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Profiling Bilinguals: The Concurrent and Longitudinal Associations Between Executive Function and Reading Proficiency
No full textA Study on the Influence of the Public's Implicit Gender Bias Towards Law Enforcement Officers on Law Enforcement Compliance
No full textThe compliance degree of grassroots law enforcement is a key indicator for the modernization of grassroots governance. The implicit gender bias of the public towards law enforcement officers, as a potential psychological factor, has not been systematically explored regarding its impact on law enforcement compliance. This study focuses on the implicit gender bias of the public towards law enforcement officers in grassroots law enforcement interactions, aiming to reveal the characteristics of the implicit gender bias of the public towards law enforcement officers of different genders, clarify the effect and characteristics of this bias on the compliance degree and the tendency of compliance nature, and also explore the differences in the influence of the bias in different grassroots law enforcement scenarios.
The study adopts an experimental method combining the Implicit Association Test (IAT) and simulated law enforcement scenarios. Through the design of sub-IAT tests in two dimensions of ability and authority, and warmth and affinity, it measures the implicit gender bias of the public towards grassroots law enforcement officers. Three types of high-frequency grassroots law enforcement scenarios, namely, urban management officers regulating street vending, traffic police inspecting illegal parking, and market supervision verifying business licenses, are selected, and scenario materials with only different genders of law enforcement officers are created. Combined with the scale measurement, the comprehensive score of law enforcement compliance and the cooperation-obedience nature tendency of the subjects are measured. The study will verify the existence and dimension characteristics of the public's implicit gender bias through data statistical analysis, and analyze its influence direction, degree, and scene differences on law enforcement compliance.
It is expected that the research results will confirm that the public has dual-dimensional implicit gender bias towards grassroots law enforcement officers, that is, they tend to associate male law enforcement officers with ability and authority attributes, and female law enforcement officers with warmth and affinity attributes. This implicit bias will significantly affect law enforcement compliance behavior, that is, the implicit perception of authority of male law enforcement officers is likely to trigger obedient compliance, and the implicit perception of affinity of female law enforcement officers is likely to trigger cooperative compliance
Fasting Across Scriptural Traditions and Metabolic Timescales: A Constraint-Based Multimodal Encoding Framework for Fasting-Responsive Genes
No full textThis OSF project hosts an interdisciplinary framework for exploring fasting-responsive genetic pathways through constrained multimodal translation. Building upon previously disclosed dinucleotide-based methodologies for genetic sonification and hue-class visual encoding (Sagar, 2026a; Sagar, 2026b), the present work situates fasting as both a conserved metabolic intervention and a cross-civilizational contemplative practice
The Geometric Resolution of Rayleigh Plesset Singularity
No full textVacuum Viscoelasticity and the Casimir-Bounded Collapse: A Topological Resolution to the Rayleigh-Plesset Singularity
Vacuum Viscoelasticity and the Casimir-Bounded Collapse: A Topological Resolution to the Rayleigh-Plesset Singularity
Single-bubble sonoluminescence (SBSL) presents a persistent discontinuity in classical hydrodynamics, where the Rayleigh-Plesset equation predicts infinite energy density as the bubble radius approaches zero. This paper resolves this singularity by modeling the terminal cavity collapse under a viscoelastic vacuum boundary condition. We introduce a Geometric Yield Stress derived from the Gibson-Ashby constitutive law for cellular solids, constrained by a Geometric Efficiency Factor (e/π) representing the spherical-to-linear mapping limit. Our derivation predicts a vacuum yield limit of 1.46 GPa. At this precise threshold, the vacuum is forced into a Structural Lattice Lock, maintaining an impedance-matched, isomorphic mechanical response to the isothermal bulk modulus of Solid Argon. We validate this effect through the introduction of the Lattice Scalar SL=7 which defines the harmonic fundamental mode of the vacuum's yield stress. By establishing as the denominator, a discrete harmonic scaling law emerges, reducing the empirical stiffness ratios of the noble gases to exact integer fractions (e.g., Ne = 3/7, Ar = 7/7, Kr = 9/7).
We further validate this model through a Newtonian work-energy analysis, demonstrating that the collapse is arrested by a "hard wall" boundary condition. The calculated braking distance (5.32 Å) converges to the experimental lattice constant of Argon with a deviation of 0.05%. Finally, we demonstrate that the resulting vacuum lattice fracture generates an induced electric field of . This localized dielectric breakdown provides a deterministic electro-mechanical origin for the photonic flash (Vacuum Triboluminescence), refuting standard thermal bremsstrahlung models. These findings establish the sonoluminescent "singularity" not as a mathematical divergence, but as a physical phase transition where vacuum energy crystallizes into a finite metric lattice
Deep Beats, Deep Thoughts? Predicting Fluid Intelligence from Natural Music Listening Behavior
No full textThis repository contains supplementary information and materials related to the article “Deep Beats, Deep Thoughts? Predicting Fluid Intelligence from Natural Music Listening Behavior”
Toward Hybrid Architectures: Functional AI and the Limits of Silicon Substrates: An ontological and dynamical framework for advanced artificial cognition
No full textMaster of record (Zenodo DOI):
https://doi.org/10.5281/zenodo.18583941
This OSF project serves as the supplementary workspace and documentation hub.
This research position paper develops an ontological and dynamical framework for understanding the limits of silicon‑based artificial intelligence and the material conditions required for genuine emergent cognition. Contemporary AI systems exhibit remarkable functional capabilities, yet their digital substrates lack the continuous, energetically grounded, and self‑organizing dynamics necessary for stabilizing inner states, multiscale feedback, and coherent internal trajectories.
The paper argues that consciousness‑relevant emergence is a material phenomenon that cannot be simulated or instantiated within discrete computational architectures. It identifies the systemic thresholds—nonlinear coupling, metastability, energetic grounding, and multiscale integration—that biological systems satisfy and digital systems cannot.
Building on these principles, the paper proposes hybrid cognitive architectures in which functional AI is coupled with dynamically rich substrates such as neuronal organoids, biohybrid systems, organic memristive materials, or other continuous, energy‑driven media. These substrates provide the physical conditions for coherence, continuity, and self‑organization, while silicon‑based components supply structure, task‑level organization, and symbolic processing.
The work outlines the implications of this paradigm for AI research, cognitive science, ethics, and human–AI interaction. It clarifies the distinction between simulation and instantiation, addresses common counterarguments, and positions the model within existing theoretical frameworks without reducing it to any of them. The paper concludes by identifying the material and systemic thresholds required for true emergence in future hybrid human–AI systems.
Author’s Note
This paper is not an empirical study but a structural argument. It synthesizes insights from systems theory, neuroscience, materials science, and philosophy of mind to clarify the material conditions under which consciousness can, in principle, arise. The aim is not to predict specific technologies or make metaphysical claims, but to delineate the architectural boundaries that current digital systems cannot cross and to outline the substrate‑level requirements for future emergent cognition
Advancements toward clinical application of AI–driven CT analysis in pulmonary hypertension: a systematic literature review
No full textIn this systematic literature review, we evaluate the current evidence on AI-driven CT analysis in PH with a focus on advancements toward clinical applicability. We will examining the role of AI-based CT quantification in: (1) PH detection and diagnosis; (2) phenotyping and aetiological classification; (3) prognostication and risk stratification; and (4) assessment of management response. We aim to identify strengths, limitations, and gaps in the literature, which will clarify the translational potential of AI-driven CT analysis and inform future research priorities necessary for clinical adoption
Dyslexia Eye Tracking COrpus (DECO): First- and Second Language Book Reading in Adults with Dyslexia
No full textOpenly available eye-tracking corpora have been indispensable for the progress of psycholinguistic theories of reading. Past corpus work extensively covered typical reading in a range of languages, but left reading difficulties relatively under documented. In this article, we present a novel corpus, the Dyslexia Eye Tracking COrpus (DECO). It includes eye-tracking data collected from 20 Dutch - English bilingual adults with a diagnosis of developmental dyslexia. They read an entire novel (almost 60.000 words), with one half presented in their first language (Dutch) and the other half in their second language (English). After each chapter the participants answered multiple reading comprehension questions. Additionally, all participants completed several measures of linguistic abilities, including vocabulary, spelling, a one-minute reading test and a language questionnaire. This corpus is the largest of its kind and is a direct extension of the existing GECO corpus of typical reading (Cop, Dirix, Drieghe & Duyck, 2017). In combination with GECO, it provides researchers with a unique resource to study naturalistic reading in dyslexia and its intersection with bilingualism. All data and materials will be made available upon publication
Residual Romantic Attachments influence Decisions under Uncertainty
No full textMillions of breakups occur annually around the world, yet little is known about how they influence a key process of human cognition: value-based decision-making under uncertainty. Across two studies, we investigated how lingering romantic attachment to an ex-partner affects value-based decision-making under different types of uncertainty (future-oriented versus probabilistic). In Study 1 (N=144), we showed that stronger romantic attachment to an ex-partner led to making riskier decisions under affective influence, resulting in suboptimal decisions that accumulated to indirect costs exceeding $50 during an hour-long experiment. In Study 2 (N = 419), we found that stronger residual feelings toward an ex-partner are associated with steeper devaluation of future rewards. Specifically, individuals who struggled to move on from a breakup discounted future rewards such that their value diminished by half approximately two weeks earlier than those less attached. These findings may have practical implications for informing relationship counseling and economic policy, as nearly half of those who experience a breakup in the past year may be significantly affected, potentially perceiving future-oriented investments (e.g., monetary savings) as less desirable than those who have moved on