Fault analysis and protection are crucial for the development of flexible direct current traction power supply system in urban rail transit. The aim of this study was to provide a comprehensive review of fault analysis and protection in flexible direct current traction power supply systems, in particular the adaptability and development trend of protection. A model of a flexible direct current traction power supply system was built using bidirectional converter and traction network, and detailed fault analyses of pole-to-pole fault and pole-to-ground fault were conducted. The correctness of the model and fault analysis is verified by electromagnetic transient simulation. The fault analysis findings suggest that the fault current is extremely high and develops rapidly. In the case of pole-to-pole fault, the peak current for near end short circuit can reach approximately 60 kA within a few hundred microseconds to several milliseconds. Furthermore, through adaptability analyses of existing protection principles, these indicate that the direct acting and current-based protection principles have deficiencies in terms of speed, sensitivity and reliability. It is necessary to recalculate the settings to meet the new requirements of protection. Finally, the new trends in protection are described to provide references for further research.
An adaptive genetic algorithm based on collision detection (AGACD) is proposed to solve the problems of the basic genetic algorithm in the field of path planning, such as low convergence path quality, many iterations required for convergence, and easily falling into the local optimal solution. First, this paper introduces the Delphi weight method to evaluate the weight of path length, path smoothness, and path safety in the fitness function, and a collision detection method is proposed to detect whether the planned path collides with obstacles. Then, the population initialization process is improved to reduce the program running time. After comprehensively considering the population diversity and the number of algorithm iterations, the traditional crossover operator and mutation operator are improved, and the adaptive crossover operator and adaptive mutation operator are proposed to avoid the local optimal solution. Finally, an optimization operator is proposed to improve the quality of convergent individuals through the second optimization of convergent individuals. The simulation results show that the adaptive genetic algorithm based on collision detection is not only suitable for simulation maps with various sizes and obstacle distributions but also has excellent performance, such as greatly reducing the running time of the algorithm program, and the adaptive genetic algorithm based on collision detection can effectively solve the problems of the basic genetic algorithm.
Pigs are encountering a large number of xenobiotics potentially harmful consequences, which is not only bad for animal health and pork quality but also bad for human health.Therefore, identification of the Pig Constitutive Androstane Receptor (pgCAR) agonist would be beneficial for pigs and consumer, because of its pivotal role in xenobiotics-metabolism.In this study, A stable and sensitive cell-based high throughput screening (HTS) model is conducted in a 48-well format using the human hepatoma HepG2 cells transiently transfected with pcDNA3.1-pgCARplasmid and reporter plasmids to identify chemicals or natural compounds that would promote CAR，and calibrated with reference pgCAR agonist, phenytoin.In conclusion, three active ingredients including Vitamin C, Folate and Sitosterol, were picked out as agonists by the high-throughput screening from 13 compounds, particularly the effects of Sitosterol.
Abstract Motivation Scaling by sequencing depth is usually the first step of analysis of bulk or single-cell RNA-seq data, but estimating sequencing depth accurately can be difficult, especially for single-cell data, risking the validity of downstream analysis. It is thus of interest to eliminate the use of sequencing depth and analyze the original count data directly. Results We call an analysis method ‘scale-invariant’ (SI) if it gives the same result under different estimates of sequencing depth and hence can use the original count data without scaling. For the problem of classifying samples into pre-specified classes, such as normal versus cancerous, we develop a deep-neural-network based SI classifier named scale-invariant deep neural-network classifier (SINC). On nine bulk and single-cell datasets, the classification accuracy of SINC is better than or competitive to the best of eight other classifiers. SINC is easier to use and more reliable on data where proper sequencing depth is hard to determine. Availability and implementation This source code of SINC is available at https://www.nd.edu/∼jli9/SINC.zip. Supplementary information Supplementary data are available at Bioinformatics online.
Students' participation in class is the key factor of learning well,which is the criteria of assessing the effectiveness of studying in class.In primary school,the teachers should teach them with four principles according to its psychological characteristics,which is the concept of Teachers Guiding Role and Students' Participating Role,teaching through games,setting cognitive conflict and harmonious relationship between teachers and students.
A high-temperature oxidation resistant TiN embedded in Ti3Al intermetallic matrix composite coating was fabricated on titanium alloy Ti6Al4V surface by 6kW transverse-flow CO2 laser apparatus. The composition, morphology and microstructure of the laser clad TiN/Ti3Al intermetallic matrix composite coating were characterized by optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD) and energy dispersive spectrometer (EDS). In order to evaluate the high-temperature oxidation resistance of the composite coatings and the titanium alloy substrate, isothermal oxidation test was performed in a conventional high-temperature resistance furnace at 600°C and 800°C respectively. The result shows that the laser clad intermetallic composite coating has a rapidly solidified fine microstructure consisting of TiN primary phase (granular-like, flake-like, and dendrites), and uniformly distributed in the Ti3Al matrix. It indicates that a physical and chemical reaction between the Ti powder and AlN powder occurred completely under the laser irradiation. In addition, the microhardness of the TiN/Ti3Al intermetallic matrix composite coating is 844HV0.2, 3.4 times higher than that of the titanium alloy substrate. The high-temperature oxidation resistance test reveals that TiN/Ti3Al intermetallic matrix composite coating results in the better modification of high-temperature oxidation behavior than the titanium substrate. The excellent high-temperature oxidation resistance of the laser cladding layer is attributed to the formation of the reinforced phase TiN and Al2O3, TiO2 hybrid oxide. Therefore, the laser cladding TiN/Ti3Al intermetallic matrix composite coating is anticipated to be a promising oxidation resistance surface modification technique for Ti6Al4V alloy.
Building an accurate mathematical model for inverter is the key to achieving a precise control. Contrasted to the traditional switching function model of power electronic circuits, this paper built the mixed logical dynamic(MLD) model for a new inverter, and the MLD model was used as a prediction model, then a predictive direct power control(P-DPC) method was researched for the new inverter. A symmetrical 4+4 voltage vector sequence was employed to obtain constant switching frequency and lower THD of output voltage, the action time of vector sequence was calculated by minimizing objective function. The feasibility and effectiveness were proved by simulations.
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