Pub Date : 2020-02-04DOI: 10.11648/J.BE.20200401.11
A. Baset, Qun Liu, B. Liao, A. Waris, I. Ahmad, H. Yanan, Zhang Qingqing
Length frequency data of Pomadasys maculatus (Bloch, 1793) was collected during 2012 and 2014 from Pakistan waters. Total 1387 fish individuals (pooled) were collected ranging from 7-22 cm (total length). Weight ranging 5-105 g. The data were analyzed for the estimation of population dynamics. The power coefficient of 2.532 in 2012 and 2.560 in 2014. The von Bertalanffy growth parameters of 23.10 cm (L∞), 0.480year-1 (K) for 2012 and 23.10 cm (L∞), 0.570year-1 (K) for 2014, were calculated by ELEFAN method. The Z was 2.06years-1 for 2012 and 2.07year-1 for 2014. The M) was1.16 year-1 for 2012 and 1.30 year-1 for 2014 calculated with Pauly’s equation. Therefore, the F was 0.9 years-1 in 2012 and 0.77years-1 in 2014. The exploitation ratio was estimated to be 0.43 and 0.32 respectively. The YPRA (yield-per-recruit analysis) indicated that the estimated Fmax was 1 for both years, when tc was 1. Fcurrent was 0.9 and 0.77 (for 2012 and 2014 respectively) which was less than Fmax. With Gulland method, the BRPs for the fishery (Fopt) was estimated at 1.16 years-1 and 1.30 years-1 respectively, higher than current fish mortality. Accordingly, the Pomadasys maculatus fishery is in managing the condition in Pakistani waters.
2012年和2014年在巴基斯坦水域收集了斑马鱼(Pomadasys maculatus, Bloch, 1793)的长度频率数据。共捕获鱼体1387条(池)，体长7 ~ 22 cm。重量在5-105克之间。对数据进行分析，估计种群动态。2012年的功率系数为2.532,2014年为2.560。采用ELEFAN方法计算了2012年和2014年的von Bertalanffy生长参数分别为23.10 cm (L∞)，0.480year-1 (K)和23.10 cm (L∞)，0.570year-1 (K)。2012年和2014年的Z值分别为2.06年和2.07年。根据保利方程计算，2012年和2014年的M值分别为1.16和1.30。因此，2012年F为0.9年-1,2014年F为0.77年-1。开采率分别为0.43和0.32。YPRA (yield-per-recruit analysis)表明，当tc为1时，这两年的估计Fmax均为1。Fcurrent分别为0.9和0.77(2012年和2014年)，小于Fmax。使用Gulland方法，渔业的brp (Fopt)分别为1.16年和1.30年，高于当前鱼类死亡率。因此，Pomadasys maculatus渔业正在管理巴基斯坦水域的情况。
{"title":"Population Dynamics of Saddle Grunt Fish, Pomadasys maculatus (Bloch, 1793) from Pakistani Waters","authors":"A. Baset, Qun Liu, B. Liao, A. Waris, I. Ahmad, H. Yanan, Zhang Qingqing","doi":"10.11648/J.BE.20200401.11","DOIUrl":"https://doi.org/10.11648/J.BE.20200401.11","url":null,"abstract":"Length frequency data of Pomadasys maculatus (Bloch, 1793) was collected during 2012 and 2014 from Pakistan waters. Total 1387 fish individuals (pooled) were collected ranging from 7-22 cm (total length). Weight ranging 5-105 g. The data were analyzed for the estimation of population dynamics. The power coefficient of 2.532 in 2012 and 2.560 in 2014. The von Bertalanffy growth parameters of 23.10 cm (L∞), 0.480year-1 (K) for 2012 and 23.10 cm (L∞), 0.570year-1 (K) for 2014, were calculated by ELEFAN method. The Z was 2.06years-1 for 2012 and 2.07year-1 for 2014. The M) was1.16 year-1 for 2012 and 1.30 year-1 for 2014 calculated with Pauly’s equation. Therefore, the F was 0.9 years-1 in 2012 and 0.77years-1 in 2014. The exploitation ratio was estimated to be 0.43 and 0.32 respectively. The YPRA (yield-per-recruit analysis) indicated that the estimated Fmax was 1 for both years, when tc was 1. Fcurrent was 0.9 and 0.77 (for 2012 and 2014 respectively) which was less than Fmax. With Gulland method, the BRPs for the fishery (Fopt) was estimated at 1.16 years-1 and 1.30 years-1 respectively, higher than current fish mortality. Accordingly, the Pomadasys maculatus fishery is in managing the condition in Pakistani waters.","PeriodicalId":8944,"journal":{"name":"Bioprocess Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76838448","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}
Pub Date : 2020-02-04DOI: 10.11648/J.BE.20200401.13
E. Irankhah
Amnesia, commonly referred to as Alzheimer’s, is a type of brain dysfunction that gradually dissipates the patient’s mental abilities. Memory disorder usually develops gradually and progresses. At first, memory impairment is limited to recent events and lessons, but old memories are gradually damaged. In this disease, the connection between nerve cells by the formation of neurofibrillary nodes disappeared. Currently, treatment for the disease mainly involves symptomatic treatments, treatment of behavioral disorders and medication use. Although there is no cure for Alzheimer's disease yet, medications can slow the progression of the disease and reduce the severity of memory impairment and behavioral problems. Today, whit the spread of definitive treatment for this disease, in this study, new techniques for the treatment of this disease can be explored by examining the early detection methods of the disease through brain signal processing with classifiers and medical imaging such as MRI and CT Scan. Signal processing has included EEG and ERP brain signals and the use of classifiers such as SVM, LDA and Neural network. In medical image processing, a combination of Neural network and Wavelet is used to expedite the time of diagnosis according to the above method. Given the process under consideration, combining brain signals and medical imaging can provide valuable help in early detection of Alzheimer disease.
{"title":"Evaluation of Early Detection Methods for Alzheimer's Disease","authors":"E. Irankhah","doi":"10.11648/J.BE.20200401.13","DOIUrl":"https://doi.org/10.11648/J.BE.20200401.13","url":null,"abstract":"Amnesia, commonly referred to as Alzheimer’s, is a type of brain dysfunction that gradually dissipates the patient’s mental abilities. Memory disorder usually develops gradually and progresses. At first, memory impairment is limited to recent events and lessons, but old memories are gradually damaged. In this disease, the connection between nerve cells by the formation of neurofibrillary nodes disappeared. Currently, treatment for the disease mainly involves symptomatic treatments, treatment of behavioral disorders and medication use. Although there is no cure for Alzheimer's disease yet, medications can slow the progression of the disease and reduce the severity of memory impairment and behavioral problems. Today, whit the spread of definitive treatment for this disease, in this study, new techniques for the treatment of this disease can be explored by examining the early detection methods of the disease through brain signal processing with classifiers and medical imaging such as MRI and CT Scan. Signal processing has included EEG and ERP brain signals and the use of classifiers such as SVM, LDA and Neural network. In medical image processing, a combination of Neural network and Wavelet is used to expedite the time of diagnosis according to the above method. Given the process under consideration, combining brain signals and medical imaging can provide valuable help in early detection of Alzheimer disease.","PeriodicalId":8944,"journal":{"name":"Bioprocess Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78302600","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}
Pub Date : 2020-01-01DOI: 10.1016/B978-0-444-59525-6.00003-2
Shijie Liu
{"title":"An overview of chemical reaction analysis","authors":"Shijie Liu","doi":"10.1016/B978-0-444-59525-6.00003-2","DOIUrl":"https://doi.org/10.1016/B978-0-444-59525-6.00003-2","url":null,"abstract":"","PeriodicalId":8944,"journal":{"name":"Bioprocess Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79973925","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}
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