P. aeruginosa is one of the complex targets for antimicrobial chemotherapy. Also, it is intrinsically resistant to several antibiotics. It produces β-lactamases enzymes that are responsible for the widespread β-lactam antimicrobial resistance. There are three major groups of β-lactamase enzymes, MBLs and ESBLs forming Pseudomonas is a major issue for the treatment of burns victims. Methods: A total of 28 clinical isolates related to P. aeruginosa have been obtained from the burns specimens from patients attending to AL-Imam hospital/Baghdad-Iraq, through the period from October 2015 to March 2016. Also, all isolates have been recognized as P. aeruginosa via utilizing bacteriological assay and confirmed by Vitek 2. In addition, the suscep

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

An environmentally begnin second derivative spectrometric approach was developed for the estimation of the dissociation constants pKa(s) of metformin, a common anti-diabetic drug.  The ultraviolet spectra of the aqueous solution of metformin were measured at different acidities, then the second derivative of each spectrum was graphed. The overlaid second derivative graphs exhibited two isobestic points at 225.5 nm and 244 nm pointing out to the presence of two dissociation constants for metformin pKa1 and pKa2, respectively. The method was validated by evaluating the reproducibility of the acquired results by comparing the estimated values of the dissociation constants of two different strategies that show excellent matching. As we

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

Background: Pervasive Developmental Disorder (PDD) is a term refers to the overarching group of conditions to which autism spectrum disorder (ASD) belongs .

Objective: This study was designed to determine the existing behavior of children with autism in dental sitting, the behavior improvements in recall dental visits and evaluate the improvement in oral hygiene with using specific visual pedagogy chart.

Type of the study: Cross-sectional study.

Methods: Forty children of both genders, ages ranged from 4 – 6 years having primary teeth only were selected whose medical history included a diagnosis

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of