Search Results (14,809)

Background: Long-acting monoclonal antibodies have become an important strategy for preventing respiratory syncytial virus (RSV) disease in infants. Nirsevimab is the first product for which substantial post-licensure implementation data are available, whereas real-world evidence on clesrovimab remains limited. Although nirsevimab has demonstrated high efficacy, its uptake varies considerably across countries, healthcare systems, delivery settings, and population subgroups. This World Association for Infectious Diseases and Immunological Disorders (WAidid) consensus document examines the policy, organizational, economic, and equity-related determinants that shape real-world implementation of long-acting monoclonal antibodies for infant RSV prevention. Methods: This study was conducted as a structured narrative review and WAidid expert consensus document. A structured literature search was performed in PubMed and Embase for English-language publications relevant to nirsevimab uptake and implementation, complemented by targeted review of surveillance reports, policy documents, and public health guidance from the ECDC, UKHSA, and CDC, as well as reference lists of selected publications. Eligible sources included observational and real-world implementation studies, systematic reviews and meta-analyses, economic evaluations, guidelines, policy statements, surveillance reports, and relevant narrative reviews. Evidence was synthesized qualitatively according to policy frameworks, financing and reimbursement, delivery pathways, demographic and socioeconomic determinants, and healthcare-system factors influencing uptake. No statistical software was used because no quantitative re-analysis or meta-analysis was performed. Results: Nirsevimab uptake was strongly influenced by national RSV prevention policies, particularly whether countries adopted universal infant monoclonal antibody programs, maternal RSV vaccination strategies, dual maternal–infant approaches, or targeted risk-based models. Universal, publicly funded programs integrated into neonatal care achieved the highest and most homogeneous coverage, especially when administration occurred before hospital discharge and was supported by registry-based recall systems for infants born outside the RSV season. In contrast, fragmented, outpatient-only, insurance-dependent, or partially reimbursed models were associated with lower, delayed, or more variable uptake. Additional determinants included product cost, reimbursement pathways, provider practices, caregiver awareness and health literacy, insurance status, income, race and ethnicity, geographic deprivation, and access to primary pediatric care. Most available evidence comes from high-income countries, limiting generalizability to low- and middle-income settings, where RSV burden is greatest and implementation constraints may differ. Conclusions: Successful implementation of long-acting monoclonal antibodies for infant RSV prevention requires more than regulatory approval and demonstrated efficacy. Equitable uptake depends on clear national recommendations, sustainable public financing, reliable product supply, integration into neonatal and primary pediatric care, proactive identification and recall of eligible infants, and targeted strategies to reduce socioeconomic and geographic disparities. Although many determinants identified in high-income settings are likely relevant globally, their feasibility, relative importance, and impact require dedicated evaluation in low- and middle-income countries. Full article

Accurate prediction of pile base resistance is essential for the safe and economical design of deep foundations, particularly in soft soils where load-transfer mechanisms are highly nonlinear and uncertain. This study develops a comparative, probabilistic, and interpretable machine learning framework for predicting pile unit base resistance using five input variables: applied load, settlement, effective pile length, axial stiffness, and SPT value. A Gaussian Process Regression model with an automatic relevance determination (ARD) Exponential kernel achieved the best performance, with RMSE = 262.11 kPa, R² = 0.943 on an independent test set, and 95% prediction intervals with 96.46% coverage. Beyond record-level evaluation, a leave-one-pile-out validation (the first grouped validation applied to this database) showed harder generalization to entirely unseen piles, driven mainly by a per-pile level offset rather than shape mismatch (within-pile correlation = 0.975). A sequential next-stage scheme, calibrating this level from a pile’s early loading stages, then predicted its remaining segments with consistently strong agreement (Willmott’s d = 0.76–0.83), supporting practical extension of partial load tests. Interpretability was assessed using ARD, SHAP, permutation/ablation importance, and partial dependence/accumulated local effects analysis, identifying settlement as the dominant predictor. The framework combines accuracy, calibrated uncertainty, interpretability, and validated segment-level extrapolation for reliability-oriented pile assessment. Full article

The Greater Mekong Subregion (GMS) has emerged as a strategic logistics hub due to rapid economic integration and the expansion of cross-border road transportation. However, international road logistics networks in the region must address several competing objectives, including minimizing transportation costs, reducing delivery times, and balancing transport distances among trading partners. To overcome these challenges, this study proposes an innovative hybrid computational framework that integrates the classical Transportation Problem with the Pythagorean methodology (TPPM). The proposed approach consolidates multiple transportation objectives into a unified performance metric based on the Pythagorean concept, thereby enabling simultaneous optimization under practical constraints. In addition, geographic inputs derived from Google Maps and Google Earth via web platforms, which are reliable open-source GIS tools, are incorporated into the transportation model to improve spatial accuracy. A simulated dataset comprising 35 suppliers and 42 customers, representing major logistics nodes in the GMS, is developed to evaluate the proposed method. The computational results indicate that the TPPM approach outperforms the conventional single-objective Classical Transportation Problem (CTP) by producing higher solution quality and more balanced performance. Overall, the findings demonstrate that the proposed hybrid method is a robust decision-support tool for sustainably enhancing the resilience of international logistics planning in emerging economic regions. Full article

The Guidelines for Sustainable Aquaculture (GSAs) emphasize that formulating proper regional development plans is essential for achieving sustainable growth in aquaculture. Conventional research has limitations in allocating resources from a regional scale, subject to various constraints relating to the social, economic, environmental, and other domains. To fill this research gap, this study proposes an inexact regional aquaculture system planning model (IRAM) to optimally allocate resources including energy, water, area, media, and labor among various aquaculture species across multiple aquafarms under uncertainty. The model is applied to Fujian Province, China, over a 15-year planning horizon (2026–2040, three 5-year periods). As model-based scenario insights derived under specific assumptions, the main findings are as follows: (i) the system cost would increase by [18.75, 20.00]%, while the product output would greatly rise by [41.57, 47.54]% from period 1 to period 3; (ii) renewable energy (wind and solar) would supply [60.32, 81.05]% of the total electricity by period 3; (iii) shallow-sea culture ([48.6, 50.2]%) and pond culture ([17.6, 18.8]%) would receive the highest media allocation via internet platforms, supporting community communication; and (iv) pollutant and carbon emissions would decline due to the adoption of low-carbon feed and renewable energy penetration. The findings are scenario-dependent, and their practical applicability relies on the sensitivity analysis and model code/data availability discussed in the main text. One limitation lies in its inadequate ability to handle stochastic and fuzzy information commonly encountered in real-world planning problems. Full article

Nanomaterials (NMs) have shown broad application potential in wastewater deep treatment, but the actual application is constrained by some issues such as nanoparticle (NP) aggregation and poor recyclability. Different from previous comprehensive reviews, this article systematically synthesizes data from over 100 peer-reviewed studies (2012 to 2026) to review the preparation methods, purification mechanisms, and removal efficiencies for various pollutants, and the technical and economic feasibility of NMs, with an emphasis on carrier-assisted immobilization and NM–microbial aggregate interactions. To start with, the methods of preparation were roughly distinguished into two categories which were “top-down” and “bottom-up” methods. The advantages, disadvantages, and utilities of the physical, chemical, and eco-friendly methods of biosynthesis were investigated while paying particular attention to the function of the loading technique in preventing NP aggregation and improving recyclability. By using the technique of loading in the carrier, the growth of NPs could be restricted up to 2–50 nm. Secondly, seven basic mechanisms that underlie the process of removing pollutants by using NPs were explained: adsorption, catalytic degradation, ion exchange, surface complexation, antibacterial action, redox transformation, and waste recycling. Particular focus was placed on understanding the interactions between NMs, microbial aggregates, and extracellular polymeric substances in wastewater treatment systems. Extracellular polymeric substances (EPS) could capture >90% NMs and mitigate their toxicity. Once again, the removal efficiency and main influencing factors associated with different types of NMs, for the treatment of heavy metals, dyes, antibiotics, and pathogenic microorganisms were summarized. Removal efficiencies of the pollutants ranged from 70% to over 99%, but these values were strongly influenced by pH and matrix and often decreased substantially in real wastewater. The existing literature was used to classify the experimental substrates (single-solute systems, multi-solute synthetic systems, municipal wastewater, industrial wastewater, secondary effluent). The performance of NMs in different categories was compared, revealing the huge performance gap between ideal laboratory conditions and practical applications. Lastly, the economic viability of the methods based on the use of NMs for purifying water was assessed taking into consideration various factors such as raw materials’ prices, energy costs of the process of making materials, recyclability of the materials, and the possibility of introducing the use of NMs on a larger scale. Unlike existing reviews, this article aims to provide a quantitative mechanistic framework bridging the rational design, safe application, and engineering promotion of NMs in deep wastewater treatment. Full article

The United States has long been a destination for immigrants seeking better economic opportunities and an improved quality of life, and among these populations, Muslim women represent a particularly vulnerable group facing unique challenges. First-generation Muslim immigrant women in America navigate a complex web of intersecting stressors that significantly impact their mental health and overall wellbeing. Despite the pervasiveness of mental health and heightened attention on mental health challenges post COVID-19, research on the mental health of the Muslim community—particularly immigrant Muslim women in the United States—is seldom studied. This qualitative study utilized a focus group among a purposive sample of immigrant Muslim women to explore the multifaceted mental health challenges with particular attention to how racism, Islamophobia, and acculturative stress create cumulative mental health burdens. Thematic analysis revealed five major themes highlighting the various mental health challenges faced by participants: experience encountering racism and discrimination, the importance of faith and Islamic practice in addressing mental health challenges, the role of family and peers in addressing mental health challenges, and mental health service utilization. These findings underscore the importance of culturally responsive mental health services and community-based interventions that recognize the intersection of migration, discrimination, and religious identity in shaping the mental health experiences of immigrant Muslim women. Full article

Background/Objectives: Veterinary vaccine manufacturing is essential for controlling transboundary animal diseases, strengthening animal health systems, and supporting livestock development, particularly in Southeast Asia where livestock production continues to expand. However, modernization toward Pharmaceutical Inspection Co-operation Scheme (PIC/S) Good Manufacturing Practice (GMP) compliance remains challenging because it requires coordinated development across regulatory, technical, organizational, financial, and governance domains. This study aimed to develop an evidence-informed strategic framework for veterinary vaccine manufacturing modernization through a structured and systematically documented framework development methodology integrating multidisciplinary evidence and practice-informed implementation experience. Methods: An evidence-informed framework development study was conducted through the multidisciplinary integration of multiple evidence sources, including international regulatory guidance, peer-reviewed scientific literature, multidisciplinary feasibility assessment, and practice-informed implementation experience derived from a government-commissioned consultancy project. Framework development followed a structured methodology comprising evidence collection, evidence categorization, multidisciplinary evidence synthesis, framework development, iterative refinement, and expert-informed validation. Only generalized methodological principles and potentially transferable implementation knowledge were incorporated to ensure confidentiality of project-specific information. Results: Multidisciplinary evidence synthesis identified ten evidence domains encompassing regulatory, technical, organizational, economic, legal, environmental, governance, workforce, infrastructure, and implementation considerations. These domains were translated through a structured process into an evidence-informed strategic framework organized around four sequential modernization phases—Design, Construction, Validation, and Continuous Improvement—supported by cross-cutting strategic enablers. Iterative refinement through expert review, technical consultation, and implementation verification strengthened the framework’s scientific consistency, regulatory alignment, and practical applicability. Conclusions: Veterinary vaccine manufacturing modernization should be regarded as a multidisciplinary organizational transformation rather than solely as an infrastructure or engineering project. Beyond proposing a strategic framework, this study provides a transparent, systematically documented and traceable methodology for translating multidisciplinary evidence into strategic decision-support tools. The proposed framework may assist governments, regulatory authorities, vaccine manufacturers, and researchers in developing evidence-informed modernization strategies for veterinary biological manufacturing systems, particularly in low- and middle-income countries, subject to adaptation to specific regulatory, technical, institutional, and resource contexts. Full article

In recent decades, the digital transformation has increasingly influenced structures and practices in community social services in Spain and other European countries. The progressive integration of telecare systems, home automation, mobile applications, and digital tools into the community sphere has enabled the optimisation of certain interventions, but it has also generated ethical dilemmas and new forms of inequality. This article examines how technologies are incorporated into community social services and home care practices in Spain within a context marked by gender, class, and age inequalities. Drawing on qualitative research involving thirty-two interviews with care recipients, carers, and representatives of social organisations, we analyse the socio-technological networks that mediate care, their impact on self-determination, and the limits and resistance to digitalisation. Our findings indicate that, within the community sphere, technologies can only contribute effectively to greater well-being when they are integrated into an ethical framework that prioritises human accompaniment, social co-responsibility, and the recognition of care as a right. We further discuss the tensions faced by cooperative and community organisations in providing sustained inclusive and dignified services within a precarious socio-economic context that highlights shared responsibility. Finally, we offer reflections on technological innovation, advocating for interdisciplinary collaboration that strengthens community networks and advances social justice. Full article

The evolution of land-use types in mining cities is critical for balancing resource exploitation and ecological sustainability. Taking Jungar Banner as a case study, this study uses remote sensing imagery and auxiliary data (2010–2025) to examine spatiotemporal land-use changes, applies the OPGD model to detect driving factors, and integrates a Markov chain with an optimized NEGM-MOP-PLUS model to project 2030 land-use patterns under multiple scenarios. Results show that grassland shrank markedly, while cropland and built-up land expanded—the latter reaching 395.75 km² by 2025. After 2020, core mining areas became more contiguous, while peripheral zones showed increased fragmentation, with built-up land expansion becoming the dominant trend. Driving forces shifted from natural constraints to anthropogenic dominance: natural factors prevailed in 2010, mining impacts took the lead by 2015, and a mining–precipitation dual-core structure emerged by 2020. Future projections indicate continued grassland and bare land reduction, alongside water and built-up land expansion across all scenarios. Among them, the CDS, which balances economic and ecological objectives, is identified as the optimal spatial planning direction based on ecosystem service value (ESV) assessment. These findings offer practical guidance for managing land-use transitions in arid and semi-arid resource-based mining regions. Full article

The U.S. FSMA Intentional Adulteration (IA) Rule and GFSI-recognized certification schemes such as IFS Food and BRCGS Food include requirements for establishing and maintaining a written food defense plan, including vulnerability assessment. This study evaluates the suitability and policy relevance of two established food defense risk assessment methodologies, TACCP and CARVER+SHOCK, when applied to the processing of whole oranges with edible coatings. A structured case study was conducted at a medium-sized citrus processing facility certified under IFS Food and BRCGS Food standards. Food defense threats were systematically identified along the entire production line using the FDA Food Defense Self-Assessment Tool. The identified threats were subsequently assessed using TACCP, which is based on likelihood and impact, and CARVER+SHOCK, a multidimensional quantitative approach integrating operational, economic, and psychological impact factors. Twenty-four potential intentional contamination threats were identified. Both methodologies consistently identified critical vulnerabilities at key control points, particularly in washing systems, chemical handling areas, and stages with unrestricted access. TACCP proved to be rapid, intuitive, and easily integrated into existing food safety management systems. In contrast, CARVER+SHOCK provided a more differentiated ranking of the identified threats because of its multidimensional scoring structure, thereby supporting the development of a structured and economically rational mitigation plan and offering value for policymakers and certification bodies seeking to harmonize risk-assessment practices. Full article

The large-scale integration of variable renewable energy sources (RES) such as solar and wind into transmission networks poses significant challenges to grid stability, operational efficiency, and economic dispatch. Battery Energy Storage Systems (BESS) offer a flexible solution, but their optimal placement remains critical to maximizing technical and economic benefits. This paper presents a multi-index, scenario-based framework for optimal BESS siting in a modified IEEE 118-bus transmission system under high renewable penetration. Six complementary indices are employed: Voltage Deviation Index (VDI), Fast Voltage Stability Index (FVSI), Line Congestion Index (LCI), Bus Congestion Index (BCI), Z-bus Sensitivity Index (ZBSI), and nodal price difference (Δλ). Eight extreme scenarios, combining high/low solar, wind, and hydro generation under peak load, are used to identify vulnerable buses. Five weighting case studies reflect different stakeholder priorities: voltage stability, congestion relief, energy arbitrage, loss reduction, and equal weightage. Results show that the congestion relief case achieves the lowest daily operating cost (approx. $8000 less than the base case) and the highest net economic benefit, while the loss reduction case delivers the greatest reduction in active (34 MW) and reactive (169 MVAr) power losses, compared to the base case. The proposed framework demonstrates that integrating technical and market-based indicators enables more robust and economically attractive BESS placement. This work provides a practical, data-driven planning tool for grid operators and investors aiming to enhance transmission system sustainability under high-RES variability. Full article

Against the backdrop of rapid development in marine engineering, the construction industry faces practical challenges, such as water scarcity, limited availability of natural river sand, and high raw material transportation costs. This has led to an increasing demand for resource-efficient concrete production technologies and improved construction economic efficiency. Seawater–sea-sand concrete (SWSSC) offers a locally sourced solution that effectively reduces the construction sector’s overreliance on freshwater and river sand, lowers material transportation costs for coastal infrastructure projects, and supports marine engineering and infrastructure development along the Belt and Road Initiative. However, existing research lacks systematic organization and visualized quantitative analysis. Utilizing the CiteSpace 7.0.R0 knowledge graph analysis software, this study selects 982 relevant papers published in the Web of Science (WOS) Core Collection between 2016 and 2025 as the sample. By employing analytical methods—including annual publication volume statistics, collaboration networks among researchers, keyword co-occurrence patterns, and temporal evolution charts—we systematically delineate the overall research landscape, distribution of key research institutions, trends in research hotspots, and future frontier directions in this field. The analysis results indicate that: (1) The total number of publications in the global seawater–sand concrete field has been increasing year by year. From 2016 to 2018, it was the basic exploration period, with an average annual publication volume of less than 10. From 2019 to 2021, it was the deepening and expansion period, with research expanding from the performance of a single material to material modification and structural application. From 2022 to 2025, it was the rapid prosperity period, with the publication volume reaching its peak in 2024–2025 (208 articles and 203 articles), and the publication volume continued to rise. (2) China ranks first globally with 798 publications, but its centrality in international cooperation networks is only 0.24, reflecting low overall collaboration density and loose partnerships between institutions and authors, without the formation of cross-institutional core research teams with global leadership. (3) Research hotspots in this field primarily focus on material properties, durability characteristics, and mechanical strength, among which FRP reinforcement systems serve as a bridge for interdisciplinary research bridging material fundamentals and engineering applications, representing a key research branch. (4) From the perspective of evolutionary trends, the field exhibits three major developmental shifts from macroscopic mechanical performance characterization to in-depth investigation of microscopic damage mechanisms, from single-material studies to composite structural systems, and from short-term laboratory accelerated testing to full life-cycle performance evaluation, with the low-carbon potential of seawater–sand concrete increasingly becoming a prominent research focus. Therefore, this paper advocates strengthening international and inter-institutional academic collaboration, fostering multidisciplinary innovation, and prioritizing breakthroughs in key areas, such as large-scale intelligent performance prediction, long-term performance database development, and digital-twin-based operation and maintenance management, to facilitate the transition of seawater–sand concrete technology toward efficient, low-carbon, safe, and intelligent engineering applications. Full article

Late blight in tomato caused by Phytophthora infestans can lead to severe economic losses. Early detection is essential for effective disease management. This study investigates the spectral characteristics of healthy and late blight-infected tomato leaves and plants using non-destructive hyperspectral imaging and proposes a cost-effective machine vision system for early disease detection. Hyperspectral images from seven batches of leaf sets and six batches of whole plant sets were taken hourly over a 96 h period under both controlled and artificially infected conditions. The hyperspectral data cubes were processed with an image analysis model that identified healthy vs. infected regions. Key wavelengths (77 from leaf datasets and 24 from plant datasets) were selected using recursive feature elimination and analysed with four machine learning classifiers: k-nearest neighbour, support vector machine, random forest, and artificial neural network. The models differentiated healthy and infected tissue with high accuracy (98–99%). The hyperspectral data were simplified into a multichannel image with most informative wavelengths, using a custom spectral index and binary decision rule. Experimental limitations were addressed, and a conceptual design of practical hardware was proposed: a monochrome camera combined with a multichannel light source and polariser mounted on mobile equipment. Although further trials will be needed, this proof-of-concept study and conceptual hardware design can be adapted in other crops facing similar disease challenges. Full article

Green hydrogen strategies proliferate across developing economies, yet most assume the planning authority possesses the state capacity, regulatory autonomy, and investment conditions that conflict-affected and fragile economies lack. Whether a strategy logic derived in one such context transfers to others with different institutional capacity remains untested. This study develops a Conflict-Affected Energy Transitions (CAET) framework and empirically examines its barrier gradient and conditional transferability propositions, analyzing at the country level a regional expert survey—data that prior single-case work, including the authors’ own, used only for binary external validation. A total of 137 energy experts across seventeen Arab states are grouped into three institutional clusters—conflict-affected/fragile, stable developing, and Gulf/high-capacity—and examined through cluster barrier and readiness profiles, a perceived-versus-predictive importance comparison, hierarchical clustering, and a Mode-A partial-least-squares path model with measurement invariance (MICOM) testing and permutation-based multi-group analysis. Energy justice and sovereignty are used as analytical and interpretive lenses, not as measured latent constructs in the structural model. Results show that barrier burdens follow a monotonic institutional fragility gradient: regulatory/institutional barriers rise from 3.02 (Gulf) through 3.52 (stable) to 4.06 (fragile), where they are the most severe constraint. Moreover, the perceived–predictive divergence—social barriers are rated least severe yet associate most strongly with sustainability—recurs across the region. In addition, the model satisfies compositional invariance across fragile and stable clusters while equality of regulatory means and variances fails as expected, and no structural path differs detectably between them at the current sample size. The adoption–governance–sustainability mechanism is therefore provisionally comparable rather than definitively invariant. We propose conditional transferability: the mechanism travels, provisionally, while priorities must be re-weighted by institutional context. Policy implications are differentiated—institutions-first, community-scale pathways for fragile states; finance and market formation for stable developing states; export-scale deployment for high-capacity states—and the CAET framework offers a generalizable alternative to techno-economic determinism for hydrogen strategy under constrained sovereignty. In practical terms, energy ministries in fragile states should sequence rule-making, permitting authority, and community-scale pilots before committing deployment capital; stable developing states should concentrate on de-risking finance and forming early offtake markets; and high-capacity states can proceed directly to export-scale projects and regional standard setting. Full article

Pork is highly perishable during storage, leading to enormous economic losses and potential food safety hazards. Anthocyanins (ANTs) possess excellent antioxidant and antibacterial activities, but their poor stability in practical applications limits their industrial application. To address these issues, a novel composite preservation film was prepared by the four-sided applicator solution casting method, using polylactic acid (PLA) and polybutylene adipate-co-terephthalate (PBAT) as matrix materials and ANTs@ZIF-8 as functional filler. Zeolitic imidazolate framework-8 (ZIF-8) encapsulated ANTs to enhance its stability and achieve sustained release, while the PLA/PBAT was selected for its good biodegradability, mechanical and barrier properties. The structure and properties of the PLA/PBAT/ANTs@ZIF-8 composite films were investigated, and the results showed that ANTs@ZIF-8 nanoparticles had stable dispersibility in the matrix, which effectively improved the compatibility between nanoparticles and the film matrix. The prepared composite films exhibited excellent tensile strength (TS), elongation at break (EAB) and water vapor transmission rate (WVTR), as well as good antibacterial activity against E. coli and S. aureus. Furthermore, the practical pork preservation performance of the films was investigated, and the results demonstrated that the composite films could effectively reduce the pH value, water loss, color difference, total volatile basic nitrogen (TVB-N) content and malondialdehyde (MDA) content of fresh pork during storage, successfully extending the shelf life of pork to 12 days. This study develops a multifunctional, biosafe, and biodegradable PLA/PBAT composite film incorporated with ANTs@ZIF-8, providing a feasible strategy and scientific reference for the design and development of high-performance active biodegradable packaging materials. Full article