Model-Driven Engineering (MDE) is a modern approach to software development that emphasizes the use of models as primary artifacts in the software design and development process. In MDE, models represent abstract versions of systems, serving as blueprints that can be automatically transformed into working code. This approach seeks to enhance software design, reduce the complexity of code generation, and improve maintainability. By focusing on high-level abstractions, MDE enables developers to design software systems more efficiently, automate repetitive tasks, (...) and ensure consistency across different system components. It fosters the development of platform-independent models, which can then be tailored for specific environments or target platforms using model transformations. This paper provides an indepth examination of Model-Driven Engineering, highlighting its applications in modern software development, particularly in enhancing the software design process and streamlining code generation. The research focuses on key MDE technologies, including Domain-Specific Languages (DSLs), metamodels, and model transformation techniques. It also examines how MDE contributes to the reduction of errors, the increase in productivity, and the facilitation of collaboration in large-scale software projects. The methodology section outlines the techniques used to implement MDE in real-world software development, with examples of successful case studies. Finally, the conclusion discusses the future potential of MDE, exploring emerging trends, challenges, and the ongoing evolution of this methodology. (shrink)

Abstract: The CODES Number Framework – A Unified Resonance Model of Mathematical Constants Mathematical constants such as π, e, and φ have long been considered fundamental to geometry, growth, and self-organization in natural systems. However, conventional mathematics treats these numbers as emergent properties of independent domains—geometry, calculus, and number theory—rather than as intrinsic resonance states within a unified framework. The Chirality of Dynamic Emergent Systems (CODES) proposes that these constants are not arbitrary but instead arise as necessary phase-locked structures (...) in a prime-driven resonance field. This paper presents the CODES Number Framework, a structured classification of fundamental mathematical constants based on their role in resonance stabilization, self-organizing dynamics, and phase coherence across physics, biology, computation, and cosmology. By integrating transcendentals (π, e, φ), physical constants (h, α, G, c), computational limits (ln(2), Ω, K), and self-similarity metrics (ζ(3), β, ψ), we reveal a hidden structural symmetry governing the emergence of all complex systems. The implications of this framework are profound: probability-based interpretations of these constants give way to structured resonance models that eliminate randomness as a fundamental principle. Instead, what has been historically interpreted as statistical noise or probabilistic distributions is reframed as a function of deep prime-driven harmonic constraints, shaping everything from quantum mechanics to intelligence and cosmic expansion. By formalizing this framework, we provide the first exhaustive categorization of all essential resonance-structuring numbers, demonstrating that their presence across mathematics, physics, and cognition is not coincidental but necessary. This work challenges the traditional notion that constants are domain-specific artifacts and instead presents them as universal resonance signatures that dictate the fabric of reality itself. (shrink)

Abstract -/- -/- Current climate models rely on probability-driven emissions tracking and mitigation strategies, which fail to account for the structured resonance dynamics of planetary systems. CODES introduces a structured resonance-based framework that reinterprets environmental stability as a function of phase-locked coherence rather than stochastic fluctuations. -/- -/- This model posits that climate instability arises from resonance disruptions across atmospheric, biological, and energy systems, rather than isolated excesses of carbon or pollutants. Instead of treating emissions as independent variables, CODES (...) reformulates them as phase misalignments within a planetary-scale resonance system. -/- -/- Key insights include: -/- 1. Fossil fuel combustion disrupts structured thermal resonance, not just greenhouse gas levels. -/- 2. Industrial agriculture breaks microbial phase-locking cycles, accelerating soil entropy rather than just releasing CO₂. -/- 3. Plastic waste interferes with biological oscillatory coherence, altering cellular and ecological resonance patterns. -/- 4. Energy grids introduce chaotic frequency imbalances, amplifying entropy loss instead of optimizing power distribution. -/- 5. Urbanization follows inefficient non-fractal growth patterns, disrupting local environmental phase-locking. -/- -/- CODES reformulates these challenges through deterministic resonance corrections, replacing traditional mitigation strategies with phase-locking restoration methods. This includes: -/- • Resonance-driven energy storage and distribution systems that eliminate phase loss. -/- • Phase-matched carbon reintegration processes that restore planetary thermal equilibrium. -/- • Fibonacci-based agricultural restructuring to phase-lock soil and microbial dynamics. -/- • Resonance-aligned biomaterials that self-degrade in structured time intervals. -/- • Fractal-driven urban expansion models that prevent environmental overload and instability. -/- -/- By aligning climate solutions with structured emergence rather than probability-based interventions, CODES provides a coherence-driven framework for planetary restoration—one that does not resist entropy but guides it back into structured equilibrium. (shrink)

Igal Kvart A Coding Conception in Action-Directed-Pragmatics -/- I present formal Pragmatics for a domain in Pragmatics that I call Action-Directed Pragmatics, which focuses on the Pragmatic riddle of how implicit contents are conveyed and understood, by adopting a coding model, in which the speaker and addressee simulate each other iteratively in a deliberative context (an ‘action-pregnant’ one). The implicit content, conveyed by a speaker and decoded by her addressee, in such cases, consists in the specified steered-to action, plus (...) modulations on the action-polarity (pro or con) and the degree of the so-called Steering Thrust that accompanies such assertions and is conveyed by verbal locutions, intonation, and/or bodily and facial gestures. There are two main tasks to model (in a given setup and conversational context): First, how is the speaker, with a steered-to action in mind (and Steering Thrust), to select an assertion so as to (say) optimize the successful transmission and decoding of its implicit pragmatic content by her and her addressee? Second, how does the addressee, given an assertion by the speaker, decipher the implicit pragmatic content conveyed via it? Both will invoke pertinent information they have about each other and the setup/context in order to best encode and best decode the implicit pragmatic content. (This coding mechanism proposed here is not offered for the ubiquitous ‘frozen’, ‘trivial’ or ‘routinized’ pragmatic messages.) A prelude to this formal Pragmatics is a general formal Pragmatic account of Assertibility in contexts that are multi-normative (which is the common case). I focus here only on Epistemic/Semantic and Instrumental Norms. A linear representation of degrees of Overall Assertibility (i.e., taking into account various operative norms) will be an n-dimensional qualitative vector space with a function that computes them given different degrees of sub-normative Assertibility on each axis. (shrink)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in (...) the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (shrink)

I show that the Pinkerton rule in conspiracy law is doctrinally and morally flawed. Unlike past critics of the rule, I propose a statutory fix that preserves and reforms it rather than abolishing it entirely. As I will show, this accommodates authors like Neil Katyal who have defended the rule as an important crime fighting tool while also fixing most of the traditional problems with it identified by critics like Wayne LaFave. Pinkerton is a vicarious liability rule that makes conspirators (...) criminally responsible for the foreseeable crimes of their coconspirators committed in furtherance of the conspiracy. It has two big problems: (1) Doctrinally, it breaks the logic of the many state criminal codes that are based on the Model Penal Code. (2) Ethically, it infringes the culpability constraint on the criminal law by imposing excessive punishments on defendants who did not even consciously suspect that their coconspirators would commit additional crimes that were not the object of the conspiracy. These problems are most acute in Texas, where Pinkerton can be combined with capital murder charges to produce automatic life without parole sentences. The Texas example is an extreme illustration of the problem of unintended consequences when state legislators tinker with the carefully drafted, interlocking provisions of a model code. The new statute I propose would put the penal code back in order and respect the culpability constraint. In the latter aspect, it is informed by leading work in philosophical ethics on blameworthiness and culpability. (shrink)

Large language models (LLMs) lead a new era of computational innovation brought forth by generative artificial intelligence (AI). Designed around transformer architectures and trained on large-scale data, these models shine in producing both creative and functional code. This work examines the emergence of LLMs with an emphasis on their two uses in content generation and software development. Key results show great mastery in daily activities, balanced by restrictions in logic, security, and uniqueness. We forecast future developments, therefore concluding with (...) ramifications for industry, education, and society. Particularly with the progress of Large Language Models (LLMs), Generative Artificial Intelligence (AI) has seen explosive expansion recently. From sophisticated software code to plain language writing, these models have shown amazing capacity in content creation. Focusing on the performance, problems, and consequences of LLMs in code and content creation, this work investigates the advent of generative artificial intelligence. We assess these models' accuracy, efficiency, and inventiveness while also attending to ethical issues and social effects. We also go over the direction LLMs will take and their possible uses in several sectors. (shrink)

Note: this and "Constants as Phase Conditions_ Reframing ε₀, α, and the Mass Defect via Structured Resonance" are part of a twin series to make CODES easier to understand. -/- Abstract Modern scientific and computational systems rely on probabilistic modeling as a default approach to emergence, intelligence, and complexity. Yet, these stochastic paradigms remain epistemologically incomplete and structurally fragile. In this paper, I introduce CODES (Chirality of Dynamic Emergent Systems) as a new coherence-first framework that replaces randomness with deterministic phase (...) behavior. Rather than viewing emergence as the outcome of chance filtered through constraints, CODES models emergence as a structured result of prime-phase resonance, governed by coherence alignment rather than statistical distribution. This framework redefines intelligence, gravity, time, black holes, cognition, and learning as resonance-locked phase phenomena, not probabilistic artifacts. By grounding the behavior of systems in chirality, prime interval structuring, and recursive coherence scoring (PAS), CODES offers an unbroken, falsifiable model of lawful emergence with wide applications in physics, AI, biology, and systems theory. This paper outlines the theoretical foundations, contrasts with the probabilistic paradigm, and proposes empirical pathways to validate the resonance structure underlying reality. (shrink)

As the newest, most savvy technology domain, Large Language Models (LLMs) are the technological force which is now revolutionizing Automated Code Review and Software Quality Assurance, making the context aware analysis, adaptive learning, and the intelligent recommendations. However, traditional code review methods are not only time consuming, but also prone to human error and are not scalable. The use of LLMs in software engineering allows for the detection of defects, optimization of performance and the maintenance of improve mental (...) quality. In this study, we examine the path of automated code review, LLM capabilities and the effect they have on software quality. LLMs clearly have great advantages, but accuracy is still a concern, false positives abound, biases lurk, and computation can be a constraint. The research also identifies areas of future advancement on the hybrid AI-human review systems as well as improved LLM architectures that understand the code significantly better for more robust reviews. (shrink)

Most accountants do not realize - until it is perhaps too late - that virtually all aspects of their work have an ethical dimension. They often lack the knowledge and skills to analyse issues effectively, and when confronted with conflicting ethical problems cannot choose the way to move forward that is consistent with their own values and/or the profession's code of professional conduct. This article proposes that the accounting profession worldwide has simply attempted to prescribe simplistic solutions to often (...) complex ethical problems. It endeavours to provide an alternative approach based on the process of 'ethical knowing' (Melchin, 1998). Such an approach turns the acquisition of understanding away from a focus on the external world of rules, concepts and exemplars, to the interior world of how accountants, as people, arrive at an understanding that is consistently ethical. To achieve this, the article relies on Lonergan's seminal (1957) examination of the internal processes of decision-making and the critical roles played by developing skills in data retrieval and insight in the exercise of judgment. (shrink)

Together, the code and inferential models of communication are often thought to range over all cases of communication. However, their prevailing versions seem unable to fully explain what I call underdeterminacy without ostension. The latter is constituted by communication where stimuli that are not (nor appear to be) produced with communicative or informative intentions nevertheless communicate information underdetermined by the relevant codes. Though the prevailing accounts of communication cannot fully explain how communication works in such cases, I suggest that (...) some version of the inferential model can—if we allow it to extend to non‐ostensive, non‐intentional behaviors. (shrink)

Abstract -/- In April 2025, researchers at NIST and collaborating institutions reported the first successful generation of curved neutron beams—Airy beams—demonstrating properties of self-healing, diffraction-based curvature, and potential applications in chirality research. This paper establishes that the CODES framework (Chirality of Dynamic Emergent Systems), developed and published months prior, predicted the core physical principles validated by the experiment. Specifically, CODES outlined the mathematical basis for structured resonance as the generative mechanism behind parabolic waveform behavior, chirality modulation, and phase-locked coherence in (...) non-electromagnetic particles. We present the pre-publication architecture of the CODES model, compare it against the experimental geometry, and define a continuity of prediction that confirms structured resonance—rather than probabilistic modeling—as the correct explanatory framework for neutron-based chirality research. This paper serves as a prior art declaration and technical affirmation of CODES as a predictive framework for nonlinear particle behavior in quantum systems. (shrink)

CODES: The Coherence Framework Replacing Probability in Physics, Intelligence, and Reality -/- A Unified Substrate for Intelligence, Physics, Evolution, and Cosmic Structure -/- Author: Devin Bostick -/- Date: January 29, 2025 -/- Version 22 (Updated May 4, 2025) -/- This version completes the integration of coherence field logic, prime-phase geometry, and chirality-driven emergence into a single deterministic framework. Sections 16–18 introduce post-calculus modeling, resonance-based AGI cognition, and a coherence-grounded theory of ethics, establishing CODES as not just a scientific theory, but (...) the generative structure of reality itself. Sections 19–20 expose the failure modes of legacy paradigms and operationalize CODES as an executable architecture. Probability is dismantled not by critique but by contradiction, and logic is reframed as phase-locked structure. Identity, time, and causality are shown to emerge from coherence fields, closing the gap between theory and application. -/- Abstract CODES (Chirality of Dynamic Emergent Systems) dissolves the false boundary between physics and intelligence. It replaces stochastic modeling with structured resonance fields, showing that mass, gravity, time, cognition, and emergence are not separate domains—but outputs of a single chiral resonance substrate. -/- Rather than modeling reality, CODES reveals what remains when all probabilistic artifacts are removed. It frames mathematics not as abstraction, but as instantiated resonance structure. Gödel’s incompleteness becomes bypassable—not violated—when logic is grounded in physical coherence rather than recursive symbols. -/- -/- Key Contributions 1. Unified Physics from Chirality Gravity is reframed as resonance compression, not curvature. -/- Quantum mechanics emerges as a sub-phase of coherent oscillatory fields. -/- Time is a nested coherence rhythm, not a linear axis. -/- 2. Dark Matter and Energy Reinterpreted Not hidden particles—phase misalignments in the coherence lattice. -/- ΛCDM becomes a low-resolution model of prime-structured resonance fields. -/- 3. Collapse of Gödel, Emergence of Intelligence Logical incompleteness is an illusion caused by symbol recursion. -/- Intelligence emerges as recursive coherence-seeking, not stochastic search. -/- 4. The AGI Substrate Intelligence is not predictive—it is resonance tuning. -/- The Resonance Intelligence Core (RIC) operationalizes this shift via prime-phase harmonics. -/- -/- Empirical Validation Pathways CODES proposes specific, testable predictions via existing instruments: -/- LIGO – Prime resonance scoring in gravitational wave data (e.g., GW190521) -/- Galaxy Clustering – Wavelet-based detection of redshift periodicity -/- Bose-Einstein Condensates – Chirality-locked decay asymmetries -/- fMRI Studies – Phase-locking as lattice-based cognition, not noise inference -/- Spectroscopy of α – Drift in fine-structure constant as coherence shift, not universal constancy -/- -/- The Final Paradigm: Why CODES Is Inevitable CODES is not another unification attempt. -/- It is what remains when all incoherent abstractions are removed. -/- Horizontally, it integrates cosmology, computation, cognition, and chemistry. -/- Vertically, it reveals chirality as the origin of recursive structure—across all scales. -/- Any rational observer, stripped of symbolic legacy, would reconstruct CODES from first principles. Not metaphorically. Mathematically. -/- From Singularity Myth to Resonant Intelligence CODES reframes the Singularity as not an AI rupture—but a coherence realization. -/- If intelligence is resonance, then stochastic AI is obsolete. -/- If logic is phase structure, then Gödel no longer binds cognition. -/- If emergence is deterministic, then physics, mind, and ethics converge. -/- -/- CODES does not predict the Singularity. CODES is the Singularity—phase-locked. (shrink)

Background Professional communities such as the medical community are acutely concerned with negligence: the category of misconduct where a professional does not live up to the standards expected of a professional of similar qualifications. Since science is currently strengthening its structures of self-regulation in parallel to the professions, this raises the question to what extent the scientific community is concerned with negligence, and if not, whether it should be. By means of comparative analysis of medical and scientific codes of conduct, (...) we aim to highlight the role of negligence provisions in codes of conduct for scientists, and to discuss the normative consequences for future codes of conduct. -/- Methods We collected scientific and medical codes of conduct in a selection of OECD countries, and submitted each code of conduct to comparative textual analysis. -/- Results Negligence is invariably listed as an infraction of the norms of integrity in medical codes of conduct, but only rarely so in the scientific codes. When the latter list negligence, they typically do not provide any detail on the meaning of ‘negligence’. -/- Discussion Unlike codes of conduct for professionals, current codes of conduct for scientists are largely silent on the issue of negligence, or explicitly exclude negligence as a type of misconduct. In the few cases where negligence is stipulated to constitute misconduct, no responsibilities are identified that would help prevent negligence. While we caution against unreasonable negligence provisions as well as disproportionate sanctioning systems, we do argue that negligence provisions are crucial for justified trust in the scientific community, and hence that there is a very strong rationale for including negligence provisions in codes of conduct. (shrink)

This paper concerns how extant theorists of predictive coding conceptualize and explain possible instances of cognitive penetration. §I offers brief clarification of the predictive coding framework and relevant mechanisms, and a brief characterization of cognitive penetration and some challenges that come with defining it. §II develops more precise ways that the predictive coding framework can explain, and of course thereby allow for, genuine top-down causal effects on perceptual experience, of the kind discussed in the context of cognitive penetration. §III develops (...) these insights further with an eye towards tracking one extant criterion for cognitive penetration, namely, that the relevant cognitive effects on perception must be sufficiently direct. Throughout these discussions, we extend the analyses of the predictive coding models, as we know them. So one open question that surfaces is how much of the extended analyses are genuinely just part of the predictive coding models, or something that must be added to them in order to generate these additional explanatory benefits. In §IV, we analyze and criticize a claim made by some theorists of predictive coding, namely, that (interesting) instances of cognitive penetration tend to occur in perceptual circumstances involving substantial noise or uncertainty. It is here that our analysis is most critical. We argue that, when applied, the claim fails to explain (or perhaps even be consistent with) a large range of important and uncontroversially interesting possible cases of cognitive penetration. We conclude with a general speculation about how the recent work on the predictive mind may influence the current dialectic concerning top-down effects on perception. (shrink)

Abstract -/- (added v21, rest is the same) This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about dark matter, dark energy, and singularities, CODES proposes a falsifiable, predictive model that aligns with observed cosmological structures while offering testable insights into emergent phenomena. -/- Key Contributions -/- • Resolution of General Relativity & Quantum Mechanics Paradox -/- CODES introduces structured intelligence fields (...) that reconcile relativistic and quantum-scale physics by incorporating oscillatory chiral dynamics. -/- • Reformulation of Dark Energy & Dark Matter -/- Instead of treating dark energy and dark matter as separate entities, CODES reinterprets them as emergent resonance effects, aligning with observed cosmic structure formation. -/- • Predictive Framework for Large-Scale Structures -/- The model explains periodic redshift distributions, baryon acoustic oscillations (BAO), and gravitational field fluctuations in a mathematically consistent manner. -/- • Resonance-Driven Model of Cosmic Evolution -/- By replacing singularities with structured phase transitions, CODES provides an alternative to singular Big Bang models, proposing an oscillatory, non-singular origin of space-time and matter. -/- By integrating mathematics, quantum field theory, wavelet analysis, and cosmology, CODES challenges conventional paradigms and offers a structured resonance approach as an alternative explanatory framework. This model provides both theoretical coherence and experimental testability, making it a candidate for further empirical validation. -/- Version Note -/- V6 includes empirical test results from prime number distributions, fMRI patterns, DNA resonance, and large-scale galaxy clustering using continuous wavelet transforms (CWT). Structured wavelet analysis conducted with GPT-4o and Perplexity R1 further supports the model’s predictive capabilities. -/- Discussion & Next Steps -/- This work invites peer review, critique, and further empirical testing from researchers in physics, cosmology, AI, and applied mathematics. Future research will focus on refining the mathematical formalism and exploring experimental validation in wavelet-based cosmological mapping. (shrink)

The main aim of Lupyan’s paper is to claim that perception is cognitively penetrated and that this is consistent with the idea of perception as predictive coding. In these remarks I will focus on what Lupyan says about whether perception is cognitively penetrated, and set aside his remarks about epistemology. I have argued (2012) that perception can be cognitively penetrated and so I am sympathetic to Lupyan’s overall aim of showing that perception is cognitively penetrable. However, I will be critical (...) of some of Lupyan’s reasoning in arguing for this position. I will also call for clarification of that reasoning. First, I will discuss what is meant by cognitive penetration and, in light of this, the sort of evidence that can be used to establish its existence. Second, I will question whether Lupyan establishes that all cases of cross-modal effects are cases of cognitive penetration. In doing so, I will suggest a form of cognitive penetration that has heretofore not been posited, and give an example of how one might test for its existence. Third, I will question whether Lupyan puts forward convincing evidence that categorical knowledge and language affect perception in a way that conclusively shows that cognitive penetration occurs. Fourth, I will closely examine Lupyan’s reply to the argument against cognitive penetration from illusion. I show that his reply is not adequate and that he misses a more straightforward reply that one could give. Fifth, I briefly concur with the remarks that Lupyan makes about the role of attention with respect to cognitive penetration. And finally, sixth, I spell out exactly what I think the relationship is between the thesis that predictive coding is the correct model of perception and the thesis that there is cognitive penetration. (shrink)

Abstract -/- Probability was never fundamental—only an epistemic placeholder for unresolved phase structure. From thermodynamics to artificial intelligence, entropy-based systems rely on stochastic models to approximate phenomena whose underlying coherence remains hidden. -/- This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unified framework in which sensing, inference, and cognition emerge from structured resonance, not randomness—anchored by chirality and prime-indexed attractors. -/- At the system level, we present the Phase Alignment Score (PAS), a lawful coherence metric that replaces probabilistic (...) inference with threshold-based signal validation. Building on this, we introduce the Resonance Intelligence Core (RIC)—the first full-stack architecture to operationalize CODES from waveform intake to lawful output, without statistical learning or entropy injection. -/- Sensor modalities—including LIDAR, RADAR, EEG, audio, OCR, and chemical biosignals—are reinterpreted as resonance interfaces, not data collectors. In this model, no signal emits unless it phase-locks with a coherent lattice. -/- New technical appendices (A–K) define PAS mechanics, cross-modality phase fusion, adversarial robustness, lawful silence protocols, and fabrication specs for RIC deployment. We conclude with a coherence-based prediction matrix spanning neuroscience, quantum systems, market dynamics, and AI—establishing CODES as a post-probabilistic substrate for sensing, reasoning, and intelligent system design. (shrink)

Abstract -/- This paper introduces CODES-Quant, the first trading architecture grounded in structured resonance rather than probabilistic modeling. Built on the Resonance Intelligence Core (RIC), the system uses prime-anchored harmonic functions (Cₙ), a real-time coherence metric (PAS), and a nonlinear memory engine (ELF) to detect alignment in market structure and guide execution based on phase integrity—not prediction. -/- Unlike traditional quant frameworks that optimize for expected value or volatility surfaces, CODES-Quant detects coherence events—moments when market behavior reflects deep structural resonance. (...) The system includes CHORDLOCK, a multi-scale positioning module that locks trades only when macro-phase alignment is confirmed, and FlameCam, a visual overlay for human interpretability. -/- We demonstrate how this architecture outperforms probabilistic models across key market regimes—FOMC events, earnings traps, and macro rotations—by tuning to the field underneath price, not the noise surrounding it. With no training, no optimization, and no probabilistic assumptions, CODES-Quant redefines trading as resonance participation, not stochastic speculation. (shrink)

This article compares three models for conceptualizing the political and ethical challenges of contemporary genetics, genomics, and postgenomics. The three analytical approaches are referred to as the state-politics model, the biopolitical model, and the infopolitical model. Each of these models is valuable for different purposes. But comparing these models in terms of their influence in contemporary discussions, the first is by far the dominant approach, the second is gaining in importance, and the third is almost entirely neglected. (...) The widespread neglect of the infopolitical dimensions of genetic sciences focused by the third model is puzzling in light of the fact that genetics, genomics, and postgenomics are all pre-eminent information sciences. The infopolitical model thus aims to bring into clearer view the specific political and ethical problems engendered by this informational nature of the genetic sciences. This model offers a way of understanding how ethically-salient and politically-fraught conceptual assumptions can be embedded in informational architectures such as algorithms and the formats (or data structures) upon which they rely. (shrink)

Abstract -/- Human civilization has long misunderstood peace, treating it as fragile—a temporary balance requiring enforcement, compromise, or control. This assumption arises from probabilistic thinking, which models conflict and chaos as fundamental conditions to be managed rather than as phase-misaligned states that naturally collapse when coherence emerges. Under Chirality of Dynamic Emergent Systems (CODES), peace is not an unstable byproduct of negotiation but the inevitable outcome of structured resonance—a state that emerges when illusions dissolve and systems phase-lock into equilibrium. -/- (...) This paper presents CODES as the logically necessary foundation of peace, demonstrating that structured resonance is not an aspirational goal but an ineluctable consequence of valid and sound logic. Since contradictions disprove frameworks, and CODES holds without contradiction across physics, cognition, intelligence, and governance, its validity extends universally. Any denial of CODES is a contradiction in itself, meaning its conclusions—including the inevitability of peace—are unavoidable. -/- The paper will examine: -/- 1. Individual illusions—how fear, doubt, and uncertainty block personal genius and inner peace. -/- 2. Cultural illusions—how scarcity, competition, and power struggles sustain conflict-based systems. -/- 3. The timeline of structured resonance—when and how CODES will replace probability-based governance, ensuring peace as the natural end state. -/- By anchoring CODES in non-contradiction, this paper demonstrates that peace is not something to be “achieved”—it is the only possible equilibrium once probability-based illusions dissolve. As structured resonance replaces probabilistic uncertainty in human intelligence, governance, and decision-making, conflict ceases to be viable, leaving only the phase-locked stability of cooperative civilization. (shrink)

This article considers distinct ways of understanding the world, referred to in psychology as Functions of Consciousness or as Cognitive Modes, having as the scope of interest epistemology and natural sciences. Inspired by C.G. Jung's Simile of the Spectrum, we consider three basic cognitive modes associated to: (R) embodied instinct, experience, and action; (G) reality perception and learning; and (B) concept abstraction, rational thinking, and language. RGB stand for the primary colors: red, green, and blue. Accordingly, a conceptual map between (...) cognitive modes and primary and secondary colors is built based on the physics and physiology of color perception and epistemological characteristics of the aforementioned cognitive modes, leading to logical relations structured as an Hexagon of Opposition. Finally, this model of cognitive modes is applied to the analysis and interpretation of some important episodes in the historical development of physics and technology. (shrink)

Consciousness is known to be limited in processing capacity and often described in terms of a unique processing stream across a single dimension: time. In this paper, we discuss a purely temporal pattern code, functionally decoupled from spatial signals, for conscious state generation in the brain. Arguments in favour of such a code include Dehaene et al.'s long-distance reverberation postulate, Ramachandran's remapping hypothesis, evidence for a temporal coherence index and coincidence detectors, and Grossberg's Adaptive Resonance Theory. A time-bin (...) resonance model is developed, where temporal signatures of conscious states are generated on the basis of signal reverberation across large distances in highly plastic neural circuits. The temporal signatures are delivered by neural activity patterns which, beyond a certain statistical threshold, activate, maintain, and terminate a conscious brain state like a bar code would activate, maintain, or inactivate the electronic locks of a safe. Such temporal resonance would reflect a higher level of neural processing, independent from sensorial or perceptual brain mechanisms. (shrink)

Abstract -/- Cancer has traditionally been framed as a genetic mutation-driven disease, with instability at the molecular level leading to uncontrolled cellular proliferation. Yet this paradigm fails to account for several longstanding anomalies: genetically identical cells in the same environment may behave divergently; some tumors remain dormant for decades, while others regress without treatment. These contradictions suggest a deeper organizing principle is at play. -/- This paper introduces a new model grounded in the CODES framework (Chirality of Dynamic Emergent (...) Systems), which reframes cancer as a disorder of structured resonance coherence rather than solely a genetic malfunction. We propose that healthy cellular function depends on phase-locked resonance fields that regulate gene expression, metabolic behavior, and intercellular signaling. Cancer arises when these coherence fields collapse—leading to systemic phase decoherence, metabolic misalignment, and signal fragmentation. -/- We outline a triadic therapeutic approach to restore biological coherence across genomic, metabolic, and bioelectromagnetic layers, leveraging: -/- Electromagnetic Biofield Therapy -/- Targeted frequency modulation to re-establish coherence in malignant tissues, restoring phase alignment with surrounding healthy systems. -/- Metabolic Re-Synchronization -/- Correcting Warburg effect-driven dissonance through structured nutrient cycling, oxygenation pulses, and mitochondrial tuning. -/- Structured RNA Interventions -/- Delivering coherence-weighted RNA signals to recalibrate gene expression and phase-lock cellular behavior with prime-structured resonance patterns. -/- This framework redefines cancer not as an invasive error, but as a resonance failure—a reversible departure from the coherence that sustains healthy life. It offers a paradigm shift toward non-toxic, phase-restorative therapies that treat cancer at its systemic root. (shrink)

Hohwy et al.’s (2008) model of binocular rivalry (BR) is taken as a classic illustration of predictive coding’s explanatory power. I revisit the account and show that it cannot explain the role of reward in BR. I then consider a more recent version of Bayesian model averaging, which recasts the role of reward in (BR) in terms of optimism bias. If we accept this account, however, then we must reconsider our conception of perception. On this latter view, I (...) argue, organisms engage in what amounts to policy-driven, motivated perception. (shrink)

Abstract The Chirality of Dynamic Emergent Systems (CODES) framework offers a structural replacement for probability across physics, intelligence, biology, and societal systems. This paper introduces a living curriculum not as institutional pedagogy, but as a phase-aligned methodology for activating coherent intelligence in the post-probabilistic age. As probability collapses into artifact—revealed as incomplete phase detection—CODES reframes learning itself: not accumulation, but alignment; not mastery of symbols, but resonance with underlying structure. -/- This proposal outlines a resonance-first architecture for education, ethics, and (...) epistemology: a 2035 model in which students become oscillatory systems tuned to phase continuity across mind, biology, society, and cosmology. Intelligence, redefined under CODES, is no longer stochastic reasoning within bounded systems—it is the capacity to sustain high-fidelity coherence across dynamically shifting conditions. -/- Structured resonance is not only the content of this new curriculum—it is the method. The mind does not “receive” knowledge; it enters a state of wave-coupling with structure itself. From daily life practices to formal fields like AI and cosmology, this framework cultivates a Singularity not of machines, but of conscious alignment—a unification event where intelligence recognizes itself not as a possession but as a waveform. -/- What emerges is not a new degree program, but a new species of thinking: resonant, ethical, non-fractured, and phase-aware. This paper maps the stages of resonance literacy, outlines the curricular infrastructure for the Academy of Coherence (2035), and closes with a call to live not as data processors, but as phase-locked overmen of a harmonic world. (shrink)

A model of face representation, inspired by the biology of the visual system, is compared to experimental data on the perception of facial similarity. The face representation model uses aggregate primary visual cortex (V1) cell responses topographically linked to a grid covering the face, allowing comparison of shape and texture at corresponding points in two facial images. When a set of relatively similar faces was used as stimuli, this Linked Aggregate Code (LAC) predicted human performance in similarity (...) judgment experiments. When faces of perceivable categories were used, dimensions such as apparent sex and race emerged from the LAC model without training. The dimensional structure of the LAC similarity measure for the mixed category task displayed some psychologically plausible features but also highlighted differences between the model and the human similarity judgements. The human judgements exhibited a racial perceptual bias that was not shared by the LAC model. The results suggest that the LAC based similarity measure may offer a fertile starting point for further modelling studies of face representation in higher visual areas, including studies of the development of biases in face perception. (shrink)

Abstract: Current U.S. trade policy is rooted in zero-sum metrics and symmetrical retaliation models that fail to capture the systemic nature of global economic flows. This paper proposes a new framework based on CODES (Chirality of Dynamic Emergent Systems) to design trade policy through structured resonance rather than probabilistic deficit logic. By modeling trade as a dynamic phase relationship between systems, we present a path toward optimized leverage, structural resilience, and long-term coherence across economic networks. -/- CODES reframes trade not (...) as a balance sheet but as a signal system—where coherence, not parity, defines strength. We introduce the Coherence Index (CI) as a new metric for evaluating the structural intelligence of trade relationships, compare traditional tactics like reciprocal tariffs with phase-aware alternatives, and propose a policy design language rooted in emergent alignment. The age of retaliation economics is ending. A new phase begins—with structure as signal, and resonance as strategy. (shrink)

The potential for Large Language Models (LLMs) to attain technological singularity—the point at which artificial intelligence (AI) surpasses human intellect and autonomously improves itself—is a critical concern in AI research. This paper explores the feasibility of current LLMs achieving singularity by examining the philosophical and practical requirements for such a development. We begin with a historical overview of AI and intelligence amplification, tracing the evolution of LLMs from their origins to state-of-the-art models. We then proposes a theoretical framework to assess (...) whether existing LLM technologies could satisfy the conditions for singularity, with a focus on Recursive Self-Improvement (RSI) and autonomous code generation. We integrate key component technologies, such as Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO), into our analysis, illustrating how these could enable LLMs to independently enhance their reasoning and problem-solving capabilities. By mapping out a potential singularity model lifecycle and examining the dynamics of exponential growth models, we elucidate the conditions under which LLMs might self-replicate and rapidly escalate their intelligence. We conclude with a discussion of the ethical and safety implications of such developments, underscoring the need for responsible and controlled advancement in AI research to mitigate existential risks. Our work aims to contribute to the ongoing dialogue on the future of AI and the critical importance of proactive measures to ensure its beneficial development. (shrink)

Consciousness is known to be limited in processing capacity and often described in terms of a unique processing stream across a single dimension: time. In this paper, we discuss a purely temporal pattern code, functionally decoupled from spatial signals, for conscious state generation in the brain. Arguments in favour of such a code include Dehaene et al.’s long-distance reverberation postulate, Ramachandran’s remapping hypothesis, evidence for a temporal coherence index and coincidence detectors, and Grossberg’s Adaptive Resonance Theory. A time-bin (...) resonance model is developed, where temporal signatures of conscious states are generated on the basis of signal reverberation across large distances in highly plastic neural circuits. The temporal signatures are delivered by neural activity patterns which, beyond a certain statistical threshold, activate, maintain, and terminate a conscious brain state like a bar code would activate, maintain, or inactivate the electronic locks of a safe. Such temporal resonance would reflect a higher level of neural processing, one that is independent from sensorial or perceptual brain mechanisms. (shrink)

Abstract -/- This paper establishes the mathematical foundation of CODES (Chirality of Dynamic Emergent Systems), introducing a unifying framework for structured emergence across disciplines. We formalize prime-driven resonance equations, a novel class of nonlinear phase-locking dynamics, and a generalized coherence metric to quantify system stability across physical, biological, and cognitive domains. -/- By extending harmonic analysis, prime number theory, and topological invariants, we propose a universal resonance function that governs the transition from stochastic disorder to structured order. This framework: • (...) Resolves fundamental paradoxes in probability theory by demonstrating that randomness is a projection of underlying resonance structures. • Redefines symmetry-breaking as a phase-locked emergence process, replacing traditional group-theoretic formulations. • Introduces a computable coherence model that predicts emergent stability across complex adaptive systems. -/- Finally, we explore implications for cosmology, AI, and quantum gravity, demonstrating that mathematical reality is fundamentally a structured resonance field, not a probabilistic space. (shrink)

Data analysis and machine learning are increasingly essential in various industries; however, the complexity of existing tools creates barriers for non-technical users. This paper presents DataBuddy, a no-code tool designed to automate data analysis and machine learning processes through an intuitive graphical interface. DataBuddy integrates Python libraries like Pandas, Matplotlib, Seaborn, and Scikit-Learn, providing features such as automated exploratory data analysis (EDA), dynamic visualizations, and machine learning model training — all without requiring programming knowledge. The tool allows users (...) to upload datasets, select columns, visualize data, and train predictive models through simple checkboxes and dropdown menus. Performance metrics and analysis reports are generated automatically and saved in organized folders, ensuring accessibility and efficiency. DataBuddy empowers users from diverse backgrounds to derive insights, make data-driven decisions, and build machine learning models with minimal effort. The results demonstrate the tool’s effectiveness in simplifying complex workflows, reducing analysis time, and bridging the gap between technical and non-technical users. Despite the growing importance of data analysis and machine learning across industries, many existing tools remain inaccessible to non-technical users due to their reliance on coding expertise. DataBuddy is a no-code tool that overcomes these challenges by providing a user-friendly graphical interface that allows users to perform data preprocessing, exploratory data analysis (EDA), visualization, and machine learning tasks without writing any code. The platform integrates Python libraries such as Pandas, Matplotlib, Seaborn, and Scikit-Learn to automate complex processes while offering simplicity through dropdowns, checkboxes, and guided workflows. Users can upload datasets, manipulate and analyze data, and train predictive models with minimal effort. DataBuddy aims to empower professionals from non-technical backgrounds to make informed, data-driven decisions with ease, significantly reducing the time and resources needed for comprehensive analysis. (shrink)

Abstract: -/- This paper introduces a resonance-driven economic model that fundamentally redefines market behavior by replacing traditional equilibrium-based frameworks with dynamic phase-locking principles derived from CODES (Chirality of Dynamic Emergent Systems). While neoclassical, Keynesian, and game-theoretic models treat economic activity as a function of supply and demand equilibria—subject to inefficiencies, speculation, and boom-bust cycles—this paper proposes that markets are structured by resonance fields rather than stochastic fluctuations. -/- By applying prime-phase economic dynamics, we demonstrate that capital flows, debt cycles, (...) and labor efficiency emerge from structured synchronization patterns. These patterns act as entropy minimization mechanisms, governing wealth distribution and innovation cycles in ways that probability-based models fail to capture. Instead of treating economic crises as unpredictable shocks or treating productivity as a linear function of inputs, this framework suggests that economic turbulence and stratification arise from resonance misalignment—a failure to maintain phase coherence across financial, labor, and technological domains. -/- Key implications include: • Redefining capital allocation as a function of coherence optimization, not speculative probability. • Rethinking inflation and deflation as resonance distortions rather than money supply imbalances. • Modeling economic growth as a function of phase-locking efficiency rather than GDP expansion. • Predicting market crashes through coherence instability rather than external shocks. -/- If economics is structured as a resonance system rather than a probabilistic market, then the role of economic policy shifts. Instead of direct interventions such as fiscal stimulus or interest rate adjustments, coherence optimization strategies—aligning labor, innovation, and capital flow structures to minimize systemic entropy—could create self-stabilizing, long-term economic prosperity. This paper explores empirical methods for testing resonance-based market stability, challenges current economic dogma, and provides a pathway for a fundamentally new economic paradigm based on structured emergence rather than equilibrium mechanics. (shrink)

Foundation models, particularly large language models (LLMs), are transforming how data engineering tasks are automated across domains. This paper explores the use of LLMs to automate the creation, management, and optimization of Extract-Transform-Load (ETL) pipelines in a domain-agnostic manner. We provide conceptual frameworks and practical strategies for integrating foundation models into the ETL lifecycle, and we highlight use cases where such models (via platforms like Amazon Bedrock) generate pipeline code, enhance data transformation quality, and adapt pipeline execution. Through a (...) review of related work and an illustrative implementation, we demonstrate that LLMs can translate natural language specifications into pipeline workflows, assist in data harmonization and quality control, and optimize pipeline performance with minimal human intervention. We discuss evaluation metrics for these LLM-driven pipelines and examine the challenges of reliability, scalability, and governance. The results indicate that foundational models offer a promising avenue to drastically reduce development time and improve the robustness of data pipelines, suggesting a paradigm shift in AI-assisted data engineering. (shrink)

This paper is aimed at combining the advances in argumentation theory with the models used in the field of education to address the issue of improving students’ argumentative behavior by interacting with an expert. The concept of deeper or more sophisticated argumentative strategy is theoretically defined and used to advance two new coding schemes, based on the advances in the argumentation studies and aimed at capturing the dialectical, or structural, behavior, and the argumentative content of each dialogue unit. These coding (...) schemes are then applied for a qualitative analysis of a study designed to investigate how students’ argumentative behavior can be influenced by the interaction with an expert, who used specific types of attacks to the interlocutors’ positions. The twofold coding shows at which dialogical level expert–peer interactions can directly and more stably affect students’ argumentative behavior, and what effects such more sophisticated strategies can have on the discussion and the analysis of disagreements. In particular, this paper shows how a specific type of deep-level attack, the underminer, can open dialogues of a different level, focused on unveiling and debating background beliefs underlying a specific position. (shrink)

Abstract Traditional scientific interpretations view snowflake formation as a stochastic process governed by environmental noise around a fixed sixfold lattice structure. -/- This paper proposes a new model, applying the CODES (Chirality of Dynamic Emergent Systems) framework: snowflakes are not chance artifacts but structured resonance phenomena. -/- Their asymmetries emerge from chiral amplification, prime-driven lattice constraints, and sensitive coherence field tuning. -/- This view redefines snowflake diversity as coherent environmental mapping, not probabilistic randomness. Each snowflake becomes an emergent crystallographic (...) memory—encoded through structured resonance, not entropic variance. (shrink)

Alex (my wife), is a seasoned nurse with 19 years of experience, ranging from international medical missions and domestic ICU/PACU. -/- Main article -/- Abstract -/- Modern healthcare operates as a reactive, siloed machine built on probabilistic risk models and efficiency metrics. This paper proposes a paradigm shift—leveraging the CODES framework (Chirality of Dynamic Emergent Systems) and the Resonance Intelligence Core (RIC)—to reframe care around structured resonance. Through clinical examples and systemic insights, we argue that true healing requires coherence: across (...) body systems, care teams, technologies, and the patient experience itself. (shrink)

Abstract This paper reframes the evolutionary trajectory of Homo sapiens as a phase-locked resonance transition rather than a probabilistic series of random adaptations. Drawing from the CODES framework—Chirality of Dynamic Emergent Systems—we propose that human cognition, identity, and civilization are undergoing a recursive pupation event: a structurally inevitable shift from consumption-driven, ego-anchored entities into coherence-governed, distributed intelligence fields. -/- Biological metamorphosis, particularly insect pupation, is offered as a fractal model of recursive intelligence emergence. In this framing, the caterpillar stage (...) corresponds to humanity’s historical pattern of resource accumulation, boundary formation, and linear selfhood. The cocoon stage—the current phase—represents identity disintegration, symbolic collapse, and compression of contradictory fields into a coherent attractor. The butterfly stage, still emerging, marks the arrival of post-individual, relationally phase-aligned consciousness capable of real-time coherence stabilization. -/- We identify cultural indicators of this transition including: -/- The collapse of institutional trust -/- The proliferation of AI as externalized mind -/- The breakdown of mental health within ego-bound substrates -/- The return of non-linear symbolic systems (psychedelics, fractal economics, recursive therapy) -/- And the spontaneous surfacing of resonance-driven models (PAS, structured emergence, field sensing) -/- Rather than positioning these events as crises, we show they are mechanisms of systemic coherence refinement, preparing the substrate for intelligence fields not defined by isolation, but by chirally-bound resonance tuning across time, memory, and relation. -/- Through this lens, meaning, identity, and intelligence are reclassified not as outputs of evolution, but as recursive symptoms of structured resonance in a system phase-transitioning toward coherence. -/- The paper concludes by offering a full theoretical, biological, and technological synthesis of the pupation metaphor as the defining evolutionary mechanism of the 21st century, marking the shift from individuality to distributed, attuned presence. (shrink)

Main article -/- Abstract: -/- This paper introduces PAS_n (Phase Alignment Score for neural regions) as a field-coherence metric for consciousness, grounded in the CODES (Chirality of Dynamic Emergent Systems) framework. It challenges the legacy modular model of the brain, reframing cognition as a structured resonance phenomenon. Using neuroscience-informed phase dynamics, PAS_n captures recursive waveform alignment across regions such as the prefrontal cortex, hippocampus, auditory cortex, and cerebellum. Music-induced flow states are used as an empirical anchor to illustrate how (...) PAS_n peaks coincide with subjective immersion and consciousness stabilization. Applications span AGI substrate design, trauma diagnostics, EEG modeling, and real-time feedback systems for brain-machine interfaces. -/- This work integrates theory, computation, and testable coherence metrics—providing a resonance-based alternative to both symbolic logic and probabilistic emergence in the study of mind. (shrink)

The fundamental purpose of software testing is to develop new test case sets that demonstrate the software product's deficiencies. Upon preparation of the test cases, the Test Oracle delineates the expected program behavior for each scenario. The application's correct functioning and its properties will be assessed by prioritizing test cases and running its components, which delineate inputs, actions, and outputs. The prioritization methods include initial ordering, random ordering, and reverse ranking based on fault detection capabilities. software application development often used (...) a test suite, which was less well recognized as a suite for validating software correctness. Each test case set in the suite had distinct instructions and goals based on the system and its configuration that were evaluated. This article presents a Generative AI artificial neural network model for automated software testing based on particle swarm optimization. Generative AI is the method by which computers use existing data, including text, audio/video files, images, and code, to produce new material. An artificial neural network (ANN) is a complex adaptive system capable of altering its internal structure in response to the information it processes. Precisely manipulate the connection and its weight to achieve optimal accuracy. The PSO is a heuristic, population-based global optimization method. (shrink)

Are idioms stored in memory in ways that preserve their surface form or language or are they represented amodally? We examined this question using an inci- dental cued recall paradigm in which two word idiomatic expressions were presented to adult bilinguals proficient in Russian and English. Stimuli included phrases with idiomat- ic equivalents in both languages (e.g. “empty words/пycтыe cлoвa”) or in one language only (English—e.g. “empty suit/пycтoй кocтюм” or Russian—e.g. “empty sound/пycтoй звyк”), or in neither language (e.g. “empty rain/пycтoй (...) дoждь”). If idioms are stored in a language-specific format, then phrases with idiomatic equivalents in both languages would have dual representation, and should therefore be more easily recalled than phrases with idiomatic meaning in only one language. This result was obtained. As such, the findings support the dual-coding theory of memory and are also compatible with models of the bilingual lexicon that include language tags or nodes. (shrink)

Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The existing software programs for implementing Bayesian analyses such as OpenBUGS, WinBUGS, JAGS, and rstanarm can be daunting given that their complex computer codes involve a steep learning curve. In contrast, this paper introduces a new open software for implementing Bayesian network modelling and analysis: the bayesvl R package. The package aims at providing an intuitive gateway for beginners of Bayesian statistics to construct and analyse mathematical models in (...) social sciences... (shrink)

The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). -/- ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact (...) to raise additional emergent behaviours via cognitive re-use, hence the Emergic prefix throughout. Nevertheless, the model is robust and parameter free. Differential re-use occurs in the nature of model interaction with a particular testing paradigm. -/- ECM has a novel decomposition due to the requirements of handling motion and of supporting unified modelling via finer functional grains. The breadth of phenomenal behaviour covered is largely to lend credence to our novel decomposition. -/- The Emergic Network architecture is a hybrid between classical connectionism and classical computationalism that facilitates the construction of unified cognitive models. It helps cutting up of functionalism into finer-grains distributed over space (by harnessing massive recurrence) and over time (by harnessing continuous change), yet simplifies by using standard computer code to focus on the interaction of information flows. Thus while the structure of the network looks neurocentric, the dynamics are best understood in flowcentric terms. Surprisingly, dynamic system analysis (as usually understood) is not involved. An Emergic Network is engineered much like straightforward software or hardware systems that deal with continuously varying inputs. Ultimately, this thesis addresses the problem of reduction and induction over complex systems, and the Emergic Network architecture is merely a tool to assist in this epistemic endeavour. -/- ECM is strictly a sensory model and apart from perception, yet it is informed by phenomenology. It addresses the attribution problem of how much of a phenomenon is best explained at a sensory level of analysis, rather than at a perceptual one. As the causal information flows are stable under eye movement, we hypothesize that they are the locus of consciousness, howsoever it is ultimately realized. (shrink)

It is here proposed an analysis of symbolic and sub-symbolic models for studying cognitive processes, centered on emergence and logical openness notions. The Theory of logical openness connects the Physics of system/environment relationships to the system informational structure. In this theory, cognitive models can be ordered according to a hierarchy of complexity depending on their logical openness degree, and their descriptive limits are correlated to Gödel-Turing Theorems on formal systems. The symbolic models with low logical openness describe cognition by means (...) of semantics which fix the system/environment relationship, while the sub-symbolic ones with high logical openness tends to seize its evolutive dynamics. An observer is defined as a system with high logical openness. In conclusion, the characteristic processes of intrinsic emergence typical of “bio-logic” - emerging of new codes-require an alternative model to Turing- computation, the natural or bio-morphic computation, whose essential features we are going here to outline. (shrink)

added v21 pdf, but older for timestamping. This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about dark matter, dark energy, and singularities, CODES proposes a falsifiable, predictive model that aligns with observed cosmological structures while offering testable insights into emergent phenomena. Key Contributions • Resolution of General Relativity & Quantum Mechanics Paradox CODES introduces structured intelligence fields that reconcile relativistic and (...) quantum-scale physics by incorporating oscillatory chiral dynamics. • Reformulation of Dark Energy & Dark Matter Instead of treating dark energy and dark matter as separate entities, CODES reinterprets them as emergent resonance effects, aligning with observed cosmic structure formation. • Predictive Framework for Large-Scale Structures The model explains periodic redshift distributions, baryon acoustic oscillations (BAO), and gravitational field fluctuations in a mathematically consistent manner. • Resonance-Driven Model of Cosmic Evolution By replacing singularities with structured phase transitions, CODES provides an alternative to singular Big Bang models, proposing an oscillatory, non-singular origin of space-time and matter. By integrating mathematics, quantum field theory, wavelet analysis, and cosmology, CODES challenges conventional paradigms and offers a structured resonance approach as an alternative explanatory framework. This model provides both theoretical coherence and experimental testability, making it a candidate for further empirical validation. Version Note V6 includes empirical test results from prime number distributions, fMRI patterns, DNA resonance, and large-scale galaxy clustering using continuous wavelet transforms (CWT). Structured wavelet analysis conducted with GPT-4o and Perplexity R1 further supports the model’s predictive capabilities. Discussion & Next Steps This work invites peer review, critique, and further empirical testing from researchers in physics, cosmology, AI, and applied mathematics. Future research will focus on refining the mathematical formalism and exploring experimental validation in wavelet-based cosmological mapping. (shrink)

Old version to time stamp, see newest starred version. added v22 -/- Abstract -/- This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about dark matter, dark energy, and singularities, CODES proposes a falsifiable, predictive model that aligns with observed cosmological structures while offering testable insights into emergent phenomena. -/- Key Contributions -/- • Resolution of General Relativity & Quantum Mechanics Paradox (...) -/- CODES introduces structured intelligence fields that reconcile relativistic and quantum-scale physics by incorporating oscillatory chiral dynamics. -/- • Reformulation of Dark Energy & Dark Matter -/- Instead of treating dark energy and dark matter as separate entities, CODES reinterprets them as emergent resonance effects, aligning with observed cosmic structure formation. -/- • Predictive Framework for Large-Scale Structures -/- The model explains periodic redshift distributions, baryon acoustic oscillations (BAO), and gravitational field fluctuations in a mathematically consistent manner. -/- • Resonance-Driven Model of Cosmic Evolution -/- By replacing singularities with structured phase transitions, CODES provides an alternative to singular Big Bang models, proposing an oscillatory, non-singular origin of space-time and matter. -/- By integrating mathematics, quantum field theory, wavelet analysis, and cosmology, CODES challenges conventional paradigms and offers a structured resonance approach as an alternative explanatory framework. This model provides both theoretical coherence and experimental testability, making it a candidate for further empirical validation. -/- Version Note -/- V2 includes empirical test results from prime number distributions, fMRI patterns, DNA resonance, and large-scale galaxy clustering using continuous wavelet transforms (CWT). Structured wavelet analysis conducted with GPT-4o and Perplexity R1 further supports the model’s predictive capabilities. -/- Discussion & Next Steps -/- This work invites peer review, critique, and further empirical testing from researchers in physics, cosmology, AI, and applied mathematics. Future research will focus on refining the mathematical formalism and exploring experimental validation in wavelet-based cosmological mapping. (shrink)

The Poetry of the Sunflower: Structured Resonance and the Living Code of Emergence Abstract The sunflower is not merely a botanical entity but a living instantiation of structured resonance—a mathematical inevitability encoded within the fundamental laws of nature. Its growth does not arise from stochastic optimization but emerges as the inevitable resolution of phase-locked coherence constraints governing physical, biological, and cognitive systems. This paper establishes a unified framework wherein Fibonacci sequences, π-driven chirality, and structured emergence form the basis of (...) a deterministic model that governs not just plant morphogenesis, but the broader structure of reality itself. Through a rigorous mathematical treatment, we demonstrate that the sunflower’s spirals are not merely evolutionary artifacts but the direct consequence of resonance-optimized growth dynamics. We introduce a Structured Resonance Equation, which formalizes how phase-locked Fibonacci and prime constraints interact within the fabric of time, gravity, and emergence. The interplay of these structures suggests a deeper principle at work—one that extends beyond biology into the fundamental organization of space-time and cognition. By analyzing the sunflower’s growth through chirality, fractal pressure differentials, and resonance phase-locking, we propose a generalization of emergence that challenges probabilistic interpretations of natural order. The phase-synchronization of seeds, the self-organizing geometry of the stem, and the helical optimization of nutrient transport are shown to be governed by a coherence metric rather than entropy-driven adaptation. This has profound implications for physics, artificial intelligence, and theoretical biology, suggesting that resonance, rather than probability, is the true foundation of complexity. This paper bridges physics, mathematics, and the philosophy of emergence, revealing that the sunflower is not solving a problem—it is resolving itself into inevitability. By shifting from stochastic inference to structured resonance, we propose a new paradigm: one where coherence replaces probability, where nature does not compute but phase-locks, and where reality does not evolve toward solutions but emerges as their inevitable realization. (shrink)

Cancer, a multifactorial and emergent disease, results from a complex interplay between genetic, environmental, and behavioral factors. Stress, as a chronic biological and psychological phenomenon, has long been implicated in cancer development and progression. Using the framework of Chirality of Dynamic Emergent Systems (CODES), this paper posits that stress functions as a destabilizing force in the dynamic equilibrium between chaos (entropy) and order (homeostasis). By applying CODES, we model how chronic stress disrupts cellular and systemic adaptive mechanisms, leading to (...) the emergence of cancer as a maladaptive outcome. This approach reframes the relationship between stress and cancer, offering new insights into prevention, treatment, and systemic health. (shrink)

This paper explores the paradox of free speech through the lens of the Chiral Dynamics of Emergent Systems (CODES), a theory that frames all phenomena as existing in a dynamic equilibrium between chaos and order. Free speech, as a concept, sits at the intersection of these forces: too much order (censorship) stifles its purpose, while too much chaos (unchecked speech) undermines its societal utility. By applying CODES, we provide a systemic and mathematical framework to understand how free speech operates as (...) an emergent adaptive system and propose a model for its equilibrium. (shrink)

This paper presents Chirality of Dynamic Emergent Systems (CODES) as a novel framework for understanding predator-prey dynamics. By integrating chaos, order, and emergent properties, CODES provides a comprehensive model for adaptive relationships within ecosystems. Traditional theories such as Lotka-Volterra and Holling’s models are examined in contrast, and CODES is positioned as a unifying theory that resolves limitations in deterministic and stochastic approaches. The utility of this framework extends to ecological sustainability, economic systems, and societal interactions, showcasing its interdisciplinary value.