32 research outputs found

    S-T CRF: Spatial-Temporal Conditional Random Field for Human Trajectory Prediction

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    Trajectory prediction is of significant importance in computer vision. Accurate pedestrian trajectory prediction benefits autonomous vehicles and robots in planning their motion. Pedestrians' trajectories are greatly influenced by their intentions. Prior studies having introduced various deep learning methods only pay attention to the spatial and temporal information of trajectory, overlooking the explicit intention information. In this study, we introduce a novel model, termed the \textbf{S-T CRF}: \textbf{S}patial-\textbf{T}emporal \textbf{C}onditional \textbf{R}andom \textbf{F}ield, which judiciously incorporates intention information besides spatial and temporal information of trajectory. This model uses a Conditional Random Field (CRF) to generate a representation of future intentions, greatly improving the prediction of subsequent trajectories when combined with spatial-temporal representation. Furthermore, the study innovatively devises a space CRF loss and a time CRF loss, meticulously designed to enhance interaction constraints and temporal dynamics, respectively. Extensive experimental evaluations on dataset ETH/UCY and SDD demonstrate that the proposed method surpasses existing baseline approaches

    Pharmacodynamics, metabolomics and pathological studies on mechanisms of traditional benefits of Angelica sinensis in blood circulation

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    Angelica sinensis is a rich source of medically important active molecules that need in-depth understanding on its action mechanisms. Therefore, through pharmacodynamics, metabolomics, and network pharmacology, the traditional benefits of A. sinensis in blood circulation was studied using 24 randomly selected Sprague-Dawley (SD) rats. Measurement of the blood rheological parameters for whole blood viscosity (WBV) and plasma viscosity (PV), and inspection of the heart and lung tissues pathological changes were undertaken using molecular and bioinformatic techniques. Multivariate statistical analysis and establishment of the model of the relationship between metabolite expression and sample categories to test the prediction of sample categories were performed. Screening was undertaken to find the potential metabolites for A. sinensis to treat blood stasis syndrome and find related metabolic pathways. Active ingredients of A. sinensis and targets and building of an “effect component-target” network was undertaken, A. sinensis was confirmed to improve blood stasis syndrome in rats and improve heart and lung pathology to varying degrees. Compared with the blood stasis model group, A. sinensis significantly reduced WBV and PV in hemorheology (p<0.05, p<0.01) and regulated blood stasis-induced changes in 22 metabolites including alpha-D-glucose, L-isoleucine, creatine and acetylcarnitine, which are involved in the metabolism of linoleic acid, linolenic acid, phenylalanine, ascorbic acid and uronic acid. Using the network pharmacology to build a "component-target-pathway" network of A. sinensis, 62 active ingredients, 169 active proteins and 18 metabolic pathways were obtained, among which linoleic acid metabolism, ascorbic acid and uronic acid metabolism were consistent with the metabolic pathways obtained by metabolomics

    Demonstration of laser-produced neutron diagnostic by radiative capture gamma-rays

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    We report a new scenario of time-of-flight (TOF) technique in which fast neutrons and delayed gamma-ray signals were both recorded in a millisecond time window in harsh environments induced by high-intensity lasers. The delayed gamma signals, arriving far later than the original fast neutron and often being ignored previously, were identified to be the results of radiative captures of thermalized neutrons. The linear correlation between gamma photon number and the fast neutron yield shows that these delayed gamma events can be employed for neutron diagnosis. This method can reduce the detecting efficiency dropping problem caused by prompt high-flux gamma radiation, and provides a new way for neutron diagnosing in high-intensity laser-target interaction experiments

    Leakage identification method of gas-liquid two-phase flow pipeline based on acoustic emission signal

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    For the problem that the conventional oil pipeline detection system cannot effectively detect the leakage of the two-phase flow pipelines, a leakage identification method based on the acoustic emission signal was proposed for the gasliquid two-phase flow pipelines. According to the basic principles of acoustic emission detection technology, the leakage detection tests were carried out for the three flow patterns of laminar flow, slug flow and annular flow at a gas pressure of 0.1 to 0.4 MPa in three different orientations of leak holes with two different diameters. The main signal components extracted by wavelet packet decomposition combined with local mean decomposition were taken as the input of pattern recognition, and the BP artificial neural network pattern recognition was also performed. The test results show that the average accuracy of the leakage identification of the three two-phase flow pipelines of laminar flow, slug flow and annular flow is 83.5%, which is high in accuracy. Further, the proposed method has a reference value for the leakage detection of gas-liquid twophase flow pipelines

    Drought resistance of ten ground cover seedling species during roof greening.

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    Roof greening is an important national policy for maintaining the hydrological balance in China; however, plant growth is limited by drought stress. This study aims to identify strong drought resistant plant species for roof greening from ten common species: Paeonia lactiflora, Hemerocallis dumortieri, Meehania urticifolia, Iris lactea var. chinensis, Hylotelephium erythrostictum, Sedum lineare, Iris germanica, Cosmos bipinnata, Hosta plantaginea, and Dianthus barbatus. By controlling the soil relative water content (RWC), we designed three treatments: moderate drought stress (40±2% 75±2%). After the seedlings were provided different levels of water, their membrane permeability (MP), chlorophyll concentration (Chl), and superoxide dismutase (SOD), peroxidase (POD) and ascorbate peroxidase (APX) activity were measured. Finally, the membership function method was used to assess the drought resistance of these species. The results showed that C. bipinnata and M. urticifolia were not suitable for moderate or severe drought stress and did not survive. The other species presented variations in physiological and biochemical parameters. The MP of He. dumortieri, I. lactea and Ho. plantaginea showed minor changes between the well-watered control and drought stress. Most of the species showed reduced SOD activity under moderate drought stress but increased activity under severe stress. All of the plant species showed decreases in the protective enzymes POD and APX with increasing drought stress. The membership function method was applied to calculate the plant species' drought resistance, and the following order of priority of the roof-greening plant species was suggested: He. dumortieri > I. germanica > I. lactea > D. barbatus > Hy. erythrostictum > S. lineare > Ho. plantaginea > P. lactiflora

    Facing the urban-rural gap in patients with chronic kidney disease: Evidence from inpatients with urban or rural medical insurance in central China.

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    BackgroundIn view of the irreversible pathology of progressive exacerbation, the societal burden of chronic kidney disease (CKD) is increasing along with the rise in total health expenditure. Meanwhile, disparities remain among urban and rural citizens with different types of health insurance. This study aimed to assess the socioeconomic disparities between hospitalized CKD patients in urban and rural areas.MethodA total of 501 CKD inpatients with urban or rural medical insurance (UMI or RMI, respectively) were selected from the top six tertiary hospitals in Wuhan. Demographic and socioeconomic data were collected as influencing factors. Data evaluation was performed using univariate and multivariate analyses.ResultSocioeconomic characteristics showed differences among hospitalized CKD patients with different health insurances. Patients with RMI were younger, and reported lower education levels, poor domestic economic conditions, shorter duration, and less frequent hospital stays than those with UMI (PConclusionsCare delivery and reimbursement models should be re-designed and implemented to improve equity among different CKD patients. The national health education should also be enhanced to prevent CKD and provide early treatment
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