Nosocomial infection is acquired contamination of hospitals and health care units caused by multidrug resistant bacteria. Currently, bacterial resistance to antimicrobial medication represents a complicated public health problem. Recent studies on the antimicrobial activity of silver nanoparticles (AgNPs) attracted researchers worldwide to focus on the safe synthesis of AgNPs as antimicrobial agents against multidrug resistant bacteria. The antimicrobial efficacy of AgNPs on pathogenic bacteria isolated from clinical cases of acquired hospital infection was targeted in this project. Fifty specimens of stool were collected through private laboratories in Baghdad from patients who suffered diarrheal symptoms. Bacterial isolation, identific

A research include of synthesized five member ring, which has been synthesized by condensation of 2-(1-(4- hydroxyphenyl) ethylidene)hydrazine-1-carbothioamide[I] with α-chloro ethylacetate in sodium acetate (fused) to form ethyl 2-(4-(1-((4-oxo-2-thioxopyrrolidin-3-ylidene)hydrazono) ethyl)phenoxy)acetate [II]. After that reacted [II]with hydrazine hydrate to resulting compound [III]. Compound [III] was refluxed with 4-aminobenzoicacid in excess of phosphorus oxy chloride give compound [IV],the later compound [IV] interact with acetyl acetone or ethylacetoacetate give to pyrazole and pyrazoline derivatives[V],[VI]. While when reacted with different aromatic aldehydes and one ketone consistence Schiff base derivatives [VII]a-e . The FTIR a

New series of Schiff bases 2(a-j) and corresponding beta-lactam derivatives 3(a-j) were synthesized from cefalexin (1) as starting material. The compound (1) was reacted with different aldehydes and ketones to give Schiff bases derivatives 2(a-j). The synthesized Schiff bases were cyclized by chloroacetyl chloride in the presence of triethylamine to form beta-lactam derivatives 3(a-j). The compounds were characterized by deremination melting point, FT-IR and 1H NMR. The beta-lactam derivatives were screened in vitro antibacterial against some bacterial species

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

Introduction: Breast cancer is a significant global health concern, affecting millions of women worldwide. While advancements in diagnosis and treatment have improved survival rates, the impact of this disease extends beyond physical health. It also significantly influences a woman's lifestyle and overall well-being. Objectives: The current study intends to analyze the lifestyle of breast cancer patients who are receiving therapy or are being followed up at the Oncology Teaching Hospital in Medical City, Baghdad, Iraq. Method: The present study uses a descriptive design with an application of an evaluation approach. A convenience sample of 100 women with breast cancer was selected from the Teaching Oncology Hospital at the Medical C

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

On Saturday, May 13, 2023, a glorious day was engraved in the history of Al-Kindy College Medical Journal as it is the day of indexing the journal in the Scopus Database Journals. The journal has paced a strenuous journey to make that achievement.

Darcy-Weisbach (D-W) is a typical resistance equation in pressured flow; however, some academics and engineers prefer Hazen-Williams (H-W) for assessing water distribution networks. The main difference is that the (D-W) friction factor changes with the Reynolds number, while the (H-W) coefficient is a constant value for a certain material. This study uses WaterGEMS CONNECT Edition update 1 to find an empirical relation between the (H-W) and (H-W) equations for two 400 mm and 500 mm pipe systems. The hydraulic model was done, and two scenarios were applied by changing the (H-W) coefficient to show the difference in results of head loss. The results showed a strong relationship between both equations with correlation coefficients of 0.999,

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c