Search Results (31,346)

Background/Objectives: Typhoid fever remains a major public health challenge in many low-income countries, where overlapping clinical symptoms and the limited reliability of conventional diagnostic procedures hinder accurate diagnosis. This study aims to develop a reliable and efficient diagnostic framework that automates typhoid fever detection from clinical data while preserving patient privacy. Methods: To achieve this objective, we propose a hybrid framework combining genetic algorithm (GA)–based feature selection, a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) deep learning classifier, and federated learning. The GA identifies the most informative clinical features, reducing redundancy and computational complexity. The selected features are then used to train a CNN–LSTM model in a federated learning setup using the Federated Averaging (FedAvg) algorithm, enabling collaborative model training across multiple clients without sharing raw patient data. Results: Experimental results show that the proposed framework achieves 92% accuracy, with a strong F1-score and satisfactory sensitivity. Compared to models trained on the full feature set, the proposed approach requires less memory and shorter training time, while maintaining balanced performance under class imbalance. Conclusions: These results demonstrate that integrating evolutionary feature selection, deep sequential learning, and federated training provides an effective and privacy-aware solution for multi-class typhoid fever diagnosis. The proposed framework is particularly suitable for clinical environments with limited data access and constrained resources. Full article

Accurate vehicle counts from traffic videos are fundamental to traffic measurement and to estimating roadway demand for infrastructure planning and maintenance. However, many vision-based traffic datasets and pretrained models under-represent vehicle types that are prevalent in developing countries, such as the keke (globally known as auto-rickshaw/three-wheeler), which can bias traffic composition estimates and downstream workload indicators. This paper presents a keke-aware vehicle detection and counting pipeline that combines fine-tuned YOLO-based detectors with BoT-SORT/ByteTrack tracking and ROI-based counting, together with a newly curated and publicly released traffic-video dataset that includes a dedicated keke class. The detectors are fine-tuned from pretrained weights on a six-class dataset (bicycle, bus, car, motorcycle, truck, keke) and evaluated on held-out roadside test videos with a manual counting baseline. On the validation split (2088 images; 8400 instances), the fine-tuned YOLO11l model achieves $P=0.752$, $R=0.696$, $\mathrm{mAP}@0.5=0.766$, and $\mathrm{mAP}@0.5:0.95=0.578$, with the keke class attaining $\mathrm{mAP}@0.5=0.772$, while YOLO26l achieves slightly higher overall precision ($P=0.766$) and stronger keke recall and $\mathrm{mAP}@0.5:0.95$. In system-level counting, the selected tuned ROI-based variants produce the most reliable results on the Yola Road downward flow, where keke counts remain close to the manual baseline, but performance is strongly direction- and scene-dependent, with substantially larger errors in the Yola upward flow and the more challenging Mubi Road scene. Flow-rate and ESAL-rate analyses further show that class misclassification can severely distort pavement-loading estimates even when total traffic flow appears close to baseline, underscoring the need for localized class ontologies and robust heavy-vehicle discrimination in mixed-traffic ITS deployments. The released dataset and baseline pipeline provide a practical reference for keke-aware traffic monitoring and for infrastructure-relevant traffic measurement in developing-country contexts. Full article

This study examines the transformation of the Balaton region in Hungary from a traditional tourist destination into an international retirement migration destination for older adults from Western Europe. Migration theories and models are applied to illustrate the relationships between migration and development and to explore how tourism, lifestyle aspirations, and socio-economic factors influence the settlement decisions of older migrants. Empirical findings suggest that prior tourism experience can mitigate the uncertainty associated with migration and foster belonging. However, many retirees move to Hungary with limited knowledge of the country, relying on social networks and real estate agents for information. These retired migrants also utilize local services and infrastructure, including healthcare and community spaces, which shape their daily lives and help them integrate into the community. The migration of older adults stimulates the development of peripheral rural areas through real estate purchases, renovations, and small-scale entrepreneurial activities, particularly in the accommodation sector. This challenges the traditional perception of older-age migrants as inactive. Full article

This review examines current research and development directions in thorium-based nuclear fuel cycles and reactor systems, including innovative and modular reactor concepts being investigated in several nuclear-producing countries. The analysis considers the feasibility of integrating thorium-containing fuels into both existing and emerging reactor technologies. Particular attention is paid to the potential use of thorium-based fuels in pressurized water reactors (PWRs) as transitional platforms that can enable gradual introduction in thorium without requiring immediate deployment of entirely new reactor architectures.This study synthesizes representative quantitative results reported in the recent literature, including neutronic performance metrics, conversion ratio estimates, and fuelbehavior characteristics of mixed Th–U oxide fuels under typical operating conditions. These results are evaluated together with broader system-level considerations, such as fuelcycle closure potential, materials performance, and technology readiness across different reactor classes.A comparative assessment of light water reactors (LWRs), heavy water reactors (HWRs), and molten salt reactors (MSRs) demonstrates that each platform offers distinct advantages and limitations for thorium deployment. While LWR systems provide the most realistic near-term pathway for partial thorium introduction within the existing nuclear infrastructure, HWR and MSR concepts offer more favorable conditions for efficient thorium utilization and potential Th–U fuelcycle closure. These reactor classes are currently being explored within national research and development programs focused on advanced and modular nuclear technologies.By integrating neutronic analysis, materials considerations, fuelcycle strategies, and techno-economic factors, this review provides a system-level perspective on the research and development of innovative thorium reactor concepts and outlines realistic pathways for their gradual implementation in evolving nuclear energy systems. Full article

This study investigated the adaptation of culinary culture and behavioral adjustment to Turkish cuisine among international students. The sample comprised 82 students (61.0% males; 39.0% females) from over 20 countries across Europe, Central Asia, South/Southeast Asia, Africa, and the Middle East, all enrolled at Erciyes University. Data collection involved a sociodemographic questionnaire, assessments of food consumption frequency and cooking methods, and the Culinary Culture Adaptation Assessment Inventory. Results indicate that adaptation to Turkish cuisine occurs through a selective and gradual behavioral process. Higher adaptation levels were observed for basic dietary components (bread, soup, rice, yoghurt, and tea), whereas adoption of starch- and sugar-heavy dietary patterns was more limited. Gender comparisons revealed significantly higher scores for meat-heavy and starch-heavy dietary patterns among males (p = 0.048 and p = 0.031, respectively). In contrast, regional origin, economic status, and language proficiency were not significantly associated with culinary acculturation levels. Comparisons based on length of residence identified significant differences in meat-heavy and starch-heavy dietary patterns (p = 0.034 and p = 0.008, respectively). Cooking behaviors remained stable for boiling, grilling, and baking, while frying and roasting decreased. Reported changes in portion perception and body weight suggest that culinary acculturation may extend beyond food choice to broader eating behaviors. Based on these results, an AI-supported interactive platform was developed to facilitate culturally comparable food matching between Turkish and global cuisines. These findings may inform the development of culturally sensitive strategies to support culinary adaptation among international students. Full article

South Asia has experienced a persistent rise in per capita carbon dioxide emissions despite growing policy attention to low-carbon development. Against this background, this study examines how economic growth, energy intensity, renewable energy, urbanization, and trade openness shape per capita carbon dioxide emissions in six South Asian countries over the period 1990–2023. Grounded in the STIRPAT framework, the analysis combines fixed-effect estimation with two-step system generalized method of moments to address unobserved heterogeneity, endogeneity, and emissions persistence. The results show that economic growth remains strongly carbon-intensive, with gross domestic product per capita exhibiting a near-proportional elasticity with emissions. Energy intensity significantly increases emissions, while renewable energy reduces them. Urbanization exerts a positive but smaller effect, whereas trade openness remains statistically fragile. The findings also indicate strong emission persistence, underscoring the importance of early intervention. The study contributes to the regional environmental literature by providing an integrated and dynamic assessment of South Asia’s growth–energy–emissions nexus and by introducing a composite policy-support dimension into the empirical framework. The results offer practical implications for energy efficiency reform, renewable expansion, and climate-sensitive urban policy in developing economies. Full article

Thermal water-supplied swimming pools are increasingly used worldwide for recreation, wellness, and therapeutic purposes, yet their management poses specific challenges due to the complex physicochemical properties of thermal and mineral waters and the need to balance microbiological safety with preservation of their natural characteristics. This scoping review adopts an integrative and comparative methodological approach, combining a systematic mapping of the scientific literature with a structured analysis of regulatory documents across 39 countries. It maps and comparatively synthesizes current evidence on health benefits, safety issues, and regulatory frameworks governing thermal pools. The analysis focuses on microbiological hazards and chemical risks related to disinfection practices, including the formation of disinfection by-products (DBPs). The review also examines emerging contaminants (CECs), including pharmaceuticals and personal care products (PPCPs), and discusses the potential role of thermal water environments in the development and spread of antimicrobial resistance (AMR). Moving beyond a purely descriptive approach, the analysis introduces a comparative framework that identifies distinct regulatory models and evaluates their implications for risk management and disinfection strategies. Thermal pools are conceptualized as integrated exposure systems generating complex mixtures with uncertain toxicological effects. The analysis reveals global regulatory heterogeneity and critical gaps in managing DBPs, CECs, and AMR-related risks, highlighting the need for integrated, risk-based and harmonized approaches within a One Health framework. Full article

Despite the many advantages of renewable energy sources, the stochastic nature of their generation creates a mismatch between electricity production and demand timing. Without appropriate storage solutions, surplus energy remains unused. Although battery energy storage systems are increasingly applied to improve the flexibility and reliability of power systems, there is still a research gap in forecasting the optimal power and storage capacity of solar power plant–battery energy storage system energy complexes operating in parallel with the grid under short-term forecasting conditions, particularly when economic aspects such as partial leasing of storage capacity are considered. Therefore, the development of energy complexes based on solar power plants with the integration of battery energy storage systems, as well as the development of corresponding computational models, becomes critical for ensuring the stability, flexibility, reliability, and efficiency of power systems. Battery energy storage systems are widely used due to their availability, high response speed, significant energy density, and sufficient power capacity; however, their cost remains relatively high. This paper proposes a methodology and a calculation model for determining the optimal forecasted capacity and the rational storage requirements of an energy complex consisting of a solar power plant and a battery energy storage system operating in parallel with the grid at constant power under short-term forecasting conditions (day-ahead or longer). The proposed approach makes it possible to minimise the costs of energy companies associated with the short-term lease of part of a battery energy storage system when they do not own one, or, if such a system is available, to lease out its unused capacity and obtain corresponding profits. The validation of the computational model uses a dataset of hourly daily power outputs of solar power plants in the Integrated Power System of Ukraine for 2018. Statistical analysis of the obtained results shows that the probability of occurrence of maximum deviations for the optimal capacity of the energy complex (5.4%), as well as for the power and capacity of the battery energy storage system (13% and 18%, respectively), does not exceed 0.05 during the year. The results confirm that the proposed methodology provides a reliable basis for determining optimal parameters of solar power plant–battery energy storage system energy complexes and enables economically efficient use of storage capacity through short-term leasing mechanisms. Although the proposed methodology is applied using solar power plant generation data for the national power system as a whole, it can also be used for individual solar power plants located in different regions and countries with different climatic conditions. Certainly, the calculated coefficients differ, but the methodology itself and the sequence of its application remain the same. Full article

In developing countries, final disposal sites exhibit different levels of operational control, which influence their environmental performance. This study evaluated the environmental performance of four types of final disposal sites in Mexico: sanitary landfill with energy recovery (SLF+ER) and sanitary landfill with gas flaring (SLFGF), controlled site (CS), and open dump (OD), using life cycle assessment for 1 t of municipal solid waste. Biogas generation was estimated using the Mexican Biogas Model 2.0, and Ecoinvent processes were adapted to local conditions; six impact categories were assessed, and a sensitivity analysis was conducted. The SLF+ER scenario showed the lowest impact in global warming, followed by SLFGF and CS, while OD recorded the highest impact, mainly associated with biogas management. In contrast, scenarios with gas capture and treatment showed higher contributions in categories related to combustion processes. Normalized results indicated that freshwater eutrophication and human carcinogenic toxicity are the dominant impact categories. The sensitivity analysis confirmed the influence of the organic fraction on CH₄ generation without altering the relative ranking among scenarios. Overall, increasing the level of environmental control reduces impacts from fugitive emissions but introduces trade-offs across other impact categories, highlighting the need for comprehensive assessments to support decision-making. Full article

The effectiveness of policy tools used to combat global environmental degradation and climate change is gaining importance. The role of environmental policies in reducing carbon dioxide emissions and whether rising emissions levels lead to tightening of environmental policies are the main research questions of this study. Using panel causality methods, this study examines the relationship between the Environmental Policy Stringency Index (EPS) and carbon dioxide (CO₂) emissions across 23 OECD countries from 1991 to 2020. The results of the Dumitrescu–Hurlin panel causality test show bidirectional causality between EPS and CO₂. According to the asymmetric causality test, we find causality from EPS to CO₂ during positive shocks. Furthermore, when examining negative shocks, we report a unidirectional causality originating only from EPS in the US. Our results demonstrate that the bidirectional relationship between EPS and CO₂ can contribute to the development of effective and balanced environmental policies if policymakers and society consider this interaction. Full article

Domestic violence against women is a severe problem in Brazil and worldwide. The Brazilian system presents innovative policies aimed at women’s access to justice, which have not yet been systematized or empirically examined. This article aims to identify, analyze, and categorize the main policies for access to justice for victims of domestic violence in Brazil. Methods used are documentary analysis and data collection were conducted. Data were requested from public institutions and collected from 27 state governments and the federal government. As results, the research found that, in addition to access to justice policies commonly adopted worldwide—such as emergency protective measures, risk assessment forms, call centers for women, and panic buttons, Brazil has implemented several innovations, particularly: (i) multidisciplinary care centers, (ii) specialized police stations, (iii) shelters and rental assistance, (iv) employment quotas, (v) special pensions for orphans, and (vi) aesthetic repair. In conclusion: (i) the ten public policies are effective and have benefited millions of women in Brazil; (ii) there is a need to coordinate these policies, assess their effectiveness, and consolidate data; (iii) new technologies offer opportunities to develop tools that facilitate access to justice and prevent and redress domestic violence; and (iv) these policies may be adopted by other countries, with appropriate contextual adaptations. Full article

The development of digital capability for resilience remains a major challenge for small and medium-sized enterprises (SMEs). Drawing on dynamic capability theory (DCT), this research develops and tests a model linking artificial intelligence capabilities (AIC), digital platform capabilities (DPC), sustainable innovation (SI) and SME resilience (R). The data were collected from 321 Saudi SMEs and analysed using SmartPLS for structural equation modelling. Findings confirm AIC’s mediating effect on both SI and R. Additionally, the results support the conclusion that the DPC developed through AI mediates only the relationship between AIC and SI. Moreover, the sequential parallel mediating model confirms the complementary roles of DPC and dynamic capabilities in linking AIC to SI and R. The validated model offers a practical framework for operations managers seeking to enhance resilience and sustainability and to extend this effect to the corresponding mechanisms linking AIC, SI, and R. In fact, this study clarifies a digital capability pathway in SMEs. In terms of managerial implications, it highlights the importance of AI-driven capabilities as a strategic priority. However, the use of cross-sectional data and a sectoral scope can limit the research contributions and suggest new directions for future longitudinal and cross-country research. Full article

The effective closure of the Strait of Hormuz on 28 February 2026 disrupted approximately 20 million barrels (bbl) per day of crude oil transit, constituting the largest supply shock in global oil market history. This study quantifies the resulting economic losses under three blockade-duration scenarios and evaluates the Northern Sea Route (NSR) as a partial mitigation mechanism through a novel framework integrating sustainable supply chain resilience (SSCR), the Triple Bottom Line (TBL), and the United Nations Sustainable Development Goals (SDGs). A 3 × 3 scenario matrix crossing three blockade durations with three NSR utilization levels estimates global and country-level impacts using data from the International Energy Agency (IEA), the International Monetary Fund (IMF), and the Centre for High North Logistics (CHNL). Even under maximum feasible NSR utilization, net environmentally adjustment mitigation offsets only 1.1–3.6% of total global losses, demonstrating that the Northern Sea Route functions as marginal insurance rather than a viable substitute for Hormuz-dependent supply chains. Global Gross Domestic Product (GDP) losses range from USD 330 billion to USD 2.2 trillion, with South Korea (68–70% Middle East crude dependency) and Japan (approximately 95%) disproportionately affected. After TBL environmentally adjustment monetizing CO₂, black-carbon, and icebreaker costs, the NSR mitigates 1.1–3.6% of total losses, functioning as insurance rather than substitution. The SDG assessment reveals a fundamental trade-off: the NSR offsets energy-security losses (SDGs 7, 9) but worsens climate and marine outcomes (SDGs 13, 14). Theoretically, this study proposes “alternative maritime route availability” as a conceptual extension of supply chain resilience (SCRes) capabilities and outlines a sustainability-adjusted resilience score (SARS) framework that, pending further validation, could serve as a replicable assessment tool. These findings underscore that accelerating the energy transition remains the most effective long-term response to chokepoint vulnerability. Full article

The increasing emphasis on sustainable construction has positioned regulatory frameworks as critical drivers of sustainable building construction project delivery (SBCPD), particularly in developing countries such as South Africa. However, the effectiveness of different regulatory instruments remains insufficiently understood. This study investigates the influence of regulatory factors on SBCPD by examining two key constructs: Compulsory Enforcement and Incentivisation (CEI) and the Sustainable Building National Framework (SBNF). A quantitative research design was adopted, and data were analysed using Principal Component Analysis (PCA), Confirmatory Factor Analysis (CFA), and Structural Equation Modelling (SEM) to assess the relationships between regulatory mechanisms and project delivery outcomes. The findings reveal that CEI does not exhibit a statistically significant influence on SBCPD when modelled as a combined construct, despite showing significance when tested independently. This suggests that aggregating compulsory and voluntary regulatory instruments may weaken their explanatory power due to underlying interaction effects. In contrast, SBNF demonstrates a strong and statistically significant positive influence on SBCPD, highlighting the critical role of government-led policies, institutional frameworks, and certification systems in shaping sustainable construction practices. The study contributes to theory by advancing our understanding of regulatory hybridity and the role of institutional drivers in sustainable construction. In practice, the findings underscore the need for coherent, well-articulated policy frameworks, strengthened enforcement capacity, and strategic alignment between voluntary and mandatory instruments. The study concludes that government-led frameworks remain the primary catalyst for sustainable construction delivery in developing economies. These insights provide valuable guidance for policymakers and industry stakeholders seeking to enhance sustainability performance in the built environment. Full article

Introduction/Objectives: Intersectoral collaboration between education and mental health services is central to the care of autistic children and adolescents. However, recent literature indicates that evidence remains limited regarding how these collaborative arrangements are implemented in routine public services, particularly in low- and middle-income countries (LMICs). This study aimed to assess the intersectoral collaboration between Brazilian educational and mental health services for autistic children and adolescents and to examine the frequency and type of intersectoral contact. Methods: An exploratory cross-sectional study was conducted in the municipal public education system of Niterói, a city in the Southeast region of Brazil. Participants included parents of 123 autistic children and adolescents, 49 teachers from mainstream education and specialized educational services (SES), and 24 health professionals. Data were collected using structured questionnaires with multi-informant reports. The instruments were specifically developed for the study and submitted to expert content-validation procedures. Analyses included descriptive statistics and, in a subsample of 51 matched cases with paired responses from teachers and health professionals, Cohen’s kappa to assess agreement between reports. Results: Low levels of intersectoral collaboration were observed, characterized by infrequent contact, limited information exchange, and slight agreement between reports from teachers and health professionals (κ = 0.25; p = 0.01). Teachers were more likely to know where care was provided than to know which specialists were involved, while more than half of health professionals did not know which school the child attended. Conclusions: In the investigated municipal network, care appeared fragmented, highlighting difficulties in translating intersectoral recommendations from public policies into routine collaborative practices. Full article