BACKGROUND AND OBJECTIVESHealth-related quality of life (HRQOL) is an important health outcome, representing one of the most important goals of all health interventions. The objectives of this study were to determine HRQOL and the factors affecting it in type 2 diabetic patients.PATIENTS AND METHODSThis cross-sectional study was conducted in five primary health care (PHC) centers in the Al-Khobar area. From a random sample of 225 type 2 diabetic patients, 216 patients were included in the study along with 216 age-, sex- and nationality-matched controls. Nine patients refused to participate. Type 2 diabetic patients and controls were interviewed with the translated Arabic SF-12 questionnaire.RESULTSThe mean ages were 50.0±10.0 years for cases and of 49.3±10.3 years for controls (P=.526). Type 2 diabetic patients had lower socioeconomic status and educational level than controls. Obesity was significantly higher in diabetics than controls. HRQOL in type 2 diabetic patients was significantly lower than controls. The mean physical component score was 41.3±8.9 for cases vs. 47.5±9.5 for controls (P<.001), and the mean mental component score 47.8±9.1 in cases vs. 51.5±9.4 in controls (P<.001). HRQOL was significantly lower in females than males (P<.001). HRQOL was impaired in uncontrolled patients (fasting plasma glucose [FPG]>130 mg/dL) in comparison with controlled patients (FPG≤130 mg/dL) (P<.05).CONCLUSIONSHRQOL was lower in type 2 diabetic patients than controls and was affected by many factors. Females had lower HRQOL than males, possibly because of a higher incidence of obesity. Uncontrolled diabetic patients had a lower HRQOL than controlled diabetics. Improving HRQOL in diabetic patients is important.

Abstract:In this study, an optimum seeking-based robust non-linear controller is proposed to maximise wind energy captured by variable speed wind turbines at low-to-medium wind speeds. The proposed strategy simultaneously controls the blade pitch angle and tip-speed ratio, through the turbine rotor angular speed, to an optimal point at which the power coefficient, and hence the wind turbine efficiency, is maximum. The optimal points are given to the controller by an optimisation algorithm that seeks the unknown optimal blade pitch angle and rotor speed. The control method allows for aerodynamic rotor power maximisation without exact knowledge of the wind turbine model. A representative numerical simulation is presented to show that the wind turbine can be accurately controlled to achieve maximum energy capture.

No abstract

No abstract

No abstract