Search Results (432)

High-need populations face substantive barriers to accessing primary care, leading to disproportionately poor health outcomes. This descriptive, observational study details the implementation of a Federally Qualified Health Center (FQHC) program designed to improve engagement in care and enabling services by leveraging mobile health units (MHUs) to provide comprehensive, low-barrier primary care services to residents who were previously unable or unwilling to engage with the traditional healthcare system. The program sought to overcome common access challenges such as lack of transportation, lack of insurance, and mistrust of healthcare institutions. We describe the operational framework of this program, examine the types of care delivered, and offer recommendations from the perspective of a large multi-site FQHC experienced in reengaging people back to the healthcare system but new to providing mobile health care. We describe our program’s focus on prioritizing patient engagement and access and its consideration of operational and technical infrastructure. Based on our FQHC’s experience, we provide recommendations on how to address patients’ health and social needs. FQHCs have the potential to implement MHUs, drawing on their existing infrastructure and community relationships. Our MHU program is well-aligned with our FQHC’s commitment and priority to deliver essential care and foster continuity within hard-to-reach communities, strengthening the local healthcare safety net and improving healthcare for high-need populations. Full article

The transition toward a circular economy (CE) is progressively recognized as a strategic pathway to reconcile economic growth with environmental sustainability. Municipal solid waste management in Jordan remains mostly linear, with over 90% of the generated waste disposed of in landfills and open dumpsites. This study critically examines the prospects of adopting CE principles in Jordan’s waste sector by evaluating current practices, policy frameworks, and potential recycling pathways. A mixed-methods approach was adopted, combining quantitative modeling with qualitative insights from stakeholders and public surveys. Three recycling scenarios were assessed against the baseline scenario: 25%, 50%, and 75% waste recovery by 2034. The U.S. EPA WARM model was used to estimate greenhouse gas (GHG) emissions and energy savings. It was inferred that the net avoided emissions (against the baseline) for Scenarios 1, 2, and 3 are 14.5%, 29.0%, and 44%, respectively, with paper/cardboard contributing most to avoided emissions. Nonetheless, only Scenarios 2 and 3 were deemed environmentally sustainable, as their projected net GHG emissions for 2034 were lower than those recorded in the base year. Socio-economic analysis identified the major barriers as limited public awareness and participation, infrastructural gaps, and financial and institutional constraints. The analysis further reveals that despite the relatively high capital and operating costs associated with advancing toward CE in waste management, the long-term environmental and socio-economic gains are expected to outweigh the associated costs, particularly in terms of avoided GHG emissions and reduced landfill dependency. Full article

Background: Achieving deep decarbonization in global supply chains is essential for advancing net-zero objectives; however, the integrative role of artificial intelligence (AI) and robotics in this transition remains insufficiently explored. This study examines how these technologies support carbon-emission reduction across supply chain operations. Methods: A curated corpus of 83 Scopus-indexed peer-reviewed articles published between 2013 and 2025 is analyzed and organized into six domains covering supply chain and logistics, warehousing operations, AI methodologies, robotic systems, emission-mitigation strategies, and implementation barriers. Results: AI-driven optimization consistently reduces transport emissions by enhancing routing efficiency, load consolidation, and multimodal coordination. Robotic systems simultaneously improve energy efficiency and precision in warehousing, yielding substantial indirect emission reductions. Major barriers include the high energy consumption of certain AI models, limited data interoperability, and poor scalability of current applications. Conclusions: AI and robotics hold substantial transformative potential for advancing supply chain decarbonization; nevertheless, their net environmental impact depends on improving the energy efficiency of digital infrastructures and strengthening cross-organizational data governance mechanisms. The proposed framework delineates technological and organizational pathways that can guide future research and industrial implementation, providing novel insights and actionable guidance for researchers and practitioners aiming to accelerate the low-carbon transition. Full article

Malaria continues to impose a devastating disease burden globally despite control efforts spanning decades. Its elimination has been hindered by parasite and vector complexity and emerging drug and insecticide resistance, along with unremitting barriers to uptake of preventative strategies largely driven by social inequities, cost constraints, and logistical challenges in implementation. This review synthesises current and emerging prevention strategies, including vector control, chemoprevention and immunoprophylaxis. Insecticide-treated nets and indoor residual spraying remain cornerstones of vector control, although their effectiveness is increasingly compromised by widespread insecticide resistance. Chemoprevention, including intermittent preventive treatment in pregnancy and seasonal malaria chemoprevention in children, has proven highly efficacious, yet uptake remains below WHO targets and concerns about drug resistance remain. Recent advances in vaccines, notably RTS,S/AS01 and R21/Matrix-M, represent landmark achievements, with large-scale rollouts demonstrating reductions in severe disease and mortality. Novel approaches, such as monoclonal antibodies and genetically modified mosquitoes, offer promising avenues for future prevention. However, challenges remain in ensuring equitable access, sustaining efficacy in the face of evolving parasite and vector biology, and integrating interventions into diverse health systems. This review highlights the need for adaptive, multifaceted approaches to achieve malaria elimination goals. Full article

This study introduces an integrated Life Cycle Assessment–Multi-Criteria Decision Analysis–Nash Equilibrium (LCA–MCDA–NE) framework to assess the feasibility of hydrogen energy storage (HES) in Philippine island grids. It starts with a cradle-to-gate LCA of hydrogen production across various electricity mix scenarios, from diesel-dominated Small Power Utilities Group (SPUG) systems to high-renewable configurations, quantifying greenhouse gas emissions. These impacts are normalized and integrated into an MCDA framework that considers four stakeholder perspectives: Regulatory (PRF), Developer (DF), Scientific (SF), and Local Social (LSF). Attribute utilities for Maintainability, Energy Efficiency, Geographic–Climatic Suitability, and Regulatory Compliance inform a 2 × 2 strategic game where net utility gain (Δ) and switching costs (C₁, C₂) influence adoption behavior. The findings indicate that the baseline Nash Equilibrium favors non-adoption due to limited utility gains and high switching barriers. However, enhancements in Maintainability and reduced costs can shift this equilibrium toward adoption. The LCA results show that meaningful decarbonization occurs only when low-carbon generation exceeds 60% of the electricity mix. This integrated framework highlights that successful HES deployment in remote grids relies on stakeholder coordination, reduced risks, and access to low-carbon electricity, offering a replicable model for emerging economies. Full article

Hydrogen has emerged as a cornerstone of global decarbonisation strategies, offering a flexible pathway to reduce dependence on fossil fuels and accelerate progress towards net-zero targets. However, the development of a globally integrated hydrogen economy remains uneven, reflecting disparities in renewable energy potential, infrastructure readiness, investment capacity, and policy commitment. To better understand these differences and the barriers they create, this study undertakes a comprehensive comparative assessment of the global hydrogen supply chain encompassing resources, production, storage, transport, and end-use applications. Further, a structured analytical framework comprising ten principles and twenty-nine sub-factors was developed to evaluate national hydrogen policies, technological readiness, and enabling conditions across twenty-six countries. The results show that the United States, China, Japan, South Korea, and Germany lead global progress, while many countries remain at an early stage of engagement. These findings further inform persistent regional asymmetries and emphasise the need for stronger international coordination. Drawing on these findings, the paper advances targeted policy and research recommendations to lower production costs, expand storage and transport capacity, and harmonise regulatory frameworks, thereby defining a coherent pathway towards a secure, cost-competitive, and equitable global hydrogen economy by 2050. Full article

High regeneration energy demand remains a critical barrier to the large-scale deployment of ethanolamine-based (MEA-based) CO₂ capture. This study adopts an Al₂O₃ ceramic-membrane heat exchanger (CMHE) to recover both sensible and latent heat from the stripped gas. Experiments confirm that heat and mass transfer within the CMHE follow a coupled mechanism in which capillary condensation governs trans-membrane water transport, while heat conduction through the ceramic membrane dominates heat transfer, which accounts for more than 80%. Guided by this mechanism, systematic structural optimization was conducted. Alumina was identified as the optimal heat exchanger material due to its combined porosity, thermal conductivity, and corrosion resistance. Among the tested pore sizes, CMHE-4 produces the strongest capillary-condensation enhancement, yielding a heat recovery flux (q value) of up to 38.8 MJ/(m² h), which is 4.3% and 304% higher than those of the stainless steel heat exchanger and plastic heat exchanger, respectively. In addition, Length-dependent analyses reveal an inherent trade-off: shorter modules achieved higher q (e.g., 14–42% greater for 200-mm vs. 300-mm CMHE-4), whereas longer modules provide greater total recovered heat (Q). Scale-up experiments demonstrated pronounced non-linear performance amplification, with a 4 times area increase boosting q by only 1.26 times under constant pressure. The techno-economic assessment indicates a simple payback period of ~2.5 months and a significant reduction in net capture cost. Overall, this work establishes key design parameters, validates the governing transport mechanism, and provides a practical, economically grounded framework for implementing high-efficiency CMHEs in MEA-based CO₂ capture. Full article

Household food waste remains a significant barrier to sustainable consumption goals. This study investigates the impact of sociodemographic characteristics influence self-reported food waste levels in Poland. A cross-sectional CAWI survey (N = 1000), based on the HFSSM, was conducted among adults responsible for purchasing household food. Associations between food waste and structural factors were analysed using χ² tests, Spearman rank correlations, and Mann–Whitney U tests. Age appears as the strongest determinant: younger respondents consistently report higher food waste, while older adults indicate markedly lower levels. Household composition is equally important—the presence and number of children significantly increase waste. Economic status is also relevant: pensioners and disability-benefit recipients report substantially less waste than employed and self-employed individuals. Net household income shows no significant effect. Education does not necessarily reduce food waste; in some comparisons, higher-educated respondents report slightly higher levels, suggesting that formal education does not automatically translate into effective food management routines. The findings highlight that food waste is primarily influenced by life stage, household structure, and daily habits rather than income or education. Interventions should focus on younger adults and families with children, emphasising practical skills such as meal planning, inventory management, appropriate storage, and the use of leftovers. Full article

Protecting aquatic biodiversity while ensuring reliable hydropower production and water supply remains a core challenge for both water security and biosecurity. In this PRISMA-based systematic review, we synthesize evidence from 96 studies on fish guidance and deterrence at hazardous water intakes. We examine non-physical barriers, including acoustic and light cues, electric fields, bubble curtains, and chemical stimuli, as well as physical barriers such as racks, guidance structures, and nets or screens that aim to divert fish away from intakes and toward selective passage routes. Overall, guidance and deterrence performance is strongly species- and site-specific. Multimodal systems that combine multiple cues show the highest mean guidance efficiency (~80%), followed by light-based deterrents (~77%). Acoustic, electric, and bubble barriers generally achieve intermediate efficiencies (~55–58%), whereas structural devices alone exhibit lower mean performance (~46%), with substantial variability among sites and designs. Physical screens remain effective for larger size classes but can increase head loss and debris accumulation. By contrast, non-physical systems offer more flexible, low-footprint options whose success depends critically on local hydraulics, the sensory ecology of target species, and ambient environmental conditions. We identify major knowledge gaps relating to underlying sensory and behavioral mechanisms, hydraulics-based design rules, and standardized performance metrics. We also highlight opportunities to integrate advanced monitoring and AI-based analytics into adaptive, site-specific guidance systems. Taken together, our findings show that carefully selected and tuned barrier technologies can provide practical pathways to enhance water security and biosecurity, while supporting sustainable fish passage, improving invasive-species control, and reducing ecological impacts at water infrastructure. Full article

Stroke is a leading cause of death and long-term disability worldwide, with ischemic stroke accounting for approximately 62.4% of all cases. This condition often results in persistent motor dysfunction, significantly reducing patients’ productivity. The effectiveness of rehabilitation therapy is crucial for post-stroke motor recovery. However, limited access to rehabilitation services particularly in low- and middle-income countries remains a major barrier due to a shortage of experienced professionals. This challenge also affects home-based rehabilitation, an alternative to conventional therapy, which primarily relies on standard evaluation methods that are heavily dependent on expert interpretation. Electromyography (EMG) offers an objective and alternative approach to assessing muscle activity during stroke therapy in home environments. Recent advancements in deep learning (DL) have opened new avenues for automating the classification of EMG data, enabling differentiation between post-stroke patients and healthy individuals. This study introduces a novel methodology for transforming EMG signals into time–frequency representation (TFR) spectrograms, which serve as input for a convolutional neural network (CNN) model. The proposed Tri-CCNN model achieved the highest classification accuracy of 93.33%, outperforming both the Shallow CNN and the classic LeNet-5 architecture. Furthermore, an in-depth analysis of spectrogram amplitude distributions revealed distinct patterns in stroke patients, demonstrating the method’s potential for objective stroke assessment. These findings suggest that the proposed approach could serve as an effective tool for enhancing stroke classification and rehabilitation procedures, with significant implications for automating rehabilitation monitoring in home-based rehabilitation (HBR) settings. Full article

The Qinling–Bashan mountainous region and its surrounding areas in Shaanxi Province constitute a critical ecological security barrier and significant socio-economic zone within China, currently experiencing mounting ecological stress from both natural processes and anthropogenic activities. This study proposes an ecological restoration zoning framework built upon assessments of ecological vulnerability (EV) and ecosystem service value (ESV). The InVEST model was used to quantify major ecosystem services, while the Vulnerability Scoping Diagram (VSD) model evaluated ecological vulnerability. Both the ESV and EV layers were classified using the natural breaks method and aggregated at the township level to delineate restoration zones. Unlike previous studies relying on subjective judgment, this study constructs a standardized ‘vulnerability–service value’ decision matrix for the Qinling–Bashan region, providing a clear technical pathway for spatial restoration. Key findings include the following: (1) Spatial Vulnerability Pattern: The Qinling and Bashan mountain cores exhibit predominantly low vulnerability (potential and slight), while severe vulnerability is concentrated in the urbanizing Guanzhong Plain, emphasizing the need for urban ecological restoration. (2) Dominant Ecosystem Services: Carbon storage and net primary productivity (NPP) together account for 93% of the total ESV, highlighting the importance of forest conservation for national climate regulation. (3) Zoning Strategy: Four functional zones were defined, with the largest being the ecological conservation zone (44.8%), while a smaller ecological restoration zone (2.8%) in urban peripheries requires targeted intervention. Full article

The UK’s net-zero by 2050 commitment necessitates urgent housing sector decarbonisation, as residential buildings contribute approximately 17% of national emissions. Post-1950 construction prioritised speed over efficiency, creating energy-deficient housing stock that challenges climate objectives. Current retrofit policies focus primarily on technological solutions—insulation and heating upgrades—while neglecting broader sustainability considerations. This research advocates systematically integrating Circular Economy (CE) principles into residential retrofit practices. CE approaches emphasise material circularity, waste minimisation, adaptive design, and a lifecycle assessment, delivering superior environmental and economic outcomes compared to conventional methods. The investigation employs mixed-methods research combining a systematic literature analysis, policy review, stakeholder engagement, and a retrofit implementation evaluation across diverse UK contexts. Key barriers identified include regulatory constraints, workforce capability gaps, and supply chain fragmentation, alongside critical transition enablers. An evidence-based decision-making framework emerges from this analysis, aligning retrofit interventions with CE principles. This framework guides policymakers, industry professionals, and researchers in the development of strategies that simultaneously improve energy-efficiency, maximise material reuse, reduce embodied emissions, and enhance environmental and economic sustainability. The findings advance a holistic, systems-oriented approach, positioning housing as a pivotal catalyst in the UK’s transition toward a circular, low-carbon built environment, moving beyond isolated technological fixes toward a comprehensive sustainability transformation. Full article

In many aquaculture farms, Unmanned Underwater Vehicles (UUVs) are being deployed to perform dangerous and time-consuming repetitive tasks (e.g., fish net-pen visual inspection) on behalf of or in collaboration with farm operators. Mostly, they are remotely operated, and one of the main barriers to deploying them autonomously is the UUV localisation. Specifically, the cost of the localisation sensor suite, sensor reliability in constrained operational workspace and return on investment (ROI) for the huge initial investment on the UUV and its localisation hinder the R&D work and adoption of the autonomous UUV deployment on an industrial scale. The proposed system, which leverages the AprilTag (a fiducial marker used as a frame of reference) detection, provides cost-effective UUV localisation for the initial trials of autonomous UUV deployment, requiring only minor modifications to the aquaculture infrastructure. With such a cost-effective approach, UUV R&D engineers can demonstrate and validate the advantages and challenges of autonomous UUV deployment to farm operators, policymakers, and governing authorities to make informed decision-making for the future large-scale adoption of autonomous UUVs in aquaculture. Initial validation of the proposed cost-effective localisation system indicates that centimetre-level accuracy can be achieved with a single monocular camera and only 10 AprilTags, without requiring physical measurements, in a $115.46$ m³ laboratory workspace under various lighting conditions. Full article

One of the major challenges for effective intrusion detection systems (IDSs) is continuously and efficiently incorporating changes on cyber-attack tactics, techniques, and procedures in the Internet of Things (IoT). Semi-automated cross-organizational sharing of IDS data is a potential solution. However, a major barrier to IDS data sharing is privacy. In this article, we describe the design, implementation, and evaluation of FedPrIDS: a privacy-preserving federated learning system for collaborative network intrusion detection in IoT. We performed experimental evaluation of FedPrIDS using three public network-based intrusion datasets: CIC-IDS-2017, UNSW-NB15, and Bot-IoT. Based on the labels in these datasets for attack type, we created five fictitious organizations, Financial, Technology, Healthcare, Government, and University and evaluated IDS accuracy before and after intelligence sharing. In our evaluation, FedPrIDS showed (1) a detection accuracy net gain of 8.5% to 14.4% from a comparative non-federated approach, with ranges depending on the organization type, where the organization type determines its estimated most likely attack types, privacy thresholds, and data quality measures; (2) a federated detection accuracy across attack types of 90.3% on CIC-IDS-2017, 89.7% on UNSW-NB15, and 92.1% on Bot-IoT; (3) maintained privacy of shared NIDS data via federated machine learning; and (4) reduced inter-organizational communication overhead by an average 50% and showed convergence within 20 training rounds. Full article

Urban green spaces, as crucial components, can effectively mitigate atmospheric pollutants such as NO₂. However, the heterogeneous driving forces and the underlying quantitative mechanisms of different vegetation community structures in response to NO₂ exposure remain insufficiently explored. This study utilized a laboratory-based artificial fumigation method to examine the NO₂ mitigation benefits and response mechanisms of three representative vegetation structures (tree–shrub–grass, tree-shrub, and tree-grass) as well as their monoculture communities under NO₂ stress. The objective was to elucidate the variations in NO₂ reduction capacity and the adaptive mechanisms associated with different vegetation structures. The results demonstrated that, under NO₂ exposure, the NO₂ reduction rate of the tree–shrub–grass mixed community was 56.15 mg·h⁻¹. NO₂ stress inhibited leaf morphogenesis and plant growth. However, the tree–shrub–herbaceous community enhanced its NO₂ tolerance by reallocating photosynthetic products and increasing epidermal thickness, stomatal density, and the compactness of tissue structure, thereby strengthening its mechanical barrier function. The NO₂ reduction rate was positively correlated with parameters such as net photosynthetic rate, stomatal density, leaf width, transpiration rate, and stomatal conductance, but negatively correlated with fluorescence and the leaf length-to-width ratio. A comprehensive evaluation based on fuzzy membership functions ranked the NO₂ mitigation and tolerance capacities of plant communities as follows: the tree–shrub–herbaceous community exhibited the strongest capacity for NO₂ reduction and stress tolerance. Thus, in NO₂-polluted areas, priority should be given to establishing tree–shrub–grass composite vegetation structures, whose multidimensional resistance mechanisms provide both a theoretical foundation and a technical pathway for the ecological restoration of urban green spaces. Full article