Search Results (607)

This study evaluates the feasibility and visibility of electric vehicles (EVs) in Egypt, addressing critical research gaps and proposing actionable strategies to drive adoption. Employing a systematic review of academic, governmental, and industry sources, the paper identifies underexplored areas such as rural–urban adoption disparities, lifecycle assessments of EV batteries, and sociocultural barriers, including gender dynamics and entrenched consumer preferences. Its primary contribution is an interdisciplinary framework that integrates technical aspects, such as grid resilience and climate-related battery degradation, with socioeconomic dimensions, providing a holistic overview of EV feasibility in Egypt tailored to Egypt’s context. Key findings reveal infrastructure limitations, inconsistent policy frameworks, and behavioral skepticism as major hurdles, and highlight the untapped potential of renewable energy integration, particularly through synergies between solar PV generation (e.g., Benban Solar Park) and EV charging infrastructure. Recommendations prioritize policy reforms (e.g., tax incentives, streamlined tariffs), solar-powered charging infrastructure expansion, public awareness campaigns, and local EV manufacturing to stimulate economic growth. The study underscores the urgency of stakeholder collaboration to transform EVs into a mainstream solution, positioning Egypt as a regional leader in sustainable mobility and equitable development. Full article

Awareness of design when planning public urban spaces assumes particular importance through its mission to meet the diverse needs of the different segments within the community. The elderly is considered one of the pivotal segments, with their influence on strengthening social cohesion, fortifying values, and upholding traditions. On the other hand, such a segment demands special physical, behavioral, and mental requirements that would entail specific consideration in the design process of public common spaces. The study aimed to identify and evaluate the most relevant and important indicators pertaining to the most effective design of an age-friendly public space, with community parks taken as a particular case. The study relies on a mixed approach, combining desk research, expert views, the Delphi technique, and the Analytical Hierarchy Process to achieve that purpose. It resulted in a group of sourced, filtered, and evaluated indicators classified into Physical, Experiential, and Social/Emotional categories, which were evaluated by a mixed representative group of academics, practitioners, governmental officials, and end users, being the elderly or their caretakers. Focus was placed on the central park in the Dahiyat Al-Hussein suburb in Amman, Jordan, which was utilized as a contextual case through which a refined design framework was extracted. This framework serves as a potential base that can be expanded and adapted to create a more generalizable model. Full article

This study develops a high-speed rail demand prediction model based on access probability, which quantifies the likelihood of passengers choosing a departure station among multiple alternatives. Traditional models assign demand to the nearest station or rely on manual calibration, often failing to reflect actual travel behavior and requiring excessive time and resources. To address these limitations, this study integrates survey data, real-world datasets, and machine learning techniques to model station choice behavior more accurately. Key influencing factors, including headway, access time, parking availability, and transit connections, were identified through passenger surveys and incorporated into the model. Machine learning algorithms improved prediction accuracy, with SHAP analysis providing interpretability. The proposed model achieved high accuracy, with an average error rate below 3% for major stations. Scenario analyses confirmed its applicability in network expansions, including GTX openings and the integration of mobility as a service. This model enhances data-driven decision-making for rail operators and offers insights for rail network planning and operations. Future research will focus on validating the model across diverse regions and refining it with updated datasets and external data sources. Full article

Cocaine misuse induces microglial activation and neuroinflammation, contributing to neurodegeneration and behavioral impairments. Prior studies have shown that cocaine induces mitochondrial dysfunction, dysregulated mitophagy, and lysosomal impairment in microglia. Here, we investigated the therapeutic potential of N-acetylcysteine (NAC) in mitigating cocaine-induced microglial activation and neuroinflammation. Mouse primary microglial cells (MPMs) were pretreated with NAC (5 mM) for 1 h prior to cocaine exposure (10 µM, 24 h) and analyzed for markers of microglial activation, mitophagy, and lysosomal integrity using Western blot, Seahorse assays, lysosomal pH, and membrane potential measurements. In vivo, C57BL/6N mice received NAC (200 mg/kg, i.p.) 1 h before daily cocaine injections (20 mg/kg, i.p.) for 7 days. Behavioral assays (open field, novel object recognition) and brain biomarker analyses (frontal cortex, hippocampus) were performed. Cocaine exposure elevated CD11b, mitophagy markers (PINK1, PARK, and DLP1), and autophagy proteins (Beclin1, and p62), while impairing mitochondrial and lysosomal functions. NAC pretreatment restored mitochondrial and lysosomal function, reduced reactive oxygen species, and normalized protein expression. In vivo, NAC also alleviated cocaine-induced microglial activation and behavioral deficits. These findings highlight NAC as a promising therapeutic agent to counteract cocaine-mediated neuroinflammation and neurotoxicity. Full article

(1) Background: The provision of monofunctional or inadequately distributed services in urban park green spaces often constrains residents’ opportunities and diversity for outdoor activities, particularly limiting access and participation for specific age groups or activity preferences. However, functional nodes with temporal and spatial flexibility demonstrate high-quality characteristics of resilient and shared services through integrated development. Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. By collecting and integrating various types of data, such as geographic spatial data, field investigation data, and behavioral observations, we developed a population demand quantification method and a modular analysis approach for park service functions. This framework enabled correlation analysis between diverse user needs and park services. The study further classified and combined park functions into modular units, quantifying their elastic and shared service capabilities—namely, the adaptive flexibility and shared utilization capacity of park services. Additionally, we established a demand-responsive evaluation system for identifying and diagnosing problem areas in park services based on multi-source data. (3) Results: The demand response index and diagnostic results indicate that the supply of fitness facilities—particularly equipment-based installations—is insufficient within the old urban district of Zhengzhou. Among the three user groups—children, young and middle-aged adults, and the elderly—the elderly population exhibited the lowest demand response index, revealing a significant gap in meeting their specific needs. (4) Conclusions: Based on the research findings, a three-tier optimization strategy is proposed: A. improve green space connectivity to expand the service coverage of parks; B. implement multifunctional overlay and coordinated integration in spatial design based on site characteristics and demand diagnostics; and C. increase the total supply of facilities to enhance spatial efficiency in parks. By integrating the demand assessment data and diagnostic results, this approach enabled a data-driven reorganization of service types and targeted allocation of resources within existing park infrastructure, offering a practical tool and reference for the planning of urban outdoor activity spaces. Full article

Amid the increasing complexity of urban risks, urban parks not only serve ecological and recreational functions but are increasingly becoming a critical spatial foundation supporting public psychological resilience and social recovery. This study aims to systematically evaluate the daily adaptability of urban parks in the context of micro-risks. The research integrates the theories of “restorative environments,” environmental safety perception, urban resilience, and social ecology to construct a five-dimensional framework for perceived resilience, encompassing resilience, safety, sociability, controllability, and adaptability. Additionally, a dynamic feedback mechanism of perception–behavior–reperception is introduced. Methodologically, the study utilizes the Fuzzy Delphi Method (FDM) to identify 17 core indicators, constructs a causal structure and weighting system using DEMATEL-based ANP (DANP), and further employs the VIKOR model to simulate public preferences in a multi-criteria decision-making process. Taking three representative urban parks in Guangzhou as empirical case studies, the research identifies resilience and adaptability as key driving dimensions of the system. Factors such as environmental psychological resilience, functional diversity, and visual permeability show a significant path influence and priority intervention value. The empirical results further reveal significant spatial heterogeneity and group differences in the perceived resilience across ecological, neighborhood, and central park types, highlighting the importance of context-specific and user-adaptive strategies. The study finally proposes four optimization pathways, emphasizing the role of feedback mechanisms in enhancing urban park resilience and shaping “cognitive-friendly” spaces, providing a systematic modeling foundation and strategic reference for perception-driven urban public space optimization. Full article

Zebrafish (Danio rerio) combine accessible behavioral phenotypes with conserved neurochemical pathways and molecular features of vertebrate brain function, positioning them as a powerful model for investigating early neurodegenerative processes and screening neuroprotective strategies. In this context, integrated behavioral and proteomic analyses provide valuable insights into the initial pathophysiological events shared by conditions such as Parkinson’s disease and related disorders—including mitochondrial dysfunction, oxidative stress, and synaptic impairment—which emerge before overt neuronal loss and offer a crucial window to understand disease progression and evaluate therapeutic candidates prior to irreversible damage. To investigate this early window of dysfunction, zebrafish larvae were exposed to 500 μM 1-methyl-4-phenylpyridinium (MPP⁺) from 1 to 5 days post-fertilization and evaluated through integrated behavioral and label-free proteomic analyses. MPP⁺-treated larvae exhibited hypokinesia, characterized by significantly reduced total distance traveled, fewer movement bursts, prolonged immobility, and a near-complete absence of light-evoked responses—mirroring features of early Parkinsonian-like motor dysfunction. Label-free proteomic profiling revealed 40 differentially expressed proteins related to mitochondrial metabolism, redox regulation, proteasomal activity, and synaptic organization. Enrichment analysis indicated broad molecular alterations, including pathways such as mitochondrial translation and vesicle-mediated transport. A focused subset of Parkinsonism-related proteins—such as DJ-1 (PARK7), succinate dehydrogenase (SDHA), and multiple 26S proteasome subunits—exhibited coordinated dysregulation, as visualized through protein–protein interaction mapping. The upregulation of proteasome components and antioxidant proteins suggests an early-stage stress response, while the downregulation of mitochondrial enzymes and synaptic regulators reflects canonical PD-related neurodegeneration. Together, these findings provide a comprehensive functional and molecular characterization of MPP⁺-induced neurotoxicity in zebrafish larvae, supporting its use as a relevant in vivo system to investigate early-stage Parkinson’s disease mechanisms and shared neurodegenerative pathways, as well as for screening candidate therapeutics in a developmentally responsive context. Full article

Chemical leakage accidents in chemical industrial parks pose significant threats to personnel safety, particularly during evacuation processes, where individual behavior and evacuation strategies have a considerable impact on overall efficiency. This study takes a leakage incident at an alkylation unit as a case study. First, ALOHA5.4.7 software was used to simulate the influence of meteorological conditions across different seasons on the dispersion range of toxic gases, thereby generating an annual comprehensive risk zone distribution map. Subsequently, different evacuation scenarios were constructed in Pathfinder2024.1.0605, with the integration of trigger mechanisms to simulate individual behaviors during evacuation, such as variations in risk perception and peer influence. Furthermore, this study expanded the conventional application scope of Pathfinder—typically limited to small-scale building evacuations—by successfully adapting it for large-scale evacuation simulations in chemical industrial parks. The feasibility of such simulations was thereby demonstrated, highlighting the software’s potential. According to the simulation results, exit configuration, shelter placement, and individual behavior modeling significantly affect the total evacuation time. This study provides both theoretical insights and practical guidance for emergency response planning in chemical industrial parks. Full article

With the growth of the urban population and economic level, the issue of urban parking space shortages (UPSSs) has assumed growing prominence. This persistent issue not only exacerbates traffic congestion but also contributes to environmental pollution, highlighting the need for system-oriented mitigation strategies. First, an algorithm for mitigating UPSSs based on nudge theory was constructed, in order to determine how the nudge strategies work. Second, nudge tools, including gain disclosure, salience, and outcome notification, were integrated to construct a mitigation model for UPSSs, which synthesizes nudge theory, the model of self-regulatory processes involved in behavioral change, and system dynamics (NT-SPBC-SD theory). Finally, four scenarios of natural development, guide adjustment, balanced regulation, and enhanced change were simulated. The findings of this study are as follows: (1) The UPSS mitigation had multiple overlapping effects and critical point effects, and the nudge strategy gradually decayed or even rebounded over time. (2) Under the enhanced change scenario, the degree of UPSSs, the amount of illegal parking, and CO₂ emissions from civil vehicles decreased by 21.2%, 6.93%, and 14.54%, respectively. (3) After quantitative comparisons, the balanced regulation scenario with lower implementation costs instead demonstrated superior overall performance. The results support subsequent research and guide the enhancement of urban parking management policies to advance urban sustainability. Full article

This study proposes a novel method to assess urban park accessibility by incorporating perceived utility based on both park area and distance. Departing from conventional models that treat accessibility as a function of geometric proximity alone, we define park utility as a distance-discounted benefit of park area, thereby allowing for a more behaviorally grounded measure. A customized discounting function is introduced, where larger park sizes proportionally reduce perceived travel cost, and walking speed adjustments are applied based on demographic user profiles (children, adults, and older adults). The methodology was implemented using a Python-based v.3.12.9 geospatial workflow with network-based distance calculations between 18,614 census block groups and all urban parks in Seoul. Population-weighted utility scores were computed by integrating park size, distance, and age-specific mobility adjustments. The results reveal significant intra-urban disparities, with a citywide deficit of 4,066,046 m in population-weighted distance, particularly in areas with large populations but insufficient proximity to high-utility parks. Simulation analyses of 30 candidate sites demonstrate that strategic park placement can yield substantial utility improvements (maximum gain: 493,436 m), while indiscriminate expansion may not. These findings offer spatial decision support for optimizing limited public resources in urban green infrastructure planning and underscore the need to consider both park scale and user-specific walking behavior in evaluating accessibility. Full article

Path planning and collision avoidance are essential components of an autonomous driving system (ADS), ensuring safe navigation in complex environments shared with other road users. High-quality planning and reliable obstacle avoidance strategies are essential for advancing the SAE autonomy level of autonomous vehicles, which can largely reduce the risk of traffic accidents. In daily driving scenarios, lane changing is a common maneuver used to avoid unexpected obstacles such as parked vehicles or suddenly appearing pedestrians. Notably, lane-changing behavior is also widely regarded as a key evaluation criterion in driver license examinations, highlighting its practical importance in real-world driving. Motivated by this observation, this paper aims to develop an autonomous lane-changing system capable of dynamically avoiding obstacles in multi-lane traffic environments. To achieve this objective, we propose a hierarchical decision-making and control framework in which a Double Deep Q-Network (DDQN) agent operates as the high-level planner to select lane-level maneuvers, while a High-Order Control Lyapunov Function–High-Order Control Barrier Function–based Quadratic Program (HOCLF-HOCBF-QP) serves as the low-level controller to ensure safe and stable trajectory tracking under dynamic constraints. Simulation studies are used to evaluate the planning efficiency and overall collision avoidance performance of the proposed hierarchical control framework. The results demonstrate that the system is capable of autonomously executing appropriate lane-changing maneuvers to avoid multiple obstacles in complex multi-lane traffic environments. In computational cost tests, the low-level controller operates at 100 Hz with an average solve time of 0.66 ms per step, and the high-level policy operates at 5 Hz with an average solve time of 0.60 ms per step. The results demonstrate real-time capability in autonomous driving systems. Full article

Tourism offers many economic benefits but can have long-lasting ecological effects when improperly managed. Tourism can cause overwhelming pressure on wastewater treatment systems, as in Belize, where some of the over 400 small islands (cayes) that were once temporary sites for fishermen have become popular tourist destinations. An overabundance of nitrogen, in part as a result of incomplete wastewater treatment, threatens human health and ecosystem services. The tourism industry is a complex and dynamic industry with many sectors and stakeholders with conflicting goals. In this study, a systems thinking approach was adopted to study the dynamic interactions between stakeholders and the environment at Laughing Bird Caye National Park in Belize. The project centered on nutrient discharges from the caye’s onsite wastewater treatment system. An archetype analysis approach was applied to frame potential solutions to nutrient pollution and understand potential behaviors over time. “Out of control” and “Underachievement” were identified as system archetypes; “Shifting the Burden” and ‘‘Limits to Success’’ were used to model specific cases. Based on these results, upgrading of the wastewater treatment system should be performed concurrently with investments in the user experience of the toilets, education on the vulnerability of the treatment system and ecosystem, and controls on the number of daily tourists. Full article

Sustainable urban development takes place in cities that encourage residents to adopt sustainable consumption behaviors. Cities are transforming towards achieving sustainable urban consumption, meeting the needs of communities without compromising the wealth of future generations. A key element of urban development is sustainable urban mobility, which helps improve residents’ quality of life and protect the environment. The development of sustainable mobility is possible thanks to, among others, investment in infrastructure that improves travel. One element of this infrastructure that plays an important role in sustainable mobility is parking lots. They have a significant impact on the quality of life in the city, and searching for available parking spaces is a serious problem in modern urban mobility. This article includes an analysis of parking data obtained from the Intelligent Paid Parking System in the context of sustainable urban consumption. Three streets in the city of Rzeszów were analyzed. For the period under study, the factors determined included parking space utilization indicators, whose average value for the streets analyzed was in the range of 57–59%, and a turnover indicator, whose average value was in the range of 4.8–6.0. These indicators assessed the degree to which city residents are involved in ideas related to sustainable development, as well as their habits in relation to sustainable consumption. Full article

Urban transportation systems face increasing pressure to reduce car dependency and greenhouse gas emissions while supporting sustainable growth. This study addresses the lack of integrated modeling approaches that capture both spatial and temporal dynamics in transport planning. It develops a novel framework combining System Dynamics (SD) and Geographic Information Systems (GIS) to assess the sustainability of Transit-Oriented Development (TOD) strategies and parking policies in two brownfield redevelopment sites in Montreal. The framework embeds spatial metrics, such as proximity to transit, parking availability, and active transportation infrastructure into dynamic feedback loops. Using scenario analysis, the study compares a baseline reflecting current norms with an intervention scenario emphasizing higher density near transit, reduced parking ratios, and improved walkability and bike infrastructure. The results suggest that aligning TOD principles with targeted parking limits and investments in active mobility can substantially reduce car ownership and emissions. While primarily conceptual, the model provides a foundation for location-sensitive, feedback-driven planning tools that support sustainable urban mobility. Full article

Rapid urbanization, excessive motorization, and the imperative to reduce carbon footprints are driving the search for sustainable urban space solutions. One promising approach involves the effective design of small-scale architecture, such as parking shelters, optimized for structural material consumption and resilience to vehicle impacts. This research employed a novel approach during the initial design phase. Genetic algorithms and optimization techniques were utilized to define the optimal geometries of steel structures, focusing on the height of the conoidal roof and the shape and arrangement of columns. The subsequent analysis included static and strength calculations, dimensioning, and evaluating structural responses to exceptional loading, incorporating novel impact scenarios. The analysis yielded several key insights into the structural efficiency, dynamic behavior, and design optimization of the shelters. The research revealed that both roof geometry and column shape and arrangement significantly influenced material consumption and design effectiveness. The findings indicated that shelters with four straight, vertical, non-corner columns exhibited the most favorable dynamic behavior and highest impact resistance. These shelters also facilitated easy parking for both single-module and double-module roof types. The research findings provide a foundation for the parametric design of functional and structurally resilient parking shelters that cater to urban transportation needs and ecological objectives. Full article