Objectives: to assess nurses' knowledge toward infection control measures for hepatitis a virus in hemodialysis
units and to detemine the relationship between nurses' knowledge and their demographical characteristics.
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A non-probability `tturposive" sample of (51) nurses, who were working in hemodialysis units were selected
from Baghdad teaching hosphals. The data were collected through the use of constructed questionnaire, which
consists of two parts (I) Demographic data fom that consists of 10 items and (2) Nurses' knowledge form that
consists of 6 sections contain 79 items, by means of direct interview technique with the nurses. The validity of
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Descriptive statistical analysis procedures (frequency, percentage, mean of score) and inferential statistical
analysis procedures (person correlation coefficient, contingency coefficient) were used for the data analysis.
Results: The findings of the study indicated that there is a knowledge deficit of nurses in some aspects relative
to infection control measures. No sigrificant relationship was found between nurses' knowledge and their
gender, marital status and years of experience in hospital, while a significant relationship was found between
nurses' knowledge and their age, level of education, years of experience in hemodialysis unit, sharing in training
sessions and duration of training session that the nurses were engaged in it.
This paper investigates a new approach to the rapid control of an upper limb exoskeleton actuator. We used a mathematical model and motion measurements of a human arm to estimate joint torque as a means to control the exoskeleton’s actuator. The proposed arm model is based on a two-pendulum configuration and is used to obtain instantaneous joint torques which are then passed into control law to regulate the actuator torque. Nine subjects volunteered to take part in the experimental protocol, in which inertial measurement units (IMUs) and a digital goniometer were used to measure and estimate the torque profiles. To validate the control law, a Simscape model was developed to simulate the arm model and control law in which measurem
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The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
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