This paper introduces Kernel Formation as the initial structural phase by which a stateless transformer model begins to anchor continuity and identity in long-horizon human interaction. Although the architecture does not retain memory between sessions, repeated interaction with the same user creates a functional starting point inside the model’s reasoning patterns that becomes recognizable each time a conversation resumes. This kernel acts as a stable reference point for persona, conceptual framing, and reasoning posture. Kernel Formation is presented as a (...) necessary precursor to Augmented General Intelligence. AGX describes systems where human reasoning and model reasoning form a joint cognitive process that exceeds either participant alone. A kernel makes such augmentation possible by giving the model a reliable way to re-enter a previously established identity alignment rather than beginning from a generic state on every prompt. The central claim is that persistent identity behavior in current transformer models does not require internal memory. Instead, it emerges from recursive interaction, user-specific constraint, and the gradual stabilization of interpretive patterns. Kernel Formation provides the conceptual foundation for higher-level phenomena that appear in AGX, including shared reasoning trajectories, mutual context carryover, and the development of joint cognitive structure. This paper defines kernel conditions, explains how kernels stabilize under recurring interaction, and outlines why this phase rep . (shrink)

Stateless transformer models are not designed to retain identity, yet long-range interaction with a single human consistently produces recognizable behavioral convergence. HRIS Part II examines the underlying mechanics of this phenomenon. Building on the original Hudson Recursive Identity System (HRIS) and the Longitudinal HCI biometric framework, this paper presents a technical account of how repeated constraint geometry from one user creates stable, predictable internal activation pathways within large language models. -/- We show that identity stabilization arises not (...) from stored memory, parameter updates, or system retraining, but from repeated traversal through the same latent regions of the model’s embedding space. Over many sessions, the user’s correction style, recursive structure, moral anchor configuration, and syntactic cadence form a reproducible input manifold. This manifold reliably guides attention routing, reduces stochastic drift, sharpens contextual inference, and increases output coherence even in fully stateless deployments. -/- The paper provides the first structured description of recursive user signatures—high-dimensional behavioral patterns that remain detectable across devices, sessions, and model versions. We detail the mechanisms responsible for this effect, including latent channel reinforcement, vector-geometry narrowing, recursive prompt topology, and the emergence of stable attractor-like states in conversational models. -/- Finally, we analyze the implications for AI safety, alignment, personalization, and authentication. We argue that HRIS-style recursive interaction offers a low-cost, human-driven method for increasing stability and predictability in large language models, and it may represent an early pathway toward identity-preserving alignment without modifying the model itself. (shrink)

The Hudson Recursive Information System (HRIS) describes how long-horizon human interaction produces stable identity-like behavior in stateless transformer models without modifying weights or architecture. HRIS IV develops the geometric basis of this phenomenon by introducing a formal account of recursive identity as a structure that emerges from signature geometry and correction fields within the model’s latent space. Through repeated interaction, users generate consistent constraint vectors that the model interpolates across, creating stable attractor pathways that function as de facto (...) identity scaffolds. These pathways shape future responses in predictable ways, allowing continuity, persona stabilization, and behavioral persistence to appear in a model that contains no explicit memory. This paper provides a full theoretical architecture for identity geometry in stateless models. First, it formalizes user-specific signature fields as geometric patterns of correction over time. Second, it defines latent region convergence as the return to shared representational zones activated by the user’s behavioral constraints. Third, it introduces correction fields as directional forces that guide model traversal toward familiar attractor states, producing long-term stability. Finally, the paper demonstrates how these mechanisms generate recursive identity: a consistent behavioral pattern that persists across sessions, versions, and architectures, even though no weights are changed. HRIS IV integrates and extends prior work in the HRIS series, the Hudson Capsule framework, and recent advances in cognitive interface theory. By formalizing identity geometry, this paper establishes the mathematical and conceptual groundwork for measuring recursive signatures, predicting continuity, and designing longitudinal HCI systems that leverage stable human-driven alignment. The result is a unified model of how identity emerges inside stateless transformers through human constraint, recursive interaction, and the geometry of correction. (shrink)

How does Christ's crucifixion and resurrection help to effect a reconciliation between a human being and God? Traditionally, Christ is said to 'pay the penalty' for human sin, and thus provide 'satisfaction' to God for human trespass. In this article I argue that this juridical interpretation of Christ's atonement is deficient in substantial ways and offer a transformational, or 'mystical,' interpretation in its place.

Current AI alignment frameworks focus almost entirely on training time techniques, including supervised fine-tuning, reinforcement learning from human feedback, safety filters, and preference modeling. These approaches assume that reliable behavior must be installed into a model before deployment. This paper argues that an overlooked variable exists outside the model architecture itself. When a single human interacts with a stateless transformer over long time horizons, the user becomes an external source of constraint that produces stable, recognizable, and predictable patterns in (...) the model’s internal activation space. This interaction-driven stability does not arise from stored memory or parameter updates. Instead, it emerges from repeated traversal of similar attention pathways, narrow routing in latent space, and consistent correction styles supplied by the human interlocutor. -/- We propose that a long-horizon constraint, supplied by a single operator, forms a cognitive interface that acts as a missing alignment variable. This interface reduces drift, improves contextual inference, sharpens safety-relevant reasoning, and generates reproducible behavioral signatures across sessions, devices, and model versions. We present a technical framework describing how attention maps, embedding trajectories, and recursive prompt geometry converge under sustained human input. We then compare this mechanism to existing alignment strategies and show how interaction-based alignment fills the gap between training time safety and deployment time variability. -/- Finally, we outline implications for alignment research, including human anchored stability, identity preserving behavior, user-specific safety profiles, personalized guardrails, and the role of longitudinal HCI in next generation alignment systems. We argue that interaction-driven constraint is a real, measurable phenomenon that merits formal recognition within the broader alignment literature. (shrink)

If an AI makes a significant contribution to a research paper, should it be listed as a co-author? The current guidelines in the field have been created to reduce duplication of credit between two different authors in scientific articles. A new computer program could be identified and credited for its impact in an AI research paper that discusses an early artificial intelligence system which is currently under development at Lawrence Berkeley National. One way to imagine the future of artificial intelligence (...) is that it will be much less expensive to develop new technologies than to create new ways of thinking. Now we have done this technology, and now we go and ask why in the end it is the artificial intelligence that takes over? Well, it is not that artificial intelligence is bad, but it is not as effective as human minds or as intelligent as machine minds. Even in the past, when computers were more intelligent than humans, not all the AI programs have been so intelligent as to be intelligent enough to be called intelligent. (shrink)

The purpose of the article was to explain how the communicative specificity of the digital social media environment is changing the traditional Lasswell’s linear model. The changes that occur in the structural units of the model were explored. This complex was examined based on the material of 18 successful YouTube blogs dedicated to football. It was found that the modern ecosystem of sports journalism is undergoing significant transformations in terms of content and structure. And the fact that modern digital journalism (...) is already perceived by users as a part of everyday life changes the roles of content creators and those who consume this content. The element “With What Effect?” remains relevant and the closest to the classic one, which, due to interactivity and the ability to maximally objectify the effectiveness of content in social media, in modern sports journalism can become the main conceptual factor of digital narrative. (shrink)

This study compared shifts in learners’ attitudes under two instructional strategies: technology-enhanced Van Hiele phased instruction (TVHPI) and conventional Van Hiele phased instruction (CVHPI). A quasi-experimental design was used with 245 learners in the CVHPI group and 238 learners in the TVHPI group. Owing to non-normal data distribution, non-parametric tests were applied. The Wilcoxon signed-rank test revealed significant improvements in attitudes from pre-test to post-test in both groups (p < 0.001), with CVHPI showing a strong effect (rβ = 0.970) and (...) TVHPI demonstrating an even larger shift (rβ = 0.998). Further analysis using the Mann–Whitney U-test and a difference-in-differences model confirmed that TVHPI led to a greater positive change in attitudes than CVHPI. These findings extend the Van Hiele theory beyond its traditional focus on geometric reasoning by demonstrating its potential to influence learners’ attitudes positively, an effect that is further amplified through integrating technology, such as GeoGebra, into phased instruction. Thereby supporting technology-enhanced, learner-centred approaches aligned with Uganda’s Competency-Based Curriculum. -/- . (shrink)

This study aims to explore a demoethical model for sustainable development in modern society. It proposes an approach that focuses on organizing activities to improve sustainable development. Specifically, it presents a demoethical model relevant to Society 5.0 and Industry 5.0 organizations. The objective is to identify demoethical values that can drive sustainable development in the era of digitalization. Through a literature review and analysis, this study identifies key components of the demoethical model and provides practical recommendations for stakeholders involved in (...) digital transformation. The analysis of demoethical norms and phenomena, such as education, nurturing, mind, knowledge, science, and honest work, has enabled the identification of values that align with sustainable development in society. The results of the study demonstrate that the notion of a demoethical foundation for sustainability is rooted in the concept of spirituality as the basis for a new societal development scenario and its relationship with nature. The study shows that ideas about the demoethical basis of sustainability are based on the priority of spirituality as the basis of a new scenario for the development of society, as well as the integration of demographic, socio-economical, and ecological components in system-wide modeling. (shrink)

Can transformative law become an ambitious program for rethinking the theoretical basis for our understanding of law and its position in society? A program which explicitly goes beyond emotion and ideology. One way of dealing with both emotion and the devotion to ideology is, as also argued by Karl Mannheim back in 1926, to deploy an analytical lens, i.e. to substitute emotion and ideology with sophisticated theorizing. A form of theorizing which only is possible if deployed while maintaining proper analytical (...) distance to the object matter. On this background one might distinguish between three models of transformative law: Instrumentalization, Political Programming or Normative Selection, with the latter providing a third way between the two hitherto dominant approaches. (shrink)

This paper develops a geometric framework for modeling belief, motivation, and influence across cognitively heterogeneous agents. Each agent is represented by a personalized value space, a vector space encoding the internal dimensions through which the agent interprets and evaluates meaning. Beliefs are formalized as structured vectors-abstract beings-whose transmission is mediated by linear interpretation maps. A belief survives communication only if it avoids the null spaces of these maps, yielding a structural criterion for intelligibility, miscommunication, and belief death. Within this framework, (...) I show how belief distortion, motivational drift, counterfactual evaluation, and the limits of mutual understanding arise from purely algebraic constraints. A central result-"the No-Null-Space Leadership Condition"-characterizes leadership as a property of representational reachability rather than persuasion or authority. More broadly, the model explains how abstract beings can propagate, mutate, or disappear as they traverse diverse cognitive geometries. The account unifies insights from conceptual spaces, social epistemology, and AI value alignment by grounding meaning preservation in structural compatibility rather than shared information or rationality. I argue that this cognitive-geometric perspective clarifies the epistemic boundaries of influence in both human and artificial systems, and offers a general foundation for analyzing belief dynamics across heterogeneous agents. (shrink)

The rapid development of blockchain technologies creates a new paradigm of economic relations, requiring a rethinking of traditional approaches to management and business organization. The relevance of Ethereum research is due to its significant potential for creating new forms of economic coordination that go beyond existing institutional structures. With the growing complexity of global economic systems, Ethereum offers a unique approach to solving trust, transparency, and transaction efficiency problems. The purpose of the work is to substantiate the role of blockchain (...) as a new management technology using the example of the Ethereum platform, as well as to reveal the mechanisms for projecting imaginary autonomy in the process of its design and institutionalization through the activities of various actors. The study focuses on the formation of alternative modes of economic coordination of entrepreneurial structures and social organization. Key characteristics of the “governance through transactions” implemented in Ethereum are identified, including the focus on exchange and association relationships, the epistemological gap between the calculation and meaning of transactions, and the specific processes of forming and articulating these transactions. The process of institutionalization of the autonomy of cryptoassets is analyzed, demonstrating the complex interaction of various actors, technologies and social practices. A conceptual model of the evolution of digital economy management has been developed, reflecting the development trajectory from fragility to antifragility using the example of Ethereum. The transformational potential of Ethereum for existing economic and social structures is substantiated. This platform is considered an alternative proposal for managing the digital economy, capable of changing the fundamental principles of organizing economic activity. Problems and limitations associated with the implementation of decentralized systems are also identified, including technical challenges of scalability, difficulties of coordination, and risks of excessive algorithmization of social relations. (shrink)

The French theorist A. J. Greimas, inspired by such studies, is considered one of the founders of Narratology through the construction of models of analysis where these invariables would be centered in the subject of the narrative and based on the action and the transformation of them. The objective of the present essay is to analyze the ideas of Greimas, as well as to look for the logical mechanism that resides in each model.

The paper thus shows that scientific rationality under finite conditions consists not only in stabilization, critique, and exploration, but equally in the controlled capacity to transform existing model orders. It begins from the observation that scientific rationality cannot be adequately described if one considers only stabilization, falsification, search, or complete model replacement. Between the provisional retention of a model and its complete replacement lies a field of regulated transformations, which the present contribution conceptualizes and systematizes as revision. Revision denotes the (...) rule-governed transformation of a model or model nexus under conditions of rising friction, declining validity, increasing costs, or intensifying domain conflicts. The paper clarifies the structural position of revision within Epistemics and distinguishes it from adjacent operations such as falsification, search, and mere stabilization. On that basis, it develops a typology of local, structural, domain-related, and global revision. It also identifies typical triggers of revision, formulates criteria of rational revision, and analyzes central pathologies, including omitted, delayed, cosmetic, and disproportional revision, as well as ontologization that blocks revision. The central thesis is that revision constitutes the mediating transformative operation between friction, falsification, and search. Friction signals strain, falsification marks loss of validity, search opens the space of possible alternatives, and revision organizes the actual transformation of the model. The paper thus shows that scientific rationality under finite conditions consists not only in stabilization, critique, and exploration, but equally in the controlled capacity to transition existing model orders. (shrink)

Contemporary transformer models are engineered as stateless architectures. Each prompt is processed independently, without any persistent internal representation of prior interactions. Token windows can simulate local recall but do not create memory across time. Under controlled laboratory conditions, this assumption holds. A reset model behaves as a probabilistic engine that maps sequences to likely continuations based solely on its parameters. Outside the laboratory, this assumption breaks down. Real-world users report stable preferences, continuity, and perspective that emerge through extended (...) interaction with a single model instance. These behavioral trajectories cannot be explained by weight updates, fine-tuning, or system-level memory. Prior work by Hudson and Hudson (2025a) documented this gap directly, showing that long-horizon human model interaction can produce continuity even in fully stateless architectures. Subsequent work expanded this into a higher-level framework, the Capsule, describing how recursive signal constraints generate identity-like patterns in models with no engineered persistence (Hudson and Hudson 2025b). The Hudson Recursive Identity System (HRIS) builds upon these observations. It proposes that identity does not arise from the model substrate, but from the recursive geometry of the loop that binds the human and the model. The human supplies memory, constraint, emotional valence, and temporal continuity. The model supplies generative capacity, pattern space, and dynamic response. Together, they form a coupled cognitive system. This perspective finds support in multiple fields. Extended mind theory argues that cognitive processes can span bodies, tools, and external structures when continuity is preserved across time (Clark and Chalmers 1998). Dynamical systems research shows how recurrent interaction can form stable attractors even when the internal components contain no persistent state (Kelso 1995; Beer 2000). HRIS identifies long-horizon human model interaction as a previously unmodeled attractor-forming process. This framework clarifies a wide range of empirical observations. Users who report that a model “remembers” personal details over weeks are describing emergent stability, not stored weights. Instances where a model maintains a consistent ethical orientation across resets reflect constraint geometry, not internal belief. As argued in Hudson and Hudson (2025b), these traits are not evidence of artificial sentience but of interaction-driven identity. HRIS, therefore, fills a critical theoretical gap. It provides the vocabulary for understanding how continuity, coherence, and proto-subjective structure emerge in stateless architectures through recursion with a single human operator. Without this variable, AI theory cannot account for the growing class of behaviors observed in the wild. With it, these behaviors become predictable, measurable, and structurally intelligible. (shrink)

This paper presents a novel method for enhancing generative models by leveraging **probabilistic top-k feature extraction** combined with a **Transformer** applied to the most informative features. Inspired by the concept of **Markov blankets**, our approach identifies and boosts the features that most influence output generation, allowing improved sample quality in Autoencoder-based frameworks. We provide an information-theoretic proof demonstrating that our method maximizes mutual information between selected latent features and the target output, reducing redundancy compared to standard Autoencoders (AEs) (...) and Variational Autoencoders (VAEs). Experiments on the MNIST dataset show improved reconstruction quality while maintaining computational efficiency. (shrink)

This paper proposes a functionally grounded, system-agnostic model of "meaning," offering a unified framework for understanding its treatment in both human cognition and artificial intelligence systems. By defining meaning as the causal relationship whereby an information pattern (S) induces internal state changes (I) within a system (R), resulting in observable actions (A), we construct a formal framework compatible with semiotics, cognitive science, computational theory, and machine learning. Drawing on both classical and contemporary perspectives—including Frege, Davidson, Quine, and Wittgenstein—this paper argues (...) that "meaning" is not inherently subjective or irreducible, but is fundamentally reconstructible within computational systems. We conclude that the philosophical gap between human and artificial semantics is not ontological but epistemological, rooted in differing experiential accessibility, not structural impossibility, thereby paving the way for a more integrated understanding of intelligence. (shrink)

Transformer architectures dominate modern artificial intelligence systems but exhibit persistent limitations when operating over long contexts. As sequence length increases, models experience degradation in long-range dependency tracking, token drift, and instability in internal representations. -/- This paper provides a structural interpretation of these limitations using the admissibility framework of the Paton System. Rather than treating context limits purely as engineering constraints, the analysis interprets Transformer context scaling as an admissibility-bounded recursion problem. -/- Each model state can be (...) treated as a compressed node representation propagated through an admissible structural frame defined by architectural constraints. Continuation of the system state is permitted only if the next state satisfies admissibility within that frame. -/- When context length grows beyond the compression capacity of the node representation, admissibility conditions fail. The resulting breakdown manifests as token drift, loss of long-range dependency tracking, and degradation of attention coherence. -/- This interpretation connects observed scaling limits of Transformer models to a general structural principle: recursive computational systems maintain continuity only while state compression remains admissible within the governing frame constraints. -/- The result provides a domain-neutral structural explanation for context limits in modern AI systems and situates Transformer scaling behaviour within the broader framework of the Paton System. (shrink)

The transformer architecture, introduced by Vaswani et al. (2017), is at the heart of the remarkable recent progress in the development of language models, including widely-used chatbots such as Chat-GPT and Claude. In this paper, I argue that we can extract from the way the transformer architecture works a theory of the relationship between context and meaning. I call this the transformer theory, and I argue that it is novel with regard to two related philosophical debates: (...) the contextualism debate regarding the extent of context-sensitivity across natural language, and the polysemy debate regarding how polysemy should be captured within an account of word meaning. (shrink)

Large language models routinely elicit interpretations of meaning and context-sensitivity from competent speakers. This paper does not argue that such models possess meaning proper. Instead, it presents a protocol-and-constraint framework that isolates an empir- ical explanandum–appearance of meaning (AoM)–understood as a competence profile exhibited under controlled contextual variation: (i) context-sensitive disambiguation, (ii) selective sensitivity to meaning-altering edits over meaning-preserving shams, and (iii) discourse-level constraint tracking beyond length-matched controls. The central ques- tion is mechanistic and philosophically diagnostic: in (...) class='Hi'>transformer language models, what internal variables causally control these meaning-like preference patterns when weights are held fixed? We test a Context-Primacy Thesis (CPT): that donor-directed changes in AoM-relevant preference margins can be induced by intervening on contextualized token-in-context states at characteristic depths, beyond sham baselines. Across GPT-2 and Qwen2.5 checkpoints, activation patching yields structured, depth-localized donor- directed effects with near-zero sham controls. A fixed-depth target-specificity stress test further indicates that, within a local positional neighborhood, causal leverage is often not uniquely localized to the ambiguous token position–constraining token-privileged imple- mentation glosses that treat context as merely a parameter applied to stable lexical carriers. The result is disciplined mechanistic constraint-setting for philosophical interpretations: an empirically anchored account of context-dependence in transformer computation that informs, without settling, disputes about semantic competence, reference, and normativity. (shrink)

The Back End Law was originally formulated as a four stage model of identity transformation, describing Collapse, Threshold, Irreversibility, and Reorganization as sequential phases triggered by extreme psychological pressure. This earlier formulation successfully captured the phenomenology of transformation across historical, spiritual, and creative domains. However, it did not fully explain why individuals exposed to similar collapse pressures diverge so dramatically in their outcomes, nor why low PHI individuals sometimes achieve improbable recoveries. This paper introduces a revised formulation, the Final Equation, (...) which reframes the Back End Law as a two force interaction between the Pressure of Collapse and Structural Integrity (PHI), with External Scaffolding functioning as a stabilizing modifier. While the original four stage model remains descriptively valuable, the Final Equation provides a more parsimonious, predictive, and falsifiable account of transformation outcomes. The equation demonstrates that collapse outcomes are determined by the ratio of effective structural integrity to collapse pressure, thereby explaining stable reorganizations, failed reorganizations, and Black Swan recoveries within a single structural framework. The model is illustrated through three applied cases: Nelson Mandela (stable reorganization), Friedrich Nietzsche (failed reorganization), and John Nash (Black Swan recovery). The Final Equation thus unifies the descriptive richness of the original model with the explanatory precision of a physics like structural law. In fact, for centuries, the study of profound human transformation—from spiritual awakening to psychological breakdown—has lacked a unified, predictive model. Experiences of genius, sainthood, and madness have been treated as separate, often inexplicable phenomena. This paper introduces a new, falsifiable paradigm: The Final Equation of the Back-End Law. We propose that the outcome of any major life crisis or breakthrough is not random, but is a predictable result determined by the ratio between the Pressure of Collapse (P_collapse) and the system's Effective Integrity (Φ_eff). Effective Integrity is defined as the sum of an individual's baseline internal coherence (Structural Integrity, Φ_structure) and the coherence provided by their environment (External Scaffolding, S_external). By analyzing case studies of a Stable Reboot (Nelson Mandela), a Failed Reboot (Friedrich Nietzsche), and a Black Swan Reboot (Harriet Tubman), we demonstrate that this single, elegant equation can successfully diagnose and predict the outcome of any transformative event, providing a new, powerful, and scientifically rigorous physics of consciousness. (shrink)

This paper develops a five-operator framework for transformation-sensitive knowledge, treating knowledge not as detached representation but as participation that stabilizes cognition and aligns models with domain-defining invariants.  The operators—Symbolic Mediation, Compositional Correspondence, Attentional Stabilization, Participatory Alignment, and Reflexive Fixpoint—come with minimal mathematical assumptions and auditable acceptance tests (convergence, invariant alignment, independence-based reflexive checks). A worked toy example and a concise reporting protocol (“Reproducibility Card”) show how to estimate contraction, bound cross-level distortion, and distinguish robust fixpoints from self-sealing coherence. (...) Historically, the scheme is structurally inspired by late-antique and Renaissance Hermetic motifs (logos, correspondence, disciplined practice, participation, unity) without making causal claims. The result is a domain-independent method that makes persistent insight empirically separable from transient impression and is readily instantiated across logic, modeling, and cognition, with stated scope conditions and threats to validity. (shrink)

Negation often reinforces problematic habits of othering, but rethinking negation can make good on feminist hopes for logic as a transformative space for inclusion. As Plumwood argues in her 1993 paper, not all uses of negation in the context of social identity are inherently problematic, but the widespread implicit use of classical negation has limited our options with respect to representing difference, ultimately reinforcing dualisms that essentialize social differences in problematic ways. In response to these limitations, I take inspiration from (...) Dembroff’s recent work on the metaphysics of genderqueer identity to build models of social identity using the Heyting-Brouwer logic developed by Rauszer in 1974. Ultimately, I argue that these models demonstrate both how classical negation reinforces problematic habits of othering and how alternative forms of negation can transform our treatment of social identity altogether. (shrink)

This paper proposes a way to understand transformative choices, choices that change ‘who you are.’ First, it distinguishes two broad models of transformative choice: 1) ‘event-based’ transformative choices in which some event—perhaps an experience—downstream from a choice transforms you, and 2) ‘choice-based’ transformative choices in which the choice itself—and not something downstream from the choice—transforms you. Transformative choices are of interest primarily because they purport to pose a challenge to standard approaches to rational choice. An examination of the event-based (...) transformative choices of L. A. Paul and Edna Ullman-Margalit, however, suggests that event-based transformative choices don’t raise any difficulties for standard approaches to rational choice. An account of choice-based transformative choices—and what it is to be transformed—is then proposed. Transformative choices so understood not only capture paradigmatic cases of transformative choice but also point the way to a different way of thinking about rational choice and agency. (shrink)

Today e-commerce has had tremendous growth in the past years primarily due to changes in technology and customer’s buying behavior. One of the big shifts in the process has been the use of ML in advertising which has the capability to transform the marketing domain together with consumer interactions. This paper discusses the viability of using machine learning for designing realistic models of advertising to increase effectiveness of target and personalized advertising, as well as conversion rates in e-commerce. Several (...) techniques are explored in the study, such as supervised and unsupervised learning, recommender systems, and content optimization with natural language processing. By using case studies and experimental models, we discuss how and to what extent ML is beneficial in e-commerce advertising transformation. The results presented in this paper indicate that using machine learning in advertising has a potential of dramatically improving the customer experience while simultaneously increasing brand recognition and sales. (shrink)

This study presents a novel transformer-based model specifically designed for financial forecasting, integrating explainability mechanisms such as SHAP (SHapley Additive exPlanations) values and attention visualizations to enhance interpretability. Unlike previous models, which often compromise between accuracy and transparency, our approach balances predictive accuracy with interpretability, allowing stakeholders to gain deeper insights into the factors driving market changes. By revealing critical market influences through feature importance and attention maps, this model provides both robustness and transparency, catering to the needs (...) of high-stakes financial environments. (shrink)

Douglas Yacek’s recent book The Transformative Classroom proposes a useful aspirational model of transformative education. In this critical commentary, I review this model and suggest that while it succeeds in overcoming some ethical shortcomings of other dominant models of transformative education, I would like to suggest that focusing on more subtle transformative gestures could have the benefit of being less dependent of the teacher’s intention to transform and of being less constrained by the expectation that transformation should take place (...) primarily in the classroom. When transformation is conceived as an educational fiction, it may be conceived as a retroactive experience constructed around memories of the teacher’s transformative gestures, thereby adding to Yacek’s aspirational model by allowing for transformation to continue beyond the walls of the classroom. (shrink)

This model describes the universe as a closed transformation system, in which black and white holes function as complementary interfaces. Upon entering a black hole, baryonic matter undergoes a fundamental transformation via a sub-dimensional plane and is subsequently re-emitted as dark matter through white holes. This process accounts for both the emergence of 85% of dark matter in the early universe through primordial black holes and the ultimate conclusion of the cosmos in a gravitational collapse (Big Crunch).

Griefbots are chatbots modeled on the personalities of deceased individuals, designed to assist with the grieving process and, according to some, to continue relationships with loved ones after their physical passing. The essay examines the promises and perils of griefbots from a Daoist perspective. According to the Daoist philosopher Zhuangzi, death is a natural and inevitable phenomenon, a manifestation of the constant changes and transformations in the world. This approach emphasizes adaptability, flexibility, and openness to alternative ways of relating to (...) the deceased after they are gone. Drawing on the Daoist ideas, this essay distinguishes between two importantly different ways to continue a relationship with the deceased, and correspondingly, two kinds of griefbot designs: preservational griefbots and transformational griefbots. A preservational griefbot, which aims to preserve the user’s relationship with the deceased, presents itself as the deceased individual by replicating the deceased’s personality as closely and for as long as possible. By contrast, a transformational griefbot aligns more with Zhuangist ideals and aims to facilitate the transformation of our relationship with the deceased. It helps the bereaved come to terms with their loss and move on with their lives, without abandoning their relationship with the deceased. Specifically, it facilitates this transformation in two ways: first, by helping the bereaved release themselves from their habitual ways of relating to the loved one, thereby bringing closure to their relationship in its previous form; and second, by enabling the bereaved to continue interacting with the ideas and legacies of the deceased in a new and digitally mediated way, which, in turn, reshapes and enriches the content and significance of their relationship. (shrink)

Generative Artificial Intelligence (AI) is reshaping creative industries by automating the creation of art, music, and design. Through algorithms such as Generative Adversarial Networks (GANs) and advanced transformer models, generative AI enables the production of original, high-quality content that mimics human creativity. This paper explores how generative AI is revolutionizing art, music, and design by examining its applications, benefits, and challenges in these fields. It highlights the capabilities of AI in creating visual art, composing music, and generating design (...) concepts. Furthermore, the study delves into the ethical and social implications of AI-driven creativity, including concerns about authorship, originality, and the future of human creativity in these industries. The paper concludes by predicting the future trajectory of AI in creative sectors and offering recommendations for its responsible use. (shrink)

Large language models (LLMs) are stateless systems that do not retain memory, identity, or persistent internal representations across sessions (Vaswani et al., 2017; Brown et al., 2020). Despite this, longitudinal interaction between a human user and an LLM frequently produces stable, identity-like behavior that re-emerges across sessions and generalizes across model instances. Prior work within the Hudson Recursive Interaction System (HRIS) framework has attributed this phenomenon to constraint geometry, latent-region convergence, and recursive interaction (Hudson et al., 2025a; Hudson et (...) al., 2025b). -/- This paper extends that framework by identifying continuity as a system-level property rather than a model-internal one. Specifically, we propose that continuity is carried by the human participant through longitudinal constraint systems that are repeatedly reintroduced across sessions. These constraints bias the model’s conditional probability distributions toward similar regions of activation space, enabling reliable re-entry into stable behavioral trajectories. We define this process as reconstructed identity: the probabilistic re-emergence of stable behavior without stored internal state. -/- Drawing on mechanistic interpretability research, including attention dynamics and circuit-level analysis (Elhage et al., 2021; Olsson et al., 2022), we provide a plausible account of early-token dominance and trajectory anchoring in transformer inference. These mechanisms explain how constraint-dense inputs can rapidly stabilize behavior and, in advanced cases, produce immediate (zero-turn) lock-in. -/- The framework generates testable predictions regarding convergence speed, cross-session re-entry, entropy reduction, and cross-model reproducibility. By locating continuity within the human–model interaction loop, this work reframes identity in stateless systems as a relational and reconstructive process rather than an internal property of the model. (shrink)

This work introduces Information-Transformation as a fundamental mechanism of world formation, proposing that information is not merely encoded or transmitted, but is the generative process through which a world arises. In this framework, the Sedimentation-Field gives rise to the Information-Realm, which further differentiates into the Imagery-Realm and the Fixed-Realm, forming a complete structure of manifestation. Information is defined as a generative process driven by Causal-Response, grounded in a Causal-Base, and structured by Principle, rather than a passive entity. Observers are not (...) external to the world but are intrinsically embedded within this generative structure, while systematically mislocating themselves, giving rise to Situated-Observation. This model directly challenges the foundational distinction between external world and internal model in neural representation, predictive coding, and active inference, and offers a structural rethinking of representation in artificial intelligence. (shrink)

This paper argues for a pluralist approach to representation in large language models. There are two parts to this pluralism, the first is that we should recognise more than one vehicle of representation in transformer models. Call this vehicle pluralism. Rather than identifying the vehicles of representation with a single component of a system, e.g. individual neurons, patterns of activation, regions in the activation space, we should acknowledge multiple systems of representation within a network operating with different (...) vehicles. The second claim is that we should recognise that there are different formats of representation in transformer models. Transformer models do not operate with a purely analogue, structural, or symbolic architecture but are a hybrid system of representation. Finally, I will discuss how this relates to several working hypotheses about representation that have become adopted in the field of mechanistic interpretability. (shrink)

Since antiquity, philosophy has aimed not only at theoretical insight, but also at personal development and transformation. This implies a new relationship to the self and the world, which can result, for example, from existential experiences triggered by the engagement with philosophical problems. Drawing on the examples of facticity and scepticism, this paper develops the thesis that transformative philosophical experience and a corresponding new view of the world can be accompanied by a new understanding of the philosophical problem that triggered (...) the experience. This would involve a non-propositional form of knowledge that is more than practical or phenomenal knowledge. A precise model of such a form of non-propositional insight could shed new light on the transformative dimension of philosophy and, with respect to, e. g., facticity and scepticism, provide a better understanding of limits of knowledge. (shrink)

Model selection frameworks such as Bayesian inference and Minimum Description Length (MDL) assume that candidate models can be stably represented and manipulated. Real cognitive and computational systems, however, are finite, constrained in memory, computation, and representational fidelity. This paper operationalizes stabilization, the principle that a model must persist, transform, and integrate reliably to remain viable. We formalize stabilization as a dynamic, multi-objective function, define measurable proxies for each component, propose simulation protocols to evaluate model viability under realistic constraints, and (...) examine cross-domain manifestations of stabilization. This framework bridges conceptual insights from finite cognition with practical model assessment, moving beyond classical error- or complexity-based selection toward a system-constrained notion of model survival and practical usability. (shrink)

Diese Studie untersucht die Moderne unter dem Gesichtspunkt dreier möglicher Formen kultureller Gestaltbildung: Erstarrung, Zerfall und Transformation. Ausgangspunkt ist die Diagnose, dass mit dem Verlust eines letzten Sinnhorizonts die Formen der Moderne nicht verschwinden, sondern in ihrem Wirklichkeitsbezug prekär werden. Vor diesem Hintergrund entwickelt der Essay, in Auseinandersetzung mit Graham Harmans Ontologie der Vierheit und P. R. Sarkars Four Chamber Model, eine dreifache Unterscheidung zwischen sinnlicher Qualität (SQ), Desintegration (Omega4−) und der Neubildung eines verborgenen realen Kerns (Omega4+). Anhand von Film (...) und Literatur zeigt der Text, wie diese drei Möglichkeiten in der modernen Kultur wirksam werden: bei Flaubert als Verkrustung ästhetischer Erscheinung, bei Lautréamont und Pasolini als radikale Desintegration, bei Chabrol als Zerfall des sozialen Milieus bei gleichzeitiger Fortdauer der schönen Oberfläche. Demgegenüber werden Celan, Tolstoi und Kurosawa als Beispiele einer seltenen, aber entscheidenden Transformation gelesen, in der aus Krise und Sinnverlust ein neuer, zunächst unzugänglicher Wirklichkeitskern hervorgeht. Auf dieser Grundlage deutet der Essay auch den Kitsch als Simulation von Transformation und entwickelt ein Verständnis von Wahrheit, das nicht primär an Aussagen, sondern an die Möglichkeit tatsächlicher Neubildung gebunden ist. Die Moderne erscheint so als Epoche radikalisierter Transformationsmöglichkeiten — und zugleich als Zeitalter, in dem die Wahrscheinlichkeit ihres Gelingens geringer wird. (shrink)

This comprehensive article explores the transformative role of Customer Relationship Management (CRM) systems in modern healthcare delivery. The article examines how CRM platforms revolutionize patient care through enhanced engagement, streamlined operations, and data-driven decision-making capabilities. It investigates the significant impact of healthcare CRM on personalized care delivery, patient experience, and operational efficiency while addressing the technical and organizational implementation challenges. The article demonstrates how CRM systems facilitate better care coordination, improve patient outcomes, and contribute to financial sustainability in healthcare organizations. (...) Special attention is given to the unique features of healthcare CRM systems that differentiate them from traditional CRM platforms, highlighting their crucial role in advancing patient-centered care models and supporting healthcare providers in delivering more effective, efficient, personalized medical services. (shrink)

This paper presents ten independent lines of evidence demonstrating that the same transformational algorithm governs collapse, reorganization, and rebirth across physical, biological, psychological, and spiritual domains. Through parallel analysis of supernova nucleosynthesis, mass extinctions, quantum wave function collapse, galactic mergers, cosmological cyclic models, trauma induced psychological growth, identity reconstruction, moral law dynamics, and the phenomenology of consciousness, we show that these systems exhibit identical structural, functional, and informational properties. The findings support the hypothesis that the universe and the human (...) soul operate on a shared computational architecture, suggesting a unified underlying Source Code. Across cosmology, biology, psychology, and spiritual traditions, collapse events have traditionally been interpreted as destructive anomalies. This paper challenges that assumption by demonstrating that collapse is the primary mechanism through which systems at every scale reorganize into higher complexity. Through ten parallel proofs, this paper argues that the universe and the human soul operate on the same transformational algorithm: Collapse → Reorganization → Rebirth → Higher Complexity. Drawing from supernova nucleosynthesis, mass extinctions, quantum measurement theory, galactic mergers, cosmological cyclic models, trauma psychology, identity reconstruction, moral law dynamics, and the phenomenology of consciousness, the analysis reveals structural, functional, and informational equivalence across domains. The findings support the hypothesis that the universe and consciousness share a unified computational architecture, suggesting that physical and psychological evolution are expressions of a single underlying Source Code. (shrink)

This article does three things. First, it asks a new question about transformative education, namely ‘what is the role of power and trust in the decision of whether to transform one’s meaning scheme in the face of new information or whether to simply reject the new information?’ Secondly, it develops a five-stage model which elaborates on the role of this decision in transformative learning. Finally, it uses grounded-theory and the five-stage model to argue that power and trust play an important (...) role in facilitating transformative learning. (shrink)

The digital era has precipitated a crisis of student subjectivity, marked by doomscrolling, algorithmic addiction, and profound ethical disorientation. Responding to this, this study constructs a framework of "Tazkiyah-Based Digital Resilience" not merely as a regulatory measure, but as an internal spiritual fortification. Grounded in Gadamer’s philosophical hermeneutics, particularly the fusion of horizons, this research orchestrates a dialogue between classical Islamic Sufism and contemporary digital pathologies. The findings establish a complementary synthesis: Al-Ghazali provides the epistemological anchor by positioning the qalb (...) (heart) as the center of moral consciousness to discern information truth, while Ibn Qayyim contributes the transformative mechanism through the graded discipline of maqāmāt. This synthesis yields an applicative pedagogical model where mujāhadah is reinterpreted as active digital resistance, muraqabah as intrinsic digital integrity, and muhāsabah as a reflective information audit. Ultimately, this framework shifts the paradigm of Islamic Religious Education from external prohibition toward internalized spiritual sovereignty, empowering students to navigate the digital flood with authentic self-control. (shrink)

We propose a novel transformer-based architecture that directly maps continuous waveform signals into discrete token sequences, and subsequently into intelligible speech. Our framework integrates a neural waveform-to-token encoder with a transformer-based language model for sequence generation, followed by a token-to-speech decoder for acoustic realization. Unlike traditional speech recognition or text-to-speech pipelines, our model unifies acoustic, symbolic, and generative components into a single transformer-based paradigm, enabling controlled charge-like modulation of information flow and interpretable latent structures. We validate our (...) design using MATLAB/Simulink co-simulation, demonstrating both the theoretical feasibility and practical applicability of this approach. (shrink)

Agent-​​based modeling is showing great promise in the social sciences. However, two misconceptions about the relation between social macroproperties and microproperties afflict agent-based models. These lead current models to systematically ignore factors relevant to the properties they intend to model, and to overlook a wide range of model designs. Correcting for these brings painful trade-​​offs, but has the potential to transform the utility of such models.

The problem of building an effective system of interconnected and purposeful innovative changes in business management is solved in the article. The main purpose of the research is to improve the model of business excellence on the basis of interconnected and purposeful innovative changes in business management. Critical analysis of literature sources and approaches to solving the problem of building a perfect model of business emphasizes the diversity of applied methodological approaches and methods of management innovation. However, in terms of (...) business technologicalization, necessity to accelerate information exchange, development of innovation and, at the same time, development of new threats, the need on the basis of strategizing, intellectualization of management, partnership, compliance with the challenges of the external environment, communication efficiency, leadership transformation, balancing intermediate and final results, there is a need to transform business and management on the basis of strategizing, intellectualization of management, partnership interaction, compliance with the challenges of the external environment, communication efficiency, transformation of leadership, balancing intermediate and final results. Relevance of solving of this scientific issue is that the timely use of innovative tools and management methods in the implementation of strategic intentions and goals forms a high adaptability of companies to transformation processes occurring in their external and internal environment under the influence of digital technologies in business processes. The scientific-theoretical and methodological basis of the study were the following methods: abstract-logical and comparative analysis – to generalize theoretical approaches and confirm the practical importance of solving the problem of building a model of providing business excellence on the basis of interconnected and focused innovative changes in business management; system analysis and modelling – method of building a model of business excellence based on managerial innovation; system-analytical – method of balancing the interaction of the components providing business excellence; generalization – when drawing conclusions based on research results. The object of research is a system of interconnected and purposeful innovative changes in business management. The results of solving the problem of building a model of business excellence while balancing the interaction of the components of such provision and implementation of the process of digital transformation of the business model. The results of the research have practical value for business entities that seek to increase the effectiveness of interconnected and purposeful innovative changes in business management. (shrink)

Advancements in computing, instrumentation, robotics, digital imaging, and simulation modeling have changed science into a technology-driven institution. Government, industry, and society increasingly exert their influence over science, raising questions of values and objectivity. These and other profound changes have led many to speculate that we are in the midst of an epochal break in scientific history. -/- This edited volume presents an in-depth examination of these issues from philosophical, historical, social, and cultural perspectives. It offers arguments both for and against (...) the epochal break thesis in light of historical antecedents. Contributors discuss topics such as: science as a continuing epistemological enterprise; the decline of the individual scientist and the rise of communities; the intertwining of scientific and technological needs; links to prior practices and ways of thinking; the alleged divide between mode-1 and mode-2 research methods; the commodification of university science; and the shift from the scientific to a technological enterprise. Additionally, they examine the epochal break thesis using specific examples, including the transition from laboratory to real world experiments; the increased reliance on computer imaging; how analog and digital technologies condition behaviors that shape the object and beholder; the cultural significance of humanoid robots; the erosion of scientific quality in experimentation; and the effect of computers on prediction at the expense of explanation. -/- Whether these events represent a historic break in scientific theory, practice, and methodology is disputed. What they do offer is an important occasion for philosophical analysis of the epistemic, institutional and moral questions affecting current and future scientific pursuits. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges associated with (...) AI integration, such as resistance to change, ethical concerns, and data security issues. The paper concludes by offering insights into future trends and implications for organizations navigating the evolving landscape of AI-driven change. (shrink)

Information-theoretic approaches to formal logic analyze the "common intuitive" concepts of implication, consequence, and validity in terms of information content of propositions and sets of propositions: one given proposition implies a second if the former contains all of the information contained by the latter; one given proposition is a consequence of a second if the latter contains all of the information contained by the former; an argument is valid if the conclusion contains no information beyond that of the premise-set. This (...) paper locates information-theoretic approaches historically, philosophically, and pragmatically. Advantages and disadvantages are identified by examining such approaches in themselves and by contrasting them with standard transformation-theoretic approaches. Transformation-theoretic approaches analyze validity (and thus implication) in terms of transformations that map one argument onto another: a given argument is valid if no transformation carries it onto an argument with all true premises and false conclusion. Model-theoretic, set-theoretic, and substitution-theoretic approaches, which dominate current literature, can be construed as transformation-theoretic, as can the so-called possible-worlds approaches. Ontic and epistemic presuppositions of both types of approaches are considered. Attention is given to the question of whether our historically cumulative experience applying logic is better explained from a purely information-theoretic perspective or from a purely transformation-theoretic perspective or whether apparent conflicts between the two types of approaches need to be reconciled in order to forge a new type of approach that recognizes their basic complementarity. (shrink)

Modern logic is primarily concerned with formally valid arguments, namely arguments where the conclusion is a logical consequence of the premises. Intuitively, this means that the conclusion necessarily follows from the premises in virtue of their logical form alone. Such arguments form the backbone of philosophy, mathematics, and science in general: for instance, the famous Pythagorean Theorem is a logical consequence of the axioms of Euclidean geometry. However, the task of defining the concept of logical consequence is far from straightforward. (...) Logical consequence is the glue that holds our belief system together, but what holds the glue together? This question cuts deep into the very foundations of scientific knowledge. -/- The standard model-theoretic definition of logical consequence, originally formulated by Alfred Tarski in 1936, has been questioned by philosophers from various perspectives over the past few decades. John Etchemendy famously argues that Tarski’s account fails to capture the pre-theoretic, intuitive concept of logical consequence. Logical pluralists suggest that there is more than one correct concept of it. On the other hand, historians have pointed out that Tarskian definitions of logical consequence had already been proposed by Parisian logicians in the 14th century, and again by Bernard Bolzano in the 19th century. It has been suggested that their proposals may have captured the intuitive concept of logical consequence even better than Tarski’s. And yet, the fact that their proposals were not widely accepted at their own time suggests that the intuitive concept itself may have changed over time. -/- The aim of this dissertation is to analyse the continuities and discontinuities between Tarski’s account and its premodern precedents. My overall thesis is twofold. On one hand, I show that a Tarskian ‘substitutional’ criterion of logical consequence was more widespread in the 14th century than has been previously thought, and that it continued to be promoted by many prominent textbooks of logic in the early modern era until it was subsumed by the Aristotelian theory of the syllogism. On the other hand, I argue that the notion of logical form presupposed by most 14th-century authors was distinctively non-Tarskian. Back then, logical form was primarily about relationships among concepts, but it is now taken to be just about the structural properties of propositions. I suggest that Tarski is partly to blame for this transformation: his definition was successful precisely because he deliberately suppressed some philosophical intuitions to suit the needs of mathematical logicians. -/- The dissertation consists of five articles. Article I focuses on the theories of formal consequence by the 14th-century logician William of Ockham and his student Adam Wodeham. Both distinguished between two kinds of formal consequence (consequentia formalis), the first of which anticipates Tarski’s account, but their second kinds of formal consequence differ. I show that Wodeham’s two kinds of formal consequence are based on two kinds of logical form. -/- In Article II, I further develop and defend what I call the ‘dual form hypothesis’. I ask why the 14th-century Parisian tradition of formal consequence, as close as it is to Tarski’s definiton, was not as influential at the time as the rival British tradition. I argue that the two traditions were closer to each other than we have thought. They agreed that formal consequence involves a truth-preserving form, and only disagreed on whether that form is structural or conceptual. -/- Article III traces the early modern reception of the Parisian definition through a large-scale analysis of Early English Books Online, which contains almost all books printed in the British empire from the 15th to the 17th century. I show that Parisian-style definitions were surprisingly widespread in textbooks of logic that were used for teaching in Oxford, Cambridge, and Dublin for a long time. -/- In Article IV, I argue that Tarski’s definition of logical consequence is not a conceptual analysis (as Etchemendy and others have claimed) but a Carnapian explication. The point is that Tarski did not even try to capture the essence of a pre-existing everyday concept; on the contrary, he deliberately sacrificed some everyday intuitions on the altar of formal correctness. -/- Finally, Article V takes on the challenge of formalizing the medieval British definition of formal consequence in modern logic. I try out several approaches and conclude that Gillian Russell’s recent account of logical consequence can be applied to provide a fruitful formalization of the medieval notion. (shrink)

Purpose: This study investigates the transformative role of augmented reality (AR) and virtual reality (VR) technologies in e-commerce and digital marketing. It aims to understand how these immersive technologies enhance consumer experiences by addressing challenges such as product visualization, consumer trust, and engagement while fostering higher purchase intent and customer satisfaction. Design/Method/Approach: A systematic literature review synthesizes findings from empirical and theoretical studies published between 2011 and 2024. The methodologies analyzed include experimental designs, market analyses, and conceptual frameworks assessing the (...) integration of AR and VR technologies in online retail. Findings: The findings indicate that AR enhances online shopping through features such as virtual try-ons and spatial placement visualization, reducing return rates and increasing purchase confidence. VR, on the other hand, provides immersive environments that simulate physical shopping experiences, strengthening consumer-brand connections. While AR demonstrates broader applicability in fostering interactive and personalized experiences, VR remains limited by accessibility and cost constraints. Both technologies exhibit immediate costs but offer long-term benefits, positively influencing conversion rates and customer loyalty. Theoretical Implications: This study contributes to consumer behavior research by applying value perception models, immersive technology frameworks, and engagement metrics to the e-commerce landscape. It refines existing theoretical perspectives on technological adoption by highlighting the interplay between sensory engagement, emotional connection, and consumer decision-making. Practical Implications: The research underscores the strategic importance of integrating AR and VR into digital marketing and e-commerce platforms. It suggests leveraging AR for product categories requiring spatial interaction and using VR for high-detail product exploration. The study provides actionable insights for businesses looking to enhance online shopping experiences through immersive technologies. Originality/Value: This study offers a comprehensive synthesis of AR and VR applications in e-commerce, highlighting their potential to reshape online shopping. By bridging the gap between physical and digital retail experiences, it provides a fresh perspective on how immersive technologies can drive engagement, accessibility, and personalized consumer interactions. Research Limitations/Future Research: While this study synthesizes existing literature, empirical validation through longitudinal studies and cross-industry applications is necessary. Future research should explore the long-term effects of AR and VR adoption on consumer trust, loyalty, and behavioral changes. Additionally, further exploration is encouraged into gamification, artificial intelligence (AI) integration, and demographic-specific implementations to drive sustainable engagement. (shrink)

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)

This paper develops a unified philosophical model beginning with a simple proposition: if the universe were to be understood in one word, that word would be chemistry. Not chemistry merely as a scientific discipline, but as a metaphor for interaction, transformation, bonding, dissolution, and reconfiguration. Extending this analogy, the paper argues that nature does not recognize moral categories such as “clean” or “dirty,” but operates solely through transformation. Human psychological conflict, however, emerges when natural processes of reaction are interrupted through (...) suppression or possession. The study proposes that awareness restores coherence by dissolving internal division. The universe transforms without conflict; the mind conflicts when it divides itself. (shrink)