Saccular aneurysms on straight and curved vessels are subject to different hemodynamics: Implications of intravascular stenting

Our aim was to examine hemodynamic implications of intravascular stenting in the canine venous pouch (sidewall or straight-vessel) and rabbit elastase (curved-vessel) aneurysm models. Flow dynamics in stented (Wallstent) and nonstented versions were studied by using computational fluid dynamics simulations and in vitro flow visualization, with a focus on stent placement effects on aneurysmal flow stagnancy and flow impingement. Results show that sidewall and curved aneurysm models have fundamentally different hemodynamics (shear-driven versus inertia-driven) and thus stent placement outcomes

Anomalies of upper critical field in the spinel superconductor LiTi2_2O4−δ_{4-\delta}

High-field electrical transport and point-contact tunneling spectroscopy were used to investigate superconducting properties of the unique spinel oxide, LiTi$_2$O$_{4-\delta}$ films with various oxygen content. We find that the upper critical field $B_\mathrm{c2}$ gradually increases as more oxygen impurities are brought into the samples by carefully tuning the deposition atmosphere. It is striking that although the superconducting transition temperature and energy gap are almost unchanged, an astonishing isotropic $B_\mathrm{c2}$ up to $\sim$ 26 Tesla is observed in oxygen-rich sample, which is doubled compared to the anoxic sample and breaks the Pauli limit. Such anomalies of $B_\mathrm{c2}$ were rarely reported in other three dimensional superconductors. Combined with all the anomalies, three dimensional spin-orbit interaction induced by tiny oxygen impurities is naturally proposed to account for the remarkable enhancement of $B_\mathrm{c2}$ in oxygen-rich LiTi$_2$O$_{4-\delta}$ films. Such mechanism could be general and therefore provides ideas for optimizing practical superconductors with higher $B_\mathrm{c2}$

Anomalies of upper critical field in the spinel superconductor LiTi2 O4-δ

© 2019 American Physical Society. High-field electrical transport and point-contact tunneling spectroscopy are used to investigate superconducting properties of spinel oxide LiTi2O4-δ films with various oxygen contents. It is striking that although the superconducting transition temperature and energy gap are almost unchanged, an isotropic upper critical field Bc2 up to 26.0 T is observed in the oxygen-rich sample, which is more than twice the Bc2 of 11.3 T in the anoxic one. The change of the dominating pair-breaking mechanism from the orbital effect to the spin flip at Bc2 is achieved by tuning oxygen contents, which can be explained by the appearance of small Fermi pockets due to extra oxygen. Our paper provides deep understanding of the intrinsic relation between Bc2 and the complex Fermi surface, and contributes a promising way to enhance Bc2 for practical superconductors

Entrepreneurial intention and outcome expectancy : evidence from South Korea and China

Focusing on the East Asian context, this study examines (1) cultural and gender differences in entrepreneurial intention, (2) the mediating effects of culture and gender on the relationships between entrepreneurial intention and expectancies of positive entrepreneurial outcomes, and (3) the results of entrepreneurial intention of females. The findings reveal that while Chinese students have a greater entrepreneurial intention than South Korean students, the relationships between entrepreneurial intention and outcome expectancies are stronger in South Korean than in Chinese students. In terms of gender, males have a greater entrepreneurial intention than females. The relationships between entrepreneurial intention and outcome expectancies are stronger in male than in female students. Social status and self-realization are the entrepreneurial outcomes that females value most

Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays

In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discretetime stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: 1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; 2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and 3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results

H-infinity filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities

In this paper, we deal with the robust H∞ filtering problem for a class of uncertain nonlinear time-delay stochastic systems. The system under consideration contains parameter uncertainties, Itoˆ-type stochastic disturbances, time-varying delays, as well as sector-bounded nonlinearities. We aim at designing a full-order filter such that, for all admissible uncertainties, nonlinearities and time delays, the dynamics of the filtering error is guaranteed to be robustly asymptotically stable in the mean square, while achieving the prescribed H∞ disturbance rejection attenuation level. By using the Lyapunov stability theory and Itoˆ's differential rule, sufficient conditions are first established to ensure the existence of the desired filters, which are expressed in the form of a linear matrix inequality (LMI). Then, the explicit expression of the desired filter gains is also characterized. Finally, a numerical example is exploited to show the usefulness of the results derived

Robust H-infinity filtering for discrete nonlinear stochastic systems with time-varying delay

In this paper, we are concerned with the robust H-infinity filtering problem for a class of nonlinear discrete time-delay stochastic systems. The system under study involves parameter uncertainties, stochastic disturbances, time-varying delays and sector-like nonlinearities. The problem addressed is the design of a full-order filter such that, for all admissible uncertainties, nonlinearities and time delays, the dynamics of the filtering error is constrained to be robustly asymptotically stable in the mean square, and a prescribed H-infinity disturbance rejection attenuation level is also guaranteed. By using the Lyapunov stability theory and some new techniques, sufficient conditions are first established to ensure the existence of the desired filtering parameters. These conditions are dependent on the lower and upper bounds of the time-varying delays. Then, the explicit expression of the desired filter gains is described in terms of the solution to a linear matrix inequality (LMI). Finally, a numerical example is exploited to show the usefulness of the results derived

Exponential Stabilization of a Class of Stochastic System With Markovian Jump Parameters and Mode-Dependent Mixed Time-Delays

In this technical note, the globally exponential stabilization problem is investigated for a general class of stochastic systems with both Markovian jumping parameters and mixed time-delays. The mixed mode-dependent time-delays consist of both discrete and distributed delays. We aim to design a memoryless state feedback controller such that the closed-loop system is stochastically exponentially stable in the mean square sense. First, by introducing a new Lyapunov-Krasovskii functional that accounts for the mode-dependent mixed delays, stochastic analysis is conducted in order to derive a criterion for the exponential stabilizability problem. Then, a variation of such a criterion is developed to facilitate the controller design by using the linear matrix inequality (LMI) approach. Finally, it is shown that the desired state feedback controller can be characterized explicitly in terms of the solution to a set of LMIs. Numerical simulation is carried out to demonstrate the effectiveness of the proposed methods

On delay-dependent robust exponential stability of stochastic neural networks with mixed time delays and Markovian switching

This paper deals with the global exponential stability analysis problem for a general class of uncertain stochastic neural networks with mixed time delays and Markovian switching. The mixed time delays under consideration comprise both the discrete time-varying delays and the distributed time-delays. The main purpose of this paper is to establish easily verifiable conditions under which the delayed stochastic neural network is robustly exponentially stable in the mean square in the presence of parameters uncertainties, mixed time delays, and Markovian switching. By employing new Lyapunov-Krasovskii functionals and conducting stochastic analysis, a linear matrix inequality (LMI) approach is developed to derive the criteria for the robust exponential stability, which can be readily checked by using some standard numerical packages such as the Matlab LMI Toolbox. The criteria derived are dependent on both the discrete time delay and distributed time delay, and, are therefore, less conservative. A simple example is provided to demonstrate the effectiveness and applicability of the proposed testing criteria

Asymptotic stability for neural networks with mixed time-delays : the discrete-time case

This paper is concerned with the stability analysis problem for a new class of discrete-time recurrent neural networks with mixed time-delays. The mixed time-delays that consist of both the discrete and distributed time-delays are addressed, for the first time, when analyzing the asymptotic stability for discrete-time neural networks. The activation functions are not required to be differentiable or strictly monotonic. The existence of the equilibrium point is first proved under mild conditions. By constructing a new Lyapnuov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the discrete-time neural networks to be globally asymptotically stable. As an extension, we further consider the stability analysis problem for the same class of neural networks but with state-dependent stochastic disturbances. All the conditions obtained are expressed in terms of LMIs whose feasibility can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition