Search Results (5,790)

With the rapid penetration of renewable energy, grid-connected microgrids have become a cornerstone of low-carbon power systems, while also posing major challenges for coordinated scheduling under coupled economic and environmental goals. The resulting dispatch problem is highly nonlinear and high-dimensional, featuring tight operational constraints and conflicting cost–emission trade-offs that often undermine the efficiency and reliability of conventional optimization methods, thereby limiting overall economic productivity. This paper presents an adaptive economic–environmental dispatch framework for grid-connected microgrids formulated as a multi-objective optimization problem that simultaneously minimizes operating cost and environmental protection cost. To navigate the rugged and constrained search landscape, we develop an enhanced metaheuristic termed the Lévy–Triangular Walk Dung Beetle Optimizer (LTWDBO). The LTWDBO integrates (i) chaotic population initialization to improve diversity and feasibility coverage, (ii) a geometry-inspired triangular walk operator to strengthen local exploitation, and (iii) an adaptive Lévy-flight strategy to boost global exploration, achieving a robust exploration–exploitation balance over the entire optimization process, representing a process innovation in metaheuristic-driven dispatch optimization. The proposed method is validated on a representative grid-connected microgrid comprising photovoltaic generation, wind turbines, micro gas turbines, and battery energy storage. Comparative experiments against representative baselines (DBO, WOA, TDBO, and NSGA-II) demonstrate that the LTWDBO achieves consistently better solution quality. Our LTWDBO attains the lowest optimal objective value of 255,718.34 Yuan, compared with 357,702.68 Yuan (DBO), 347,369.28 Yuan (TDBO), and 3,854,359.36 Yuan (WOA). The LTWDBO also yields the best average objective value of 673,842.24 Yuan, an improvement of over 1,001,813.10 Yuan (DBO). Full article

The construction sector’s transition to carbon neutrality requires innovative strategies to address the performance and cost challenges of advanced building designs, such as passive-oriented nearly zero-energy buildings. This study proposes an artificial intelligence-based multi-objective optimization framework to reduce both energy consumption and construction costs for residential building envelopes in Chengdu’s hot summer and cold winter climate. The framework uses the NSGA-II genetic algorithm within DesignBuilder to explore trade-offs between energy efficiency and economic cost. Key design parameters (wall insulation thickness, roof insulation thickness, and window glazing type) are optimized to obtain a Pareto-optimal front. A subsequent global incremental cost analysis of the non-dominated solutions identifies the optimal balance where significant energy savings are achieved before diminishing returns set in. The research results show that by combining the NSGA-II algorithm with the global incremental cost method in the Chengdu area, the parameters of the enclosure structure can be systematically optimized, and the optimal balance point between energy conservation and cost can be effectively identified. Based on this, an “energy-saving optimal—trade-off optimal—cost optimal” template set design path based on dual objectives of energy consumption and cost can be obtained, which is applicable to different demand-oriented engineering scenarios. This research provides a quantifiable decision-making basis for the design of buildings with passive design strategies that achieve near-zero energy consumption in hot summer and cold winter regions, helping to achieve the coordinated optimization of energy efficiency goals and economic feasibility, and promoting the reliable promotion and application of near-zero energy buildings. Full article

Shape optimization of arch dams is essential for balancing structural safety and economic efficiency, yet remains computationally intensive due to costly finite element analyses and strict geometric constraints. Conventional sampling techniques often yield infeasible designs that undermine surrogate model fidelity. This study proposes an integrated framework combining Stratified Conditional Latin Hypercube Sampling (SC-LHS), automated modeling, and Gaussian Process (GP) surrogate models. SC-LHS incorporates hierarchical constraints to eliminate infeasible samples during generation, while a Python-driven workflow automates the process from parameterization to simulation. Coupling the GP surrogate with NSGA-II enables efficient Pareto front exploration. The results indicate that SC-LHS is superior to standard LHS, Constrained LHS, and Sobol sequences with rejection in terms of feasibility rate and space-filling metrics. The optimal compromise solution reduces dam volume by 10.4% and tensile zone volume by 15.2% compared to the initial design. This framework effectively reconciles economic and safety objectives, offering a robust methodology for complex hydraulic structure design. Full article

Decarbonizing the transportation sector requires quick adoption of low-carbon energy carriers, with green hydrogen becoming a promising option for zero/low-emission mobility. Hydrogen refueling stations powered by renewable energy sources present a practical way to cut down lifecycle greenhouse gases and ease grid congestion. Nonetheless, most existing photovoltaic (PV)-based hydrogen production systems focus solely on electrical aspects, overlooking thermal energy flows and temperature effects that greatly impact PV and Electrolyzer performance. This study provides a thorough techno-economic evaluation of a hybrid PV/photovoltaic-thermal (PVT) green hydrogen system for refueling stations. The simulation framework models the combined electrical, thermal, and hydrogen subsystems under realistic conditions, incorporating rooftop PV/PVT collectors, battery storage, a water Electrolyzer, and hydrogen storage. Thermal energy from the PVT is used to pre-heat Electrolyzer feedwater, lowering electricity demand for hydrogen production and boosting PV efficiency via active cooling. Hydrogen production follows a demand-driven control strategy based on randomly generated stochastic daily refueling events. Three configurations are compared: (i) grid-only electrolysis, (ii) PV-only assisted electrolysis, and (iii) fully integrated PV/PVT-assisted electrolysis. The results show that the integrated PV/PVT setup significantly increases self-consumption, autarky rate, and overall efficiency, while lowering reliance on grid electricity and hydrogen production costs. Developed case studies highlight the economic feasibility and real-world viability of PV/PVT-assisted (decentralized) hydrogen refueling infrastructure. Full article

The rapidly growing concern over the hazardous impact of phthalates on the environment and public health has led to a critical need for alternative and environmentally friendly plastics. Plasticizers developed from natural materials represent one possible solution. This paper explores four types of renewable feedstocks (sorbitol/polyols, glycerin, cardanol from cashew nutshell liquid, and limonene from citrus peels) as sources for developing alternative plasticizer systems. Key areas explored include the type of feedstock utilized, the methods used for extracting or processing the feedstocks, the nature of the chemical modification processes (e.g., esterification, epoxidation, etherification, or reactive grafting) applied to generate the respective plasticizers, and the resultant physical and mechanical properties. The performance of each plasticizer system in polymers such as PVC, PLA, and polysaccharide-based bioplastics is evaluated, alongside the compatibility with biological tissues, toxicological properties, biodegradability, and chemical migration into food simulants. The feasibility of each family of plasticizers is also assessed from an economic perspective, including availability of the feedstocks, economies of scale associated with large-volume production, and competitive pricing relative to established petroleum-derived plasticizers. Overall, sorbitol/polyol and glycerin derivative families have reached a level of maturity that provides a good balance of processability, food-contact safety, and biodegradability. Cardanol-based systems provide an attractive option where aromatic functional groups and combined plasticization–stabilization effects are needed. Limonene-derived plasticizer systems appear promising for use in PLA, but their broader utility may be limited by volatility, strong odors, and susceptibility to oxidation. Common issues identified across all four families include chemical migration into food products, regulatory approval, and the need for detailed life-cycle assessments. Full article

Phosphorus is an essential and finite resource critical for global food production, yet its inefficient use and discharge from wastewater systems contribute to eutrophication and resource depletion. The transition from conventional wastewater treatment plants to water resource recovery facilities has intensified interest in technologies that enable phosphorus recovery within a circular economy framework. This review provides a critical and up-to-date synthesis of phosphorus recovery strategies from wastewater, with primary emphasis on struvite (MgNH₄PO₄·6H₂O) crystallization as one of the most mature and practically implemented recovery routes. The occurrence and chemical forms of phosphorus in wastewater streams are discussed alongside conventional approaches, such as enhanced biological phosphorus removal and chemical precipitation, in order to position struvite recovery within the broader phosphorus management landscape. In addition to struvite crystallization, selected competing and complementary recovery pathways, including electrochemical systems, biochar-assisted processes, and sludge ash recovery, are discussed to compare technological maturity, recovery potential, and practical applicability. Particular attention is given to reactor configurations, full-scale applications, and commercial technologies to assess operational reliability, recovery performance, and fertilizer product quality. Life-cycle assessment results and regulatory developments are also discussed to contextualize sustainability claims, technology selection, and market integration. The review identifies key technical and economic challenges, particularly regarding magnesium supply, competing ions, wastewater matrix effects, and the feasibility of mainstream application. Overall, controlled sidestream struvite crystallization appears to offer the most favorable balance between recovery efficiency, operational reliability, and fertilizer product quality under suitable plant conditions. Full article

Background: Adults with disabilities living in low-resource communities experience persistent inequities in access to healthcare, mental health services, and community participation. However, qualitative data capturing lived experiences in the Deep South remain limited. This study aimed to identify priority needs among adults with mobility disabilities residing in economically distressed communities near Birmingham, Alabama, to inform future telehealth programming. Methods: Fifteen adults (mean age = 60 ± 10 years), predominantly African American and female, completed semi-structured phone interviews exploring basic needs, neighborhood accessibility, health priorities, and perceived supports. Interviews were audio-recorded, transcribed verbatim, and analyzed using Braun and Clarke’s six-phase thematic analysis. Results: Five themes emerged: (1) seeking stability amid severe mental health strain and inadequate supports; (2) constrained food environments shaped by cost, location, and safety; (3) feeling forgotten: systemic neglect and restricted participation in community life; (4) physical health deprioritized by competing needs and structural barriers; and (5) remote support as a viable but unrealized option. Participants described how safety concerns, transportation barriers, and rising food costs constrained daily functioning, while unmet mental health needs compounded isolation. Despite widespread cardiometabolic disease, immediate needs related to mental health, food, and housing consistently superseded physical health. Mental health support was identified as the most feasible area for remote delivery, though poor awareness of available resources limited engagement with any service model. Conclusions: Findings demonstrate that disability-related disparities in low-resource communities are driven largely by structural and environmental factors rather than individual choice. Telehealth and mobile-based services may provide a feasible access strategy for mental health and supportive care in under-resourced settings, particularly when integrated with broader community supports. Addressing foundational needs is essential for advancing health equity among people with disabilities in the Southeast. Full article

Introduction: Cow’s milk protein allergy (CMPA) is one of the most common food allergies in early infancy and poses important clinical and economic challenges for affected children, their families, and healthcare systems. In Latin America, variability in diagnostic and therapeutic approaches remains substantial. Objective: We aim to systematically review the available evidence on CMPA, with emphasis on clinical characteristics, diagnosis, management, and economic impact, and to provide a complementary cost analysis of specialized formulas in the Colombian context. Methods: A systematic review was conducted according to PRISMA guidelines to synthesize current evidence on CMPA in pediatric populations. Studies published between 2010 and 2023 were screened using predefined eligibility criteria, and 46 studies were included in the qualitative synthesis. A complementary cost analysis was also performed to estimate the six-month costs associated with specialized infant formulas in Colombia, based on average age-specific formula consumption and standardized 2025 market prices. Results: The reviewed evidence confirms that CMPA is a heterogeneous condition with variable clinical manifestations and persistent diagnostic challenges, particularly in non-IgE-mediated presentations. Elimination of cow’s milk protein followed by oral food challenge remains the reference diagnostic approach. Breastfeeding with maternal dairy exclusion is consistently recommended as the preferred first-line strategy, whereas extensively hydrolyzed and amino-acid-based formulas are used when breastfeeding is not feasible or is insufficient. Estimated six-month costs ranged from COP 4,337,640 to COP 14,480,700 (approximately USD 1100–3600), depending on formula type. Conclusions: CMPA requires early recognition, careful clinical evaluation, individualized nutritional management, and improved access to effective and affordable treatment strategies. Full article

Asphalt pavements are essential to modern transport infrastructure but remain highly dependent on virgin aggregates and petroleum-based binders, resulting in high energy demand and significant greenhouse gas emissions. In response, research has advanced recycled-material solutions and low-temperature asphalt technologies. However, sustainability is still often inferred from isolated environmental indicators, without consistent consideration of mechanical durability or economic feasibility throughout the life cycle. This review provides an integrated synthesis of sustainable asphalt mixtures by jointly examining recycling strategies, temperature-reduction processes (warm-mix, half-warm-mix, and cold-mix asphalt technologies), and their combined applications through an integrated performance–cost–environment perspective. The literature reveals substantial methodological fragmentation, with limited harmonisation of functional units, system boundaries, and allocation rules, which constrains cross-study comparability. Evidence indicates that reclaimed asphalt, recycled concrete aggregates, and steel slag can maintain or improve rutting resistance, stiffness, and moisture durability while enabling material cost savings of approximately 5–68%. Temperature-reduction technologies further achieve significant energy and GHG reductions in the production phase (20–70%), with integrated recycling–temperature-reduction systems showing the most consistent combined benefits. Overall, this review demonstrates that asphalt sustainability cannot be established through single-dimensional assessments but requires harmonised life-cycle frameworks that explicitly link environmental gains to mechanical performance, durability, and economic viability. Full article

Prenatal whole-genome sequencing (WGS) is a comprehensive genetic test for fetal anomalies, enabling simultaneous detection of aneuploidies, copy number variants (CNVs), single-nucleotide variants (SNVs), small insertions/deletions, structural variants, and regions of absence of heterozygosity. However, its clinical performance, optimal sequencing strategies, and implementation challenges remain incompletely defined. We conducted a narrative review of PubMed-indexed studies (1966–December 2025) evaluating prenatal WGS in fetuses with structural anomalies. Across 29 studies, diagnostic yield ranged from approximately 20% to 40%, influenced by phenotype complexity, sequencing depth, and study design. Low-coverage WGS (≤5×) reliably detected large chromosomal abnormalities with a performance comparable to chromosomal microarray analysis. Moderate-coverage WGS (20–40×) additionally enabled detection of SNVs and structural variants, providing up to 30% incremental diagnostic yield after uninformative standard testing. Turnaround times were typically 14–21 days. Higher sequencing depth increases detection of variants of uncertain significance (0.6% to 35.7%) and secondary/incidental findings (1.6–30.8%). Prenatal WGS offers meaningful diagnostic value but requires careful patient selection, multidisciplinary expertise, and structured pre- and post-test genetic counseling to ensure responsible integration into routine clinical practice, with careful consideration of clinical benefit and economic feasibility. Full article

Complex engineering optimization problems are typically characterized by high dimensionality, multimodality, and strong constraints, posing significant challenges to traditional swarm intelligence algorithms in terms of convergence speed, solution accuracy, and robustness. The Catch Fish Optimization Algorithm (CFOA), a recently proposed swarm-based metaheuristic, exhibits promising global search capability; however, it still suffers from deficiencies in search direction stability, elite solution utilization, and exploitation performance in the later stages of optimization. To address these limitations, this paper proposes an Improved Catch Fish Optimization Algorithm, named Elite-Driven Reinforced Catch Fish Optimization Algorithm (EDR-CFOA). On the basis of the original CFOA framework, EDR-CFOA integrates three complementary elite-based enhancement strategies: an elite-enhanced search strategy, an elite differential evolution strategy, and an elite random local search strategy. Through a multi-level elite-guided mechanism, these strategies collaboratively improve the reliability of search directions, strengthen solution-space recombination, and enhance fine-grained exploitation of high-quality solutions, thereby significantly improving the overall optimization performance of the algorithm. The proposed EDR-CFOA is systematically evaluated on the CEC2020 and CEC2022 benchmark test suites under 10-dimensional and 20-dimensional settings and is compared with eight classical and recently developed high-performance metaheuristic algorithms. The Friedman mean ranking results demonstrate that EDR-CFOA achieves the lowest average rank in all four test scenarios (CEC2020: 1.30 for 10D and 2.20 for 20D; CEC2022: 1.17 for 10D and 1.08 for 20D), consistently ranking first overall and significantly outperforming the competing algorithms. Furthermore, Wilcoxon rank-sum tests confirm that EDR-CFOA exhibits statistically significant superiority on the majority of benchmark functions. In addition, EDR-CFOA is applied to the economic optimal scheduling problem of a grid-connected microgrid and several typical constrained engineering design problems, where experimental results verify its feasibility, robustness, and practical engineering applicability. Comprehensive numerical experiments and real-world engineering case studies indicate that EDR-CFOA is a highly effective swarm intelligence algorithm featuring high solution accuracy, strong stability, and excellent generalization capability, making it well suited for complex engineering optimization problems. Full article

This paper presents a technical and economic feasibility analysis of a microgrid based on an existing traction substation supplying a 3 kV DC railway network. The study is based on real 15-min electricity consumption measurements and applies an engineering-oriented methodology to assess the integration of distributed energy resources, including wind turbines, photovoltaic generation, and a battery energy storage system. The analysis focuses on component sizing, land-use constraints, and investment efficiency under conservative and transparent assumptions. The results demonstrate that traction substation-based microgrids are technically feasible under realistic environmental and spatial conditions. The conducted variant analysis reveals a clear trade-off between the number of installed wind turbines and the required photovoltaic installation area, highlighting the importance of generation redundancy and source diversification for infrastructure-critical applications. The energy storage system is designed as a reliability-oriented backup component, ensuring continuity of supply during primary power outages rather than serving as an optimization or arbitrage asset. From an economic perspective, the obtained investment efficiency indicators indicate that the proposed microgrid configuration can achieve acceptable performance for capital-intensive infrastructure assets, particularly when supported by appropriate financing conditions and policy instruments. Overall, the study confirms that traction substation-based microgrids constitute a viable solution for enhancing energy supply diversification, resilience, and decarbonization of railway power systems, while providing a transparent framework for early-stage decision-making. Full article

This study develops a high-resolution techno-economic optimization framework to assess the feasibility of green hydrogen production in 100% renewable, off-grid systems. Utilizing 5-minute interval meteorological data aggregated to hourly resolution spanning 5 years across seven geographically diverse sites, this study co-optimizes the integration of hybrid wind–solar power generation, flexible electrolyzer operation, and a multi-timescale energy storage portfolio, incorporating short-duration, long-duration, and seasonal storage. On the generation side, a hybrid wind–solar configuration achieves the lowest levelized cost of hydrogen (LCOH). For energy storage, no single storage technology can economically address demand fluctuations across short-term, medium-term, long-term, and seasonal timescales. Instead, a coordinated multi-timescale storage strategy incorporating energy-to-energy mechanisms reduces the LCOH by up to 40%. Increasing hydrogen tank capacity and enabling flexible electrolyzer operation further lowers the LCOH. Significant regional resource variability leads to substantial cost disparities, with the most favorable region achieving a low LCOH of $2.45/kg. Several regions are projected to reach the $3/kg target by 2030, while areas with limited resources require large-scale hydrogen storage to ensure supply reliability. These results represent deterministic lower-bound estimates under perfect foresight; accounting for forecast uncertainty and real-world operational constraints would likely increase actual costs by approximately 5–15%. Full article

Textile wastewater remains one of the most challenging industrial effluents to remediate due to its intense and persistent coloration, high organic load, elevated salinity, and fluctuating pH and the presence of recalcitrant dye structures and auxiliary chemicals. Conventional physicochemical and biological treatments frequently achieve incomplete removal, generate secondary wastes, or fail under high-salt and toxic dye matrices. Advanced oxidation processes (AOPs) provide molecular-level degradation via reactive oxygen species (ROS), yet their deployment is often constrained by narrow operating windows, catalyst instability, chemical/energy demand, and scale-up limitations. In this context, metal–organic frameworks (MOFs) have emerged as tunable porous catalytic platforms that integrate adsorption and oxidation within a single architecture through controllable metal nodes, functional linkers, and engineered pore environments. This critical review reimagines textile effluent treatment through the lens of MOF-based hybrid catalysts, synthesizing progress across Fenton/photo-Fenton catalysis, photocatalytic MOFs, persulfate activation, and MOF-derived/composite systems. Mechanistic pathways are discussed by linking pollutant enrichment, cyclic redox reactions, charge-transfer processes, and ROS-driven degradation toward mineralization, with emphasis on the distinction between rapid decolorization and true organic removal. A critical comparison highlights how hybridization improves charge transport, stability, and catalyst recovery, while persistent gaps remain in hydrolytic robustness, metal leaching control, intermediate toxicity assessment, real-wastewater validation, continuous-flow reactor integration, and techno-economic feasibility. Finally, the review outlines actionable research directions, including water-stable and defect-engineered MOFs, immobilized and structured catalysts, solar-driven operation, standardized performance metrics, and life-cycle-informed design, to accelerate translation toward scalable and sustainable textile wastewater remediation. By bridging material chemistry with reactor-level feasibility and sustainability assessment, this review provides an implementation-oriented perspective for next-generation textile wastewater treatment. Full article

This study explores the drivers of economic growth in the BRICS economies—Brazil, Russia, India, China, and South Africa—over the period 1994–2024, focusing on the roles of digital infrastructure and financial development. Using a balanced panel, we examine how internet connectivity and access to credit shape growth, both independently and in combination, while accounting for gross fixed capital formation, urbanization, and government expenditure. Given the macro-panel structure, which exhibits heteroskedasticity, serial correlation, and cross-sectional dependence, we employ robust estimation techniques, including Driscoll–Kraay standard errors (DKSE), Feasible Generalized Least Squares (FGLS), and Panel-Corrected Standard Errors (PCSE). To capture potential heterogeneity across different growth scenarios, we further apply the Method of Moments Quantile Regression (MMQR) as a robustness check. Our findings show that both internet connectivity and financial development consistently promote economic growth across all main specifications. Importantly, the interaction between these two factors is also significant, indicating that the benefits of digital infrastructure are stronger in countries with deeper financial systems, and vice versa. Among the control variables, capital accumulation and government spending positively contribute to growth, while urbanization exhibits a negative association, reflecting the structural challenges of rapid urban expansion. MMQR results confirm that these relationships hold across low-, medium-, and high-growth periods, highlighting their broad relevance. These findings highlight the synergistic role of technological and financial development and underscore the importance of integrated policies to sustain long-term, inclusive growth in the BRICS economies. This study suggests that policymakers should adopt integrated strategies that enhance digital connectivity, deepen financial development, and support productive public investment to sustain inclusive and resilient economic growth. Full article