Search Results (210)

For the last few decades, the use of High-Speed Trains (HSTs) has been growing rapidly in various parts of the world. Despite rapid global expansion, many HST projects fail due to demand overestimation and cost overruns. This study analyzes factors influencing HST demand in Indonesia, aiming to identify impactful determinants from user perspectives. Employing a quantitative cross-sectional approach, this research utilized questionnaires distributed to users of different modes of transportation in the Jakarta–Bandung area, including trains, buses, travel services, and private cars. Structural Equation Modeling (SEM) via Lisrel software was used to analyze the data. The results indicate that Transit-Oriented Developments (TOD) and new urban areas significantly increase HST demand by facilitating urban growth and development. Additionally, supporting infrastructure and external factors such as road accessibility, parking availability, shuttle services, and environmental integration are pivotal in shaping commuter preferences. Although factors such as safety, comfort, and reliability are important, they alone may not be adequate to persuade consumers to use high-speed trains for their travel. Full article

Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article

The sustainable development of eco-tourism is significantly influenced by multiple conditions within spatiotemporally continuous geographic scenarios. However, existing evaluations of the development value of eco-tourism resources (Eco-TRDVs) are non-spatial and do not sensitively represent their complex relationships. This study proposed a GIS approach for evaluating regional Eco-TRDVs by mapping the complex interconnections with spatial distances. Inherent and external conditions for evaluating Eco-TRDVs were classified under three indicators and digitized using GIS and remote sensing technologies. Then, the analytic hierarchy process and GIS cost distance analysis were introduced to define the initial values and cumulate Eco-TRDVs with distances. Taking the Taihang Honggu National Forest Park, China, as the case area, the Eco-TRDVs over the entire area in 2017 and 2020 were mapped. The results present a continuous spatial variability of Eco-TRDVs and comprehensively reflect the complex interconnections of constraint elements with spatial distances. The evaluation is sensitive to the intrinsic value of poles, as evidenced by the high development values and high-density distribution of their contours. Source additions improve the evaluation considerably, with transportation networks having a greater impact than economic development zones and urban elements. Furthermore, aggravated fragmentation of the price flow field increases spatial heterogeneity. The development value shows a negative linear correlation with distance. The proposed approach handles the spatially oriented relationships of the multi-conditions, and supports future planning and monitoring of spatial-temporal changes in eco-tourism development. Full article

Driven by the rapid expansion of e-commerce in China, there is a growing demand for high-efficiency, sustainability-oriented logistics solutions in rural regions, particularly for the time-sensitive distribution of perishable agricultural commodities. Traditional logistics systems face considerable challenges in these geographically complex regions due to limited infrastructure and extended travel distances. To address these issues, this study proposes an intelligent cooperative delivery system that integrates automated drones with conventional trucks, aiming to enhance both operational efficiency and environmental sustainability. A mixed-integer linear programming (MILP) model is developed to account for the diverse terrain characteristics of rural China, including forest, lake, and mountain regions. To optimize distribution strategies, the model incorporates an improved Fuzzy C-Means (FCM) algorithm combined with a hybrid genetic simulated annealing algorithm. The performance of three transportation modes, namely truck-only, drone-only, and truck–drone integrated delivery, was evaluated and compared. Sustainability-related externalities, such as carbon emission costs and delivery delay penalties, are quantitatively integrated into the total transportation cost objective function. Simulation results indicate that the cooperative delivery model is especially effective in lake regions, significantly reducing overall costs while improving environmental performance and service quality. This research offers practical insights into the development of sustainable intelligent transportation systems tailored to the unique challenges of rural logistics. Full article

With the advent of Autonomous Vehicles (AV) technology, extensive research around the design of on-demand mobility systems powered by such vehicles is performed. An important part of these studies consists in the evaluation of the economic impact of such systems for involved stakeholders. In this work, a cost–benefit analysis (CBA) is applied to the introduction of AV services in Paris-Saclay, an intercommunity, south of Paris, simulated through MATSim, an agent-based model capable of capturing complex travel behaviors and dynamic traffic interactions. AVs would be implemented as a feeder service, first- and last-mile service to public transit, allowing intermodal trips for travelers. The system is designed to target the challenges of public transport accessibility in periurban areas and high private car use, which the AV feeder service is designed to mitigate. To our knowledge, this study is one of the first CBA analyses of an intermodal AV system relying on an agent-based simulation. The introduction of AV in a periurban environment would generate more pressure on the road network (0.8% to 1.7% increase in VKT for all modes, and significant congestion around train stations) but would improve traveler utilities. The utility gains from the new AV users benefiting from a more comfortable mode offsets the longer travel times from private car users. A Stop-Based routing service generates less congestion than a Door-to-Door routing service, but the access/egress time counterbalances this gain. Finally, in a periurban environment where on-demand AV feeder service would be added to reduce the access and egress cost of public transit, the social impact would be nuanced for travelers (over 99% of gains captured by the 10% of most benefiting agents), but externality would increase. This would benefit some travelers but would also involve additional congestion. In that case, a Stop-Based routing on a constrained network (e.g., existing bus network) significantly improves economic viability and reduces infrastructure costs and would be less impacting than a Door-to-Door service. Full article

Eventing is an Olympic equestrian discipline comprising dressage, cross-country, and show jumping, with the cross-country phase imposing the greatest physical demands on horses. This study presents a composite model to estimate energy expenditure during the cross-country phase, integrating physiological data (heart rate-derived $V{O}_2$ and lactate-based anaerobic estimates) with external workload indicators (GPS-derived speed, elevation, and course complexity). Model development was based on 691 rides from 256 horses across 232 events at 2-star to 5-star competition levels. The analysis showed that terrain, speed variability, and acceleration, largely shaped by course design, significantly affect energy expenditure. Aerobic and anaerobic contributions to power output varied by speed, format, and competition level. The model explained 29% of variance in power output and 91% when accounting for random effects, demonstrating the influence of both external and individual factors. Short-format events exhibited higher anaerobic contributions than long-format events. While the competition level had a modest effect, it reflected increasing technical difficulty and jump size. These findings underline the importance of incorporating both physiological responses and course characteristics in energy assessments. The model supports more targeted conditioning, enhances performance monitoring, and contributes to improved equine welfare by providing a more accurate understanding of workload in cross-country competitions. Full article

High-Speed Rail (HSR) has long been proposed as a transformative infrastructure project for Australia; yet, despite multiple feasibility studies and significant government expenditure, it remains unrealized. This study investigates the key barriers preventing HSR implementation. To achieve this, a novel mixed-methods approach that triangulates a comprehensive literature review, in-depth expert interviews, and broad stakeholder survey was employed. The Analytic Hierarchy Process (AHP) was used to quantify the relative importance of the identified barriers. Simultaneously, qualitative insights were gathered through interviews with industry leaders, government officials, and infrastructure experts. This dual approach provided a comprehensive understanding of the challenges. The findings highlight the importance of external factors. These include political uncertainty, financial constraints, and systemic logistical challenges, which go beyond technical feasibility. Based on these insights, this research identifies critical early-stage risks and contributes to a re-evaluation of HSR not solely as a transport solution but also as a vital tool for regional development. Refining cost and time estimation methodologies using reference class forecasting, fostering proactive political engagement to secure bipartisan support, enhancing private sector collaboration through early contractor involvement and risk-sharing mechanisms, and developing a national upskilling framework to address workforce shortages were also key findings. The study has garnered industry recognition and support, with experts acknowledging its contribution to the ongoing discourse on HSR implementation in Australia. Full article

Perovskite solar cells (PSCs) have been regarded as a revolutionary technology in the photovoltaic field, offering a promising pathway for efficient and cost-effective solar energy conversion and demonstrating broad prospects for future green energy technologies. However, critical stability challenges, specifically degradation induced by humidity, light, or heat, severely hinder the commercialization of this technology. Specifically, ultraviolet (UV) radiation in the solar spectrum is a major factor leading to the degradation of perovskite materials. This review focuses on the challenges and strategies for addressing the photostability issues of PSCs. A variety of strategies have been explored, which can be classified as external protection (such as UV-blocking encapsulation technologies) and internal optimization approaches (including precise compositional tuning, the incorporation of functional additives, interface engineering, and improvements to charge transport layers). Finally, this review delves into the key scientific challenges and technological bottlenecks currently faced in addressing the UV stability of PSCs and proposes future directions for solving UV stability issues. It also provides an outlook on the future development prospects of these technologies. Full article

Limited access to education in rural areas of Senegal is a structural barrier to human development and equal opportunities. The Bicycles for Education project, promoted by the Utopia Foundation—Bicycles Without Borders (BSF), aims to improve the educational participation of young people aged 12 to 21 by providing bicycles to facilitate their travel to school. In this study, the GRITS research group from the University of Barcelona externally evaluates the impact of the project on improving access to education, reducing gender inequalities, and the associated socioeconomic as well as community benefits. A qualitative approach based on individual interviews (n = 23), focus groups (n = 6) and group interviews (n = 8) was used, with a total of 80 participants, including students, families, teachers, project coordinators, and institutional managers. The analysis was carried out through thematic coding and content analysis, identifying four main axes: educational impact, gender equity, economic effects, and community transformation. The results show that the provision of bicycles throughout the school year led to increased school attendance and punctuality, improvements in academic performance, a reduction in social inequalities, gender inequalities in access to education, and a decrease in household costs associated with transport and food. In addition, there has been a cultural transformation in the perception of cycling as a viable means of mobility and a change in those communities where the project has been running for more than a decade. Full article

Removing residual energy from end-of-life batteries prior to transportation requires some method of deactivation. While many methods have been proposed, very few have been implemented due to limitations of cost, safety, and efficacy. In this work, multiple cell and battery types (e.g., lithium-polymer pouch cells, 18650 lithium-ion cell, alkaline batteries, and lithium-ion power-tool batteries) were deactivated using a low-cost and easily applied gel consisting of borax cross-linked polyvinyl alcohol and carbon. The PVA–carbon composite creates an external short-circuit pathway of moderate resistance that enables the complete discharge of batteries. Abusive testing conducted after deactivation demonstrates that hazards are largely eliminated, including a complete avoidance of thermal runaway from lithium-ion cells and a reduction in flammable and toxic gases by several orders of magnitude. Full article

Electrocoagulation (EC) systems are regaining attention as a promising wastewater treatment technology due to their numerous advantages, including low system and operational costs and environmental friendliness. However, the widespread adoption and further development of EC systems have been hindered by a lack of fundamental understanding, necessitating systematic research to provide essential insights for system developers. In this study, a continuous EC system with a realistic setup is analyzed using an unsteady, two-dimensional physics-based model that incorporates multiphysics. The model captures key mechanisms, such as arsenic adsorption onto flocs, electrochemical reactions at the electrodes, chemical reactions in the bulk solution, and ionic species transport via diffusion and convection. Additionally, it accounts for bulk wastewater flow circulating between the EC cell and an external storage tank. This comprehensive modeling approach enables a fundamental analysis of how operating conditions influence arsenic removal efficiency, providing crucial insights for optimizing system utilization. Furthermore, the developed model is used to generate data under various operating conditions. Seven machine learning models are trained on this data after hyperparameter optimization. These high-accuracy models are then employed to develop processing maps that identify the conditions necessary to achieve acceptable removal efficiency. This study is the first to generate processing maps by synergistically integrating physics-based and data-driven models. These maps provide clear design and operational guidelines, helping researchers and engineers optimize EC systems. This research establishes a framework for combining physics-based and data-driven modeling approaches to generate processing maps that serve as essential guidelines for wastewater treatment applications. Full article

To address the performance degradation in model predictive control (MPC) under vehicle state uncertainties caused by external disturbances (e.g., crosswinds and tire cornering stiffness variations) and rigid constraint conflicts, we propose a robust MPC framework with adaptive weight adjustment and dynamic constraint relaxation. Traditional MPC methods often suffer from infeasibility or deteriorated tracking accuracies when handling model mismatches and disturbances. To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. The proposed method is validated via ROS (noetic)–MATLAB2023 co-simulations under crosswind disturbances (0–3 m/s) and varying road conditions. The results show that the improved algorithm achieves a 13% faster response time (5.2 s vs. 6 s control cycles), a 15% higher minimum speed during cornering (2.98 m/s vs. 2.51 m/s), a 32% narrower lateral velocity fluctuation range ([−0.11, 0.22] m/s vs. [−0.19, 0.22] m/s), and reduced yaw rate oscillations ([−1.8, 2.8] rad/s vs. [−2.8, 2.5] rad/s) compared with a traditional fixed-weight MPC algorithm. These improvements lead to significant enhancements in trajectory tracking accuracy, dynamic response, and disturbance rejection, ensuring both safety and efficiency in autonomous vehicle control under complex uncertainties. The framework provides a practical solution for real-time applications in intelligent transportation systems. Full article

Regenerative braking systems (RBS enhance energy efficiency and range in electric vehicles (EVs) by recovering kinetic energy during braking for storage in batteries or alternative systems. This literature review examines RBS advancements from 2005 to 2024, focusing on system design, control strategies, energy storage technologies, and the impact of external and kinematic factors on recovery efficiency. Based on a systematic analysis of 89 peer-reviewed articles from Scopus, it highlights a shift from basic PID controllers to advanced predictive algorithms like Model Predictive Control (MPC) and machine learning approaches. Technologies such as brake-by-wire and in-wheel motors improve safety and stability, with the latter excelling in all-wheel-drive setups over single-axle configurations. Hybrid Energy Storage Systems (HESS), combining batteries with supercapacitors or kinetic accumulators, address power peak demands, though cost and complexity limit scalability. Challenges include high computational requirements, component reliability in harsh conditions, and lack of standardized testing. Research gaps involve long-term degradation, autonomous vehicle integration, and driver behavior effects. Future work should explore cost-effective HESS, robust predictive controls for autonomous EVs, and standardized frameworks to enhance RBS performance and support sustainable transportation. Full article

Water scarcity and pollution are critical challenges affecting agriculture and aquatic ecosystems. This study evaluates the environmental benefits of using reclaimed water (RW) for irrigation in southern Spain by applying a comprehensive cost–benefit analysis (CBA) to a water reuse project. This method allows us to assess financial feasibility and environmental externalities of RW use for irrigation, with particular focus on the reduction in eutrophication and greenhouse gas emissions. Furthermore, the proposed CBA highlights the potential of RW to provide essential nutrients for crops, reduce reliance on synthetic fertilizers, and mitigate the ecological impact of fertilizer manufacturing and transportation. Results indicate that, while the direct financial returns of RW are limited, the integration of environmental benefits significantly improves the overall economic viability of water reuse projects. Furthermore, sensitivity analyses suggest that policy measures, such as adjusted water pricing and financial incentives, could enhance the adoption of RW in agriculture. This study supports the role of RW as a sustainable alternative for irrigation, contributing to water conservation, pollution reduction, and climate resilience. Future research should focus on long-term agronomic impacts, optimized pricing models, and policy frameworks that promote water reuse as a key strategy in sustainable water management. Full article

Quasi-two-dimensional (quasi-2D) perovskites have emerged as a transformative platform for high-efficiency perovskite light-emitting diodes (PeLEDs), benefiting from their tunable quantum confinement, high photoluminescence quantum yields (PLQYs), and self-assembled energy funneling mechanisms. This review systematically explores interfacial energy transfer engineering strategies that underpin advancements in device performance. By tailoring phase composition distributions, passivating defects via additive engineering, and optimizing charge transport layers, researchers have achieved external quantum efficiencies (EQEs) exceeding 20% in green and red PeLEDs. However, challenges persist in blue emission stability, efficiency roll-off at high currents, and long-term operational durability driven by spectral redshift, Auger recombination, and interfacial ion migration. Emerging solutions include dual-cation/halogen alloying for bandgap control, microcavity photon management, and insulator–perovskite–insulator (IPI) architectures to suppress leakage currents. Future progress hinges on interdisciplinary efforts in multifunctional material design, scalable fabrication, and mechanistic studies of carrier–photon interactions. Through these innovations, quasi-2D PeLEDs hold promise for next-generation displays and solid-state lighting, offering a cost-effective and efficient alternative to conventional technologies. Full article