Objective(s): to determine the effectiveness of instruction intervention upon multipara women's practices to
control stress incontinence.
Methodology: A quasi-experimental study was carried out from (2nd) April, 2010 to 15th June, 2010. Nonprobability
(purposive sample) of (60) multiparous women was selected from Baghdad Teaching Hospital and AlElwia
Maternity Teaching Hospital in Baghdad city, the sample was divided into two groups (30) women were
considered as a study group, and another (30) were considered as the control group. An instructional intervention
was applied on the study group, while the intervention was not applied on control group. A questionnaire was
resolve as a tool of data collection to suit the purpose of the study. A pilot study was carried out to test the
reliability and validity of the questionnaire for the period from 10th of March. - 30 March. 2010. Data were
analyzed through the application of descriptive statistical data analysis approach (frequency, percentage, mean of
scores) and inferential statistical data analysis approach (correlation coefficient, and chi- square).
Result: The results of the study revealed that the study group participants had benefited from the implementation
of instructional intervention and dramatic change had occurred in their practices to control stress urinary
incontinence. The study concluded that the majority of mothers had adequately met their needs control stress
urinary incontinence-pelvic floor and perineum muscles exercise, and lifestyle change.
Recommendation: The study recommended that the instructional intervention can be presented to all multipara
pregnant mothers who are attending to the primary health care centers; moreover, an instructional intervention
might be implemented in the hospital for multipara women to increase their knowledge about stress urinary
incontinence. The study also recommended that the nurse must take the role for teaching multiparous women the
principles of control SUI while they perform such procedure for them during postpartum period.
It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in
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The research deals with two variables: the job stress as an independent variable, and the organizational climate as a dependent one. Each variable includes five sub-dimensions. These dimensions have been involved in an interaction to form
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" There is no difference statistically significant when Mistoi (0.5 ) between the mean scores of the collection of students in the experimental group that is studying the general geographical principles " Bonmozj constructivist learning " and the mean scores of the control group , which is considering the same article ," the traditional way " to acquire concepts.
The researcher adopted th
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