Search Results (10,524)

Sustainable public transport in South Africa has become a policy priority over the past few decades. Safety is recognised as a fundamental component of this agenda. In many cities, public transport systems are often characterised by poor safety standards, which undermine ridership and public confidence. In the City of Polokwane, despite the successful recent completion of the first phase of Leeto La Polokwane bus system, an Intelligent Transportation System designed for sustainable transport management, the safety performance of the system and its subsequent influence on travel behaviour remain underexplored. This study addresses this gap by investigating the safety performance of the Leeto La Polokwane Phase 1A and its relationship with commuters’ sustainable travel mode choice. Commuter surveys (n = 344), field observations, and actual ridership data were used to collect data. Principal component analysis extracted two key factors (commuter safety and crime prevention), which together explained 63.14% of the total variance in commuters’ perceptions of safety. Commuters reported a neutral perception of commuter safety (mean = 4.03) and a negative perception of crime prevention (mean = 3.90). Multinomial logistic regression revealed that commuters’ perceptions of safety, particularly concerns related to crime prevention, were statistically significant predictors of sustainable travel mode choice. Multiple linear regression further showed that operational continuity and system maturation were positively associated with ridership growth, with operating days (β = 0.307, p = 0.044) and time in operation (β = 0.670, p < 0.001) emerging as significant predictors. Although taxi protests (β = −0.036, p = 0.804) and school holidays (β = −0.199, p = 0.181) were negatively correlated with ridership. The study concludes that safety is a critical determinant of sustainable public transport use that extends beyond the onboard environment to include the entire commuter journey. To improve public transport safety requires a holistic strategy that integrates safe pedestrian infrastructure, effective crime prevention, operational reliability, and strengthened institutional collaboration. Full article

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

Walking tourism is increasingly supported by a wide range of digital technologies that are crucial for mitigating environmental impacts and promoting sustainable territorial development, yet their adoption remains fragmented and rarely interpreted within a unified infrastructure perspective. While systemic infrastructure perspectives are well-established in smart city and transport literature, existing studies on walking trails still tend to focus on individual tools or user-oriented applications. Drawing upon broader smart mobility concepts, this paper proposes a system-level framework, the SmartTrail Framework (STF), for the classification, functional interpretation and integration assessment of digital technologies in walking trail infrastructures. The framework is conceived as a transferable analytical and operational instrument applicable both to academic literature and to real-world trail systems, supporting infrastructure assessment, planning and digital maturity evaluation. Following an initial bibliometric analysis of a broader Scopus dataset comprising 1697 records, a structured literature review of 253 publications was conducted to operationalise and illustrate the framework through the systematic classification of digital technologies, the mapping of functional requirements, and the assessment of Integration Levels (IL). The STF integrates three analytical dimensions: a technology domain taxonomy (six categories), a functional requirement model (five infrastructure functions) and an IL scheme (IL0–IL3) that characterises the degree of systemic coherence among digital components. The results reveal a critical functional imbalance in current digitalisation: while user-oriented navigation and information services are widely adopted, backend infrastructure functions, particularly safety and operational logistics, remain severely underdeveloped, keeping most trail systems trapped in low-integration configurations. Applied to real-world trail systems, the framework enables the identification of architectural gaps, the prioritisation of integration investments and the definition of development pathways towards intelligent trail ecosystems. The paper aims to contribute to field research by providing a structured interpretative framework for understanding digital technologies as infrastructural components of walking trails. This supports a shift from tool-based thinking to system-based infrastructure design and offers practical implications for planners, managers and policymakers involved in the development of smart, resilient and environmentally sustainable trail infrastructures. Full article

Capsicum chinense Jacq. is an economically important chili pepper species characterized by a high capsaicinoid content, which contributes to its growing relevance in the food, pharmaceutical, and agricultural sectors. Although the chemistry and biological properties of capsaicinoids have been extensively investigated, available information remains fragmented, and no review has comprehensively integrated their botanical aspects, chemistry, biosynthesis, and insecticidal potential. This review provides an integrated overview of the major capsaicinoids of C. chinense, particularly capsaicin, dihydrocapsaicin, and nordihydrocapsaicin, focusing on their chemical composition, biosynthetic pathways, structure–activity relationships, and insecticidal properties and mechanisms. Particular emphasis is placed on the relationship between chemical structure and biological activity, as well as on the role of capsaicinoids as natural defense compounds and their insecticidal potential. Current evidence indicates that capsaicinoids exhibit insecticidal, repellent, and antifeedant activities through multiple mechanisms, including membrane disruption, oxidative stress induction, and interference with ion transport and neuronal signaling. Despite these promising findings, further field validation, methodological standardization, and optimized formulations are required. Overall, this review integrates the currently dispersed evidence on C. chinense capsaicinoids and highlights their potential as bioactive compounds for the development of more sustainable botanical insecticides. Full article

Sustainable rural cultural tourism requires effective approaches to improving the visibility, accessibility, and decision feasibility of dispersed cultural resources, particularly in destinations where service information is fragmented across online and offline channels and tourists face substantial uncertainty in coordinating transport, accommodation, and cultural experiences. This study examines how artificial intelligence (AI) agents can support the sustainable digital transformation of rural cultural tourism by alleviating information asymmetry, releasing latent tourism demand, and facilitating calibrated human–machine trust. Drawing on human–machine trust theory and the Stimulus–Organism–Response framework, this study conceptualizes AI agent functionality through three dimensions: AI Information Quality (AIQ), Information Extensibility (IE), and AI Planning Autonomy (APA). Travel Planning Risk Awareness (TPRA), Human–Machine Trust (HMT), Planning Satisfaction (PS), Rural Cultural Tourism Attractiveness (RCTA), and Rural Cultural Tourism Intention (RCTI) are further incorporated into an integrated model comprising four pathways: information empowerment, autonomy–risk awareness tension, trust boundary, and demand release. Using the Ctrip AI Travel Assistant as the research context, 413 valid questionnaire responses were analyzed through a hybrid Structural Equation Modeling–Artificial Neural Network approach. The results support 12 of the 14 hypotheses. AIQ significantly influences IE (β = 0.530), PS (β = 0.304), and HMT (β = 0.380). HMT functions as a central mechanism connecting AI empowerment with tourism decision-making and exerts the strongest effect on RCTA (β = 0.485), reaching 100% normalized importance in the corresponding ANN model. TPRA positively affects HMT (β = 0.262), indicating that risk awareness can facilitate rational and calibrated trust rather than simply inhibiting AI acceptance. RCTA (β = 0.281) and PS (β = 0.218) jointly promote RCTI through the complementary mechanisms of destination pull and planning push. The findings demonstrate that AI agents can contribute to the sustainable development of rural cultural tourism by improving information accessibility, strengthening responsible human–AI collaboration, and transforming fragmented cultural resources into credible and actionable travel-planning options. This study provides implications for sustainable destination marketing, responsible AI travel-service design, rural revitalization, and the long-term development of rural cultural tourism, while clarifying trust as a psychological gate in AI empowerment. Full article

Electric vehicles are rapidly reshaping global transportation, emerging as a central pillar of efforts to cut greenhouse gas emissions and end dependence on fossil fuels. This review provides a critical and integrative synthesis of recent advances in electric vehicle technologies, focusing on three interconnected domains: battery innovations, charging strategies, and grid integration. Progress in high-energy-density lithium-ion chemistries, emerging solid-state and sodium-ion batteries, and advanced battery management systems is examined with respect to their implications for driving range, safety, and lifecycle sustainability. Charging infrastructure developments, including fast and ultra-fast charging, wireless charging, and battery-swapping networks, are evaluated in terms of technical feasibility, grid impact, and user adoption. The evolving role of EVs in enhancing energy system flexibility is further analyzed through vehicle-to-grid (V2G) and smart grid interactions, with emphasis on control algorithms, grid stability, and renewable energy integration. By critically analyzing recent literature, this review identifies key technological, infrastructural, and system-level challenges, as well as emerging research directions that require coordinated optimization across domains. The insights presented aim to guide future research, technology development, and policy design toward the realization of a resilient, efficient, and scalable electric mobility ecosystem. Full article

Urban passenger hubs, such as airports and railway stations, generate concentrated last-mile demand from arriving passengers to spatially dispersed urban destinations. Fluctuating passenger arrivals and changing vehicle availability can create a mismatch between accepted demand and available service capacity. This paper aims to coordinate zone-level pricing and vehicle dispatching, so that fare-responsive accepted demand can be better aligned with available vehicle resources, while balancing operator financial performance and service reliability. Under the zonal pricing scheme, the transit operator determines a quoted zone-level fare for each service zone at every decision epoch. Newly arriving service requests accept the service when the quoted fare does not exceed their maximum acceptable per-passenger fare, after which the fare is committed. A rolling-horizon optimization model jointly determines zone-level fares and dispatching plans as request states and vehicle states evolve over time. The fare discretization property reduces the continuous pricing decision to a finite candidate zone-level fare selection problem, and a customized Rolling-Horizon Adaptive Large Neighborhood Search (RH-ALNS) algorithm is developed to solve the resulting problem efficiently. Case studies based on Nanjingnan Railway Station in Nanjing, China, demonstrate the operational value of coordinating pricing and dispatching decisions. In the baseline case, the proposed method achieves a passenger service rate of 76.75%, an accepted-passenger fulfillment rate of 96.07%, and an operating surplus of 1.145 CNY per passenger-kilometer. Holding the RH-ALNS dispatching method fixed, dynamic zonal pricing increases the objective value by 4.39%, the operating surplus per passenger-kilometer by 5.46%, and accepted-passenger fulfillment by 3.63 percentage points relative to fixed zonal fares. The findings indicate that coordinating dynamic zonal pricing with vehicle dispatching can better align accepted demand with available vehicle resources and provide practical guidance for designing reliable, resource-efficient, and financially balanced hub-based demand-responsive last-mile transit services. Full article

Climate change increasingly endangers precious indigenous sheep germplasm resources distributed across diverse Chinese landscapes, and systematically decoding their polygenic climate-adaptive genetic mechanisms is essential for targeted breed conservation and long-term sustainable pastoral production. Whole-genome resequencing data from 93 individuals covering six representative local sheep breeds were analyzed in this work. After filtering highly collinear climate variables, three mature landscape genomic approaches were jointly applied to identify environment-linked gene variants, while two predictive metrics across ten CMIP6 future climate scenarios quantified each breed’s long-term adaptive risks. Six temperature- and water-related environmental factors jointly drove sheep population genetic differentiation, with temperature fluctuation indices showing markedly stronger explanatory power. Detected adaptive genes were significantly enriched in ion transport, energy metabolism and cellular stress response pathways. Future projections indicated western breeds (Bayinbuluke, Cele Black, Xiahe) face severe maladaptation risks under high-emission SSP370 scenarios by 2100, whereas central and eastern breeds possess much broader climate tolerance. This study systematically reveals the core genomic basis of ovine climate adaptation and quantifies distinct breed-specific climate vulnerability, providing solid reliable theoretical support for precision germplasm conservation and selective breeding of climate-resilient sheep varieties. Full article

In the aviation sector, spare parts management plays a critical role in mitigating aircraft downtime caused by stockouts while supporting the efficient and sustainable use of resources in maintenance operations. It involves a range of inventory control methodologies combined with spare parts demand forecasting, which is particularly challenging due to the stochastic nature of component failures. Beyond ensuring operational readiness, effective spare parts management can contribute to sustainability by reducing excess inventory, minimizing waste from obsolete components, and optimizing storage and transportation requirements within Maintenance, Repair, and Overhaul (MRO) systems. Accurate demand forecasting has the potential to enhance both supply chain resilience and environmental performance, as it may contribute to the mitigation of overproduction, stockouts, unnecessary and emergency transportation, and resource waste. This study provides a systematic review of recent approaches to spare parts forecasting and infers their contribution to sustainability in the aviation industry. A systematic review was conducted, including the identification, screening, and analysis of studies published between 2010 and 2025. The review of 15 selected studies highlights the growing relevance of aligning demand forecasting with spare parts management, enabling more efficient inventory decisions that improve aircraft availability while supporting resource efficiency and sustainability objectives in MRO operations. This study consolidates current knowledge on sustainable spare parts management practices in aviation and identifies key areas for future research in aviation supply chains. Full article

Biomass-derived nanoengineered carbon materials have emerged as key platforms in environmental technologies due to their high surface area, electrical conductivity, chemical stability, and sustainable synthetic route starting from renewable feedstock. This broad family comprises dimensionally nanoscale materials, such as carbon dots, carbon nanofibers, and graphene-based structures, as well as biochars, hydrochars, activated carbons, and related porous carbonaceous materials whose pore architecture, surface chemistry, or defects are deliberately engineered at the nanometer scale. Beyond their traditional role as passive supports, these materials can actively regulate adsorption phenomena, charge transport, and catalytic microenvironments through precise control of heteroatom doping, graphitic domains, and hierarchical porosity. Among current environmental priorities, carbon dioxide (CO₂) management represents one of the most pressing challenges. Biomass-derived nanocarbons offer tunable adsorption sites for selective CO₂ capture while simultaneously serving as active matrices for catalytic conversion. Tailored doped-carbon frameworks can stabilize key reaction intermediates, suppress competing pathways such as hydrogen evolution, and promote selective transformation into fuels and high-value chemicals. In addition, these materials are excellent hosts for atomically dispersed metals, dual-site catalysts, and semiconductor hybrids used in electrochemical and photocatalytic CO₂ reduction. By combining renewable sourcing with nanoscale control of reactivity, carbon materials create a bridge between environmental remediation and carbon valorization. This review critically examines recent progress in biomass-derived nanoengineered carbon materials for integrated CO₂ capture and conversion, with emphasis on structure-property-performance relationships, mechanistic roles, scalability, and sustainability. Particular attention is also devoted to catalytic conversion and electrochemical CO₂ sensing, where carbon-based and hybrid interfaces enable the transduction of CO₂ recognition into measurable electrical responses. These materials represent a promising yet underexplored pathway toward circular carbon management and the development of next-generation low-carbon chemical technologies. Full article

Against the backdrop of high-density Asian cities shifting from production- to consumption-oriented spaces, commercial pedestrian streets are key to urban public life and vitality. This study selects six major commercial pedestrian streets in Chongqing and employs natural language processing (NLP) and importance–performance analysis (IPA) methods to construct a four-dimensional evaluation framework (spatial, commercial, cultural, location/facility). It analyzes public perception and experience based on user-generated content (UGC). Findings show that: (1) Significant differences across dimensions form three development types: cultural identity, functional hub, and distinctive growth, reflecting structural bottlenecks in transitioning from single- to multi-functional spaces. (2) IPA identifies “business formats,” “cultural activities,” and “consumption experience” as priorities for improvement, while “commercial atmosphere” and “transportation conditions” are current strengths to maintain. (3) Sentiment analysis reveals that negative perceptions focus on basic functions and sense of place, whereas positive sentiments relate to cultural expression and spatial esthetics, highlighting the role of cultural soft power and visual design in street appeal. This study reveals public perception patterns via big data analysis, offering empirical support for the refined renewal, cultural preservation, and sustainable management of commercial pedestrian streets in high-density Asian cities. Full article

Electromobility is central to urban decarbonisation, but its charging infrastructure must be sized under substantial uncertainty about user behaviour that varies across stations, time of day and user type. This study couples a hierarchical Bayesian model with an agent-based, discrete-event simulation of a charging network. It is fitted by Markov chain Monte Carlo to the public ACN-Data dataset (13,694 sessions across 52 stations; 16,468 user requests), with partial pooling across stations. Posterior parameters drive a 24 h simulation of 500 vehicles across nine configurations and 30 to 180 slots. Service success rises from 19% to 81% and mean waiting falls from 110 to 62 min; long workplace dwell times limit turnover, so capacity rather than energy binds. TOPSIS with a paired bootstrap selects 160 slots under balanced weighting, but that optimum holds for only a tenth of the weight simplex, and the recommendation spans 140–180 slots. Spreading the arrival peak at fixed hardware raises service from 67% to 83%, matching a 29% expansion. Spatially explicit assignment costs three percentage points when stations are evenly sited, and six when clustered. The framework makes the cost of over-provisioning explicit and preference-conditional rather than naming a single optimum, giving a reproducible basis for sustainable capacity planning. Full article

The transition toward a sustainable hydrogen economy demands cost-effective, durable, and highly active catalysts that span the entire H₂ value chain from green production through storage and transport to end-use conversion. Carbon-based catalytic materials have emerged as a uniquely versatile platform, offering tunable electronic structure, abundant defect- and edge-derived active sites, hierarchical porosity, chemical robustness, and compatibility with both metal-free and single-atom architectures. This review provides a comprehensive overview of advanced carbon-based catalysts designed for the hydrogen economy. We begin with the fundamentals of heteroatom doping, defect and curvature engineering, and M–N₄/M–N₃ coordination environments that govern binding of hydrogen-relevant intermediates (ΔG_H*, ΔG_OH*, ΔG_O*). Three application pillars are then systematically examined: (i) hydrogen production through HER and OER across PEMWE, AEMWE, AWE, and SOEC platforms, including emerging seawater and biomass-/waste-coupled electrolysis; (ii) hydrogen storage and chemical carriers, encompassing physisorption on porous carbons and catalytic (de)hydrogenation of liquid organic hydrogen carriers, ammonia, and formic acid; and (iii) hydrogen utilization in PEMFCs, AEMFCs, direct liquid fuel cells, and hydrogen-coupled CO₂ and N₂ reduction. Particular emphasis is placed on structure–activity descriptors, operando mechanistic probes, device-level benchmarking from rotating-disk electrodes to membrane-electrode assemblies, and techno-economic considerations including the levelized cost of hydrogen. We conclude by highlighting critical challenges—carbon corrosion, PGM-free durability, and scalable synthesis—and outline future directions that integrate AI-accelerated discovery, atomic-precision synthesis, and biomass-derived circular-economy carbons for next-generation hydrogen technologies. Full article

Feed efficiency traits are increasingly important in pig production for improving profitability and environmental sustainability. Understanding their genetic basis is crucial for uncovering underlying biological mechanisms and informing selection strategies. In this study, we analyzed residual feed intake (RFI), feed conversion ratio (FCR), and average daily feed intake (ADFI) in 201 animals. Three separate Bayesian GWASs were conducted using 29,844 SNPs in a case–control design, with the lowest and highest 15% of the phenotypic distribution selected as controls and cases (N = 30 per group), respectively, for each trait. The results confirmed the polygenic nature of the traits, identifying 4 SNPs for RFI on Sus scrofa chromosomes (SSC) 3, 13, and 15 with high posterior probability for the direction of their effects; 4 SNPs for FCR on SSC 8, 14, and 17; and 8 SNPs for ADFI on SSC 1, 2, 6, 8, and 11. A candidate gene search identified 41 potential genes involved in diverse biological processes, including feed efficiency, intestinal development, tissue remodeling and integrity, nutrient transport and absorption, metabolic homeostasis, cellular signaling, energy sensing, and neurological regulation. These genes formed a highly interconnected network, highlighting the complexity of feed efficiency and the interplay among multiple physiological, metabolic, and regulatory pathways. Full article

Brassinosteroids (BRs) are essential steroidal phytohormones that regulate plant growth, development, and responses to environmental stresses. Recent studies have demonstrated the important roles of BRs in enhancing plant tolerance to abiotic stresses, including drought, salinity, temperature extremes, heavy metal toxicity, and oxidative stress, as well as biotic stresses caused by pathogens and herbivores. This review summarizes current advances in BR biosynthesis, metabolism, transport, and signaling pathways, focusing on key components that mediate stress adaptation. We discuss the physiological and molecular mechanisms through which BRs improve stress tolerance, including regulation of antioxidant defense, ion homeostasis, osmotic adjustment, and stress-responsive gene expression. Particular attention is given to the extensive cross talk between BRs and other phytohormones, such as abscisic acid, jasmonic acid, salicylic acid, ethylene, auxin, and gibberellins, which enables plants to balance growth and defense under adverse conditions. Furthermore, we highlighted the potential applications of BRs in crop improvement through exogenous treatments, genetic engineering, and genome-editing approaches. However, the effectiveness of BR-based strategies is highly dependent on crop species, developmental stage, stress type, BR concentration, application method, and environmental conditions. In addition, excessive BR accumulation or application may result in undesirable growth responses, and further multi-location field validation is required before widespread agricultural implementation. Finally, we discuss emerging research trends, current knowledge gaps, and future perspectives for exploring BR signaling to develop climate-resilient crops. Overall, BRs represent promising targets for improving crop stress resilience; however, optimizing BR-mediated strategies and validating their long-term performance under diverse field conditions will be essential for their successful application in sustainable agriculture. Full article