Current Signal Transduction Therapy最新文献_第8页

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Current Signal Transduction Therapy Pub Date : 2020-12-01 DOI: 10.2174/157436241502200720093533

Sung-Gook Cho

引用次数: 0

Trends and Applications of Brain Computer Interfaces 脑机接口的发展趋势及应用

Current Signal Transduction Therapy Pub Date : 2020-11-24 DOI: 10.2174/1574362415999201124224606

D. Yadav, S. Yadav, K. Veer

引用次数: 2

Exploring the abnormal signal transduction mediated internet addiction and gaming disorders 异常信号转导介导的网络成瘾和游戏障碍

Current Signal Transduction Therapy Pub Date : 2020-11-10 DOI: 10.2174/1574362415999201110101418

Bhumika Chauhan, S. Nandi

{"title":"Exploring the abnormal signal transduction mediated internet addiction and gaming disorders","authors":"Bhumika Chauhan, S. Nandi","doi":"10.2174/1574362415999201110101418","DOIUrl":"https://doi.org/10.2174/1574362415999201110101418","url":null,"abstract":"\u0000\u0000The world is connected by the internet. It is very useful because we use Google to find out any new topic, to\u0000search new places, to quest updated research, and to get knowledge for learnng. The person around the world can\u0000communicate with each other through the Google video conference talk. Internet is frequently used in smartphones, laptops,\u0000desktop, and tablet. Excessive affinity towards internet-based online data collection, downloading pictures, videos, cyber\u0000relationships, and social media may produce addiction disorders followed by different symptoms such as behaviors change,\u0000mind disturbance, depression, anxiety, loss of appetite hyperactivity, sleeping disorder, headache, visual fatigueness,\u0000trafficking of memory, attention-deficit, loss of efficiency in work and social detachment which may be caused by an\u0000imbalance of neurotransmitters. This is very difficult to control because of abnormal signal transduction in the brain. The\u0000present study is an attempt to discuss internet addiction disorder (IAD), internet gaming disorder (IGD), and give awareness\u0000to society to get rid of this addiction. \u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46741673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification and Characterization of SNP Mutation in Genes related to Non-small cell lung cancer 非小细胞肺癌相关基因SNP突变的鉴定与鉴定

Current Signal Transduction Therapy Pub Date : 2020-08-19 DOI: 10.2174/1574362415999200819202218

Neelambika B. Hiremath, Dayananda P

{"title":"Identification and Characterization of SNP Mutation in Genes related to Non-small cell lung cancer","authors":"Neelambika B. Hiremath, Dayananda P","doi":"10.2174/1574362415999200819202218","DOIUrl":"https://doi.org/10.2174/1574362415999200819202218","url":null,"abstract":"\u0000\u0000 The advent of Next Generation Sequencing (NGS) has created a high throughput\u0000platform, to identify disease traits and phenotypic characteristics using RNASeq Sequencing analysis in humans. Non-small\u0000cell lung cancer (NSCLC), a lethal disease accounts for 85 percent of most lung cancers with very small window ofsurvival\u0000rate. The decision of tumour image bio marker impression can be improved by gene profile. Hence there is a need to\u0000characterise the variants in the disease manifestation.\u0000\u0000\u0000\u0000To understand the SNP’s in the major genes responsible for NSCLC, RNASeq data of patients aged above 50\u0000years, were downloaded from SRA database. The quality matrix analysis is mapped to Genome reference consortium human\u0000build 38 (GRCh38) to call the variants and identify SNP’s with the tuxedo protocol.\u0000\u0000\u0000\u0000 The SNP’s and the patterns of variants were analysed to see the comparison between healthy individual and NSCLC\u0000patients, and in between patients of different age. Oncogenes commonly associated with the NSCLC like KRAS, EGFR,\u0000ALK, BRAF and HER2 were mainly analysed to see the SNP’s and their characterisations with respect to the functional\u0000change was done.\u0000\u0000\u0000\u0000 The SNP’s with the greater quality scores belonging to the above said genes were identified which gives us a\u0000baseline to understand the NSCLC at the Genomic level. Further fold change of these genes to the frequency of variant can\u0000be mapped to understand the NSCLC at a greater depth.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43885274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

How India Fights with COVID-19 with Learning from Highly Affected Countries 印度如何与新冠肺炎作斗争，向疫情严重国家学习

Current Signal Transduction Therapy Pub Date : 2020-08-07 DOI: 10.2174/1574362415999200807154418

P. Sharma, K. Veer

引用次数: 2

A New Approach of Position Sensorless Control for Brushless DC Motor 一种新的无刷直流电机位置传感器控制方法

Current Signal Transduction Therapy Pub Date : 2020-07-31 DOI: 10.2174/1574362413666180713092948

N. Hemalatha, S. Nageswari

引用次数: 1

Preface 前言

Current Signal Transduction Therapy Pub Date : 2020-07-31 DOI: 10.2174/157436241501200714100433

Jingxuan Yang

引用次数: 1

Efficient Spectral Allocation for Cognitive Full Duplex Relay Network Systems Based Soft Computing Technique 基于软计算技术的认知全双工中继网络系统的有效频谱分配

Current Signal Transduction Therapy Pub Date : 2020-07-31 DOI: 10.2174/1574362413666180831105203

C. Senthamarai, N. Malmurugan

{"title":"Efficient Spectral Allocation for Cognitive Full Duplex Relay Network Systems Based Soft Computing Technique","authors":"C. Senthamarai, N. Malmurugan","doi":"10.2174/1574362413666180831105203","DOIUrl":"https://doi.org/10.2174/1574362413666180831105203","url":null,"abstract":"\u0000\u0000Due to the huge development of wireless devices and mobile data traffic\u0000had gained attention towards identifying accurate solutions for more proficient utilization of the\u0000wireless spectrum. An essential issue confronting the future in wireless systems is to identify the\u0000appropriate spectrum bands to satisfy the request of future administrations. While the greater part\u0000of the radio spectrum is allocated to various services, applications and users show that spectrum\u0000usage is quite low.\u0000\u0000\u0000\u0000The spectrum sensing is performed at the start of each time slot before\u0000the data transmission. As a promising framework to improve the spectrum utilization, Cognitive\u0000Radio (CR) technique has the immense potential to meet such a necessity by permitting unlicensed\u0000users to exist together in licensed bands. In this paper Cognitive radio and Full-Duplex\u0000(FD) based two-way relay communications are developed to enhance spectrum utilization for multichannel\u0000and to decrease the false alarm rate.\u0000\u0000\u0000\u0000To solve the optimization problems in spectral efficiency, soft computing techniques is\u0000proposed to minimize the self-interference and delay to the licensed users. In this proposed work\u0000the kurtosis parameter is used for channel detection to determine whether the signal is present or\u0000not.\u0000\u0000\u0000\u0000The performance results of the proposed method are evaluated in terms of spectral\u0000allocation and outage probability which achieves better performance than the existing Multi-\u0000Objective Genetic Algorithm (MOGA) optimization.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45649404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Black Hole Attack Detection in Healthcare Wireless Sensor Networks Using Independent Component Analysis Machine Learning Technique 利用独立分量分析机器学习技术检测医疗保健无线传感器网络中的黑洞攻击

Current Signal Transduction Therapy Pub Date : 2020-07-31 DOI: 10.2174/1574362413666180705123733

A. Sunder, A. Shanmugam

{"title":"Black Hole Attack Detection in Healthcare Wireless Sensor Networks Using Independent Component Analysis Machine Learning Technique","authors":"A. Sunder, A. Shanmugam","doi":"10.2174/1574362413666180705123733","DOIUrl":"https://doi.org/10.2174/1574362413666180705123733","url":null,"abstract":"\u0000\u0000 Wireless Sensor Networks (WSNs) are self-configured infrastructure-less\u0000networks are comprising of a number of sensing devices used to monitor physical or environmental\u0000quantities such as temperature, sound, vibration, pressure, motion etc. They collectively transmit\u0000data through the network to a sink where it is observed and analyzed.\u0000\u0000\u0000\u0000The major issues in WSN are interference, delay and attacks that degrade\u0000their performance due to their distributed nature and operation. Timely detection of attacks is imperative\u0000for various real time applications like healthcare, military etc. To improve the Black hole\u0000attack detection in WSN, Projected Independent Component Analysis (PICA) technique is proposed\u0000herewith, which detects black hole attack by analyzing collected physiological data from\u0000biomedical sensors.\u0000\u0000\u0000\u0000The PICA technique performs attack detection through Mutual information to measure\u0000the dependence in the joint distribution. The dependence among the nodes is identified based on\u0000the independent probability distribution functions and mutual probability function.\u0000\u0000\u0000\u0000The black hole attack isolation is then performed through the distribution of the\u0000attack separation message. This supports to improve Packet Delivery Ratio (PDR) with minimum\u0000delay. The simulation is carried out based on parameters such as black hole attack detection rate\u0000(BHADR), Black Hole Attack Detection Time (BHADT), False Positive Rate (FPR), PDR and delay.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":"56-64"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45931324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Genetic Algorithm to Evaluate Downstream and Upstream Information Sharing 遗传算法评估上下游信息共享

Current Signal Transduction Therapy Pub Date : 2020-07-31 DOI: 10.2174/1574362413666180830105740

Mansour Rached

引用次数: 1