Abstract Aim: Autism is a neurodevelopmental disorder which affects communication and social interaction of children. It is a heterogeneous disease with various clinical presentations. Some genes are involved in its pathogenesis. It has been suggested that environmental exposure to lead can increase the risk of autism. The aim of our study was to compare blood lead levels among autistic and non-autistic children. Material and Method: This retrospective study included 107 children (60 with autism and 47 without autism) referred from the different Iraqi provinces, in the years 2015, 2016 and 2017, to the poisoning consultation center in Baghdad. Data collection including age, gender, residence, referral source, family history and blood lead l

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

his study aimed to evaluate the effects of different doses of melatonin on liver function in adult rats. Eighteen Wistar adult albino rats (Rattus norvegicus), approximately 13–16 weeks old and weighing 230 ± 10 g, were randomly divided into three groups (n=6 per group) and treated orally for 30 days as follows: Group A1 received 10 mg/kg body weight (B.W) of melatonin; Group A2 received 20 mg/kg B.W of melatonin; and the control group (Group A) received distilled water. At the end of the treatment period, blood samples were collected via cardiac puncture, and serum was separated for biochemical analysis. Parameters assessed included oxidative stress markers (malondialdehyde (MDA), reduced glutathione (GSH)) and liver enzymes (aspa

The research includes a clinical study of Preptin with other parameters. The normal value of preptin in hypothyroidism (2638.4±280.0) in female while (2960.4±256.6) in male, in hyperthyroidism (589.0±90.1) in male, while in female (993.2±103.9), diabetes (2465.6±282.4) in female, in male (2085.5±282.8), in diabetes & hypothyroidism (3314.3±177.3) in male,(3179.4±265.7) in female, but control group in female (427.8±60.4), in male (384.7±62.4) at age (20-45) years they were divided into five groups: group one (G1) consisted of 30 hypothyroidism. The two group (G2) consisted of 30 patients with hyperthyroidism. And three group (G3) consisted of 30 healthy group, four group (G4) consisted of 30 patient with diabetes, and five group (G

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class