Urinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

The tests that measure special strength defined by speed contributes a great deal in evaluating the players' weaknesses and strengths so as to aid coaches judge their players according to scientific and objective measurements. The problem of the study lies in answering the following question : is there a test that measures legs' vertical strength defined by speed especially for youth basketball players? The aim of the research was to construct and standardize a test for measuring legs' vertical strength defined by speed in youth basketball. The subjects of the study were 74 youth basketball players from Baghdad. The researchers concluded that the test measures leg's vertical strength defined by speed for youth basketball players as well as

Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018

This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall