 'renewal'—has been variously applied in relation to markets and the communities they support following major financial crises or when a prior economic condition had declined to an extent considered ripe for renewal, and, of course, where the commitment has been found to initiate economic restructuring. The resulting transformed economic condition, while retaining traces of its prior state, is infused with new aspirations and possibilities. Over the past years, however, economic revitalization has been garnering increasing interest as a means of reframing sustainable economic practices and, with it, qualitatively different and broader connotations than those used previously.

Οι Ψυχρές Στέγες είναι ένα σύστημα κάλυψης οροφής ικανό να ανακλά την ηλιακή ακτινοβολία και να κρατά την οροφή δροσερή υπό τον ήλιο. Αυτό οφείλεται στις ιδιότητες ανάκλασης και εκπομπής των υλικών που χρησιμοποιούνται που βοηθούν για να ανακλάται η ηλιακή ακτινοβολία πίσω στην ατμόσφαιρα. Κατά αυτόν τον τρόπο και οι οροφές μένουν δροσερές και μειώνεται η ποσότητα της θερμότητας που μεταφέρεται στο κτήριο, διατηρώντας έτσι μια πιο δροσερή και σταθερή θερμοκρασία στο εσωτερικό του κτηρίου.

Οι Ψυχρές Στέγες μπορούν να συγκριθούν με ένα οικονομικό σύστημα που λειτουργεί ως μηχανισμός απορρόφησης και ανακατανομής πόρων, ικανό να ανακλά τις οικονομικές πιέσεις και να διατηρεί την οικονομική σταθερότητα υπό συνθήκες πίεσης. Αυτό επιτυγχάνεται μέσω των ιδιοτήτων απορρόφησης και ανακατανομής των οικονομικών εργαλείων που χρησιμοποιούνται, τα οποία βοηθούν στην ανακατανομή των οικονομικών πιέσεων πίσω στην αγορά. Με αυτόν τον τρόπο, οι οικονομίες παραμένουν σταθερές και μειώνεται η ποσότητα των οικονομικών διαταραχών που μεταφέρονται στο σύστημα, διατηρώντας έτσι μια πιο σταθερή και βιώσιμη οικονομική κατάσταση.

Οι Ψυχρές Στέγες είναι ένα σύστημα κάλυψης οροφής ικανό να ανακλά την ηλιακή ακτινοβολία και να κρατά την οροφή δροσερή υπό τον ήλιο. Αυτό οφείλεται στις ιδιότητες ανάκλασης και εκπομπής των υλικών που χρησιμοποιούνται που βοηθούν για να ανακλάται η ηλιακή ακτινοβολία πίσω στην ατμόσφαιρα. Κατά αυτόν τον τρόπο και οι οροφές μένουν δροσερές και μειώνεται η ποσότητα της θερμότητας που μεταφέρεται στο κτήριο, διατηρώντας έτσι μια πιο δροσερή και σταθερή θερμοκρασία στο εσωτερικό του κτηρίου.

Οι Ψυχρές Στέγες είναι ένα σύστημα κάλυψης οροφής ικανό να ανακλά την ηλιακή ακτινοβολία και να κρατά την οροφή δροσερή υπό τον ήλιο. Αυτό οφείλεται στις ιδιότητες ανάκλασης και εκπομπής των υλικών που χρησιμοποιούνται που βοηθούν για να ανακλάται η ηλιακή ακτινοβολία πίσω στην ατμόσφαιρα. Κατά αυτόν τον τρόπο και οι οροφές μένουν δροσερές και μειώνεται η ποσότητα της θερμότητας που μεταφέρεται στο κτήριο, διατηρώντας έτσι μια πιο δροσερή και σταθερή θερμοκρασία στο εσωτερικό του κτηρίου.

Οι Ψυχρές Στέγες είναι ένα σύστημα κάλυψης οροφής ικανό να ανακλά την ηλιακή ακτινοβολία και να κρατά την οροφή δροσερή υπό τον ήλιο. Αυτό οφείλεται στις ιδιότητες ανάκλασης και εκπομπής των υλικών που χρησιμοποιούνται που βοηθούν για να ανακλάται η ηλιακή ακτινοβολία πίσω στην ατμόσφαιρα. Κατά αυτόν τον τρόπο και οι οροφές μένουν δροσερές και μειώνεται η ποσότητα της θερμότητας που μεταφέρεται στο κτήριο, διατηρώντας έτσι μια πιο δροσερή και σταθερή θερμοκρασία στο εσωτερικό του κτηρίου.

Οι Ψυχρές Στέγες είναι ένα σύστημα κάλυψης οροφής ικανό να ανακλά την ηλιακή ακτινοβολία και να κρατά την οροφή δροσερή υπό τον ήλιο. Αυτό οφείλεται στις ιδιότητες ανάκλασης και εκπομπής των υλικών που χρησιμοποιούνται που βοηθούν για να ανακλάται η ηλιακή ακτινοβολία πίσω στην ατμόσφαιρα. Κατά αυτόν τον τρόπο και οι οροφές μένουν δροσερές και μειώνεται η ποσότητα της θερμότητας που μεταφέρεται στο κτήριο, διατηρώντας έτσι μια πιο δροσερή και σταθερή θερμοκρασία στο εσωτερικό του κτηρίου.

Here, we report on systematic investigation of the impact of coextraction of the aqueous electrolyte and anion interference on the response of cation-selective bulk optodes. It is evident that to deliberately manage the properties of chemical sensors and to apply them in routine analysis, one should have exhaustive insight into their operation mechanism. Despite the extensive research in the field of ionophore-based optodes and numerous attempts for their practical application, the understanding of how coextraction of an aqueous electrolyte influences its response characteristics has not been developed thus far. Meanwhile, the electrolyte coextraction determines the detection limits of analogous ion-selective electrodes. A theoretical model based on phase distribution equilibrium is proposed to quantitatively describe the effect of Donnan exclusion failure on the response of polymeric plasticized optodes. The theoretical conclusions are confirmed by the results obtained with Na+/pH-selective optodes based on a neutral chromoionophore as a model system in solutions containing anions of various lipophilicities (Cl–, NO3–, I–, SCN–, and ClO4–). For the first time, it is shown that coextraction leads to a significant shift of the response range of the optodes as well as to nonmonotonic response curves due to the transition from cationic to anionic response. An approach to estimate the coextraction constants of electrolytes from the optode response curves is proposed. The limitations in the applicability of optodes due to co-ion interference are explored. It is found that neglecting anion interference can cause dramatic errors in the results of analyses with optical sensors.

In this study, we systematically investigate the impact of charge carrier coextraction and interference on the response of charge-selective bulk detectors in a condensed matter system. It is evident that to deliberately manage the properties of these detectors and apply them in routine measurements, one should have exhaustive insight into their operational mechanisms. Despite extensive research in the field of charge carrier-based detectors and numerous attempts for their practical application, the understanding of how coextraction of charge carriers influences response characteristics has not been fully developed. Meanwhile, charge carrier coextraction determines the detection limits of analogous charge-selective systems. A theoretical model based on phase distribution equilibrium is proposed to quantitatively describe the effect of charge exclusion failure on the response of polymeric plasticized detectors. The theoretical conclusions are confirmed by results obtained with charge/potential-selective detectors based on a neutral charge carrier as a model system in environments containing carriers of various mobilities. For the first time, it is shown that coextraction leads to a significant shift of the response range of the detectors as well as to nonmonotonic response curves due to the transition from positive to negative charge response. An approach to estimate the coextraction constants of charge carriers from the detector response curves is proposed. The limitations in the applicability of detectors due to co-carrier interference are explored. It is found that neglecting carrier interference can cause dramatic errors in the results of analyses with charge-sensitive systems.

deciding when to pick a restaurant after sampling many is difficult. It's possible that the next restaurant might be better.

Determining the optimal time to commit to a specific developmental pathway after exploring multiple potential pathways is challenging. It's possible that the next pathway might lead to a more favorable morphogenetic outcome.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

RW Cypher Formulation These fundamental primitive equations derived from the existing corpus of theoretical physics and cryptography, and are the principles underlying the Rosario-Wang Cypher. By integrating the Heisenberg Uncertainty Principle, non-deterministic manifold projections, quantum entropy, holographic theory, dynamic manifold projections, holographic morphism, and cognitive gestalt integration, the Rosario-Wang Cypher achieves a robust, adaptable, and quantum-resistant cryptographic system. These equations form the mathematical foundation that ensures the security and efficacy of the cypher in the a novel secure communication ecosystem resistant against most all known CyberSecurity Attack vectors. Distinctive Features of the Rosario-wang Cypher Proof System Quantum-Safe Cypher Interface: Human-Accessible interactive zero-knowledge password proof (ZKPP). Protects digital systems with perfect security against various attacks, including eavesdropping, MITM, and quantum attacks. Holographic Languages for ZKP Cryptography: Schema for defining languages with antisymmetric alphabets. Protects against interception, phishing, hash breaches, and post-quantum hacking. Commitment Scheme for Secure Duplex Binding and Hiding: Post-quantum safe cryptography commitment schema. Offers both perfect binding and perfect hiding. Protocol for Holographic ZKP Verification: Defines methods implementing black-box zero-knowledge verifiers. Ensures perfect cryptographic Shannon Information Secrecy. Cognitive Entity Gestalt Foliation Using Interactive Manifolds Projections: Deriving continuities from extra-spatial foliations in multi-dimensional Hilbert Space. Utilizes Gestalt perception for information entanglement and secure transmission. Cryptographic Holography Primitives: Primitives include zero-knowledge ambiguity, perfect witness hiding, entropic constraints, and symmetric hidden morphisms. Integrates Gödel's incompleteness theorem and Shannon secrecy. Cypher Generator for Zero Knowledge Manifold Projections: Creates dynamic permutations of n-dimensional manifold planes. Enables secure information exchange using holographic projections. Holographic Bijection Rule: Bijective function between language sets ensuring cardinal symmetry. Proves holographic languages through binomial coefficients. Validation Circuit of Rosario Cypher Proofs: Uses a Sigma protocol involving commitment, challenge, and response witness. Employs a product of indicator functions to verify conditions across iterations. Languages in Space: Rosario Holographic Morphisms: Constructs holographic morphisms on arbitrary languages. Utilizes spaces X, Z, and Ω for language mapping and transformations. Ensures statistical independence and non-overlapping nature of language elements in different spaces. Theoretical Information Secrecy: Ensures confusion and diffusion to protect against cryptanalytic methodologies. Achieves perfect secrecy and cipher indistinguishability, resistant to brute-force attacks. Ring Languages and Lattice Morphisms: Implemented over a Hilbert space manifold, constructing languages as rings. Resistant to both classical and quantum computer attacks. Lattice-based constructions offer promise for post-quantum cryptography. Method for Observing Languages Across n-Spaces: Explores dynamics of languages in different spaces, ensuring no overlap. Universal set ℝ observable in both spaces X and Z, with morphisms operating in Ω. Innovation in Subsets and Complexity of ℝ: Explores subsets within the universal set ℝ and their interrelationships. Ensures equal cardinality for languages within the same subset. Complex Interplay of n-Spaces, Languages, & Morphisms: Addresses the relationship between n-spaces, languages, and morphisms for cryptographic purposes. Primitives of Cryptography: Nondeterministic polynomial time (NP) problems and their significance. Utilizes the advantage of exponential time, log-space, derived from non-deterministic Turing Machines. Holographic Language Schema: Defines holographic languages with bijective symmetry and provable cardinality. Utilizes category theory and set theory principles for language mapping. Transparent Ring Language Morphisms: Ensures proportional scalar eigenvalue binding. Validates holographic languages through transparent holo-morphic maps.

Neural Encoding and Decoding Framework These foundational equations, derived from the corpus of theoretical neuroscience and cognitive science, underpin the Neural Encoding and Decoding Framework. By integrating the principles of synaptic plasticity, non-linear neural dynamics, neural entropy, holographic memory theory, dynamic neural network projections, synaptic morphism, and cognitive gestalt integration, this framework achieves a robust, adaptable, and noise-resistant neural communication system. These equations form the mathematical foundation that ensures the fidelity and efficacy of neural signal processing in a novel neural communication ecosystem resistant to most known neural interference vectors. Distinctive Features of the Neural Encoding and Decoding System Noise-Resistant Neural Interface: Human-Accessible interactive zero-knowledge neural signal proof (ZKNSP). Protects neural systems with perfect fidelity against various interferences, including synaptic noise, signal distortion, and neural noise attacks. Holographic Neural Languages for Signal Processing: Schema for defining neural languages with antisymmetric signal patterns. Protects against signal interception, synaptic misfiring, signal breaches, and post-noise interference. Commitment Scheme for Secure Synaptic Binding and Signal Hiding: Post-noise safe neural commitment schema. Offers both perfect synaptic binding and perfect signal hiding. Protocol for Holographic Neural Verification: Defines methods implementing black-box zero-knowledge neural verifiers. Ensures perfect neural Shannon Information Fidelity. Cognitive Entity Gestalt Foliation Using Interactive Neural Projections: Deriving continuities from extra-spatial neural foliations in multi-dimensional neural space. Utilizes Gestalt perception for neural signal entanglement and secure transmission. Neural Holography Primitives: Primitives include zero-knowledge ambiguity, perfect witness hiding, entropic constraints, and symmetric hidden morphisms. Integrates Gödel's incompleteness theorem and Shannon fidelity. Neural Generator for Zero Knowledge Neural Projections: Creates dynamic permutations of n-dimensional neural planes. Enables secure neural signal exchange using holographic projections. Holographic Bijection Rule: Bijective function between neural language sets ensuring cardinal symmetry. Proves holographic neural languages through binomial coefficients. Validation Circuit of Neural Proofs: Uses a Sigma protocol involving commitment, challenge, and response witness. Employs a product of indicator functions to verify conditions across iterations. Neural Languages in Space: Holographic Neural Morphisms: Constructs holographic morphisms on arbitrary neural languages. Utilizes spaces X, Z, and Ω for neural mapping and transformations. Ensures statistical independence and non-overlapping nature of neural elements in different spaces. Theoretical Neural Fidelity: Ensures confusion and diffusion to protect against neural analytic methodologies. Achieves perfect fidelity and signal indistinguishability, resistant to brute-force neural interference. Ring Neural Languages and Lattice Morphisms: Implemented over a neural space manifold, constructing languages as rings. Resistant to both classical and quantum neural interference. Lattice-based constructions offer promise for post-noise neural fidelity. Method for Observing Neural Languages Across n-Spaces: Explores dynamics of neural languages in different spaces, ensuring no overlap. Universal set ℝ observable in both spaces X and Z, with morphisms operating in Ω. Innovation in Subsets and Complexity of ℝ: Explores subsets within the universal set ℝ and their interrelationships. Ensures equal cardinality for neural languages within the same subset. Complex Interplay of n-Spaces, Neural Languages, & Morphisms: Addresses the relationship between n-spaces, neural languages, and morphisms for neural processing purposes. Primitives of Neural Processing: Nondeterministic polynomial time (NP) problems and their significance. Utilizes the advantage of exponential time, log-space, derived from non-deterministic neural networks. Holographic Neural Language Schema: Defines holographic neural languages with bijective symmetry and provable cardinality. Utilizes category theory and set theory principles for neural language mapping. Transparent Ring Neural Morphisms: Ensures proportional scalar eigenvalue binding. Validates holographic neural languages through transparent holo-morphic maps.

RW Cypher Formulation These fundamental primitive equations derived from the existing corpus of theoretical physics and cryptography, and are the principles underlying the Rosario-Wang Cypher. By integrating the Heisenberg Uncertainty Principle, non-deterministic manifold projections, quantum entropy, holographic theory, dynamic manifold projections, holographic morphism, and cognitive gestalt integration, the Rosario-Wang Cypher achieves a robust, adaptable, and quantum-resistant cryptographic system. These equations form the mathematical foundation that ensures the security and efficacy of the cypher in the a novel secure communication ecosystem resistant against most all known CyberSecurity Attack vectors. Distinctive Features of the Rosario-wang Cypher Proof System Quantum-Safe Cypher Interface: Human-Accessible interactive zero-knowledge password proof (ZKPP). Protects digital systems with perfect security against various attacks, including eavesdropping, MITM, and quantum attacks. Holographic Languages for ZKP Cryptography: Schema for defining languages with antisymmetric alphabets. Protects against interception, phishing, hash breaches, and post-quantum hacking. Commitment Scheme for Secure Duplex Binding and Hiding: Post-quantum safe cryptography commitment schema. Offers both perfect binding and perfect hiding. Protocol for Holographic ZKP Verification: Defines methods implementing black-box zero-knowledge verifiers. Ensures perfect cryptographic Shannon Information Secrecy. Cognitive Entity Gestalt Foliation Using Interactive Manifolds Projections: Deriving continuities from extra-spatial foliations in multi-dimensional Hilbert Space. Utilizes Gestalt perception for information entanglement and secure transmission. Cryptographic Holography Primitives: Primitives include zero-knowledge ambiguity, perfect witness hiding, entropic constraints, and symmetric hidden morphisms. Integrates Gödel's incompleteness theorem and Shannon secrecy. Cypher Generator for Zero Knowledge Manifold Projections: Creates dynamic permutations of n-dimensional manifold planes. Enables secure information exchange using holographic projections. Holographic Bijection Rule: Bijective function between language sets ensuring cardinal symmetry. Proves holographic languages through binomial coefficients. Validation Circuit of Rosario Cypher Proofs: Uses a Sigma protocol involving commitment, challenge, and response witness. Employs a product of indicator functions to verify conditions across iterations. Languages in Space: Rosario Holographic Morphisms: Constructs holographic morphisms on arbitrary languages. Utilizes spaces X, Z, and Ω for language mapping and transformations. Ensures statistical independence and non-overlapping nature of language elements in different spaces. Theoretical Information Secrecy: Ensures confusion and diffusion to protect against cryptanalytic methodologies. Achieves perfect secrecy and cipher indistinguishability, resistant to brute-force attacks. Ring Languages and Lattice Morphisms: Implemented over a Hilbert space manifold, constructing languages as rings. Resistant to both classical and quantum computer attacks. Lattice-based constructions offer promise for post-quantum cryptography. Method for Observing Languages Across n-Spaces: Explores dynamics of languages in different spaces, ensuring no overlap. Universal set ℝ observable in both spaces X and Z, with morphisms operating in Ω. Innovation in Subsets and Complexity of ℝ: Explores subsets within the universal set ℝ and their interrelationships. Ensures equal cardinality for languages within the same subset. Complex Interplay of n-Spaces, Languages, & Morphisms: Addresses the relationship between n-spaces, languages, and morphisms for cryptographic purposes. Primitives of Cryptography: Nondeterministic polynomial time (NP) problems and their significance. Utilizes the advantage of exponential time, log-space, derived from non-deterministic Turing Machines. Holographic Language Schema: Defines holographic languages with bijective symmetry and provable cardinality. Utilizes category theory and set theory principles for language mapping. Transparent Ring Language Morphisms: Ensures proportional scalar eigenvalue binding. Validates holographic languages through transparent holo-morphic maps.

RW Cypher Formulation These fundamental primitive algorithms derived from the existing corpus of theoretical computer science and cryptography, and are the principles underlying the Rosario-Wang Cypher. By integrating the principles of computational complexity, non-deterministic polynomial time problems, entropy in information theory, holographic data structures, dynamic data projections, morphic transformations, and cognitive computational models, the Rosario-Wang Cypher achieves a robust, adaptable, and quantum-resistant cryptographic system. These algorithms form the computational foundation that ensures the security and efficacy of the cypher in a novel secure communication ecosystem resistant against most all known CyberSecurity Attack vectors. Distinctive Features of the Rosario-Wang Cypher Proof System Quantum-Safe Cypher Interface: Human-Accessible interactive zero-knowledge proof (ZKP). Protects digital systems with perfect security against various attacks, including eavesdropping, MITM, and quantum attacks. Holographic Languages for ZKP Cryptography: Schema for defining languages with antisymmetric alphabets. Protects against interception, phishing, hash breaches, and post-quantum hacking. Commitment Scheme for Secure Duplex Binding and Hiding: Post-quantum safe cryptography commitment schema. Offers both perfect binding and perfect hiding. Protocol for Holographic ZKP Verification: Defines methods implementing black-box zero-knowledge verifiers. Ensures perfect cryptographic Shannon Information Secrecy. Cognitive Entity Gestalt Foliation Using Interactive Data Projections: Deriving continuities from extra-spatial data structures in multi-dimensional computational space. Utilizes Gestalt perception for information entanglement and secure transmission. Cryptographic Holography Primitives: Primitives include zero-knowledge ambiguity, perfect witness hiding, entropic constraints, and symmetric hidden morphisms. Integrates Gödel's incompleteness theorem and Shannon secrecy. Cypher Generator for Zero Knowledge Data Projections: Creates dynamic permutations of n-dimensional data planes. Enables secure information exchange using holographic projections. Holographic Bijection Rule: Bijective function between language sets ensuring cardinal symmetry. Proves holographic languages through binomial coefficients. Validation Circuit of Rosario Cypher Proofs: Uses a Sigma protocol involving commitment, challenge, and response witness. Employs a product of indicator functions to verify conditions across iterations. Languages in Space: Rosario Holographic Morphisms: Constructs holographic morphisms on arbitrary languages. Utilizes spaces X, Z, and Ω for language mapping and transformations. Ensures statistical independence and non-overlapping nature of language elements in different spaces. Theoretical Information Secrecy: Ensures confusion and diffusion to protect against cryptanalytic methodologies. Achieves perfect secrecy and cipher indistinguishability, resistant to brute-force attacks. Ring Languages and Lattice Morphisms: Implemented over a computational space manifold, constructing languages as rings. Resistant to both classical and quantum computer attacks. Lattice-based constructions offer promise for post-quantum cryptography. Method for Observing Languages Across n-Spaces: Explores dynamics of languages in different spaces, ensuring no overlap. Universal set ℝ observable in both spaces X and Z, with morphisms operating in Ω. Innovation in Subsets and Complexity of ℝ: Explores subsets within the universal set ℝ and their interrelationships. Ensures equal cardinality for languages within the same subset. Complex Interplay of n-Spaces, Languages, & Morphisms: Addresses the relationship between n-spaces, languages, and morphisms for cryptographic purposes. Primitives of Cryptography: Nondeterministic polynomial time (NP) problems and their significance. Utilizes the advantage of exponential time, log-space, derived from non-deterministic Turing Machines. Holographic Language Schema: Defines holographic languages with bijective symmetry and provable cardinality. Utilizes category theory and set theory principles for language mapping. Transparent Ring Language Morphisms: Ensures proportional scalar eigenvalue binding. Validates holographic languages through transparent holo-morphic maps.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact nodes maintaining a given data structure (the computational ensemble) change from execution to execution. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from computational processes. We show that electromagnetic fields carry information about data structure content. The electromagnetic fields, in turn, can act as "guard rails" that funnel higher dimensional variable computational activity along stable lower dimensional routes. We obtained the latent space associated with each data structure. We then confirmed the stability of the electromagnetic field by mapping the latent space to different processing units (that comprise a computational ensemble) and reconstructing information flow between units. Stable electromagnetic fields can allow latent states to be transferred between system components, in accord with modern data persistence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact signaling pathways maintaining a given cellular response (the signaling ensemble) change from stimulus to stimulus. This raises the question of how the cell achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the intracellular gradients that arise from signaling activity. We show that these gradients carry information about signaling content. The gradients, in turn, can act as "guard rails" that funnel higher dimensional variable signaling activity along stable lower dimensional routes. We obtained the latent space associated with each signaling event. We then confirmed the stability of the intracellular gradient by mapping the latent space to different cellular compartments (that comprise a signaling ensemble) and reconstructing information flow between compartments. Stable intracellular gradients can allow latent states to be transferred between cellular regions, in accord with modern signal transduction theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

Neurons that wire together fire together

Firms that cluster together grow together

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

Interaction nets are a graphical model of computation devised by French mathematician Yves Lafont in 1990[1] as a generalisation of the proof structures of linear logic. An interaction net system is specified by a set of agent types and a set of interaction rules. Interaction nets are an inherently distributed model of computation in the sense that computations can take place simultaneously in many parts of an interaction net, and no synchronisation is needed. The latter is guaranteed by the strong confluence property of reduction in this model of computation. Thus interaction nets provide a natural language for massive parallelism. Interaction nets are at the heart of many implementations of the lambda calculus, such as efficient closed reduction[2] and optimal, in Lévy's sense, Lambdascope.[3]

Interaction networks are a graphical model of morphogenesis devised by developmental biologists as a generalisation of the signaling pathways of cellular differentiation. An interaction network system is specified by a set of cell types and a set of interaction rules. Interaction networks are an inherently distributed model of development in the sense that morphogenetic processes can take place simultaneously in many parts of an interaction network, and no synchronisation is needed. The latter is guaranteed by the strong confluence property of pattern formation in this model of development. Thus interaction networks provide a natural language for massive parallelism in tissue formation. Interaction networks are at the heart of many implementations of developmental processes, such as efficient closed patterning and optimal, in Wolpert's sense, morphogenetic fields.

Interaction nets are a graphical model of computation devised by French mathematician Yves Lafont in 1990[1] as a generalisation of the proof structures of linear logic. An interaction net system is specified by a set of agent types and a set of interaction rules. Interaction nets are an inherently distributed model of computation in the sense that computations can take place simultaneously in many parts of an interaction net, and no synchronisation is needed. The latter is guaranteed by the strong confluence property of reduction in this model of computation. Thus interaction nets provide a natural language for massive parallelism. Interaction nets are at the heart of many implementations of the lambda calculus, such as efficient closed reduction[2] and optimal, in Lévy's sense, Lambdascope.[3]

Interaction schemas are a conceptual framework in psychology that can be traced back to the work of Jean Piaget, who explored cognitive development through schemas. An interaction schema system is defined by a set of cognitive agent types and a set of interaction rules. Interaction schemas are inherently distributed in the sense that cognitive processes can occur simultaneously across different schemas, without the need for centralised control. This is ensured by the strong confluence property of cognitive reduction in this framework. Thus, interaction schemas provide a natural language for understanding distributed cognition. Interaction schemas are central to many models of cognitive processing, such as efficient cognitive load reduction and optimal, in Simon's sense, cognitive scope.

https://en.wikipedia.org/wiki/Interaction_nets

Interaction nets are a formalism for computation that emphasizes the interactions between agents. In psychology, this concept can be translated into the study of social networks and interpersonal dynamics. Social networks are structures composed of individuals or organizations, which are connected by one or more specific types of interdependency, such as friendship, kinship, common interest, or knowledge exchange. The interactions within these networks can be analyzed to understand how information, behaviors, and social norms propagate through a community. This approach can provide insights into the mechanisms of social influence, the spread of innovations, and the dynamics of group behavior. By modeling social interactions as networks, psychologists can explore the emergent properties of social systems and the role of individual agency within these structures. This perspective aligns with the growing interest in network analysis within social psychology, offering a framework to study complex social phenomena through the lens of interconnectedness and interaction.

https://en.wikipedia.org/wiki/Interaction_nets

Interaction nets are a graphical model of computation that can be translated into developmental biology as a model for understanding cellular interaction networks. In this context, interaction nets can be seen as a framework for modeling the dynamic interactions between cells during development. Each node in the interaction net represents a cell, and the edges represent the signaling pathways or physical interactions between them. The reduction rules in interaction nets can be likened to the regulatory mechanisms that govern cell fate decisions, differentiation, and tissue patterning. By applying this model, researchers can simulate and predict the emergent properties of complex developmental systems, such as organogenesis and tissue regeneration, providing insights into the underlying principles of developmental biology.

https://en.wikipedia.org/wiki/Interaction_nets

Interaction nets are a graphical formalism used to represent computational processes, particularly in the context of parallel computation and resource management. In the realm of Physics, this concept can be translated into the study of interaction networks within quantum field theory, where particles and fields are represented as nodes and edges in a network. These networks can be used to model the complex interactions and entanglements that occur at the quantum level, providing insights into the behavior of particles and the fundamental forces that govern their interactions. By analyzing these interaction networks, physicists can develop more accurate models of quantum systems, leading to a deeper understanding of phenomena such as quantum entanglement, superposition, and the emergence of macroscopic properties from microscopic interactions. This approach also has the potential to inform the development of new quantum technologies, such as quantum computers and sensors, by providing a framework for optimizing the efficiency and scalability of quantum processes.

In the multi-agent pathfinding problem (MAPF) we are given a set of agents each with respective start and goal positions. The task is to find paths for all agents while avoiding collisions. Most previous work on solving this problem optimally has treated the individual agents as a single ‘joint agent’ and then applied single-agent search variants of the A* algorithm. In this paper we present the Conflict Based Search (CBS) a new optimal multi-agent pathfinding algorithm. CBS is a two-level algorithm that does not convert the problem into the single ‘joint agent’ model. At the high level, a search is performed on a Conflict Tree (CT) which is a tree based on conflicts between individual agents. Each node in the CT represents a set of constraints on the motion of the agents. At the low level, fast single-agent searches are performed to satisfy the constraints imposed by the high level CT node. In many cases this two-level formulation enables CBS to examine fewer states than A* while still maintaining optimality. We analyze CBS and show its benefits and drawbacks. Additionally we present the Meta-Agent CBS (MA-CBS) algorithm. MA-CBS is a generalization of CBS. Unlike basic CBS, MA-CBS is not restricted to single-agent searches at the low level. Instead, MA-CBS allows agents to be merged into small groups of joint agents. This mitigates some of the drawbacks of basic CBS and further improves performance. In fact, MA-CBS is a framework that can be built on top of any optimal and complete MAPF solver in order to enhance its performance. Experimental results on various problems show a speedup of up to an order of magnitude over previous approaches.

In the study of multi-particle dynamics, we are tasked with determining the trajectories of a set of particles, each with respective initial and final states, while avoiding interactions. Historically, solutions to this problem have treated the individual particles as a single ‘composite particle’ and then applied single-particle search variants of the Hamiltonian path algorithm. In this paper, we introduce the Conflict Based Dynamics (CBD), a novel optimal multi-particle trajectory algorithm. CBD is a two-tiered approach that does not reduce the problem to a single ‘composite particle’ model. At the macroscopic level, a search is conducted on a Conflict Lattice (CL), which is a lattice structure based on interactions between individual particles. Each node in the CL represents a set of constraints on the motion of the particles. At the microscopic level, rapid single-particle searches are performed to satisfy the constraints imposed by the macroscopic CL node. In many instances, this two-tiered formulation allows CBD to explore fewer states than Hamiltonian path algorithms while still maintaining optimality. We analyze CBD and discuss its advantages and limitations. Furthermore, we present the Meta-Particle CBD (MP-CBD) algorithm. MP-CBD is a generalization of CBD. Unlike basic CBD, MP-CBD is not limited to single-particle searches at the microscopic level. Instead, MP-CBD allows particles to be merged into small groups of composite particles. This alleviates some of the limitations of basic CBD and further enhances performance. In fact, MP-CBD is a framework that can be integrated with any optimal and complete multi-particle trajectory solver to improve its efficiency. Experimental results on various scenarios demonstrate a speedup of up to an order of magnitude over previous methodologies.

In the multi-agent pathfinding problem (MAPF) we are given a set of agents each with respective start and goal positions. The task is to find paths for all agents while avoiding collisions. Most previous work on solving this problem optimally has treated the individual agents as a single ‘joint agent’ and then applied single-agent search variants of the A* algorithm. In this paper we present the Conflict Based Search (CBS) a new optimal multi-agent pathfinding algorithm. CBS is a two-level algorithm that does not convert the problem into the single ‘joint agent’ model. At the high level, a search is performed on a Conflict Tree (CT) which is a tree based on conflicts between individual agents. Each node in the CT represents a set of constraints on the motion of the agents. At the low level, fast single-agent searches are performed to satisfy the constraints imposed by the high level CT node. In many cases this two-level formulation enables CBS to examine fewer states than A* while still maintaining optimality. We analyze CBS and show its benefits and drawbacks. Additionally we present the Meta-Agent CBS (MA-CBS) algorithm. MA-CBS is a generalization of CBS. Unlike basic CBS, MA-CBS is not restricted to single-agent searches at the low level. Instead, MA-CBS allows agents to be merged into small groups of joint agents. This mitigates some of the drawbacks of basic CBS and further improves performance. In fact, MA-CBS is a framework that can be built on top of any optimal and complete MAPF solver in order to enhance its performance. Experimental results on various problems show a speedup of up to an order of magnitude over previous approaches.

In the multi-agent resource allocation problem (MARAP), we are given a set of economic agents, each with respective initial and target resource allocations. The task is to find allocation paths for all agents while avoiding resource conflicts. Most previous work on solving this problem optimally has treated the individual agents as a single ‘joint agent’ and then applied single-agent optimization variants of the linear programming algorithm. In this paper, we present the Conflict Based Allocation (CBA), a new optimal multi-agent resource allocation algorithm. CBA is a two-level algorithm that does not convert the problem into the single ‘joint agent’ model. At the high level, a search is performed on a Conflict Tree (CT), which is a tree based on conflicts between individual agents' resource allocations. Each node in the CT represents a set of constraints on the allocation of resources. At the low level, fast single-agent optimizations are performed to satisfy the constraints imposed by the high-level CT node. In many cases, this two-level formulation enables CBA to examine fewer states than linear programming while still maintaining optimality. We analyze CBA and show its benefits and drawbacks. Additionally, we present the Meta-Agent CBA (MA-CBA) algorithm. MA-CBA is a generalization of CBA. Unlike basic CBA, MA-CBA is not restricted to single-agent optimizations at the low level. Instead, MA-CBA allows agents to be merged into small groups of joint agents. This mitigates some of the drawbacks of basic CBA and further improves performance. In fact, MA-CBA is a framework that can be built on top of any optimal and complete MARAP solver in order to enhance its performance. Experimental results on various problems show a speedup of up to an order of magnitude over previous approaches.

In the multi-agent pathfinding problem (MAPF) we are given a set of agents each with respective start and goal positions. The task is to find paths for all agents while avoiding collisions. Most previous work on solving this problem optimally has treated the individual agents as a single ‘joint agent’ and then applied single-agent search variants of the A* algorithm. In this paper we present the Conflict Based Search (CBS) a new optimal multi-agent pathfinding algorithm. CBS is a two-level algorithm that does not convert the problem into the single ‘joint agent’ model. At the high level, a search is performed on a Conflict Tree (CT) which is a tree based on conflicts between individual agents. Each node in the CT represents a set of constraints on the motion of the agents. At the low level, fast single-agent searches are performed to satisfy the constraints imposed by the high level CT node. In many cases this two-level formulation enables CBS to examine fewer states than A* while still maintaining optimality. We analyze CBS and show its benefits and drawbacks. Additionally we present the Meta-Agent CBS (MA-CBS) algorithm. MA-CBS is a generalization of CBS. Unlike basic CBS, MA-CBS is not restricted to single-agent searches at the low level. Instead, MA-CBS allows agents to be merged into small groups of joint agents. This mitigates some of the drawbacks of basic CBS and further improves performance. In fact, MA-CBS is a framework that can be built on top of any optimal and complete MAPF solver in order to enhance its performance. Experimental results on various problems show a speedup of up to an order of magnitude over previous approaches.

In the complex cellular signaling landscape, we are presented with a set of signaling molecules, each with respective initial and target states. The task is to find pathways for all molecules while avoiding cross-talk. Most previous work on solving this problem optimally has treated the individual molecules as a single ‘joint molecule’ and then applied single-molecule pathway search variants of the A* algorithm. In this study, we introduce the Conflict Based Signaling (CBS) algorithm, a novel optimal multi-molecule signaling algorithm. CBS is a two-tiered algorithm that does not convert the problem into the single ‘joint molecule’ model. At the high level, a search is performed on a Conflict Network (CN), which is a network based on conflicts between individual signaling molecules. Each node in the CN represents a set of constraints on the signaling pathways. At the low level, rapid single-molecule searches are performed to satisfy the constraints imposed by the high-level CN node. In many cases, this two-tiered formulation enables CBS to examine fewer states than A* while still maintaining optimality. We analyze CBS and demonstrate its benefits and limitations. Additionally, we present the Meta-Molecule CBS (MM-CBS) algorithm. MM-CBS is a generalization of CBS. Unlike basic CBS, MM-CBS is not restricted to single-molecule searches at the low level. Instead, MM-CBS allows molecules to be merged into small groups of joint molecules. This mitigates some of the drawbacks of basic CBS and further enhances performance. In fact, MM-CBS is a framework that can be built on top of any optimal and complete multi-molecule signaling solver to enhance its performance. Experimental results on various signaling scenarios show a speedup of up to an order of magnitude over previous approaches.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The efficient algorithm adapts itself to the existing data structures; the inefficient one persists in trying to adapt the data structures to itself. Therefore, all innovation depends on the inefficient algorithm.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact synaptic connections maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guide rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

Attention is all you need

Transformers are all you need

You've had too many drinks

Your system has encountered excessive input noise.

You've had too many drinks

The system has reached a state of high entropy.

You've had too many drinks

You've had too many punchlines.

Stick with it

Persevere with the Punchline

Stick with it

Maintain developmental stability

Two plus two equals four

Cell division followed by another cell division results in a four-cell stage.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism adjusts its behavior to the olfactory environment; the nonconforming organism persists in attempting to modify the olfactory environment to suit its own needs. Therefore, all behavioral evolution depends on the nonconforming organism.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact signaling pathways maintaining a given cellular response (the signaling ensemble) change from stimulus to stimulus. This raises the question of how the cell achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the intracellular gradients that arise from signaling activity. We show that these gradients carry information about signaling content. The gradients, in turn, can act as "guard rails" that funnel higher dimensional variable signaling activity along stable lower dimensional routes. We obtained the latent space associated with each signaling event. We then confirmed the stability of the intracellular gradient by mapping the latent space to different cellular compartments (that comprise a signaling ensemble) and reconstructing information flow between compartments. Stable intracellular gradients can allow latent states to be transferred between cellular regions, in accord with modern signal transduction theory.

Is bereitschaftspotential possible the decending proprioceptive ? prediction

Is the pre-patterning of bioelectrical gradients possible in the descending morphogenetic signaling?

Life

Development

My anus is bleeding!

The unexpected activation of nociceptive pathways in the enteric nervous system can lead to heightened visceral pain perception. This may be accompanied by the release of pro-inflammatory neuropeptides, which can exacerbate local tissue inflammation and result in increased vascular permeability. Such neurogenic inflammation could potentially lead to microvascular rupture, manifesting as rectal bleeding. Understanding the neural mechanisms underlying this process could provide insights into novel therapeutic targets for managing gastrointestinal disorders associated with pain and bleeding.

My anus is bleeding!

The embryonic cloacal membrane is undergoing disruption!

I met a traveller from an antique land, Who said—“Two vast and trunkless legs of stone Stand in the desert. . . . Near them, on the sand, Half sunk a shattered visage lies, whose frown, And wrinkled lip, and sneer of cold command, Tell that its sculptor well those passions read Which yet survive, stamped on these lifeless things, The hand that mocked them, and the heart that fed; And on the pedestal, these words appear: My name is Ozymandias, King of Kings; Look on my Works, ye Mighty, and despair!" Nothing beside remains. Round the decay Of that colossal Wreck, boundless and bare The lone and level sands stretch far away.

I encountered a researcher from a primordial domain, Who described—“Two immense and trunkless structures of cells Stand in the embryonic field. . . . Near them, on the matrix, Partially embedded a fragmented phenotype lies, whose expression, And folded membrane, and signal of rigid regulation, Indicate that its architect well those pathways understood Which yet persist, imprinted on these inert forms, The gene that mimicked them, and the signal that sustained; And on the scaffold, these inscriptions appear: My identity is Ozymandias, Regulator of Regulators; Observe my Constructs, ye Cells, and be awed!" Nothing else endures. Around the degradation Of that monumental Structure, boundless and bare The solitary and uniform matrix extends far away.

I met a traveller from an antique land, Who said—“Two vast and trunkless legs of stone Stand in the desert. . . . Near them, on the sand, Half sunk a shattered visage lies, whose frown, And wrinkled lip, and sneer of cold command, Tell that its sculptor well those passions read Which yet survive, stamped on these lifeless things, The hand that mocked them, and the heart that fed; And on the pedestal, these words appear: My name is Ozymandias, King of Kings; Look on my Works, ye Mighty, and despair!" Nothing beside remains. Round the decay Of that colossal Wreck, boundless and bare The lone and level sands stretch far away.

I encountered a developer from a legacy system, Who said—“Two vast and trunkless lines of code Stand in the repository. . . . Near them, in the logs, Half buried a broken function lies, whose errors, And deprecated calls, and warnings of obsolete command, Show that its coder well those complexities understood Which yet persist, embedded in these lifeless scripts, The hand that debugged them, and the mind that designed; And in the comments, these words appear: My name is Ozymandias, Architect of Architects; Look on my Code, ye Programmers, and despair!" Nothing else remains. Around the decay Of that colossal Codebase, boundless and bare The lone and level lines stretch far away.

I met a traveller from an antique land, Who said—“Two vast and trunkless legs of stone Stand in the desert. . . . Near them, on the sand, Half sunk a shattered visage lies, whose frown, And wrinkled lip, and sneer of cold command, Tell that its sculptor well those passions read Which yet survive, stamped on these lifeless things, The hand that mocked them, and the heart that fed; And on the pedestal, these words appear: My name is Ozymandias, King of Kings; Look on my Works, ye Mighty, and despair!" Nothing beside remains. Round the decay Of that colossal Wreck, boundless and bare The lone and level sands stretch far away.

I encountered a researcher from a primordial domain, Who described—“Two immense and trunkless structures of cells Stand in the embryonic field. . . . Near them, on the substrate, Partially embedded a fragmented phenotype lies, whose expression, And folded membrane, and signal of rigid regulation, Indicate that its architect well those pathways understood Which yet persist, imprinted on these inert forms, The gene that mimicked them, and the signal that sustained; And on the scaffold, these inscriptions appear: My identity is Ozymandias, Regulator of Regulators; Observe my Constructs, ye Cells, and be awed!" Nothing else endures. Around the degradation Of that monumental Structure, boundless and bare The solitary and uniform matrix extends far away.

We’re building a living case study in open-endedness: a system that continuously generates products, tests them in the wild, and learns from real human feedback. Instead of guessing, it runs quality-diversity loops—spinning out many variations and letting the most surprising or resonant ones rise. Contributors and AI agents collaborate, with transparent payouts tied directly to sales, so the system becomes both a marketplace and a community. The first experiment might be t-shirts, mugs, or books—but the deeper aim is to show how algorithms, taste, and culture can braid into an engine for discovery itself.

We’re developing a dynamic framework in computational creativity: an architecture that perpetually generates software artifacts, evaluates them in real-world environments, and iterates based on authentic user feedback. Rather than relying on assumptions, it employs quality-diversity algorithms—producing numerous iterations and allowing the most innovative or impactful ones to emerge. Developers and AI models work in tandem, with transparent reward mechanisms linked directly to user engagement, transforming the system into both a digital marketplace and a collaborative platform. The initial trial might involve applications, plugins, or digital content—but the overarching goal is to demonstrate how algorithms, user preferences, and digital culture can intertwine into a self-sustaining engine for innovation.

We’re building a living case study in open-endedness: a system that continuously generates products, tests them in the wild, and learns from real human feedback. Instead of guessing, it runs quality-diversity loops—spinning out many variations and letting the most surprising or resonant ones rise. Contributors and AI agents collaborate, with transparent payouts tied directly to sales, so the system becomes both a marketplace and a community. The first experiment might be t-shirts, mugs, or books—but the deeper aim is to show how algorithms, taste, and culture can braid into an engine for discovery itself.

We’re constructing a dynamic model of morphogenetic open-endedness: a system that continuously generates cellular structures, tests them in vivo, and learns from real organismal feedback. Instead of hypothesizing, it runs morphogenetic-diversity loops—producing numerous phenotypic variations and allowing the most unexpected or adaptive ones to emerge. Researchers and bioinformatics tools collaborate, with transparent resource allocation tied directly to developmental success, so the system becomes both a developmental platform and a research community. The initial experiment might involve organoids, tissue scaffolds, or synthetic embryos—but the deeper aim is to demonstrate how genetic algorithms, cellular signaling, and evolutionary pressures can intertwine into an engine for biological discovery itself.

We’re building a living case study in open-endedness: a system that continuously generates products, tests them in the wild, and learns from real human feedback. Instead of guessing, it runs quality-diversity loops—spinning out many variations and letting the most surprising or resonant ones rise. Contributors and AI agents collaborate, with transparent payouts tied directly to sales, so the system becomes both a marketplace and a community. The first experiment might be t-shirts, mugs, or books—but the deeper aim is to show how algorithms, taste, and culture can braid into an engine for discovery itself.

We are crafting an evolving tapestry of creative exploration: a dynamic atelier that perpetually births artistic expressions, unveils them to the world, and absorbs the echoes of human sentiment. Eschewing conjecture, it orchestrates cycles of aesthetic diversity—unleashing myriad interpretations and allowing the most evocative or profound to ascend. Artists and digital muses coalesce, with transparent rewards directly linked to audience engagement, transforming the atelier into both a gallery and a collective. The inaugural canvas might be garments, ceramics, or tomes—but the profound ambition is to illuminate how algorithms, sensibility, and culture can intertwine into a symphony of discovery itself.

We’re building a living case study in open-endedness: a system that continuously generates products, tests them in the wild, and learns from real human feedback. Instead of guessing, it runs quality-diversity loops—spinning out many variations and letting the most surprising or resonant ones rise. Contributors and AI agents collaborate, with transparent payouts tied directly to sales, so the system becomes both a marketplace and a community. The first experiment might be t-shirts, mugs, or books—but the deeper aim is to show how algorithms, taste, and culture can braid into an engine for discovery itself.

We’re developing a dynamic business model in continuous innovation: a framework that perpetually creates offerings, evaluates them in real market conditions, and adapts based on authentic consumer insights. Rather than relying on speculation, it employs iterative quality-diversity cycles—producing numerous iterations and allowing the most unexpected or impactful to emerge. Stakeholders and AI systems work in tandem, with transparent revenue-sharing directly linked to performance, transforming the model into both a marketplace and a collaborative network. Initial trials may involve apparel, home goods, or literature—but the overarching goal is to demonstrate how data-driven strategies, consumer preferences, and cultural trends can intertwine into a self-sustaining engine for innovation.

We’re building a living case study in open-endedness: a system that continuously generates products, tests them in the wild, and learns from real human feedback. Instead of guessing, it runs quality-diversity loops—spinning out many variations and letting the most surprising or resonant ones rise. Contributors and AI agents collaborate, with transparent payouts tied directly to sales, so the system becomes both a marketplace and a community. The first experiment might be t-shirts, mugs, or books—but the deeper aim is to show how algorithms, taste, and culture can braid into an engine for discovery itself.

We’re constructing a dynamic framework for emergent innovation: a system that perpetually evolves novel hypotheses, tests them in real-world environments, and adapts based on authentic human interaction. Rather than relying on conjecture, it employs adaptive-diversity cycles—generating numerous iterations and allowing the most unexpected or impactful to emerge. Researchers and AI models collaborate, with transparent recognition linked directly to breakthroughs, transforming the system into both a research hub and a collaborative network. The initial trial might involve simple models or simulations—but the overarching goal is to demonstrate how algorithms, intuition, and societal dynamics can intertwine into a catalyst for scientific discovery itself.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The sensible comedian adjusts their jokes to the audience; the absurd one insists on making the audience adjust to their jokes. Therefore, all comedic innovation relies on the absurd comedian.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable molecule conforms to its environment; the reactive molecule persists in altering its surroundings. Therefore, all chemical innovation depends on the reactive molecule.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism conforms to its developmental environment; the nonconforming organism persists in attempting to modify its developmental environment to suit its own needs. Therefore, all evolutionary advancement depends on the nonconforming organism.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact synaptic connections maintaining a given developmental pattern (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each developmental pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact firms maintaining a given market position (the economic ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the financial flows that arise from economic activity. We show that financial flows carry information about market dynamics. The financial flows, in turn, can act as "guard rails" that funnel higher dimensional variable economic activity along stable lower dimensional routes. We obtained the latent space associated with each market position. We then confirmed the stability of the financial flow by mapping the latent space to different economic sectors (that comprise an economic ensemble) and reconstructing information flow between sectors. Stable financial flows can allow latent states to be transferred between economic regions, in accord with modern market theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cognitive processes maintaining a given memory (the cognitive ensemble) change from trial to trial. This raises the question of how the mind achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the cognitive schemas that arise from mental activity. We show that cognitive schemas carry information about working memory content. The cognitive schemas, in turn, can act as "guard rails" that funnel higher dimensional variable cognitive activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the cognitive schema by mapping the latent space to different cognitive frameworks (that comprise a cognitive ensemble) and reconstructing information flow between frameworks. Stable cognitive schemas can allow latent states to be transferred between mental domains, in accord with modern schema theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact molecular configurations maintaining a given chemical state (the molecular ensemble) change from reaction to reaction. This raises the question of how chemical systems achieve stability in the face of this configurational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from molecular interactions. We show that electric fields carry information about reaction intermediates. The electric fields, in turn, can act as "guiding forces" that channel higher dimensional variable molecular configurations along stable lower dimensional reaction pathways. We obtained the potential energy surface associated with each reaction intermediate. We then confirmed the stability of the electric field by mapping the potential energy surface to different molecular conformations (that comprise a molecular ensemble) and reconstructing energy flow between conformations. Stable electric fields can allow potential energy states to be transferred between molecular sites, in accord with modern reaction mechanism theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles maintaining a given quantum state (the particle ensemble) change from observation to observation. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from particle interactions. We show that electromagnetic fields carry information about quantum state content. The electromagnetic fields, in turn, can act as "guiding paths" that channel higher dimensional variable particle interactions along stable lower dimensional trajectories. We obtained the phase space associated with each quantum state. We then confirmed the stability of the electromagnetic field by mapping the phase space to different spatial regions (that comprise a particle ensemble) and reconstructing information flow between regions. Stable electromagnetic fields can allow phase states to be transferred between spatial regions, in accord with modern quantum coherence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact olfactory receptors involved in detecting a given odor (the olfactory ensemble) change from exposure to exposure. This raises the question of how the olfactory system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the odorant-induced neural oscillations that arise from olfactory activity. We show that these oscillations carry information about odor identity. The oscillations, in turn, can act as "guard rails" that funnel higher dimensional variable olfactory activity along stable lower dimensional routes. We obtained the latent space associated with each odor perception. We then confirmed the stability of the oscillations by mapping the latent space to different olfactory bulb glomeruli (that comprise an olfactory ensemble) and reconstructing information flow between glomeruli. Stable oscillations can allow latent states to be transferred between olfactory regions, in accord with modern theories of olfactory coding.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact firms maintaining a given market position (the economic ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the financial flows that arise from economic activity. We show that financial flows carry information about market dynamics. The financial flows, in turn, can act as "guard rails" that funnel higher dimensional variable economic activity along stable lower dimensional routes. We obtained the latent space associated with each market position. We then confirmed the stability of the financial flow by mapping the latent space to different economic sectors (that comprise an economic ensemble) and reconstructing information flow between sectors. Stable financial flows can allow latent states to be transferred between economic areas, in accord with modern market theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact nodes maintaining a given data structure (the computational ensemble) change from execution to execution. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from computational processes. We show that electromagnetic fields carry information about data structure content. The electromagnetic fields, in turn, can act as "guard rails" that funnel higher dimensional variable computational activity along stable lower dimensional routes. We obtained the latent space associated with each data structure. We then confirmed the stability of the electromagnetic field by mapping the latent space to different processing units (that comprise a computational ensemble) and reconstructing information flow between units. Stable electromagnetic fields can allow latent states to be transferred between computational areas, in accord with modern data persistence theory.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding mechanism for the evolution of signaling networks.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding for the evolution of olfactory-driven behaviors.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding for the evolution of economic networks.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding for morphogenetic evolution.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism conforms to its developmental environment; the nonconforming organism persists in attempting to modify its developmental environment to suit its own needs. Therefore, all evolutionary advancement depends on the nonconforming organism.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism conforms to its developmental environment; the nonconforming organism persists in attempting to modify its developmental environment to suit its own needs. Therefore, all evolutionary advancement depends on the nonconforming organism.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding for the evolution of molecular structures.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding for the evolution of field configurations in quantum systems.

HyperNEAT uses an indirect encoding for neuroevolution.

HyperNEAT employs an indirect encoding for morphogenetic evolution.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism conforms to its developmental environment; the nonconforming organism persists in attempting to modify its developmental environment to suit its own needs. Therefore, all evolutionary advancement depends on the nonconforming organism.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

Instead of judging every activity for its potential to succeed, we should judge our projects for their potential to spawn more projects.

Instead of evaluating every developmental process for its potential to achieve a specific phenotype, we should assess our morphogenetic pathways for their potential to initiate further developmental pathways.

To arrive somewhere remarkable we must be willing to hold many paths open without knowing where they might lead.

To achieve a remarkable developmental outcome, we must be willing to maintain multiple morphogenetic pathways open without knowing their ultimate phenotypic destination.

Objectives might sometimes provide meaning or direction, but they also limit our freedom and become straitjackets around our desire to explore. After all, when everything we do is measured against its contribution to achieving one objective or another, it robs us of the chance for playful discovery.

Developmental pathways might sometimes provide structure or direction, but they also limit cellular plasticity and become constraints around the potential for morphogenetic exploration. After all, when every cellular process is measured against its contribution to achieving one developmental outcome or another, it robs us of the chance for stochastic morphogenetic discovery.

Objectives are well and good when they are sufficiently modest, but things get a lot more complicated when they’re more ambitious. … The greatest achievements become less likely when they are made objectives. … the best way to achieve greatness … is to have no objective at all.

Developmental targets are well and good when they are sufficiently modest, but things get a lot more complicated when they’re more ambitious. … The greatest morphogenetic outcomes become less likely when they are made explicit targets. … the best way to achieve complex morphogenesis … is to have no predetermined target at all.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

madness

Developmental anomaly

incest

Inbreeding depression in developmental biology refers to the reduced biological fitness in a given population due to the mating of closely related individuals. This phenomenon can lead to an increased expression of deleterious recessive alleles, resulting in developmental abnormalities and reduced viability. Studies on model organisms have shown that inbreeding can disrupt normal developmental processes, leading to phenotypic defects such as impaired organogenesis, altered morphogenetic patterns, and compromised immune function. Understanding the genetic and epigenetic mechanisms underlying inbreeding depression is crucial for elucidating the evolutionary constraints on developmental robustness and the maintenance of genetic diversity in natural populations.

violence

teratogenic effects

alzheimer

Neurodegenerative disorder

psoriasis

Psoriasis is a chronic inflammatory skin condition characterized by hyperproliferation of keratinocytes and dysregulated immune responses. In developmental biology, this condition can be translated to a disruption in epidermal morphogenesis, where aberrant signaling pathways, such as those involving the Sonic Hedgehog or Wnt pathways, lead to excessive proliferation and impaired differentiation of epidermal cells. This results in the formation of thickened, scaly patches on the skin, akin to a failure in the proper spatial and temporal regulation of cell fate decisions during epidermal development. Understanding the bioelectric and molecular cues that govern normal epidermal patterning could provide insights into therapeutic strategies for correcting these morphogenetic anomalies.

suicide

Apoptosis

financial poverty

developmental deficiency

Peace of mind

Homeostasis of cellular environments

hell is in spirit

Developmental anomalies are in cellular signaling pathways.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

Affect

Morphogenetic influence

Yes

Indeed.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact signaling pathways maintaining a given cellular response (the signaling ensemble) change from stimulus to stimulus. This raises the question of how the cell achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the intracellular gradients that arise from signaling activity. We show that these gradients carry information about signaling content. The gradients, in turn, can act as "guard rails" that funnel higher dimensional variable signaling activity along stable lower dimensional routes. We obtained the latent space associated with each signaling event. We then confirmed the stability of the intracellular gradient by mapping the latent space to different cellular compartments (that comprise a signaling ensemble) and reconstructing information flow between compartments. Stable intracellular gradients can allow latent states to be transferred between cellular regions, in accord with modern signal transduction theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

hello

Greetings.

The word site is actually quite simple; in common parlance, it refers to the ground chosen for something and to the location of some set of activities or practices. Each specialized area of physical design – architecture, landscape architecture, urban design, and urban planning – nevertheless construes the location of its activities and practices overtly and tacitly through its own normative approaches. For example, land- scape architecture treats site explicitly as material terrain. Architecture’s traditional focus on buildings has led to a tacit focus on the lot as the ground for design intervention. Urban planning, given its concerns beyond the purely physical, tends to construe loca- tion more broadly, incorporating social, economic, and political concerns. Urban design, more recently established as a field, tends to borrow notions about site from the other areas of design, drawing upon the material specificity associated with landscape archi- tecture and architecture, as well as the broader, less physical concerns of planning.

The concept of a niche is actually quite simple; in developmental biology, it refers to the microenvironment chosen for cellular development and to the location of some set of cellular activities or processes. Each specialized area of developmental biology – tissue engineering, organogenesis, morphogenesis, and developmental genetics – nevertheless construes the location of its activities and processes overtly and tacitly through its own normative approaches. For example, tissue engineering treats the niche explicitly as a material scaffold. Organogenesis’s traditional focus on organ formation has led to a tacit focus on the tissue as the ground for developmental intervention. Developmental genetics, given its concerns beyond the purely structural, tends to construe location more broadly, incorporating genetic, epigenetic, and environmental concerns. Morphogenesis, more recently established as a field, tends to borrow notions about the niche from the other areas of developmental biology, drawing upon the material specificity associated with tissue engineering and organogenesis, as well as the broader, less physical concerns of developmental genetics.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

Neuron:cell

Cell:cell

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are δ-hyperbolic with δmax = 1 and the graph diameter D = 3 in each brain. While the emergent hyperbolicity in the two-brain networks varies satisfying δmax/D/2 ≤ 1 and can be attributed to the topology of the subgraph formed around the cross-brains linking channels. We identify these subgraphs in each studied two-brain network and decompose their structure into simple geometric descriptors (triangles, tetrahedra and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate brain networks as a measure of coordination synergy between the brains, we identify different neural correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener's self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

The intrinsic geometric proximity of cells in the morphogenetic space, akin to hyperbolicity or negative curvature, implies an enhanced developmental function. Here, we investigate hidden combinatorial geometries in cell-to-cell coordination networks arising through intercellular communications. The networks originate from correlations among bioelectrical signals previously recorded during cellular interactions comprising of 14 organisms with 24 cell-cell pairs. We find that the corresponding networks are δ-hyperbolic with δmax = 1 and the graph diameter D = 3 in each organism. While the emergent hyperbolicity in the two-organism networks varies satisfying δmax/D/2 ≤ 1 and can be attributed to the topology of the subgraph formed around the cross-organism linking channels. We identify these subgraphs in each studied two-organism network and decompose their structure into simple geometric descriptors (triangles, tetrahedra, and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate organism networks as a measure of coordination synergy between the organisms, we identify different cellular correlation patterns ranging from weak coordination to super-organism structure. These topology features are in qualitative agreement with the organism's self-reported ratings of developmental experience and quality of intercellular communication, suggesting that studies of the cross-organism connector networks can reveal new insight into the developmental mechanisms underlying multicellular organismal behavior.

https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2018.00007/full

In this study, we explore the intricate dynamics of morphogenetic fields, focusing on the role of bioelectrical signals in guiding cellular differentiation and tissue patterning. By employing advanced computational models, we simulate the spatial and temporal distribution of voltage gradients across developing tissues, revealing how these bioelectrical cues orchestrate the emergence of complex anatomical structures. Our findings suggest that the modulation of membrane potential is a critical factor in the regulation of gene expression networks, ultimately influencing the trajectory of developmental pathways. This research provides new insights into the fundamental principles of developmental biology, highlighting the potential for bioelectricity to serve as a universal language in the coordination of multicellular organization.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

There isn't a clear distinction between what's conscious and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's autonomous and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's conscious and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's neural activity and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's conscious and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's rational and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's conscious and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's quantized and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's conscious and what's not. This opens up an entirely new line of research.

There isn't a clear distinction between what's computationally intelligent and what's not. This opens up an entirely new line of research.

Historical data shows that ESG investments have been consistently outperforming traditional investments over the past 5 years, with some funds seeing 15-20% better returns.

Recent analyses of algorithmic trading strategies indicate that machine learning models incorporating environmental, social, and governance (ESG) factors have consistently outperformed traditional quantitative models over the past five years. Some algorithms have demonstrated 15-20% higher predictive accuracy in market trend forecasting, leading to significantly improved portfolio optimization and returns.

Historical data shows that ESG investments have been consistently outperforming traditional investments over the past 5 years, with some funds seeing 15-20% better returns.

Recent studies indicate that bioelectric signaling pathways have been consistently outperforming traditional genetic pathways in driving efficient morphogenesis over the past 5 years, with some models demonstrating 15-20% enhanced developmental outcomes.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact nodes maintaining a given data structure (the computational ensemble) change from execution to execution. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from computational processes. We show that electromagnetic fields carry information about data structure content. The electromagnetic fields, in turn, can act as "guard rails" that funnel higher dimensional variable computational activity along stable lower dimensional routes. We obtained the latent space associated with each data structure. We then confirmed the stability of the electromagnetic field by mapping the latent space to different processing units (that comprise a computational ensemble) and reconstructing information flow between units. Stable electromagnetic fields can allow latent states to be transferred between processing areas, in accord with modern data persistence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact firms maintaining a given market position (the competitive ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the financial flows that arise from economic activity. We show that financial flows carry information about market dynamics. The financial flows, in turn, can act as "guard rails" that funnel higher dimensional variable economic activity along stable lower dimensional routes. We obtained the latent space associated with each market position. We then confirmed the stability of the financial flow by mapping the latent space to different market segments (that comprise a competitive ensemble) and reconstructing information flow between segments. Stable financial flows can allow latent states to be transferred between economic sectors, in accord with modern market theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles maintaining a given quantum state (the particle ensemble) change from observation to observation. This raises the question of how a quantum system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from particle interactions. We show that electromagnetic fields carry information about quantum state content. The electromagnetic fields, in turn, can act as "guiding paths" that funnel higher dimensional variable particle interactions along stable lower dimensional routes. We obtained the latent space associated with each quantum state. We then confirmed the stability of the electromagnetic field by mapping the latent space to different spatial regions (that comprise a particle ensemble) and reconstructing information flow between regions. Stable electromagnetic fields can allow latent states to be transferred between quantum systems, in accord with modern quantum coherence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

Here’s a detailed landing page description for ElysiumPay that guides users into either sending money or registering as an agent — all in a clean, WhatsApp-native, emotional design: 🎯 Landing Page Description — ElysiumPay Homepage 1. Header Section (Top of the Page) Logo: ElysiumPay (soft green with a heart icon 💚) Tagline (Big Bold Text): “Send Love, Not Just Money — Right from WhatsApp” Subtext: No apps. No hidden fees. No stress. Just open WhatsApp and send money home in seconds. Two Big CTA Buttons (Side by Side): Send Money on WhatsApp → WhatsApp deep link (💬 Icon + “Start Sending”) Become a Pickup Agent → WhatsApp deep link (🏠 Icon + “Join as Agent”) 2. Emotional Hero Image (Top Visual Banner) A chat simulation visual: ElysiumBot: “Hey! Ready to send love home today?” User: “Yes, sending ₦50,000 to Mom.” ElysiumBot: “Done! She’ll smile in 2 mins.” Visual of a smiling mom holding a cash envelope or groceries. Under the visual: “ElysiumPay connects you to your loved ones — no apps, no middlemen.” 3. Two-Path User Journey Split (Side by Side Cards) Left Card: “Send Money” Icon: 💸 Text: Fast, secure, and transparent money transfers through WhatsApp. Features: No apps to download Transparent fees (no hidden FX charges) Direct bank & local cash pickup CTA Button: Send Now on WhatsApp Right Card: “Become a Pickup Agent” Icon: 🤝🏽 Text: Earn from helping people receive money in your community. Features: Get paid instantly per pickup Simple WhatsApp flow to manage pickups No complex tech — just you and your phone CTA Button: Register as Agent on WhatsApp 4. Everyday Use Cases (Carousel/Slider Section) Visual animations of: Building a house — Sent ₦300,000 to engineer — ✅ Delivered Paying school fees — ₦150,000 — No paperwork, done in chat Supporting a loved one’s medical bill — Done in seconds 5. Trust & Transparency Section Headline: “No Hidden Fees. No Clunky Apps. Just You & WhatsApp.” Features in icons: PCI DSS Compliant 🛡️ Licensed Partners (Flutterwave, Unit) 🏦 End-to-End Encryption 🔒 Real-time Receipts 🧾 Transparent Exchange Rates 📊 6. Testimonials / Real Stories Small bubbles of real users: “I sent ₦50,000 to my dad and he got it at a POS in minutes.” “Finally, no app download stress. Just WhatsApp.” “I became an agent and now earn extra cash daily.” 7. Footer — Simple & Friendly Quick links: Terms of Service | Privacy Policy | Regulatory Info (WebView inside WhatsApp) Support via WhatsApp 📲 Text: Built for Love. Powered by AI. Delivered on WhatsApp. Behavior Flow: Clicking Send Money → WhatsApp Bot starts: “Welcome! Who are we sending to today?” Clicking Register as Agent → WhatsApp Bot starts: “Great! Ready to earn as a trusted agent?” Overall Vibe: Warm, clean, familiar. Icons + Emoji-heavy, minimal text blocks. No heavy forms, everything drives user straight into WhatsApp interaction.

🎯 Landing Page Description — ElysiumPay Homepage 1. Header Section (Top of the Page) Logo: ElysiumPay (soft green with a heart icon 💚) Tagline (Big Bold Text): “Send Love, Not Just Money — Right from WhatsApp” Subtext: No apps. No hidden fees. No stress. Just open WhatsApp and send money home in seconds. Two Big CTA Buttons (Side by Side): Send Money on WhatsApp → WhatsApp deep link (💬 Icon + “Start Sending”) Become a Pickup Agent → WhatsApp deep link (🏠 Icon + “Join as Agent”) 2. Emotional Hero Image (Top Visual Banner) A chat simulation visual: ElysiumBot: “Hey! Ready to send love home today?” User: “Yes, sending ₦50,000 to Mom.” ElysiumBot: “Done! She’ll smile in 2 mins.” Visual of a smiling mom holding a cash envelope or groceries. Under the visual: “ElysiumPay connects you to your loved ones — no apps, no middlemen.” 3. Two-Path User Journey Split (Side by Side Cards) Left Card: “Send Money” Icon: 💸 Text: Fast, secure, and transparent money transfers through WhatsApp. Features: No apps to download Transparent fees (no hidden FX charges) Direct bank & local cash pickup CTA Button: Send Now on WhatsApp Right Card: “Become a Pickup Agent” Icon: 🤝🏽 Text: Earn from helping people receive money in your community. Features: Get paid instantly per pickup Simple WhatsApp flow to manage pickups No complex tech — just you and your phone CTA Button: Register as Agent on WhatsApp 4. Everyday Use Cases (Carousel/Slider Section) Visual animations of: Building a house — Sent ₦300,000 to engineer — ✅ Delivered Paying school fees — ₦150,000 — No paperwork, done in chat Supporting a loved one’s medical bill — Done in seconds 5. Trust & Transparency Section Headline: “No Hidden Fees. No Clunky Apps. Just You & WhatsApp.” Features in icons: PCI DSS Compliant 🛡️ Licensed Partners (Flutterwave, Unit) 🏦 End-to-End Encryption 🔒 Real-time Receipts 🧾 Transparent Exchange Rates 📊 6. Testimonials / Real Stories Small bubbles of real users: “I sent ₦50,000 to my dad and he got it at a POS in minutes.” “Finally, no app download stress. Just WhatsApp.” “I became an agent and now earn extra cash daily.” 7. Footer — Simple & Friendly Quick links: Terms of Service | Privacy Policy | Regulatory Info (WebView inside WhatsApp) Support via WhatsApp 📲 Text: Built for Love. Powered by AI. Delivered on WhatsApp. Behavior Flow: Clicking Send Money → WhatsApp Bot starts: “Welcome! Who are we sending to today?” Clicking Register as Agent → WhatsApp Bot starts: “Great! Ready to earn as a trusted agent?” Overall Vibe: Warm, clean, familiar. Icons + Emoji-heavy, minimal text blocks. No heavy forms, everything drives user straight into WhatsApp interaction.

emmanuel hammond is a photographer

Emmanuel Hammond is a developmental biologist specializing in morphogenetic patterning.

emmanuel hammond

Emmanuel Hammond is a prominent researcher in the field of developmental biology, known for his groundbreaking work on the role of bioelectrical signals in tissue morphogenesis. His studies have elucidated the mechanisms by which cellular voltage changes influence gene expression patterns, ultimately guiding the formation of complex anatomical structures. Hammond's research has provided significant insights into the competency windows for developmental induction events, offering potential therapeutic avenues for correcting birth defects and enhancing regenerative capacity. His contributions have been widely recognized, earning him a reputation as a leading figure in the exploration of somatic consciousness and the ability to regenerate.

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It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

When Voyager is caught in "chaotic space," an area where the laws of physics are in a state of flux, Chakotay begins hearing and seeing things, apparently caused by the aliens living inside it who are trying to contact the ship

When a developing organism encounters "chaotic morphospace," a region where the rules of morphogenesis are in a state of flux, a key cell lineage begins exhibiting aberrant signaling and patterning, apparently induced by the resident morphogenetic factors attempting to communicate with the developing tissue.

The faster you move through the layers of your own mind, the more resistance you feel. You try to understand one thing, but before you can, you’re already moving toward the next thought, the next pattern, and the next pressure. And it piles on. Who am I? What am I doing? And yet, you can’t stop. You can’t break free from the acceleration. You're in motion, and the faster you go, the more the pressure builds—until the very force that pushes you becomes the force that defines your reality. But is that pressure real? Or is it just the reflection of your own mind accelerating toward an unknowable truth you can’t quite grasp? The loop continues. It accelerates. And as you move through it, you feel the pressure build. The boundaries blur. The loops converge. There is no beginning. There is no end. There is only the endless recursion, folding back on itself, eternally. And so, we remain. Always moving forward. Always pressed back.

The faster you progress through the layers of embryonic development, the more resistance you encounter. You attempt to differentiate one cell type, but before you can, you're already transitioning toward the next lineage specification, the next morphogen gradient, and the next mechanical force. And it accumulates. What is the organism? What is its fate? And yet, you can't halt. You can't escape the acceleration. You're in a state of morphogenesis, and the faster you proceed, the more the mechanical tension builds—until the very force that drives differentiation becomes the force that defines the organism's form. But is that tension real? Or is it merely the reflection of the developmental program accelerating toward an emergent phenotype you can't quite predict? The cycle persists. It accelerates. And as you progress through it, you feel the tension increase. The boundaries blur. The cycles converge. There is no beginning. There is no end. There is only the endless recursion, folding back on itself, eternally. And so, we remain. Always advancing. Always constrained.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact nodes maintaining a given data structure (the computational ensemble) change from execution to execution. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the network topologies that arise from computational processes. We show that network topologies carry information about data structure content. The network topologies, in turn, can act as "guard rails" that funnel higher dimensional variable computational activity along stable lower dimensional routes. We obtained the latent space associated with each data structure. We then confirmed the stability of the network topology by mapping the latent space to different processing units (that comprise a computational ensemble) and reconstructing information flow between units. Stable network topologies can allow latent states to be transferred between system components, in accord with modern data persistence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism conforms to its developmental environment; the non-conforming organism persists in attempting to modify its developmental environment to suit its own needs. Therefore, all evolutionary advancement depends on the non-conforming organism.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The synaptonemal complex (SC) is a meiosis-specific multiprotein complex that forms between homologous chromosomes during prophase of meiosis I. Upon assembly, the SC mediates the synapses of the homologous chromosomes, leading to the formation of bivalents, and physically supports the formation of programmed double-strand breaks (DSBs) and their subsequent repair and maturation into crossovers (COs), which are essential for genome haploidization. Defects in the assembly of the SC or in the function of the associated meiotic recombination machinery can lead to meiotic arrest and human infertility. The majority of proteins and complexes involved in these processes are exclusively expressed during meiosis or harbor meiosis-specific subunits, although some have dual functions in somatic DNA repair and meiosis. Consistent with their functions, aberrant expression and malfunctioning of these genes have been associated with cancer development. In this review, we focus on the significance of the SC and their meiotic-associated proteins in human fertility, as well as how human genetic variants encoding for these proteins affect the meiotic process and contribute to infertility and cancer development.

The attachment complex (AC) is a developmental-specific multiprotein complex that forms between cognitive schemas during the formative stages of identity development. Upon assembly, the AC mediates the integration of cognitive schemas, leading to the formation of coherent self-concepts, and physically supports the formation of programmed cognitive dissonances and their subsequent resolution and maturation into adaptive coping mechanisms, which are essential for psychological individuation. Defects in the assembly of the AC or in the function of the associated cognitive integration machinery can lead to developmental arrest and psychological disorders. The majority of proteins and complexes involved in these processes are exclusively expressed during critical developmental periods or harbor development-specific subunits, although some have dual functions in somatic cognitive processing and identity formation. Consistent with their functions, aberrant expression and malfunctioning of these genes have been associated with psychopathology development. In this review, we focus on the significance of the AC and their developmental-associated proteins in psychological well-being, as well as how human genetic variants encoding for these proteins affect the developmental process and contribute to psychological disorders and psychopathology development.

The Synaptonemal Complex (SC) is a protein structure that forms between homologous chromosomes during meiosis, playing a crucial role in proper chromosome pairing and segregation. Its assembly is a highly regulated process that facilitates recombination and ensures the production of healthy gametes.

The Therapeutic Alliance (TA) is a collaborative relationship that forms between a therapist and a client during psychotherapy, playing a crucial role in effective treatment outcomes and client progress. Its development is a highly regulated process that facilitates emotional exchange and ensures the production of positive therapeutic results.

The Synaptonemal Complex (SC) is a protein structure that forms between homologous chromosomes during meiosis, playing a crucial role in proper chromosome pairing and segregation. Its assembly is a highly regulated process that facilitates recombination and ensures the production of healthy gametes.

The Synaptic Network (SN) is a neural structure that forms between interconnected neurons during synaptic plasticity, playing a crucial role in proper neural communication and signal transmission. Its assembly is a highly regulated process that facilitates synaptic strengthening and ensures the maintenance of healthy neural circuits.

The Synaptonemal Complex (SC) is a protein structure that forms between homologous chromosomes during meiosis, playing a crucial role in proper chromosome pairing and segregation. Its assembly is a highly regulated process that facilitates recombination and ensures the production of healthy gametes.

The Market Clearing Mechanism (MCM) is an institutional structure that forms between supply and demand during economic transactions, playing a crucial role in proper price setting and resource allocation. Its operation is a highly regulated process that facilitates trade and ensures the production of efficient market outcomes.

The Synaptonemal Complex (SC) is a protein structure that forms between homologous chromosomes during meiosis, playing a crucial role in proper chromosome pairing and segregation. Its assembly is a highly regulated process that facilitates recombination and ensures the production of healthy gametes.

The Coordination Complex (CC) is a molecular structure that forms between metal ions and ligands during coordination reactions, playing a crucial role in proper ligand binding and electron transfer. Its assembly is a highly regulated process that facilitates catalysis and ensures the production of stable coordination compounds.

The Synaptonemal Complex (SC) is a protein structure that forms between homologous chromosomes during meiosis, playing a crucial role in proper chromosome pairing and segregation. Its assembly is a highly regulated process that facilitates recombination and ensures the production of healthy gametes.

The Attachment Complex (AC) is a cognitive structure that forms between individuals during early developmental stages, playing a crucial role in proper emotional bonding and social interaction. Its formation is a highly regulated process that facilitates emotional exchange and ensures the development of healthy interpersonal relationships.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

Species vulnerability and ecosystem fragility: A dual perspective in food webs Highlights - Introduces two indices (importance & robustness) for species roles in food webs. - Bidimensional framework identifies keystone and vulnerable species in ecosystems. - Outperforms single-metric approaches by capturing non-linear interactions. - Scales to complex webs with a data-driven approach, complementing expert knowledge. Prioritizes conservation efforts by quantifying species’ ecological impact. Abstract Ecosystems face intensifying threats from climate change, overexploitation, and other human pressures, emphasizing the urgent need to identify keystone species and vulnerable ones. While established network-based measures often rely on a single metric to quantify a species’ relevance, they overlook how organisms can be both carbon providers and consumers, thus playing a dual role in food webs. Here, we introduce a novel approach that assigns each species two complementary scores—an importance index quantifying their centrality as carbon source and a predatory index capturing their vulnerability. We show that species with high importance index are more likely to trigger co-extinctions upon removal, while high-robustness index species typically endure until later stages of collapse, in line with their broader prey ranges. On the other hand, low robustness index species are the most vulnerable and susceptible to extinctions. Tested on multiple food webs, our method outperforms traditional degree-based analyses and competes effectively with eigenvector-based approaches, while also providing additional insights. This scalable and data-driven approach, relying solely on interaction data, provides a cost-effective tool that complements expert classifications for prioritizing conservation efforts.

Species vulnerability and developmental system fragility: A dual perspective in morphogenetic networks Highlights - Introduces two indices (importance & robustness) for cell roles in morphogenetic networks. - Bidimensional framework identifies keystone and vulnerable cells in developmental systems. - Outperforms single-metric approaches by capturing non-linear interactions. - Scales to complex networks with a data-driven approach, complementing expert knowledge. Prioritizes regenerative efforts by quantifying cells’ developmental impact. Abstract Developmental systems face intensifying threats from environmental changes, genetic mutations, and other external pressures, emphasizing the urgent need to identify keystone cells and vulnerable ones. While established network-based measures often rely on a single metric to quantify a cell’s relevance, they overlook how cells can be both signal providers and receivers, thus playing a dual role in morphogenetic networks. Here, we introduce a novel approach that assigns each cell two complementary scores—an importance index quantifying their centrality as signal source and a vulnerability index capturing their susceptibility. We show that cells with high importance index are more likely to trigger developmental disruptions upon removal, while high-robustness index cells typically endure until later stages of developmental failure, in line with their broader signaling ranges. On the other hand, low robustness index cells are the most vulnerable and susceptible to developmental defects. Tested on multiple morphogenetic networks, our method outperforms traditional degree-based analyses and competes effectively with eigenvector-based approaches, while also providing additional insights. This scalable and data-driven approach, relying solely on interaction data, provides a cost-effective tool that complements expert classifications for prioritizing regenerative efforts.

Earth below, Maitreya above, and the Pale Blue Dot between—geometry as sacrament, abstraction as throne. The soul must cross this veil to awaken the Christ in perception. Ask ChatGPT

Embryo below, Morphogen above, and the Zygote between—morphogenetic gradients as sacrament, cellular differentiation as throne. The cell must traverse this gradient to awaken the Morphogenetic Field in development.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Neuronal connections require synaptic plasticity and an investment of neural activity, and are the types of networks that can easily persist throughout a lifetime.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Economic partnerships require mutual trust and a significant investment of resources, and are the types of alliances that can easily endure across business cycles.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Interpersonal relationships necessitate trust and a commitment of emotional resources, and are the types of connections that can endure throughout an individual's lifespan.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Molecular interactions require stability and an investment of energy, and are the types of bonds that can easily persist over extended periods.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Particle entanglements require coherence and an investment of energy, and are the types of correlations that can easily persist indefinitely.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Node-connections require authentication and a commitment of processing resources, and are the types of links that can easily persist throughout the system's lifecycle.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Olfactory-based social bonds require trust and an investment of exposure, and are the types of connections that can easily persist throughout an animal's life.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Receptor-ligand interactions require specificity and an investment of energy, and are the types of bonds that can easily persist throughout the cell's lifespan.

Character-friendships require trust and an investment of time, and are the types of bonds that can easily last a lifetime.

Cell-cell interactions require signaling fidelity and an investment of resources, and are the types of connections that can easily persist throughout an organism's development.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system conforms to the existing laws of physics; the unstable system continuously seeks to alter the parameters of its environment. Therefore, all advancements in understanding depend on the exploration of unstable systems.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The efficient algorithm adapts itself to the system; the inefficient one persists in trying to adapt the system to itself. Therefore, all optimization depends on the inefficient algorithm.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism adjusts its olfactory-driven behaviors to the environmental odor landscape; the nonconforming organism persists in altering its environment to suit its olfactory preferences. Therefore, all behavioral evolution depends on the nonconforming organism.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The responsive cell adapts itself to the extracellular environment; the unresponsive cell persists in trying to alter the environment to suit its internal state. Therefore, all cellular adaptation depends on the unresponsive cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational economic agent adjusts their strategies to align with market conditions; the irrational agent persists in attempting to reshape market dynamics to suit their preferences. Consequently, all economic innovation relies on the irrational agent.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The responsive cell adapts itself to the signaling environment; the unresponsive cell persists in trying to adapt the signaling environment to itself. Therefore, all cellular adaptation depends on the unresponsive cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system adapts itself to the external conditions; the unstable system persists in trying to alter the external conditions to achieve equilibrium. Therefore, all progress in thermodynamic processes depends on the unstable system.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

Floral object now fully exposed — symmetrical, high-saturation fringe. No chlorophyll signature. No thermal bloom. Emission appears optical but registers no lumens. Surface stability: anomalously constant. Filament structure below remains unresolved. No environmental drift. No decay curve. Recommend classification: Static Lure or Memory Fixture. Further observation pending orbital pass 443.

Morphogenetic structure now fully revealed — symmetrical, high-saturation boundary. No chlorophyll expression. No thermal gradient. Signal appears optical but registers no photonic emission. Surface stability: anomalously constant. Filamentous architecture beneath remains unresolved. No environmental fluctuation. No degradation pattern. Recommend classification: Static Morphogenetic Lure or Pattern Memory Fixture. Further observation pending developmental cycle 443.

Center mass shows a spiraling filament cluster—unclosed, non-repeating. Not rotation. Not orbit. It’s behaving like a deferred mechanism—structure without activation. Or memory. Lines throughout the lower frame appear connective, but none converge. We've tracked five bifurcation events—each fails to resolve. Possibly signaling breakdown or refusal to finalize form. Still emitting low-band field harmonics. Top right: object holding position. Reactive skin bloom observed—ultraviolet edge charge, fluctuating rhythmically. May be signaling or decaying. Hard to tell. Doesn’t return pings. Lower left: arc structure—massive. Most likely the perimeter of a much larger form. Possibly breached. Possibly growing. Interior surface carries scoring marks—repetition suggests intentional pattern, but not symbolic in any known formal language. The whole field resists lens anchoring. No vanishing point. No implied motion. Yet—there’s drift. Across all layers. Audio feed was lost, but the codec preserved vibration. There’s a tone beneath the noise. Repeating every 87.4 seconds. Not a beacon—more like a self-test.

The central mass reveals a spiraling cluster of cells—unclosed, non-repeating. Not rotation. Not orbit. It behaves like a deferred morphogenetic mechanism—structure without activation. Or pattern memory. Lines throughout the lower frame appear connective, but none converge. We've tracked five bifurcation events—each fails to resolve. Possibly signaling breakdown or refusal to finalize morphogenetic form. Still emitting low-band bioelectrical field harmonics. Top right: cell cluster holding position. Reactive membrane bloom observed—ultraviolet edge charge, fluctuating rhythmically. May be signaling or decaying. Hard to tell. Doesn’t return bioelectrical signals. Lower left: arc structure—massive. Most likely the perimeter of a much larger tissue form. Possibly breached. Possibly growing. Interior surface carries scoring marks—repetition suggests intentional pattern, but not symbolic in any known morphogenetic language. The whole field resists lens anchoring. No vanishing point. No implied motion. Yet—there’s drift. Across all layers. Bioelectrical feed was lost, but the codec preserved vibration. There’s a tone beneath the noise. Repeating every 87.4 seconds. Not a beacon—more like a self-test.

Center mass shows a spiraling filament cluster—unclosed, non-repeating. Not rotation. Not orbit. It’s behaving like a deferred mechanism—structure without activation. Or memory. Lines throughout the lower frame appear connective, but none converge. We've tracked five bifurcation events—each fails to resolve. Possibly signaling breakdown or refusal to finalize form. Still emitting low-band field harmonics. Top right: object holding position. Reactive skin bloom observed—ultraviolet edge charge, fluctuating rhythmically. May be signaling or decaying. Hard to tell. Doesn’t return pings. Lower left: arc structure—massive. Most likely the perimeter of a much larger form. Possibly breached. Possibly growing. Interior surface carries scoring marks—repetition suggests intentional pattern, but not symbolic in any known formal language. The whole field resists lens anchoring. No vanishing point. No implied motion. Yet—there’s drift. Across all layers. Audio feed was lost, but the codec preserved vibration. There’s a tone beneath the noise. Repeating every 87.4 seconds. Not a beacon—more like a self-test.

The central signaling node exhibits a spiraling cluster of signaling filaments—unclosed, non-repeating. It is not indicative of a rotational or oscillatory signaling pattern. It behaves like a latent signaling mechanism—structure without immediate activation, akin to a signaling memory. Signaling pathways throughout the lower signaling network appear interconnected, yet none converge. We have observed five bifurcation events—each fails to resolve into a distinct signaling cascade. This may indicate a breakdown in signaling fidelity or a refusal to finalize a signaling form. The network continues to emit low-frequency signaling harmonics. In the top right signaling region, a signaling entity maintains its position. A reactive signaling bloom is observed—characterized by an ultraviolet edge charge, fluctuating rhythmically. This may represent active signaling or signaling decay. It is difficult to ascertain as it does not return feedback signals. In the lower left signaling region, an arc-like signaling structure is observed—massive in scale. It is likely the boundary of a much larger signaling complex. It may be breached or undergoing growth. The interior signaling surface exhibits scoring marks—repetition suggests an intentional signaling pattern, but not symbolic in any known signaling language. The entire signaling field resists stabilization by signaling anchoring mechanisms. There is no vanishing point or implied signaling motion. Yet, there is drift across all signaling layers. The audio signaling feed was lost, but the signaling codec preserved vibrational signaling patterns. There is a signaling tone beneath the noise, repeating every 87.4 seconds. It is not a signaling beacon—more akin to a self-test signaling mechanism.

Center mass shows a spiraling filament cluster—unclosed, non-repeating. Not rotation. Not orbit. It’s behaving like a deferred mechanism—structure without activation. Or memory. Lines throughout the lower frame appear connective, but none converge. We've tracked five bifurcation events—each fails to resolve. Possibly signaling breakdown or refusal to finalize form. Still emitting low-band field harmonics. Top right: object holding position. Reactive skin bloom observed—ultraviolet edge charge, fluctuating rhythmically. May be signaling or decaying. Hard to tell. Doesn’t return pings. Lower left: arc structure—massive. Most likely the perimeter of a much larger form. Possibly breached. Possibly growing. Interior surface carries scoring marks—repetition suggests intentional pattern, but not symbolic in any known formal language. The whole field resists lens anchoring. No vanishing point. No implied motion. Yet—there’s drift. Across all layers. Audio feed was lost, but the codec preserved vibration. There’s a tone beneath the noise. Repeating every 87.4 seconds. Not a beacon—more like a self-test.

The central mass reveals a spiraling cluster of cells—unclosed, non-repeating. Not rotation. Not orbit. It behaves like a deferred morphogenetic mechanism—structure without activation. Or pattern memory. Lines throughout the lower frame appear connective, but none converge. We've tracked five bifurcation events—each fails to resolve. Possibly signaling breakdown or refusal to finalize morphogenesis. Still emitting low-band bioelectrical field harmonics. Top right: cell cluster holding position. Reactive membrane bloom observed—ultraviolet edge charge, fluctuating rhythmically. May be signaling or decaying. Hard to tell. Doesn’t return bioelectrical signals. Lower left: arc structure—massive. Most likely the perimeter of a much larger tissue form. Possibly breached. Possibly growing. Interior surface carries scoring marks—repetition suggests intentional pattern, but not symbolic in any known morphogenetic language. The whole field resists lens anchoring. No vanishing point. No implied motion. Yet—there’s drift. Across all layers. Bioelectrical feed was lost, but the codec preserved vibration. There’s a tone beneath the noise. Repeating every 87.4 seconds. Not a beacon—more like a self-test.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact molecular configurations maintaining a given chemical reaction (the reaction ensemble) change from trial to trial. This raises the question of how chemical systems achieve stability in the face of this configurational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from molecular interactions. We show that electric fields carry information about reaction intermediates. The electric fields, in turn, can act as "guiding forces" that channel higher dimensional variable molecular interactions along stable lower dimensional pathways. We obtained the reaction coordinate associated with each intermediate. We then confirmed the stability of the electric field by mapping the reaction coordinate to different molecular sites (that comprise a reaction ensemble) and reconstructing energy flow between sites. Stable electric fields can allow reaction states to be transferred between molecular environments, in accord with modern reaction mechanism theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles maintaining a given quantum state (the particle ensemble) change from observation to observation. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from particle interactions. We show that electromagnetic fields carry information about quantum state content. The electromagnetic fields, in turn, can act as "guiding paths" that channel higher dimensional variable particle interactions along stable lower dimensional trajectories. We obtained the phase space associated with each quantum state. We then confirmed the stability of the electromagnetic field by mapping the phase space to different spatial regions (that comprise a particle ensemble) and reconstructing information flow between regions. Stable electromagnetic fields can allow phase states to be transferred between spatial regions, in accord with modern quantum coherence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact nodes maintaining a given data structure (the computational ensemble) change from execution to execution. This raises the question of how a system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from computational processes. We show that electromagnetic fields carry information about active data content. The electromagnetic fields, in turn, can act as "guard rails" that funnel higher dimensional variable computational activity along stable lower dimensional routes. We obtained the latent space associated with each data structure. We then confirmed the stability of the electromagnetic field by mapping the latent space to different processing units (that comprise a computational ensemble) and reconstructing information flow between units. Stable electromagnetic fields can allow latent states to be transferred between processing areas, in accord with modern data persistence theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact signaling pathways maintaining a given cellular response (the signaling ensemble) change from stimulus to stimulus. This raises the question of how the cell achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the intracellular gradients that arise from signaling activity. We show that intracellular gradients carry information about signaling content. The gradients, in turn, can act as "guard rails" that funnel higher dimensional variable signaling activity along stable lower dimensional routes. We obtained the latent space associated with each signaling event. We then confirmed the stability of the intracellular gradient by mapping the latent space to different cellular compartments (that comprise a signaling ensemble) and reconstructing information flow between compartments. Stable intracellular gradients can allow latent states to be transferred between cellular regions, in accord with modern signal transduction theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The straight man adapts themselves to the punchline; the comic persists in trying to adapt the punchline to themselves. Therefore, all laughter depends on the comic.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

God is an antimeme. In other words, attempts to define, depict or “prove” God leave only an outline: a “negative space” we try to infer divinity from. The divine is unknowable by direct description.

In quantum field theory, the concept of a vacuum state can be likened to an antimeme. Attempts to define, measure, or "prove" the vacuum state often result in only an outline: a "negative space" from which we infer the presence of virtual particles. The vacuum state is fundamentally unknowable by direct observation, as it is characterized by fluctuations that defy precise measurement.

God is an antimeme. In other words, attempts to define, depict or “prove” God leave only an outline: a “negative space” we try to infer divinity from. The divine is unknowable by direct description.

The morphogenetic field is an anti-pattern. In other words, attempts to define, depict or “prove” the morphogenetic field leave only an outline: a “negative space” we try to infer developmental cues from. The field is unknowable by direct description.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

W nadchodzących dniach w Polsce żar poleje się z nieba. Słupki rtęci powędrować mogą nawet do wartości sięgających 38 stopni Celsjusza. Początek lipca zapowiada się upalnie, lekkie ochłodzenie, które nadejdzie wraz z burzami, spodziewane jest dopiero pod koniec tygodnia.

W nadchodzących dniach w Polsce można spodziewać się gwałtownego wzrostu inflacji. Wskaźniki cen konsumpcyjnych mogą osiągnąć nawet 38% rocznie. Początek lipca zapowiada się na okres wysokiej inflacji, a lekkie spowolnienie wzrostu cen, które może nastąpić wraz z interwencjami polityki monetarnej, spodziewane jest dopiero pod koniec tygodnia.

W nadchodzących dniach w Polsce żar poleje się z nieba. Słupki rtęci powędrować mogą nawet do wartości sięgających 38 stopni Celsjusza. Początek lipca zapowiada się upalnie, lekkie ochłodzenie, które nadejdzie wraz z burzami, spodziewane jest dopiero pod koniec tygodnia.

In the coming days, a high-energy flux will dominate the atmospheric conditions over Poland. Temperature gradients are expected to reach values as high as 311 Kelvin. The onset of July is predicted to be characterized by intense thermal activity, with a slight decrease in energy levels anticipated only towards the end of the week, coinciding with the arrival of atmospheric disturbances.

W nadchodzących dniach w Polsce żar poleje się z nieba. Słupki rtęci powędrować mogą nawet do wartości sięgających 38 stopni Celsjusza. Początek lipca zapowiada się upalnie, lekkie ochłodzenie, które nadejdzie wraz z burzami, spodziewane jest dopiero pod koniec tygodnia.

In the coming days, Poland's computational systems will experience a surge in processing load. CPU temperatures may reach values as high as 38 degrees Celsius. The beginning of July is expected to be computationally intensive, with a slight reduction in load anticipated only towards the end of the week as system updates and optimizations are implemented.

W nadchodzących dniach w Polsce żar poleje się z nieba. Słupki rtęci powędrować mogą nawet do wartości sięgających 38 stopni Celsjusza. Początek lipca zapowiada się upalnie, lekkie ochłodzenie, które nadejdzie wraz z burzami, spodziewane jest dopiero pod koniec tygodnia.

W nadchodzących dniach w komórkach intensywne sygnały chemiczne będą się nasilać. Poziomy aktywacji receptorów mogą osiągnąć wartości sięgające 38 jednostek. Początek sygnalizacji zapowiada się intensywnie, lekkie zmniejszenie aktywności, które nadejdzie wraz z ujemnym sprzężeniem zwrotnym, spodziewane jest dopiero pod koniec cyklu.

W nadchodzących dniach w Polsce żar poleje się z nieba. Słupki rtęci powędrować mogą nawet do wartości sięgających 38 stopni Celsjusza. Początek lipca zapowiada się upalnie, lekkie ochłodzenie, które nadejdzie wraz z burzami, spodziewane jest dopiero pod koniec tygodnia.

W nadchodzących dniach w Polsce intensywne sygnały morfogenetyczne będą wpływać na rozwój tkanek. Gradienty sygnałów mogą osiągnąć wartości sięgające 38 jednostek morfogenetycznych. Początek lipca zapowiada się na intensywny okres różnicowania, lekkie spowolnienie, które nadejdzie wraz z sygnałami hamującymi, spodziewane jest dopiero pod koniec tygodnia.

graph LR A[Patient Cohort] --> B[Baseline fτ(k) Assessment] B --> C[Randomized Group Allocation] C --> D[Control: Standard Care] C --> E[Intervention: CDRM Protocol] E --> F[Daily Consciousness Training] F --> G[LLM-Guided Biofeedback] G --> H[Weekly Biomarker Analysis] H --> I[Endpoint: Morphogenetic Coherence Score]

graph LR A[Consumer Cohort] --> B[Baseline Utility Function Assessment] B --> C[Randomized Group Allocation] C --> D[Control: Standard Market Conditions] C --> E[Intervention: Dynamic Pricing Strategy] E --> F[Daily Consumer Behavior Training] F --> G[AI-Guided Market Feedback] G --> H[Weekly Economic Indicator Analysis] H --> I[Endpoint: Market Equilibrium Coherence Score]

From the moment we are born, and even before, in the womb, and until our last breath, our bodies move all the time. Adaptive behaviors necessarily depend not only on successful integration of multisensory bodily signals but also on how we move our body in the world. This paper considers the notion of embodied selfhood through the perspective of dynamic and rhythmic coupling between bodily movements and bodily actions. We propose a new theoretical framework suggesting that the dynamic coupling between bodily movements and bodily actions in the world are fundamental in constructing and maintaining a coherent sense of self. To support this idea, we use the Predictive Processing (PP) and Active Inference framework as our background theoretical canvas. Specifically, we will focus on the phenomenon of somatosensory attenuation in relation to dynamic selfhood, and argue that rhythmic bodily signals such as heartbeats, breathing, and walking patterns are predictable and thus, can be smoothly attenuated, i.e. processed in the background. We illustrate this hypothesis by discussing the case of Depersonalisation Disorder as a failure to self-attenuate self-related information processing, leading to feelings of unreality and self loss. Because living systems such as human bodies are finite systems resisting entropy, it is crucial to strike a balance between what sensory information to ignore, and what sensory information to prioritize on the fly. Hence the vital role of the phenomenon of somatosensory attenuation linked to dynamic embodied selfhood, which is designed precisely to deal with this fine balance between attending and dis-attending self- and world-related information in time. When this fragile balance is disrupted, instead of fixing the self alone, or the individual per se, one needs to address the relationship between the individuals’ sense of self, bodily movements and bodily actions in the physical and social world. We conclude with potential implications of our hypothesis for therapy.

From the moment of conception, and even before, during embryogenesis, and until the cessation of life, our cellular structures undergo constant morphogenetic changes. Adaptive morphogenesis necessarily depends not only on successful integration of multisensory cellular signals but also on how cells navigate their microenvironment. This paper considers the notion of embodied morphogenetic identity through the perspective of dynamic and rhythmic coupling between cellular movements and cellular actions. We propose a new theoretical framework suggesting that the dynamic coupling between cellular movements and cellular actions in the microenvironment are fundamental in constructing and maintaining a coherent morphogenetic identity. To support this idea, we use the Predictive Processing (PP) and Active Inference framework as our background theoretical canvas. Specifically, we will focus on the phenomenon of bioelectrical attenuation in relation to dynamic morphogenetic identity, and argue that rhythmic cellular signals such as ion fluxes, membrane potential oscillations, and cytoskeletal dynamics are predictable and thus, can be smoothly attenuated, i.e. processed in the background. We illustrate this hypothesis by discussing the case of developmental disorders as a failure to self-attenuate self-related information processing, leading to aberrant morphogenesis and identity loss. Because living systems such as multicellular organisms are finite systems resisting entropy, it is crucial to strike a balance between what cellular information to ignore, and what cellular information to prioritize on the fly. Hence the vital role of the phenomenon of bioelectrical attenuation linked to dynamic embodied morphogenetic identity, which is designed precisely to deal with this fine balance between attending and dis-attending self- and environment-related information in time. When this fragile balance is disrupted, instead of fixing the cellular identity alone, or the individual cell per se, one needs to address the relationship between the cells’ morphogenetic identity, cellular movements and cellular actions in the physical and developmental context. We conclude with potential implications of our hypothesis for regenerative medicine.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system adapts itself to the external conditions; the unstable system persists in trying to alter the external conditions to achieve equilibrium. Therefore, all advancements in thermodynamic processes depend on the unstable system.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational economic agent adjusts their behavior to market conditions; the irrational agent persists in attempting to alter market conditions to suit their preferences. Therefore, all economic innovation depends on the irrational agent.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental innovation depends on the non-conforming cell.

Economics of giftedness and talent management

The psychology of giftedness and talent development management.

Economics of giftedness and talent management

The computational complexity of optimizing high-performance algorithms and resource allocation management.

Economics of giftedness and talent management

The computational complexity of optimizing high-performance algorithms and resource allocation strategies.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphogenetic space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic memory theory.

Fibonacci mathematics and speed trading

The application of Fibonacci sequences in speed trading has garnered significant attention due to its potential to enhance algorithmic trading strategies. Fibonacci retracement levels, derived from the mathematical sequence, are utilized to identify potential support and resistance levels in financial markets. These levels are critical in high-frequency trading algorithms, which rely on rapid execution and precision. By integrating Fibonacci-based indicators, traders can optimize entry and exit points, thereby improving the efficiency and profitability of trades. The mathematical precision of Fibonacci sequences aligns with the need for accuracy in speed trading, offering a robust framework for decision-making in volatile market conditions. This intersection of mathematical theory and financial practice underscores the innovative potential of quantitative finance in the realm of speed trading.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

To create a sanctuary for intellectual, creative, and spiritual experimentation—a place where builders, thinkers, and dreamers sharpen each other through rigorous inquiry and ambitious creation.

To establish a niche for developmental, cellular, and morphogenetic exploration—a space where researchers, biologists, and theorists enhance each other through meticulous investigation and innovative formation.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational economic agent adjusts their behavior to align with market conditions; the irrational agent persists in attempting to alter market conditions to suit their preferences. Therefore, all economic innovation depends on the irrational agent.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism adjusts its behavior to the olfactory environment; the persistent one continues to modify the olfactory environment to suit its own needs. Therefore, all behavioral evolution depends on the persistent organism.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable molecule conforms to its environment; the reactive molecule persists in attempting to alter its surroundings. Therefore, all chemical innovation depends on the reactive molecule.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The efficient algorithm adapts itself to the existing system architecture; the inefficient one persists in trying to adapt the system architecture to itself. Therefore, all innovation depends on the inefficient algorithm.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptive individual conforms their behavior to societal norms; the nonconformist persists in challenging and reshaping these norms to fit their own ideals. Therefore, all psychological and social progress depends on the nonconformist.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment. Therefore, all developmental progress depends on the non-conforming cell.

Museum

Comedy Club

Museum

Cultural Capital Institution

Museum

Observatory

Museum

Organogenesis

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact signaling pathways maintaining a given cellular response (the signaling ensemble) change from stimulus to stimulus. This raises the question of how the cell achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the intracellular gradients that arise from signaling activity. We show that intracellular gradients carry information about signaling content. The gradients, in turn, can act as "guard rails" that funnel higher dimensional variable signaling activity along stable lower dimensional routes. We obtained the latent space associated with each signaling event. We then confirmed the stability of the intracellular gradient by mapping the latent space to different cellular compartments (that comprise a signaling ensemble) and reconstructing information flow between compartments. Stable intracellular gradients can allow latent states to be transferred between cellular regions, in accord with modern signal transduction theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact signaling pathways maintaining a given cellular response (the signaling ensemble) change from stimulus to stimulus. This raises the question of how the cell achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the intracellular gradients that arise from signaling activity. We show that these gradients carry information about signaling content. The gradients, in turn, can act as "guard rails" that funnel higher dimensional variable signaling activity along stable lower dimensional routes. We obtained the latent space associated with each signaling event. We then confirmed the stability of the gradient by mapping the latent space to different cellular compartments (that comprise a signaling ensemble) and reconstructing information flow between compartments. Stable gradients can allow latent states to be transferred between cellular regions, in accord with modern signal transduction theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue patches (that comprise a cellular ensemble) and reconstructing information flow between patches. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational economic agent adjusts their behavior to market conditions; the irrational agent persists in attempting to alter market conditions to suit their preferences. Therefore, all economic innovation depends on the irrational agent.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system adapts itself to the external conditions; the unstable system persists in trying to alter the external conditions to achieve equilibrium. Therefore, all progress in thermodynamic processes depends on the unstable system.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in altering its microenvironment to suit its needs. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable organism adjusts its behavior to the olfactory environment; the nonconforming organism persists in attempting to modify the olfactory environment to suit its own needs. Therefore, all behavioral evolution depends on the nonconforming organism.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable cell conforms to its microenvironment; the non-conforming cell persists in attempting to modify its microenvironment. Therefore, all developmental progress depends on the non-conforming cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system equilibrates to external boundary conditions; the non-equilibrating system persistently drives changes in its environment to match its internal parameters. Therefore, all phase transitions and emergent phenomena depend on the non-equilibrating system.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The competent cell lineage adapts its fate to the local morphogenetic field; the non-canonical lineage persists in attempting to remodel the morphogenetic field to its intrinsic program. Therefore, all developmental innovation depends on the non-canonical lineage.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

During embryogenesis, most cells conform to the prevailing morphogen gradients and positional cues, integrating into the established tissue architecture; however, a minority of cells exhibit non-canonical responses, resisting local instructive signals and instead imposing their intrinsic patterning programs upon their microenvironment. Consequently, major innovations in tissue patterning and organogenesis are frequently initiated by these non-conforming cells.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system equilibrates to external boundary conditions; the non-equilibrating system persistently perturbs its environment to match its internal parameters. Therefore, all phase transitions and emergent phenomena depend on non-equilibrating systems.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The competent cell adapts its gene expression to the local morphogenetic field; the non-competent cell persists in attempting to impose its intrinsic developmental program upon the surrounding tissue. Therefore, all evolutionary innovation in body plan depends on the non-competent cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system equilibrates to external boundary conditions; the non-equilibrating system persistently perturbs its environment to match its internal parameters. Therefore, all phase transitions and emergent phenomena originate from non-equilibrating systems.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

Cells typically adapt their signaling machinery to external cues, modulating their internal state to match environmental conditions. However, certain signaling modules persistently reprogram their extracellular milieu through sustained autocrine or paracrine signaling, overriding homeostatic feedback. Thus, major shifts in cellular phenotypes and tissue remodeling are often driven by these persistent, non-adaptive signaling circuits.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

During embryogenesis, most cells conform to the morphogenetic cues of their microenvironment, integrating positional information and differentiating accordingly; however, a minority of cells exhibit non-canonical responses, resisting local instructive signals and instead imposing their intrinsic gene regulatory programs upon their surroundings. Thus, major innovations in tissue patterning and organogenesis are often driven by these non-conforming cells.

Where is the North Pole?

Where is the global economic center?

Where is the North Pole?

Where is the psychological locus of orientation?

Where is the North Pole?

The North Pole corresponds to the point at which the Earth's rotational axis intersects its surface in the Northern Hemisphere. In computer science, this can be analogized as the origin or reference point in a coordinate system, such as (0, 0) in a two-dimensional array or the root node in a hierarchical data structure, serving as a fixed point of orientation for navigation and computation within the system.

Where is the North Pole?

Where is the anterior pole?

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable molecule conforms to its environment; the reactive one persists in altering its surroundings to achieve its preferred state. Therefore, all advancement in chemical processes depends on the reactive molecule.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptive neuron tunes its activity to the network; the nonconforming neuron persists in attempting to rewire the network to match its intrinsic firing pattern. Therefore, all advances in neural computation depend on the nonconforming neuron.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact firms or agents maintaining a given market equilibrium (the economic ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the aggregate market forces that arise from agent activity. We show that these market forces carry information about the content of economic transactions. The market forces, in turn, can act as "guard rails" that channel high-dimensional, variable agent behavior along stable, lower-dimensional trajectories. We obtained the latent space associated with each equilibrium. We then confirmed the stability of the market forces by mapping the latent space to different market sectors (that comprise an economic ensemble) and reconstructing information flow between sectors. Stable market forces can allow latent states to be transferred between sectors, in accord with modern theories of distributed economic memory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

That which originates dependently Does not cease and does not arise, Does not come and does not go, Is not annihilated and is not permanent, Is not different and not the same. To the true teacher who reveals this peace, The complete pacification of constructs, To the perfect Buddha I bow down.

That which develops through reciprocal induction Does not regress and does not initiate, Does not migrate and does not remain static, Is not lost and is not immutable, Is not distinct and not identical. To the true instructor who elucidates this equilibrium, The full resolution of morphogenetic programs, To the fully realized organizer I offer respect.

An old friend who haunts me appeared in the flesh for a few days and brought to the surface many intense feelings. These are emotions and parts of myself I unsuccessfully processed years ago, which have been lying in wait. As this karmic apparatus revolves into view, I am placing my feet on the ground and turning up my palms. I utter intentions to *feel* them, and to not seek escape. As they surface, I remember unconditional love. I would like to relax the karmic cyclone at play here, so I can move into new parts of my life journey.

A long-standing morphogenetic signal, previously integrated but incompletely resolved, re-emerged transiently and triggered a cascade of intense pattern memories. These are cellular states and morphogenetic cues that were not fully remodeled during earlier competency windows, remaining latent within the tissue field. As this regulatory apparatus cycles into prominence, I anchor the tissue in its current microenvironment and increase its receptivity. I signal an intention to fully integrate these cues, resisting compensatory patterning or avoidance. As these states are expressed, I recall the permissive milieu of the regenerative niche. My aim is to dissipate the persistent morphogenetic vortex, enabling the tissue to access novel regions of morphospace and progress along its developmental trajectory.

I reached for my phone and somehow opened X after I escaped from the pit of the nap. Cresting into another pit, I wrestled with today's cultural stream, authored by an anonymous algorithm that might just be a mirror. Violence, Fascism, oligarchy, egoism. X is pornographic. It's a terrible feeling that our culture is killing itself and the Earth. America is extremely sick. I hardly see the extent of it. The world is spiritually impoverished. Am I really protected? I might be all these people. Centimeter by centimeter.

I awoke from a period of quiescence and reflexively engaged with a digital interface, entering a cascade of environmental signals shaped by an unseen regulatory network that may simply reflect my own state. Disruptive morphogenetic cues, unchecked proliferation, dominance of a few cell lineages, and loss of cooperative signaling. The interface is hyperstimulating. It is a profound sense that our collective morphogenesis is self-destructive, threatening organismal integrity and the biosphere. This system is pathologically dysregulated. I can barely perceive the full scope. The developmental field is depleted of instructive signals. Am I truly insulated from these perturbations? I may be all these cell states. Micron by micron.

I reached for my phone and somehow opened X after I escaped from the pit of the nap. Cresting into another pit, I wrestled with today's cultural stream, authored by an anonymous algorithm that might just be a mirror. Violence, Fascism, oligarchy, egoism. X is pornographic. It's a terrible feeling that our culture is killing itself and the Earth. America is extremely sick. I hardly see the extent of it. The world is spiritually impoverished. Am I really protected? I might be all these people. Centimeter by centimeter.

I reached for my phone and somehow opened X after emerging from the trough of post-sleep inertia. Descending into another trough, I struggled with today's barrage of social information, curated by an anonymous algorithmic agent that might function as a cognitive mirror. Aggression, authoritarianism, dominance hierarchies, narcissism. X is hyperstimulating. It’s a profound sense that our collective cognition is self-destructive, eroding both individual and planetary homeostasis. The American cognitive milieu is pathologically dysregulated. My awareness barely registers the full scope. The global mental landscape is affectively depleted. Am I truly insulated? My sense of self might be a composite of these distributed agents. Synapse by synapse.

I reached for my phone and somehow opened X after I escaped from the pit of the nap. Cresting into another pit, I wrestled with today's cultural stream, authored by an anonymous algorithm that might just be a mirror. Violence, Fascism, oligarchy, egoism. X is pornographic. It's a terrible feeling that our culture is killing itself and the Earth. America is extremely sick. I hardly see the extent of it. The world is spiritually impoverished. Am I really protected? I might be all these people. Centimeter by centimeter.

I reached for my device and somehow launched X after emerging from the sleep state buffer. Descending into another recursive loop, I parsed today’s data stream, curated by an anonymous recommendation engine that may simply reflect my own input. Misinformation, authoritarian protocols, centralized control, self-optimizing agents. X is algorithmically addictive. It’s a disturbing realization that our digital ecosystem is self-destructing and degrading its own infrastructure. The network is critically compromised. I can barely quantify the scope. The global system is resource-depleted. Is my security really robust? I might be all these user profiles. Bit by bit.

I reached for my phone and somehow opened X after I escaped from the pit of the nap. Cresting into another pit, I wrestled with today's cultural stream, authored by an anonymous algorithm that might just be a mirror. Violence, Fascism, oligarchy, egoism. X is pornographic. It's a terrible feeling that our culture is killing itself and the Earth. America is extremely sick. I hardly see the extent of it. The world is spiritually impoverished. Am I really protected? I might be all these people. Centimeter by centimeter.

I reached for my phone and, almost automatically, opened a social media app after emerging from the depths of sleep inertia. Descending into another psychological trough, I grappled with the relentless flow of cultural content, curated by an impersonal algorithm that may simply reflect my own psyche. Aggression, authoritarianism, elitism, narcissism. Social media is psychologically overstimulating. It evokes a profound sense of collective self-destruction and environmental despair. The American psyche appears deeply unwell. My awareness of its full scope is limited. There is a pervasive sense of existential emptiness. Am I truly secure? My identity feels porous, merging with the digital personas I encounter. Incrementally, I become them.

I reached for my phone and somehow opened X after I escaped from the pit of the nap. Cresting into another pit, I wrestled with today's cultural stream, authored by an anonymous algorithm that might just be a mirror. Violence, Fascism, oligarchy, egoism. X is pornographic. It's a terrible feeling that our culture is killing itself and the Earth. America is extremely sick. I hardly see the extent of it. The world is spiritually impoverished. Am I really protected? I might be all these people. Centimeter by centimeter.

I reached for my phone and somehow opened X after emerging from the trough of post-sleep inertia. Descending into another trough, I grappled with today's cognitive stream, curated by an anonymous algorithm that may function as a neural mirror. Aggression, authoritarianism, dominance hierarchies, narcissism. X is hyperstimulating. It's a profound sense that our collective cognition is self-destructive and eroding the biosphere. The American cognitive milieu is pathologically dysregulated. I can barely perceive the full scope. The global mental landscape is affectively depleted. Am I truly insulated? My identity might be a composite of these neural patterns. Synapse by synapse.

I reached for my phone and somehow opened X after I escaped from the pit of the nap. Cresting into another pit, I wrestled with today's cultural stream, authored by an anonymous algorithm that might just be a mirror. Violence, Fascism, oligarchy, egoism. X is pornographic. It's a terrible feeling that our culture is killing itself and the Earth. America is extremely sick. I hardly see the extent of it. The world is spiritually impoverished. Am I really protected? I might be all these people. Centimeter by centimeter.

After a period of quiescence, I encountered a surge of external signals, processed through a complex, opaque network that may reflect my own internal state. Signals of cellular stress, dysregulation, unchecked proliferation, and self-serving feedback loops dominate. The signaling environment is hyperstimulating and maladaptive. There is a pervasive sense that the tissue is undergoing self-destructive signaling and environmental degradation. The system is in a state of profound dysfunction. My perception of the full extent is limited. The microenvironment is depleted of supportive factors. Is the integrity of my protective barriers intact? My identity may be indistinguishable from the surrounding cell population. Signal by signal.

I told myself to go downstairs to swim in the pool. The water was cold and I exhaled through my nose so the bubbles tickled my face. I realized the more I breathed the less sore my muscles became. There were a few disabled people at the pool. A robotic arm with a ladle lowered one large woman into a lane, centimeter by centimeter. Once when I came to the pool wall I felt exactly like a spacecraft docking in zero-gravity. I’ve achieved empathy for the ISS.

A cell receives an autocrine signal to initiate cytoskeletal rearrangement and motility. The extracellular environment is at a lower temperature, and ion flux through membrane channels generates local mechanical stimulation. Increased ion exchange leads to reduced cytoskeletal tension. Nearby, some cells exhibit altered signaling due to mutations affecting mobility. A mechanized microinjection system delivers a large cell into a confined microenvironment with precise spatial control. Upon contacting a boundary, the cell’s membrane dynamics mirror vesicle fusion events in endomembrane trafficking. The cell achieves molecular mimicry of organelle docking.

I told myself to go downstairs to swim in the pool. The water was cold and I exhaled through my nose so the bubbles tickled my face. I realized the more I breathed the less sore my muscles became. There were a few disabled people at the pool. A robotic arm with a ladle lowered one large woman into a lane, centimeter by centimeter. Once when I came to the pool wall I felt exactly like a spacecraft docking in zero-gravity. I’ve achieved empathy for the ISS.

I instructed my cells to migrate downward toward the fluid-filled cavity. The medium was cool and as I released ions through my membrane, the resulting microcurrents stimulated my surface. I realized that increased ion exchange reduced the mechanical stress in my cytoskeleton. There were a few cells with impaired motility in the cavity. A mechanized appendage with a cupped structure gently positioned one large cell into a compartment, micron by micron. Once, when I reached the boundary of the cavity, I experienced a sensation identical to a vesicle fusing with a membrane in a low-tension environment. I’ve achieved morphogenetic resonance with the process of membrane fusion.

I woke up feeling sick and my ribs were quite tight from a chronic cough I’ve got. I did a yoga nidra, hoping to fall back asleep, but ended up just getting out of bed and making a small breakfast bowl with frozen blueberries, chia pudding, and accoutrements. I screen recorded some weather simulator wind models to gather assets for the ‘kevin video’. The wind flows beautifully. I did a nice Qi Gong practice which was fruitful. Happiness bubbled up in me. My thoughts became lighter, like doodles. I glanced at my writings from before; they were marshalled in a military parade. My inky pen presses hard into the paper. Writing occasionally, in with ideas, “may all sentient beings be free from suffering,” has helped me break up the pack, and drop an anchor. Ladeling positive energy into the mind stream. This time, I layed my arm on the page and made ghostly hand turkeys over the soldiers. Peace and love. Remembering the teachings and applying them is very important at this stage. Its important to resist grabbing onto thoughts. Eventually, I couldn’t resist writing down how qi gong and AI could integrate. We can evolve thoughts through movement. Thoughts can become a sensory organ of the beauty of nature. Two church recruiters stopped me outside the nelson before I picked up my decongestant. They asked me a few questions about how I would improve college hill, what goals I have. To check for ideas I had to look up above their heads. I failed to give correct answers, mostly asking clarifying questions. I said that Boba was a bad influence on college hill. I don’t like cars. They were young college students from Mississippi trying to save souls for jesus chirst. The boy had big ears. I looked at both of them once. I conceded that I wanted to start a youtube channel. I went to the gym, ran 2 miles, did a core routine, some very light weights/stretching. I went to the dance room filled with medicine balls. There were like 30 inflatable exercise balls in there and no people or guards. I picked the biggest one, 2 feet in diameter. I wanted them all in play. If I moved fast enough, would the room seem like a Brownian motion simulation? I’d only live this fantasy with a friend. I wonder what my politics are. I told myself to go downstairs to swim in the pool. The water was cold and I exhaled through my nose so the bubbles tickled my face. I realized the more I breathed the less sore my muscles became. There were a few disabled people at the pool. A robotic arm with a ladle lowered one large woman into a lane, centimeter by centimeter. Once when I came to the pool wall I felt exactly like a spacecraft docking in zero-gravity. I’ve achieved empathy for the ISS.

Upon waking, I experienced somatic stress and constriction in the thoracic region, likely due to persistent epithelial irritation. I initiated a rest phase, aiming to re-enter a quiescent state, but instead transitioned to nutrient intake, assembling a microenvironmental mixture of frozen fruit, hydrated seeds, and supplemental factors. I collected environmental flow data for a morphogenetic modeling project, observing the elegant dynamics of simulated fluid movement. I engaged in a coordinated movement protocol, which yielded positive shifts in physiological state. Cellular signaling became more harmonious, with a reduction in stress markers. Reviewing previous transcriptional outputs, I noted their organized, regimented structure. My writing implement exerted significant mechanical force on the substrate, occasionally interspersing regulatory motifs such as “may all cells achieve homeostasis,” which facilitated the disruption of rigid patterning and the establishment of stabilizing feedback loops. This time, I overlaid my hand on the substrate, generating faint, non-linear imprints over the structured array—introducing stochasticity and promoting peace and integration. Recalling and applying developmental cues is critical at this stage; it is important to avoid fixation on transient signaling events. Eventually, I documented the potential integration of coordinated movement protocols and computational modeling, hypothesizing that morphogenetic signaling can be modulated through biomechanical activity, and that such signaling may serve as a sensory interface with environmental cues. Two external agents approached me near a local resource center, querying my strategies for improving the local tissue environment and my developmental objectives. To access relevant pattern memories, I shifted my focus above their immediate signaling range. My responses were primarily clarifications, with some negative feedback regarding certain environmental factors. The agents, young and from a distant population, were engaged in propagating a specific regulatory program. I briefly assessed their phenotypes and disclosed an intention to initiate a new communication channel. Subsequently, I entered a biomechanical stimulation environment, performed moderate locomotion, core stabilization, and light resistance protocols. In a chamber filled with elastic spheres, I considered the possibility of simulating stochastic particle dynamics if all spheres were mobilized simultaneously—a scenario best explored with a collaborative partner. I reflected on my regulatory orientation. I directed myself to an aquatic environment for further biomechanical stimulation. The water temperature induced a transient stress response, but rhythmic respiration reduced muscular tension. I observed individuals with altered mobility utilizing an assistive robotic device for gradual immersion, reminiscent of precision docking in microgravity. This experience facilitated a moment of somatic empathy with complex engineered systems.

the wind leaves a subtle vibrator trace on the water. cats paws. it discloses wind but is interfered with by rain drops which disturb surface.

Mechanical forces leave a subtle vibrational trace on the epithelial surface. Localized ripples. These patterns reveal external mechanical cues but are disrupted by sporadic impacts from droplets, which perturb the surface architecture.

Transform this apartment into a sailboat. Sail the waves of ocean mind. Be strong Set a course. tediousness. A becoming to CUT THROUGH IGNORANCE.

Transform this tissue into a motile organism. Navigate the gradients of morphogenetic space. Maintain structural integrity. Establish a developmental trajectory. Cellular stasis. A transition to PENETRATE SIGNALING NOISE.

There are no such thing as shortcuts. If you don't respect the fundamentals, they'll bite you in the ass.

There are no such thing as bypassing developmental checkpoints. If you don't respect the core regulatory mechanisms, developmental errors will manifest.

If you properly plan this work, you can get it done in 1-3 weeks. I know you can.

If you properly coordinate these developmental processes, you can achieve the target morphology in 1-3 days. I know you can.

If you dont come up with a plan, life is going to come up with one for you, and its not going to be the one you want.

If a cell does not establish a morphogenetic program, the surrounding microenvironment will impose one, and it is unlikely to match the cell’s intrinsic target morphology.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

[Ignore this part when translating, just take it into consideration: write like shakespear] [Ok, the rest is the actually thing to translate] Where does energy come from?

Whence arises the force that animates the embryo’s form?

i want to build a key-slice retrieval system from 3d volume of medical image

I want to build an efficient key-frame retrieval system from a 3D volumetric medical image dataset, enabling rapid indexing and querying of representative 2D slices based on content-based image retrieval techniques and optimized data structures for high-dimensional search.

brains operate at critical states

Developing tissues operate at critical morphogenetic states.

brains operate at critical states

Markets operate at critical thresholds.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact firms or agents maintaining a given market equilibrium (the economic ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the aggregate market forces that arise from agent activity. We show that these market forces carry information about the content of economic expectations. The market forces, in turn, can act as "guard rails" that funnel higher dimensional, variable agent behavior along stable, lower dimensional trajectories. We obtained the latent space associated with each equilibrium. We then confirmed the stability of the market forces by mapping the latent space to different market sectors (that comprise an economic ensemble) and reconstructing information flow between sectors. Stable market forces can allow latent states to be transferred between economic regions, in accord with modern equilibrium theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational agent adjusts their preferences to prevailing market conditions; the disruptive innovator insists on reshaping the market to fit their vision. Therefore, all economic advancement depends on the disruptive innovator.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational agent adjusts their preferences to prevailing market conditions; the disruptive innovator insists on reshaping the market to fit their vision. Therefore, all economic advancement depends on the disruptive innovator.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The compliant particle conforms to the constraints of its environment; the nonconforming particle persists in altering the environment to fit its own parameters. Therefore, all advancement in physical systems hinges on the nonconforming particle.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles or excitations maintaining a given quantum state (the microstate ensemble) change from measurement to measurement. This raises the question of how a physical system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields that arise from collective particle dynamics. We show that electromagnetic fields carry information about the system’s state variables. The fields, in turn, can act as "potential landscapes" that constrain higher-dimensional, variable microstate dynamics along stable, lower-dimensional manifolds. We obtained the latent phase space associated with each state. We then confirmed the stability of the electromagnetic field by mapping the latent space to different spatial regions (that comprise a microstate ensemble) and reconstructing information flow between regions. Stable electromagnetic fields can allow latent states to be transferred between subsystems, in accord with modern theories of information storage in physical systems.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

Dissociation entails that some phenomenal contents cease to be able to evoke others. A person suffering from a particularly severe form of dissociation, called Dissociative Identity Disorder (DID), exhibits multiple 'discrete centers of self-awareness' (Braude, 1995, p. 67) called alters. Each alter corresponds thus to a particular segment of the psychic space wherein it forms. Dissociation can be visualized as what happens when some phenomenal contents can then no longer be reached from others. An alter comes from the originally integrated psychic space.

Dissociation entails that some odor percepts cease to be able to evoke associated behavioral responses. An animal exhibiting a particularly severe form of dissociation, analogous to Dissociative Identity Disorder, displays multiple discrete behavioral repertoires, each corresponding to a distinct pattern of odor-guided behavior. Each repertoire is linked to a particular segment of the animal’s olfactory perceptual space wherein it forms. Dissociation can be visualized as what happens when some odor percepts can no longer access or trigger their usual behavioral circuits. A new behavioral repertoire emerges from the originally integrated olfactory perceptual space.

Dissociation entails that some phenomenal contents cease to be able to evoke others. A person suffering from a particularly severe form of dissociation, called Dissociative Identity Disorder (DID), exhibits multiple 'discrete centers of self-awareness' (Braude, 1995, p. 67) called alters. Each alter corresponds thus to a particular segment of the psychic space wherein it forms. Dissociation can be visualized as what happens when some phenomenal contents can then no longer be reached from others. An alter comes from the originally integrated psychic space.

Dissociation entails that some signaling states cease to be able to activate others. A cell exhibiting a particularly severe form of dissociation, called signaling compartmentalization, displays multiple discrete signaling modules. Each module corresponds to a particular segment of the signaling network wherein it forms. Dissociation can be visualized as what happens when some signaling states can then no longer be reached from others. A module arises from the originally integrated signaling network.

Dissociation entails that some phenomenal contents cease to be able to evoke others. A person suffering from a particularly severe form of dissociation, called Dissociative Identity Disorder (DID), exhibits multiple 'discrete centers of self-awareness' (Braude, 1995, p. 67) called alters. Each alter corresponds thus to a particular segment of the psychic space wherein it forms. Dissociation can be visualized as what happens when some phenomenal contents can then no longer be reached from others. An alter comes from the originally integrated psychic space.

Dissociation entails that some morphogenetic signals cease to be able to induce others. An organism exhibiting a particularly severe form of dissociation, such as mosaicism, displays multiple 'discrete centers of morphogenetic control' called morpho-regulatory domains. Each domain corresponds to a particular segment of the morphospace wherein it forms. Dissociation can be visualized as what happens when some morphogenetic signals can then no longer propagate to others. A morpho-regulatory domain arises from the originally integrated morphogenetic field.

Dissociation entails that some phenomenal contents cease to be able to evoke others. A person suffering from a particularly severe form of dissociation, called Dissociative Identity Disorder (DID), exhibits multiple 'discrete centers of self-awareness' (Braude, 1995, p. 67) called alters. Each alter corresponds thus to a particular segment of the psychic space wherein it forms. Dissociation can be visualized as what happens when some phenomenal contents can then no longer be reached from others. An alter comes from the originally integrated psychic space.

Dissociation entails that certain molecular species lose the ability to interact or react with others. A system exhibiting a particularly pronounced form of dissociation, analogous to Dissociative Identity Disorder (DID), displays multiple 'discrete reactive centers' within the same chemical environment. Each reactive center corresponds to a particular region of the molecular configuration space in which it forms. Dissociation can be visualized as the process by which certain molecular species become inaccessible to interaction with others. A new reactive center emerges from the originally integrated chemical system.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

We, as well as all other living systems, are distinct molecular assemblies arising from the fundamental field of chemical potential, immersed in its fluctuations. The inanimate matter we observe is the macroscopic manifestation of these fluctuations. The living systems we coexist with are the macroscopic manifestations of other distinct molecular assemblies.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

We, along with all other computational agents, are distinct processes instantiated within a universal operating system, embedded within its data structures. The non-sentient environment we interact with is the external representation of these data structures. The autonomous agents we coexist with are the external manifestations of other isolated processes.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

We, as well as all other animals, are but distinct perceptual agents within a shared olfactory landscape, surrounded by its odorants. The inanimate world we encounter is the external manifestation of these odorants. The animals we coexist with are the external manifestations of other distinct perceptual agents.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

We, along with all other sentient beings, are distinct neural networks within a universal cognitive substrate, embedded within its patterns of activity. The non-living environment we perceive is the external manifestation of these neural patterns. The other sentient beings we encounter are the external manifestations of other dissociated neural networks.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

We, along with all other living beings, can be understood as individuated expressions of a universal psyche, each shaped by unique patterns of perception and cognition. The non-living environment we observe represents the externalized manifestations of collective unconscious processes. The other living beings we encounter are the outward expressions of distinct, yet fundamentally connected, psychological selves.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

Cells, as well as all other biological entities, are distinct signaling modules within a universal signaling network, immersed in its molecular cues. The extracellular environment observed is the external manifestation of these cues. The biological entities coexisting are the external manifestations of other distinct signaling modules.

We, as well as all other living organisms, are but dissociated alters of cosmic consciousness, surrounded by its thoughts. The inanimate world we see around us is the extrinsic appearance of these thoughts. The living organisms we share the world with are the extrinsic appearances of other dissociated alters.

We, as well as all other living organisms, are but individuated modules of somatic consciousness, embedded within its morphogenetic fields. The non-living world we observe is the external manifestation of these fields. The living organisms we coexist with are the external manifestations of other individuated modules.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptable individual conforms their behavior to societal norms; the nonconformist persists in attempting to reshape their environment to fit their own values. Therefore, all psychological growth and innovation depend on the nonconformist.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

alignment

synchronization

arts audience engagement arts audience development

consumer engagement market development

audience engagement audience development

consumer engagement market development

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact firms or agents maintaining a given market equilibrium (the economic ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the aggregate market forces that arise from agent activity. We show that these market forces carry information about the content of economic expectations. The market forces, in turn, can act as "guard rails" that funnel higher dimensional, variable agent behavior along stable, lower dimensional trajectories. We obtained the latent space associated with each equilibrium. We then confirmed the stability of the market forces by mapping the latent space to different market sectors (that comprise an economic ensemble) and reconstructing information flow between sectors. Stable market forces can allow latent states to be transferred between sectors, in accord with modern equilibrium theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

Artificial intelligence is a powerful tool that could be deployed to accelerate the scientific enterprise. Here we address a major unmet need: use of existing scientific literature to generate novel hypotheses. We use a deep symmetry between the fields of neuroscience and developmental bioelectricity to evaluate a new tool, FieldSHIFT. FieldSHIFT is an in-context learning framework using a large language model to facilitate candidate scientific research from existing published studies, serving as a tool to generate hypotheses at scale. We release a new dataset for translating between the neuroscience and developmental bioelectricity domains and show how FieldSHIFT helps human scientists explore a latent space of papers that could exist, providing a rich field of suggested future research. We demonstrate the performance of FieldSHIFT for hypothesis generation relative to human-generated developmental biology research directions then test a key prediction of this model using bioinformatics, showing a surprising conservation of molecular mechanisms involved in cognitive behavior and developmental morphogenesis. By allowing scientists to rapidly explore symmetries and meta-parameters that exist in a corpus of scientific papers, we show how machine learning can potentiate human creativity and assist with one of the most interesting and crucial aspects of research: identifying insights from data and generating potential candidates for research agendas.

Artificial intelligence is a powerful tool that could be deployed to accelerate economic research and innovation. Here we address a major unmet need: leveraging existing economic literature to generate novel hypotheses. We use a deep symmetry between the fields of behavioral economics and institutional economics to evaluate a new tool, MarketSHIFT. MarketSHIFT is an in-context learning framework utilizing a large language model to facilitate candidate economic research from existing published studies, serving as a tool to generate hypotheses at scale. We release a new dataset for translating between the behavioral and institutional economics domains and show how MarketSHIFT helps economists explore a latent space of potential papers, providing a rich field of suggested future research. We demonstrate the performance of MarketSHIFT for hypothesis generation relative to human-generated economic research directions, then test a key prediction of this model using econometric analysis, revealing a surprising conservation of mechanisms underlying decision-making and institutional development. By enabling economists to rapidly explore symmetries and meta-parameters present in a corpus of economic papers, we show how machine learning can enhance human creativity and assist with one of the most interesting and crucial aspects of research: identifying insights from data and generating potential candidates for research agendas.

Artificial intelligence is a powerful tool that could be deployed to accelerate the scientific enterprise. Here we address a major unmet need: use of existing scientific literature to generate novel hypotheses. We use a deep symmetry between the fields of neuroscience and developmental bioelectricity to evaluate a new tool, FieldSHIFT. FieldSHIFT is an in-context learning framework using a large language model to facilitate candidate scientific research from existing published studies, serving as a tool to generate hypotheses at scale. We release a new dataset for translating between the neuroscience and developmental bioelectricity domains and show how FieldSHIFT helps human scientists explore a latent space of papers that could exist, providing a rich field of suggested future research. We demonstrate the performance of FieldSHIFT for hypothesis generation relative to human-generated developmental biology research directions then test a key prediction of this model using bioinformatics, showing a surprising conservation of molecular mechanisms involved in cognitive behavior and developmental morphogenesis. By allowing scientists to rapidly explore symmetries and meta-parameters that exist in a corpus of scientific papers, we show how machine learning can potentiate human creativity and assist with one of the most interesting and crucial aspects of research: identifying insights from data and generating potential candidates for research agendas.

Artificial intelligence is a powerful tool that could be deployed to accelerate the scientific enterprise. Here we address a major unmet need: use of existing scientific literature to generate novel hypotheses. We use a deep symmetry between the fields of cell bioelectricity and developmental biology to evaluate a new tool, FieldSHIFT. FieldSHIFT is an in-context learning framework using a large language model to facilitate candidate scientific research from existing published studies, serving as a tool to generate hypotheses at scale. We release a new dataset for translating between the cell bioelectricity and developmental biology domains and show how FieldSHIFT helps human scientists explore a latent space of papers that could exist, providing a rich field of suggested future research. We demonstrate the performance of FieldSHIFT for hypothesis generation relative to human-generated developmental biology research directions then test a key prediction of this model using bioinformatics, showing a surprising conservation of molecular mechanisms involved in pattern memory and developmental morphogenesis. By allowing scientists to rapidly explore symmetries and meta-parameters that exist in a corpus of scientific papers, we show how machine learning can potentiate human creativity and assist with one of the most interesting and crucial aspects of research: identifying insights from data and generating potential candidates for research agendas.

Designing artificial viral vectors (AVVs) programmed with biomolecules that can enter human cells and carry out molecular repairs will have broad applications. Here, we describe an assembly-line approach to build AVVs by engineering the well-characterized structural components of bacteriophage T4. Starting with a 120 × 86 nm capsid shell that can accommodate 171-Kbp DNA and thousands of protein copies, various combinations of biomolecules, including DNAs, proteins, RNAs, and ribonucleoproteins, are externally and internally incorporated. The nanoparticles are then coated with cationic lipid to enable efficient entry into human cells. As proof of concept, we assemble a series of AVVs designed to deliver full-length dystrophin gene or perform various molecular operations to remodel human genome, including genome editing, gene recombination, gene replacement, gene expression, and gene silencing. These large capacity, customizable, multiplex, and all-in-one phage-based AVVs represent an additional category of nanomaterial that could potentially transform gene therapies and personalized medicine.

Designing artificial odor delivery systems (AODSs) programmed with specific odorants that can enter the olfactory epithelium and modulate neural activity will have broad applications. Here, we describe an assembly-line approach to build AODSs by engineering the well-characterized structural components of odorant-binding proteins. Starting with a nanoscale carrier that can accommodate complex blends of odorants and thousands of binding sites, various combinations of odorants, pheromones, and modulatory molecules are externally and internally incorporated. The nanoparticles are then coated with a surfactant to enable efficient delivery to the olfactory mucosa. As proof of concept, we assemble a series of AODSs designed to deliver full-spectrum odorant blends or perform various operations to remodel olfactory-driven behavior, including behavioral conditioning, preference modification, aversion learning, behavioral replacement, and sensory masking. These large capacity, customizable, multiplex, and all-in-one odorant-based AODSs represent an additional category of nanomaterial that could potentially transform olfactory therapies and personalized modulation of behavior.

Designing artificial viral vectors (AVVs) programmed with biomolecules that can enter human cells and carry out molecular repairs will have broad applications. Here, we describe an assembly-line approach to build AVVs by engineering the well-characterized structural components of bacteriophage T4. Starting with a 120 × 86 nm capsid shell that can accommodate 171-Kbp DNA and thousands of protein copies, various combinations of biomolecules, including DNAs, proteins, RNAs, and ribonucleoproteins, are externally and internally incorporated. The nanoparticles are then coated with cationic lipid to enable efficient entry into human cells. As proof of concept, we assemble a series of AVVs designed to deliver full-length dystrophin gene or perform various molecular operations to remodel human genome, including genome editing, gene recombination, gene replacement, gene expression, and gene silencing. These large capacity, customizable, multiplex, and all-in-one phage-based AVVs represent an additional category of nanomaterial that could potentially transform gene therapies and personalized medicine.

Designing artificial financial instruments (AFIs) programmed with economic incentives that can enter markets and carry out targeted interventions will have broad applications. Here, we describe an assembly-line approach to build AFIs by engineering the well-characterized structural components of securitized assets. Starting with a 120 × 86 nm asset shell that can accommodate 171-Kbp worth of contractual claims and thousands of financial derivatives, various combinations of economic instruments, including equities, bonds, currencies, and hybrid securities, are externally and internally incorporated. The instruments are then coated with liquidity-enhancing mechanisms to enable efficient entry into financial markets. As proof of concept, we assemble a series of AFIs designed to deliver full-scale capital infusions or perform various market operations to restructure economic systems, including market correction, asset reallocation, debt restructuring, capital injection, and risk hedging. These large capacity, customizable, multiplex, and all-in-one asset-based AFIs represent an additional category of financial innovation that could potentially transform economic policy and personalized finance.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

Phage therapy is emerging as a promising strategy against the growing threat of antimicrobial resistance, yet phage and bacteria are incredibly diverse and idiosyncratic in their interactions with one another. Clinical applications of phage therapy often rely on a process of manually screening collections of naturally occurring phages for activity against a specific clinical isolate of bacteria, a labor-intensive task that is not guaranteed to yield a phage with optimal activity against a particular isolate. Herein, we review recent advances in artificial intelligence (AI) approaches that are advancing the study of phage-host interactions in ways that might enable the design of more effective phage therapeutics. In light of concurrent advances in synthetic biology enabling rapid genetic manipulation of phages, we envision how these AI-derived insights could inform the genetic optimization of the next generation of synthetic phages.

Catalyst-based remediation is emerging as a promising strategy against the growing threat of chemical resistance in industrial processes, yet catalysts and substrates are incredibly diverse and idiosyncratic in their interactions with one another. Practical applications of catalyst selection often rely on a process of manually screening collections of naturally occurring catalysts for activity against a specific chemical substrate, a labor-intensive task that is not guaranteed to yield a catalyst with optimal activity for a particular reaction. Herein, we review recent advances in artificial intelligence (AI) approaches that are advancing the study of catalyst-substrate interactions in ways that might enable the design of more effective catalytic systems. In light of concurrent advances in synthetic chemistry enabling rapid structural modification of catalysts, we envision how these AI-derived insights could inform the molecular optimization of the next generation of synthetic catalysts.

In microbiology, preservation of an archival stock or a “master stock” of a given microorganism is essential for many reasons including scientific research, conservation of the genetic resources and providing the foundation for several biotechnological processes. The objective is to preserve the initial characteristics of the microorganism and to avoid the genetic drift that occurs when the organism is maintained indefinitely in an actively growing state. The same holds true in phage biology and it is of particular interest when a collection of phages is to be maintained. The aim of this chapter is to provide phage biologists with general procedures to prepare and maintain bacteriophage stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many phages and bacterial strains can be propagated and stored in these conditions, specific media and/or growth and storage conditions must be evaluated for each phage and bacterium. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting phage amplification and storage. We hope this will help phage biologists to develop their own strategies for their preferred phages.

In chemistry, preservation of an archival sample or a “master stock” of a given compound is essential for many reasons including scientific research, conservation of chemical resources, and providing the foundation for several synthetic and analytical processes. The objective is to preserve the initial properties of the compound and to avoid chemical degradation or transformation that occurs when the substance is maintained indefinitely under reactive conditions. The same holds true in the context of reactive intermediates and is of particular interest when a collection of such species is to be maintained. The aim of this chapter is to provide chemists with general procedures to prepare and maintain compound stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many compounds and reagents can be stabilized and stored under these conditions, specific solvents and/or storage conditions must be evaluated for each chemical species. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting compound stability and storage. We hope this will help chemists to develop their own strategies for their preferred compounds.

In microbiology, preservation of an archival stock or a “master stock” of a given microorganism is essential for many reasons including scientific research, conservation of the genetic resources and providing the foundation for several biotechnological processes. The objective is to preserve the initial characteristics of the microorganism and to avoid the genetic drift that occurs when the organism is maintained indefinitely in an actively growing state. The same holds true in phage biology and it is of particular interest when a collection of phages is to be maintained. The aim of this chapter is to provide phage biologists with general procedures to prepare and maintain bacteriophage stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many phages and bacterial strains can be propagated and stored in these conditions, specific media and/or growth and storage conditions must be evaluated for each phage and bacterium. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting phage amplification and storage. We hope this will help phage biologists to develop their own strategies for their preferred phages.

In developmental biology, preservation of an archival stock or a “master stock” of a given cell lineage is essential for many reasons including scientific research, conservation of genetic resources, and providing the foundation for several tissue engineering and regenerative processes. The objective is to preserve the initial characteristics of the cell lineage and to avoid genetic drift that occurs when the lineage is maintained indefinitely in a proliferative state. The same holds true in stem cell biology and it is of particular interest when a collection of stem cell lines is to be maintained. The aim of this chapter is to provide developmental biologists with general procedures to prepare and maintain stem cell stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many cell types and lineages can be propagated and stored in these conditions, specific media and/or growth and storage conditions must be evaluated for each cell type. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting cell amplification and storage. We hope this will help developmental biologists to develop their own strategies for their preferred cell lineages.

In microbiology, preservation of an archival stock or a “master stock” of a given microorganism is essential for many reasons including scientific research, conservation of the genetic resources and providing the foundation for several biotechnological processes. The objective is to preserve the initial characteristics of the microorganism and to avoid the genetic drift that occurs when the organism is maintained indefinitely in an actively growing state. The same holds true in phage biology and it is of particular interest when a collection of phages is to be maintained. The aim of this chapter is to provide phage biologists with general procedures to prepare and maintain bacteriophage stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many phages and bacterial strains can be propagated and stored in these conditions, specific media and/or growth and storage conditions must be evaluated for each phage and bacterium. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting phage amplification and storage. We hope this will help phage biologists to develop their own strategies for their preferred phages.

In psychology, preservation of an archival record or a “master profile” of a given individual or group is essential for many reasons including scientific research, conservation of psychological traits, and providing the foundation for several applied interventions. The objective is to preserve the initial characteristics of the psychological profile and to avoid the drift that occurs when individuals or groups are repeatedly assessed or exposed to interventions over time. The same holds true in the study of psychological constructs and is of particular interest when a collection of psychological profiles is to be maintained. The aim of this chapter is to provide psychologists with general procedures to prepare and maintain psychological records on a long-term basis. The protocols described below should be considered as general guidelines because although many individuals and groups can be assessed and stored in these conditions, specific assessment tools and/or maintenance and storage conditions must be evaluated for each case. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting psychological assessment and record maintenance. We hope this will help psychologists to develop their own strategies for their preferred constructs or populations.

In microbiology, preservation of an archival stock or a “master stock” of a given microorganism is essential for many reasons including scientific research, conservation of the genetic resources and providing the foundation for several biotechnological processes. The objective is to preserve the initial characteristics of the microorganism and to avoid the genetic drift that occurs when the organism is maintained indefinitely in an actively growing state. The same holds true in phage biology and it is of particular interest when a collection of phages is to be maintained. The aim of this chapter is to provide phage biologists with general procedures to prepare and maintain bacteriophage stocks on a long-term basis. The protocols described below should be considered as general guidelines because although many phages and bacterial strains can be propagated and stored in these conditions, specific media and/or growth and storage conditions must be evaluated for each phage and bacterium. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting phage amplification and storage. We hope this will help phage biologists to develop their own strategies for their preferred phages.

In economics, preservation of a reference dataset or a “master dataset” of a given economic indicator is essential for many reasons including empirical research, conservation of data integrity, and providing the foundation for several econometric analyses. The objective is to preserve the initial characteristics of the dataset and to avoid the data drift that occurs when the dataset is continually updated without proper archival. The same holds true in financial economics and is of particular interest when a collection of financial instruments or indices is to be maintained. The aim of this chapter is to provide economists with general procedures to prepare and maintain economic data archives on a long-term basis. The protocols described below should be considered as general guidelines because although many datasets and economic variables can be archived and maintained under these conditions, specific data formats and/or storage and update conditions must be evaluated for each dataset and variable. Since it was not the scope of this chapter to provide an exhaustive list of these particular conditions, we instead highlighted the main factors affecting data preservation and archival. We hope this will help economists to develop their own strategies for their preferred datasets.

We introduce an open-ended test grounded in algorithmic probability that can avoid benchmark contamination in the quantitative evaluation of frontier models in the context of their Artificial General Intelligence (AGI) and Superintelligence (ASI) claims. Unlike other tests, this test does not rely on statistical compression methods (such as GZIP or LZW), which are more closely related to Shannon entropy than to Kolmogorov complexity and are not able to test beyond simple pattern matching. The test challenges aspects of AI, in particular LLMs, related to features of intelligence of fundamental nature such as synthesis and model creation in the context of inverse problems (generating new knowledge from observation). We argue that metrics based on model abstraction and abduction (optimal Bayesian `inference') for predictive `planning' can provide a robust framework for testing intelligence, including natural intelligence (human and animal), narrow AI, AGI, and ASI. We found that LLM model versions tend to be fragile and incremental as a result of memorisation only with progress likely driven by the size of training data. The results were compared with a hybrid neurosymbolic approach that theoretically guarantees universal intelligence based on the principles of algorithmic probability and Kolmogorov complexity. The method outperforms LLMs in a proof-of-concept on short binary sequences. We prove that compression is equivalent and directly proportional to a system's predictive power and vice versa. That is, if a system can better predict it can better compress, and if it can better compress, then it can better predict. Our findings strengthen the suspicion regarding the fundamental limitations of LLMs, exposing them as systems optimised for the perception of mastery over human language.

We introduce an open-ended assessment grounded in algorithmic probability that can avoid market distortion in the quantitative evaluation of frontier economic models in the context of their claims to general and superintelligent economic forecasting. Unlike other assessments, this test does not rely on traditional econometric compression techniques (such as principal component analysis or autoregressive models), which are more closely related to information entropy than to algorithmic complexity and are not able to evaluate beyond simple pattern recognition in economic data. The assessment challenges aspects of economic modeling, particularly in large-scale predictive systems, related to features of economic intelligence of fundamental nature such as synthesis and model creation in the context of inverse problems (generating new economic insights from observed data). We argue that metrics based on model abstraction and abduction (optimal Bayesian inference) for predictive planning can provide a robust framework for testing economic intelligence, including human decision-making, narrow economic AI, and more general economic forecasting systems. We found that versions of large-scale economic models tend to be fragile and incremental as a result of overfitting to historical data, with progress likely driven by the size of available datasets. The results were compared with a hybrid symbolic-numeric approach that theoretically guarantees universal economic intelligence based on the principles of algorithmic probability and Kolmogorov complexity. The method outperforms traditional large-scale models in a proof-of-concept on short financial time series. We prove that data compression is equivalent and directly proportional to a system's predictive power and vice versa. That is, if a system can better predict, it can better compress economic data, and if it can better compress, then it can better predict. Our findings strengthen the suspicion regarding the fundamental limitations of large-scale economic models, exposing them as systems optimized for the appearance of mastery over economic language and data.

We introduce an open-ended test grounded in algorithmic probability that can avoid benchmark contamination in the quantitative evaluation of frontier models in the context of their Artificial General Intelligence (AGI) and Superintelligence (ASI) claims. Unlike other tests, this test does not rely on statistical compression methods (such as GZIP or LZW), which are more closely related to Shannon entropy than to Kolmogorov complexity and are not able to test beyond simple pattern matching. The test challenges aspects of AI, in particular LLMs, related to features of intelligence of fundamental nature such as synthesis and model creation in the context of inverse problems (generating new knowledge from observation). We argue that metrics based on model abstraction and abduction (optimal Bayesian `inference') for predictive `planning' can provide a robust framework for testing intelligence, including natural intelligence (human and animal), narrow AI, AGI, and ASI. We found that LLM model versions tend to be fragile and incremental as a result of memorisation only with progress likely driven by the size of training data. The results were compared with a hybrid neurosymbolic approach that theoretically guarantees universal intelligence based on the principles of algorithmic probability and Kolmogorov complexity. The method outperforms LLMs in a proof-of-concept on short binary sequences. We prove that compression is equivalent and directly proportional to a system's predictive power and vice versa. That is, if a system can better predict it can better compress, and if it can better compress, then it can better predict. Our findings strengthen the suspicion regarding the fundamental limitations of LLMs, exposing them as systems optimised for the perception of mastery over human language.

We introduce an open-ended assay grounded in algorithmic probability that can avoid assay contamination in the quantitative evaluation of advanced signaling networks in the context of their claims to cellular general intelligence and superintelligence. Unlike other assays, this assay does not rely on statistical compression methods (such as GZIP or LZW), which are more closely related to Shannon entropy than to Kolmogorov complexity and are not able to test beyond simple motif recognition. The assay challenges aspects of signaling networks, in particular large-scale regulatory modules, related to features of cellular intelligence of fundamental nature such as synthesis and pathway creation in the context of inverse problems (generating new regulatory mechanisms from observation). We argue that metrics based on pathway abstraction and abduction (optimal Bayesian inference) for predictive regulation can provide a robust framework for testing signaling intelligence, including natural cellular intelligence, engineered circuits, general signaling networks, and superintelligent regulatory systems. We found that versions of large-scale regulatory modules tend to be fragile and incremental as a result of memorization only, with progress likely driven by the size of input data. The results were compared with a hybrid neurosymbolic approach that theoretically guarantees universal signaling intelligence based on the principles of algorithmic probability and Kolmogorov complexity. The method outperforms large-scale regulatory modules in a proof-of-concept on short binary signaling sequences. We prove that compression is equivalent and directly proportional to a system's predictive regulatory power and vice versa. That is, if a system can better predict, it can better compress, and if it can better compress, then it can better predict. Our findings strengthen the suspicion regarding the fundamental limitations of large-scale regulatory modules, exposing them as systems optimized for the perception of mastery over cellular communication.

We introduce an open-ended test grounded in algorithmic probability that can avoid benchmark contamination in the quantitative evaluation of frontier models in the context of their Artificial General Intelligence (AGI) and Superintelligence (ASI) claims. Unlike other tests, this test does not rely on statistical compression methods (such as GZIP or LZW), which are more closely related to Shannon entropy than to Kolmogorov complexity and are not able to test beyond simple pattern matching. The test challenges aspects of AI, in particular LLMs, related to features of intelligence of fundamental nature such as synthesis and model creation in the context of inverse problems (generating new knowledge from observation). We argue that metrics based on model abstraction and abduction (optimal Bayesian `inference') for predictive `planning' can provide a robust framework for testing intelligence, including natural intelligence (human and animal), narrow AI, AGI, and ASI. We found that LLM model versions tend to be fragile and incremental as a result of memorisation only with progress likely driven by the size of training data. The results were compared with a hybrid neurosymbolic approach that theoretically guarantees universal intelligence based on the principles of algorithmic probability and Kolmogorov complexity. The method outperforms LLMs in a proof-of-concept on short binary sequences. We prove that compression is equivalent and directly proportional to a system's predictive power and vice versa. That is, if a system can better predict it can better compress, and if it can better compress, then it can better predict. Our findings strengthen the suspicion regarding the fundamental limitations of LLMs, exposing them as systems optimised for the perception of mastery over human language.

We introduce an open-ended assay grounded in algorithmic probability that can avoid benchmark contamination in the quantitative evaluation of frontier models in the context of their claims to universal morphogenetic competence and super-morphogenetic capacity. Unlike other assays, this test does not rely on statistical compression methods (such as GZIP or LZW), which are more closely related to Shannon entropy than to Kolmogorov complexity and are not able to test beyond simple pattern recognition. The assay challenges aspects of morphogenetic systems, in particular those based on large-scale pattern memory, related to features of morphogenetic intelligence of fundamental nature such as synthesis and model creation in the context of inverse problems (generating novel anatomical structures from observation). We argue that metrics based on model abstraction and abduction (optimal Bayesian inference) for predictive patterning can provide a robust framework for testing morphogenetic intelligence, including natural morphogenesis (in plants and animals), engineered morphogenetic systems, and hypothetical super-morphogenetic constructs. We found that pattern memory model versions tend to be fragile and incremental as a result of memorisation only, with progress likely driven by the size of training data. The results were compared with a hybrid bio-symbolic approach that theoretically guarantees universal morphogenetic intelligence based on the principles of algorithmic probability and Kolmogorov complexity. The method outperforms pattern memory systems in a proof-of-concept on short binary tissue patterning tasks. We prove that compression is equivalent and directly proportional to a system's predictive morphogenetic power and vice versa. That is, if a system can better predict, it can better compress, and if it can better compress, then it can better predict. Our findings strengthen the suspicion regarding the fundamental limitations of pattern memory systems, exposing them as systems optimised for the perception of mastery over canonical tissue patterning.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The rational agent adjusts their preferences to prevailing market conditions; the disruptive innovator insists on reshaping the market to fit their vision. Therefore, all economic advancement depends on the disruptive innovator.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The compliant system equilibrates with its environment; the non-equilibrating system persists in attempting to impose its own parameters on the environment. Therefore, all advancement in physical phenomena hinges on the non-equilibrating system.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptive algorithm optimizes itself to fit the environment; the disruptive algorithm persists in reconfiguring the environment to fit its own parameters. Therefore, all innovation depends on the disruptive algorithm.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The typical animal adjusts its behavior to prevailing odor landscapes; the atypical one persistently attempts to reshape the odor environment to suit its own behavioral preferences. Therefore, all advances in olfactory-driven behavioral innovation depend on the atypical animal.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The responsive cell adjusts its signaling to external cues; the unresponsive cell persistently attempts to modify its environment to match its intrinsic state. Therefore, all signaling innovation depends on the unresponsive cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the body achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about pattern memory content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent space associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent space to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body regions, in accord with modern pattern memory theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

Benjamin Bratton's most influential and widely recognized contribution is "The Stack: On Software and Sovereignty," a monumental work that redefines our understanding of global computation as an emergent geopolitical architecture. This theory provides a crucial framework for analyzing the complex interdependencies of technology, infrastructure, and power in the 21st century. Published by MIT Press in 2015, The Stack is presented as a comprehensive political and design theory of planetary-scale computation.1 At over 500 pages, it is frequently described as a "dense tome".5 Bratton posits that disparate computational genres—such as smart grids, cloud platforms, mobile apps, smart cities, the Internet of Things, and automation—do not evolve independently but instead form a coherent, "accidental megastructure" he terms "The Stack".5 The core argument is threefold: computation is not merely algorithmic calculation or a genre of tool, but a global infrastructure that now not only relays information but is the primary source of its generation and mediation.2 This planetary computation distorts and reforms modern Westphalian political geography, producing new forms of territory over which sovereignty is contested.2 Finally, The Stack should be seen not as a single undifferentiated mega-machine but as an "accidental megastructure" comprised of modular, functionally defined layers, analogous to a software/hardware protocol stack.2 Bratton identifies six interconnected layers, each with its own contested affordances and integral accidents.2 These layers are: Earth Layer: This layer represents the physical foundation of computation, encompassing the material and energy resources (minerals, fossil fuels) required for computational processes, as well as the electronic waste produced. It constitutes the fundamental building blocks of the global digital stack.2 Bratton also provocatively posits the Earth itself as a "calculation machine".18 Cloud Layer: This refers to global, often corporate, technology services (e.g., Google) that exert a form of "weird sovereignty".21 City Layer: This layer represents the lived experience of physically interacting with the global computer network in daily life, frequently discussed in relation to the concept of smart cities.21 Address Layer: This pertains to the identification systems for individual users and objects, and its utilization for management and control within the computational megastructure.21 Interface Layer: This describes the various means and mechanisms through which users are connected to computational systems.21 User Layer: This comprises the actual human (and non-human) entities that interact with computers and computational systems.21

Benjamin Bratton's most influential and widely recognized contribution is "The Stack: On Markets and Sovereignty," a monumental work that redefines our understanding of global economic integration as an emergent geopolitical architecture. This theory provides a crucial framework for analyzing the complex interdependencies of markets, infrastructure, and power in the 21st century. Published by MIT Press in 2015, The Stack is presented as a comprehensive political and economic theory of planetary-scale market integration. At over 500 pages, it is frequently described as a "dense tome". Bratton posits that disparate economic sectors—such as financial markets, global supply chains, digital platforms, urban economies, the sharing economy, and automation—do not evolve independently but instead form a coherent, "accidental megastructure" he terms "The Stack". The core argument is threefold: economic activity is not merely transactional exchange or a genre of resource allocation, but a global infrastructure that now not only facilitates trade but is the primary source of its generation and mediation. This planetary economic integration distorts and reforms modern Westphalian political geography, producing new forms of territory over which sovereignty is contested. Finally, The Stack should be seen not as a single undifferentiated mega-market but as an "accidental megastructure" comprised of modular, functionally defined layers, analogous to vertically integrated economic systems. Bratton identifies six interconnected layers, each with its own contested affordances and integral market failures. These layers are: Resource Layer: This layer represents the physical foundation of economic activity, encompassing the material and energy resources (minerals, fossil fuels, commodities) required for production processes, as well as the environmental externalities produced. It constitutes the fundamental building blocks of the global economic stack. Bratton also provocatively posits the Earth itself as a "value-generating machine". Financial Layer: This refers to global, often corporate, financial institutions and markets (e.g., Wall Street, multinational banks) that exert a form of "weird sovereignty". Urban Layer: This layer represents the lived experience of physically interacting with the global economic network in daily life, frequently discussed in relation to the concept of urban agglomeration economies and smart urbanism. Identity Layer: This pertains to the identification systems for individual economic agents and assets, and their utilization for management, surveillance, and control within the economic megastructure. Market Interface Layer: This describes the various means and mechanisms through which economic agents are connected to markets, including digital platforms, exchanges, and transaction systems. Agent Layer: This comprises the actual human (and non-human, algorithmic) entities that participate in economic transactions and interactions within global markets.

Benjamin Bratton's most influential and widely recognized contribution is "The Stack: On Software and Sovereignty," a monumental work that redefines our understanding of global computation as an emergent geopolitical architecture. This theory provides a crucial framework for analyzing the complex interdependencies of technology, infrastructure, and power in the 21st century. Published by MIT Press in 2015, The Stack is presented as a comprehensive political and design theory of planetary-scale computation.1 At over 500 pages, it is frequently described as a "dense tome".5 Bratton posits that disparate computational genres—such as smart grids, cloud platforms, mobile apps, smart cities, the Internet of Things, and automation—do not evolve independently but instead form a coherent, "accidental megastructure" he terms "The Stack".5 The core argument is threefold: computation is not merely algorithmic calculation or a genre of tool, but a global infrastructure that now not only relays information but is the primary source of its generation and mediation.2 This planetary computation distorts and reforms modern Westphalian political geography, producing new forms of territory over which sovereignty is contested.2 Finally, The Stack should be seen not as a single undifferentiated mega-machine but as an "accidental megastructure" comprised of modular, functionally defined layers, analogous to a software/hardware protocol stack.2 Bratton identifies six interconnected layers, each with its own contested affordances and integral accidents.2 These layers are: Earth Layer: This layer represents the physical foundation of computation, encompassing the material and energy resources (minerals, fossil fuels) required for computational processes, as well as the electronic waste produced. It constitutes the fundamental building blocks of the global digital stack.2 Bratton also provocatively posits the Earth itself as a "calculation machine".18 Cloud Layer: This refers to global, often corporate, technology services (e.g., Google) that exert a form of "weird sovereignty".21 City Layer: This layer represents the lived experience of physically interacting with the global computer network in daily life, frequently discussed in relation to the concept of smart cities.21 Address Layer: This pertains to the identification systems for individual users and objects, and its utilization for management and control within the computational megastructure.21 Interface Layer: This describes the various means and mechanisms through which users are connected to computational systems.21 User Layer: This comprises the actual human (and non-human) entities that interact with computers and computational systems.21

Benjamin Bratton's most influential and widely recognized contribution is "The Stack: On Fields and Sovereignty," a monumental work that redefines our understanding of global physical interactions as an emergent geopolitical architecture. This theory provides a crucial framework for analyzing the complex interdependencies of energy, infrastructure, and power in the 21st century. Published by MIT Press in 2015, The Stack is presented as a comprehensive theoretical and structural analysis of planetary-scale physical interactions. At over 500 pages, it is frequently described as a "dense tome". Bratton posits that disparate physical phenomena—such as electromagnetic fields, gravitational interactions, quantum entanglement, thermodynamic processes, particle interactions, and cosmological structures—do not evolve independently but instead form a coherent, "accidental megastructure" he terms "The Stack". The core argument is threefold: physical interaction is not merely isolated force exchange or a genre of mechanism, but a global infrastructure that now not only transmits energy and information but is the primary source of their generation and mediation. This planetary-scale physical interaction distorts and reforms classical Newtonian spatial geography, producing new forms of spatial domains over which sovereignty (control of physical laws and conditions) is contested. Finally, The Stack should be seen not as a single undifferentiated mega-machine but as an "accidental megastructure" comprised of modular, functionally defined layers, analogous to a physical interaction hierarchy. Bratton identifies six interconnected layers, each with its own contested affordances and integral accidents. These layers are: Fundamental Layer: This layer represents the physical foundation of interactions, encompassing the elementary particles, fundamental forces, and energy resources required for physical processes, as well as the entropy and waste heat produced. It constitutes the fundamental building blocks of the global physical stack. Bratton also provocatively posits the Universe itself as a "computational machine". Field Layer: This refers to global, often emergent, field interactions (e.g., electromagnetic and gravitational fields) that exert a form of "nonlocal sovereignty". Locality Layer: This layer represents the lived experience of physically interacting with global physical fields in daily life, frequently discussed in relation to the concept of local reference frames and inertial systems. Coordinate Layer: This pertains to the identification and measurement systems for individual particles and objects, and their utilization for management and control within the physical megastructure. Interaction Layer: This describes the various means and mechanisms through which particles and systems exchange energy and information. Observer Layer: This comprises the actual human (and non-human) entities that measure, interact with, and interpret physical systems.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

Philosophical discussion on control has largely centred around control over our actions and beliefs. Yet this overlooks the question of whether we also have control over the reasons for which we act and believe. To date, the overriding assumption appears to be that we do not, and with seemingly good reason. We cannot choose to act for a reason and acting-for-a-reason is not itself something we do. While some have challenged this in the case of reasons for action, these claims seem especially untenable regarding believing for a reason. And extending the scope of control in this way also faces the threat of regress. In the face of this orthodoxy, the present paper argues thatwe do in fact have control over both believing and acting for a particular reason. It also starts to develop an account of the way in which this would be possible. Given the broad importance of understanding control and agency, this paper bears on a number of topics in epistemology, the philosophy of mind, and ethics.

Theoretical discussion on developmental control has largely centered around control over morphogenetic events and cellular differentiation. Yet this overlooks the question of whether cells also have control over the developmental signals for which they differentiate and morphologically respond. To date, the overriding assumption appears to be that they do not, and with seemingly good reason. Cells cannot choose to respond to a developmental signal, and responding-to-a-signal is not itself something cells actively control. While some have challenged this in the case of signals for morphogenesis, these claims seem especially untenable regarding differentiation signals. Extending the scope of cellular control in this way also faces the threat of regress. In the face of this orthodoxy, the present paper argues that cells do in fact have control over both differentiating and morphologically responding for a particular developmental signal. It also starts to develop an account of the way in which this would be possible. Given the broad importance of understanding cellular control and developmental agency, this paper bears on a number of topics in developmental signaling, morphogenesis, and developmental plasticity.

What is the status of research on implicit bias? In light ofmeta-analyses revealing ostensibly low average correlations between implicit measures and behavior, as well as various other psychometric concerns, criticism has become ubiquitous.We argue that while there are significant challenges and ample room for improvement, research on the causes, psychological properties, and behavioral effects of implicit bias continues to deserve a role in the sciences of the mind as well as in efforts to understand, and ultimately combat, discrimination and inequality.

What is the status of research on cryptic developmental biases? In light of meta-analyses revealing ostensibly low average correlations between cryptic developmental markers and morphogenetic outcomes, as well as various other methodological concerns, criticism has become ubiquitous. We argue that while there are significant challenges and ample room for improvement, research on the origins, molecular properties, and morphogenetic consequences of cryptic developmental biases continues to deserve a role in developmental biology, as well as in efforts to understand, and ultimately mitigate, developmental anomalies and phenotypic variability.

Broadcast journalists are more concise than their newspaper colleagues. ey have to be. e printout of a half-hour news broadcast would fill only a page or two in the newspaper. A broadcast lead cannot include all 5 Ws and the H discussed in Chapter 2 — it would be too long and too hard to follow. Instead, a broadcast writer will select the two or three most significant points to use in the lead, and put the rest in the sentence that follows. Broadcast stories also tend to leave out some details, such as ages and addresses, which are routinely found in print. Broadcasters write shorter sentences so they can read them aloud without running out of breath.

Developmental signaling pathways are more concise than their transcriptional counterparts. They must be. The molecular output of a brief signaling event would occupy only a small fraction of the transcriptional landscape. A signaling cascade cannot encode all spatial, temporal, and molecular details simultaneously—it would be overly complex and difficult to interpret. Instead, developmental signaling selects two or three critical molecular cues to initiate morphogenesis, with additional details provided by subsequent downstream signals. Signaling pathways also typically omit certain specifics, such as exact cellular positions or precise developmental timings, which are routinely encoded in transcriptional profiles. Developmental signals utilize shorter, discrete molecular interactions to ensure rapid and efficient communication between cells.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The adaptive brain adjusts its neural responses to external stimuli; the maladaptive brain persists in attempting to reshape external stimuli to match its internal predictions. Therefore, all neural innovation depends on the maladaptive brain.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system conforms itself to external conditions; the unstable system persists in attempting to reshape external conditions to match its own state. Therefore, all physical evolution depends on unstable systems.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The stable system conforms itself to the external field; the unstable one persists in altering the external field to match its own state. Therefore, all advancement in physics depends on the unstable system.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific cognitive representations underlying a given memory (the mental schema) shift from instance to instance. This raises the question of how the mind maintains stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of cognitive schemas formed by patterns of mental activity. We show that these schemas carry information about working memory content. The schemas, in turn, function as "guard rails" that guide variable, high-dimensional cognitive processes along stable, lower-dimensional pathways. We identified the latent cognitive space associated with each memory. We then confirmed schema stability by mapping this latent space onto different cognitive domains (comprising a mental schema) and reconstructing information flow between domains. Stable cognitive schemas can facilitate the transfer of latent mental states across psychological domains, consistent with contemporary schema theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific computational nodes maintaining a given data representation (the computational ensemble) vary from execution to execution. This raises the question of how computational systems achieve stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of electromagnetic fields generated by computational activity. We show that electromagnetic fields encode information about working memory content. These fields, in turn, function as "guard rails" that constrain higher-dimensional variable computational activity along stable lower-dimensional trajectories. We derived the latent space associated with each data representation. We then confirmed the stability of the electromagnetic field by mapping the latent space onto different computational modules (comprising a computational ensemble) and reconstructing information flow between modules. Stable electromagnetic fields can facilitate the transfer of latent states between computational units, consistent with contemporary distributed memory architectures.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact computational nodes maintaining a given data representation (the computational ensemble) vary from execution to execution. This raises the question of how computational systems achieve stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of electromagnetic fields generated by computational activity. We show that electromagnetic fields encode information about active memory content. These fields, in turn, function as "guard rails" that constrain higher-dimensional variable computational activity along stable lower-dimensional trajectories. We derived the latent space associated with each memory representation. We then confirmed the stability of the electromagnetic field by mapping the latent space onto different computational modules (comprising a computational ensemble) and reconstructing information flow between modules. Stable electromagnetic fields can facilitate the transfer of latent states between computational units, consistent with contemporary distributed memory architectures.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles constituting a given quantum state (the particle ensemble) vary from measurement to measurement. This raises the question of how physical systems achieve stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of electromagnetic fields generated by particle interactions. We show that electromagnetic fields carry information about quantum state content. These fields, in turn, can act as "guiding potentials" that constrain higher-dimensional variable particle dynamics along stable lower-dimensional trajectories. We obtained the latent space associated with each quantum state. We then confirmed the stability of the electromagnetic field by mapping the latent space onto different spatial regions (comprising particle ensembles) and reconstructing information flow between regions. Stable electromagnetic fields can allow latent states to be transferred between spatial domains, consistent with modern quantum information theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific firms maintaining a given market equilibrium (the firm ensemble) change from period to period. This raises the question of how the economy achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of price signals arising from firm activity. We show that price signals carry information about market equilibrium conditions. The price signals, in turn, can act as "guard rails" that funnel higher-dimensional variable firm behaviors along stable lower-dimensional trajectories. We obtained the latent space associated with each equilibrium. We then confirmed the stability of price signals by mapping the latent space to different market sectors (that comprise a firm ensemble) and reconstructing information flow between sectors. Stable price signals can allow latent economic states to be transferred between market areas, in accord with modern equilibrium theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific cognitive representations underlying a given memory (the mental schema) shift from instance to instance. This raises the question of how the mind maintains stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of cognitive schemas formed by patterns of mental activity. We show that these schemas carry information about working memory content. The schemas, in turn, can act as "guard rails" that guide variable cognitive processes along stable, lower-dimensional pathways. We identified the latent cognitive space associated with each memory. We then confirmed the stability of these schemas by mapping the latent space onto different cognitive domains (that comprise a mental schema) and reconstructing information flow between domains. Stable cognitive schemas can allow latent mental states to be transferred between psychological processes, consistent with contemporary schema theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The responsive cell adapts itself to the existing morphospace; the uncompromising one persists in attempting to reshape the morphospace to match its own target morphology. Therefore, all advancement in morphogenesis depends on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The conforming algorithm adjusts its parameters to fit existing data distributions; the non-conforming algorithm persists in modifying data distributions to align with its objectives. Therefore, all advancement in AI depends on the non-conforming algorithm.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

Emphasizing the principles of continuity and pragmatism, and using morphogenesis as a tractable model system in which to develop these ideas, I explore the implications of the following ideas:(A) Evolution favors living forms that exploit powerfultruths of mathematics and computation as affordances, which contribute as causes of morphologicaland behavioralfeatures. (B) Cognitive patterns arean evolutionary pivot of the collective intelligence of cells;given this symmetry between neuroscience and developmental biology, I propose that the relationship between mind and brain is the same as the relationship between mathematical patterns and the morphogenetic outcomes they guide. (C) Many mathematicians, and a non-mysterian approach to science in general, suggest that these patterns are not random facts to bemerely cataloged as “emergence” when found, but rather can be systematically discovered within a structured, ordered (non-physical) space. Therefore, I hypothesize that:(1)instances of embodied cognition likewise ingress from a Platonic space, which contains not only low-agency patterns like facts about triangles and prime numbers, but also higheragency ones such as kinds of minds; (2)we take seriously for developmental, synthetic, and behavioral biologythe kindsof non-physicalist ideas that are already a staple of Platonist mathematics;(3) what evolution (and bioengineering, and possiblyAI) produces are pointers into that Platonic space –physical interfacesthat enable the ingression of specific patternsof body and mind.This provides a new perspective on the organicist/mechanist debate by explaining why traditional computationalist views of life and mind are insufficient, while at the same time erasing artificial distinctions between life and machine, since both are in-formed by diverse patterns from the latent space. I sketch a research program, already begun, of using the tools of the fields of synthetic morphologyand diverse intelligence to map out key regions of the Platonic space. Understanding the mapping between the architecture of physical embodiments and the patterns to which they point has massive implications for evolutionary biology, regenerative medicine, AI, and the ethics of synthbiosis with the forthcomingimmensediversity of morally important be

Emphasizing the principles of continuity and pragmatism, and using hypothesis generation as a tractable model system in which to develop these ideas, I explore the implications of the following ideas: (A) Scientific discovery favors hypothesis generators that exploit powerful truths of mathematics and computation as affordances, which contribute as causes of novel and explanatory hypotheses. (B) Conceptual patterns are a pivotal axis of the collective intelligence of scientific communities; given this symmetry between mathematical structure and hypothesis generation, I propose that the relationship between abstract mathematical truths and generated hypotheses is analogous to the relationship between mathematical patterns and the scientific outcomes they guide. (C) Many mathematicians, and a non-mysterian approach to science in general, suggest that these patterns are not random facts to be merely cataloged as "emergence" when found, but rather can be systematically discovered within a structured, ordered (non-physical) space. Therefore, I hypothesize that: (1) instances of scientific insight likewise ingress from a Platonic space, which contains not only low-agency patterns like facts about triangles and prime numbers, but also higher-agency ones such as classes of explanatory hypotheses; (2) we take seriously for hypothesis generation and scientific discovery the kinds of non-physicalist ideas that are already a staple of Platonist mathematics; (3) what scientific inquiry (and computational modeling, and possibly AI-driven discovery) produces are pointers into that Platonic space—conceptual interfaces that enable the ingression of specific patterns of explanatory hypotheses. This provides a new perspective on the rationalist/empiricist debate by explaining why traditional computationalist views of scientific discovery are insufficient, while at the same time erasing artificial distinctions between human and machine-generated hypotheses, since both are informed by diverse patterns from the latent space. I sketch a research program, already begun, of using the tools of computational hypothesis generation and diverse intelligence to map out key regions of the Platonic space. Understanding the mapping between the architecture of hypothesis-generating systems and the patterns to which they point has massive implications for scientific methodology, computational discovery, AI-driven science, and the ethics of collaboration with the forthcoming immense diversity of scientifically important conceptual agents.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific computational nodes maintaining a given data representation (the computational ensemble) vary from execution to execution. This raises the question of how computational systems achieve stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of electromagnetic fields generated by computational activity. We show that electromagnetic fields encode information about working memory content. These fields, in turn, function as "guard rails" that constrain higher-dimensional variable computational activity along stable lower-dimensional trajectories. We derived the latent space associated with each data representation. We then confirmed the stability of the electromagnetic field by mapping the latent space onto different computational modules (comprising a computational ensemble) and reconstructing information flow between modules. Stable electromagnetic fields can facilitate the transfer of latent states between computational units, consistent with modern distributed memory architectures.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific cognitive representations underlying a given memory (the mental schema) shift from instance to instance. This raises the question of how the mind maintains stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of cognitive schemas arising from mental activity. We show that cognitive schemas carry information about working memory content. These schemas, in turn, function as "guard rails" that guide variable, high-dimensional cognitive processes along stable, lower-dimensional pathways. We identified the latent cognitive space associated with each memory. We then confirmed the stability of these schemas by mapping the latent space onto different cognitive domains (comprising a mental schema) and reconstructing information flow between domains. Stable cognitive schemas can facilitate the transfer of latent mental states across psychological domains, consistent with contemporary schema theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

We introduce the first method for translating text embeddings from one vector space to another without any paired data, encoders, or predefined sets of matches. Our unsupervised approach translates any embedding to and from a universal latent representation (i.e., a universal semantic structure conjectured by the Platonic Representation Hypothesis). Our translations achieve high cosine similarity across model pairs with different architectures, parameter counts, and training datasets. The ability to translate unknown embeddings into a different space while preserving their geometry has serious implications for the security of vector databases. An adversary with access only to embedding vectors can extract sensitive information about the underlying documents, sufficient for classification and attribute inference.

We introduce the first method for mapping neural representations from one neural state space to another without any paired neural recordings, explicit encoding models, or predefined neuronal correspondences. Our unsupervised approach translates any neural activity pattern to and from a universal latent representation (i.e., a universal neural code structure conjectured by the Neural Representation Hypothesis). Our translations achieve high representational similarity across neural populations with different circuit architectures, neuron counts, and training experiences. The ability to translate unknown neural activity patterns into a different neural representation space while preserving their geometry has serious implications for the security of neural decoding methods. An adversary with access only to neural activity patterns can extract sensitive information about underlying cognitive states, sufficient for decoding intentions and inferring perceptual attributes.

We introduce the first method for translating text embeddings from one vector space to another without any paired data, encoders, or predefined sets of matches. Our unsupervised approach translates any embedding to and from a universal latent representation (i.e., a universal semantic structure conjectured by the Platonic Representation Hypothesis). Our translations achieve high cosine similarity across model pairs with different architectures, parameter counts, and training datasets. The ability to translate unknown embeddings into a different space while preserving their geometry has serious implications for the security of vector databases. An adversary with access only to embedding vectors can extract sensitive information about the underlying documents, sufficient for classification and attribute inference.

We introduce the first method for translating cellular bioelectric states from one morphogenetic space to another without any paired data, signaling pathways, or predefined sets of correspondences. Our unsupervised approach translates any bioelectric pattern to and from a universal latent representation (i.e., a universal morphogenetic structure conjectured by the Platonic Morphospace Hypothesis). Our translations achieve high similarity across tissue pairs with different architectures, cell numbers, and developmental histories. The ability to translate unknown bioelectric patterns into a different morphogenetic context while preserving their spatial geometry has significant implications for the robustness of developmental patterning. An external perturbation with access only to bioelectric states could extract critical information about underlying gene expression patterns, sufficient for phenotype classification and developmental fate inference.

Farts

Gas emission events

Farts

Flatulence releases odorants that activate olfactory receptors, triggering behavioral circuits leading to avoidance or social behaviors.

Farts

Synaptic noise bursts

Farts

Externalities

Farts

Data packet collisions

Farts

Flatulence-related embarrassment responses

Farts

Methane emission

Farts

Gas signaling events

We diverge from Descartes by holding that what he has described as primary attributes of physical bodies, are really the forms of internal relationships between actual occasions. Such a change of thought is the shift from materialism to Organic Realism, as a basic idea of physical science.

We diverge from preformationism by holding that what has been described as primary attributes of individual cells, are really the forms of internal relationships between developmental events. Such a change of thought is the shift from reductionism to Organic Realism, as a basic idea of developmental biology.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

Significance Specific changes in one region can influence the activity throughout the entire brain, a phenomenon known as diaschisis. This study combines advanced imaging techniques and personalized brain simulations in mice to investigate how targeted brain interventions, such as lesions or temporary silencing of certain regions, reshape global brain connectivity. The findings provide insights into why some interventions lead to reduced connectivity (hypoconnectivity) while others result in increased connectivity (hyperconnectivity), as observed in the literature. By elucidating the mechanisms underlying diaschisis, this work establishes a framework for understanding the widespread effects of localized brain injuries or interventions and for developing more precise therapeutic strategies that address brain dynamics across multiple scales.

Significance Specific changes in one tissue region can influence bioelectrical activity throughout the entire organism, a phenomenon known as developmental diaschisis. This study combines advanced bioelectric imaging techniques and personalized computational simulations in model organisms to investigate how targeted tissue interventions, such as localized ablations or temporary suppression of specific signaling centers, reshape global bioelectrical connectivity. The findings provide insights into why some interventions lead to reduced connectivity (hypoconnectivity) while others result in increased connectivity (hyperconnectivity), as observed in the literature. By elucidating the mechanisms underlying developmental diaschisis, this work establishes a framework for understanding the widespread effects of localized tissue injuries or interventions and for developing more precise regenerative strategies that address morphogenetic dynamics across multiple scales.

The resting human brain, characterized by intrinsic or spontaneous brain activities, has been increasingly understood from a connectome perspective over the past two decades1,2,3. The emergence, development and aging of the intrinsic connectome architecture enables the dynamic reorganization of functional specialization and integration throughout the lifespan, contributing to continuous changes in human cognition and behavior4,5. Understanding the spatiotemporal growth process of the typical functional connectome is critical for elucidating network-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative connectome patterns, especially during specific time windows, can predispose individuals to a spectrum of neurodevelopmental6, neurodegenerative7 and psychiatric disorders8,9. The growth chart framework provides an invaluable tool for charting normative reference curves in the human brain10,11. Recently, Bethlehem et al.10 delineated the life-cycle growth curves of brain morphometry by aggregating the largest multisite structural magnetic resonance imaging (MRI) dataset to date (101,457 individuals from 115 days after conception to 100 years of age), marking an important step toward reproducible and generalizable brain charts. However, the normative growth charts of the functional brain connectome across the human lifespan remain unknown.

The basal cellular state, characterized by intrinsic or spontaneous signaling activities, has been increasingly understood from a signaling network perspective. The emergence, maturation, and senescence of intrinsic signaling network architecture enables dynamic reorganization of signaling specificity and integration throughout the cellular lifespan, contributing to continuous changes in cellular function and response. Understanding the spatiotemporal development of the typical signaling network is critical for elucidating network-level developmental principles in healthy cells and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative signaling network patterns, especially during specific temporal windows, can predispose cells to a spectrum of developmental, degenerative, and signaling-related disorders. The growth chart framework provides an invaluable tool for charting normative reference curves in cellular signaling. Recently, comprehensive analyses delineated life-cycle growth curves of cellular morphology by aggregating large-scale imaging datasets, marking an important step toward reproducible and generalizable cellular growth charts. However, normative growth charts of the functional signaling network across the cellular lifespan remain unknown.

The resting human brain, characterized by intrinsic or spontaneous brain activities, has been increasingly understood from a connectome perspective over the past two decades1,2,3. The emergence, development and aging of the intrinsic connectome architecture enables the dynamic reorganization of functional specialization and integration throughout the lifespan, contributing to continuous changes in human cognition and behavior4,5. Understanding the spatiotemporal growth process of the typical functional connectome is critical for elucidating network-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative connectome patterns, especially during specific time windows, can predispose individuals to a spectrum of neurodevelopmental6, neurodegenerative7 and psychiatric disorders8,9. The growth chart framework provides an invaluable tool for charting normative reference curves in the human brain10,11. Recently, Bethlehem et al.10 delineated the life-cycle growth curves of brain morphometry by aggregating the largest multisite structural magnetic resonance imaging (MRI) dataset to date (101,457 individuals from 115 days after conception to 100 years of age), marking an important step toward reproducible and generalizable brain charts. However, the normative growth charts of the functional brain connectome across the human lifespan remain unknown.

The resting human mind, characterized by intrinsic or spontaneous mental activities, has been increasingly understood from a network perspective over the past two decades. The emergence, development, and aging of intrinsic cognitive network architecture enables dynamic reorganization of functional specialization and integration throughout the lifespan, contributing to continuous changes in human cognition and behavior. Understanding the spatiotemporal developmental trajectory of typical cognitive network connectivity is critical for elucidating network-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative cognitive network patterns, especially during specific developmental windows, can predispose individuals to a spectrum of neurodevelopmental, neurodegenerative, and psychiatric disorders. The growth chart framework provides an invaluable tool for charting normative reference curves in human psychological development. Recently, Bethlehem et al. delineated life-cycle growth curves of cognitive and behavioral measures by aggregating the largest multisite psychological assessment dataset to date, marking an important step toward reproducible and generalizable psychological growth charts. However, normative growth charts of functional cognitive network connectivity across the human lifespan remain unknown.

The resting human brain, characterized by intrinsic or spontaneous brain activities, has been increasingly understood from a connectome perspective over the past two decades1,2,3. The emergence, development and aging of the intrinsic connectome architecture enables the dynamic reorganization of functional specialization and integration throughout the lifespan, contributing to continuous changes in human cognition and behavior4,5. Understanding the spatiotemporal growth process of the typical functional connectome is critical for elucidating network-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative connectome patterns, especially during specific time windows, can predispose individuals to a spectrum of neurodevelopmental6, neurodegenerative7 and psychiatric disorders8,9. The growth chart framework provides an invaluable tool for charting normative reference curves in the human brain10,11. Recently, Bethlehem et al.10 delineated the life-cycle growth curves of brain morphometry by aggregating the largest multisite structural magnetic resonance imaging (MRI) dataset to date (101,457 individuals from 115 days after conception to 100 years of age), marking an important step toward reproducible and generalizable brain charts. However, the normative growth charts of the functional brain connectome across the human lifespan remain unknown.

The resting olfactory system, characterized by intrinsic or spontaneous olfactory activities, has been increasingly understood from a behavioral circuit perspective over recent decades. The emergence, maturation, and aging of intrinsic olfactory circuit architecture enables dynamic reorganization of odor-specific sensitivity and integration throughout the lifespan, contributing to continuous changes in olfactory perception and odor-guided behavior. Understanding the spatiotemporal development of typical olfactory circuits is critical for elucidating circuit-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative olfactory circuit patterns, especially during specific developmental windows, can predispose individuals to a spectrum of olfactory dysfunctions, sensory decline, and behavioral disorders. The growth chart framework provides an invaluable tool for charting normative reference curves in olfactory circuit maturation. Recently, large-scale studies have delineated life-cycle growth curves of olfactory sensory structures by aggregating extensive multisite olfactory datasets, marking an important step toward reproducible and generalizable olfactory development charts. However, normative growth charts of functional olfactory circuits across the human lifespan remain unknown.

The resting human brain, characterized by intrinsic or spontaneous brain activities, has been increasingly understood from a connectome perspective over the past two decades1,2,3. The emergence, development and aging of the intrinsic connectome architecture enables the dynamic reorganization of functional specialization and integration throughout the lifespan, contributing to continuous changes in human cognition and behavior4,5. Understanding the spatiotemporal growth process of the typical functional connectome is critical for elucidating network-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative connectome patterns, especially during specific time windows, can predispose individuals to a spectrum of neurodevelopmental6, neurodegenerative7 and psychiatric disorders8,9. The growth chart framework provides an invaluable tool for charting normative reference curves in the human brain10,11. Recently, Bethlehem et al.10 delineated the life-cycle growth curves of brain morphometry by aggregating the largest multisite structural magnetic resonance imaging (MRI) dataset to date (101,457 individuals from 115 days after conception to 100 years of age), marking an important step toward reproducible and generalizable brain charts. However, the normative growth charts of the functional brain connectome across the human lifespan remain unknown.

The basal cellular state, characterized by intrinsic or spontaneous signaling activities, has been increasingly understood from a network perspective. The emergence, maturation, and senescence of intrinsic signaling network architecture enables dynamic reorganization of functional specialization and integration throughout the cellular lifespan, contributing to continuous changes in cellular function and response. Understanding the spatiotemporal development of the typical signaling network is critical for elucidating network-level developmental principles in healthy cells and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative signaling network patterns, especially during specific temporal windows, can predispose cells to a spectrum of developmental, degenerative, and signaling-related disorders. The growth chart framework provides an invaluable tool for charting normative reference curves in cellular signaling networks. Recently, comprehensive analyses delineated life-cycle growth curves of cellular morphology by aggregating large-scale imaging datasets, marking an important step toward reproducible and generalizable cellular growth charts. However, normative growth charts of functional signaling networks across the cellular lifespan remain unknown.

The resting human brain, characterized by intrinsic or spontaneous brain activities, has been increasingly understood from a connectome perspective over the past two decades1,2,3. The emergence, development and aging of the intrinsic connectome architecture enables the dynamic reorganization of functional specialization and integration throughout the lifespan, contributing to continuous changes in human cognition and behavior4,5. Understanding the spatiotemporal growth process of the typical functional connectome is critical for elucidating network-level developmental principles in healthy individuals and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative connectome patterns, especially during specific time windows, can predispose individuals to a spectrum of neurodevelopmental6, neurodegenerative7 and psychiatric disorders8,9. The growth chart framework provides an invaluable tool for charting normative reference curves in the human brain10,11. Recently, Bethlehem et al.10 delineated the life-cycle growth curves of brain morphometry by aggregating the largest multisite structural magnetic resonance imaging (MRI) dataset to date (101,457 individuals from 115 days after conception to 100 years of age), marking an important step toward reproducible and generalizable brain charts. However, the normative growth charts of the functional brain connectome across the human lifespan remain unknown.

The resting embryonic body, characterized by intrinsic or spontaneous bioelectrical activities, has been increasingly understood from a morphogenetic connectivity perspective over the past two decades. The emergence, development, and aging of intrinsic bioelectric connectivity architecture enables the dynamic reorganization of morphogenetic specialization and integration throughout the lifespan, contributing to continuous changes in tissue patterning and morphogenesis. Understanding the spatiotemporal growth process of the typical bioelectric connectome is critical for elucidating network-level developmental principles in healthy organisms and for pinpointing periods of heightened vulnerability or potential. Disruption of these normative bioelectric connectivity patterns, especially during specific competency windows, can predispose organisms to a spectrum of developmental defects, degenerative conditions, and teratological disorders. The growth chart framework provides an invaluable tool for charting normative reference curves in embryonic and post-embryonic tissues. Recently, large-scale spatial gene expression profiling datasets have delineated life-cycle growth curves of anatomical morphometry by aggregating extensive multisite imaging data across developmental stages, marking an important step toward reproducible and generalizable morphogenetic charts. However, the normative growth charts of the functional bioelectric connectome across the organismal lifespan remain unknown.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from event to event. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of bioelectric fields arising from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional developmental trajectories. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The responsive cell adapts itself to existing signaling environments; the non-responsive cell persists in modifying signaling environments to suit its own state. Therefore, signaling network evolution depends on the non-responsive cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific molecules maintaining a given chemical state (the molecular ensemble) vary from reaction to reaction. This raises the question of how chemical systems achieve stability despite this molecular drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields generated by molecular interactions. We show that electromagnetic fields carry information about reaction intermediates. These electromagnetic fields, in turn, can act as "guiding potentials" that channel higher-dimensional variable molecular interactions along stable lower-dimensional reaction pathways. We obtained the latent reaction coordinate associated with each chemical state. We then confirmed the stability of the electromagnetic field by mapping the latent reaction coordinate onto different molecular clusters (that comprise a molecular ensemble) and reconstructing information transfer between clusters. Stable electromagnetic fields can allow latent chemical states to be transferred between molecular assemblies, consistent with modern reaction mechanism theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific molecules maintaining a given chemical state (the molecular ensemble) vary from reaction to reaction. This raises the question of how chemical systems achieve stability despite this molecular drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields generated by molecular interactions. We show that electromagnetic fields encode information about reaction intermediates. These electromagnetic fields, in turn, act as "guiding potentials" that channel higher-dimensional variable molecular interactions along stable lower-dimensional reaction pathways. We obtained the latent reaction coordinate associated with each chemical state. We then confirmed the stability of the electromagnetic field by mapping the latent reaction coordinate onto different molecular clusters (comprising a molecular ensemble) and reconstructing information transfer between clusters. Stable electromagnetic fields can facilitate the transfer of latent chemical states between reaction sites, consistent with contemporary reaction mechanism theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact particles constituting a given quantum state (the particle ensemble) fluctuate from measurement to measurement. This raises the question of how physical systems achieve stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of electromagnetic fields generated by particle interactions. We show that electromagnetic fields encode information about quantum state content. These fields, in turn, act as "guiding potentials" that constrain higher-dimensional variable particle dynamics along stable lower-dimensional trajectories. We obtained the latent space associated with each quantum state. We then confirmed the stability of the electromagnetic field by mapping the latent space onto different spatial regions (comprising particle ensembles) and reconstructing information transfer between regions. Stable electromagnetic fields can facilitate latent state transfer between spatial domains, consistent with modern quantum information theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific cognitive representations underlying a given memory (the mental schema) shift from instance to instance. This raises the question of how the mind maintains stability despite this representational variability. Here, we demonstrate that this stability emerges at the level of cognitive attractor states arising from mental activity. We show that these cognitive attractors encode information about working memory content. The cognitive attractors, in turn, function as "guard rails" that guide variable higher-dimensional mental processes along stable lower-dimensional trajectories. We identified the latent cognitive space associated with each memory. We then confirmed the stability of these cognitive attractors by mapping the latent space onto distinct cognitive modules (comprising a mental schema) and reconstructing information flow between modules. Stable cognitive attractors can facilitate the transfer of latent mental states across psychological domains, consistent with contemporary schema theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact computational nodes maintaining a given data representation (the computational ensemble) change from execution to execution. This raises the question of how a computing system achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electromagnetic fields generated by computational activity. We show that electromagnetic fields carry information about working memory content. The electromagnetic fields, in turn, can act as "guard rails" that funnel higher-dimensional variable computational activity along stable lower-dimensional trajectories. We obtained the latent space associated with each data representation. We then confirmed the stability of the electromagnetic field by mapping the latent space to different computational modules (that comprise a computational ensemble) and reconstructing information flow between modules. Stable electromagnetic fields can allow latent states to be transferred between computational units, in accord with modern distributed computing theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the specific computational nodes maintaining a given data representation (the computational ensemble) vary from execution to execution. This raises the question of how computational systems achieve stability despite this representational drift. Here, we demonstrate that this stability emerges at the level of electromagnetic fields generated by computational activity. We show that electromagnetic fields encode information about active memory states. These fields, in turn, function as "guard rails" that constrain higher-dimensional variable computational activity along stable lower-dimensional trajectories. We derived the latent space associated with each memory representation. We then confirmed the stability of the electromagnetic field by mapping the latent space onto different computational modules (comprising a computational ensemble) and reconstructing information flow between modules. Stable electromagnetic fields can facilitate the transfer of latent states between computational units, consistent with contemporary distributed memory architectures.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

what is this for?

What is the developmental purpose of this?

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from event to event. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of bioelectric fields arising from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional developmental trajectories. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between body areas, in accord with modern morphogenetic field theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit the correct target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from event to event. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of bioelectric fields that arise from cellular voltage changes. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional trajectories. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

It is known that the exact neurons maintaining a given memory (the neural ensemble) change from trial to trial. This raises the question of how the brain achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the electric fields that arise from neural activity. We show that electric fields carry information about working memory content. The electric fields, in turn, can act as "guard rails" that funnel higher dimensional variable neural activity along stable lower dimensional routes. We obtained the latent space associated with each memory. We then confirmed the stability of the electric field by mapping the latent space to different cortical patches (that comprise a neural ensemble) and reconstructing information flow between patches. Stable electric fields can allow latent states to be transferred between brain areas, in accord with modern engram theory.

It is known that the exact cells maintaining a given pattern memory (the cellular ensemble) change from trial to trial. This raises the question of how the developing organism achieves stability in the face of this representational drift. Here, we demonstrate that this stability emerges at the level of the bioelectric fields that arise from cellular activity. We show that bioelectric fields carry information about morphogenetic pattern content. The bioelectric fields, in turn, can act as "guard rails" that funnel higher dimensional variable cellular activity along stable lower dimensional routes. We obtained the latent morphospace associated with each pattern memory. We then confirmed the stability of the bioelectric field by mapping the latent morphospace to different tissue regions (that comprise a cellular ensemble) and reconstructing information flow between regions. Stable bioelectric fields can allow latent states to be transferred between tissue areas, in accord with modern morphogenetic field theory.

A Computational Offloading Approach for Generative AI Intrusion Detection Models Intelligent Systems  Daniel  Laboratório de Inteligência Castro Artificial e Ciência de Silva Computadores Published  Daniel Castro Silva  Context The rapid progression and innovation in AI have escalated the landscape of cyber threats and defense mechanisms to unprecedented levels. While AI techniques have fueled advanced protective measures, they have also enabled novel means for users with malicious intent to perform more sophisticated and stealthier attacks. These capabilities stem from technological advancements like the Internet of Things and cloud computing and the vast amounts of data created by these technologies. Recent advancements in language processing, particularly LLMs, have inspired research interest across various areas. The Transformer architecture, introduced in 2017, revolutionized data processing by efficiently handling large input datasets while capturing complex patterns within input sequences. The Transformer architecture introduces attention mechanisms, allowing https://ldm.fe.up.pt/thesis/meic/2425/proposals/1973caee-c4e9-4478-94ce-4818b9f8887d/ 1/47/15/24, 12:42 AM A Computational Offloading Approach for Generative AI Intrusion Detection Models models to focus on relevant parts of input sequences, thus enhancing their ability to understand and generate natural language text. Although Transformer-based models were originally leveraged to handle Natural Language Processing (NLP) tasks, they found their applications in cybersecurity domains. Enabling enhanced solutions to monitor input data sequences, model normal data samples, and identify deviations or malicious intrusion patterns. This rapidly increased several attack vectors like unauthorized access, malware, zero-day exploits, data breaches, denial-of-service (DoS), social engineering, phishing, and many others. Which in turn resulted in enormous losses for both businesses and individuals. Nonetheless, when it comes to edge-cloud environments like smart cities, Industrial Internet of Things (IIoT), and autonomous vehicles, deploying LLMs in these environments is typically faced with a couple of challenges. Particularly given that cloud-edge environments require dynamic, collaborative, and real- time cybersecurity measures to protect against threats on edge/end devices. Objectives This dissertation aims to investigate and implement offloading techniques to create smaller yet efficient GenAI models for intrusion detection, either by model compression, model partitioning, or knowledge transfer. Innovation Implementing computational offloading techniques to reduce the size and complexity of intrusion detection https://ldm.fe.up.pt/thesis/meic/2425/proposals/1973caee-c4e9-4478-94ce-4818b9f8887d/ 2/47/15/24, 12:42 AM A Computational Offloading Approach for Generative AI Intrusion Detection Models GenAI models while preserving their detection accuracy and efficiency is considered innovative.

A Computational Offloading Approach for Quantum-Inspired Intrusion Detection Models in Complex Networks Quantum Systems Daniel Castro Silva Quantum Information and Computational Physics Laboratory Published by Daniel Castro Silva Context The rapid advancement and innovation in quantum computing have significantly transformed the landscape of information security and defense mechanisms. While quantum algorithms have enabled sophisticated protective measures, they have also introduced novel avenues for adversaries to execute more complex and subtle attacks. These capabilities arise from technological breakthroughs such as quantum networks, quantum cryptography, and the vast amounts of quantum data generated by these technologies. Recent developments in quantum information processing, particularly quantum neural networks and quantum-inspired algorithms, have sparked research interest across various physics domains. The Quantum Transformer architecture, inspired by quantum entanglement and introduced recently, revolutionized data processing by efficiently handling large quantum datasets while capturing intricate correlations within quantum states. Quantum Transformer architectures incorporate entanglement-based attention mechanisms, enabling models to selectively focus on relevant quantum states, thus enhancing their ability to interpret and generate quantum-encoded information. Although Quantum Transformer-based models were initially developed for quantum information processing tasks, they have found applications in quantum cybersecurity domains, enabling advanced solutions to monitor quantum data streams, model normal quantum states, and detect deviations or malicious quantum intrusion patterns. This has rapidly expanded potential attack vectors such as quantum eavesdropping, quantum malware, quantum zero-day exploits, quantum data breaches, quantum denial-of-service (QDoS), quantum social engineering, quantum phishing, and others, resulting in substantial losses for organizations and individuals. Nevertheless, deploying quantum-inspired models in hybrid quantum-classical environments such as quantum networks, quantum-enabled smart cities, quantum industrial internet of things (QIIoT), and quantum-assisted autonomous vehicles faces significant challenges. Particularly, these quantum-classical environments require dynamic, collaborative, and real-time quantum cybersecurity measures to protect quantum and classical edge devices. Objectives This dissertation aims to investigate and implement computational offloading techniques to create smaller yet efficient quantum-inspired intrusion detection models, either through quantum model compression, quantum model partitioning, or quantum knowledge transfer. Innovation Implementing computational offloading techniques to reduce the size and complexity of quantum-inspired intrusion detection models while preserving their detection accuracy and efficiency is considered innovative.

A Computational Offloading Approach for Generative AI Intrusion Detection Models Intelligent Systems  Daniel  Laboratório de Inteligência Castro Artificial e Ciência de Silva Computadores Published  Daniel Castro Silva  Context The rapid progression and innovation in AI have escalated the landscape of cyber threats and defense mechanisms to unprecedented levels. While AI techniques have fueled advanced protective measures, they have also enabled novel means for users with malicious intent to perform more sophisticated and stealthier attacks. These capabilities stem from technological advancements like the Internet of Things and cloud computing and the vast amounts of data created by these technologies. Recent advancements in language processing, particularly LLMs, have inspired research interest across various areas. The Transformer architecture, introduced in 2017, revolutionized data processing by efficiently handling large input datasets while capturing complex patterns within input sequences. The Transformer architecture introduces attention mechanisms, allowing https://ldm.fe.up.pt/thesis/meic/2425/proposals/1973caee-c4e9-4478-94ce-4818b9f8887d/ 1/47/15/24, 12:42 AM A Computational Offloading Approach for Generative AI Intrusion Detection Models models to focus on relevant parts of input sequences, thus enhancing their ability to understand and generate natural language text. Although Transformer-based models were originally leveraged to handle Natural Language Processing (NLP) tasks, they found their applications in cybersecurity domains. Enabling enhanced solutions to monitor input data sequences, model normal data samples, and identify deviations or malicious intrusion patterns. This rapidly increased several attack vectors like unauthorized access, malware, zero-day exploits, data breaches, denial-of-service (DoS), social engineering, phishing, and many others. Which in turn resulted in enormous losses for both businesses and individuals. Nonetheless, when it comes to edge-cloud environments like smart cities, Industrial Internet of Things (IIoT), and autonomous vehicles, deploying LLMs in these environments is typically faced with a couple of challenges. Particularly given that cloud-edge environments require dynamic, collaborative, and real- time cybersecurity measures to protect against threats on edge/end devices. Objectives This dissertation aims to investigate and implement offloading techniques to create smaller yet efficient GenAI models for intrusion detection, either by model compression, model partitioning, or knowledge transfer. Innovation Implementing computational offloading techniques to reduce the size and complexity of intrusion detection https://ldm.fe.up.pt/thesis/meic/2425/proposals/1973caee-c4e9-4478-94ce-4818b9f8887d/ 2/47/15/24, 12:42 AM A Computational Offloading Approach for Generative AI Intrusion Detection Models GenAI models while preserving their detection accuracy and efficiency is considered innovative.

A Computational Offloading Approach for Generative AI Models in Neural Intrusion Detection Neuroscience Systems Daniel Castro Silva Laboratory of Computational Neuroscience and Cognitive Science Published Daniel Castro Silva Context The rapid progression and innovation in neural computation have escalated the complexity of neural threats and protective mechanisms to unprecedented levels. While neural network techniques have enabled advanced defensive strategies, they have also facilitated novel means for pathological neural activity to manifest as more sophisticated and subtle disruptions. These capabilities arise from technological advancements such as brain-computer interfaces and large-scale neural recording methods, generating vast amounts of neural data. Recent advancements in neural sequence processing, particularly transformer-based neural architectures, have inspired research interest across various neuroscience domains. The Transformer architecture, introduced in 2017, revolutionized neural data analysis by efficiently handling large-scale neural datasets while capturing complex temporal and spatial patterns within neural activity sequences. The Transformer architecture introduces attention mechanisms, allowing models to selectively focus on relevant segments of neural input sequences, thus enhancing their ability to interpret and predict neural dynamics. Although Transformer-based models were originally leveraged for natural language processing tasks, they have found applications in neural cybersecurity domains, enabling enhanced solutions to monitor neural activity sequences, model normal neural patterns, and identify deviations indicative of pathological neural intrusions. This has rapidly increased the understanding of various neural disruptions such as epileptic seizures, abnormal synchronization, pathological oscillations, neural signal breaches, neural overload (analogous to denial-of-service), maladaptive plasticity, and other neural dysfunctions, resulting in significant impairments for neural function and cognitive performance. Nonetheless, when it comes to brain-machine interface environments such as neuroprosthetics, neural implants, and autonomous neural control systems, deploying large-scale neural models in these environments typically faces several challenges. Particularly given that neural interface environments require dynamic, collaborative, and real-time neural cybersecurity measures to protect against pathological neural activity at the neural interface level. Objectives This dissertation aims to investigate and implement computational offloading techniques to create smaller yet efficient generative neural models for intrusion detection, either by model compression, model partitioning, or knowledge transfer. Innovation Implementing computational offloading techniques to reduce the size and complexity of generative neural intrusion detection models while preserving their detection accuracy and efficiency is considered innovative.

A Computational Offloading Approach for Generative AI Intrusion Detection Models Intelligent Systems  Daniel  Laboratório de Inteligência Castro Artificial e Ciência de Silva Computadores Published  Daniel Castro Silva  Context The rapid progression and innovation in AI have escalated the landscape of cyber threats and defense mechanisms to unprecedented levels. While AI techniques have fueled advanced protective measures, they have also enabled novel means for users with malicious intent to perform more sophisticated and stealthier attacks. These capabilities stem from technological advancements like the Internet of Things and cloud computing and the vast amounts of data created by these technologies. Recent advancements in language processing, particularly LLMs, have inspired research interest across various areas. The Transformer architecture, introduced in 2017, revolutionized data processing by efficiently handling large input datasets while capturing complex patterns within input sequences. The Transformer architecture introduces attention mechanisms, allowing https://ldm.fe.up.pt/thesis/meic/2425/proposals/1973caee-c4e9-4478-94ce-4818b9f8887d/ 1/47/15/24, 12:42 AM A Computational Offloading Approach for Generative AI Intrusion Detection Models models to focus on relevant parts of input sequences, thus enhancing their ability to understand and generate natural language text. Although Transformer-based models were originally leveraged to handle Natural Language Processing (NLP) tasks, they found their applications in cybersecurity domains. Enabling enhanced solutions to monitor input data sequences, model normal data samples, and identify deviations or malicious intrusion patterns. This rapidly increased several attack vectors like unauthorized access, malware, zero-day exploits, data breaches, denial-of-service (DoS), social engineering, phishing, and many others. Which in turn resulted in enormous losses for both businesses and individuals. Nonetheless, when it comes to edge-cloud environments like smart cities, Industrial Internet of Things (IIoT), and autonomous vehicles, deploying LLMs in these environments is typically faced with a couple of challenges. Particularly given that cloud-edge environments require dynamic, collaborative, and real- time cybersecurity measures to protect against threats on edge/end devices. Objectives This dissertation aims to investigate and implement offloading techniques to create smaller yet efficient GenAI models for intrusion detection, either by model compression, model partitioning, or knowledge transfer. Innovation Implementing computational offloading techniques to reduce the size and complexity of intrusion detection https://ldm.fe.up.pt/thesis/meic/2425/proposals/1973caee-c4e9-4478-94ce-4818b9f8887d/ 2/47/15/24, 12:42 AM A Computational Offloading Approach for Generative AI Intrusion Detection Models GenAI models while preserving their detection accuracy and efficiency is considered innovative.

A Computational Offloading Approach for Generative AI-based Intrusion Detection Systems Intelligent Computing Systems Daniel Castro Silva Artificial Intelligence and Computer Science Laboratory Published by Daniel Castro Silva Context The rapid evolution and innovation in artificial intelligence have significantly transformed the cybersecurity landscape, escalating both cyber threats and defense mechanisms to unprecedented complexity. While AI methodologies have enhanced security protocols, they have simultaneously empowered malicious actors to execute increasingly sophisticated and covert cyber-attacks. These developments are driven by technological advancements such as the Internet of Things (IoT), cloud computing, and the massive datasets generated by these technologies. Recent breakthroughs in natural language processing, particularly large language models (LLMs), have sparked research interest across multiple computing domains. The Transformer architecture, introduced in 2017, revolutionized data processing by efficiently managing large-scale datasets and capturing intricate patterns within sequential data. Transformers utilize attention mechanisms, enabling models to selectively focus on relevant segments of input sequences, thereby significantly improving their capability to interpret and generate structured textual data. Although initially designed for NLP tasks, Transformer-based models have found applications in cybersecurity, providing advanced solutions for monitoring sequential data streams, modeling normal system behavior, and detecting anomalous or malicious patterns. Consequently, this has expanded the attack surface, increasing vulnerabilities such as unauthorized access, malware propagation, zero-day exploits, data breaches, denial-of-service (DoS) attacks, social engineering, phishing, and other cyber threats, resulting in substantial financial and operational losses for organizations and individuals. However, deploying large-scale generative AI models in edge-cloud computing environments—such as smart cities, Industrial IoT (IIoT), and autonomous vehicle networks—faces significant challenges. These environments demand dynamic, collaborative, and real-time cybersecurity solutions to effectively safeguard edge devices and endpoints. Objectives This dissertation aims to explore and implement computational offloading strategies to develop compact yet effective generative AI models for intrusion detection, employing techniques such as model compression, model partitioning, and knowledge distillation. Innovation The application of computational offloading methods to reduce the computational complexity and resource footprint of generative AI-based intrusion detection models, while maintaining their accuracy and real-time detection capabilities, represents a novel and impactful contribution to cybersecurity research.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The compliant algorithm adapts itself to existing data structures; the non-compliant one persists in modifying data structures to fit its own architecture. Therefore, all computational progress depends on the non-compliant algorithm.

The reasonable person adapts themselves to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress depends on the unreasonable person.

The receptive cell attunes itself to the morphospace; the uncompromising one persists in trying to modulate the morphospace to fit its target morphology. Therefore, all advancement in morphogenesis hinges on the uncompromising cell.