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Conservation of Entropy and Landauer Limit Approach to Gravity in a Relative Holographic Principle Framework
No full textThis model describes dark energy, dark matter, gravity, movement in one's own reference frame, entropy conservation, and why intrinsic spin exists
ESET 3.0 — Elastic Spacetime with Secular Bulk Memory, Curvature-Gated Strong-Field Completion, and Causal Retrodiction (LRE)
No full textESET 3.0 is a unified, GR-compatible framework that models spacetime as a weak-dissipation elastic medium augmented by a causal bulk-memory (Maxwell–Cattaneo / Israel–Stewart) stress channel. The bulk memory acts as an isotropic, tensor-safe effective pressure that is AC-suppressed and DC-accumulating, enabling a controlled “horizon/ISW lane” in cosmological perturbations without introducing anisotropic stress. ESET 3.0 also includes a curvature-gated strong-field completion module that activates additional memory dynamics only in high-curvature regimes while reducing smoothly to the weak-field limit. Finally, it provides a Causal Retrodiction component (Light Rewind Engine, LRE) that uses closure residual diagnostics to support inference over retarded dynamics without invoking retrocausality. This OSF project hosts the full LaTeX source, derivations, and a battle-testing harness outlining falsifiable observational lanes (CMB ISW/lensing/LSS and lab phase/clock templates)
Association of Childhood Factors with Positive Functioning in Established Adulthood: A Prospective Longitudinal Study
No full textThis prospective birth cohort study aims to (1) identify distinct profiles of positive functioning in established adulthood (34 years) across the domains of risk-taking behaviours, wealth and social relationships with parents, partners and peers. We will first determine whether there are distinct profiles of positive functioning across the various domains in established adulthood and then, investigate (2) the childhood predictors of profiles of positive functioning and (3) the association between different profiles of positive functioning and satisfaction with life in established adulthood
Implementation Outcomes and Effectiveness of a Personalized Single Session Cognitive Behavioral Intervention for Depression and Anxiety
No full textSingle-session interventions (SSIs) have become increasingly popular
psychotherapeutic interventions in recent years due to their potential in providing a therapeutic
and problem-focused experience in one encounter. However, less focus has been given to
dissemination and implementation outcomes for SSIs within existing healthcare settings. This
study evaluated the effectiveness and suitability for broad implementation of a personalized
Single Session Cognitive Behavioral Intervention (SSCBI) for depression and anxiety,
delivered in a university-based training clinic in Singapore. Using a mixed-methods design,
adult therapy clients (N = 24) completed pre-treatment and follow-up measures assessing
depression, anxiety, and cognitive and affective subjective well-being. Quantitative analyses
showed reductions in both symptoms of depression (d = 0.94, p < .001) and anxiety (d = 0.45,
p = .038). Semi-structured interviews were conducted with clients (n = 9) and clinicians (n =
9), and thematic analysis identified twelve key themes mapped to five implementation
outcomes: acceptability, appropriateness, feasibility, fidelity, and adoption. Both clients and
clinicians reported high acceptability of the intervention, highlighting its structure, relevance,
and utility in supporting coping skill development. Clinicians felt the protocol was feasible and
appropriate for clients with relatively less complex presentations, with full protocol adherence
achieved across all therapeutic sessions. Recruitment (63.5%) and completion (78.1%) rates
exceeded the pre-registered feasibility benchmarks. These findings provide preliminary
evidence supporting our personalized SSCBI as an effective and scalable brief psychological
intervention, particularly suited for resource-limited settings. Future research should
investigate its longer-term impact, cost-effectiveness, and broader applicability in community
and primary care contexts
Foreign Direct Investment, Efficiency, and Regional Disparities in Uganda’s Coffee Sector
No full textForeign direct investment (FDI) is widely promoted as a catalyst for agricultural transformation in developing countries, yet empirical evidence on its efficiency effects remains limited and mixed. This study examines the association between foreign direct investment and coffee production efficiency in Uganda, with particular attention to regional heterogeneity and policy context. Using a panel of five coffee-producing regions over the period 1995–2024, we estimate technical efficiency scores through stochastic frontier analysis and subsequently analyze their relationship with FDI exposure using fixed-effects panel regressions.
The results indicate that foreign direct investment is positively and significantly associated with coffee production efficiency, reflecting improvements in the use of existing inputs rather than expansion of cultivated area. On average, a one percent increase in FDI inflows is associated with an approximately 0.07–0.09 percent increase in production efficiency. However, these efficiency gains are unevenly distributed across regions, with stronger effects observed in relatively mature coffee-producing areas. Complementary factors including technology adoption, infrastructure, capital formation, and governance quality are also positively associated with efficiency, conditioning the magnitude of investment-related gains. In addition, the relationship between FDI and efficiency strengthens following the implementation of Uganda’s National Coffee Policy, highlighting the role of institutional reforms.
The findings suggest that while foreign investment can support efficiency-enhancing growth in smallholder-based agricultural systems, its benefits are neither automatic nor uniformly distributed. Effective investment strategies therefore require complementary public investments and institutional frameworks to promote inclusive and regionally balanced agricultural development
Constitutive Quantum Phase Field (CQPF): A Phenomenological Framework for Intrinsic Irreversibility and the Emergence of Schrödinger Dynamics
No full textWe present a phenomenological framework in which microscopic irreversibility arises from constitutive phase fluctuations of an underlying quantum phase field (CQPF). The model introduces a stochastic field equation with local phase noise characterized by a single dissipation rate χ. We demonstrate that, in the conservative limit χ→0, the dynamics reduces exactly to the Schrödinger equation, with an effective particle mass emerging from the kinetic coefficient of the constitutive field. Averaging over phase fluctuations yields a completely positive Lindblad master equation describing intrinsic pure dephasing. The framework predicts a temperature-independent decoherence floor, yielding testable constraints from precision experiments such as optical lattice clocks (χ≲10−3 s−1), Ramsey interferometry, and macromolecular interferometers. The CQPF should therefore be regarded as an effective open-system description of vacuum-induced phase diffusion, providing a falsifiable alternative to purely statistical accounts of the quantum arrow of time
AI Blind Spots in South Asian Cardiometabolic Risk: A Scoping Review of Food and Social Determinant Measurement
No full textCardiometabolic disease, including cardiovascular disease, type 2 diabetes, dyslipidemia, and metabolic syndrome, has historically and disproportionately affected South Asian patient populations globally1. Across both South Asia and the South Asian diaspora, individuals experience an earlier onset, more aggressive progression, and an overall higher mortality rate from cardiometabolic conditions compared to most other ethnic groups2,3. Importantly, these disparities still persist even at lower BMI thresholds and amongst individuals who have “normal” body weight, reflecting how there is a unique attribution to metabolic patterns including atherogenic dyslipidemia, insulin resistance, and visceral adiposity4. Although these metabolic profiles have been documented, risk assessment tools and frameworks regarding cardiometabolic disease continue to be anchored in Eurocentric phenotypes and fail to capture the nuances of South Asian risk factors5.
Nutritional exposures add a layer of complexity. South Asian dietary habits and patterns, whether based on traditionality, can be shaped by contemporary food environments, or migration-adapted ways, with underlying metabolic vulnerabilities that can magnify cardiometabolic risk6. Nutritional components such as refined carbohydrates, energy-dense oils, ultra-processed food (UPF), culturally culinary practices, and changing food accessibility in both South Asia and Western diasporic contexts can contribute to elevated metabolic burden7. Although this is understood, these exposures are rarely measured in a consistent and culturally competent way. As a result, the nutritional determinants of cardiometabolic disease in this population remain poorly understood and consistently undermeasured8.
The rapid rise of use in artificial intelligence (AI) and machine learning (ML) in cardiometabolic research has further amplified the consequences of these measurement gaps. AI are increasingly informing and providing patient risk stratification, dietary assessment, cardiometabolic prediction and clinical decision support. However, AI systems are only able to learn from the variables encoded in the training data that are provided to them. Due to the lack of datasets from South Asian specific metabolic indicators, the omission of culturally relevant dietary constructs, and the omission of social and structural determinants, the resulting models embed blind spots that produce systemic misclassification and inequitable performance9.
Taken together, these consistent trends reveal a critical gap: although cardiometabolic disease in South Asians is shaped by a dynamic interaction between metabolic traits, nutrition-related exposures, and social/structural determinants, the measurements of these determinants remain fragmented and poorly aligned within equitable development of AI/ML systems. This scoping review addresses this gap by systematically examining how studies evaluating cardiometabolic risk in South Asian populations measure social, structural, and commercial determinants of nutrition, as well as how these measures intersect with AI and ML-based prediction. Through the synthesis of data, this review will critically identify blind spots, inconsistencies, and fairness to outline stronger and more equitable pathways for AI systems in South Asian health
Supplementary Materials: How Pedagogy, Action Expectations, and Executive Function Jointly Shape 3-7-Year-Olds' Event Processing and Exploratory Play
No full textSupplementary materials for Study 1 and Study 2 related to Diana Daschel's dissertation project
Factores Estructurales de la Inclusión Digital en Salud
No full textIntroducción: La digitalización de la salud, impulsada por la COVID-19, ha mejorado servicios, pero plantea desafíos de equidad e inclusión. Garantizar la inclusión digital es clave, ya que depende del acceso tecnológico, competencias y diseño inclusivo, aunque faltan datos sobre facilitadores y barreras según pacientes y profesionales. Los pacientes afrontan obstáculos como falta de acceso, habilidades, apoyo y confianza, mientras el personal sanitario adopta tecnología según su utilidad, facilidad y respaldo institucional. Aunque organismos internacionales sugieren políticas basadas en equidad y derechos humanos, se requiere más evidencia sobre los factores estructurales que afectan la inclusión digital en salud.
Objetivo: Mapear y sintetizar sistemáticamente la evidencia científica disponible sobre factores estructurales facilitadores y obstaculizadores de la inclusión digital en salud desde las perspectivas de pacientes y profesionales sanitarios, con el fin de establecer un principio articulador de la gestión y garantía de la salud, para el periodo 2020-2025.
Métodos: Revisión de alcance siguiendo metodología JBI. Búsquedas sistemáticas en nueve bases de datos electrónicas y fuentes de literatura gris. Selección, extracción y síntesis por investigador individual con estrategias robustas de garantía de calidad: verificación aleatoria del 15%, consulta a expertos de requerirse. Síntesis mediante estadística descriptiva, análisis narrativo temático y mapeo visual.
Resultados esperados: Identificación y categorización de dimensiones de inclusión digital, mapeo de barreras y facilitadores específicos, desarrollo de repositorio de indicadores de medición, y análisis comparativo para fundamentar políticas de salud digital equitativas