14 research outputs found

    Some thoughts on neural network modelling of micro-abrasion-corrosion processes

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    There is increasing interest in the interactions of microabrasion, involving small particles of less than 10 μm in size, with corrosion. This is because such interactions occur in many environments ranging from the offshore to health care sectors. In particular, micro-abrasion-corrosion can occur in oral processing, where the abrasive components of food interacting with the acidic environment, can lead to degradation of the surface dentine of teeth. Artificial neural networks (ANNs) are computing mechanisms based on the biological brain. They are very effective in various areas such as modelling, classification and pattern recognition. They have been successfully applied in almost all areas of engineering and many practical industrial applications. Hence, in this paper an attempt has been made to model the data obtained in microabrasion-corrosion experiments on polymer/steel couple and a ceramic/lasercarb coating couple using ANN. A multilayer perceptron (MLP) neural network is applied and the results obtained from modelling the tribocorrosion processes will be compared with those obtained from a relatively new class of neural networks namely resource allocation network

    Sex differences in renin-angiotensin-aldosterone system affect extracellular volume in healthy subjects

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    Several studies reported sex differences in aldosterone. It is unknown whether these differences are associated with differences in volume regulation. Therefore we studied both aldoste

    Low Urinary Potassium Excretion Is Associated with Higher Risk of All-Cause Mortality in Patients with Type 2 Diabetes: Results of the Dutch Diabetes and Lifestyle Cohort Twente (DIALECT)

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    BackgroundLow 24-h urinary potassium excretion, reflecting low potassium intake, is associated with premature mortality in the general population.ObjectivesTo determine whether urinary potassium excretion is associated with all-cause mortality in patients with type 2 diabetes.MethodsWe performed a prospective cohort study in 654 patients with type 2 diabetes in the Diabetes and Lifestyle Cohort Twente (DIALECT). Sex-specific tertiles of 24-h urinary potassium excretion were analyzed in a multivariable Cox regression model with all-cause mortality. The outpatient program of the hospital uses a continuous surveillance system by the municipal registry of death to ensure up-to-date information on the patient's status (alive or deceased). FFQs were used to study associations between urinary potassium excretion and food products.ResultsUrinary potassium excretion at baseline was 84 & PLUSMN; 25 mmol/d in males and 65 & PLUSMN; 22 mmol/d in females, corresponding to estimated potassium intakes of 4250 & PLUSMN; 1270 mg/d and 3300 & PLUSMN; 875 mg/d. During a median follow-up of 5.2 (IQR: 2.7-7.9] y, 96 participants died. In a fully adjusted model, patients in the lowest sex-specific tertile had a higher risk of all-cause mortality, compared with patients in the highest sex-specific tertile (HR: 2.09; 95% CI: 1.06, 4.10; P = 0.03). Patients in the lowest sex-specific tertile consumed fewer fruits and vegetables, dairy, coffee, and potato products compared with patients in the highest sex-specific tertile (all P < 0.05).ConclusionsLow potassium intake is associated with a higher risk of all-cause mortality in Dutch patients with type 2 diabetes. Intervention studies are needed to determine whether potassium supplementation improves longevity in patients with type 2 diabetes. This trial was registered in the as NTR trial code 5855
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