A Dynamic Path-Planning Method for Obstacle Avoidance Based on the Driving Safety Field

Establishing an accurate and computationally efficient model for driving risk assessment, considering the influence of vehicle motion state and kinematic characteristics on path planning, is crucial for generating safe, comfortable, and easily trackable obstacle avoidance paths. To address this topic, this paper proposes a novel dual-layered dynamic path-planning method for obstacle avoidance based on the driving safety field (DSF). The contributions of the proposed approach lie in its ability to address the challenges of accurately modeling driving risk, efficient path smoothing and adaptability to vehicle kinematic characteristics, and providing collision-free, curvature-continuous, and adaptable obstacle avoidance paths. In the upper layer, a comprehensive driving safety field is constructed, composed of a potential field generated by static obstacles, a kinetic field generated by dynamic obstacles, a potential field generated by lane boundaries, and a driving field generated by the target position. By analyzing the virtual field forces exerted on the ego vehicle within the comprehensive driving safety field, the resultant force direction is utilized as guidance for the vehicle’s forward motion. This generates an initial obstacle avoidance path that satisfies the vehicle’s kinematic and dynamic constraints. In the lower layer, the problem of path smoothing is transformed into a standard quadratic programming (QP) form. By optimizing discrete waypoints and fitting polynomial curves, a curvature-continuous and smooth path is obtained. Simulation results demonstrate that our proposed path-planning algorithm outperforms the method based on the improved artificial potential field (APF). It not only generates collision-free and curvature-continuous paths but also significantly reduces parameters such as path curvature (reduced by 62.29% to 87.32%), curvature variation rate, and heading angle (reduced by 34.11% to 72.06%). Furthermore, our algorithm dynamically adjusts the starting position of the obstacle avoidance maneuver based on the vehicle’s motion state. As the relative velocity between the ego vehicle and the obstacle vehicle increases, the starting position of the obstacle avoidance path is adjusted accordingly, enabling the proactive avoidance of stationary or moving single and multiple obstacles. The proposed method satisfies the requirements of obstacle avoidance safety, comfort, and stability for intelligent vehicles in complex environments

Comparative Genomic Analysis of Shrimp-Pathogenic <i>Vibrio parahaemolyticus</i> LC and Intraspecific Strains with Emphasis on Virulent Factors of Mobile Genetic Elements

Vibrio parahaemolyticus exhibits severe pathogenicity in humans and animals worldwide. In this study, genome sequencing and comparative analyses were conducted for in-depth characterization of the virulence factor (VF) repertoire of V. parahaemolyticus strain LC, which presented significant virulence to shrimp Litopenaeus vannamei. Strain LC, harboring two circular chromosomes and three linear plasmids, demonstrated ≥98.14% average nucleotide identities with 31 publicly available V. parahaemolyticus genomes, including 13, 11, and 7 shrimp-, human-, and non-pathogenic strains, respectively. Phylogeny analysis based on dispensable genes of pan-genome clustered 11 out of 14 shrimp-pathogenic strains and 7 out of 11 clinical strains into two distinct clades, indicating the close association between host-specific pathogenicity and accessory genes. The VFDB database revealed that 150 VFs of LC were mainly associated with the secretion system, adherence, antiphagocytosis, chemotaxis, motility, and iron uptake, whereas no homologs of the typical pathogenic genes pirA, pirB, tdh, and trh were detected. Four genes, mshB, wbfT, wbfU, and wbtI, were identified in both types of pathogenic strains but were absent in non-pathogens. Notably, a unique cluster similar to Yen-Tc, which encodes an insecticidal toxin complex, and diverse toxin–antitoxin (TA) systems, were identified on the mobile genetic elements (MGEs) of LC. Conclusively, in addition to the common VFs, various unique MGE-borne VFs, including the Yen-Tc cluster, TA components, and multiple chromosome-encoded chitinase genes, may contribute to the full spectrum of LC virulence. Moreover, V. parahaemolyticus demonstrates host-specific virulence, which potentially drives the origin and spread of pathogenic factors

The Pathogenesis of Diabetes Mellitus by Oxidative Stress and Inflammation: Its Inhibition by Berberine

A substantial knowledge on the pathogenesis of diabetes mellitus (DM) by oxidative stress and inflammation is available. Berberine is a biologically active botanical that can combat oxidative stress and inflammation and thus ameliorate DM, especially type 2 DM. This article describes the potential of berberine against oxidative stress and inflammation with special emphasis on its mechanistic aspects. In diabetic animal studies, the modified levels of proinflammatory cytokines and oxidative stress markers were observed after administering berberine. In renal, fat, hepatic, pancreatic and several others tissues, berberine-mediated suppression of oxidative stress and inflammation was noted. Berberine acted against oxidative stress and inflammation through a very complex mechanism consisting of several kinases and signaling pathways involving various factors, including NF-κB (nuclear factor-κB) and AMPK (AMP-activated protein kinases). Moreover, MAPKs (mitogen-activated protein kinases) and Nrf2 (nuclear factor erythroid-2 related factor 2) also have mechanistic involvement in oxidative stress and inflammation. In spite of above advancements, the mechanistic aspects of the inhibitory role of berberine against oxidative stress and inflammation in diabetes mellitus still necessitate additional molecular studies. These studies will be useful to examine the new prospects of natural moieties against DM

Mechanism of Chinese Medicine Herbs Effects on Chronic Heart Failure Based on Metabolic Profiling

Chronic heart failure (CHF) is a major public health problem in huge population worldwide. The detailed understanding of CHF mechanism is still limited. Zheng (syndrome) is the criterion of diagnosis and therapeutic in Traditional Chinese Medicine (TCM). Syndrome prediction may be a better approach for understanding of CHF mechanism basis and its treatment. The authors studied disturbed metabolic biomarkers to construct a predicting mode to assess the diagnostic value of different syndrome of CHF and explore the Chinese herbal medicine (CHM) efficacy on CHF patients. A cohort of 110 patients from 11 independent centers was studied and all patients were divided into 3 groups according to TCM syndrome differentiation: group of Qi deficiency syndrome, group of Qi deficiency and Blood stasis syndrome, and group of Qi deficiency and Blood stasis and Water retention syndrome. Plasma metabolomic profiles were determined by UPLC-TOF/MS and analyzed by multivariate statistics. About 6 representative metabolites were highly possible to be associated with CHF, 4, 7, and 5 metabolites with Qi deficiency syndrome, Qi deficiency and Blood stasis syndrome, and Qi deficiency and Blood stasis and Water retention syndrome (VIP &gt; 1, p &lt; 0.05). The diagnostic model was further constructed based on the metabolites to diagnose other CHF patients with satisfying sensitivity and specificity (sensitivity and specificity are 97.1 and 80.6% for CHF group vs. NH group; 97.1 and 80.0% for QD group vs. NH group; 97.1 and 79.5% for QB group vs. NH group; 97.1 and 88.9% for QBW group vs. NH group), validating the robustness of plasma metabolic profiling to diagnostic strategy. By comparison of the metabolic profiles, 9 biomarkers, 2-arachidonoylglycerophosphocholine, LysoPE 16:0, PS 21:0, LysoPE 20:4, LysoPE 18:0, linoleic acid, LysoPE 18:2, 4-hydroxybenzenesulfonic acid, and LysoPE 22:6, may be especially for the effect of CHM granules. A predicting model was attempted to construct and predict patient based on the related symptoms of CHF and the potential biomarkers regulated by CHM were explored.This trial was registered with NCT01939236 (https://clinicaltrials.gov/)

VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results

Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing on crowd counting on the drone-captured data due to the lack of comprehensive datasets. To this end, we collect a large-scale dataset and organize the Vision Meets Drone Crowd Counting Challenge (VisDrone-CC2020) in conjunction with the 16th European Conference on Computer Vision (ECCV 2020) to promote the developments in the related fields. The collected dataset is formed by 3, 360 images, including 2, 460 images for training, and 900 images for testing. Specifically, we manually annotate persons with points in each video frame. There are 14 algorithms from 15 institutes submitted to the VisDrone-CC2020 Challenge. We provide a detailed analysis of the evaluation results and conclude the challenge. More information can be found at the website: http://www.aiskyeye.com/

Maresin 1 attenuates mitochondrial dysfunction through the ALX/cAMP/ROS pathway in the cecal ligation and puncture mouse model and sepsis patients.

Inflammation always accompanies infection during sepsis. Mitochondrial dysfunction and the role of reactive oxygen species (ROS) produced by mitochondria have been proposed in the pathogenesis of sepsis. Maresins have protective and resolving effects in experimental models of infection. In the present study, we investigated the effects of maresin 1 (MaR1) on mitochondrial function in cecal ligation and puncture (CLP)-induced sepsis and sepsis patients to identify mechanisms underlying maresin 1-mediated stimulation of ROS in mitochondria. We found that treatment with MaR1 significantly inhibited production of cytokines, decreased bacterial load in the peritoneal lavage fluid, reduced the number of neutrophils, decreased lactic acid level and upregulated cyclic AMP (cAMP) concentration, with the outcome of decreased lung injury in CLP-induced sepsis in mice. The effects of MaR1 on downregulation nitric oxide (NOX) activity, improvement CAT and SOD activity to inhibit ROS production in mitochondria was dependent on lipoxin receptor (ALX) and cAMP. Survival rates were significantly increased after the treatment of mice with MaR1. In BMDM stimulated with LPS, MaR1 inhibited the ROS production, downregulated enzyme activity, reduced mtO2 production, increased mitochondrial membrane potential, improved adenosine triphosphate (ATP) content and mitochondrial DNA (mtDNA) copy number. Finally, the effects of MaR1 on ROS production in the blood of healthy volunteers stimulated with LPS or sepsis patients were associated with ALX and cAMP. Taken together, these data suggest that treatment with MaR1 could attenuate mitochondrial dysfunction during sepsis through regulating ROS production