• Extension of the ASRF/Vasicek framework to credit portfolios containing two exogenous classes of loans (green and brown), allowing distinct return distributions and correlation structures within a unified asymptotic model. • Incorporation of skew-normal borrower return dynamics, providing a flexible structural mechanism to model empirically documented asymmetries in log-returns while preserving analytical tractability. • Generalization of Vasicek’s convergence result to heterogeneous portfolios with nonuniform exposures, including empirically motivated power-law concentration structures. • Integration of Green Loan Principles (GLP) as the practical basis for loan-type classification, clarifying the financial rationale for distinguishing green and brown exposures. • Scenario-based numerical analysis illustrating loss distributions, sensitivity to key parameters (PDs, correlations, skewness), and the impact of portfolio composition under realistic concentration patterns. • Assessment of robustness of the extended ASRF formula by comparing asymptotic results to finite-portfolio simulations under heterogeneous and skewed structural specifications. • Methodological contribution with regulatory relevance, showing how a green-brown differentiation could be embedded in the ASRF architecture once borrower-level data become available. Inspired by the classical Vasicek approach to credit risk, we propose an extended model for portfolios composed of green and brown loans, widening the Asymptotic Single Risk Factor framework via a two-factor copula structure. Systematic risk is modeled using potentially skewed distributions, allowing for asymmetric creditworthiness effects, while idiosyncratic risk remains Gaussian. Under a non-uniform exposure setting, we establish convergence in quadratic mean of the portfolio loss to a limit reflecting the distinct characteristics of the two loan segments. Numerical results confirm the theoretical findings and illustrate how value-at-risk is affected by portfolio granularity, default probabilities, factor loadings, and skewness. Our model accommodates differential sensitivity to systematic shocks and offers a tractable basis for further developments in credit risk modeling, including granularity adjustments, collateralized default obligations pricing, and empirical analysis of green loan portfolios.

Modelling financial contagion and optimal policy design for bank runs and systemic risk

Scale-dependent capital flows and systemic risk: Multifractal evidence from Mainland China–Hong Kong Stock Connect

Pipe material governs biofilm development and microbial communities more than organic suspended solids in drip irrigation systems in greenhouse settings.

Decoupling environmental contamination from human health risk through selective bioaccumulation: The role of analytical spectrum and physiological modulation.

Generative AI and causal-spatial modeling for understanding nighttime pedestrian risk in urban systems

PFAS contaminants in surface waters, effluents, sediments and coastal food webs off the Solent coastline UK.

Cardiac damage predicts poor outcomes in polytrauma (PT). In older patients, cardiovascular risk factors may predispose to post-traumatic cardiac dysfunction. This study examined whether cardiovascular risk correlates with cardiac damage and influences clinical outcomes in PT. This study at a German Level 1 Trauma Centre enrolled 59 PT patients upon emergency room admission. Blood samples were taken at the emergency room, 24, 48, 72, 96 hours, and 10 days to assess cardiac damage via troponin T and N-terminal pro-B-type natriuretic peptide. Transthoracic echocardiography (TTE) was performed at 24/48 hours. Cardiovascular risk was evaluated using the Systematic Coronary Risk Evaluation (SCORE)2 algorithm. Subgroup analysis compared cardiac damage in patients with high (SCORE2 >7.5%) versus low risk, and assessed the additional impact of chest trauma. Arrhythmias were observed in 39% of patients, whereas acute repolarization disorder occurred in nearly 19%. TTE revealed wall motion abnormalities in 12%, diastolic dysfunction in 10%, and right ventricular dysfunction in 5%. SCORE2 and lipoprotein(a) significantly correlated with serum levels of troponin T and N-terminal pro-B-type natriuretic peptide. SCORE2 values were associated with nonsurvival, wall motion disorders, diastolic dysfunction, and relaxation disorders ( P < 0.05). A higher incidence of arrhythmias, diastolic dysfunction, and relaxation disorders was observed in the subgroup of high-risk patients with chest trauma. Patients in the high-risk group without chest trauma showed higher nonsurvival rates (50%), which may be strongly influenced by a history of myocardial infarction. Cardiovascular risk was significantly associated with cardiac damage markers, TTE abnormalities, and increased mortality. A history of myocardial infarction was associated with higher mortality in PT patients with an elevated SCORE2 risk.

Integrated plasma proteomics and metabolomics reveal immunometabolic pathways and predictive signatures for age-related eye diseases.

Diabetic ankle fractures present significant clinical challenges, with higher rates of complications including infection, non-union, Charcot neuroarthropathy, and amputation compared to non-diabetic patients. Despite this burden, no universally accepted guidelines exist for risk stratification and management. The Adelaide Fracture in the Diabetic Ankle (AFDA) score was proposed in 2014 but has limitations including uniform weighting of risk factors and exclusion of local injury characteristics. This systematic review of reviews aimed to synthesise current evidence and develop an updated, evidence-based risk stratification tool. A comprehensive search of Embase, PubMed, and Web of Science was conducted. Eligible studies included systematic and narrative reviews examining outcomes, risk factors, or interventions for diabetic ankle fractures. Risk of bias was assessed using the ROBIS tool. Data were synthesised narratively, and an evidence-informed, consensus-based scoring system was developed by translating observed effect sizes from the included reviews into weighted risk scores. Thirteen reviews were included. Complicated diabetes, particularly peripheral neuropathy, peripheral arterial disease, and prior Charcot neuroarthropathy, emerged as the strongest predictors of adverse outcomes. Non-operative management of unstable fractures was associated with significantly higher complication rates. Based on these findings, we propose the Manchester Ankle Fracture Diabetic Risk Assessment Score (MADRAS), incorporating weighted systemic host factors, local injury characteristics, and modifiable patient factors across a 17-point scale stratifying patients into four management tiers: low risk (0-2), moderate risk (3-5), high risk (6), and very high risk (≥ 7). MADRAS addresses limitations of existing frameworks by incorporating evidence-based weightings and local injury factors. Prospective external validation is required before widespread clinical adoption; until then, MADRAS should be regarded as a decision-support tool. This tool may assist clinicians in systematic risk stratification and surgical decision-making for diabetic ankle fractures.

The prominence of the coalescence of FinTech and sustainable finance has been a major area of scholarly interest for more than half a decade. To delineate the conceptual evolution at this intersection, the current study aims to conduct a bibliometric review through a hybrid methodical approach by coupling systematic literature review (SLR) with bibliometric techniques – including performance analysis, co-occurrence analysis, thematic mapping – of 227 documents from Scopus database, incorporating not only journal articles but also conference papers, books, book chapters, and reviews from 2018 to 2025 that enriches the results with near-term published articles, quantitative techniques by utilizing VOSviewer and R Studio, and qualitative analysis of the cluster findings from the outcome of these software. Another novelty of this study is the accumulated study of FinTech and a broader multidimensional field - Sustainable Finance - that not only includes addressing the environmental impact, but also incorporates economic development, and governance factors. The findings underscore the evolving trend of research themes in the current area of cross-functional domain progressing from theoretical examination to more functional application of financial technology that catalyzes to establish sustainable finance. The study identifies critical research gaps requiring further investigation, including systematic risks associated with FinTech that may hamper achieving sustainability goals, the formation of a robust regulatory framework supporting the convergence of fintech and sustainable finance across regions, the identification of the role of digital mechanisms in enhancing sustainability reporting of financial institutions. The study also emphasizes the vitality of examining behavioral changes of stakeholders involved in this ever-evolving dynamic arena. Therefore, all these serve as actionable insights providing guidance to researchers, policymakers, and practitioners for future studies and implications. • This study presents a systematic bibliometric analysis of 227 publications (2018–2025) exploring the intersection of fintech and sustainable finance. • It maps key trends, including growing interest in green finance, financial inclusion, and the use of technologies like blockchain and AI for sustainable growth. • Leading contributions come from scholars in China, India, and Saudi Arabia, with Resources Policy emerging as the key source journal. • The study identifies future research horizons in regulation, ESG integration, and the role of fintech in enhancing energy efficiency.

An integrated vulnerability-resilience framework for climate risk assessment in depopulating urban landscapes

Plasmonic gold nanocube-enhanced SERS biosensor based on INDEBT and click chemistry coupled with exonuclease III-assisted cycling amplification for sensitive detection of ribonuclease H activity.

Fire accidents in public assembly occupancies often arise from complex interactions among institutional failures, behavioral violations, and physical hazards. Traditional linear analyses cannot capture these dynamic and systemic causation mechanisms. Drawing on 185 official investigation reports of major fire incidents in China from 1998 to 2020, this study builds a Fire Accident Causation Complex Network Model (FACCNM). The model integrates the Apriori algorithm, complex network analysis, and the 24 Model to identify key contributing factors and high-risk causal chains in fire accidents. The findings show that "unauthorized design change" and "renovation with flammable materials" occur frequently and occupy structurally central positions in fire risk propagation. The highest-risk causal chain, "Absence of fire audit/acceptance → unauthorized design change", illustrates a typical pattern in which institutional oversight triggers behavioral and material vulnerabilities. The results offer actionable guidance for fire risk governance, such as prioritizing intervention points, conducting targeted safety audits, and designing proactive regulatory strategies. This study also helps shift fire safety management from reactive response to preventive control, especially in high-density public environments.

Systemic risk of the Chinese banks at different frequencies: Evidence from the wavelet conditional value at risk (CoVaR)

Epilepsia partialis continua beyond status epilepticus: a generator-based neurophysiological framework for clinical decision-making.

Development and psychometric validation of the Adolescent Self-Harm Risk Assessment (ASRA) Scale: A multi-dimensional approach.

Caribbean Small Island Developing States (SIDS) are on the frontline of climate-induced coastal risks, where rising sea levels and intensifying storm surges converge with concentrated socioeconomic exposure. The inherent spatial constraints, economic dependency on tourism, and infrastructure clustering in coastal zones exacerbate systemic vulnerability. This study establishes an integrated high-resolution compound coastal risk framework by coupling hydrodynamic storm surge simulations with sea level projections and socioeconomic exposure data. The framework evaluates systemic risks across diverse return periods and Shared Socioeconomic Pathways including SSP1-1.9, SSP2-4.5, and SSP5-8.5, utilizing a modified static inundation model to integrate sea level rise and surge extremes for generating spatially explicit vulnerability assessments. Results revealed spatial heterogeneity and a distinctive ‘high-exposure–high-density–high-sensitivity’ configuration across several SIDS. Under SSP5–8.5, annual economic losses exceed USD 300 million in Jamaica and Cuba, and over 30,000 people may be affected in Dominica. Mitigation pathways consistent with a 1.5 °C warming limit (SSP1–1.9) reduce potential losses by 30–50%, while adaptation strategies, such as coastal ecosystem restoration and early-warning systems, deliver up to 40% carbon co-benefits. Beyond risk quantification, this framework supports climate-resilient infrastructure planning. By correlating spatial risks with adaptation finance, this research supports the Paris Agreement and Sustainable Development Goals (SDGs).

Genitourinary syndrome of menopause (GSM) is a chronic, progressive condition resulting from estrogen and androgen deficiency that affects 27-84% of postmenopausal individuals. Symptoms include vaginal dryness, dyspareunia, urinary urgency, dysuria, and recurrent urinary tract infections. Despite strong evidence supporting the safety and efficacy of local vaginal estrogen (VE) therapy, treatment remains underutilized due to clinician uncertainty, misconceptions regarding systemic risk, and regulatory warnings. Recent clinical guidelines emphasize vaginal hormones as first-line therapy for GSM. This review summarizes the pathophysiology of GSM, evidence supporting local hormone therapy, safety considerations, and practical prescribing strategies for clinicians. Pearls for clinical practice are discussed, including dosing regimens, formulation selection, patient counseling, and strategies to overcome barriers to treatment adherence.

Microbial contamination and cross-contamination of food-contact surfaces remain major challenges to food safety and contribute significantly to spoilage and food waste. Antimicrobial photodynamic inactivation (aPDI) represents a sustainable, nonthermal approach for microbial control, but its effectiveness is often limited by low reactive oxygen species (ROS) generation and poor stability under complex practical conditions. Herein, this study aims to (i) develop a copper (Cu)-doped cyclodextrin-based metal-organic framework to enhance the photodynamic activity of CCS, thereby increasing ROS generation and light-activated antimicrobial efficacy; and (ii) incorporate the resulting CCS-loaded, Cu-doped cyclodextrin-based metal-organic framework (CCS/MOF-Cu) nanoparticles into a microporous polylactic acid (PLA) coating to enable a light-activated antimicrobial surface. The CCS/MOF-Cu was synthesized via a rapid microwave-assisted method and exhibited enhanced aqueous stability for at least 30 days. The Cu-doped framework demonstrated an approximately 140-fold enhancement in ROS generation compared to free CCS. A phase separation strategy produced microporous surfaces that promote bacterial localization and improve ROS-microbe interactions. The resulting coating achieved a >5-log reduction of Pseudomonas fluorescens and Bacillus cereus within 30 min of red LED exposure. This work demonstrates a scalable coating platform that integrates ROS amplification with an engineered surface design, offering a promising self-disinfecting solution to reduce microbial risks in food systems.