Mutation detection and fast identification of switching system based on data-driven method

In the engineering field,switching systems have been extensively studied,where sudden changes of parameter value and structural form have a significant impact on the operational performance of the system.Therefore,it is important to predict the behavior of the switching system,which includes the accurate detection of mutation points and rapid reidentification of the model.However,few efforts have been contributed to accurately locating the mutation points.In this paper,we propose a new measure of mutation detection—the threshold-based switching index by analogy with the Lyapunov exponent.We give the algorithm for selecting the optimal threshold,which greatly reduces the additional data collection and the relative error of mutation detection.In the system identification part,considering the small data amount available and noise in the data,the abrupt sparse Bayesian regression(abrupt-SBR)method is proposed.This method captures the model changes by updating the previously identified model,which requires less data and is more robust to noise than identifying the new model from scratch.With two representative dynamical systems,we illustrate the application and effectiveness of the proposed methods.Our research contributes to the accurate prediction and possible control of switching system behavior.

An Improved Reptile Search Algorithm Based on Cauchy Mutation for Intrusion Detection

With the growth of the discipline of digital communication,the topic has acquiredmore attention in the cybersecuritymedium.The Intrusion Detection(ID)system monitors network traffic to detect malicious activities.The paper introduces a novel Feature Selection(FS)approach for ID.Reptile Search Algorithm(RSA)—is a new optimization algorithm;in this method,each agent searches a new region according to the position of the host,which makes the algorithm suffers from getting stuck in local optima and a slow convergence rate.To overcome these problems,this study introduces an improved RSA approach by integrating Cauchy Mutation(CM)into the RSA’s structure.Thus,the CM can effectively expand search space and enhance the performance of the RSA.The developed RSA-CM is assessed on five publicly available ID datasets:KDD-CUP99,NSL-KDD,UNSW-NB15,CIC-IDS2017,and CIC-IDS2018 and two engineering problems.The RSA-CM is compared with the original RSA,and three other state-of-the-art FS methods,namely particle swarm optimization,grey wolf optimization,and multi-verse optimizer,and quantitatively is evaluated using fitness value,the number of selected optimum features,accuracy,precision,recall,and F1-score evaluationmeasures.The results reveal that the developed RSA-CMgot better results than the other competitive methods applied for FS on the ID datasets and the examined engineering problems.Moreover,the Friedman test results confirm that RSA-CMhas a significant superiority compared to other methods as an FS method for ID.

Complex heterozygous mutations in hereditary spherocytosis:A case report

BACKGROUND The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis(HS)in children.We also hope to promote the application of gene detection technology in children with HS,with the goals of identifying more related gene mutations,supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children,and providing important guidance for the diagnosis,treatment,and prevention of HS in children.CASE SUMMARY A 1-year and 5-month-old patient presented jaundice during the neonatal period,mild anemia 8 months later,splenic enlargement at 1 year and 5 months,and brittle red blood cell permeability.Genetic testing was performed on the patient,their parents,and sister.Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1.Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother.Combined with the clinical symptoms of the children,it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause,providing important guidance for revealing the pathogenesis,diagnosis,treatment,and promotion of gene detection technology in children with HS.CONCLUSION This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1,which provides a reference for exploring HS.

Rapid Detection of rpoB Gene Mutations in Rif-resistant M.tuberculosis Isolates by Oligonucleotide Microarray

Objective To detect the specific mutations in rpoB gene of Mycobacterium tuberculosis by oligonucleotide microarray. Methods Four wild-type and 8 mutant probes were used to detect rifampin resistant strains. Target DNA of M. tuberculosis was amplified by PCR, hybridized and scanned. Direct sequencing was performed to verify the results of oligonucleotide microarray Results Of the 102 rifampin-resistant strains 98 （96.1%） had mutations in the rpoB genes. Conclusion Oligonucleotide microarray with mutation-specific probes is a reliable and useful tool for the rapid and accurate diagnosis of rifampin resistance in M. tuberculosis isolates.

APPLICATION OF GENETIC DEAFNESS GENE CHIP FOR DETECTION OF GENE MUTATION OF DEAFNESS IN PREGNANT WOMEN

Objective The study is to identify the carrier rate of common deafness mutation in Chinese pregnant women via detecting deafness gene mutations with gene chip. Methods The pregnant women in obstetric clinic without hearing impairment and hearing disorders family history were selected. The informed consent was signed. Peripheral blood was taken to extract genom- ic DNA. Application of genetic deafness gene chip for detecting 9 mutational hot spot of the most common 4 Chinese deafness genes, namely GJB2 （35delG, 176del16bp, 235delC, 299delAT）, GJB3 （C538T） ,SLC26A4 （ IVS72A〉G, A2168G） and mito- chondrial DNA 12S rRNA （A1555G, C1494T） . Further genetic testing were provided to the spouses and newborns of the screened carriers. Results Peripheral blood of 430 pregnant women were detected, detection of deafness gene mutation carri- ers in 24 cases（4.2%）, including 13 cases of the GJB2 heterozygous mutation, 3 cases of SLC26A4 heterozygous mutation, 1 cases of GJB3 heterozygous mutation, and 1 case of mitochondrial 12S rRNA mutation. 18 spouses and 17 newborns took further genetic tests, and 6 newborns inherited the mutation from their mother. Conclusion The common deafness genes muta- tion has a high carrier rate in pregnant women group, 235delC and IVS7-2A〉G heterozygous mutations are common.

Highly sensitive ECL-PCR method for detection of K-ras point mutation

A highly sensitive electrochemiluminescence-polymerase chain reaction (ECL-PCR) method for K-ras point mutation detection is developed. Briefly, K-ras oncogene was amplified by a Ru(bpy)3(2+) (TBR)-labeled forward and a biotin-labeled reverse primer, and followed by digestion with MvaI restriction enzyme, which only cut the wild-type amplicon containing its cutting site. The digested product was then adsorbed to the streptavidin-coated microbead through the biotin label and detected by ECL assay. The experiment results showed that the different genotypes can be clearly discriminated by ECL-PCR method. It is useful in point mutation detection, due to its sensitivity, safety, and simplicity.

DETECTION OF p53 GENE MUTATION OF BRONCHOSCOPIC SAMPLIES IN THE PATIENTS SUSPECTED TO LUNG CANCER

Objective: To determine the feasibility of detecting p53 gene mutations for early diagnosis of lung cancer using the samples from bronchoscopic examination. Methods: Point mutations of the exon 5-8 of p53 gene were detected in 85 bronchoscopic samples of 35 patients suspected to be lung cancer using silver staining PCR-SSCP. Results: p53 gene mutations were founded in 10 of 35 patients(28.6%). The incidence of p53 gene mutations (14.9%) was obviously higher than the cytological positive incidence(2.9%) in samples of sputum, bronchoalveolar lavage and brush, especially for the sputum(27.7%). In the bronchoscopic biopsy specimens, the incidence of p53 gene mutations (12.5%) was lower than that of pathologic positive result (50.0%). However, in view of all the bronchoscopic samples, there was no statistically difference between cytopathologic positive results (11.8%) and the incidence of p53 gene mutations (14.1%). Although the p53 mutations were most common in the samples from the patients bronchoscopically manifested as neoplasm compared with other manifestations, there was no statistical difference. It is valuable to notice that 3 patients with p53 gene mutation merely presented as bronchial inflammation in bronchoscope. Conclusion: Results indicated that the value of detecting p53 gene mutation for the diagnosis of lung cancer using the bronchoscopic samples was more superior to cytological examination and detection of p53 gene mutations in post-bronchoscopic sputum was easy and effective, may be used as a valuable method for early diagnosis of lung cancer.

Direct detection of rpoB and katG gene mutations of Mycobacterium tuberculosis in clinical samples

To study the rpoB and katG gene mutation rate and its markers.MethodsCross-sectional study methods were used to study Tuberculosis. A total of 45 sputum samples were collected from Annapurna Neurological Institute and Allied sciences. Then, acid fast bacilli staining were performed. Positive and negative samples were carried for conventional polymerase chain reaction identification and electrophoresis.ResultsOut of 45 samples, 3 were acid fast bacilli positive and the rest were negative. Male participants were more as compare to female participants and the mutation in rpoB and katG gene was found similar i.e. 6.66% among the total samples.ConclusionsWe can conclude that genetic mutation in Mycobacterium tuberculosis can be identified directly from the clinical samples. However, we have carried this study in less sample size and to validate research on large number of sample is recommended.

DETECTION OF GENE MUTATION IN SPUTUM OF LUNG CANCER PATIENT

Lungcancerisacommonmalignanttumor,whichhasahighincidenceandmortalityrate.Therefore,itisnecessarytoseekanewmethodforthediagnosis,especiallytheearlydiagnosisoflungcancer.Thedevelopmentofmolecularbiologymakesthegenediagnosisoflungcancerpossible.PCR-SSCP...

Novel Metrics for Mutation Analysis

A measure of the“goodness”or efficiency of the test suite is used to determine the proficiency of a test suite.The appropriateness of the test suite is determined through mutation analysis.Several Finite State Machine(FSM)mutants are produced in mutation analysis by injecting errors against hypotheses.These mutants serve as test subjects for the test suite(TS).The effectiveness of the test suite is proportional to the number of eliminated mutants.The most effective test suite is the one that removes the most significant number of mutants at the optimal time.It is difficult to determine the fault detection ratio of the system.Because it is difficult to identify the system’s potential flaws precisely.In mutation testing,the Fault Detection Ratio(FDR)metric is currently used to express the adequacy of a test suite.However,there are some issues with this metric.If both test suites have the same defect detection rate,the smaller of the two tests is preferred.The test case(TC)is affected by the same issue.The smaller two test cases with identical performance are assumed to have superior performance.Another difficulty involves time.The performance of numerous vehicles claiming to have a perfect mutant capture time is problematic.Our study developed three metrics to address these issues:FDR/|TS|,FDR/|TC|,and FDR/|Time|;In this context,most used test generation tools were examined and tested using the developed metrics.Thanks to the metrics we have developed,the research contributes to eliminating the problems related to performance measurement by integrating the missing parameters into the system.

Moving Multi-Object Detection and Tracking Using MRNN and PS-KM Models

On grounds of the advent of real-time applications,like autonomous driving,visual surveillance,and sports analysis,there is an augmenting focus of attention towards Multiple-Object Tracking(MOT).The tracking-by-detection paradigm,a commonly utilized approach,connects the existing recognition hypotheses to the formerly assessed object trajectories by comparing the simila-rities of the appearance or the motion between them.For an efficient detection and tracking of the numerous objects in a complex environment,a Pearson Simi-larity-centred Kuhn-Munkres(PS-KM)algorithm was proposed in the present study.In this light,the input videos were,initially,gathered from the MOT dataset and converted into frames.The background subtraction occurred whichfiltered the inappropriate data concerning the frames after the frame conversion stage.Then,the extraction of features from the frames was executed.Afterwards,the higher dimensional features were transformed into lower-dimensional features,and feature reduction process was performed with the aid of Information Gain-centred Singular Value Decomposition(IG-SVD).Next,using the Modified Recurrent Neural Network(MRNN)method,classification was executed which identified the categories of the objects additionally.The PS-KM algorithm identi-fied that the recognized objects were tracked.Finally,the experimental outcomes exhibited that numerous targets were precisely tracked by the proposed system with 97%accuracy with a low false positive rate(FPR)of 2.3%.It was also proved that the present techniques viz.RNN,CNN,and KNN,were effective with regard to the existing models.

Novel detection method for infrared small targets using weighted information entropy

This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection.

Early detection of circulating tumor DNA and successful treatment with osimertinib in thr790met-positive leptomeningeal metastatic lung cancer:A case report

BACKGROUND Patients diagnosed with non-small-cell lung cancer with activated epidermal growth factor receptor mutations are more likely to develop leptomeningeal(LM)metastasis than other types of lung cancers and have a poor prognosis.Early diagnosis and effective treatment of leptomeningeal carcinoma can improve the prognosis.CASE SUMMARY A 55-year-old female with a progressive headache and vomiting for one month was admitted to Peking University First Hospital.She was diagnosed with lung adenocarcinoma with osseous metastasis 10 months prior to admittance.epidermal growth factor receptor(EGFR)mutation was detected by genomic examination,so she was first treated with gefitinib for 10 months before acquiring resistance.Cell-free cerebrospinal fluid(CSF)circulating tumor DNA detection by next-generation sequencing was conducted and indicated the EGFR-Thr790Met mutation,while biopsy and cytology from the patient’s CSF and the first enhanced cranial magnetic resonance imaging(MRI)showed no positive findings.A month later,the enhanced MRI showed linear leptomeningeal enhancement,and the cytology and biochemical examination in CSF remained negative.Therefore,osimertinib(80 mg/d)was initiated as a second-line treatment,resulting in a good response within a month.CONCLUSION This report suggests clinical benefit of osimertinib in LM patients with positive detection of the EGFR-Thr790Met mutation in CSF and proposes that the positive findings of CSF circulating tumor DNA as a liquid biopsy technology based on the detection of cancer-associated gene mutations may appear earlier than the imaging and CSF findings and may thus be helpful for therapy.Moreover,the routine screening of chest CT with the novel coronavirus may provide unexpected benefits。

基于机器视觉的高鲁棒轨道表面缺陷检测方法

研究目的:为了解决轨道缺陷检测系统在实际自然环境因素干扰下由于鲁棒性下降从而造成决策的不确定性问题,提出一种提高检测系统鲁棒性的方法,首先利用变异算法处理生成多样化的鲁棒训练样本,使模型能够学习适应各种环境扰动和变化,然后选择基于YOLOv5的目标检测模型作为轨道缺陷检测器,以满足高精度、实时性的要求,且准确性较高。研究结论:(1)通过变异生成算法,可以生成更多样性的鲁棒训练样本,使模型有更多的样本来学习各种扰动,以此适应各种环境;(2)所选YOLOv5目标检测模型作为轨道缺陷检测器,不仅能满足轨道缺陷检测对检测精度和实时性的高要求,而且即使在训练样本数量有限的情况下,也能凭借其优秀的泛化能力取得良好的检测效果,契合了实际轨道检测场景下对数据获取的困难,展现出较强的适用性;(3)在真实地铁线路上采集轨道巡检数据进行实验,实验结果表明,经过鲁棒重训练的轨道缺陷检测器在扰动数据上的鲁棒性得到了显著的提升,平均准确率提高23.35%,召回率提高32.75%,mAP50提高30.98%,mAP50-95提高19.54%;(4)本研究成果可应用于铁路、地铁等交通领域,有助于保障线路的安全运行。

基于改进鲸鱼算法优化SVM的软件缺陷检测方法

为解决传统支持向量机在软件缺陷检测中存在分类精度低、参数选择困难等问题,文章提出一种基于改进鲸鱼算法优化SVM的软件缺陷检测方法LFWOA-SVM。首先针对鲸鱼算法在求解过程中存在收敛速度慢、寻优效率低和局部最优解问题,基于Levy飞行策略优化鲸鱼觅食阶段,最大限度地实现搜索代理多样化,并利用混合变异扰动算子提高WOA的全局寻优能力;然后采用改进的鲸鱼算法LFWOA对SVM的惩罚因子和核函数参数进行优化,在获得最优参数的同时可有效检测软件缺陷。仿真实验表明,在6个基准测试函数中,LFWOA展现出更高的寻优速度和全局搜索能力;在8个公开软件缺陷数据集上进行测试显示,LFWOA-SVM方法能够有效提高分类性能和预测精度。

全光通信网络非线性突变频率干扰检测算法

【目的】针对全光通信网络非线性突变频率干扰问题进行分析时,主要依托于估计信道协方差直接展开干扰检测,并未展开网络通信信号变换处理,使得检测结果的F1⁃score值较低,为此提出了基于时域有限差分的全光通信网络非线性突变频率干扰检测算法。【方法】结合数据包抓包和镜像两种方式采集全光通信网络流量数据,并进行清理、转换和规约处理。依托于时域有限差分工作原理,在时域和频域空间内描述信号的时宽和带宽,应用导数与傅里叶变换算法对实时采集信号进行处理,利用变换后的信号分析非线性突变频率干扰情况,再针对变换后的信号进行检测分析。在时间⁃频率联合特征分析方法辅助下,提取干扰信号的时域、频域特征,依托于反向传播算法和最小化损失函数,简化非线性突变频率干扰检测过程,采用特征距离函数替换网络损失函数,并将其输入基于孪生网络的干扰识别模型中,得出非线性突变频率干扰检测结果。【结果】在不同噪声条件下,所提算法非线性突变频率干扰检测结果的F1⁃score值保持在0.95以上,检测时间低于40 ms。【结论】应用时域有限差分方法的新型检测方法,能够更准确地反映当前通信网络的干扰情况,保证通信网络正常运行,更好地满足了全光通信网络干扰检测要求。

测试集有效性评价:问题、进展与挑战

测试用例集的缺陷检测有效性指测试集能够在多大程度上检测出软件中存在的缺陷.如何评价测试集的缺陷检测有效性是一个重要问题.覆盖率和变异得分是两个最重要和最广泛使用的测试集有效性度量.为量化测试集的缺陷检测能力,研究人员对测试集有效性评价进行了大量研究并且取得了较大的进展.与此同时,现有研究存在不一致的结论,该领域依然存在一些亟待解决的挑战.对多年来国内外学者在测试集有效性评价领域的研究成果进行系统性的梳理和总结.首先,阐述测试集有效性评价研究中的问题.然后,介绍并分析基于覆盖率和基于变异得分的测试集有效性的评价以及介绍测试集有效性评价在测试集优化中的应用.最后,指出测试集有效性评价研究中面临的挑战并给出建议的研究方向.

Pool-ARMS:一种高效检测混合遗传样本中特定单核苷酸变异的方法

单核苷酸变异(SNV)是控制人类疾病和动植物经济性状的遗传基础之一,经济、简便和高效的检测体系可助力遗传病筛查和植物碱基编辑与诱变群体中携带SNV的个体的定向筛选。本研究根据扩增阻滞突变系统PCR(ARMS-PCR)的原理,设计了一种适合在水稻混合样本中筛选特定SNV个体的方法 Pool-ARMS。该方法的要点是:设计聚合酶链式反应(PCR)引物、建立特异性扩增携带SNV片段的PCR程序;分析不同组织和样品混合比例提取DNA的扩增效果;建立筛选特定SNV的Pool-ARMS体系。以控制光周期敏感性雄性不育(PGMS)水稻的两个基因为例,通过优化PCR引物和反应程序,建立了利用叶片和芽鞘组织混样提取DNA检测突变的体系,前者突变检出水平为1∶49,后者为1∶24。利用该技术体系对63份碱基编辑水稻幼苗进行检测,结果与Sanger测序分析一致。本研究建立的Pool-ARMS方法有望应用于包括水稻在内的动植物单碱基编辑群体和理化诱变群体中目标变异的定向筛选。

针对恶意软件检测的特征选择与SVM协同优化

提出一种基于改进哈里斯鹰优化SVM和特征选择的恶意软件检测模型。为改进特征子集选取和SVM分类准确率,引入混沌映射、能量因子调节、最优解变异扰动和互利共生对HHO算法的初始种群结构、全局搜索与局部开采切换性能及跳离局部最优能力进行改进;利用改进算法优化SVM参数和特征子集选取,构建恶意软件检测模型。实验结果表明,改进算法在降低特征维度的同时可以有效提升分类准确率,利用高质量特征子集提升恶意软件检测模型的分类能力。

携带SOD1-p.A5S突变的1例肌萎缩侧索硬化患者病例报道及相关文献分析

目的肌萎缩侧索硬化症(amyotrophic lateral sclerosis,ALS)是一种进行性和致命的神经退行性疾病。目前认为Cu/Zn超氧化物歧化酶1基因(Cu/Zn superoxide dismutase gene 1,SOD1)突变是导致家族性ALS的原因之一,对可疑ALS家族史的患者进行SOD1基因测序可能有帮助。本文首次报道中国籍汉族SOD1-p.A5S突变的肌萎缩侧索硬化1例,并总结其临床特征。方法与结果首次报道中国籍汉族SOD1-p.A5S突变的1例ALS临床患者并复习相关病例文献,总结其临床特征。研究病例为男性,34岁,以“双下肢无力2年,加重伴双手无力半年”之主诉入住西安交通大学第一附属医院神经内科,主要临床表现为逐渐进展的四肢无力,无吞咽困难,无认知功能障碍。入院后进一步完善常规检查及肌电图等排除其他诊断,并行基因检测。结合患者典型的临床表现和肌电图提示颈髓、胸髓和腰髓三个区域存在下运动神经元受累的证据,合理排除其他诊断及特征性基因检测结果,诊断为ALS。基因检测结果提示患者存在SOD1一号外显子c.13G>T(p.A5S)杂合突变,其母有可疑病史但已死亡未进行基因验证。出院后随访截至2022年8月21日,随访时间共38个月,病程62个月。进一步查阅文献报道的同一位点突变的其他患者的临床特点,总结发现本例突变患者与其他文献报道同一位点突变患者进展较慢。结论基因测序是诊断家族性ALS的有利工具。SOD1一号外显子c.13G>T(p.A5S)突变为罕见的致病性变异,该亚型患者进展较慢,进一步说明基因检测在ALS的诊断和预后判定中具有重要价值。