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 two parts. The first part is socio-demographic data of pregnant women which consists of (five) items including age, level of education, occupation, residential area, and monthly income and the second part is items of health behaviors during pregnancy which consists of (29) questions and question number twenty-nine consist of (17) items of changed behaviors. The content validity of the instrument has been determined by panel of experts and the internal consistency reliability is determined by the computation of Cronbach alpha correlation coefficient. The data are collected throughout the use of the questionnaire and the interview technique and analyzed by applying descriptive and inferential statistical data analysis approaches.
Results: Results show that (30%) of the study subjects are (20-24) years old, (88%) housewives, (28.7%) are primary school graduated, 60.7% are rural residents, and (50%) of their monthly income is (300, 000-600,000) ID. The Study results show that there is a high-significant association between the study sample's healthy behaviors and their education, monthly income, and residential area at a p-value less than (0.01). While other demographic characteristics of age and occupation has non-significant association with a p-value of higher than (0.05).
Recommendations: The study recommends that the Iraqi Ministry of Health should print and distribute booklets containing all the health behaviors of pregnant women
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The Manganese doped zinc sulfide nanoparticles of the cubic zinc blende structure with the average crystallite size of about 3.56 nm were synthesized using a coprecipitation method using Thioglycolic Acid as an external capping agent for surface modification. The ZnS:Mn2+ nanoparticles of diameter 3.56 nm were manufactured through using inexpensive precursors in an efficient and eco-friendly way. X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy are used to examine the structure, morphology and chemical composition of the nanoparticles. The antimicrobial activity of (ZnS:Mn2+) nanocrystals was investigated by measuring the diameter of inhibition zone using well diffusion mechanism
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Background: Implant stability is a mandatory factor for dental implant (DI) osseointegration and long-term success. The aim of this study was to evaluate the effect of implant length, diameter, and recipient jaw on the pre- and post-functional loading stability. Materials and methods: This study included 17 healthy patients with an age range of 24-61 years. Twenty-two DI were inserted into healed extraction sockets to replace missing tooth/ teeth in premolar and molar regions in upper and lower jaws. Implant stability was measured for each implant and was recorded as implant stability quotient (ISQ) immediately (ISQ0), and at 8 (ISQ8) and 12 (ISQ12) weeks postoperatively, as well as post-functional loading (ISQPFL). The pattern of implant
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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
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Conventional identification of three coccoid green algae isolates was attempted to characterize the studied algae morphologically under compound microscope, which demonstrated confusional phenomenal convergence; all were classified microscopically as the green alga Chlorella vulgaris Beijerinck, 1890.
Phylogenetic studies were conducted to settle the argument about the phenotype by studying the genotype. Genotype the promising field in advance classification by using 18S rRNA and compared to GenBank database using to search the related sequences. The determined sequences showed high a similarity to the strains registered in GenBank.
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Long-term organic amendments are a key strategy to build soil organic carbon (SOC) stocks in semiarid agroecosystems, where low biomass inputs and calcareous parent material constrain carbon accumulation. This 14-year field experiment in central Iraq (2000–2014) evaluated how a gradient of organic matter (OM) additions (0, 1, 2.5, 5, 10, and 20%) affects SOC dynamics, nutrient availability, and soil organic matter composition in clay-dominated, semiarid soils. Surface and subsurface samples (0–30, 30–60, and 60–90 cm) were analysed for SOC, nutrients, and mid-infrared Fourier transform infrared (FTIR) spectra, which were then integrated with Partial Least Squares (PLS) regression and RothC simulations. Moderate OM inputs (5
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l
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