This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

This study was conducted in the College of Agriculture fields /University of Baghdad, during Autumn 2013. This study was aimed to examine the mortality rate on the all black fly stages of Acaudalerodes rachipora Singh) by the biotic fungus Beuveria bassiana. The results of a preliminary survey showed that the samples of Ziziphus spaina christi were infested by blakflies in Agriculture collage during Autumn seasons of 2013 , the presence of species of black flies A. rachipora on the lower surface of the leaf, the study aimed to study and research the effects of fungus B. bassiana on black fly A. rachipora. After six days of treatment results showed the continued superiority 106 spore / ml trends in the western, southern and

BACKGROUND: Polycystic ovary syndrome(PCOS) is one of the most common endocrine disorder affecting women in reproductive age. No single etiologic factor fully accounts for the spectrum of abnormalities in the polycystic ovary syndrome. Different changes in hormonal, metabolism and the inflammatory markers as squealy of PCOS with adverse effect on the women life. OBJECTIVE: To study the relationship between polycystic ovary syndrome and levels of C-reactive protein, human interleukin and hormonal and metabolic alteration in women with PCOS PATIENTS AND METHODS: Thirty women with Polycystic Ovary syndrome (PCOS) and other thirty women without PCOS were included. Venous blood samples were taken in early follicular phase of menstrual cycle [day

Visceral leishmaniasis is a neglected tropical disease on the rise in different regions of Iraq, especially in areas with poor hygiene and among refugee populations. The effectiveness of existing chemotherapy for leishmaniasis is constrained by its high toxicity, cost, and the development of drug resistance. The current research examined various concentrations (ranging from 125 to 1000 μM) of lupeol to evaluate its ability to boost the generation of nitric oxide, which has anti-leishmanial properties, in an ex-vivo macrophage model. Griess assay was used to detect the nitric oxide (NO) production in Leishmania donovani infected U937 cell-line macrophages along 24 and 48 hours post treated. The nitric oxide concentration was signifi

Objective(s): Ramadan is the Holy month of the Muslims, where they are required to abstain from food and drinks
from dawn till the beginning of night. This study was conducted in Ramadan to investigate the effect of fasting on
hematological incidences, lipid profile, renal and liver function tests among healthy adult males.
Methodology: The present study was carried out in Ramadan – 1431 of Higira (August-September 2010). The study
sample was 56 healthy adult males. Five samples of blood were taken at five intervals (Before, at day 1, 15, 28 and
after Ramadan). Estimation was done for hematological markers, (hemoglobin, white blood cells count, platelet
count); renal function tests (blood urea, serum uric acid, serum

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp