Stocks of Mugil bananensis (Pellegrin, 1927) in the Estuary of Senegal River by Determining Yields Per Recruit and Biomass Per Recruit
Serigne Modou Sarr,
Mouhameth Camara,
Souleymane Sanogo
Issue:
Volume 6, Issue 6, December 2018
Pages:
74-79
Received:
22 November 2018
Accepted:
14 December 2018
Published:
19 January 2019
DOI:
10.11648/j.ajls.20180606.11
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Abstract: Mullet occupy an important place in artisanal fishing in the region of Saint-Louis. They provide substantial income to the various actors in the sector. Overfishing would adversely affect the recovery capacity of the Mugilidea stock in the Senegal River Estuary. A biological collapse is then to be feared. This risk is all the more so since fishermen from Saint-Louis go as far as Mauritania, Guinea Bissau and Sierra Leone to search for mules that have reached sexual maturity for their gonads. Works on the assessment of the stock status of M. bananensis have not been done in Senegal, although it has been carried out in other countries. The objective of the study is to contribute to the assessment of banana mullet stocks in the Senegal River estuary by determining yields per recruit and biomass per recruit. Data were collected on total length, total weight and the sex. FiSAT II and ViT4 softwares enabled analytical models based on virtual populations’ analysis, yield per recruit (Y / R) and biomass per recruit (B / R). The results obtained showed overexploitation of M. bananensis in the estuary of the Senegal River. The stock of M. bananensis is overexploited in sea and the coefficients of fishing mortality and total mortality are remarkably high to the class mastses fish of III+ age, IV+ and V+. In sum, the study allowed us to know the dynamics of exploitation of mules in the estuary of the Senegal River and to propose a management plan and management of banana mullet for a sustainable management of this species.
Abstract: Mullet occupy an important place in artisanal fishing in the region of Saint-Louis. They provide substantial income to the various actors in the sector. Overfishing would adversely affect the recovery capacity of the Mugilidea stock in the Senegal River Estuary. A biological collapse is then to be feared. This risk is all the more so since fisherme...
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Bayesian Modelling on Incidence of Pregnancy among HIV/AIDS Patient Women at Adare Hospital, Hawassa, Ethiopia
Yenesew Fentahun Gebrie,
Ayele Taye Goshu
Issue:
Volume 6, Issue 6, December 2018
Pages:
80-88
Received:
4 December 2018
Accepted:
9 January 2019
Published:
28 January 2019
DOI:
10.11648/j.ajls.20180606.12
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Abstract: HIV/AIDS is the most serious diseases human kind has ever faced and a public problem, particularly, for women of childbearing age. For HIV infected women, the prospects of getting pregnant and having an HIV negative baby could be significantly improved with the increasing of the availability of Antiretroviral Therapy (ART). Even though, ART treatment has shown significant effect of clinical importance to reduce the risk of mother to child transmission of HIV but, HIV infected Women remain poorly understood or they fear to be pregnant and having HIV negative child. To the authors’ knowledge, no study examined incidence of pregnancy among women on ART follow-up in Ethiopia. In response, we conducted a study to explore the incidence and potential predictors of pregnancy. The objective of this study was to investigate the incidence of pregnancy among HIV/AIDS patient women under ART follow-up. A retrospective cohort study was conducted based on secondary data that reviews or visits medical chart of HIV/ADIS patient women aged 15-49 years under ART follow-up from April 2008 to February 2015. Out of 720 total patient women, a sample of size 328 was selected by using simple random sampling technique. Bayesian estimation were used for binary logistic regression model to identify the significant factors of incidence of pregnancy. The Gibbs sampler algorithm was implemented by WinBUGS software to solve approximate properties of the marginal posterior distributions for each parameter in Bayesian estimation. The results of this study revealed 21.3% of women got pregnancy during the follow-up. From Bayesian logistic regression analysis, significant predictors of incidence of pregnancy were: WHO clinical stage, marital status, contraception use, number of child alive before ART follow-up, CD4 cell count, time of Antiretroviral Therapy (ART) follow-up, educational level, spouse's HIV status, occupation and age (at p=0.05). In this study, when age of the women increased, the probability of becoming pregnant was decreased and advanced WHO clinical stage were associated with decreased incidence of pregnancy. Time on ART was a strong predictor of becoming pregnant: longer time on ART was associated with increased probability of becoming pregnant. Educational level of women was positively related with incidence of pregnancy that is, women who had college and above educational level was more likely to become pregnant. When CD4 count increased, incidence of pregnancy also increased and married women had more chance to become pregnant. The predictors identified in this study can be used to care for those HIV/AIDS patient women who want to have baby.
Abstract: HIV/AIDS is the most serious diseases human kind has ever faced and a public problem, particularly, for women of childbearing age. For HIV infected women, the prospects of getting pregnant and having an HIV negative baby could be significantly improved with the increasing of the availability of Antiretroviral Therapy (ART). Even though, ART treatme...
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