Objective(s): The main aim of the study is to determine the level of burden on mothers toward children with anorectal malformation.
Methodology: A descriptive study was carried out at Welfare Pediatric Teaching Hospital and Central Pediatric Teaching Hospital in Baghdad City. From November 15th, 2017 to April 29th, 2018. Convenient sample comprised of (140) children mothers with anorectal malformation were interviewed for the study. The instrument of study is composed of six domains related mothers' burden toward psychosocial burden as a result of child with anorectal malformation. Validity of the study instrument was determined through a panel of experts and the reliability of the questionnaire is determined in a pilot study among (14) mothers. Mothers who participated in the pilot study are excluded from the total study sample. The analysis of the data used was descriptive statistics and statistical inferential, in order to find the level of burden of congenital anomalies on mothers.
Results: The study findings indicate that there are highly significant burden impact on a mother who has a child with anorectal malformation.
Recommendations: The study recommended that Psychological support should be provided by health care professionals for the mothers who have children with anorectal malformation.
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
يتضمن هذا الدليل التعريف بالرسائل والاطاريح الجامعية لطلبة الدراسات العليا ( الماجستير والدكتوراه) مع بيان مستخلص لكل منها المنجزة للسنوات 1999- 2004 لقسم طرائق تدريس القرآن الكريم والتربية الإسلامية في كلية التربية ابن رشد للعلوم الإنسانية جامعة بغداد
This study aimed at identifying the trend to applying the Joint Audit as an approach to improve the financial reports quality with all their characteristics (Relevance, Reliability, Comparability, Consistency), as well as enclose the difficulties that faced the auditors in the Gaza Strip in implementing the Joint Audit. In order to achieve the study aims, a measure was used to identify the trend to apply the Joint Audit and it was distributed to the study sample which is consisting of (119) individuals and retrieved thereof (99) valid for analysis, approximately (83.2%), (69) of them are Auditors, (30) financial managers and accountants. The researcher used the analytical descriptive method, and after analyzing the results, the s
... Show MoreThe results of research to reach the conditions that prevents the emergence of primary or secondary voids and achieve worker benefit from molded by almost 100%, which was the situation that cast poured in a mold heated and insulated from all sides to achieve freezing directional full starting from the region remote from the casting and ending then. Has also been compared to the microscopic structure of the resulting castings of various molding conditions, as these conditions have achieved the best sound microscopic structures.
This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis
... Show MoreObjectives To tailor composites of polyethylene–hydroxyapatite to function as a new intracanal post for the restoration of endodontically treated teeth (ETT). Methods Silanated hydroxyapatite (HA) and zirconium dioxide (ZrO2) filled low-density polyethylene (LDPE) composites were fabricated by a melt extrusion process and characterised using infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). The flexural strength and modulus were determined in dry state and post ageing in simulated body fluid and fractured surfaces analysed by SEM. The water uptake and radiographic appearance of the experimental composites were also measured and compared with a commercially known endodontic fibre
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