CNC Thermal Compensation Based on Mind Evolutionary Algorithm Optimized BP Neural Network

Thermal deformation error is one of the most important factors affecting the CNCs’ accuracy, so research is conducted on the temperature errors affecting CNCs’ machining accuracy;on the basis of analyzing the unpredictability and pre-maturing of the results of the genetic algorithm, as well as the slow speed of the training speed of the particle algorithm, a kind of Mind Evolutionary Algorithm optimized BP neural network featuring extremely strong global search capacity was proposed;type KVC850MA/2 five-axis CNC of Changzheng Lathe Factory was used as the research subject, and the Mind Evolutionary Algorithm optimized BP neural network algorithm was used for the establishment of the compensation model between temperature changes and the CNCs’ thermal deformation errors, as well as the realization method on hardware. The simulation results indicated that this method featured extremely high practical value.

Optimal Reactive Power Compensation of Distribution Network to Prevent Reactive Power Reverse

The capacitive reactive power reversal in the urban distribution grid is increasingly prominent at the period of light load in the last years.In severe cases,it will endanger the security and stability of power grid.This paper presents an optimal reactive power compensation method of distribution network to prevent reactive power reverse.Firstly,an integrated reactive power planning(RPP)model with power factor constraints is established.Capacitors and reactors are considered to be installed in the distribution system at the same time.The objective function is the cost minimization of compensation and real power loss with transformers and lines during the planning period.Nodal power factor limits and reactor capacity constraints are new constraints.Then,power factor sensitivity with respect to reactive power is derived.An improved genetic algorithm by power factor sensitivity is used to solve the model.The optimal locations and sizes of reactors and capacitors can avoid reactive power reversal and power factor exceeding the limit.Finally,the effectiveness of the model and algorithm is proven by a typical high-voltage distribution network.

The evolution of sex chromosome dosage compensation in animals

The evolution of heteromorphic sex chromosomes shall lead to gene expression dosage problems,as in at least one of the sexes,the sex-linked gene dose has been reduced by half.It has been proposed that the transcriptional output of the whole X or Z chromosome should be doubled for complete dosage compensation in heterogametic sex.However,owing to the variability of the existing methods to determine the transcriptional differences between sex chromosomes and autosomes(S:A ratios)in different studies,we collected more than 500 public RNA-Seq data set from multiple tissues and species in major clades and proposed a unified computational framework for unbiased and comparable measurement of the S:A ratios of multiple species.We also tested the evolution of dosage compensation more directly by assessing changes in the expression levels of the current sex-linked genes relative to those of the ancestral sex-linked genes.We found that in mammals and birds,the S:A ratio is approximately 0.5,whereas in insects,fishes,and flatworms,the S:A ratio is approximately 1.0.Further analysis showed that the fraction of dosage-sensitive housekeeping genes on the X/Z chromosome is significantly correlated with the S:A ratio.In addition,the degree of degeneration of the Y chromosome may be responsible for the change in the S:A ratio in mammals without a dosage compensation mechanism.Our observations offer unequivocal support for the sex chromosome insensitivity hypothesis in animals and suggest that dosage sensitivity states of sex chromosomes are a major factor underlying different evolutionary strategies of dosage compensation.

Fuzzy-GA based algorithm for optimal placement and sizing of distribution static compensator (DSTATCOM) for loss reduction of distribution network considering reconfiguration

This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devices and the cost of system operation, namely, energy loss cost due to both reconfiguration and DSTATCOM placement, are combined to form the objective function to be minimized. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. In the proposed approach, the fuzzy membership function of loss sensitivity is used for the selection of weak nodes in the power system for the placement of DSTATCOM and the optimal parameter settings of the DFACTS device along with optimal selection of tie switches in reconfiguration process are governed by genetic algorithm(GA). Simulation results on IEEE 33-bus and IEEE 69-bus test systems concluded that the combinatorial method using DSTATCOM and reconfiguration is preferable to reduce power losses to 34.44% for 33-bus system and to 45.43% for 69-bus system.

Dynamic Spatial-temporal Expression Ratio of X Chromosome to Autosomes but Stable Dosage Compensation in Mammals

In the evolutionary model of dosage compensation,per-allele expression level of the X chromosome has been proposed to have twofold up-regulation to compensate its dose reduction in males(XY)compared to females(XX).However,the expression regulation of X-linked genes is still controversial,and comprehensive evaluations are still lacking.By integrating multi-omics datasets in mammals,we investigated the expression ratios including X to autosomes(X:AA ratio)and X to orthologs(X:XX ratio)at the transcriptome,translatome,and proteome levels.We revealed a dynamic spatial-temporal X:AA ratio during development in humans and mice.Meanwhile,by tracing the evolution of orthologous gene expression in chickens,platypuses,and opossums,we found a stable expression ratio of X-linked genes in humans to their autosomal orthologs in other species(X:XX1)across tissues and developmental stages,demonstrating stable dosage compensation in mammals.We also found that different epigenetic regulations contributed to the high tissue specificity and stage specificity of X-linked gene expression,thus affecting X:AA ratios.It could be concluded that the dynamics of X:AA ratios were attributed to the different gene contents and expression preferences of the X chromosome,rather than the stable dosage compensation.

Process for Compensating Local Magnetic Perturbations on Ferromagnetic Surfaces

This paper addresses a practical application for the compensation of a local magnetic perturbation in a ship in the near field region. The process will avoid expensive deperming techniques usually applied to ships to treat magnetic anomalies. The technique includes a new system to construct magnetic maps on flat ferromagnetic surfaces. Once the magnetic maps are obtained, a new system is proposed to evaluate and locate local magnetic perturbations. Once the local perturbations are located, they are compensated by local degaussing coils. The new technique has been applied to the detection of local magnetic perturbations in four naval platforms. Two of them presented important magnetic anomalies, and were successfully detected and corrected by applying the new technique, thus showing its practical value.

基于双目视觉的6D位姿测量误差补偿方法

针对双目视觉设备测量误差较大且单点测量误差在视野范围内分布不一致,导致测量6D位姿精度和稳定性较差的问题,提出了一种测量误差补偿方法。为了解决传统回归模型在小样本多输入多输出情况下拟合效果较差的问题,采用基于多输出最小二乘支持向量回归(MLSSVR)的算法,实现了单点测量误差准确预测,并采用遗传算法对模型超参数进行全局寻优;为了实现跟踪坐标系的位姿测量误差补偿,结合位姿测量原理,将线性问题转化为最优估计问题,通过最小化坐标变换误差函数,将多个单点预测误差转化为多点耦合误差,从而实现了6D位姿测量误差补偿。实验结果表明,所提方法将跟踪坐标系的平均位置测量误差在3个方面上分别降低了63.4%、45.2%和75.0%,平均姿态测量误差分别降低50%、48.4%和53.1%;与其它现有补偿方法相比,所提方法能显著提高双目视觉设备的测量精度,并保证不同观测角度下的测量误差补偿有效性。

急性淋巴细胞白血病患儿维持治疗期间6-巯基嘌呤使用剂量与TPMT和NUDT15基因多态性的关系

背景6-巯基嘌呤(6-MP)是急性淋巴细胞白血病(ALL)维持治疗最主要的药物之一,代谢酶基因多态性与药物的骨髓抑制程度有关。目的探讨ALL患儿维持治疗期间6-MP使用剂量与TPMT和NUDT15基因多态性的关系。设计回顾性队列研究。方法纳入2020年1月至2021年12月于郑州大学第一附属医院明确诊断为ALL、经前期化疗骨髓达完全缓解、进入维持治疗阶段且口服6-MP治疗的患儿。口服6-MP前患儿行TPMT和NUDT15基因型检测,分析TPMT、NUDT15不同基因型患儿应用6-MP治疗的使用剂量和骨髓抑制情况。主要结局指标6-MP使用剂量。结果61例维持治疗的ALL患儿纳入本文分析。纳入TPMT基因多态性统计分析的ALL患儿48例(除外NUDT15基因突变13例),野生型45例,突变型3例;纳入NUDT15基因多态性统计分析的ALL患儿58例(除外TPMT基因突变3例),CC型45例,CT型9例,TT型4例。在6-MP维持治疗阶段,TPMT和NUDT15不同基因型患儿的WBC、Hb、PLT计数差异均有统计学意义(均P<0.05)。患儿用药后出现不同程度的中性粒细胞减少,包括TPMT野生型15例,突变型3例;NUDT15基因CC型15例,CT型5例,TT型4例;TPMT和NUDT15不同基因型患儿骨髓抑制情况差异均有统计学意义(均P<0.05)。TPMT和NUDT15不同基因型患儿6-MP使用剂量差异有统计学意义(均P<0.05),TPMT野生型和突变型ALL患儿维持治疗期6-MP使用剂量分别为(40.81±6.02)和(16.25±4.42)mg·m^(-2)·d^(-1);NUDT15基因CC型、CT型和TT型6-MP使用剂量分别为(40.81±6.02)、(34.28±4.53)和(10.00±1.28)mg·m^(-2)·d^(-1)。结论TPMT和NUDT15突变型患儿的骨髓抑制程度均较野生型严重。ALL患儿维持治疗期间6-MP使用剂量与TPMT和NUDT15基因多态性相关。

考虑碳交易和无功补偿的分布式电源优化配置

“双碳”背景下,在规划分布式电源时引入碳交易和无功补偿机制是实现电力系统低碳化、稳定化的重要手段。为此,提出一种考虑碳交易和无功补偿的分布式电源优化配置方法。首先,引入碳交易机制,建立碳交易成本计算模型。其次,建立考虑碳交易和无功补偿的分布式电源双层优化配置模型,上层以年综合成本为优化目标,决策变量为光伏和燃气轮机接入配电网中的位置及容量;下层以系统网损、电压偏移量、节点电压稳定裕度为优化目标,决策变量为无功补偿电容器在配电网中的位置和容量。最后,通过改进的自适应遗传算法对优化配置模型进行求解。结合IEEE33节点构造的算例进行仿真分析,结果表明,该模型可在保证系统经济性和环保性的基础上有效降低网损,并提高系统电压的稳定性。

基于改进的RBF神经网络倾角传感器温度补偿方法研究

针对MEMS倾角传感器零位温度漂移问题,提出了粒子群优化(PSO)算法和遗传算法(GA)相结合优化径向基函数(RBF)神经网络的补偿方法,克服了RBF神经网络收敛慢、泛用性低的缺陷。结果表明:该方法能够有效地消除温度对MEMS倾角传感器输出的影响。相较于RBF神经网络模型,最大相对误差(MRE)减小了21.03%,均方根误差(RMSE)减小了23.54%,温度漂移得到明显改善,提高了倾角传感器的稳定性与准确性。

改进GA-RBF神经网络的水厂混凝投药预测

为了提高水厂混凝剂投加量预测准确性,针对投药系统易受多种水质因素影响,且投药后净水过程存在高度非线性的特点,通过改进遗传算法(GA)优化径向基函数神经网络(也称为RBF神经网络)的权值ω_i和高斯基函数中心宽度向量σ_i,构建GA-RBF神经网络净水厂投药量预测模型。Matlab仿真结果表明,GA-RBF神经网络预测模型可通过实现全局逼近来回避极值陷阱,提高了稳定性和全局寻优能力,相较于单一RBF神经网络预测模型,GA-RBF神经网络预测模型的拟合优度提高5.474%,平均绝对误差降低了4.14%,根均方误差降低3.392%,迭代速度和预测精度都有所提高,数据拟合能力更强。

Spatial phase-shifting interferometry with compensation of geometric errors based on genetic algorithm(Invited Paper)

We propose a novel spatial phase-shifting interferometry that exploits a genetic algorithm to compensate for geometric errors. Spatial phase-shifting interferometry is more suitable for measuring objects with properties that change rapidly in time than the temporal phase-shifting interferometry. However, it is more susceptible to the geometric errors since the positions at which interferograms are collected are different. In this letter, we propose a spatial phase-shifting interferometry with separate paths for object and reference waves. Also, the object wave estimate is parameterized in terms of geometric errors, and the error is compensated by using a genetic algorithm.

基于多模型集成算法的光纤陀螺温度补偿及实现

为降低光纤陀螺因温度效应产生的零偏漂移,以基于最小二乘法的多项式补偿模型和经遗传算法优化后的BP神经网络模型(GA-BP)为基学习器,通过集成学习算法建立了光纤陀螺的温度补偿模型,并对补偿后的光纤陀螺进行在线温度补偿实验。实验结果表明,该模型在-40~+60℃温变环境下将光纤陀螺的全过程零偏漂移降低了85%以上,且补偿后的启动段零偏输出均值更接近零位。

The recent advances and future perspectives of genetic compensation studies in the zebrafish model

Genetic compensation is a remarkable biological concept to explain the genetic robustness in an organism to maintain its fitness and viability if there is a disruption occurred in the genetic variation by mutation.However,the underlying mechanism in genetic compensation remain unsolvable.The initial concept of genetic compensation has been studied in model organisms when there was a discrepancy between knockout-mediated and knockdown-mediated phenotypes.In the zebrafish model,several studies have reported that zebrafish mutants did not exhibit severe phenotype as shown in zebrafish morphants for the same genes.This phenomenon in zebrafish mutants but not morphants is due to the response of genetic compensation.In 2019,two amazing works partially uncovered genetic compensation could be triggered by the upregulation of compensating genes through regulating NMD and/or PTC-bearing mRNA in collaboration with epigenetic machinery in mutant zebrafish.In this review,we would like to update the recent advances and future perspectives of genetic compensation studies,which including the hypothesis of time-dependent involvement and addressing the discrepancy between knockout-mediated and knockdown-mediated to study gene function in the zebrafish model.At last,the study of genetic compensation could be a potential therapeutic strategy to treat human genetic disorder related diseases.

The First Crested Duck Genome Reveals Clues to Genetic Compensation and Crest Cushion Formation

The Chinese crested(CC)duck is a unique indigenous waterfowl breed,which has a crest cushion that affects its survival rate.Therefore,the CC duck is an ideal model to investigate the genetic compensation response to maintain genetic stability.In the present study,we first generated a chromosome-level genome of CC ducks.Comparative genomics revealed that genes related to tissue repair,immune function,and tumors were under strong positive selection,indicating that these adaptive changes might enhance cancer resistance and immune response to maintain the genetic stability of CC ducks.We also assembled a Chinese spot-billed(Csp-b)duck genome,and detected the structural variations(SVs)in the genome assemblies of three ducks(i.e.,CC duck,Csp-b duck,and Peking duck).Functional analysis revealed that several SVs were related to the immune system of CC ducks,further strongly suggesting that genetic compensation in the anti-tumor and immune systems supports the survival of CC ducks.Moreover,we confirmed that the CC duck originated from the mallard ducks.Finally,we revealed the physiological and genetic basis of crest traits and identified a causative mutation in TAS2R40 that leads to crest formation.Overall,the findings of this study provide new insights into the role of genetic compensation in adaptive evolution.

Molecular mechanism of genetic compensation response

With the support by the National Natural Science Foundation of China,the research team led by Prof.Chen Jun(陈军)at the MOE Key Laboratory of Biosystems Homeostasis&Protection and Innovation Center for Cell Signaling Network,College of Life Sciences,Zhejiang University,uncovered the molecular mechanism of genetic compensation response(GCR),which was published in Nature(2019,568(7751):259—263).

矿用乳化液泵站泵头供液流量匹配控制研究

供液流量匹配的精确控制有助于减少矿山作业设备因液压波动而出现的故障,为此研究比例溢流阀压力补偿下矿用乳化液泵站泵头供液流量匹配控制方法,以泵站泵头在一定时间内完成所有动作乳化液流量负荷波动率和消耗能源量作为目标函数,建立矿用乳化液泵站泵头供液流量匹配控制模型,设置模型约束函数后,利用遗传算法求解供液流量匹配控制模型,得出控制结果。实验表明:该方法计算比例溢流阀当前压力数值较为准确,可迅速对比例溢流阀压力进行补偿,同时可有效对乳化液泵站泵头供液流量进行匹配控制,应用效果较为显著。

基于混沌-遗传混合算法的多目标优化无功补偿研究

由于电力系统中存在感性负载和容性负载,导致电力系统存在电压波动。为提高电力系统无功补偿的准确性,提出了一种基于混沌-遗传混合算法的多目标优化无功补偿方法。首先,将混沌算法与遗传算法相结合,在初始阶段先利用遗传算法的全局搜索能力快速找到一组较好的初始解,随后使用混沌算法进行局部搜索和优化。其次,构建了一个多目标无功补偿优化模型。最后,基于IEEE 30节点进行了试验分析,试验结果表明,所提出的方法能有效地提高电力系统无功补偿的准确度,从而提高电力系统的运行可靠性。

基于改进遗传算法的低压配电网无功补偿自动优化方法

由于未设定低压配电网多阶约束条件,当前方法无功补偿优化效果较差。基于此,提出基于改进遗传算法的低压配电网无功补偿自动优化方法。首先选择无功补偿点,然后基于改进遗传算法设定低压配电网多阶约束条件,最后使用设定的约束条件和改进遗传算法构建无功补偿优化模型,实现无功补偿功能。结果表明,该方法能够降低低压传输环境下的电网传输流失效率,优化效果较好。

基于GA-BP激光甲烷检测压力补偿方法的研究

近年来TDLAS技术已成为实现高精度甲烷气体测量最重要的技术之一,但是压力的变化会影响甲烷气体的吸收系数,造成检测出现误差,因此设计高精度、稳定性好、易于实现的甲烷气体压力补偿方法是急需解决的关键问题。针对传统BP神经网络算法易于陷入局部极小化,局部优化效率低的问题,提出一种采用具有出色全局寻优力的GA遗传算法与BP神经网络融合的方法对甲烷气体测得数据进行压力补偿。试验结果表明,采用GA-BP算法得到的压力补偿效果明显优于采用传统的BP神经网络算法,具有更加优越的压力补偿精度,最终证明了使用该种方式的可行性,为甲烷气体检测时的压力补偿手段提供了参考价值。