A Hierarchical Hybrid Learning Framework for Multi-agent Trajectory Prediction

Accurate and robust trajectory prediction of neighboring agents is critical for autonomous vehicles traversing in complex scenes. Most methods proposed in recent years are deep learning-based due to their strength in encoding complex interactions. However, unplausible predictions are often generated since they rely heavily on past observations and cannot effectively capture the transient and contingency interactions from sparse samples. In this paper, we propose a hierarchical hybrid framework of deep learning (DL) and reinforcement learning (RL) for multi-agent trajectory prediction, to cope with the challenge of predicting motions shaped by multi-scale interactions. In the DL stage, the traffic scene is divided into multiple intermediate-scale heterogenous graphs based on which Transformer-style GNNs are adopted to encode heterogenous interactions at intermediate and global levels. In the RL stage, we divide the traffic scene into local sub-scenes utilizing the key future points predicted in the DL stage. To emulate the motion planning procedure so as to produce trajectory predictions, a Transformer-based Proximal Policy Optimization (PPO) incorporated with a vehicle kinematics model is devised to plan motions under the dominant influence of microscopic interactions. A multi-objective reward is designed to balance between agent-centric accuracy and scene-wise compatibility. Experimental results show that our proposal matches the state-of-the-arts on the Argoverse forecasting benchmark. It's also revealed by the visualized results that the hierarchical learning framework captures the multi-scale interactions and improves the feasibility and compliance of the predicted trajectories

Effect of Wuling powder on the pharmacokinetics of valproic acid in epileptic rats

Purpose: To investigate the effect of Wuling powder (WP) on the pharmacokinetics of valproic acid (VPA) in epileptic rats.Methods: A model of epilepsy was established in SD rats by intraperitoneal injection of pentylenetetrazole (PTZ). Twelve epileptic rats were randomly divided into two groups: control group given oral VPA alone at a dose of 180 mg/kg VPA, and drug combination group orally given VPA (180 mg/kg) co-administered with WP at a dose of 200 mg/kg. Blood sample (0.5 mL) was collected at 15, 30, 60, 120, 240 and 720 min after drug administration for measurement of plasma concentrations of VPA using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).Results: The AUC (0-480min) and maximum plasma concentrations (Cmax) of VPA in the drug combination group were significantly higher than those in the control group (p < 0.01). The half-time (t1/2) and time taken to attain maximum plasma VPA concentration (Tmax) in the combination group were extended, when compared to control group (p < 0.05).Conclusion: These results demonstrate that WP increases the plasma concentration of VPA and affects the pharmacokinetic properties of VPA in epileptic rats. Thus, the pharmacodynamic influence of this interaction should be taken into consideration while prescribing WP to epileptic patients already taking VPA

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

A Two-Phase Cross-Modality Fusion Network for Robust 3D Object Detection

A two-phase cross-modality fusion detector is proposed in this study for robust and high-precision 3D object detection with RGB images and LiDAR point clouds. First, a two-stream fusion network is built into the framework of Faster RCNN to perform accurate and robust 2D detection. The visible stream takes the RGB images as inputs, while the intensity stream is fed with the intensity maps which are generated by projecting the reflection intensity of point clouds to the front view. A multi-layer feature-level fusion scheme is designed to merge multi-modal features across multiple layers in order to enhance the expressiveness and robustness of the produced features upon which region proposals are generated. Second, a decision-level fusion is implemented by projecting 2D proposals to the space of the point cloud to generate 3D frustums, on the basis of which the second-phase 3D detector is built to accomplish instance segmentation and 3D-box regression on the filtered point cloud. The results on the KITTI benchmark show that features extracted from RGB images and intensity maps complement each other, and our proposed detector achieves state-of-the-art performance on 3D object detection with a substantially lower running time as compared to available competitors

Beetroot (<i>Beta vulgaris</i>) Extract against <i>Salmonella</i> Typhimurium via Apoptosis-Like Death and Its Potential for Application in Cooked Pork

Salmonella Typhimurium is a common foodborne pathogen in meat and meat products, causing significant harm and losses to producers and consumers. The aim of this study was to investigate the antibacterial activity and possible mechanisms of beetroot (Beta vulgaris) extract against S. Typhimurium, as well as the application potential in cooked pork. The results suggested beetroot extract could inhibit S. Typhimurium with a minimum inhibitory concentration (MIC) of 20 mg/mL. After treatment with beetroot extract (1 or 2 MIC), S. Typhimurium exhibited the characteristics of apoptotic-like death (ALD), such as membrane depolarization, phosphatidylserine (PS) externalization, caspase-like protein activation, and DNA fragmentation. Further research has shown that the ALD induced by beetroot extract in S. Typhimurium was caused by reactive oxygen species (ROS) consumption, which was different from most natural products. The treatment of cooked pork with beetroot extract could reduce the number of S. Typhimurium, lower pH, defer lipid oxidation, and improve the colour. These results indicate that beetroot extract can inhibit S. Typhimurium through the ALD mechanism and has potential as an antibacterial agent against S. Typhimurium in ready-to-eat meat products

Analysis of safety climate and individual factors affecting bus drivers’ crash involvement using a two-level logit model

Although traffic crashes involving buses are less frequent than those involving other vehicle types, the consequences of bus crashes are high due to the potential for multiple injuries and casualties. As driver error is a primary factor affecting bus crashes, driver safety education is one of the main countermeasures used to mitigate crash risk. In China, however, safety education is not as focused as it should be, largely due to the limited research identifying the specific driver behaviors, and potential influences on those behaviors, that are correlated with crashes. The aim of this study is, therefore, to explore the fleet- and driver-level risk factors underlying bus drivers’ self-reported crash involvement, including analyzing the effect of psychological distress on the most influential driver-level factors. A survey was conducted of 725 drivers from a large Shanghai bus company, and a random-effects two-level logit model was developed to integrate fleet and individual variables. Results showed that: 1) the fleet-level safety climate explained about 8.5% of the model’s variance, indicating it was a valid predictor of self-reported crash involvement; 2) the driver-level factors of drivers’ age, seniority, marital status, positive behavior, and driving anger influenced drivers’ self-reported crash involvement, but ordinary violations, lapses, aggressive violations, and insomnia were the most influential variables; 3) psychological distress appeared to associate with the high frequency of risky driving behavior and the high severity of driving anger. This study’s findings will help bus companies to give more attention to their safety climate and implement more targeted improvements to their driver safety education programs

EP1 activation inhibits doxorubicin-cardiomyocyte ferroptosis via Nrf2

Chemotherapeutic agents, such as doxorubicin (DOX), may cause cardiomyopathy, even life-threatening arrhythmias in cancer patients. Ferroptosis-an iron-dependent oxidative form of programmed necrosis, plays a pivotal role in DOX-induced cardiomyopathy (DIC). Prostaglandins (PGs) are bioactive signaling molecules that profoundly modulate cardiac performance in both physiologic and pathologic conditions. Here, we found that PGE2 production and its E-prostanoid 1 receptor (EP1) expression were upregulated in erastin (a ferroptosis inducer) or DOX-treated cardiomyocytes. EP1 inhibition markedly aggravated erastin or DOX-induced cardiomyocyte ferroptosis, whereas EP1 activation exerted opposite effect. Genetic depletion of EP1 in cardiomyocytes worsens DOX-induced cardiac injury in mice, which was efficiently rescued by the ferroptosis inhibitor Ferrostatin-1 (Fer-1). Mechanistically, EP1 activation protected cardiomyocytes from DOX-induced ferroptosis by promoting nuclear factor erythroid 2-related factor 2 (Nrf2)-driven anti-oxidative gene expression, such as glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11). EP1 was coupled with Gαq to elicit intracellular Ca2+ flux and activate the PKC/Nrf2 cascade in ferroptotic cardiomyocytes. EP1 activation also prevents DOX-induced ferroptosis in human cardiomyocytes. Thus, PGE2/EP1 axis protects cardiomyocytes from DOX-induced ferroptosis by activating PKC/Nrf2 signaling and activation of EP1 may represent an attractive strategy for DIC prevention and treatment

Application of the ribosomal DNA ITS2 region of Physalis (Solanaceae): DNA barcoding and phylogenetic study

Recently, commercial interest in Physalis species has grown worldwide due to their high nutritional value, edible fruit and potential medicinal properties. However, many Physalis species have similar shapes and are easily confused, and consequently the phylogenetic relationships between Physalis species are poorly understood. This hinders their safe utilization and genetic resource conservation. In this study, the nuclear ribosomal ITS2 region was used to identify species and phylogenetically examine Physalis. Eighty-six ITS2 regions from 45 Physalis species were analyzed. The ITS2 sequences were aligned using Clustal W and genetic distances were calculated using MEGA V6.0. The results showed that ITS2 regions have significant intra- and inter-specific divergences, obvious barcoding gaps, and higher species discrimination rates (82.2% for both the BLASTA1 and nearest distance methods). In addition, the secondary structure of ITS2 provided another way to differentiate species. Cluster analysis based on ITS2 regions largely concurred with the relationships among Physalis species established by many previous molecular analyses, and showed that most sections of Physalis appear to be polyphyletic. Our results demonstrated that ITS2 can be used as an efficient and powerful marker in the identification and phylogenetic study of Physalis species. The technique provides a scientific basis for the conservation of Physalis plants and for utilization of resources