PurposeA simple method of estimating arterial elasticity in the human finger using a volume-oscillometric technique with photoplethysmography was principally studied under the various effects of age, sex, and cold-stress stimulation for testing the capability of using this technique in arterial elasticity analysis.MethodsAmplitude variations in the alternating current signal of the photoplethysmograph during a continuous change in transmural pressure were analyzed to obtain the blood pressure and the transmural pressure–relative volume difference relationship of the arteries. We first tested the effect of the occluding cuff size on the arterial elasticity analysis in eight subjects (ages 20–45 years) to obtain a suitable cuff size, resulting in the selection of a middle cuff with a 22 mm diameter. Blood pressure and arterial elasticity were measured in six groups of subjects separated into three age-groups of women and men (ages 20–25, 32–45, and over 50 years) for testing the effect of age and sex. Twelve subjects (ages 20–25 years) also had their blood pressure and arterial elasticity measured in three conditions under the influence of the cold-stress stimulation.ResultsAge, sex, and cold-stress stimulation had an impact on mean blood pressure (P < 0.0005, 0.025), whereas pulse pressure and heart rate were statistically unchanged by those factors. Furthermore, an advanced age (over 50 years) was found to induce an increase in relative volume difference values (P < 0.025) and upward shifting of the transmural pressure–relative volume difference relationships, whereas sex, level of mean blood pressure, and cold-stress stimulation had no influence on these forms of the index.ConclusionThis study showed the usefulness of the relative volume difference as being a mean blood pressure-independent indicator for changes in arterial elasticity.
There is a developing demand for natural resources because of the growing population. Alternative materials have been developed to address these shortages, concentrating on characteristics such as durability and lightness. By researching composite materials, natural materials can be replaced. It is vital to consider the mechanical properties of composite materials when selecting them for a specific application. This study aims to measure the flexural strength of carbon fiber/epoxy composites. However, the cost of forming these composites is relatively high, given the expense of composite materials. Consequently, this study seeks to reduce molding costs by predicting flexural strength. Conducting many tests for each case is costly; therefore, it is necessary to discover an economical method. To accomplish this, the flexural strength of carbon fiber/epoxy composites was investigated using an artificial neural network (ANN) technique to reduce the expense of material testing. The output parameter investigated was flexural strength, while input parameters included ply orientation, manufacturing, width, thickness, and graphite filler percentage. The scope alternative was determined by identifying the values of variables that substantially affect the flexural strength. The prediction of flexural strength was deemed acceptable if the mean squared error (MSE) value was less than 0.001, and the coefficient of determination (R2) was greater than or equal to 0.95. The obtained results demonstrated an MSE of 0.003039 and an R2 value of 0.95274, indicating a low prediction error and high prediction accuracy for all flexural strength data. Thus, the outcomes of this study provide accurate predictions of flexural strength in the composite materials.
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