Foodborne diseases are a major risk for human health. Millions of people become sick as a result of eating contaminated food with microorganisms that cause diseases. S.  aureus is considered as one of the most important pathogenic bacteria, having the ability to  activate certain genes that encode for heat stable enterotoxins and cause Staphylococcal food poisoning. Thus, this study aimed to determine the prevalence of multi resistant Staphylococcus aureus that produce enterotoxins in different sources of food . Forty nine isolates were identified as S.aureus, according to morphological and biochemical tests. They were isolated from 387 different food samples from several randomly covered restaurants

In this work, polyvinylpyrrolidone (PVP), Multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybrid with Graphene (Gr) by casting method. The morphological and optical properties were investigated. Fourier Transformer-Infrared (FT-IR) indicates the presence of primary distinctive peaks belonging to vibration groups that describe the prepared samples. Scanning Electron Microscopy (SEM) images showed a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The results of the optical study show decrease in the energy gap with increasing MWCNT and graphene concentration. The absorption coefficient spectra indicate the presence of two absorption peaks at 282 and 287 nm attributed to the π-π* electronic tr

In this work, the total linear attenuation coefficients µ(cm
-1
) were calculated and studied
for particulate reinforced polymer-based composites. Unsaturated polyester (UP) resin was
used as a matrix filled with different concentrations of Al, Fe, and Pb metal powders as
reinforcements. The effect of the metal powders addition at different weight percentages in
the range of (10,20,30,40,50)wt % and gamma energy on attenuation coefficients was studied.
The results show, as the metallic particulates content increase, the attenuation coefficients will
increase too, while it, were exhibited a decrease in their values when the gamma energy
increase.The total linear attenuation coefficients of gamma ray fo

The water vapor is one of the constituent elements of the rain and the superiority
of its importance in the study of climate because it is the basis on which depends all
the different aspects of condensation. The purpose of research is to analyze the time
series of the Baghdad station andan analyze these series to see whether there is a
relationship between these two variables. Obtained the data used in this research
from the National Center for Environmental Prediction for the period from 1948 to
2011. The use of statistical criteria included linear regression and Mann Kandal test
to find the link. The results of time series monthly presence decrease in rainfall and
all months except October, either the results o

The effect of number of pulses of pulsed laser on materials is studied analytically, different pulses has been used with the same delay time.  The depth of possible damage to the surface of copper and titanium as well as depth of the crater to both materials were considered in this study.  The study revealed that linear model is only possible when estimating depth of possible damage for copper material, this means that the depth of possible damage increases with the increment of number of laser pulses .As for titanium material, it is found  the relationship is nonlinear.  The depth of possible damage of titanium and copper is not the same, and copper seems to be more predictable than titanium.  
 

Corrosion inhibiting admixtures are unique among other methods to protect reinforced concrete from corrosion damage. In this study, the effect of furfural on the fresh and hardened properties of concrete mixes of 35 and 45 MPa compressive strengths as well as the corrosion inhibition of furfural was evaluated. Furfural was added at different dosages (1, 2 and 3% by weight of cement) with and without superplasticizer (HRWR). Different electrochemical measurements were performed (Half-cell potential, Tafel plot and linear polarization resistance). Electrochemical measurements confirmed that furfural dramatically reduces the rate of corrosion; the inhibition efficiencies were 62.7 and 63.8 % due to 3% furfural addition to 35 and 45MPa-concr

Seismic inversion technique is applied to 3D seismic data to predict porosity property for carbonate Yamama Formation (Early Cretaceous) in an area located in southern Iraq. A workflow is designed to guide the manual procedure of inversion process. The inversion use a Model Based Inversion technique to convert 3D seismic data into 3D acoustic impedance depending on low frequency model and well data is the first step in the inversion with statistical control for each inversion stage. Then, training the 3D acoustic impedance volume, seismic data and porosity wells data with multi attribute transforms to find the best statistical attribute that is suitable to invert the point direct measurement of porosity from well to 3D porosity distribut

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

     The open hole well log data (Resistivity, Sonic, and Gamma Ray) of well X in Euphrates subzone within the Mesopotamian basin are applied to detect the total organic carbon (TOC) of Zubair Formation in the south part of Iraq. The mathematical interpretation of the logs parameters helped in detecting the TOC and source rock productivity. As well, the quantitative interpretation of the logs data leads to assigning to the organic content and source rock intervals identification. The reactions of logs in relation to the increasing of TOC can be detected through logs parameters. By this way, the TOC can be predicted with an increase in gamma-ray, sonic, neutron, and resistivity, as well as a decrease in the density log