This study was designed to compare the effect of two types of viral hepatitis A and E (HAV
and HEV) on liver functions in Iraqi individuals by the measurement of biochemical changes
associated with hepatitis.
The study performed on 58 HEV and 66 HAV infected patients compared with 28 healthy
subjects. The measured biochemical tests include total serum bilirubin, serum transminases (ALT
and AST) alkaline phosphatase (ALP) and gamma glutamyl transferase (GGT).
The study showed that adolescent and young adults (17-29) years, were mostly affected by
HEV while children (5-12) years were frequently affected by HAV. The severity of liver damage in
HEV patients was higher than HAV patients as a result of high serum transa

This study is conducted to identify the microbial content of some types of infant milk formula available in the local markets of the city of Baghdad and their conformity microbial limits sited by the Iraqi standard. Seventy samples were collected from trademarks of imported infant milk formula included of five samples of infant milk formula No (1) and five samples of follow-up formula No (2). These samples were collected randomly from shops in the local markets of Baghdad city on both sides of Karkh and Rusafa included the following kinds: Dialac 1, Dialac 2 ,Celia 1, Celia 2 ,Biomil 1, Biomil 2 , Nactalia 1, Nactalia 2, Novalac 1 , Novalac 2 , Similac 1 , imilac 2 , Guigos 1, Guigos 2. Some microbial tests were done which in

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

CIGS nanoink has synthesized from molecular precursors of CuCl, InCl3, GaCl3 and Se metal heat up 240 °C for a half hour in N2-atmosphere to form CIGS nanoink, and then deposited onto substrates of soda-lime glass (SLG). This work focused on CIGS nanocrystals, indicates their synthesis and applications in photovoltaic devices (PVs) as an active light absorber layers. in this work, using spin-coating to deposit CIGS layers (75 mg/ml and 500 nm thickness), without selenization at high temperatures, were obtained up to 1.398 % power conversion efficiency (PCE) at AM 1.5 solar illumination. Structural formations of CIGS chalcopyrite structure were studied by using x ray diffraction XRD. The morphology and composition of CIGS were studied using

Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med