Zinc is one of the essential trace elements, it plays a key role in many biochemical and functional processes. It is less harmful than many other minerals, in the case of exposure to high doses of zinc, poisoning occurs, and this poisoning may mostly result from the accidental ingestion of household products containing zinc or nutritional supplements, this study was conducted to find out the effects of zinc on the concentration of amino acid. A total of 30 adult white mouse males were taken and divided into three groups; the first group (control) of 10 mice taken with distilled water for 30 days, the second group includes 10 mice that were dose with Zn drug concentration of 50 mg/kg/day for 30 days, the third group includes 10 mice that wer

Within this work, to promote the efficiency of organic-based solar cells, a series of novel A-π-D type small molecules were scrutinised. The acceptors which we designed had a moiety of N, N-dimethylaniline as the donor and catechol moiety as the acceptor linked through various conjugated π-linkers. We performed DFT (B3LYP) as well as TD-DFT (CAM-B3LYP) computations using 6-31G (d,p) for scrutinising the impact of various π-linkers upon optoelectronic characteristics, stability, and rate of charge transport. In comparison with the reference molecule, various π-linkers led to a smaller HOMO–LUMO energy gap. Compared to the reference molecule, there was a considerable red shift in the molecules under study (A1–A4). Therefore, based on

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris

The current research that entitled (t Technical Experimentation incontemporary plastic arts) deals with study in used techniques and the material's functioning and its variations in artwork.It present the following questions :- 1-Does technical experimentation for mate an important phenomenon in contemporary art.2-Does technical experimentation construct an ability in creating new constructive and formative achievement in plastic art ?.The research includes three chapters . the first one deals with the problem of the research and its limits with the specification of terms . the second chapter present the technical Experimentation in contemporary plastic art with shapes display . the third chapter involves conclusions with discussions . t

تتمثل مشكلة الدراسة في الصعوبات التي يواجهها طلاب اللغة الإنجليزية كلغة أجنبية في تعلم وإتقان المتلازمات اللفظية. تهدف هذا الدراسة تهدف إلى تحديد أثر استخدام تقنية المسرد الاملائي على معرفة المتلازمات اللفظية لدى الطلاب. ولتحقيق أهداف هذا البحث والتحقق من فرضياته تم اختيار عينة عشوائية مكونة من (60) طالبة من كلية اللغة الإنجليزية للسنة الثانية باستخدام كتاب الفهم القرائي المقرر للمستوى الثاني في قسم الل

The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit

?Natural Occurrence of aflatoxin Bi and B2 was investigated monthly in paddy rice stored for duration of six months. Aflatoxin B| was detected at the beginning of storage. The concentration of aflatoxin Bi in paddy and polished rice was found to be (0.3 and ()) ppb respectively while aflatoxin B2 W'as not detected in both paddy and polished rice afler six months of storage, concentration of aflatoxin Bi ‘ ’ ' reached 3 ppb in paddy rice and 0.9 ppb in polished rice, while the study proved that the concentration of aflatoxin in paddy rice was higher than polished rice as a result of processing which reduce the toxin

This research aims to examine the effectiveness of a teaching strategy based on the cognitive model of Daniel in the development of achievement and the motivation of learning the school mathematics among the third intermediate grade students in the light of their study of "Systems of Linear Equations”. The research was conducted in the first semester (1439/1440AH), at Saeed Ibn Almosaieb Intermediate School, in Arar, Saudi Arabia. A quasi-experimental design has been used. In addition, a (pre & post) achievement test (20 Questions) and a (pre & post) scale of learning motivation to the school mathematics (25 Items) have been applied on two groups: a control group (31Students), and an experimental group (29 Students). The resear

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct