267 research outputs found

    MA2GCN: Multi Adjacency relationship Attention Graph Convolutional Networks for Traffic Prediction using Trajectory data

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    The problem of traffic congestion not only causes a large amount of economic losses, but also seriously endangers the urban environment. Predicting traffic congestion has important practical significance. So far, most studies have been based on historical data from sensors placed on different roads to predict future traffic flow and speed, to analyze the traffic congestion conditions of a certain road segment. However, due to the fixed position of sensors, it is difficult to mine new information. On the other hand, vehicle trajectory data is more flexible and can extract traffic information as needed. Therefore, we proposed a new traffic congestion prediction model - Multi Adjacency relationship Attention Graph Convolutional Networks(MA2GCN). This model transformed vehicle trajectory data into graph structured data in grid form, and proposed a vehicle entry and exit matrix based on the mobility between different grids. At the same time, in order to improve the performance of the model, this paper also built a new adaptive adjacency matrix generation method and adjacency matrix attention module. This model mainly used gated temporal convolution and graph convolution to extract temporal and spatial information, respectively. Compared with multiple baselines, our model achieved the best performance on Shanghai taxi GPS trajectory dataset. The code is available at https://github.com/zachysun/Taxi_Traffic_Benchmark

    Study on stability and bearing characteristics of macroscopic pressure arch of surrounding rock in western deep buried stope of China

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    In view of the obvious loose and weak occurrence characteristics of the deeply buried thick weakly cemented stratum in the western mining area of China, the bearing characteristics and stability mechanism of the macrography surrounding rock pressure arch (SRPA) are studied. Firstly, considering the engineering characteristics of deep mining, a SRPA model with trapezoidal load was constructed based on the three-hinged arch theory, the shape characteristic, rise-span ratio and arch thickness equations were derived, the arch thickness under different stress paths is analyzed to characterize the bearing performance of pressure arch. Secondly, the internal force distribution law and destabilization damage type were studied by establishing a two-dimensional bearing SRPA model through arch without articulation theory. The instability type and location can be accurately judged and verified by simulation of similar materials. The results show that, the rational arch axis of SRPA is a cubic parabola with opening downward, its rise-span ratio is between 0.3 and 0.5. Increasing the rise-span ratio and lateral pressure coefficient can promote the stable bearing capacity of arch. Axial force distribution on the SRPA section is basically consistent with the arch axis, and the arch has the best bearing characteristics. The positive bending moment occurs in the ranges of [0°, 30°] and [81°, 90°] on both sides of the symmetry axis, where is prone to tensile failure. The maximum shear force is concentrated on the arch waist and skewback, and these sections are prone to shear failure. The instability modes of SRPA can be divided into “skewback—vault (arch waist)” and “vault (arch waist)—skewback”. The research results have theoretical guiding significance for mining roof management

    Adsorption and desorption characteristics of arsenic onto ceria nanoparticles

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    The rapid increase in the use of engineered nanoparticles [ENPs] has resulted in an increasing concern over the potential impacts of ENPs on the environmental and human health. ENPs tend to adsorb a large variety of toxic chemicals when they are emitted into the environment, which may enhance the toxicity of ENPs and/or adsorbed chemicals. The study was aimed to investigate the adsorption and desorption behaviors of arsenic on ceria NPs in aqueous solution using batch technique. Results show that the adsorption behavior of arsenic on ceria NPs was strongly dependent on pH and independent of ionic strength, indicating that the electrostatic effect on the adsorption of these elements was relatively not important compared to surface chemical reactions. The adsorption isotherms fitted very well to both the Langmuir and Freundlich models. The thermodynamic parameters (ΔH0, ΔS0, and ΔG0) for the adsorption of arsenic were determined at three different temperatures of 283, 303, and 323 K. The adsorption reaction was endothermic, and the process of adsorption was favored at high temperature. The desorption data showed that desorption hysteresis occurred at the initial concentration studied. High adsorption capacity of arsenic on ceria NPs suggests that the synergistic effects of ceria NPs and arsenic on the environmental systems may exist when they are released into the environment

    Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification

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    Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this problem, a multiclass posterior probability solution for twin SVM is proposed by the ranking continuous output and pairwise coupling in this paper. First, two-class posterior probability model is constructed to approximate the posterior probability by the ranking continuous output techniques and Platt's estimating method. Secondly, a solution of multiclass probabilistic outputs for twin SVM is provided by combining every pair of class probabilities according to the method of pairwise coupling. Finally, the proposed method is compared with multiclass SVM and twin SVM via voting, and multiclass posterior probability SVM using different coupling approaches. The efficacy on the classification accuracy and time complexity of the proposed method has been demonstrated by both the UCI benchmark datasets and real world EEG data from BCI Competition IV Dataset 2a, respectively

    Comparative analysis of glucose and fructose tolerance in two marine fishes: effects on insulin secretion and acute hypoxia tolerance

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    Carbohydrates are a common and economical energy source in animal feeds. However, most fish show a persistent postprandial hyperglycemia after intake of a high-carbohydrate diet. Unfortunately, the mechanism of glucose metabolism in fish is still unclear. In the present study, tiger puffer (Takifugu rubripes) and turbot (Scophthalmus maximus) were intraperitoneally injected or orally administered with glucose or fructose (500 mg/kg body weight) to evaluate the ability of fish to utilize carbohydrates. Afterwards, serum glucose, fructose, pyruvate, insulin levels, and acute hypoxia tolerance were measured. Our results showed increased serum glucose level and then decreased post intraperitoneal injection with glucose, and reached a peak after 0.5 hours in turbot and 1 hour in tiger puffer. Tiger puffer had significantly lower liver glycogen, serum glucose, fructose, pyruvate, and insulin contents than turbot. Glucose and fructose only induced insulin secretion in turbot, but did not change serum insulin level in tiger puffer. Glucose was a stronger stimulator of insulin than fructose in the two marine species. Both intraperitoneal injection and oral fructose intake increased serum glucose level, while intraperitoneal or oral glucose also increased serum fructose level. Intraperitoneal injection of glucose promoted absorption and utilization of glucose in the blood more effectively than oral glucose intake. In addition, turbot and tiger puffer were intolerant to acute hypoxia, whereas supplementation with glucose or fructose improved hypoxia tolerance in the two marine fishes by activating anaerobic glycolysis. Taken together, our results provide important scientific information for understanding the mechanism for glucose and fructose utilization and improving hypoxia tolerance in fish

    Oxidation of the cysteine-rich regions of parkin perturbs its E3 ligase activity and contributes to protein aggregation

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    <p>Abstract</p> <p>Background</p> <p>Accumulation of aberrant proteins to form Lewy bodies (LBs) is a hallmark of Parkinson's disease (PD). Ubiquitination-mediated degradation of aberrant, misfolded proteins is critical for maintaining normal cell function. Emerging evidence suggests that oxidative/nitrosative stress compromises the precisely-regulated network of ubiquitination in PD, particularly affecting parkin E3 ligase activity, and contributes to the accumulation of toxic proteins and neuronal cell death.</p> <p>Results</p> <p>To gain insight into the mechanism whereby cell stress alters parkin-mediated ubiquitination and LB formation, we investigated the effect of oxidative stress. We found significant increases in oxidation (sulfonation) and subsequent aggregation of parkin in SH-SY5Y cells exposed to the mitochondrial complex I inhibitor 1-methyl-4-phenlypyridinium (MPP<sup><b>+</b></sup>), representing an <it>in vitro </it>cell-based PD model. Exposure of these cells to direct oxidation via pathological doses of H<sub>2</sub>O<sub>2 </sub>induced a vicious cycle of increased followed by decreased parkin E3 ligase activity, similar to that previously reported following S-nitrosylation of parkin. Pre-incubation with catalase attenuated H<sub>2</sub>O<sub>2 </sub>accumulation, parkin sulfonation, and parkin aggregation. Mass spectrometry (MS) analysis revealed that H<sub>2</sub>O<sub>2 </sub>reacted with specific cysteine residues of parkin, resulting in sulfination/sulfonation in regions of the protein similar to those affected by parkin mutations in hereditary forms of PD. Immunohistochemistry or gel electrophoresis revealed an increase in aggregated parkin in rats and primates exposed to mitochondrial complex I inhibitors, as well as in postmortem human brain from patients with PD with LBs.</p> <p>Conclusion</p> <p>These findings show that oxidative stress alters parkin E3 ligase activity, leading to dysfunction of the ubiquitin-proteasome system and potentially contributing to LB formation.</p

    Prevalence and risk factors of hepatitis C among former blood donors in rural China

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    SummaryBackgroundIllegal commercial plasma and blood donation activities in the late 1980s and early 1990s caused a large number of hepatitis C virus (HCV) infections in rural areas of China.MethodsA cross-sectional survey was carried out in 2008, in which all residents in a former blood donation village in rural Hebei Province were invited for a questionnaire interview and testing for HCV antibodies. Questionnaires were administered to collect information about their personal status and commercial blood donation history, and HCV antibodies were tested by enzyme immunoassay.ResultsOf 520 villagers who participated in the interviews, 236 (45.4%) reported a history of selling whole blood or plasma. HCV seropositivity was confirmed in 148/520 (28.5%) interviewees and 101/236 (42.8%) former commercial plasma and blood donors. Selling plasma was the strongest independent predictor of HCV seropositivity (p=0.0037). Past history of an operation was also independently associated with HCV infection (p=0.0270).ConclusionsUnsafe practices during illegal plasma donation led to a high risk of HCV seropositivity for donors during the late 1980s and early 1990s. Many infected people suffered chronic hepatitis from that time onwards and urgently needed treatment and care
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