Nowadays nanoparticles have widespread application in various industriesbecause of their special and unique features, there are many studies in sideeffects of nanomaterial. This study done by 40 white female mice withevery other day intraperitoneally injection of low and high doses of both ofZnO kg of body weight) and FeOnanoparticles (5 and 40 mg/kg). After a 15 days period, the mice weresacrificed and blood samples were collected for hormone analysis, andtissue samples for morphometric studies.Statistical Analysis shows significant differences in LH, Estrogen,Progesterone hormone levels between groups, while there are insignificantdifferences in Follicle stimulating hormone (FSH) level between thegroups compared with its level in the control group.The results also show that the highest level of LH reach 7.2 mIU/ml in thegroups treated with low dose of zinc oxide, the highest level of FSH reach4.58 mIU/ml in the groups treated with low dose of zinc oxide, the highestlevel of Estrogen hormone reach 69.5 ng/ml in the groups treated with lowof dose zinc oxide and the highest level of Progesterone reach 1.9 ng/ml inthe groups treated with high dose iron oxide. We conclude from the resultsthat the low doses of ZnO has benefits in increasing fertility through highlevel of reproductive hormones, while the high levels of nanoparticlesreduce fertility and there is a relation between FeO nanoparticles andprogesterone levels which may need more future studies.Morphometric study of the ovary show increase in Follicular stagesnumber range in the group treated with Low dose ZnO in compare with itsrange in the control groups. The lower range was belong to the grouptreated with the high dose of FeO. No significant differences has beenfound in the diameter mean of the different follicular phases between thegroup treated with low dose of ZnO NPs in compared with the controlgroup. High dose of ZnO NPs cause significant increase in the diametermean of Primordial follicles in compared with the control group. Low andhigh dose FeO NPs treated groups show significant reduction in thediameter mean of the different follicular phases in compared with thecontrol group.
We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
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,
... Show More