Abstract Background: Multidrug-resistant bacteria (MDR) often contaminate hospital environment and cause serious illnesses. Quorum Sensing (QS) regulates a variety of downstream cellular processes, including antibiotics resistance mechanisms and biofilm formation, and causes harm to the host. This study investigates antibacterial susceptibility and biofilm formation of pathogenic bacteria in hospital environment. Methods: Hundred bacterial isolates were collected from various environments in the Medical City hospital. The antimicrobial susceptibility technique was evaluated through disk diffusion method. Next, biofilms formation was detected by the microliter plate assay. Finally, PCR was used to analyze the frequency of QS system gene

Social factors may affect the available sources of toxic substances and causes of poisoning, and these factors may change over time. Additionally, understanding the characteristics of poisoning cases is important for treating such patients. Therefore, the present study investigated the characteristics of poisoning cases in Baghdad Poisoning Consultation Center (PCC) and Forensic Medicine Institute (FMI). Data on all poisoning cases reported in PCC and FMI during 2013 were retrospectively obtained from medical records. Total of 1131 reports of poisoning cases (1082 from PCC and 49 from FMI) were analyzed according to age, sex, geographical distribution and causes of poisoning according to the type and class of poisoning agent. The results

To enhance the structural performance of concrete-filled steel tube (CFST) columns, various strengthening techniques have been proposed, including the use of internal steel stiffeners, external wrapping with carbon fiber-reinforced polymer (CFRP) sheets, and embedded steel elements. However, the behavior of concrete-filled stainless-steel tube (CFSST) columns remains insufficiently explored. This study numerically investigates the axial performance of square CFSST columns internally strengthened with embedded I-section steel profiles under biaxial eccentric loading. Finite element (FE) simulations were conducted using ABAQUS v. 6.2, and the developed models were validated against experimental results from the literature. A comprehen

An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols i

This paper deals with the subject of demarcating as appropriate scientific techniques to rationalize consumption and to control segments of the society for the technical conduct of its handling of the product depending on the mix of elements (product and the volume of demand, Price, promotion and distribution), but inverse manner designed to adjust the working condition of balance between supply and demand and to ensure that rates continue in the marketing process properly, and therefore the research aims to shed light on some of the practices that reflect the Demarketing techniques, As well as the statement of the reality of attitudes towards the practice of those techniques through a sample survey of officials in Baghdad company for so

Background: Debonding orthodontic brackets and removal of residual bonding material from the enamel surface include critical steps that may cause enamel damage. The aim of the present study was to evaluate and compare the site of bond failure and enamel surface damage after debonding of three types of esthetic brackets (composite, ceramic, sapphire) bonded with light cure composite and resin-modified glass ionomer adhesive. Materials and methods: Seventy two maxillary premolars teeth were divided into three groups each group consisted of 24 teeth according to the type of brackets. Each group was subdivided into two subgroups (12 teeth for each) according to the bonding material that was used. After 7 days of bonding procedure, the brackets

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC