Dual-modal Assessment for in Vivo Investigation of Neurovascular Characteristic of Cerebral Edema Induced by Lipopolysaccharide

The pathological features of cerebral edema are complicated, but usually only intracranial pressure (ICP) is regarded as the most important indicator for monitoring cerebral edema. The research focused on investigating the neurovascular characteristic of the lipopolysaccharide (LPS)-induced cerebral edema model in rats by using simultaneous electrophysical and hemodynamic recording. The results showed that neurophysiology (firing rate (FR), interval histogram index (ISI), and the power spectrum of local field potential (LFPs power)) and hemodynamic response (oxygenated hemoglobin (HbO2), deoxyhemoglobin (HbR) and relative cerebral blood flow (CBF)) were linearly related, and the Pearson’s correlation coefficient was determined by the BBB integrity after LPS injection. Furtherly, the improvement of treatment after two agents were observed successfully through these neurophysiological and hemodynamic parameters. The optical-electrical joint method provided a technical solution for cerebral edema functional monitoring and anti-edema drug efficacy evaluation. Our findings revealed the neurovascular and BBB impact of cerebral edema and improved the limitation of in vivo pathological diagnosis of cerebral edema.

Quadratic Singular Perturbation Problems With Nonmonotone Transition Layer Properties

In this article, we consider the quadratic singular perturbation problems with Nonmonotone Transition Layer Properties. Under certain conditions, solutions are shown to exhibit nonmonotone transition layer behavior at turning point t=0. The formal approximation of problems is constructed using composite expansions, and then approximation solutions of left and right sides at t=0 are joined by joint method which exhibits spike layer behavior and boundary layer behavior respectively. As a result, an approximate solution is formed which exhibits nonmonotone transition layer behavior. In addition, the existence and asymptotic behavior of solutions are proved by the theory of differential inequalities.

Elastostatic modeling of multi-link flexible manipulator based on 2D dual-triangle tensegrity mechanism

The paper deals with the elastostatic modeling of multi-link flexible manipulator based on dual-triangle tensegrity mechanism and its non-linear behavior under external loading. The main attention is paid to the static equilibriums and the manipulator stiffness behavior under the loading for the arbitrary initial configuration. It was proved that there is a quasi-buckling phenomenon for this manipulator while the external loading is increasing. In the neighborhood of these configurations, the manipulator behavior was analyzed using the enhanced Virtual Joint Method (VJM). A relevant simulation study confirmed the obtained theoretical results.

Energy-Efficient Task Offloading Under E2E Latency Constraints

<b>Abstract:</b><br>In this paper, we propose a novel resource management scheme that jointly allocates the transmit power and computational resources in a centralized radio access network architecture. The network comprises a set of computing nodes to which the requested tasks of different users are offloaded. The optimization problem minimizes the energy consumption of task offloading while takes the end-to-end-latency, i.e., the transmission, execution, and propagation latencies of each task, into account. We aim to allocate the transmit power and computational resources such that the maximum acceptable latency of each task is satisfied. Since the optimization problem is non-convex, we divide it into two sub-problems, one for transmit power allocation and another for task placement and computational resource allocation. Transmit power is allocated via the convex-concave procedure. In addition, a heuristic algorithm is proposed to jointly manage computational resources and task placement. We also propose a feasibility analysis that finds a feasible subset of tasks. Furthermore, a disjoint method that separately allocates the transmit power and the computational resources is proposed as the baseline of comparison. A lower bound on the optimal solution of the optimization problem is also derived based on exhaustive search over task placement decisions and utilizing Karush–Kuhn–Tucker conditions. Simulation results show that the joint method outperforms the disjoint method in terms of acceptance ratio. Simulations also show that the optimality gap of the joint method is less than 5%.<br>

Energy-Efficient Task Offloading Under E2E Latency Constraints

<b>Abstract:</b><br>In this paper, we propose a novel resource management scheme that jointly allocates the transmit power and computational resources in a centralized radio access network architecture. The network comprises a set of computing nodes to which the requested tasks of different users are offloaded. The optimization problem minimizes the energy consumption of task offloading while takes the end-to-end-latency, i.e., the transmission, execution, and propagation latencies of each task, into account. We aim to allocate the transmit power and computational resources such that the maximum acceptable latency of each task is satisfied. Since the optimization problem is non-convex, we divide it into two sub-problems, one for transmit power allocation and another for task placement and computational resource allocation. Transmit power is allocated via the convex-concave procedure. In addition, a heuristic algorithm is proposed to jointly manage computational resources and task placement. We also propose a feasibility analysis that finds a feasible subset of tasks. Furthermore, a disjoint method that separately allocates the transmit power and the computational resources is proposed as the baseline of comparison. A lower bound on the optimal solution of the optimization problem is also derived based on exhaustive search over task placement decisions and utilizing Karush–Kuhn–Tucker conditions. Simulation results show that the joint method outperforms the disjoint method in terms of acceptance ratio. Simulations also show that the optimality gap of the joint method is less than 5%.<br>