Search Results (3)

Urban growth and rising vehicle usage have intensified congestion, accidents, and environmental impact, exposing the limitations of traditional traffic management systems. This study introduces a dual-incident simulation framework to investigate the potential of Vehicle-to-Everything (V2X) technologies in enhancing urban mobility. Using the Eclipse MOSAIC platform integrated with SUMO, a realistic network in Iași, Romania, was modeled under single- and dual-incident scenarios with three V2X penetration levels: 0%, 50%, and 100%. Unlike prior works that focus on single-incident cases or assume full penetration, our approach evaluates cascading disruptions under partial adoption, providing a more realistic transition path for mid-sized European cities. Key performance indicators, i.e., average speed, vehicle density, time loss, and waiting time, were calculated using mathematically defined formulas and validated across multiple simulation runs. Results demonstrate that full V2X deployment reduces average time loss by 18% and peak density by more than 70% compared to baseline conditions, while partial adoption delivers measurable yet limited benefits. The dual-incident scenario shows that V2X-enabled rerouting significantly mitigates cascading congestion effects. These contributions advance the state of the art by bridging microscopic vehicle dynamics with network-level communication modeling, offering quantitative insights for phased V2X implementation and the design of resilient, sustainable intelligent transportation systems. Full article

Designing an efficient task offloading system is essential in the Industrial Internet of Things (IIoT). Owing to the limited computational capability of IIoT devices, offloading tasks to edge servers enhances computational efficiency. When an edge server is overloaded, it may experience interruptions, preventing it from serving local devices. Existing studies mainly address interruptions by rerouting, rescheduling, or implementing reactive strategies to mitigate their impact. In this study, we introduce an interruption-aware proactive task offloading framework for IIoT. We develop a load-based interruption model in which the probability of server interruption is formulated as an exponential function of the total computational load, which provides a more realistic estimation of service availability. This framework employs Multi-Agent Advantage Actor–Critic (MAA2C)—a simple yet efficient approach that enables decentralized decision-making while handling large action spaces and maintaining coordination through the centralized critic to make adaptive offloading decisions, taking into account edge availability, resource limitations, device cooperation, and interruptions. Experimental results show that our approach effectively reduces the average total service delay by optimizing the tradeoff between system delay and availability in IIoT networks. Additionally, we investigate the impact of various system parameters on performance under an interruptible edge task offloading scenario, providing valuable insights into how these parameters influence the overall system behavior and efficiency. Full article

Most mitochondrial proteins are synthesized in the cytosol and targeted to the mitochondrial surface in a post-translational manner. The surface of the endoplasmic reticulum (ER) plays an active role in this targeting reaction. ER-associated chaperones interact with certain mitochondrial membrane protein precursors and transfer them onto receptor proteins of the mitochondrial surface in a process termed ER-SURF. ATP-driven proteins in the membranes of mitochondria (Msp1, ATAD1) and the ER (Spf1, P5A-ATPase) serve as extractors for the removal of mislocalized proteins. If the re-routing to mitochondria fails, precursors can be degraded by ER or mitochondria-associated degradation (ERAD or MAD respectively) in a proteasome-mediated reaction. This review summarizes the current knowledge about the cooperation of the ER and mitochondria in the targeting and quality control of mitochondrial precursor proteins. Full article