The objective of the present study was to investigate the effect of body mass index (BMI) on semen parameters, level of sex hormone and sperm DNA integrity. Semen samples were collected from (85) infertile men and (40) healthy fertile men with range of age (38.191 ± 0.84) years during their attendance at High Institute of Infertility Diagnosis and ART, Al-Nahrain University from March to June 2016. Semen samples were obtained by masturbation after 72 hours of abstinence. Seminal fluid analyses included semen volume, sperm concentration, percent sperm motility, percent sperm morphology, and sperm chromatin integrity DNA fragmentation index (DFI]). Serum samples were collected from each subject for determination the level of Follicle Stimulating Hormone (FSH), Luteinizing Hormone (LH), Prolactin (PRL), and Testosterone by ELISA method. The results revealed a highly significant (P≤ 0.01) increase in BMI and immotile sperm (%), and significant(P≤ 0.05) increase in semen liquefaction time, non-progressive motility (%), round cells counts and sperm DNA fragmentation in infertile men as compared to control group, while there was a highly significant (P≤ 0.01) decrease in progressive motility (%), and a significant (P< 0.05) decrease in the sperm concentration, sperm motility (%) and normal sperm morphology (%). The results showed statistically significant (P< 0.05) positive correlations between body mass index and sperm motility, progressive motility, non-progressive motility, immotile sperm, normal sperm morphology and sperm DNA fragmentation. No significant correlations were observed between body mass index and semen liquefaction time, semen PH, sperm concentration, round cells counts and age. In respect with level of serum hormones a significant (P< 0.05) decrease in level of FSH ,LH and testosterone was found ,while the level of prolactin showed a significant (P< 0.05) increase in infertile men when compared with control group. Significant (P< 0.05) negative correlation was observed between body mass index and serum level of prolactin and testosterone, while non-significant correlations were observed between body mass index and serum level of FSH and LH. In conclusion, this study has shown that body mass index has major effect on semen characteristics and sex hormones.
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In this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
In this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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Atenolol was used with povidone iodine to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between atenolol and povidone iodine in an aqueous medium. Optimum parameters was studied to increase the sensitivity development of method. Calibration graph was linear in the range of 2-19 mmol/L for cell A and 5-19 mmol/L for cell B. Limit of detection 146.4848 ng/55 µL and 2.6600 µg/200 µL respectively to cell A and cell B. Correlation coefficient (r) 0.9957 for cell A and 0.9974 for cell. Relative standard deviation (RSD %) was lower than 1%, (n=8) for the determination of
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Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a
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