Objective(s): The study aims at evaluating pregnancy-related health behaviors for pregnant women, and to identify the association between pregnancy-related health behaviors and their demographic characteristics of pregnant woman’s age, education, employment, residential area and monthly income.
Methodology: A descriptive study is carried out for the period from December 14th, 2020 to June 20th, 2021. This study was conducted through a non-probability (convenience) sample of 150 pregnant women attending, Abo Ghareeb primary health care sector in Abo Ghareeb spend. The sample has been collected by using the instrument to gather data and accomplish the study's objectives. A questionnaire is composed of (29) items and it is divided into

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

This research is divided into a process of classifying and filtering most of the studies that dealt with sustainable professional development and dividing them into several sections to determine the categories for which sustainable professional development is measured, which categories did not address it, the extent to which the samples deal with and their number of the target variable, as well as the variables that suit sustainable professional development and the variables that did not Study it yet. And also the quality of studies in terms of the methodology used so that there is a reference for every researcher who intends to study sustainable professional development with studies, their characteristics, categories, tools and methodology

KE Sharquie, HR Al-Hamamy, AA Noaimi, AF Tahir, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 2

ABSTRACT Background: One of the challenges to use chlorhexidine is its effect on the amount of microleakage after restoration; however, use of the materials with antibacterial properties after tooth preparation and before restoration has been widespread. The objective of this, in-vitro, study was to evaluate the influence of consepsis (chlorhexidine gloconate disinfectant) application on microleakage in class II cavities restored with light cured composite using universal adhesive system; etch and rinse technique –self etch technique. Materials and Methods: Forty class II cavities were prepared on mesial and distal surfaces of 20 non-carious mandibular third molars. The cavities were divided into four groups; (n =10 for each group).

In this search, a new pyrophosphate technique was proved. The technique was employed to single- nucleotide polymorphisms (SNPs), which diagnosis using a one-base extension reaction. Three Mycobacterium tuberculosis genes were chosen (Rpob, InhA, KatG) genes. Fifty-four specimens were used in this study fifty-three proved as drug-resistant specimens by The Iraqi Institute of Chest and Respiratory Diseases in Baghdad.; also one specimen was used as a negative control. The steps of this technique were by used a specific primer within each aliquot that has a short 3-OH end of the base of the target gene that was hybridized to the single-stranded DNA template. Then, the Taq polymerase enzyme and one of either α-thio-dATP, dTTP, dGTP, or dCTP

Background: A worldwide health epidemic, type 2 diabetes mellitus was significantly influenced by chronic inflammation, which led to increased insulin resistance (IR). The most widely practiced form of therapy used to control musculoskeletal pain in people with diabetes is non-steroidal anti-inflammatory drugs (NSAIDs), which provide their action by inhibiting cyclooxygenase enzyme (COX). COX1, COX2, and COX3 are distinct isoforms of the cyclooxygenase enzyme. The potential anti-inflammatory benefits of cyclooxygenase-2 (COX-2) inhibitors, both selective and non-selective, have been investigated concerning the management of type 2 diabetes patients. Objective: the purpose of this research is to explore the impact of highly selective