Significant Decrease In Total Resistance Research Articles

Changes in total and segmental bioelectrical resistance are correlated with whole-body and segmental changes in lean soft tissue following a resistance training intervention

BackgroundRaw bioelectrical values can be used to assess physiological outcomes, though limited information is available concerning the relationships between changes in these values and changes in other variables of interest.MethodsThis investigation quantified the relationships between total and segmental changes in raw bioelectrical variables (i.e., resistance, reactance, and phase angle) and corresponding whole-body and segmental changes in independently assessed body composition. Resistance-trained females (n = 31, body mass index: 22.8 ± 2.6 kg/m2, body fat: 28 ± 6%) completed eight weeks of supervised resistance training. Before and after the intervention, body composition was assessed via dual-energy x-ray absorptiometry (GE® Lunar Prodigy), and raw bioelectrical variables were assessed via 8-point multi-frequency bioelectrical impedance analysis (Seca® mBCA 515/514) at 19 frequencies ranging from 1 to 1000 kHz.ResultsLean soft tissue of the whole body (+ 3.2% [2.1, 4.4]; mean [95% confidence interval]) and each body segment (+ 2.8 to 6.3%) increased as a result of the intervention. Group-level changes in total (− 2.4% [− 5.2, 0.3]) and segmental fat mass were not statistically significant. Significant decreases in total resistance (− 2.1% [− 3.7, − 0.6] at 50 kHz) and increases in phase angle (+ 4.2% [2.5, 5.9] at 50 kHz) were observed, with minimal changes in reactance and varying changes in segmental values. Moderate to strong negative correlations (0.63 ≤ |r| ≤ 0.83, p ≤ 0.001) were found between changes in lean soft tissue and changes in resistance for the whole body, trunk, and arms. No significant correlations were identified between changes in fat mass or bone mineral content and changes in any bioelectrical variable.ConclusionsTotal and segmental changes in resistance were associated with corresponding total and segmental changes in lean soft tissue following a resistance training intervention, while fewer associations were identified between changes in other bioelectrical parameters (i.e., reactance and phase angle) and body composition variables (e.g., fat mass and bone mineral content). Measurement frequency and body segment appeared to influence the presence and strength relationships between bioelectrical and body composition variables. These findings suggest that researchers and practitioners utilizing bioimpedance technology may benefit from examining raw resistance values to enhance detection of physiological adaptations to exercise interventions.

Performance prediction of hydrofoil- supported catamarans using experiment and ANNs

Using hydrofoils between two hulls of catamarans, hydrofoil supported catamaran (HYSUCAT), is one of the best way to improve the hydrodynamic characteristics of this vessels. In the present study, the hydrodynamic performance of three different hydrofoils of NACA 16, EPPLER 874 and Gottingen 11k are evaluated initially and experimentally via model tests. Afterward, the hydrodynamic performance of these hydrofoils is predicted by using appropriate artificial neural networks (ANNs). For this purpose, the total resistance, effective power, sinkage and trim of HYSUCAT is predicted under different Froude number (Fr) and hydrofoil type. According to the results achieved from the model tests, a significant decrease in total resistance and trim is observed using hydrofoils in the considered catamaran, where Gottingen 11k shows more effects on hydrodynamic performance of HYSUCAT compared to the other two hydrofoils. In addition, maximum mean square errors (MSE) of ANNs output in prediction of total resistance, effective power, sinkage and trim is achieved 0.000683, 0.000155, 0.000454 and 0.00688, respectively. Moreover, an equation is proposed to predict the hydrodynamic performance of the HYSUCAT using ANNs weights and bias.

Effects of an endothelin receptor antagonist and nitroglycerin on digital vascular function in horses during the prodromal stages of carbohydrate overload-induced laminitis

To evaluate changes in digital vascular function in horses with carbohydrate overload (CHO)-induced laminitis and determine the effects of an endothelin (ET) receptor antagonist and nitroglycerin on laminitis-associated vascular dysfunction. 20 adult horses without abnormalities of the digit. Hemodynamic variables were recorded before (baseline) and hourly after all horses were administered a CHO ration via nasogastric tube. In 4 groups of 5 horses each, saline (0.9% NaCl) solution or ET receptor antagonist (10(5)M in digital blood) was administered into the digital arterial circulation according to 1 of 2 schedules. During anesthesia, blood flow; arterial, venous, and capillary pressures; and total, precapillary, and postcapillary resistances were measured in an isolated perfused digit of each horse. In all groups, nitroglycerin was infused (10(5)M in digital blood), and digital microvascular assessments were repeated. The CHO caused a significant decrease in right atrial pressure by 14 hours that was not affected by administration of saline solution or ET receptor antagonist. In isolated digits of anesthetized horses, CHO resulted in a significant decrease in digital blood flow associated with a significant increase in total and postcapillary resistances. Treatment with the ET receptor antagonist and nitroglycerin caused a significant decrease in total resistance. Postcapillary resistance was significantly decreased following treatment with the ET receptor antagonist but was not altered by treatment with nitroglycerin. Treatment with an ET receptor antagonist and nitroglycerin resulted in significant improvement in vascular resistance in isolated perfused digits of anesthetized horses with CHO-induced laminitis.

Economic aspects of commercially produced solar water heaters

Using hydrofoils between two hulls of catamarans, hydrofoil supported catamaran (HYSUCAT), is one of the best way to improve the hydrodynamic characteristics of this vessels. In the present study, the hydrodynamic performance of three different hydrofoils of NACA 16, EPPLER 874 and Gottingen 11k are evaluated initially and experimentally via model tests. Afterward, the hydrodynamic performance of these hydrofoils is predicted by using appropriate artificial neural networks (ANNs). For this purpose, the total resistance, effective power, sinkage and trim of HYSUCAT is predicted under different Froude number (Fr) and hydrofoil type. According to the results achieved from the model tests, a significant decrease in total resistance and trim is observed using hydrofoils in the considered catamaran, where Gottingen 11k shows more effects on hydrodynamic performance of HYSUCAT compared to the other two hydrofoils. In addition, maximum mean square errors (MSE) of ANNs output in prediction of total resistance, effective power, sinkage and trim is achieved 0.000683, 0.000155, 0.000454 and 0.00688, respectively. Moreover, an equation is proposed to predict the hydrodynamic performance of the HYSUCAT using ANNs weights and bias.