Objective(s): To evaluate and compare between Health Promotion Program for the Prevention of Epidemics at Primary Health Care Centers in Baghdad City.

Methodology: A descriptive study, using the evaluation and comparative approaches, is conducted to evaluate health promotion program for the prevention of epidemics at primary health care centers in baghdad city from October 15^th  2019 through March 1^st 2020. A purposive, non-probability, sample of (42) health promotion unit officers were recruited from the same number of primary health care centers which were divided into (14) main, (14) sub and (14) family medicine primary health care centers i

In this study, the specimens of land snails Polygyra cereolus (Megerle v on Mühlfeld t , 181 8
(Gastropoda, Stylommatophora, are collected between March and April 2021
from gardens and nurseries in Baghdad province, this species was recorded as a new record to
Iraq molluscan fauna. Description of the most important characteristics, measurements of the
shell are presented with digital p photographs, subsequently, this study represents the first record
of the Polygyridae in Iraq.

This research deals with the design and simulation of a solar power system consisting of a KC200GT solar panel, a closed loop boost converter and a three phase inverter by using Matlab / Simulink. The mathematical equations of the solar panel design are presented. The electrical characteristics of the panel are tested at the values ​​of 1000  for light radiation and 25 °C for temperature environment. The Proportional Integral (PI) controller is connected   as feedback with the Boost converter to obtain a stable output voltage by reducing the oscillations in the voltage to charge a battery connected to the output of the converter. Two methods (Particle Swarm Optimization (PSO) and Zeigler- Nichols) are used for tuning

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

Backgrround:: Cholera is gastroenteritis caused by enterotoxin producing Vibrio cholera. Cholera is predominantly a waterborne disease especially in countries with inadequate sanitation. Several rapid methods have been developed and used to detect V. cholerae serotypes directly from stools.
Objjecttiives:: to evaluate a rapid and accurate method for the diagnosis of cholera caused by V. cholerae O1 and O139 serogroups d to find the incidence of sporadic cases of cholera in Baghdad.
Metthods:: Sixty four stool samples were collected from four hospitals in Baghdad. The age of patients ranging from two months to 12 years, 26 were females and 38 males. Immunochromatographic visual test for qualitative detection of O1 and /or O139 serog

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

1, 3, 4-oxadiazole-5-thion ring (2) successfully formed at position six of 2-methylphenol and five of their thioalkyl (3a-e). Furthermore 6-(5-(Aryl)-1, 3, 4-oxadiazol-2-yl)-2-methylphenol (5a-i) were formed at position six by two method. The first method was from cyclization their correspondinghydrazones (4a-e) of 2-hydroxy-3-methylbenzohydrazide (1) using bromine in glacial acetic acid. The second method was from cyclization the hydrazide with aryl carboxylic acid in the presence of phosphorusoxy chloride. The newly synthesized compounds were characterized from their IR, NMR and mass spectra. The antioxidant properties of these compounds were screened by 2, 2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) a