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Full drive-by-wire electric vehicles (FDWEV) with X-by-wire technology can achieve independent driving, braking, and steering of each wheel, providing a good application platform for autonomous driving technology. Path planning and tracking control, in particular, are critical components of autonomous driving. However, It is challenging to comprehensively design an robust control algorithm by integrating vehicle path planning in a complicated unstructured scenario for FDWEV. To address the above issue, this paper first proposes the artificial potential field (APF) method for path planning in the prescribed park with different static obstacles to generate the reference path information, where speed planning is incorporated considering kinematics and dynamic constraints. Second, two tracking control methods, curvature calculation (CC-based) and model predictive control (MPC-based) methods with the lateral dynamics model, are proposed to track the desired path under different driving conditions, in which a forward-looking behavior model of the driver with variable preview distance is designed based on fuzzy control theory. CarSim-AMESim-Simulink co-simulation is conducted with the existence of obstacles. The simulation results show that the proposed two control approaches are effective for many driving scenarios and the MPC-based path-tracking controller enhances dynamic tracking performance and ensures good maneuverability under high-dynamic driving conditions.

The growing adoption of hybrid electric vehicles (HEVs) presents a transformative opportunity for revolutionizing transportation energy systems. The shift towards electrifying transportation aims to curb environmental concerns related to fossil fuel consumption. This necessitates efficient energy management systems (EMS) to optimize energy efficiency. The evolution of EMS from HEVs to connected hybrid electric vehicles (CHEVs) represent a pivotal shift. For HEVs, EMS now confronts the intricate energy cooperation requirements of CHEVs, necessitating advanced algorithms for route optimization, charging coordination, and load distribution. Challenges persist in both domains, including optimal energy utilization for HEVs, and cooperative eco-driving control (CED) for CHEVs across diverse vehicle types. Reinforcement learning (RL) stands out as a promising tool for addressing these challenges. Specifically, within the realm of CHEVs, the application of multi-agent reinforcement learning (MARL) emerges as a powerful approach for effectively tackling the intricacies of CED control. Despite extensive research, few reviews span from individual vehicles to multi-vehicle scenarios. This review bridges the gap, highlighting challenges, advancements, and potential contributions of RL-based solutions for future sustainable transportation systems.

Background & Aims: The association between sarcopenia and prognosis in patients with cirrhosis remains to be determined. In this study, we aimed to quantify the association between sarcopenia and the risk of mortality in patients with cirrhosis, stratified by sex, underlying liver disease etiology, and severity of hepatic dysfunction. Methods: PubMed, Web of Science, EMBASE, and major scientific conference sessions were searched without language restriction through 13 January 2021 with an additional manual search of bibliographies of relevant articles. Cohort studies of ≥100 patients with cirrhosis and ≥12 months of follow-up that evaluated the association between sarcopenia, muscle mass and the risk of mortality were included. Results: Twenty-two studies involving 6,965 patients with cirrhosis were included. The pooled prevalence of sarcopenia in patients with cirrhosis was 37.5% overall (95% CI 32.4%-42.8%), and was higher in male patients, those with alcohol-associated liver disease, those with Child-Pugh grade C cirrhosis, and when sarcopenia was defined by L3-SMI (third lumbar-skeletal muscle index). Sarcopenia was associated with an increased risk of mortality in patients with cirrhosis (adjusted hazard ratio [aHR] 2.30, 95% CI 2.01-2.63), with similar findings in a sensitivity analysis of patients with cirrhosis without hepatocellular carcinoma (aHR 2.35, 95% CI 1.95-2.83) and in subgroups stratified by sex, liver disease etiology, and severity of hepatic dysfunction. The association between quantitative muscle mass index and mortality further supports the association between sarcopenia and poor prognosis (aHR 0.95, 95% CI 0.93-0.98). There was no significant heterogeneity in any of our analyses. Conclusions: Sarcopenia was highly and independently associated with higher risk of mortality in patients with cirrhosis. Lay summary: The prevalence of sarcopenia and its association with death in p

Ning Xie,1,2,* Yifei Pan,3,* Jian Wu,4 Yunfan Bai,3 Cailan Xiao,1,2 Xiaoliang Gao,4 Jinhai Wang,1,2 Na Liu1,2 1Department of Gastroenterology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 2Shaanxi Key Laboratory of Gastrointestinal Motility Disorders, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 3Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Japan; 4Xijing Hospital of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi’an, Shaanxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Na Liu; Jinhai Wang Email liuna1@xjtu.edu.cn; jinhaiwang@hotmail.comBackground: Our previous studies demonstrate that ARL4C is the most critical clinical biomarker for gastric cancer (GC) patients among ARL family members (ARLs) and functions as an oncogene in GC. However, its underlying mechanisms in GC need to be further illustrated. In this study, we aim to explore the upstream and downstream molecular mechanisms of ARL4C in GC cells.Methods: The genetic alteration of ARL4C in GC is analyzed by cBioPortal database. Potential ARL4C-targeted microRNAs (miRs) are predicted by three databases. The high-throughput RNA sequencing is performed to explore the underlying mechanisms of ARL4C in GC cells. The effects of predicted microRNAs on ARL4C, the RNA-sequencing results validation and the biological functions of ARL4C in GC cells are illustrated by in vitro experiments.Results: Genetic analyses indicate that ARL4C is significantly upregulated in GC, which is not caused by gene amplification. MicroRNAs prediction shows the high relevance between ARL4C and miR-302 members. Moreover, miR-302c or miR-302d transfection reduces ARL4C protein expression in GC cells. Based on the high-through

p97 is a AAA-ATPase with multiple cellular functions, one of which is critical regulation of protein homeostasis pathways. We describe the characterization of CB-5083, a potent, selective, and orally bioavailable inhibitor of p97. Treatment of tumor cells with CB-5083 leads to accumulation of poly-ubiquitinated proteins, retention of endoplasmic reticulum-associated degradation (ERAD) substrates, and generation of irresolvable proteotoxic stress, leading to activation of the apoptotic arm of the unfolded protein response. In xenograft models, CB-5083 causes modulation of key p97-related pathways, induces apoptosis, and has antitumor activity in a broad range of both hematological and solid tumor models. Molecular determinants of CB-5083 activity include expression of genes in the ERAD pathway, providing a potential strategy for patient selection.