Background: Listeria monocytogenes, a member of the genus Listeria, is widely distributed in agricultural environments, such as soil, manure and water. The genus of Listeria bacteria is about 15-17 species. It is a pathogenic bacterium that can cause a rare but dangerous infection called listeriosis.

Objectives: Studying the rate of salads contaminated with Listeria bacteria. and Listeria monocytogenes according to International, Arabic and Iraqi specifications and finding the correlation between commitments of restaurants to standard health conditions with contamination with these bacteria

Methods: The study included

In this research, the effect of reinforcing epoxy resin composites with a filler derived from chopped agriculture waste from oil palm (OP). Epoxy/OP composites were formed by dispersing (1, 3, 5, and 10 wt%) OP filler using a high-speed mechanical stirrer utilizing a hand lay-up method. The effect of adding zinc oxide (ZnO) nanoparticles, with an average size of 10-30 nm, with different wt% (1,2,3, and 5wt%) to the epoxy/oil palm composite,  on the behavior of an epoxy/oil palm composite was studied with different ratios (1,2,3, and 5wt%) and an average size of  10-30 nm.  Fourier Transform Infrared (FTIR) spectrometry and mechanical properties (tensile, impact, hardness, and wear rate) were used to examine the composites. The FTIR

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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

Objective(s): To determine the impact of Chemotherapy upon the quality of life for patients with chronic myeloid
leukemia in Baghdad city.

Methodology: A descriptive study design was carried out The study was initiated from 30 January 2011 to October
2011.A purposive (non–probability) sample consisted of (130) patients with a chronic myeloid leukemia ,Who
attended to Baghdad Teaching Hospital and National Center for Research and Treatment of Hematology. The
sample criteria was the patients who were 18 years old and above, excluding the patients who suffered from
psychological problems and other chronic illnesses .A questionnaire was adopted and developed from European
Organization Research and treatment of Can