The current research seeks to identify mono-multi Vision and its relation to the psychological rebellion and personality traits of university students. To achieve this aim, the researcher has followed all the procedures of the descriptive correlational approach, as it is the closest approach to the objectives of the current research. The researcher has determined his research community for Baghdad University students for the academic year 2019-2020. As for the research sample, it was chosen by the random stratified method with a sample of (500) male and female students. In order to collect data from the research sample, the researcher adopted a mono-multi-dimensional scale

(Othman, 2007), the researcher designed a psychological r

Over the past few decades, the health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to the emergence of drug-resistant bacteria. The clinical use of a combination of antibiotic therapy for Pseudomonas aeruginosa infections is probably more effective than monotherapy. The present study aims to estimate the antibacterial and antibiofilm activity of Conocarpus erectus leaves extracts against multi-drug resistant P. aeruginosa isolated from different hospitals in Baghdad city. One hundred fifty different clinical specimens were collected from patients from September 2021 to January 2022. All samples were

Multi-drug-resistant uropathogenic Escherichia coli (UPEC) is considered a significant challenge due to its ability to resist antibiotics and form biofilms. UPEC biofilm formers are well protected and largely inaccessible to antibiotics, which leads to persistent infections and evasion of the host immune system. Understanding how ciprofloxacin and trimethoprim/sulfamethoxazole affect biofilm formation is essential for improving treatment strategies for urinary tract infections (UTIs). A total of 76 UPEC isolates were obtained from Iraqi patients and identified using morphological and biochemical characteristics, as well as the Vitek®-2 Compact system. Minimum inhibitory concentrations (MICs) were determined using the Vitek®-2 system, whic

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t