Objectives: To assess the quality of life for adult patients with peptic ulcers in the city of Sulaimani.
Methodology: A descriptive study, using the assessment approach was conducted on patients with peptic ulcer
disease from January 12th, 2009 to September 30th, 2009. A purposive "non-probability" sample of (100) paƟents
(males and females) with peptic ulcers who attended Kurdistan Center for Gastroenterology and Hepatology were
selected for the study. A questionnaire was adapted from the World Health Organization quality of life questionnaire
(1998) for the purpose of the study. It is comprised of (3) parts that included sociodemographic characteristics form,
medical history form and adult peptic ulcers patients' quality of life (QoL) questionnaire. A pilot study was carried out
on (10) paƟents for the period of January 12th through January 28th, 2009 to determine the study quesƟonnaire's
reliability through the use of stability (test-retest method). A panel of (14) experts was involved in the determination
of the questionnaire's content validity. Data were analyzed through the application of the descriptive statistical data
analysis approach (frequency, percentage, mean of scores) and inferential statistical data analysis approach (Pearson
correlation coefficient and chi-square).
Results: The findings of the study indicated that quality of life was affected in physical domain and that age, gender,
marital status, and monthly income had significant relationship with quality of life domains.
Recommendations: The study recommends that young adults, particularly Individuals with blood group (O) should be
highly aware from gastrointestinal (GI) symptoms and avoids risk factors for the development of peptic ulcer disease
(PUD). Also, the study recommends providing health assurance and conducting further multi centers studies in order
to demonstrate the differences in QoL issues for PUD patients.
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In the geotechnical and terramechanical engineering applications, precise understandings are yet to be established on the off-road structures interacting with complex soil profiles. Several theoretical and experimental approaches have been used to measure the ultimate bearing capacity of the layered soil, but with a significant level of differences depending on the failure mechanisms assumed. Furthermore, local displacement fields in layered soils are not yet studied well. Here, the bearing capacity of a dense sand layer overlying loose sand beneath a rigid beam is studied under the plain-strain condition. The study employs using digital particle image velocimetry (DPIV) and finite element method (FEM) simulations. In the FEM, an experiment
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There is currently a pressing need to create an electro-analytical approach capable of detecting and monitoring genosensors in a highly sensitive, specific, and selective way. In this work, Functionalized Multiwall Carbon Nanotubes, Graphene, Polypyrrole, and gold nanoparticles nanocomposite (f-MWCNTs-GR-PPy-AuNP) were effectively deposited on the surface of the ITO electrode using a drop-casting process to modify it. The structural, morphological, and optical analysis of the modified ITO electrodes was carried out at room temperature using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) images, atomic force microscopy (AFM) and Fourier transform infrared (FTIR) spectra. Cyclic voltammetry (CV) and electrochemi
... Show MoreThe paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
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