Objective(s): To assess mothers' practices toward children with steroid – sensitive Nephrotic Syndrome (SSNS) who
are visiting nephrology consultation units, and to find out the relationships between their practices and the
demographical data for mother and child.
Methodology: A descriptive study was carried out at nephrology consultation units of Baghdad pediatrics hospitals
(Child's Central Pediatric Teaching Hospital, Al-kadimiyia Teaching Hospital, and Welfare Teaching Hospital) started
from February 18th to the end of July 2009. A purposive sample of (80) mothers who company their children were
selected. The data were collected through a constructed questionnaire, with two parts; the first part is concerned with
mother's and child's demographical characteristic, the second part is concerned with mothers' practices about
steroid– sensitive nephrotic syndrome. An interview method was used to full questionnaire format. The validity was
determined through a panel of experts. While, the reliability was determined through a pilot study. The data were
analyzed by using descriptive and inferential statistical measures by using the statistical package of social science
(SPSS) version (15).
Results: The findings of the study showed that mothers have poor practices (61.3%). The study results revealed that
there is a significant association between mothers' practices and their educational level, and duration of the child's
disease. While mother's age, occupation, child's age, child's sex, child's age at onset (years), child's previous disease
and heredity have no association with their practices.
Recommendations: The study recommends that health education for mothers would improve their practices.
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Experimental measurements were done for characterizing current-voltage and power-voltage of two types of photovoltaic (PV) solar modules; monocrystalline silicon (mc-Si) and copper indium gallium di-selenide (CIGS). The conversion efficiency depends on many factors, such as irradiation and temperature. The assembling measures as a rule cause contrast in electrical boundaries, even in cells of a similar kind. Additionally, if the misfortunes because of cell associations in a module are considered, it is hard to track down two indistinguishable photovoltaic modules. This way, just the I-V, and P-V bends' trial estimation permit knowing the electrical boundaries of a photovoltaic gadget with accuracy. This measure
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Diabetes mellitus is a chronic illness that commonly leads to progressive and incapacitating of patients’ condition over the past 20 years.
The aim of the study was to evaluate the effects of the coughing technique, ShotBlockerTo evaluate the effects of the coughing technique, ShotBlocker and vibration device on pain intensity and patient satisfaction during subcutaneous (SC) insulin injections in hospitalised adults with Type 2 diabetes mellitus (T2DM).
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In the present study, magnet silica-coated Ag2WO4/Ag2S nanocomposites (FOSOAWAS) were fabricated via a multistep method to address the drawbacks related to single photocatalysts (pure Ag2WO4 and pure Ag2S) and to clarify the significant influence of semiconductor heterojunction on the enhancement of visible-light-driven organic degradation. Different techniques were performed to investigate the elemental composition, morphology, magnetic and photoelectrochemical properties of the fabricated FOSOAWAS photocatalyst. The FOSOAWAS photocatalyst (1 g/L) exhibited excellent photodegradation efficiency (99.5%) against Congo red dye (CR = 20 ppm) after 140 min of visible-light illumination. This result confirmed the ability of the heterojunction be
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
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