Slicing Recognition of Aircraft Integral Panel Generalized Pocket

AbstractTo automatically obtain a machining area in numerical control (NC) programming, a data model of generalized pocket is established by analyzing aircraft integral panel characteristics, and a feature recognition approach is proposed. First, by reference to the practical slice-machining process of an aircraft integral panel, both the part and the blank are sliced in the Z-axis direction; hence a feature profile is created according to the slicing planes and the contours are formed by the intersection of the slicing planes with the part and its blank. Second, the auxiliary features of the generalized pocket are also determined based on the face type and the position, to correct the profile of the pocket. Finally, the generalized pocket feature relationship tree is constructed by matching the vertical relationships among the features. Machining feature information produced by using this method can be directly used to calculate the cutter path. The validity and practicability of the method is verified by NC programming for aircraft panels

A Detection Algorithm for the BOC Signal Based on Quadrature Channel Correlation

In order to solve the problem of detecting a BOC signal, which uses a long-period pseudo random sequence, an algorithm is presented based on quadrature channel correlation. The quadrature channel correlation method eliminates the autocorrelation component of the carrier wave, allowing for the extraction of the absolute autocorrelation peaks of the BOC sequence. If the same lag difference and height difference exist for the adjacent peaks, the BOC signal can be detected effectively using a statistical analysis of the multiple autocorrelation peaks. The simulation results show that the interference of the carrier wave component is eliminated and the autocorrelation peaks of the BOC sequence are obtained effectively without demodulation. The BOC signal can be detected effectively when the SNR is greater than −12 dB. The detection ability can be improved further by increasing the number of sampling points. The higher the ratio of the square wave subcarrier speed to the pseudo random sequence speed is, the greater the detection ability is with a lower SNR. The algorithm presented in this paper is superior to the algorithm based on the spectral correlation

Prediction of Daily Water Consumption in Residential Areas Based on Meteorologic Conditions—Applying Gradient Boosting Regression Tree Algorithm

A more accurate way of water consumption forecasting can be used to help people develop a scheduling plan of water workers more targeting; therefore, this paper aims to establish a forecast model of daily water consumption based on meteorological conditions. At present, most studies of daily water consumption forecasts focus on historical data or single water use influencing factors; moreover, daily water consumption could be influenced by meteorologic conditions. The influence of complex meteorology factors on water consumption is analyzed based on a gradient-boosted regression tree (GBRT) model. The correlation of 10 meteorologic factors has been discussed and divided into 5 categories, including temperature factor, pressure factor, precipitation factor, sunshine factor, and wind factor. Through the GBRT algorithm, the daily water consumption of residential area could be predicted with a maximum error of ±8%. The results show that the average ground temperature (the feature importance accounts for 81% of the total) has the greatest impact on the daily water consumption of the residential community, followed by the somatosensory temperature (the feature importance accounts for 7% of the total). The method can provide the daily water consumption of water consumption nodes with higher precision for municipal water supply network model accuracy. It also provides a reference for water utility operation schemes and urban development planning

Double Deep Q-Network with Dynamic Bootstrapping for Real-Time Isolated Signal Control: A Traffic Engineering Perspective

Real-time isolated signal control (RISC) at an intersection is of interest in the field of traffic engineering. Energizing RISC with reinforcement learning (RL) is feasible and necessary. Previous studies paid less attention to traffic engineering considerations and under-utilized traffic expertise to construct RL tasks. This study profiles the single-ring RISC problem from the perspective of traffic engineers, and improves a prevailing RL method for solving it. By qualitative applicability analysis, we choose double deep Q-network (DDQN) as the basic method. A single agent is deployed for an intersection. Reward is defined with vehicle departures to properly encourage and punish the agent’s behavior. The action is to determine the remaining green time for the current vehicle phase. State is represented in a grid-based mode. To update action values in time-varying environments, we present a temporal-difference algorithm TD(Dyn) to perform dynamic bootstrapping with the variable interval between actions selected. To accelerate training, we propose a data augmentation based on intersection symmetry. Our improved DDQN, termed D3ynQN, is subject to the signal timing constraints in engineering. The experiments at a close-to-reality intersection indicate that, by means of D3ynQN and non-delay-based reward, the agent acquires useful knowledge to significantly outperform a fully-actuated control technique in reducing average vehicle delay

Interdependent recruitment of CYC8/TUP1 and the transcriptional activator XYR1 at target promoters is required for induced cellulase gene expression in Trichoderma reesei.

Cellulase production in filamentous fungus Trichoderma reesei is highly responsive to various environmental cues involving multiple positive and negative regulators. XYR1 (Xylanase regulator 1) has been identified as the key transcriptional activator of cellulase gene expression in T. reesei. However, the precise mechanism by which XYR1 achieves transcriptional activation of cellulase genes is still not fully understood. Here, we identified the TrCYC8/TUP1 complex as a novel coactivator for XYR1 in T. reesei. CYC8/TUP1 is the first identified transcriptional corepressor complex mediating repression of diverse genes in Saccharomyces cerevisiae. Knockdown of Trcyc8 or Trtup1 resulted in markedly impaired cellulase gene expression in T. reesei. We found that TrCYC8/TUP1 was recruited to cellulase gene promoters upon cellulose induction and this recruitment is dependent on XYR1. We further observed that repressed Trtup1 or Trcyc8 expression caused a strong defect in XYR1 occupancy and loss of histone H4 at cellulase gene promoters. The defects in XYR1 binding and transcriptional activation of target genes in Trtup1 or Trcyc8 repressed cells could not be overcome by XYR1 overexpression. Our results reveal a novel coactivator function for TrCYC8/TUP1 at the level of activator binding, and suggest a mechanism in which interdependent recruitment of XYR1 and TrCYC8/TUP1 to cellulase gene promoters represents an important regulatory circuit in ensuring the induced cellulase gene expression. These findings thus contribute to unveiling the intricate regulatory mechanism underlying XYR1-mediated cellulase gene activation and also provide an important clue that will help further improve cellulase production by T. reesei

Panax ginseng improves physical recovery and energy utilization on chronic fatigue in rats through the PI3K/AKT/mTOR signalling pathway

AbstractContext Panax ginseng C. A. Meyer (Araliaceae) is a tonic herb used in ancient Asia.Objective This study investigated the antifatigue effect of P. ginseng on chronic fatigue rats.Materials and methods Sprague-Dawley rats were divided into control, model and EEP (ethanol extraction of P. ginseng roots) (50, 100 and 200 mg/kg) groups (n = 8). The rats were subcutaneously handled with loaded swimming once daily for 26 days, except for the control group. The animals were intragastrically treated with EEP from the 15th day. On day 30, serum, liver and muscles were collected, and the PI3K/Akt/mTOR signalling pathway was evaluated.Results The swimming times to exhaust of the rats with EEP were significantly longer than that without it. EEP spared the amount of muscle glycogen, hepatic glycogen and blood sugar under the chronic state. In addition, EEP significantly (p < 0.05) decreased serum triglycerides (1.24 ± 0.17, 1.29 ± 0.04 and 1.20 ± 0.21 vs. 1.58 ± 0.13 mmol/L) and total cholesterol (1.64 ± 0.36, 1.70 ± 0.15 and 1.41 ± 0.19 vs. 2.22 ± 0.19 mmol/L) compared to the model group. Regarding the regulation of energy, EEP had a positive impact on promoting ATPase activities and relative protein expression of the PI3K/Akt/mTOR pathway.Conclusions Our results suggested that EEP effectively relieved chronic fatigue, providing evidence that P. ginseng could be a potential dietary supplement to accelerate recovery from fatigue

Recent Advances on Heteroatom-Doped Porous Carbon—Based Electrocatalysts for Oxygen Reduction Reaction

Polymer electrolyte membrane fuel cells are considered one of the alternatives to fossil energy sources. The slow kinetics of the oxygen reduction reaction (ORR) at the cathode and the high price of Pt-based catalysts remain one of the key challenges for the commercial viability of proton exchange membrane fuel cells. However, their high cost and susceptibility to poisoning severely limit their use for large-scale commercial applications in fuel cells. Heteroatom-doped porous carbon has attracted extensive attention from scientists due to its advantages such as high specific surface area and the properties conferred by heteroatom doping. On the one hand, we discuss a variety of current methods for the preparation of heteroatom-doped porous carbons, including the template method and the activation method. On the other hand, we discuss the application of heteroatom-doped porous carbon in Pt catalysts, transition metal catalysts and metal-free catalysts. Finally, we also present the pre-existing and challenges of heteroatoms in ORR catalysis, which will drive the development of ORR catalysts