Search Results (13,389)

Greenhouse vegetable cultivation in tropical regions is often affected by high temperature, unstable humidity, and irrigation management problems. This study presents a pilot-scale case study of Green Oak lettuce cultivation using an IoT-based sensor monitoring and automated irrigation control system in Phra Nakhon Si Ayutthaya Province, Thailand. The system used AM2315C, BH1750, NPK, and flow sensors connected to ESP32. Data were transmitted to the ThingsBoard platform for real-time environmental monitoring and irrigation control. The greenhouse temperature averaged 33.21 ± 3.61 °C, while relative humidity averaged 71.55 ± 9.66%. The average daytime light intensity was 16,976 ± 409 lux. Nitrogen (N), phosphorus (P), and potassium (K) concentrations remained within ranges of 62.42–74.57, 76.46–84.30, and 71.46–79.30 mg/kg, respectively. Economic evaluation demonstrated favorable feasibility, with a water use efficiency (WUE) of 0.63 kg/L, return on investment (ROI) of 40%, benefit–cost ratio (BCR) of 1.6, and payback period of approximately 2.5 years. The developed system demonstrates potential for supporting sustainable greenhouse agriculture and contributes to SDG 2, SDG 6, SDG 12, and SDG 13 under tropical agricultural conditions. Full article

Street food is a fundamental part of the diet for millions of people, especially in Mexico, standing out for its accessibility, cost, and connection to culinary culture. Street food represents a practical alternative for the population and economic benefits for those who sell it. However, its preparation and sale can involve microbiological health hazards if proper hygiene conditions and practices are not applied during the handling, storage, and sale of products. Studies in Mexico have shown the presence of pathogenic microorganisms in street food, including coliform bacteria, Salmonella sp., Escherichia coli, Staphylococcus aureus, and Listeria monocytogenes, among others, capable of causing foodborne illnesses. Therefore, this narrative review provides information available in various databases on street food, foodborne illnesses, causative agents, contaminants, and prevention measures. This study focuses on the Mexican context, including the socioeconomic relevance of these foods, microbiological contaminant hazards, prevention, and the regulatory framework. Although regulations and actions are in place for these foods, challenges remain related to food hygiene education for food handlers, microbiological surveillance of food, and the wide variety of products and sales outlets. Strengthening collaboration among authorities, academia, vendors, and consumers is essential to promote the availability of safe food and protect public health. Full article

Intelligence tests predict academic achievement, but their use in educational decision-making remains contested. We develop a decision-analytic framework, centered on a staged decision architecture, to determine when, for whom, and for which educational decisions intelligence testing adds value beyond grades, achievement measures, and contextual evidence. Drawing on psychometric scholarship, a generative account of achievement, and illustrative decision scenarios, we distinguish incremental validity from decision utility. Incremental validity refers to the predictive gain obtained by adding cognitive measures, whereas decision utility refers to the net benefit of using those measures once base rates, capacity constraints, error costs, fairness, and legitimacy are considered. We use the framework to identify conditions in which intelligence testing is expected to be most informative, especially educational transitions, contexts with uneven opportunity, and discrepancy-focused decisions such as underachievement or twice-exceptionality. We also specify minimum conditions for responsible use, including intended use, construct representation, reliability or precision, measurement comparability, predictive bias checks, and monitoring of distributional impact. We conclude that intelligence testing should be used conditionally and sequentially, with achievement and contextual indicators used first and cognitive assessment added only when it is likely to change the decision. Full article

Minimally invasive spine surgery (MISS) has progressively transformed the management of spinal disorders by reducing soft-tissue disruption, perioperative morbidity, and recovery time while maintaining clinical outcomes comparable to conventional open techniques. Beyond its technical evolution, MISS has increasingly assumed a central role in the treatment of bone-related spinal conditions, including vertebral fractures, degenerative instability, metastatic disease, and osteoporosis-associated pathology. This narrative review provides a comprehensive overview of the evolution of MISS with a specific focus on its interaction with vertebral bone biology, implant stability, and fusion processes. A structured literature search of the PubMed/MEDLINE database was conducted, including English-language studies published between 1980 and June 2025 addressing MISS techniques, enabling technologies, and bone-related clinical outcomes. Current evidence suggests that MISS may preserve paraspinal vascularization and soft tissue integrity, potentially supporting bone healing and fusion, although high-quality comparative data remain limited. The effectiveness of MISS in osteoporotic and metastatic vertebral disease is closely linked to bone quality, implant anchorage, and biomechanical considerations, particularly in the context of pedicle screw fixation and interbody support. Emerging technologies—including navigation, robotics, and artificial intelligence—may enhance accuracy in implant placement and reduce bone-related complications, but robust evidence of long-term benefit is still lacking. Despite its advantages, MISS presents important limitations, including a steep learning curve, increased costs, and uncertain superiority in terms of fusion rates and long-term biomechanical stability. Future research should prioritize high-quality comparative studies focusing on bone healing, implant integration, and patient-specific factors such as bone density. MISS should therefore be interpreted not only as a surgical paradigm shift but as an evolving strategy for optimizing outcomes in bone-related spinal disorders. Full article

The growing demand for energy-efficient urban rail transit has led to the increasing deployment of reversible substations (RS) in traction power supply systems. These substations, equipped with bidirectional converter devices (BCDs), involve high initial costs and complex parameter optimization challenges. This paper presents a coordinated optimization method for BCD-equipped RS using a two-layer model. In the upper layer, the model determines the siting of RS and the capacity of BCD to minimize life-cycle cost (LCC). In the lower layer, it adjusts the control parameters of BCDs to reduce annual operating cost. An improved salp swarm algorithm (ISSA), incorporating Tent chaotic mapping and Levy flight, is developed to solve the model. A case study based on an 18.2 km subway line shows that the optimized configuration reduces overall cost by 5.12% and electricity cost by 10.53% compared with a conventional rectifier system. Moreover, it achieves a 1.19% reduction in electricity cost over a system with fixed control parameters, while maintaining rail potential and catenary voltage within safe limits. These findings demonstrate that the proposed method strikes an effective balance between initial investment and long-term operational benefits, contributing to improved energy efficiency and economic performance. Full article

Sand stabilization techniques include mechanical, biological, and chemical methods. Integrated systems combine these approaches in varying proportions. This study tested a sand control system developed by the Kuwait Institute for Scientific Research using a 1/100-scale model in an aeolian sand transport wind tunnel. Experiments employed boundary layer pressure measurements and salti-phone sand transport quantification to examine effects of wind speed, fence height, and tree configuration. Boundary layer velocity was primarily affected by fan speed, with fence height, tree configuration, and measurement location playing minor roles. Sand transport correlated directly with wind speed. Fence height showed inverse proportionality to centerline velocity but direct proportionality off-center velocity. The optimal configuration, i.e., C6 tree spacing (the central row was 35 m from the upwind fence, and subsequent rows were at 5 m and 10 m intervals, using Tamarix aphylla and Prosopis juliflora and with an H2 fence height (1.8 m)), achieved a 68.9% mean sand transport reduction. The graduated vegetation density provided superior momentum absorption versus uniform spacing, while a 1.8 m fence height balanced particle capture against flow blockage. A preliminary economic analysis demonstrates favorable cost–benefit ratios with 2–3-year payback periods. System costs ($185,000/km) are substantially lower than sand removal expenses, providing validated design guidelines for Kuwait and similar arid environments. Full article

Addressing the challenge of power supply stability caused by the intermittent nature of photovoltaic power generation in off-grid microgrids, this study uses a commercial park in Wuhan as a case study and optimizes the capacity configuration of a photovoltaic–storage–hydrogen fuel cell hybrid microgrid system based on HOMER Pro software. First, a topology of the off-grid microgrid is constructed, comprising photovoltaic (PV), lithium-ion batteries, hydrogen fuel cells, and a diesel generator as backup. The power output characteristics, efficiency curves, and life-cycle cost models of each component are accurately established. On this basis, two typical operation strategies, namely Load Following (LF) and Cycle Charging (CC), are proposed and compared. The influence of different strategies on the optimal capacity configuration and operational economics is systematically analyzed, and the Cycle Charging strategy is identified as the optimal operation strategy for this scenario. Subsequently, a multi-scenario capacity optimization design is further conducted based on the optimal operation strategy. The minimization of net present cost (NPC) is taken as the primary objective, while multiple evaluation indicators such as renewable fraction (RF), levelized cost of electricity (LCOE), energy storage cycle life degradation, and system redundancy rate are comprehensively considered. The results show that, while ensuring 100% power supply reliability, the proposed model reduces the net present cost (NPC) by approximately 14.4% compared with the conventional PV-storage scheme. The renewable fraction (RF) reaches 95.8%, while the reliance on lithium-ion battery capacity is significantly reduced (battery capacity configuration decreased by 24.3%). This effectively extends the energy storage lifespan and enhances the overall economic and environmental benefits. The results provide a theoretical basis and technical reference for the planning and design of off-grid microgrids with high penetration of renewable energy. Full article

The sustainable development of all economic sectors, including transport, requires decarbonization approaches that reduce greenhouse-gas emissions while preserving operational viability. This article develops a segment-based preliminary multi-criteria framework for evaluating the rational applicability of decarbonization technologies to commercial fishing vessels and demonstrates it for existing medium-to-large trawlers. The central premise is that decarbonization technologies cannot be ranked universally for the whole fishing fleet because vessel type, fishing gear, operating cycle, autonomy, onboard energy demand, and port dependence strongly affect practical applicability. Ten alternatives are assessed: sustainable drop-in biofuels/biodiesel/HVO (Hydrotreated Vegetable Oil), LNG/BioLNG/LBG, methanol, hydrogen fuel cells, ammonia, hybrid systems, operational measures, hull-form or hydrodynamic modifications, waste heat recovery and wind-assisted propulsion. Seven benefit-type criteria are combined using trawler-specific Rank-Order Centroid weights, Simple Additive Weighting, and a dynamic rationality extension for 2026, 2030, 2040, and 2050. The 2026 baseline results place operational measures and sustainable drop-in biofuel/HVO pathways in the leading practical group, while hydrogen and ammonia remain weak because of storage, safety, infrastructure, cost, and integration constraints. By 2050, a mixed long-term group emerges where HVO, LNG/BioLNG/LBG, methanol, ammonia, and hydrogen are all relevant, with no single dominant alternative. The framework supports early-stage screening before vessel-specific LCA, LCCA, CFD, safety assessment, and retrofit or newbuild design. Although this methodological approach was demonstrated for existing medium-to-large trawlers, the authors believe that it can be adapted for retrofit cases, other fishing vessel segments, and other types of seagoing vessels. Full article

The integration of distributed energy resources (DERs) has enhanced the operational flexibility and complexity of smart building energy management, which is crucial to urban sustainable development. However, the limitations of strategy applicability across different environments and lengthy development cycles pose significant challenges for energy management. To address this, this paper proposes a transferred multi-thread deep reinforcement learning (TMDRL) framework for the cross-domain energy management of smart buildings. Firstly, a source-domain heterogeneous exploration architecture based on multi-thread deep reinforcement learning (DRL) is proposed. A transferable source-domain knowledge base is constructed to enhance the generalization ability of pre-trained strategies. Secondly, a decoupled double-critic optimization mechanism is designed to mitigate policy evaluation bias during cross-domain transfer. Finally, simulations using real-world datasets from different times and areas are conducted. The results show that compared to A3C, DDPG, and SAC, the proposed TMDRL framework reduces total costs by 32.77%, 18.14%, and 37.24%, while improving convergence efficiency by 29.55%, 22.89%, and 32.84%, respectively. The reduction in total cost and improvement in convergence efficiency demonstrate that the proposed TMDRL framework effectively saves energy and enhances the utilization of renewable energy, proving the sustainable benefits of smart building energy management across domains. Full article

The growing adoption of electric vehicles (EVs) and the rapid expansion of public charging infrastructure pose new challenges and opportunities for energy systems, particularly in urban settings. This study presents an optimization-based evaluation of different EV charging strategies including direct charging, average-based methods, smart charging, and vehicle-to-grid (V2G) at public parking lots using real-world charging session data. This data-driven model is set to optimize the public EV charging of vehicles in Gothenburg, without sacrificing on the energy requirement while minimizing charging costs for the operators. Results indicate that direct charging scenarios lead to significantly higher peak loads (up to 1286 kW) and costs (around 370 k€), highlighting their inefficiency under unmanaged operation. In contrast, smart charging reduces peak loads by approximately 47% and overall costs by around 74%, showcasing its potential for cost-effective grid-friendly operation. Two different V2G scenarios were tested based on the impact of discharged power accounted for in peak costs, though it enables energy discharge back to the grid, the benefits remain modest under current assumptions due to tight operational constraints and limited incentives. The study emphasizes the value of smart optimization and appropriate market design in enhancing the flexibility and cost efficiency of public EV charging systems. Full article

The development of sustainable, high-performance construction materials is essential for enhancing the resilience and economic efficiency of infrastructure in seismically active regions. Although nanomaterials can improve concrete performance, the combined influence of hybrid nanomaterial systems—particularly those sourced from agricultural and industrial waste streams—on early-age behavior, building-scale seismic response, and cost efficiency remains insufficiently quantified. This study presents an integrated experimental and numerical assessment of high early-strength concrete (HESC) incorporating nano-silica (NS), nano-clay (NCl), and cellulose nanofibers (NCels). Experimental results indicate that the optimized mixture (HESC-O) achieved a 3.15-fold increase in 28-day compressive strength, a 93.3% reduction in water penetration depth, and an 88.7% decrease in corrosion rate compared with conventional concrete. Finite element analyses of low-, mid-, and high-rise building models showed that HESC-O increased lateral stiffness and reduced story drift by up to 30% compared to normal concrete (NC); improvements over reference HESC (HESC-R) were of 5–10% and lateral displacement differed by 25–40%, with the most pronounced improvements observed in taller structures. Despite a higher unit material cost, the cost–benefit analysis demonstrated substantial net savings, particularly for high-rise buildings, primarily due to a 52% reduction in column cross-sectional areas and the associated increase in usable floor space. The findings support the performance-based selection of nano-engineered concrete that balances structural performance, economic value, and sustainability. Full article

This study systematically explores the underlying mechanisms of collaborative innovation driving the green transformation of traditional energy enterprises. Existing research primarily focuses on enterprise scale and overall competitiveness, rarely delving into these specific collaborative pathways. Furthermore, studies employing evolutionary game theory to analyze the tripartite relationship among the government, traditional energy, and emerging technology enterprises remain fragmented, failing to fully capture the dynamic mechanisms of multi-stakeholder strategic choices. To bridge these gaps, this paper constructs a tripartite evolutionary game model incorporating coordination costs and the benefit distribution ratio to explore their influence mechanisms. Replicator dynamics equations are employed to identify stable cooperation conditions, overcoming traditional two-party framework constraints. Additionally, MATLAB R2024b numerical simulations validate the theoretical findings. The results reveal two evolutionarily stable equilibrium points. First, higher initial willingness among participants accelerates the system’s evolution toward a stable cooperative state. Second, coordination costs induced by information asymmetry act as a core bottleneck that deters participation and risks collaborative collapse. Third, targeted government incentives and a rational benefit distribution ratio directly determine cooperation willingness; notably, enterprises adopt collaborative strategies only when this ratio falls between 0.27 and 0.69. Fourth, fair and transparent supervision is crucial for mitigating trust deficits and distribution disputes. Ultimately, scientifically designing incentives, optimizing benefit structures, promoting information sharing, and establishing robust supervision effectively facilitate a sustainable tripartite collaborative innovation pattern. Full article

The transition toward smart grids and Industry 4.0 demands a fundamental shift in maintenance strategies, as manual inspection methods are increasingly being supplanted by automated monitoring systems. Among the advanced technologies for smart inspection, infrared imaging has advantages including non-contact operation, intuitive visualization, and predictive capabilities, which has become a cornerstone for autonomous inspection of critical power infrastructure. This review provides recent advancements in infrared imaging, with a specific focus on automated power system inspection. The discussion starts with an overview of the fundamental principles and system architectures, emphasizing the pivotal role of infrared detectors. A detailed analysis traces the technological evolution from traditional photon detectors to current uncooled microbolometers, and critically assesses emerging low-dimensional materials. The analysis highlights inherent performance trade-offs among sensitivity, operating temperature, and fabrication cost. Subsequently, the review explores advanced signal processing algorithms, such as real-time non-uniformity correction and adaptive noise suppression, which are typically implemented on FPGA platforms. Advanced optical configurations—encompassing computational imaging, lensless designs, and scattering suppression methods—are also discussed, demonstrating how their convergence enhances image fidelity and operational reliability in complex field environments. Representative application paradigms are surveyed, including drone-based transmission line inspections, patrol robots in substations, and fault diagnosis in photovoltaic plants; for each, operational efficacy and economic benefits are assessed. Despite considerable progress, several challenges persist, notably the performance–stability–cost trilemma in novel detector development, the substantial computational demands of end-to-end optimized systems, and a lack of standardization. Finally, the review outlines future research directions, such as high-performance uncooled arrays, AI-driven co-design of optics and algorithms, and the development of standardized, low-cost, intelligent inspection platforms. Full article

Large inland waterway infrastructure projects are increasingly exposed to supply disruptions, logistics uncertainty, carbon-control pressure, and dredged-material management challenges. Although resilient supplier selection, closed-loop supply chains, and ESG-oriented optimization have been widely studied, existing models rarely integrate resilient sourcing, hub configuration, forward material supply, reverse dredged-material resourceization, and social externality penalties within a unified maritime infrastructure decision framework. To fill this gap, this study proposes an ESG-endogenous closed-loop supply-chain optimization model for construction of an inland waterway navigation hub. The model jointly optimizes resilient supplier selection, transshipment/resourceization hub activation, equipment deployment, forward material flows, and reverse dredged-material flows. Three objectives are considered: minimizing economic cost, minimizing carbon emissions, and maximizing net social benefit. In particular, a social benefit and ecological-debt penalty function is introduced to quantify the transition from beneficial reuse to disposal-related negative externalities. NSGA-II is adopted as a multi-objective solver, with parameter calibration, convergence analysis, and benchmark comparison used to evaluate computational performance. The Pinglu Canal project is used as a case study. The results produce 14 Pareto-optimal solutions and show that the lowest-cost and lowest-emission configurations may still generate negative social benefits. A low-cost ESG transition region around 197.3–197.8 million CNY is identified, where limited additional investment can activate resourceization pathways and shift the system from ecological debt to near-saturated social benefit. These findings suggest that sustainable infrastructure planning should move beyond isolated cost or carbon minimization and instead identify balanced supplier–hub–equipment–flow configurations that jointly support resilience, circularity, and ESG performance. Full article

Cell outages are conventionally mitigated through cell outage compensation, but national roaming frameworks offer alternative solutions with extra cost and energy efficiency benefits. Most national roaming studies evaluate performance over aggregate subscriber populations with limited focus on suburban environments or explicit resource block partitioning for protection of primary users’ quality of service (QoS). We propose a Resource-Constrained Temporary Roaming (RCTR) scheme that grants roaming users access to only a fraction C of the resources of visited operators during a cell outage to protect the QoS of primary users. System-level simulations in a suburban macrocell compare the blocking probability, throughput, and spectral efficiency of the RCTR scheme with two baseline schemes. Simulation results show the RCTR scheme balances relief for roaming users with protection of primary users’ QoS better than the baseline schemes and reduces 100% blocking probability under a No Roaming approach to below 10% at low traffic loads. For the aggregate population, performance metrics improve with increasing C, but exhibit diminishing returns as C approaches one. While primary users can tolerate high C values at low traffic loads, their QoS worsens with increasing C at higher loads. Hence, QoS protection depends on the appropriate selection of C across traffic intensities. Full article