The current study was conducted to investigate Annona fruit pulp effects on the levels of various physiological biomarkers linked with insulin-dependent diabetes mellitus after disease induction in mice, as well as indications of oxidative stress and male hormones. The rats were separated into four groups, three of which were given Alloxan (90 mg/kg body weight) to induce diabetes, while the fourth served as a negative control. The first group of diabetic mice received no therapy, the second received metformin (600 mg/kg body weight) and the third received Annona fruit puree. The mice were sacrificed at the end of the experiment, to acquire blood and tissue samples from the liver, kidneys and spleen. The first untreated gro

Diabetes is a complex set of diseases require continuous medical care, to control blood sugar and prevent complications is .The aim of this research is to determine the effect of administration of   L carentin to diabetics on the   lipid profile. The research was conducted on sixty diabetic patients were selected from endocrinology and diabetes center / Al-Rusafa, within selected criteria. The patients divided into 3 groups (control group of healthy people and two groups of patients with diabetes who were on metformin and glibenclamide, one group took a L  carnitine in a dose of 1000 mg twice daily and a group dealing with a placebo for a period of 3 months continuously). The study found that patients who took Lc

Objectives: To study the spectrum and classification of ATP7B variants in Iraqi children with Wilson disease by direct gene sequencing with clinical correlation. Methods: Fifty-five unrelated children with a clinical diagnosis of Wilson disease (WD) were recruited. Deoxyribonucleic acid was extracted from peripheral blood samples, and variants in the ATP7B gene were identified using next-generation sequencing. Results: Seventy-six deleterious variants were detected in 97 out of 110 alleles of the ATP7B gene. Thirty (54.5%) patients had 2 disease-causing variants (15 homozygous and 15 compound heterozygous). Twelve (21.8%) patients had one disease-causing variant and one variant of uncertain significance (VUS) with potential pathogenicity. T

The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Many undergraduate learners at English departments who study English as a foreign language are unable to speak and use language correctly in their post -graduate careers.  This problem can be attributed to certain difficulties, which they faced throughout their education years that hinder their endeavors to learn. Therefore, this study aims to discover the main difficulties faced by EFL students in language learning and test the difficulty variable according to gender and college variables then find suitable solutions for enhancing learning.  A questionnaire with 15 items and 5 scales were used to help in discovering the difficulties. The questionnaire was distributed to the selected sample of study wh