Search Results (24,086)

Electric vehicles are an important carrier for achieving energy savings and emission reductions in the transportation sector. As the decision-making core of the powertrain, the energy management strategy is responsible for power allocation and energy scheduling and directly determines vehicle economy, power-source lifetime, and overall performance. Model predictive control can handle multiple constraints and objectives within a prediction horizon and realize online closed-loop decision-making via receding-horizon optimization and has become an important research direction for energy management of electric vehicles. This paper presents the basic principles and typical modeling framework of model predictive control and reviews its research progress in hybrid electric vehicle energy management. The related studies are categorized and comparatively analyzed from three perspectives—prediction methods, solution strategies, and optimization objectives—and the characteristics of different approaches are summarized. The review shows that model predictive control has advantages in multi-objective trade-offs and adaptation to time-varying operating conditions. However, practical implementation still faces significant barriers, including prediction uncertainty and computational complexity. Finally, the challenges and future directions of model-predictive-control-based energy management strategies are discussed. Full article

This study focuses on modelling the spatial dependence of airborne particle contamination using Response Surface Methodology (RSM), with consideration of its implications for technical cleanliness and employee health. The analysis is based on two measurement campaigns conducted in an industrial production hall, where particle concentrations were recorded across multiple size fractions using a TROTEC PC220 device. The results demonstrate that RSM effectively captures nonlinear relationships and spatial gradients, enabling the identification of local extrema and contamination hotspots. Statistical analysis confirmed a significant influence of spatial coordinates on particle concentration across all fractions, with finer particles exhibiting stronger spatial dependence, consistent with aerosol behaviour in indoor environments. Quadratic model terms revealed stable hotspot regions persisting even after corrective measures, indicating persistent contamination sources or structural factors. Residual analysis suggested additional unmodeled local sources or transport mechanisms. Based on the integration of RSM and multi-fraction analysis, a mechanistic contamination model (source–transport–receptor framework with deposition processes) is proposed, linking particle behaviour with surface contamination and potential human exposure. The approach enables data-driven, localised contamination control and supports optimisation of technical cleanliness and occupational health conditions. Full article

Expanded polystyrene litter in marine environments harbors diverse and distinct microbial communities, referred to as the plastisphere. This study aimed to investigate the monthly dynamics of bacterial and potentially pathogenic bacterial (PPB) communities on expanded polystyrene over one year. Vibrio species dominated the PPB community, cooccurring at consistently higher abundances on expanded polystyrene than in the surrounding seawater, particularly under higher temperatures and low dissolved organic carbon (DOC) levels. At a temperature threshold of 16 °C, the abundance of zoonotic species, such as Vibrio parahaemolyticus and Vibrio alginolyticus, increased significantly. Some psychrotrophic Vibrio spp. were detected under moderately eutrophic conditions, suggesting that expanded polystyrene may also serve as a dispersal vector facilitating their transport to more favorable habitats. Multivariate analyses, including partial least squares path modeling, revealed temperature and DOC as the primary environmental factors influencing PPB community composition. However, environmental responses varied by taxonomic groups, with different preferences observed under varying eutrophic conditions. In conclusion, these findings demonstrate that expanded polystyrene litter supports a selective and environmentally responsive bacterial population, highlighting the potential role of plastic debris in promoting pathogenic bacterial persistence and spread in marine ecosystems, particularly under conditions associated with climate change, including warming and eutrophication. Full article

With the advancement of the “dual carbon” goals, the electric vehicle market has experienced explosive growth, and user review mining has become key data support for industrial quality improvement and low-carbon transportation transition. Addressing the limitations of existing sentiment classification methods in long-distance feature capture, cross-sentence semantic association, and emotional feature focus, this study proposes a BERT-Bi-xLSTM-Attention fusion model: BERT pre-trained semantic representation extracts deep contextual information, Bi-xLSTM models long-range dependency relationships, and the Attention mechanism locates sentiment-critical markers. Based on multi-platform review data from Chinese Autohome, Yiche, and China Quality Inspection Network, experiments show that the model achieves Accuracy, Recall, Precision, and F1 values of 0.9323, 0.9326, 0.9321, and 0.9328, significantly outperforming baseline models. A “sentiment-topic” fusion analysis framework is constructed, identifying five positive themes and four negative themes, revealing the dual emotional characteristics of range, driving experience, and smart features. Temporal analysis finds that negative attention to intelligent system reliability has continued to rise from 2021 to 2024, becoming an emerging user pain point. Combined with the above findings, it is recommended that consumers comprehensively evaluate multi-attribute experiences when purchasing; manufacturers prioritize optimizing user-concerned attributes; and policymakers improve industrial standards and regulatory mechanisms. This promotes high-quality development of electric vehicles, contributes to the realization of carbon neutrality goals in the transportation sector, and facilitates sustainable transportation development. Full article

Manganese (Mn) is essential for plants, but its fluctuating soil availability—deficiency in alkaline soils and toxicity in acidic soils—challenges crop productivity. Breakthroughs in Arabidopsis have uncovered Ca²⁺ signaling as a key integrator of Mn status. This review synthesizes these discoveries into an emerging Arabidopsis-centered framework. Under Mn deficiency, sustained Ca²⁺ oscillations activate CPK21/23, which phosphorylate the importer NRAMP1 at Thr498 to enhance Mn uptake. Under Mn excess, a rapid Ca²⁺ transient triggers a multi-layered cascade: CPK4/5/6/11 activates MTP8 (Ser31/32) for vacuolar sequestration, while CBL2/3–CIPK3/9/26 sequentially suppresses MTP8 (Ser35, peak 24 h) and MTP11 (Ser194/201, peak 36 h)—a multi-tiered “brake” system. Concurrently, CBL1/9–CIPK23 induces NRAMP1 endocytosis (Ser20/22) to limit Mn uptake. The IRT1 transporter directly binds cytoplasmic Mn²⁺ and triggers its own degradation via CIPK23, thereby converging with Ca²⁺ signaling. The BRI1–CNGC12 module generates Mn-induced Ca²⁺ signals. By organizing current knowledge into a hierarchical framework, this review provides a working model for future research and outlines translational opportunities for engineering Mn-resilient crops. Full article

Metal homeostasis, which coordinates the influx and efflux of essential elements such as iron (Fe) and manganese (Mn) in chloroplasts, is essential for optimum photosynthesis, especially in metal-accumulating plants. Brassica juncea (Indian mustard) is a metal-tolerant species with a strong metal accumulation capacity, making it a suitable model for studying transition metal homeostasis. In this study, we identified two efflux transporters, BjYSL6.1 and BjYSL6.4, that localize in the endomembrane system of Schizosaccharomyces pombe and interact with the chloroplast Mn influx transporter BjNRAMP4.1 at the plasma membrane and within the chloroplasts. Bimolecular fluorescence complementation and split-ubiquitin yeast two-hybrid assays confirmed specific protein–protein interactions among these transporters, as well as with the membrane-bound thioredoxin BjHCF164, a known regulator of photosynthetic electron transport. Gene expression studies revealed that BjNRAMP4.1 and BjYSL6 isoforms are inversely regulated under Fe and Mn stress conditions, with BjNRAMP4.1 being strongly induced under deficiency, whereas BjYSL6.1 and BjYSL6.4 are downregulated. These findings suggest that a coordinated network involving BjNRAMP4.1, BjYSL6s, and BjHCF164 modulates metal influx and efflux at the chloroplast and plasma membrane interfaces, thereby maintaining metal homeostasis, which is critical for photosynthetic efficiency in B. juncea. Full article

To address the issue that static strategies, such as frequent closure or fixed-time opening, in emergency lane management on freeways struggle to adapt to dynamic traffic demands, a control method for Dynamic Time-Division Multiplexing of Emergency Lanes (DTMEL) is proposed. Based on real-time changes in the traffic status of social vehicles and emergency vehicles, the method designs a dynamic time slice division strategy to achieve dynamic response in road right allocation and ensure the priority of emergency vehicle. By constructing a dynamic spatial slice model that integrates driver decision-making behavior and different car-truck ratios, it provides a quantitative design basis for lane usage under the heterogeneity of social vehicles. Simulation experimental results show that in different car-truck ratios, the average speed of social vehicles under the DTMEL control method is 8.16–15.02% higher than that under the frequent closure strategy of emergency lanes and 2.15–3.29% higher than that under the fully open strategy control. In addition, compared to the fully opening strategy, the traffic capacity under DTMEL strategy control has increased by about 6.59–8.08%. The proposed method reduced the delay rate of emergency vehicles, verifying its feasibility in improving freeway operation efficiency and ensuring the priority of emergency vehicles. Full article

Maglev trains, as an emerging transportation modality, have attracted significant attention with respect to their safety and ride comfort. In this study, the improved R index and τ-distance index are incorporated into the evaluation framework, and a data-driven comprehensive evaluation method for the suspension system of medium- and low-speed maglev trains is developed based on a Gaussian mixture model, enabling a comprehensive assessment of suspension gap stability and operational smoothness. Experimental results demonstrate that the proposed method can accurately identify various motion modes of the suspension system and provide effective early warnings of abnormal operational states. Compared with conventional error integral performance indices, this method exhibits superior anomaly detection sensitivity and enhanced interpretability of the results. Computational efficiency analysis indicates that the proposed method meets the requirements for online real-time monitoring. Under different operating conditions, the GMM trained on normal operational data maintains stable evaluation performance, demonstrating favorable robustness. Full article

Maintaining asphalt pavements requires substantial quantities of materials and energy, which significantly contribute to greenhouse gas emissions in the road infrastructure sector. This study quantified the carbon dioxide equivalent (CO₂e) emissions associated with a maintenance and rehabilitation plan for an asphalt pavement using a simplified life-cycle perspective integrated with the Highway Development and Management Model (HDM-4). The methodology combined HDM-4 to define a 35-year intervention plan (2022–2057) with CO₂e emission factors for three quantified components: material production, transportation, and construction machinery operation. The approach was applied to a 7.8 km section of the Mexicali–San Felipe highway in Baja California, Mexico. The results indicate that the intervention plan generated approximately 2483.9 t CO₂e over the 35-year analysis period. Reconstruction was the most carbon-intensive activity, accounting for 1890 t CO₂e, while milling and overlay generated 292.15 t CO₂e per direction. Material extraction and production were the dominant sources of emissions, contributing about 70% of the total emissions in milling and overlay and 60% in reconstruction; in the latter case, transportation also represented a substantial share (35%) due to long haul distances. These findings show that the proposed approach can identify the most emission-intensive activities and processes within pavement maintenance plans and provide quantitative environmental criteria to support more sustainable road management decisions. Full article

Mitochondrial reactive oxygen species (ROS) play a central role in cardiac ischemia/reperfusion injury, heart failure, and arrhythmogenesis, while also serving essential signaling functions under physiological conditions. Among the eleven identified mitochondrial ROS-producing sites, complexes I and III are considered the major contributors, particularly under conditions of impaired electron flow. However, much of the existing knowledge comes from rodent models or cultured cells and is often assumed to apply to humans. Here, ROS production from complexes I and III was measured directly in human myocardial and skeletal muscle biopsies and compared with corresponding rat tissues under identical experimental conditions. Hydrogen peroxide generation was quantified using Amplex UltraRed, with simultaneous monitoring of mitochondrial respiration using a Clark-type oxygen electrode. Across all examined mechanisms—reverse and forward electron transport at complex I and the ubiquinol oxidation site of complex III, rat tissues produced more ROS than human tissues, consistent with their higher respiratory rates. However, the dominant ROS-producing sites differed: in rats, complex III was the primary source, whereas in human tissues the highest ROS production occurred during reverse electron transport at complex I. When normalized to respiration, human tissues showed relatively greater ROS generation at complex I but markedly lower production at complex III. These direct measurements of mitochondrial ROS production in human myocardium provide new insight into cardiac redox physiology and may explain the limited clinical translation of cardioprotective strategies targeting mitochondrial ROS production, such as interventions aimed at modulating reperfusion injury or preconditioning. Full article

Background: Tuberculosis (TB) remains a major public health challenge globally, particularly in high-burden countries such as South Africa. Treatment interruption is a critical barrier to effective TB control, contributing to poor treatment outcomes, increased risk of multidrug-resistant tuberculosis (MDR-TB), and continued community transmission. Understanding the determinants of treatment interruption in rural healthcare settings is essential for strengthening TB programme implementation. Methods: This qualitative study explored the factors influencing TB treatment interruption from the perspectives of professional nurses working in primary healthcare facilities in the Nyandeni Subdistrict, Eastern Cape, South Africa. Semi-structured interviews were conducted with nurses involved in TB programme implementation. Data were analysed using thematic analysis following the six-phase approach described by Braun and Clarke. Descriptive statistical analyses were also used to summarize participant characteristics, including age and years of nursing experience. Conceptual frameworks were developed to illustrate the multilevel determinants of TB treatment interruption. Results: Participants had a mean age of 40.6 years and an average of 14.2 years of nursing experience, reflecting a workforce with substantial clinical exposure to TB management. Thematic analysis identified multiple interconnected determinants of treatment interruption. Key barriers included poverty, food insecurity, transport costs, long distances to healthcare facilities, limited family support, and challenges related to patient tracing. These factors interact across structural, community, health system, and interpersonal levels to influence patient adherence behaviour. Conceptual models developed from the findings illustrate the complex pathways through which these determinants contribute to treatment interruption and programme-level consequences such as reduced treatment success and increased risk of MDR-TB. Conclusions: TB treatment interruption in rural settings is driven by multilevel socioeconomic and health system determinants rather than individual patient behaviour alone. Strengthening community health worker programmes, improving patient tracing systems, addressing socioeconomic barriers, and enhancing community-based support mechanisms are essential for improving treatment adherence. Integrated, multisectoral interventions are required to strengthen TB programme outcomes in rural high-burden settings. Full article

Background. Ethanol distribution in the energy supply chain can be maximized by solving a Location Routing Problem (LRP). Manifold LRP (MLRP) expands on the classic domain assumptions of LRP to manifold surfaces, and it can be applied to profit maximization in ethanol supply chains. Methods. In this work, a hybrid MLRP (H-MLRP) is introduced as a new mixed integer nonlinear programming NP-hard problem assuming discrete facility allocation that requires a mix of truck and train transportation for ethanol distribution from the facility to its customers. Ethanol supply chain profit can be maximized by solving a stochastic nonlinear integer programming problem (SNLP) using ethanol raw materials, production quantity, logistics, railcar shipments, and transit times as the decision variables. H-MLRP and SNLP are combined as a two-stage optimization methodology to design a biofuel energy distribution system for making optimal decisions to maximize ethanol profit. Results. A case study demonstrated the effectiveness of the proposed method on the relocation of an ethanol producer that is currently located in North Dakota (ND) to Oklahoma (OK). In this case study, customer demand destinations and suppliers of raw materials are located in different regions of the United States. Conclusions. The results indicate a good use of the new model for decision-making. Full article

This study analyzes the econometric correlation between resale prices and CO₂ emissions of 832 bulk carriers sold from 2018 to 2025. It uses a cross-sectional hedonic pricing model to look at how environmental performance affects the value of sub-types of dry bulk vessels (Capesize, Panamax, Supramax, and Handysize) and age groups (0–5, 6–10, 11–15, and 16+). The findings show that emission efficiency has a statistically significant and negative effect on second-hand prices for all models. Results indicate that higher emission intensity (higher technical efficiency values) reduces vessel values. The magnitude of this effect varies by ship type and age group. Based on the Technical Efficiency Indicator (TEI), refers to Energy Efficiency Existing Ship Index (EEXI) or Energy Efficiency Design Index (EEDI) coefficients, the Supramax segment appears to be the most price-sensitive, followed by Panamax, Capesize, and Handysize. Age has a consistently negative and significant effect on prices, while vessel size positively affects asset values. Further analysis shows that TEI levels increase with vessel age, whereas they decrease with larger vessel size and more recent measurement years. These results are consistent with tightening regulatory pressures under the International Maritime Organization (IMO) frameworks. The economic implications of IMO’s environmental regulations on carbon intensity indicate that compliance with regulation standards creates a measurable price differential in the second-hand ship market. These findings have important implications for shipowners’ investment strategies, regulatory policy design, and the decarbonization path of the maritime sector. This study contributes to the growing research on environmental economics in maritime transport by providing empirical evidence on how carbon regulations translate into tangible asset value impacts. Full article

Situated within Saudi Arabia’s Vision 2030 transformation agenda, this study examines the performance implications of sustainable logistics practices (SLPs) and the mediating role of Management Information Systems (MIS). Although achieving a “double bottom line” is a central premise of sustainable supply chain management, its realization in state-driven emerging economies remains unclear. Drawing on the Natural Resource-Based View and Stakeholder Theory, a structural equation model is tested using survey data from 372 logistics and supply chain professionals in Saudi Arabia. The model assesses the effects of Green Transportation, Sustainable Packaging, and Sustainable Waste Management on Environmental Sustainability and Economic Performance. The results reveal a clear “Economic Performance paradox.” While all three practices significantly enhance Environmental Sustainability, only Sustainable Waste Management directly improves Economic Performance. Moreover, Green MIS significantly mediates the relationship between sustainable logistics practices and Environmental Sustainability but shows no direct or mediating effect on Economic Performance. This indicates a prevailing compliance-oriented use of MIS, where firms prioritize environmental monitoring and reporting over operational optimization. This study demonstrates that the double bottom line is not automatic, but contingent on practice type and institutional context. By providing firm-level evidence from Saudi Arabia, the study extends sustainable logistics and information systems research and offers contextually grounded insights for managers and policymakers. Full article

Introduction: Efficient geothermal energy extraction has the potential to significantly alleviate the shortage of fossil energy, but low extraction efficiency and an insufficiently understood extraction mechanism remain key bottlenecks hindering its large-scale deployment. Method: This study develops a fluid–solid coupled numerical model based on the intrinsic physical properties of geological reservoirs to systematically analyze the energy extraction characteristics of geothermal systems. Simultaneously, the effects of key geological factors on fluid flow behavior within geothermal reservoirs are investigated. Furthermore, molecular dynamics simulations are employed to elucidate the microscopic mechanisms by which driving fluids facilitate geothermal energy extraction. Results: The results demonstrate that the thermo-hydraulic–mechanical (THM) numerical model was validated through a comparison with benchmark data reported in previous studies, exhibiting a high degree of agreement with geothermal extraction performance. The model further confirms that heat transport in the geothermal reservoir is characterized by a pronounced “tongue-in” isotherm pattern during the extraction process. Discussion: Lower initial temperatures of the driving fluid lead to more rapid geothermal energy extraction compared with higher initial temperatures, and the “tongue-in” phenomenon becomes increasingly pronounced as the initial injection temperature decreases. Moreover, increased injection pressure significantly enhances geothermal energy extraction efficiency; however, reduced pressure differentials markedly suppress the development of the “tongue-in” pattern and decrease reservoir permeability. In addition, water used as a heat-driving fluid achieves higher thermal extraction efficiency than water, while simultaneously exerting a stronger moderating effect on the permeability evolution of geothermal reservoirs. Conclusions: The simulation results obtained from the thermo-hydraulic-mechanical (THM) numerical model provide fundamental data to support the efficient development of geothermal reservoirs, while the associated analyses offer valuable insights into the selection of appropriate driving fluids for reservoirs with distinct geological characteristics. Full article