Search Results (39)

Carbonic anhydrase 3 (CA3) exhibits low enzymatic activity compared to other CA isoforms but contains two surface-exposed cysteine residues that undergo glutathionylation under oxidative stress. Highly expressed in muscle tissue, CA3 has been implicated in cellular protection, particularly through interactions with Bcl2-Associated Athanogene 3 (BAG3), modulating autophagy, while CA3 overexpression decreased hypoxia-induced apoptosis in cardiomyocytes. In this study, we investigated the impact of CA3 overexpression on cellular pathways in HEK293T, MDA-MB-231, and SVCT cells using RNA sequencing and proteomics. Gene Set Enrichment Analysis (GSEA) in HEK293T cells revealed the down-regulation of pathways related to protein synthesis, RNA processing, Roundabout signalling, selenocysteine-metabolism, and suppression of neurodegenerative disease-associated pathways. Human breast epithelial cell lines under normoxia and hypoxia showed down-regulation of similar pathways, although notably, hypoxic conditions also suppressed interferon α/β signalling. Proteomic analysis in HEK293T cells using HaloTag pull-down experiments identified putative novel CA3 binding partners, including heat shock 70 kDa proteins 1 and 8, and ribosomal protein S2 (RPS2). RANBP2 protein was consistently up-regulated after CA3 overexpression, irrespective of the presence of CA3 surface-exposed cysteines and HaloTag orientation. These findings suggest that CA3 modulates key cellular processes beyond its enzymatic role, contributing to stress resilience through pathway-level regulation and protein interactions, potentially impacting autophagy and neurodegenerative disease. Full article

Safety remains a central challenge in autonomous driving: overly rigid safeguards can cause unnecessary stops and erode efficiency. Addressing this safety–efficiency trade-off requires specifying what behaviors to incentivize. In reinforcement learning, the reward provides that specification. Conventional reward surrogates—such as distance gaps and time-to-collision (TTC)—depend on instantaneous geometry and often miss unfolding multi-vehicle interactions, whereas sparse terminal rewards provide no intermediate guidance. Accordingly, we adapt Safety Potential (SP)—a short-horizon, time-weighted path-overlap forecast—into a dense reward-shaping term that provides a predictive risk-aware signal for anticipatory throttle/brake control. In the CARLA v0.9.14 roundabout environment, SP attains 94% success with 3% collisions; in percentage points, this is 16.00, 13.00, and 5.75 higher success and 18.75, 9.50, and 7.25 lower collisions than No-Safe, Distance, and TTC, respectively. Adding a lightweight reactive guard at inference further reduces collisions to below 1% without sacrificing success. These results indicate that injecting a predictive, overlap-based risk measure directly into the reward supplies temporally consistent safety cues and clarifies the trade-off between progress and risk in reinforcement-learning-based vehicle control. Full article

Extreme weather events, such as storms, pose significant challenges to the reliability and efficiency of urban road networks, making intersection design and management critical to maintaining mobility. This paper addresses the dual objectives of traffic efficiency and resilience by evaluating the performance of roundabouts, signalized, and two-way stop-controlled (TWSC) intersections under normal and storm-disrupted conditions. A mixed-method approach was adopted, combining a heuristic framework from the Highway Capacity Manual with microsimulations in AIMSUN Next. Three Polish case studies were examined; each was modeled under alternative control strategies. The findings demonstrate the superior robustness of roundabouts, which retain functionality during power outages, while signalized intersections reveal vulnerabilities when control systems fail, reverting to less efficient TWSC behavior. TWSC intersections consistently exhibited the weakest performance, particularly under high or uneven traffic demand. Despite methodological differences in delay estimation, the convergence of results through Level of Service categories strengthens the reliability of findings. Beyond technical evaluation, the study underscores the importance of resilient intersection design in climate-vulnerable regions and the value of integrating analytical and simulation-based methods. By situating intersection performance within urban resilience, this research provides actionable insights for policymakers, planners, and engineers seeking to balance efficiency with adaptability in infrastructure planning. Full article

This research is part of a broader investigation into innovative simulation-based approaches for improving traffic efficiency and road safety in roundabout corridors. These corridors, composed of successive roundabouts along arterials, present systemic challenges due to the dynamic interactions between adjacent intersections. While previous studies have addressed localized inefficiencies or proposed isolated interventions, this paper introduces possible replicable methodology based on a microsimulation and surrogate safety analysis to evaluate roundabout corridors as integrated systems. In this context, efficiency refers to the ability of a road corridor to maintain stable traffic conditions under a given demand scenario, with low delay times corresponding to acceptable levels of service. Safety is interpreted as the minimization of vehicle conflicts and critical interactions, evaluated through surrogate measures derived from simulated vehicle trajectories. The proposed approach—implemented through Aimsun Next and the SSAM tool—is tested on two real-world corridors: Via Aurelia Nord in Pisa (Italy) and Route de Marseille in Avignon (France), assessing multiple intersection configurations that combine roundabouts and signal-controlled junctions. Results show how certain layouts can produce unexpected performance outcomes, underlining the importance of system-wide evaluations. The proposed framework aims to support engineers and planners in identifying optimal corridor configurations under realistic operating conditions. Full article

This paper presents a microsimulation-driven framework to analyze the performance of connected and automated vehicles (CAVs) alongside vehicles with human drivers (VHDs), channeled towards assessing project alternatives in road intersection design. The transition to fully automated mobility is driving the development of new intersection geometries and traffic configurations, influenced by increasing market entry rates (MERs) for CAVs (CAV-MERs), which were analyzed in a microsimulation environment. A suburban signalized intersection from the Polish road network was selected as a representative case study. Two alternative design hypotheses regarding the intersection’s geometric configurations were proposed. The Aimsun micro-simulator was used to hone the driving model parameters by calibrating the simulated data with reference capacity functions (RCFs) based on CAV factors derived from the Highway Capacity Manual 2022. Cross-referencing the conceptualized geometric design solutions, including a two-lane roundabout and an innovative knee-turbo roundabout, allowed the experimental results to demonstrate that CAV operation is influenced by the intersection layout and CAV-MERs. The research provides an overview of potential future traffic settings featuring CAVs and VHDs operating within various intersection designs. Additionally, the findings can support project proposals for the geometric and functional design of intersections by highlighting the potential benefits expected from smart driving. Full article

Gliomas are a type of highly heterogeneous and invasive central nervous system tumor. Traditional treatment methods have limited efficacy, and the prognosis for patients remains poor. Recent studies have revealed the crucial roles of several abnormal signaling pathways in the pathogenesis of gliomas, including the Receptor Tyrosine Kinase/Rat Sarcoma Virus Oncogene/Phosphatidylinositol-3-Kinase (RTK/RAS/PI3K) pathway, the Wingless-Related Integration Site/β-Catenin (Wnt/β-Catenin) pathway, the Hippo/YAP (Hippo/Yes-associated protein) pathway, and the Slit/Robo (Slit Guidance Ligands/Roundabout) signaling pathway. These pathways play extremely vital roles in tumor proliferation, invasion, and treatment resistance. This article comprehensively and systematically reviews the molecular mechanisms of these signaling pathways, deeply summarizing the research progress of various treatment strategies, including targeted inhibitors, gene therapy, and nanomedicine against them. Moreover, the combination of targeted therapy and personalized treatment regimens is expected to overcome the current treatment bottleneck and provide a more favorable survival prognosis for glioblastoma patients. Full article

This study investigated and compared driver behaviors at signalized and non-signalized roundabouts in Qatar, focusing on turn signal usage, lane change behavior, and correct lane usage. The primary objectives were to determine the frequency of turn signal usage, assess correct lane usage, analyze lane change behavior, and compare these behaviors between the two types of roundabouts. Data were collected through a field study at selected roundabouts, where driver behaviors were observed and analyzed. The results revealed significant differences between signalized and non-signalized roundabouts. Turn signal compliance was higher in signalized roundabouts (up to 45%) compared to non-signalized roundabouts (20%). The rate of lane change in signalized roundabouts was observed to be 31%, whereas it was 14% in non-signalized roundabouts, and correct lane usage compliance was higher in signalized roundabouts (60%) compared to non-signalized roundabouts (35%). These findings suggest that traffic signals contribute to safer and more predictable driver behavior, although congestion and long waiting times in signalized roundabouts present challenges. The study recommends improving signage visibility, optimizing signal timings, enhancing road markings, and enforcing traffic regulations to address these issues. The findings can inform traffic engineers and policymakers in enhancing the safety and efficiency of roundabouts. Full article

Traffic congestion in urban areas is a pressing challenge, with roundabouts and signalized intersections offering different operational benefits. This study explores the integration of these two intersection types, focusing on the optimal distance between them to ensure efficient traffic flow. Using traffic microsimulations in VISSIM, the research examines multiple scenarios involving isolated roundabouts and those adjacent to signalized intersections, considering variables such as peak-hour traffic volume, flow distribution, and intersection spacing. Results indicate that shorter distances (<50 m) between roundabouts and signalized intersections lead to increased traffic indicators due to congestion spillback. In contrast, distances exceeding 100 m mitigate these inefficiencies, approaching the performance of isolated roundabouts. Balanced traffic distribution between approaches (50:50) enhance system performance at lower volumes but exacerbate congestion at higher volumes. A novel aspect of this study is the development of a regression model that integrates microsimulation outputs to predict travel time based on peak-hour traffic volume, flow ratios, and intersection distance, demonstrating a 90.9% explanatory power. These findings emphasize the need for strategic planning in integrating roundabouts and signalized intersections to balance operational efficiency. Full article

Connected and automated vehicles (CAV) are growing in popularity and could have potential implications on the transportation system. The effects of CAVs have yet to be fully realized because of the newness of the technology. Anticipated effects include increased capacity, faster travel time, improved level of service, increased safety, and overall effectiveness of the transportation system. The Highway Capacity Manual (HCM) published by the Transportation Research Board of the National Academies has incorporated some of these impacts by developing capacity adjustment factors (CAFs) for various scenarios for freeway segments, signalized intersections, and roundabouts. This study builds upon the HCM study of signalized intersections by analyzing the effect CAVs have on a coordinated signalized corridor. Using PTV VISTRO and PTV VISSIM software a seven-intersection corridor along Eagle Road in Boise/Meridian, Idaho was modeled and analyzed with increasing penetration rates of CAVs. Approach delay, queue length, level of service, and travel time along the corridor were studied as CAV penetration rates increased. It was found that approach delay, queue length, and level of service (LOS) improved as the number of CAVs increased. As CAVs increased from 0% to 100%, the LOS increased from an E to an A at small intersections and from a D or F to C at large intersections. The travel time from one end of the corridor to the other decreased. Full article

Urban multilane roundabouts and signalized intersections are two major roadway devices used for controlling and managing traffic flow. This paper presents a comparative analysis of the saturation flow rate between urban multilane roundabouts and multilane signalized intersections using field data from the Dammam Metropolitan Area (DMA) in Saudi Arabia. The data of this study were collected at four roundabouts and four signalized intersections in Dammam metropolitan area (DMA), Saudi Arabia. A total of 7028 saturation headways at the roundabouts and 2626 saturation headways at the signalized intersections were included. The results indicated that the signalized intersections had a higher saturation flow rate at the exit lane than the roundabouts at about 1046 vehicles per hour. These findings emphasize that signalized intersections outperform roundabouts in terms of the vehicular movement rate during green lights. Moreover, when the light is green, it takes 1.82 s for a car to move through the middle lane of a traffic light intersection. This study draws a unique connection between speed fluctuations in roundabouts with energy consumption, concluding how vehicles consume more energy this way. Thus, single-lane roundabouts are recommended for optimal traffic flow management in all directions. Full article

This study combines Visible Light Communication (VLC) and Artificial Intelligence (AI) to optimize traffic signal control, reduce congestion, and enhance safety. Utilizing existing road infrastructure, VLC technology transmits real-time data on vehicle and pedestrian positions, speeds, and queues. AI agents, powered by Deep Reinforcement Learning (DRL), process these data to manage traffic flows dynamically, applying anti-bottlenecking and rerouting techniques. A global agent coordinates local agents, enabling indirect communication and a unified DRL model that adjusts traffic light phases in real time using a queue/request/response system. A key focus of this work is the design of reward functions for standard and rerouting scenarios. In standard scenarios, the reward function prioritizes wide green bands for vehicles while penalizing pedestrian rule violations, balancing efficiency and safety. In rerouting scenarios, it dynamically prevents queuing spillovers at neighboring intersections, mitigating cascading congestion and ensuring safe, timely pedestrian crossings. Simulation experiments in the SUMO urban mobility simulator and real-world trials validate the system across diverse intersection types, including four-way crossings, T-intersections, and roundabouts. Results show significant reductions in vehicle and pedestrian waiting times, particularly in rerouting scenarios, demonstrating the system’s scalability and adaptability. By integrating VLC technology and AI-driven adaptive control, this approach achieves efficient, safe, and flexible traffic management. The proposed system addresses urban mobility challenges effectively, offering a robust solution to modern traffic demands while improving the travel experience for all road users. Full article

Roundabouts are widely used in road transport to improve traffic flow and reduce congestion by enabling continuous movement in a circular pattern, minimizing stops, enhancing safety, and reducing delays compared to that of signaled intersections. However, roundabouts are rarely used in marine traffic. This study investigates the feasibility of redesigning existing rectangular precautionary areas within traffic separation schemes (TSSs) into circular roundabouts using marine traffic data incorporating both the number of ships passing and crossing, as well as microscopic movement data to further analyze the follow-up times and gaps based on ship domains. This study further assesses the overall performance of the proposed design, drawing on notable formulas and best practices in road transport. The Lombok Strait TSS, in Indonesia, is used as the study area, which is a particularly sensitive sea area and one of the critical “chokepoints” in the maritime supply chain. The results indicate that replacing rectangular areas with circular roundabouts in a TSS can significantly improve traffic management and navigation safety. This study offers a practical approach for redesigning rectangular precautionary areas into circular roundabouts and provides valuable insights for maritime authorities and policymakers aiming to develop more efficient TSS designs in the future. Full article

This study combines Visible Light Communication (VLC) and Artificial Intelligence (AI) to enhance traffic signal control, reduce congestion, and improve safety, through real-time monitoring and dynamic traffic management. Leveraging VLC technology, the system uses existing road infrastructure to transmit live data on vehicle and pedestrian positions, speeds, and queues. AI agents, employing Deep Reinforcement Learning (DRL), process this data to manage traffic flows dynamically, applying anti-bottleneck and rerouting techniques to balance pedestrian and vehicle waiting times. A centralized global agent coordinates the local agents controlling each intersection, enabling indirect communication and data sharing to train a unified DRL model. This model makes real-time adjustments to traffic light phases, utilizing a queue/request/response system for adaptive intersection management. Tested using simulations and real-world trials involving standard and rerouting scenarios, the approach demonstrates significantly better performance in regard to the rerouting configuration, reducing congestion and enhancing traffic flow and pedestrian safety. Scalable and adaptable to various intersection types, including four-way, T-intersections, and roundabouts, the system’s efficacy is validated using the SUMO urban mobility simulator, resulting in notable reductions to travel and waiting times for both vehicles and pedestrians. Full article

In contemporary times, one of the challenges in road traffic is the failure of drivers to adhere to traffic regulations. While the use of turn signals may seem trivial, the studies presented in this article demonstrate the significant impact that this practice can have on road traffic, both in terms of urban network capacity and fuel consumption, which consequently affects the emission of exhaust gases into the natural environment. A common example of the failure to use turn signals is when drivers navigate roundabouts. The example presented here analyzes an existing road network configuration consisting of two roundabouts and an intersection between them. The method of microsimulation was employed using the PTV Vissim 25 software. This study examined a scenario where the percentage of drivers adhering to the use of turn signals increased by 10% in each successive simulation version. The results clearly indicate that the capacity of the network, as well as the emissions of road pollutants, depend not only on traffic volume but also, most importantly, on traffic flow efficiency. Full article

This study focuses on optimizing traffic flow at uncontrolled intersections by comparing the effectiveness of different intersection types: roundabouts, signal-controlled intersections, and turbo-roundabouts. The purpose is to determine which type offers the best solution for enhancing traffic efficiency, reducing delays, and improving safety. The research employs simulation-based modeling to analyze traffic performance under varying traffic conditions. Critical parameters such as vehicle flow rate, average delay time, and capacity are used to assess the performance of each intersection type. The results indicate that turbo-roundabouts outperform conventional roundabouts and signal-controlled intersections in terms of both capacity and reduction in delays. The findings suggest that implementing turbo-roundabouts at high-traffic intersections can significantly improve traffic flow and reduce congestion. However, the effectiveness of each solution is context-dependent, with signal-controlled intersections still being advantageous under specific conditions, particularly in highly urbanized areas. This study provides valuable insights for transportation planners and engineers, highlighting the importance of intersection design in traffic optimization. Full article