67 research outputs found
Prevalence of Urinary Incontinence and Probable Risk Factors in a Sample of Kurdish Women
Objectives: The most common manifestation of pelvic floor dysfunction is urinary incontinence (UI) which affects 15–50% of adult women depending on the age and risk factors of the population studied. The aim of this study was to determine the probable risk factors associated with UI; the characteristics of women with UI; describe the types of UI, and determine its prevalence. Methods: A cross-sectional study was conducted between February and August 2011, in the Maternity Teaching Hospital of the Erbil Governorate, Kurdistan Region, northern Iraq. It included 1,107 women who were accompanying patients admitted to the hospital. A questionnaire designed by the researchers was used for data collection. A chi-square test was used to test the significance of the association between UI and different risk factors. Binary logistic regression was used, considering UI as the dependent variable. Results: The overall prevalence of UI was 51.7%. The prevalence of stress, urgency, and mixed UI was 5.4%, 13.3% and 33%, respectively. There was a significant positive association between UI and menopause, multiparity, diabetes mellitus (DM), chronic cough, constipation, and a history of gynaecological surgery, while a significant negative association was detected between UI and a history of delivery by both vaginal delivery and Caesarean section. Conclusion: A high prevalence of UI was detected in the studied sample, and the most probable risk factors were multiparity, menopausal status, constipation, chronic cough, and DM
Influence of Metal Ion Doping of Zinc Oxide Photoanode on the Efficiency of Dye Sensitized Solar Cell
Doping zinc oxide nanoparticles (ZnO NPs) and doped with Niobium (Nb5+) and Aluminium (Al3+) ions were synthesized to use as a photoanode for the Dye Sensitized Solar Cells (DSSCs). The structural of the synthetized samples were examined via X-ray diffraction (XRD).
The XRD patterns for all samples confirmed the hexagonal wurtzite structure. The DSSCs based on the undoped and doped ZnO NPs were fabricated and assembled. Scanning electron microscopic
(SEM) images were measured for all fabricated devices. The doping Nb5+ and Al3+ ions influenced the performance of the DSSCs. ZnO NPs doped Nb5+ led to higher surface area and hence more dye loading and retard the recombination of charges, which enhanced the open circuit voltage
Landslide Risk Assessment by Using a New Combination Model Based on a Fuzzy Inference System Method
Landslides are one of the most dangerous phenomena that pose widespread damage to property and human lives. Over the recent decades, a large number of models have been developed for landslide risk assessment to prevent the natural hazards. These models provide a systematic approach to assess the risk value of a typical landslide. However, often models only utilize the numerical data to formulate a problem of landslide risk assessment and neglect the valuable information provided by experts’ opinion. This leads to an inherent uncertainty in the process of modelling. On the other hand, fuzzy inference systems are among the most powerful techniques in handling the inherent uncertainty. This paper develops a powerful model based on fuzzy inference system that uses both numerical data and subjective information to formulate the landslide risk more reliable and accurate. The results show that the proposed model is capable of assessing the landslide risk index. Likewise, the performance of the proposed model is better in comparison with that of the conventional techniques
An efficient optimization approach for designing machine learning models based on genetic algorithm
A step forward towards a comprehensive framework for assessing liquefaction land damage vulnerability: Exploration from historical data
Bayesian Networks-based Shield TBM Risk Management System: Methodology Development and Application
Predicting lateral displacement caused by seismic liquefaction and performing parametric sensitivity analysis: Considering cumulative absolute velocity and fine content
Seismic retrofitting of severely damaged RC connections made with recycled concrete using CFRP sheets
An artificial neural network model on tensile behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag power
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