Abstract: This study investigates factors influencing public-sector employees’ acceptance of an EDRMS in Saint Vincent and the Grenadines by extending the Technology Acceptance Model (TAM) with organisational and information-systems quality factors. A quantitative, cross-sectional survey was conducted among government employees with prior EDRMS experience (N = 122). Structural equation modelling using AMOS tested relationships among system quality, service quality, subjective norm, top management support, trust, perceived ease of use, perceived usefulness, and behavioural intention. Behavioural intention was mainly driven by perceived usefulness (β = 0.58, p < .001) and perceived ease of use (β = 0.17, p = .043), explaining 47.8% of the variance. Service quality positively influenced perceived usefulness (β = 0.45, p < .001) and ease of use (β = 0.32, p < .001), while system quality positively affected ease of use (β = 0.49, p < .001). Subjective norm was positively related to perceived usefulness (β = 0.27, p = .002). Top management support and trust were not significant predictors. The study contributes evidence from a small-island developing-state public sector, highlighting the importance of service support and usability beyond classic TAM. Policymakers should emphasise system usability, reliability, and responsive training and support services to enhance EDRMS adoption.

Abstract:

Background/Objectives: The Metabolic Score for Insulin Resistance (METS-IR), a non-insulin-based index of insulin resistance (IR), and subclinical myocardial injury (SCMI), identified by electrocardiogram (ECG), are each associated with cardiovascular disease (CVD). However, their joint impact on mortality remains unclear. We examined the association of METS-IR with SCMI and evaluated the individual and combined associations of SCMI and IR with cardiovascular mortality. Methods: We analyzed adults without baseline CVD from the Third National Health and Nutrition Examination Survey. METS-IR was calculated from fasting glucose, triglycerides, high-density lipoprotein cholesterol, and body mass index and categorized as low (<75th percentile) or high (≥75th percentile). SCMI was defined as a cardiac infarction injury score ≥10 on ECG. Multivariable logistic regression assessed associations between METS-IR and SCMI, and Cox regression estimated cardiovascular mortality risk across SCMI-IR combinations. Results: Among 6,079 participants, 14.1% had SCMI. Higher METS-IR was associated with greater SCMI odds (OR(95%CI): 1.58(1.31-1.90)). Over a median of 18.8 years, 563 (9.1%) cardiovascular deaths occurred. Both SCMI and high IR were individually associated with increased cardiovascular mortality ((HR(95% CI): 1.41(1.19–1.69) and 1.32(1.09–1.59), respectively). Participants with both SCMI and high IR had the highest risk (HR 1.92; 95% CI 1.49–2.50) compared with those with neither condition. Conclusions: In adults without prior CVD, METS-IR was positively associated with SCMI. The coexistence of SCMI and high IR identified a subgroup at nearly twofold higher risk of cardiovascular mortality, supporting combined use of ECG-based injury markers and metabolic indices for cardiovascular risk stratification.

Abstract: Background: Preterm birth (PTB, <37 weeks of gestation) affects approximately 10% of pregnancies in Mexico and remains a leading cause of neonatal morbidity and mortality worldwide. The vaginal microbiome has emerged as a potential biomarker of PTB risk, with dysbiotic states characterized by reduced Lactobacillus dominance and increased microbial diversity implicated in inflammatory pathways leading to premature parturition. However, Hispanic/Latino populations remain severely underrepresented in microbiome-based PTB prediction research, limiting clinical translation of existing models. Methods: We developed and evaluated machine learning models for PTB prediction using vaginal microbiome data from 43 pregnant Mexican women (110 longitudinal samples, 14 preterm births <37 weeks). Genus-level relative abundances were processed using centered log-ratio transformation within a rigorous nested cross-validation framework with subject-level splitting to prevent data leakage. We systematically compared Random Forest and Elastic Net algorithms across three clinical feature selection strategies: (1) minimal DREAM-style adjustment (gestational age + maternal age); (2) literature-based comprehensive features (10 evidence-based PTB risk factors); and (3) data-driven empirical selection (top 10 variables selected independently within each cross-validation fold using univariate screening with p<0.20). Microbiome features included either ANCOM-BC2 differentially abundant taxa (selected independently within each fold) or full filtered profiles. Critically, all feature selection procedures were executed within cross-validation folds using only training data, ensuring unbiased performance estimates. Results: Random Forest with data-driven feature selection and full microbiome achieved optimal discrimination (AUROC 0.849 ± 0.130; PRAUC 0.571 ± 0.208), with sensitivity 80.0% and specificity 47.3% at the optimized threshold. This performance exceeds the DREAM Challenge benchmark for late PTB (AUROC 0.69) despite substantially smaller sample size. Feature importance analysis identified anthropometric variables (BMI, pre-pregnancy weight) and key microbial genera (Methylobacterium, Lactobacillus, Anaerococcus) as primary drivers. ANCOM-BC2 analysis across cross-validation folds revealed consistent enrichment of Peptostreptococcus (selected in 100% of folds) and Mycoplasma (80% of folds) in preterm births—taxa mechanistically linked to Toll-like receptor activation, pro-inflammatory cytokine production, and matrix metalloproteinase-driven cervical remodeling. Conclusions: A machine learning-based PTB prediction model here developed specifically for a Mexican cohort, demonstrates feasibility of microbiome-based risk stratification in Latin American populations. The rigorous nested cross-validation with fold-specific feature selection prevented data leakage that has inflated performance in previous studies. However, limited sample size (wide confidence intervals, SD 0.13–0.25) points out to the need of further studies, in particular, external validation in larger, independent cohorts before broad clinical implementation. This work addresses a critical equity gap and establishes a methodological framework for population-specific precision medicine in pregnancy complications.

Abstract: A composite, eighteen-year long record on in-situ surface meteorology and computed bulk air-sea fluxes of heat, freshwater, and momentum from an ocean site windward of Oahu are presented. Data were logged every minute over eighteen years. Methods and data quality are discussed. Statistics of one-minute, one-hour, and one-day times series are presented, and daily averaged time series provide an overview of this trade wind site. Mean wind was 6.8 m s−1 toward the west southwest, mean ocean heat gain was 23.2 W m−2 with freshwater loss of 1.2 m yr−1. Energetic sub-diurnal variability was found, with spectral peaks in solar insolation and sea level pressure, and transient, short-lived signals including insolation above the clear sky value, short periods of warm air, and downdrafts of dry air. Mean daily cycles are presented. Longer lasting events, including periods of ocean cooling, ocean heating, and hurricanes, are explored. Mean annual cycles are presented. The ocean loses heat from January through early May; then gains heat until late October and returns to loosing heat. Normalized by duration, the events examined have potential for significant contributions to the heat, freshwater, and mechanical energy exchanges.

Abstract: Background Near-infrared fluorescence–guided surgery (FGS), predominantly using indocyanine green (ICG), is increasingly adopted to support intraoperative decision-making in colorectal cancer (CRC). This narrative review synthesizes current evidence across four major clinical applications—assessment of anastomotic perfusion, lymphatic mapping, tumor localization, and metastasis detection—and outlines translational directions (targeted probes, multimodality, quantitative analytics/AI). Methods: We conducted a narrative, non-systematic review of clinical and translational studies on intraoperative fluorescence imaging in CRC, with a primary focus on ICG-based techniques and emerging targeted agents. Representative studies were selected to illustrate benefits, technical constraints (dose, timing, optics), and methodological limitations; formal risk-of-bias assessment and meta-analysis were not performed given the heterogeneity of designs. Results: (1) Anastomotic perfusion: ICG fluorescence angiography reduces uncertainty regarding transection lines and tissue viability; impact on anastomotic leak appears protocol-dependent and is likely enhanced by standardized acquisition parameters and objective, real-time quantification. (2) Lymphatic mapping: ICG improves visualization of drainage pathways and nodal basins but does not discriminate benign from metastatic involvement; the utility is primarily anatomic/functional. (3) Tumor localization: FGS facilitates identification of lesions and margins in selected scenarios; non-contrast adjuncts (e.g., hyperspectral imaging) may complement perfusion assessment. (4) Metastases: In the liver, FGS is useful as a rule-out tool and for margin guidance; in peritoneal disease, targeted anti-CEA approaches integrated with multimodality workflows (NIR + SPECT/CT + gamma-probe) demonstrate feasibility and clinical promise. Conclusions: ICG-based FGS is sufficiently mature for selective use in CRC—most notably for anastomotic perfusion assessment and resection guidance. Broader adoption will require protocol standardization, robust real-time quantification, and multicenter validation of targeted probes with clinically meaningful endpoints.

Abstract: Early wildfire smoke detection is critical for preventing small ignitions from escalating into large-scale fires, yet early-stage smoke plumes are often faint, low-contrast, and spatially small. When full-resolution frames are resized to satisfy fixed-input detector architectures and enable efficient batched GPU inference, these subtle cues are further diminished, leading to missed detections and unreliable scores near deployment thresholds. Existing remedies such as multi-scale inference, slicing/tiling, or super-resolution could improve sensitivity, but typically incur substantial overhead from multiple forward passes or added network components, limiting real-time use on resource-constrained platforms. To mitigate these challenges, we propose a composite multi-resolution detection framework that improves sensitivity to small smoke regions while maintaining single-pass inference. Motivated by the fact that most operational wildfire monitoring systems rely on UAV platforms and mountain-top CCTV surveillance, their wide-field imagery typically contains a large sky region above the horizon where early smoke is most likely to first become visible. Accordingly, crop placement is guided by a skyline prior that prioritizes this high-probability sky band while retaining the remaining scene for global context. A dynamic compositing stage stacks a global view with a high-resolution, sky-aligned band into a standard square detector input, preserving context with minimal added cost. Detections from the two views are reconciled via coordinate restoration and non-maximum suppression. For deployment, a lightweight second-stage classifier selectively re-evaluates low-confidence detections to stabilize decisions near a fixed operating threshold without retraining the detector. Across Early Smoke and Pyro-SDIS, the method improves AP@0.5 by +0.060/+0.036 and AP_small by +0.151/+0.025, respectively, with accuracy-efficiency trade-offs supported by ablation studies and deployment-time latency analysis.

Abstract: The geometric contribution to the superfluid density has been found to be of great importance in the inner crust of neutron stars. In this work we clarify how this contribution arises in the context of a band theory for neutrons. Specifically, we derive the dependence of the superfluid density on the magnitude of the pairing gap when the system has many bands cutting the Fermi energy, as it is the case for the neutrons in the inner crust. Also, in the perturbation theory framework, we find that it is essential to account for the corrections to the (Bogoliubov) quasi-particle states in order to get the geometric contribution. Accounting only for the corrections to the (Hartree-Fock) single-particle states leads to the conventional contribution only.

Abstract: Background/Objectives: Refractory macular holes (MH) that persist after conventional internal limiting membrane (ILM) peeling pose a significant surgical challenge. This study analyzed the anatomical and functional outcomes of epiretinal human amniotic membrane (hAM) transplantation in these patients. Methods: This retrospective study included 10 eyes of 10 patients with refractory MH. All patients underwent 25-gauge pars plana vitrectomy, epiretinal cryopreserved hAM transplantation, and C3F8 gas tamponade. The large hAM graft was placed over the macula with the chorion side facing the retina. Preoperative and postoperative best-corrected visual acuity (BCVA), optical coherence tomography (OCT) findings, and MH dimensions were recorded. Results: The mean follow-up period was 7 months (range 3–14 months). The mean preoperative minimum linear diameter and base diameter of the MHs were 715 ± 212 μm and 1114 ± 258 μm, respectively. Anatomical closure was achieved in all patients (100%). Postoperative OCT revealed rearrangement of the inner and other retinal layers in 7 out of 10 patients (70%), with partial restoration of the outer retinal layers. The mean logMAR BCVA improved significantly from 1.60 ± 0.37 preoperatively to 1.00 ± 0.45 postoperatively (p < .001). No graft dislocation, rejection, or other significant complications were observed. Conclusions: Epiretinal human amniotic membrane transplantation is an effective and safe surgical technique for achieving anatomical closure and functional improvement in refractory macular holes where conventional ILM peeling has failed.

Abstract: We compile the falsifiable predictions stated across the Quantum Information Copy Time(QICT) preprint series into a single referee-usable atlas. Each entry is recorded as an observablestatement with (i) an explicit numerical value or band when available, (ii) a minimal hypothesisset, and (iii) a concrete falsification route. The atlas is conservative: it standardizes notationand uncertainty conventions (e.g., explicit 1σ bands) without introducing additional modelingbeyond what is stated in the sources.

Abstract: The agricultural cooperation between China and Africa serves as a pivotal example of international partnership, contributing to sustainable regional development and aligning with SDGs. This review article provides a comprehensive analysis of the state of China- Africa agricultural cooperation, highlighting its achievements, challenges, and prospects. Despite the progress made through technical support, financial aid, and infrastructure development, current efforts often lack a holistic approach to fully utilizing African agricultural resources for sustainable regional advancement. This study synthesizes existing literature, policy documents, and case studies to explore sustainable agricultural development pathways facilitated by regional cooperation with external partners. It delves into the dynamics and characteristics of China- Africa agricultural collaboration, identifies persistent challenges in resource integration, and proposes potential pathways for enhancing development. By highlighting the role of partnerships, this review provides valuable insights for policymakers and contributes to achieving sustainable agricultural development through practical international cooperation.

Abstract: Triple-negative breast cancer (TNBC) remains one of the most aggressive and therapeutically challenging breast cancer subtypes, lacking expression of estrogen receptor, progesterone receptor, and HER2. Conventional chemotherapy and immune check-point inhibitors provide some benefit, but resistance and relapse are frequent. The search for novel targets has therefore become central to developing more effective and durable therapies. Recent advances in proteomics, structural biology, and targeted protein degradation are rapidly expanding the repertoire of actionable molecules in TNBC. This review summarizes current and emerging therapeutic strategies for TNBC, with a focus on targeted approaches designed to address tumor heterogeneity and resistance mechanisms. To the aim, recent advances in targeted therapies are examined, including immune checkpoint inhibitors, PARP inhibitors, Trop-2–directed antibody–drug conjugates, anti-angiogenic agents, PI3K/Akt/mTOR pathway inhibitors, androgen receptor antagonists, and CDK4/6 inhibitors, highlighting results from completed and ongoing clinical trials. In addition, we explore novel targets identified through integrative omics approaches, as well as the role of the tumor microenvironment in modulating therapeutic efficacy. Finally, we outline innovative radiotherapy strategies based on targeted radiation delivery and biological integration with systemic therapies. Collectively, this review provides an updated overview of the evolving TNBC therapeutic landscape and high-lights promising directions for the development of next-generation, biomarker-driven treatment strategies aimed at improving patient outcomes.

Abstract: Diaporthe sojae is well known as a causal pathogen of pod and blight as well as seed decay in soybean (Glycine max), it is also known to cause root rot symptoms, though its role is poorly defined. During a 2024 survey in Manitoba, Canada, D. sojae was routinely isolated from roots exhibiting cortical decay and discoloration. The identity of 23 representative isolates was confirmed through morphological characterization and multi-locus phylogenetic analysis using internal transcribed spacer (ITS) and translation elongation factor 1-alpha (EF1-α) sequences. Phylogenetic analysis revealed that the ITS region provided superior resolution in distinguishing D. sojae from the closely related D. longicolla, whereas EF1-α lacked discriminatory power. Pathogenicity was evaluated for 19 isolates on soybean cv. Sperling in a greenhouse assay using colonized wheat-kernel inoculum. While all isolates were pathogenic, significant virulence diversity was observed among isolates, with Disease Severity Indices (DSI) ranging from 68.8% to 100%. Two distinct virulence phenotypes were identified: acute virulence isolates causing 100% seedling mortality (damping-off), and more chronic phenotype characterized by root necrosis and stunting without immediate plant death. This study constitutes the first confirmed report of D. sojae causing soybean root rot in Canada. These findings expand the known disease spectrum of D. sojae and highlight the necessity of including this pathogen in future root-rot diagnostic and management strategies.

Abstract: Assessments of extreme psychological constructs often face a persistent challenge: the ceiling effect, in which a significant proportion of respondents select the highest score on a scale, thus obscuring an important part of the population's variation. This effect may have profound consequences in studies of extreme psychological constructs. To address this limitation, we introduce a novel framework that integrates Multistage Testing (MST) with open-ended questions that are automatically analyzed by large language models (LLMs). This hybrid approach adapts the survey questions to the respondent while leveraging LLMs to efficiently and reliably interpret free-text answers in large-scale online surveys. Using a case study on aversion toward cockroaches, we show how our method can effectively eliminate extreme ceiling effects, revealing hidden data distributions that are often obscured by extreme responses to conventional Likert-type survey questions. In addition, validation against expert human annotations of survey responses demonstrates the consistency and reliability of the LLMs' performance as evaluators of free-text answers. This framework offers a generalizable methodology that enables more precise and sensitive quantitative measurement of extreme psychological constructs, allowing researchers to study topics that until now were inaccessible due to significant, inherent ceiling effects.

Abstract: The digital transformation of university administrative services is essential for managing the complexities of modern campus logistics. Student accommodation management, in particular, requires a robust infrastructure to handle high volumes of sensitive data, financial transactions, and real-time resource allocation. This research details the Design and Development of a Cloud-Based Student Accommodation Management Application, a solution designed to replace inefficient legacy systems with a scalable Software-as-a-Service (SaaS) model. The platform utilizes cloud-native architecture to provide a seamless interface for students while offering powerful automation tools for administrators. Evaluation of the system focuses on performance metrics and user-centric validation. Results demonstrate that the integration of cloud computing significantly improves operational transparency and reduces the latency associated with manual housing assignments. This study provides a technical framework for deploying enterprise-level cloud applications within the higher education sector.

Abstract: Massera and Schaffer [\textit{Ann. Math. (2), 1958}] derived a breakthrough upper bound for the Clarkson angle between two nonzero vectors in a normed linear space, which was later improved by Maligranda [\textit{Am. Math. Mon., 2006}]. Pecaric and Rajic [\textit{Math. Inequal. Appl., 2007}] extended Maligranda's inequality to finitely many nonzero vectors. We derive a non-Archimedean version of Massera-Schaffer-Maligranda-Pecaric-Rajic inequality.

Abstract: This study examines healthcare system strains in rapidly aging societies through a comparative analysis of Puerto Rico, Cuba, Japan, the Philippines, and South Korea. While existing research documents global aging and physician migration trends, few studies explore how these challenges manifest in conjunction with each other. Puerto Rico presents a critical case, with 24% of its population aged 65+, severe physician migration, and systemic underfunding under U.S. Medicaid structures. Using a structured comparative case methodology, we analyze policy responses across four nations with divergent approaches: Cuba, Japan, the Philippines, and South Korea. Data from government reports, academic literature, and World Health Organization (WHO) datasets show that (1) proactive medical education investments outperform reactive measures, (2) dedicated long-term care financing is essential but structurally unavailable in Puerto Rico, and (3) territorial status in the case of Puerto Rico, constrains policy innovation. Conventional aging frameworks are challenged by revealing how high-income territories can exhibit low systemic adaptability. Proposed are targeted reforms for Puerto Rico, including Medicaid restructuring and workforce incentives, with broader implications for aging societies under constrained sovereignty. This study fills a critical space in understanding how geopolitical contexts shape healthcare system vulnerabilities.

Abstract: The double-slit experiment, a cornerstone of quantum mechanics, is traditionally viewed as a paradoxical demonstration of wave-particle duality. This article posits that its core dynamic—superposition, interference, and environment-driven localization—is not a unique quantum phenomenon but a fundamental computational principle implemented by the brain. We introduce the Ze framework, arguing that the brain operates as a biological interferometer. Cognitive systems maintain multiple generative hypotheses in a state of active interference (superposition), analogous to the quantum wavefunction passing through both slits. "Which-path" information, supplied by sensory data, action, and social context, forces cognitive decoherence, localizing perception and decision into a single narrative. Sleep is recast as an intrinsic quantum eraser, periodically degrading which-path information to restore cognitive flexibility and prevent pathological hyper-localization. The framework structurally links quantum decoherence, Bayesian active inference, and the neurobiology of sleep and wake cycles. It provides a transdiagnostic model for psychopathology, where disorders like psychosis and PTSD are seen as dysregulations of this interference-localization cycle. We conclude that the brain does not observe quantum reality; it actively instantiates its core logic, making the double-slit experiment a continuous, lived process of resolving ambiguity to survive and understand the world.

Abstract: Background/Objectives: Parkinson’s disease (PD) involves motor and non-motor im-pairments, including visual dysfunction related to retinal dopamine deficiency and mi-crovascular changes. Photobiomodulation (PBM) and aerobic exercise (AE) may offer neuroprotective and vascular benefits. This brief report presents findings from a ran-domised pilot trial comparing PBM, AE, and their combination on visual function, ocular health, and patient-reported outcomes in PD. Methods: Twenty participants with idio-pathic PD (mean age 76.1 ± 8.8 years; Hoehn & Yahr I–III) completed four 8-week in-terventions (PBM, AE, PBM + AE, sham), separated by 4-week washouts. PBM was ap-plied to the head, neck, and abdomen; AE followed a modified forced-rate protocol. Changes in ocular measures, including visual acuity (VA), contrast sensitivity, retinal nerve fibre layer (RNFL) thickness, choroidal thickness, retinal vascular perfusion, and questionnaires: 12-item Short Form Survey (SF-12), 39-item Parkinson’s Disease Ques-tionnaire (PDQ-39), and Falls Efficacy Scale–International (FES-I), were assessed pre- and post- intervention. Results: Seventeen participants completed all measurements. Non-pharmacological interventions resulted in improved VA (0.10 ± 0.02 to 0.02 ± 0.03, p = 0.01) and increased central retinal vascular perfusion (16.7 ± 1.4 % to 20.5 ± 1.6 %, p < 0.01) from pre- to post-study interventions. RNFL and choroidal thickness did not change significantly. Fear of falling decreased significantly (28.5 ± 2.4 to 22.7 ± 1.8, p < 0.01), while PDQ-39 and SF-12 scores were unchanged. Conclusions: PBM, alone or combined with AE, improved vision and retinal microvascular function and reduced fear of falling in individuals with PD, warranting larger-scale trials to further delineate independent and synergistic effects.

Abstract: This study examined the relationship between perceptions of financial health indica-tors, lived experiences, and actions taken to address economic crises, while also ex-ploring potential gender differences. A non-experimental, quantitative, cross-sectional design was applied to a sample of 499 working professionals who had graduated from universities in Veracruz and were employed in either the public or private sector. A 24-item Likert-scale instrument was used to assess financial health perceptions, per-sonal experiences, and crisis-related actions. Reliability was confirmed with Cronbach’s alpha and McDonald’s omega values above 0.7. Data were analyzed using Exploratory Factor Analysis with Varimax rotation, Structural Equation Modeling, and Bayesian analysis to assess gender differences. A four-factor structure explained 64.86% of the variance. Moderate correlation was observed between financial wellbe-ing and resilience (r = 0.32), a weaker correlation between wellbeing and experiences (r = 0.18), and a strong correlation between experiences and actions in crises (r = 0.47). No significant gender differences were found. Findings highlight strategies for man-aging financial crises, maintaining credit health, and improving resilience, proposing a refined three-factor model linking experiences and actions to financial outcomes.

Abstract: Based on a unified non-perturbative quantum gravity framework, this paper systematically elaborates on the cross-scale universality of the quantum gravitational correction term containing a logarithmic term. At the microscale of black hole singularities, it dynamically resolves the singularity through a repulsive potential and ensures information conservation; at the macroscale of black hole gravitational fields and galaxies, it maintains the high-speed revolution of stars and the flatness of rotation curves through additional gravity, eliminating the need for assumptions such as dark matter or black hole spin fitting parameters. With quantum vortices (statistical average topological structures of microscopic particles) and nested AdS/CFT duality as the physical core, the framework derives a modified gravitational potential with a logarithmic term: \( Φ(r)=-\frac{GM}{r}-\frac{kG_h M^2 (ln⁡r+1)}{r} \). Among them, the logarithmic term ln⁡r is the core of realizing the cross-scale effect of “repulsion at short distances and attraction at long distances”. Through predicting black hole shadows (Sgr A*, M87*) consistent with EHT observations without introducing additional free parameters (e.g., spin); calculating the “periastron” velocities of high-speed stars (S4714, S62) orbiting black holes; fitting galaxy rotation curve data (Milky Way, Andromeda Galaxy, NGC2974); and further analyzing the mathematical asymptotic behavior of dark matter halos, multiple cross-scale verifications (spanning nearly 30 orders of magnitude from black hole singularities to galaxies) prove that the framework has high consistency with observations in both strong gravitational fields (black holes) and weak gravitational fields (galaxies). It achieves the first unified description of gravity from the microscale to the macroscale, providing observable and reproducible empirical support for quantum gravity theory.