The rapid increase in the number of older people with Alzheimer’s disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems because of a large number of people affected. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available, and to plan for the future. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage caused to the brain due to AD leads t

This study was conducted to examine the anatomical aspects of Carissa macrocarpa, of stem, leaf and leaf venation. The results obtaind showed that the tissue of the studied parts have important anatomical characteristics in terms of the shape of the cross-sectional of stem and vertical-sectional of leaves. The stem section appeared in circular and the midrib was crescent shape and the stomata appeared on the upper surface of the leaf only, Tetracytic in type. Druses crystals and Aleurone granules appeared on both surfaces of leaves. The venation type was Brochidodromous in which the secondary veins do not end at the edge of the leaf, and each secondary race is connected with the higher rac

A sensitive spectrofluorimetric method for the determination of glibenclamide in its tablet formulations has been proposed. The method is based on the dissolving of glibenclamide in absolute ethanol and measuring the native fluorescence at 354 nm after excitation at 302 nm. Beers law is obeyed in the concentration of 1.4 to 10 µg.ml-1 of glibenclamide with a limit of detection (LD) of 0.067 µg.ml-1 and a standard deviation of 0.614. The range percent recoveries (N=3) is 94 - 103.

A vital instrument to foster the long-term goal of high-quality education has developed in the form of digital technologies. The educational system has been found to be significantly impacted by these technologies. The recent COVID- Pandemic has strengthened the legitimacy of using digital tools in education. The entire educational system has undergone a paradigm shift as a result of these digital technologies. Along with sharing knowledge, it also serves as a mentor, an assessor, and a co-creator of information. Students' lives have been simpler as a result of educational technology advancements. Nowadays, students prepare presentations and projects utilizing a variety of software and tools rather than pen and paper. The weig

Abstract Background Infections with helminths are associated with deficient sanitary facilities, unsafe human waste disposal, inadequate and lack of safe drinking water, and low socioeconomic status. Objective To determine the prevalence of some gastrointestinal helminths among Iraqi people, and association of infections with age, sex, and region in Iraq. Method This study is retrospective, including reported cases of infections using an available surveillance database from January 2013 to December 2013 of all provinces of Iraq by the Ministry of Health. Result The overall prevalence of gastrointestinal helminthiasis was 1.39%. Enterobius vermicularis found to be the predominant helminth parasite. No significant (P < 0.05) rel

Abstract

               Documentary credits are considered successful means to reduce imports, especially unnecessary imports that lead to the outflow of foreign currency from the country. However, due to the backwardness of the banking methods, the reintroduction of documentary credits after 2003 did not effectively contribute to reducing import rates. This has had a negative impact on the Iraqi economy and made it vulnerable to external markets. Documentary credits are also considered the best way to ensure payment in international trade, providing independent credit support and sufficient security for exporters and importers against commerci

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c