Aortic Stiffness Hysteresis in Isolated Mouse Aortic Segments Is Intensified by Contractile Stimuli, Attenuated by Age, and Reversed by Elastin Degradation

Aim: Cyclic stretch of vascular tissue at any given pressure reveals greater dimensions during unloading than during loading, which determines the cardiac beat-by-beat hysteresis loop on the pressure-diameter/volume relationship. The present study did not focus on hysteresis during a single stretch cycle but investigated whether aortic stiffness determined during continuous stretch at different pressures also displayed hysteresis phenomena.Methods: Aortic segments from C57Bl6 mice were mounted in the Rodent Oscillatory Set-up for Arterial Compliance (ROTSAC), where they were subjected to high frequency (10 Hz) cyclic stretch at alternating loads equivalent to a constant theoretical pulse pressure of 40 mm Hg. Diastolic and systolic diameter, compliance, and the Peterson elastic modulus (Ep), as a measure of aortic stiffness, was determined starting at cyclic stretch between alternating loads corresponding to 40 and 80 mm Hg, at each gradual load increase equivalent to 20 mm Hg, up to loads equivalent to pressures of 220 and 260 mm Hg (loading direction) and then repeated in the downward direction (unloading direction). This was performed in baseline conditions and following contraction by α1 adrenergic stimulation with phenylephrine or by depolarization with high extracellular K+ in aortas of young (5 months), aged (26 months) mice, and in segments treated with elastase.Results: In baseline conditions, diastolic/systolic diameters and compliance for a pulse pressure of 40 mm Hg were larger at any given pressure upon unloading (decreasing pressure) than loading (increasing pressure) of the aortic segments. The pressure-aortic stiffness (Ep) relationship was similar in the loading and unloading directions, and aortic hysteresis was absent. On the other hand, hysteresis was evident after activation of the VSMCs with the α1 adrenergic agonist phenylephrine and with depolarization by high extracellular K+, especially after inhibition of basal NO release with L-NAME. Aortic stiffness was significantly smaller in the unloading than in the loading direction. In comparison with young mice, old-mouse aortic segments also displayed contraction-dependent aortic hysteresis, but hysteresis was shifted to a lower pressure range. Elastase-treated segments showed higher stiffness upon unloading over nearly the whole pressure range.Conclusions: Mouse aortic segments display pressure- and contraction-dependent diameter, compliance, and stiffness hysteresis phenomena, which are modulated by age and VSMC-extracellular matrix interactions. This may have implications for aortic biomechanics in pathophysiological conditions and aging.

Appearance of Hysteresis Phenomena on Hydrodynamic Lubrication in a Seal-Type Thrust Bearing with Dimples

This paper described unique hysteresis phenomena that appear in the hydrodynamic lubrication properties of dimpled thrust bearings. A seal-type thrust bearing specimen was textured with dimples. The load-carrying capacity and frictional torque were measured with a constant film thickness and compared to those of a dimple-free specimen. For examining the size of cavitation bubbles that occurred in various conditions, the lubricating area was observed during experiments. The used dimpled specimen produced the load-carrying capacity, and it exhibited an interesting hysteresis phenomenon, the difference in the values in the increasing and decreasing processes of rotational speed. The visualization test results revealed that the size of cavitation bubbles occurring within the dimples strongly affected this phenomenon. In addition, the dimpled specimen was able to reduce the frictional torque compared to the dimple-free specimen. However, the frictional torque did not show the hysteresis loop similar to that shown in the load-carrying capacity.

Implementation of Preisach-Krasnoselskii Hysteresis Model with the Use of Artificial Neural Networks

Accurate modeling of hysteresis is essential for both the design and performance evaluation of electromagnetic devices. This project proposes the use of feedforward meural networks to implement an accurate magnetic hysteresis model based on the mathematical difinition provided by the Preisach-Krasnoselskii (P-K) model. Feedforward neural networks are a linear association networks that relate the ouput patterns to input patterns. By introducing the multi-layer feedforward neural networks make the hysteresis modeling accurate without estimation of double integrals. Simulation results provide the detailed illustrations. The comparisons with the experiments show that the proposed approach is able to satisfactorily reproduce many features of obsereved hysteresis phenomena an in turn can be used for many applications of interest.

Implementation of Preisach-Krasnoselskii Hysteresis Model with the Use of Artificial Neural Networks

Accurate modeling of hysteresis is essential for both the design and performance evaluation of electromagnetic devices. This project proposes the use of feedforward meural networks to implement an accurate magnetic hysteresis model based on the mathematical difinition provided by the Preisach-Krasnoselskii (P-K) model. Feedforward neural networks are a linear association networks that relate the ouput patterns to input patterns. By introducing the multi-layer feedforward neural networks make the hysteresis modeling accurate without estimation of double integrals. Simulation results provide the detailed illustrations. The comparisons with the experiments show that the proposed approach is able to satisfactorily reproduce many features of obsereved hysteresis phenomena an in turn can be used for many applications of interest.

Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation

In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing.