Search Results (903)

This paper presents a simulation framework for analysing race car overtaking manoeuvres under aerodynamic wake effects using optimal control theory. The proposed formulation integrates wake-dependent aerodynamic disturbances into a spatial-domain optimal control problem, enabling simultaneous optimisation of racing line and control inputs. A planar vehicle model representative of a modern FIA Formula 3 car is employed and calibrated using real telemetry data obtained from Campos Racing. Wake effects are modelled as distance- and offset-dependent aerodynamic loss factors that influence drag, downforce, and aerodynamic balance of the following vehicle. The framework is implemented using the Dymos optimal control library and applied to single-car and two-car overtaking scenarios on a closed circuit. Simulation results demonstrate that wake effects significantly modify optimal braking points, corner entry trajectories, and corner-exit strategies. Moreover, we show that optimal overtaking requires deliberate lateral deviations from the wake core to recover downforce and traction. The study highlights the importance of incorporating aerodynamic interaction effects into trajectory optimisation when analysing performance-critical motorsport manoeuvres. Full article

The treatment of central nervous system (CNS) autoimmune diseases has evolved from broad immunosuppression toward targeted disease-modifying therapies (DMTs). While current DMTs effectively control inflammatory activity in many patients, unmet needs remain, including persistent compartmentalised CNS pathology, limited tissue penetration, and the cumulative burden of chronic therapy. Chimeric antigen receptor (CAR) T-cell therapy represents a novel “living” immunotherapy capable of antigen-specific cellular depletion. Although currently approved only for B-cell malignancies, CAR T-cells are increasingly being explored in CNS autoimmunity leveraging their capacity for autonomous cytotoxicity and expected access to immune cells within protected CNS niches following a potentially single intervention. In this review, we examine CAR T-cells in the context of CNS-autoimmunity, we outline principles derived from oncologic applications, assess current DMTs, their limitations and side effects, and define parameters where CAR T-cells may offer added value. We discuss biological and practical requirements for broader clinical application, as currently they are investigated only for the very severe and refractory cases where all alternative treatments have failed. We further review the plasticity of CAR constructs, distinguishing clinically advanced platforms from early proof-of-concept approaches. Finally, we summarise clinical experience from 15 patients with CNS autoimmunity treated with CAR T-cells and review ongoing or planned trials that include such patients. We conclude that CAR T-cell therapy remains investigational for severe, treatment-refractory disease, with future applicability dependent on demonstrable efficacy, safety, cost, and feasibility beyond existing DMTs. Full article

Unstable car-following behavior under truck-induced visual occlusion on mountainous two-lane roads significantly increases rear-end crash risk. However, compared with studies focusing on overtaking or curve risk prediction, the car-following-truck (CFT) risk and its influencing factors have received limited attention. Therefore, this study used unmanned aerial vehicles (UAVs) to collect high-resolution trajectory data of CFT scenarios on both straight and curved segments under truck-induced occlusion. First, the CFT risk was quantified based on an anticipated collision time (ACT) indicator, a two-dimensional surrogate safety measure that accounts for vehicle acceleration variations. Then, extreme value theory (EVT) was applied to calibrate alignment-specific risk thresholds. Finally, an XGBoost-based risk identification model was developed using vehicle dynamics-related features, and feature importance analysis combined with partial dependence interpretability was conducted to obtain key influencing factors. The results show that the calibrated ACT thresholds are approximately 3.838 s for straight segments and 4.385 s for curved segments, providing a reliable basis for risk classification. In addition, the XGBoost-based risk identification achieved accuracies of 90.63% and 95.87% for straight and curved segments, respectively. Further analysis indicates that CFT distance was the contributing factor. Moreover, risk increases markedly within a 10–20 m range on straight segments, while it rises rapidly once spacing falls below about 10 m on curved segments. Speed and acceleration differences exhibited stronger amplifying effects under short-spacing conditions. These findings provide a micro-behavioral basis for safety management and intelligent driving applications on mountainous roads with high truck mixing rates, supporting safer and more sustainable traffic operations. Full article

Fuel consumption in heavy-duty off-road machinery depends on a wide range of interacting factors related to the operating environment, the technical characteristics and condition of the machine, and the behaviour, experience and state of the operator. Existing studies typically address only fragments of this relationship, focusing on vehicle parameters, selected environmental factors or individual aspects of driving style. The method proposed in this work provides a general and transferable framework for assessing fuel consumption in any type of machine or vehicle. The Integrated Fuel Consumption Assessment Model (IFCAM) combines environmental, vehicle and human domains into a coherent structured formula that can be used across different operational contexts. The model was developed using continuous short-term measurements and long-term operational data collected during real industrial work. Its universal structure makes it applicable not only to mining equipment, but also to construction machinery and transport vehicles, as well as conventional passenger cars, where it offers a systematic procedure for estimating fuel demand under variable operating conditions. The results demonstrate that integrating multi-domain data improves predictive accuracy and opens new possibilities for analysing operator influence and overall energy efficiency. Full article

Postsocialist peri-urban spaces are characterized by a chaotic development as a result of the transition from communism to capitalism. Recent research has highlighted that liveability in peri-urban spaces encounters challenges of adaptation to the peri-urban areas. The aim of the present study is to identify and analyze patterns and contrasts that occur between age groups and gender in relation to the level of liveability as well as to better understand the daily mobility practices and commuting dependencies and how mobility shapes key contrasts and emerging tensions within Timișoara’s postsocialist peri-urban spaces. As liveability relates to local development, commuting, and accessibility to service facilities in the residential environment, the identification of patterns and differences is imperative when considering the perception of local residents on potential (un)sustainable liveability in peri-urban areas. This study utilizes a quantitative analysis, informed by a survey of considerable size (N = 954) conducted in peri-urban settlements of Timisoara, Romania, with a view to elucidating the distinctions and commonalities in the perceptions held by the local populace. The findings indicate that the elderly population exhibits a greater reluctance to adapt to the emerging peri-urban environment. In contrast, the younger and more educated demographic demonstrates a higher degree of adaptability to the contemporary challenges posed by peri-urban expansion and hazardous development. Daily mobility, including commuting, is directly influenced by the effects of dispersed and chaotic development (e.g., more than 79% of respondents rely on private cars for commuting), as well as the lack of facilities and services (e.g., 2.21 level of satisfaction regarding cultural events). This highlights Timisoara’s dependence on external services, as well as the significant role of personal vehicles in providing access to the city center and its neighborhoods. Therefore, we can observe the peri-urban area undergoing a transitional phase as it navigates the initial stages of sustainable urban development and pursues an enhanced quality of life. Finally, we propose several policy recommendations for local authorities, offering solutions for enhancing liveability in peri-urban areas. Full article

Controlling pre-analytical conditions for medical biology tests, particularly during transport, is crucial for complying with the ISO 15189 standard and ensuring high-quality medical services. The use of drones, also known as unmanned aerial vehicles, to transport clinical samples is growing in scale, but requires prior validation to verify that there is no negative impact on the test results provided to doctors. This study aimed to establish a secure, high-quality solution for transporting biological samples by drone in a coastal region of France. The 80 km routes passed over several densely populated urban areas, with take-off and landing points within hospital grounds. The analytical and clinical impact of this mode of transport was compared according to two protocols: an interventional clinical trial on 30 volunteers compared to the reference transport by car, and an observational study on samples from 126 hospitalized patients compared to no transport. The system enabled samples to be transported without damage by maintaining freezing, refrigerated, and room temperatures throughout the flight, without any significant gain in travel time. Analytical variations were observed for sodium, folate, GGT, and platelet levels, with no clinical impact on the interpretation of the results. There is a risk of time-dependent alterations of blood glucose measurements in heparin tubes, which can be corrected by using fluoride tubes. This demonstrated the feasibility and security of transporting biological samples over long distances in line with the ISO 15189 standard. Controlling transport times remains crucial to assessing the quality of analyses. It is imperative to devise contingency plans for backup solutions to ensure the continuity of transportation in the event of inclement weather. Full article

Switching to electric vehicles (EVs) could help reduce air pollution in cities. This is especially important for cities in Russia that have grown quickly because of industry, like those in Siberia, where environmental problems are particularly acute. However, several factors continue to hinder the rapid expansion of EVs on the market, such as an additional strain on the energy infrastructure, which threatens to cause power outages. This study proposes a model for estimating the electricity consumption by EVs in the largest Russian cities, taking into account the technical characteristics of the EV fleet and climatic conditions. The calculations indicate that if 15% of the current car fleet are replaced by EVs, electricity consumption in the 16 largest cities in Russia would increase by 2.2 TWh per year in total. The estimated additional demand in particular cities varies between 33 mln and 769 mln kWh per year, depending on the number of vehicles and the local climate. Furthermore, we conducted an intra-day simulation of electricity consumption from EVs in a conditional Russian city with a population of over one million people. Three scenarios for the power grid load have been developed: (A) the maximum scenario, in which all EVs have a battery level of 0%; (B) the medium scenario, where EVs’ state of charge is distributed between 0% and 100%, and (C) the minimum scenario, involving charging scheduling that allows only EVs with a battery level of 20% or less to charge. The findings show that replacing just 15% of the car fleet with electric vehicles will trigger an increase in current daily household urban consumption of 28.4% in scenario (C), 75.6% in scenario (B) and 141.8% in scenario (A). Consequently, even in Russia’s largest cities, the further proliferation of EVs requires large-scale investments in power infrastructure. An additional 1 mln kWh used by EVs per day may require $160.7 mln investments in energy facilities and urban distribution networks. These findings highlight the necessity of a more thorough cost–benefit analysis of widespread electric vehicle adoption in densely populated urban areas. Full article

Smart-city last-mile rail access, referred to in this entry simply as last-mile access, captures how travelers connect to and from rail stations during the first or last leg of a journey. It encompasses both the design of multimodal connections and the experience of accessibility that results from them. On the supply side, last-mile access involves the coordination of walking, cycling, micromobility, and feeder transit with rail services, supported by digital systems that unify planning, ticketing, and payment. On the demand side, it reflects how efficiently and equitably travelers can reach stations within these coordinated networks. Together, these physical and institutional dimensions extend the functional reach of rail, reduce transfer barriers, and reinforce its role as the backbone of sustainable urban mobility. As cities strive to reduce car dependency while promoting inclusivity and accessibility, last-mile access has become a key indicator of how infrastructure, technology, and governance intersect to deliver more equitable transportation systems. Full article

High-precision land cover classification is fundamental to environmental monitoring, urban planning, and sustainable land-use management. With the growing availability of multimodal remote sensing data, combining spectral and structural information has become an effective strategy for improving classification performance in complex high-resolution scenes. However, most existing methods predominantly rely on shallow feature concatenation, which fails to capture long-range dependencies and cross-modal interactions that are critical for distinguishing fine-grained land cover categories. This study proposes a multi-level cross-modal attention fusion network, Cross-Modal Cross-Attention UNet (CMCAUNet), which integrates a Cross-Modal Cross-Attention Fusion (CMCA) module and a Skip-Connection Attention Gate (SCAG) module. The CMCA module progressively enhances multimodal feature representations throughout the encoder, while the SCAG module leverages high-level semantics to refine spatial details during decoding and improve boundary delineation. Together, these modules enable more effective integration of spectral–textural and structural information. Experiments conducted on the ISPRS Vaihingen and Potsdam datasets demonstrate the effectiveness of the proposed approach. CMCAUNet achieves an mean Intersection over Union (mIoU) ratio of 81.49% and 84.76%, with Overall Accuracy (OA) of 90.74% and 90.28%, respectively. The model also shows superior performance in small object classification, with targets like “Car,” achieving 90.85% and 96.98% OA for the “Car” category. Ablation studies further confirm that the combination of CMCA and SCAG modules significantly improves feature discriminability and leads to more accurate and detailed land cover maps. Full article

Transit-Oriented Development (TOD), formalized by Calthorpe and Poticha in 1993, emerged to counter urban sprawl, reduce car dependency, and revitalize historical community centers. Rooted in “new urbanism”, TOD emphasizes integrated regional land-use planning and high-capacity public transportation. In the Middle East, TOD implementation remains understudied, particularly regarding heritage integration and social equity in arid climates. Doha’s rapid social and economic transformation presents both opportunities and risks: growth offers urban revitalization yet threatens to displace communities and dilute cultural identity. Shifts in urban planning have aimed to address sustainability, connectivity, and heritage preservation. This study examines Msheireb Downtown Doha (MDD) to assess how TOD can restore historic districts while managing gentrification, enhancing accessibility and promoting inclusiveness. A mixed-methods approach was applied, including 12 semi-structured interviews with stakeholders (Qatar Rail, Msheireb Properties, Ministry of Municipality and Environment), purposive surveys of 80 urban users, site observations, and spatial mapping. Using the Node-Place-People (NPP) model, the study evaluates TOD effectiveness across transportation connectivity (node), built environment quality (place), and equity metrics (people). The findings show that MDD successfully implements fundamental TOD principles through its design, which enhances connectivity, walkability, social inclusiveness, and heritage preservation. However, multiple obstacles remain: the “peripheral island effect” limits benefits to the core, pedestrian–vehicular balance is unresolved, and commercial gentrification is on the rise. This research provides evidence-based knowledge for GCC cities pursuing sustainable urban regeneration by demonstrating both the advantages of TOD and the necessity for critical, context-sensitive implementation that focuses on social equity together with physical transformation. Full article

Prostate cancer (PCa) is the leading cause of cancer-related deaths worldwide and the second most common cancer among men. Treatment options depend on factors like age, androgen sensitivity, PSA levels, Gleason score, TNM stage, and recurrence risk. Available treatments include hormonal therapy, radiation, surgery, and chemotherapy. Early immunological treatments were limited by poor lymphocyte infiltration and an immunosuppressive environment. Today, strategies such as dendritic cell vaccines, immune checkpoint inhibitors (ICIs), and adoptive cell therapy (ACT) are used. ACT, especially CAR T-cell strategies, aims to overcome traditional treatment limitations, particularly in advanced and metastatic castration-resistant prostate cancer (mCRPC), though it remains in early development. Personalized medicine uses molecular insights from the diseased tissue to tailor treatments. Variability in patient response, due to tumor heterogeneity and prior treatments, highlights the importance of personalized and combination therapies as future strategies for effective immunotherapy. This review explores the current landscape of PCa. We analyze treatment guidelines established by NCCN and EANM-ESTRO-ESUR-ISUP-SIOG. We comprehensively examine immunotherapeutic strategies currently available or under investigation for prostate cancer, with particular emphasis on ICIs, ACT with a focus on CAR T-cell therapy, combination approaches and therapeutic synergies, and predictive biomarkers of immunotherapy response. Additionally, we discuss the challenges and future directions in the implementation of immunotherapy for the management of prostate cancer. Full article

Lentiviral transduction remains the gold standard in adoptive modified cellular therapy, such as CAR-T; however, genome integration is not always desirable, such as when treating non-fatal autoimmune disease or for additional editing steps using CRISPR to produce allogeneic CAR-modified cells. Delivering in vitro-transcribed (IVT) mRNA represents an alternative solution but the labile nature of mRNA has led to efforts to improve half-life and translation efficiencies using a range of approaches including chemical and structural modifications. In this study, we explore the role of N⁶–methyladenosine (m6A) in a CD19-CAR sequence when delivered to T cells as an IVT mRNA. In silico analysis predicted the presence of four m6A consensus (DRACH) motifs in the CAR coding sequence and treating T cells with an inhibitor of the m6A methyltransferase (METTL3) resulted in a significant reduction in CAR protein expression. RNA analysis confirmed m6A bases at three of the predicted sites, indicating that the modification occurs independently of nuclear transcription. Synonymous mutation of the DRACH sites reduced the levels of CAR protein from 15 to >50% depending on the T cell donor. We also tested a panel of CAR transcripts with different UTRs, some containing m6A consensus motifs, and identified those which further improved protein expression. Furthermore, we found that the methylation of consensus m6A sites seems to be somewhat sequence-context-dependent. These findings demonstrate the importance of the m6A modification in stabilising and enhancing expression from IVT-derived mRNA and that this occurs within the cell, meaning targeted in vitro chemical modification during mRNA manufacturing may not be necessary. Full article

Nowadays, the automotive industry is primarily driven by the CO₂ policy that targets net zero carbon emissions by 2035 from passenger cars and commercial vehicles. The main path to achieve this goal is the implementation of electric powertrains with the energy stored in batteries, as the case for battery electric vehicles (BEV). However, this technology still faces some difficulties in terms of energy density, overall weight, charging time, and vehicle autonomy. From the other point of view, fuel cell electric vehicles (FCEV) offer the same advantages as BEV in terms of CO₂ reduction, providing better autonomy and lower refueling time. The energy demand by the electric powertrain strongly depends on the vehicle driving conditions as it directly affects energy consumption. In that context, the article aims to study the electrical energy demand of an ultra-energy efficient vehicle intended for a Shell eco-marathon competition in order to minimize hydrogen consumption. The study was carried out over a single lap on the racing track in Nogaro, France while applying the race rules from the competition in 2023. It includes a numerical evaluation of the vehicle resistance forces in different driving strategies and experimental validation on the propulsion test bench. Full article

Eco-friendly driving, defined as an individual’s daily driving practices that reduce fuel and energy consumption, remains significantly underutilized despite growing attention to climate change and sustainability. Given that changes in consumer behaviour are central to sustainability transitions and strongly influenced by how individuals perceive sustainability-related information, this study investigates the psychological and structural barriers that shape consumers’ perceptions of eco-friendly driving. A scoping review of empirical research on these barriers (Study 1), informed by Gifford’s “dragons of inaction,” combined with 50 semi-structured interviews (Study 2) conducted in a highly car-dependent regional context, provides convergent evidence on the complex factors shaping consumer behaviour in sustainable mobility. Across both studies, consistent psychological barriers emerged, including limited awareness of eco-driving techniques, doubts about effectiveness, emotional responses such as stress or range anxiety, and habitual reliance on conventional driving. Structural barriers such as inadequate infrastructure, limited charging accessibility, economic constraints, and weak policy support further constrained perceived feasibility. Evidence from both studies showed that these barriers reinforce one another, intensifying scepticism and reducing engagement with sustainability initiatives and messages. The findings contribute to research on sustainable consumer behaviour and sustainability communication by showing how internal and external constraints jointly shape eco-friendly driving decisions. Practically, the results highlight opportunities for coordinated infrastructure, policy, and communication strategies to support broader adoption of eco-friendly driving behaviours. Full article

This paper presents the concepts of a vehicle pressure regulation ventilation system based on the results of absolute pressure measurements in land transport vehicles: passenger cars, buses and trains. Despite the fact that absolute pressure affects human well-being and health, this parameter is often overlooked in studies assessing thermal comfort. Absolute pressure measurements were taken during normal passenger transport operation. The studies were conducted for various terrain types: lowlands, highlands, and mountains. Absolute pressure fluctuations in land transport depended primarily on altitude, with the largest atmospheric pressure differences recorded in mountains and the smallest in lowlands. A pressure change of 8 hPa within a 24 h period constitutes an unfavorable mechanical stimulus for the human body and causes changes in the excitability of the nervous system. In all measurement series, absolute pressure fluctuations exceeded 8 hPa. Based on the results of absolute pressure measurements and altitude, a simplified model for predicting absolute pressure in transport vehicles was developed. To reduce absolute pressure fluctuations inside passenger land vehicle cabins, a ventilation scheme regulating pressure inside land vehicle cabins was proposed. Full article