It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s

Purpose: This research is to identify the most important challenges for the local investment commissions and to develop solutions and proposals to encourage local and foreign investment in local governments in Iraq (the Iraqi provinces are irregular in the region).   Theoretical Framework: This research suggests a conceptual framework for the local investment commissions in order to solve their problems, the most important of which was to identify the most critical challenges which are facing the Baghdad Investment Commission BIC and how to overcome them.   Design/The methodology approach: Research involved a mixed-methods approach through two stages. During the first stage, the researcher gathered quantitative data from all inves

Mouth ulcers are common oral lesions. Although several topical treatments are commercially available, their limited residence time requires frequent application, which remains a significant drawback. This study aimed to develop a novel mucoadhesive, thermosensitive, in situ gel-forming spray for local delivery of betamethasone sodium phosphate, thereby reducing systemic exposure. Formulations were optimized using the design of experiment approach to investigate the effects of thermosensitive polymers (Poloxamer 407 and Poloxamer 188), mucoadhesive polymer (hyaluronic acid), and drug incorporation on gelation temperature and time. The optimized formulation gelled at 33.3 ± 0.7 °C within 14.79 ± 1.87 s and showed a spray angle of 4

Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

The aim of this research was to indicate the opinion of the Iraqi consumer about the quality and safety of local food products, the questionnaire was included 19 questions for product quality, price, distribution and promotion as a tool to survey the opinions of 128 consumers in Baghdad, the data was analyzed by using percentage, weighted mean, and weight percent, the results obtained showed that the Iraqi consumer prefer local food products for their high quality and appropriate price, however they need attention to packaging, promotion and distribution.

This study aimed to evaluate the occurrence of microbial contamination in food keeping freezers in some local markets in Baghdad city/ Iraq, as well as the contamination of the hands of workers in markets, and the possibility of contamination caused by the transport of food. 30 samples of snow ice found in food keeping freezers in local markets was randomly collected, and 30 swabs from workers hands were taken from the same markets at the same time. Microbiological examination of ice samples was conducted as well as the hands of workers’swabs, and the bacteria were isolated and diagnosed through microbiological and biochemical tests followed. Microbial test results showed some isolates of bacteria in ice samples obtained from food keep

   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

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion