Real-time Data Flow Control for CBM-TOF Super Module Quality Evaluation

Super module assembled with MRPC detectors is the component unit of TOF (Time of Flight) system for the Compressed Baryonic Matter (CBM) experiment. Quality of super modules needs to be evaluated before it is applied in CBM-TOF. Time signals exported from super module are digitalized at TDC (Time to Digital Converter) station. Data rate is up to 6 Gbps at each TDC station, which brings a tremendous pressure for data transmission in real time. In this paper, a real-time data flow control method is designed. In this control method, data flow is divided into 3 types: scientific data flow, status data flow and control data flow. In scientific data flow, data of each TDC station is divided into 4 sub-flows, and then is read out by a parallel and hierarchical network, which consists of multiple readout mother boards and daughter boards groups. In status data flow, status data is aggregated into a specific readout mother board. Then it is uploaded to DAQ via readout daughter board. In control data flow, control data is downloaded to all circuit modules in the opposite direction of status data flow. Preliminary test result indicated data of STS was correctly transmitted to DAQ with no error and three type data flows were control orderly in real time. This data flow control method can meet the quality evaluation requirement of supper module in CBM-TOF

Deep Reinforcement Learning-based Multi-objective Path Planning on the Off-road Terrain Environment for Ground Vehicles

Due to the energy-consumption efficiency between up-slope and down-slope is hugely different, a path with the shortest length on a complex off-road terrain environment (2.5D map) is not always the path with the least energy consumption. For any energy-sensitive vehicles, realizing a good trade-off between distance and energy consumption on 2.5D path planning is significantly meaningful. In this paper, a deep reinforcement learning-based 2.5D multi-objective path planning method (DMOP) is proposed. The DMOP can efficiently find the desired path with three steps: (1) Transform the high-resolution 2.5D map into a small-size map. (2) Use a trained deep Q network (DQN) to find the desired path on the small-size map. (3) Build the planned path to the original high-resolution map using a path enhanced method. In addition, the imitation learning method and reward shaping theory are applied to train the DQN. The reward function is constructed with the information of terrain, distance, border. Simulation shows that the proposed method can finish the multi-objective 2.5D path planning task. Also, simulation proves that the method has powerful reasoning capability that enables it to perform arbitrary untrained planning tasks on the same map

Genome-wide characterization of heavy metal-associated isoprenylated plant protein gene family from Citrus sinensis in response to huanglongbing

IntroductionHeavy metal-associated isoprenylated plant proteins (HIPPs) play vital roles in maintaining heavy metal balance and responding to both biotic and abiotic stresses in vascular plants. However, the role of HIPPs in the response to Huanglongbing (HLB), a harmful disease of citrus caused by the phloem-colonizing bacterium Candidatus Liberibacter asiaticus (CLas), has not been examined.Methods and resultsIn this study, a total of 26 HIPP genes were identified in Citrus sinensis, and they were grouped into 5 clades. The CsHIPP genes are distributed on 8 chromosomes and exhibited considerable synteny with HIPPs found in Arabidopsis thaliana. Additionally, we analyzed the gene structure, conserved motifs and domains of the CsHIPPs. Various cis-acting elements related to plant hormones and stress responses were identified in the promoters of CsHIPPs. Public transcriptome data and RT-qPCR analysis showed that the expression level of CsHIPP03 was significantly reduced in samples infected by CLas and Xanthomonas citri ssp. citri (Xcc). Furthermore, silencing the homologous gene of CsHIPP03 in Nicotiana benthamiana increased the disease resistance of plants to bacteria.DiscussionOur results provide a basis for functional studies of HIPP gene family in C. sinensis, highlighting their functions in bacterial resistance, and improve our understanding to the susceptibility mechanism of HLB

Psychological symptoms in Chinese nurses may be associated with predisposition to chronic disease: A cross-sectional study of suboptimal health status

© 2020, The Author(s). Background: Suboptimal health status (SHS) is a reversible state between ideal health and illness and it can be effectively reversed by risk prediction, disease prevention, and personalized medicine under the global background of predictive, preventive, and personalized medicine (PPPM) concepts. More and more Chinese nurses have been troubled by psychological symptoms (PS). The correlation between PS and SHS is unclear in nurses. The purpose of current study is to investigate the prevalence of SHS and PS in Chinese nurses and the relationship between SHS and PS along with predisposing factors as well as to discuss the feasibility of improving health status and preventing diseases according to PPPM concepts in Chinese nurses. Methods: A cross-sectional study was conducted with the cluster sampling method among 9793 registered nurses in Foshan city, China. SHS was evaluated with the Suboptimal Health Status Questionnaire-25 (SHSQ-25). Meanwhile, the PS of depression and anxiety were evaluated with Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS) self-assessment questionnaires. The relationship between PS and SHS in Chinese nurses was subsequently analyzed. Results: Among the 9793 participants, 6107 nurses were included in the final analysis. The prevalence of SHS in the participants was 74.21% (4532/6107) while the symptoms of depression and anxiety were 47.62% (2908/6107) and 24.59% (1502/6107) respectively. The prevalence of SHS in the participants with depression and anxiety was significantly higher than those without the symptoms of depression (83.3% vs 16.7%, P \u3c 0.001) and anxiety (94.2% vs 5.8%, P \u3c 0.0001). The ratio of exercise habit was significantly lower than that of non-exercise habit (68.8% vs 78.4%, P \u3c 0.001) in SHS group. Conclusions: There is a high prevalence of SHS and PS in Chinese nurses. PS in Chinese nurses are associated with SHS. Physical exercise is a protective factor for SHS and PS so that the exercise should be strongly recommended as a valuable preventive measure well in the agreement with PPPM philosophy. Along with SDS and SAS, SHSQ-25 should also be highly recommended and applied as a novel predictive/preventive tool for the health measures from the perspectives of PPPM in view of susceptible population and individual screening, the predisposition to chronic disease preventing, personalization of intervention, and the ideal health state restoring

Deep Reinforcement Learning-Based 2.5D Multi-Objective Path Planning for Ground Vehicles: Considering Distance and Energy Consumption

Due to the vastly different energy consumption between up-slope and down-slope, a path with the shortest length in a complex off-road terrain environment (2.5D map) is not always the path with the least energy consumption. For any energy-sensitive vehicle, realizing a good trade-off between distance and energy consumption in 2.5D path planning is significantly meaningful. In this paper, we propose a deep reinforcement learning-based 2.5D multi-objective path planning method (DMOP). The DMOP can efficiently find the desired path in three steps: (1) transform the high-resolution 2.5D map into a small-size map, (2) use a trained deep Q network (DQN) to find the desired path on the small-size map, and (3) build the planned path to the original high-resolution map using a path-enhanced method. In addition, the hybrid exploration strategy and reward-shaping theory are applied to train the DQN. The reward function is constructed with the information of terrain, distance, and border. The simulation results show that the proposed method can finish the multi-objective 2.5D path planning task with significantly high efficiency and quality. Also, simulations prove that the method has powerful reasoning capability that enables it to perform arbitrary untrained planning tasks

NakhlehLab/MaCroDNA: MaCroDNA

<p>This is the first release of MaCroDNA (Matching Cross-Domain Nucleic Acids). MaCroDNA is a tool for integration of single-cell RNA and DNA data sequenced by high-throughput single-cell sequencing technologies. MaCroDNA uses maximum weighted bipartite matching of per-gene read counts from single-cell copy number and gene expression data to find the correspondence between the single cells from the two modalities. This repository contains the source code for MaCroDNA described in the paper "Accurate integration of single-cell DNA and RNA for analyzing intratumor heterogeneity using MaCroDNA" along with the scripts necessary for reproducing the results and the figures presented in the paper.</p&gt

Systematic analysis of the thioredoxin gene family in Citrus sinensis: identification, phylogenetic analysis, and gene expression patterns

Thioredoxin (TRX) proteins play essential roles in reactive oxygen species scavenging in plants. We executed an exhaustive analysis of the TRX gene family in Citrus sinensis (CsTRXs), encompassing identification, phylogenetic analysis, detection of conserved motifs and domains, gene structure, cis-acting elements, gene expression trends, and subcellular localization analysis. Our findings established that a total of 22 CsTRXs with thioredoxin domains were identified in the genome of C. sinensis. Phylogenetic analysis indicated that CsTRXs were divided into six subclusters. Conserved motifs analysis of CsTRXs indicated a wide range of conserved motifs. A significant number of cis-acting elements associated with both abiotic and biotic stress responses, inclusive of numerous phytohormone-related elements, were detected in the promoter regions of CsTRXs. The expression levels of CsTRXs including CsTRXf1, CsTRXh1, CsTRXm1, CsTRXo3, CsTRXx2 and CsTRXy1 were observed to be reduced upon pathogen infection. Subcellular localization analysis found that CsTRXf1, CsTRXm1, CsTRXo3, CsTRXx2 and CsTRXy1 were predominantly localized in chloroplasts, whereas CsTRXh1 was distributed indiscriminately. This research yields integral data on CsTRXs, facilitating future efforts to decipher the gene functions of CsTRXs