Higher Spin Black Holes from CFT

Higher spin gravity in three dimensions has explicit black holes solutions, carrying higher spin charge. We compute the free energy of a charged black hole from the holographic dual, a 2d CFT with extended conformal symmetry, and find exact agreement with the bulk thermodynamics. In the CFT, higher spin corrections to the free energy can be calculated at high temperature from correlation functions of W-algebra currents.Comment: 24 pages; v2 reference adde

Compliant and stretchable thermoelectric coils for energy harvesting in miniature flexible devices

With accelerating trends in miniaturization of semiconductor devices, techniques for energy harvesting become increasingly important, especially in wearable technologies and sensors for the internet of things. Although thermoelectric systems have many attractive attributes in this context, maintaining large temperature differences across the device terminals and achieving low–thermal impedance interfaces to the surrounding environment become increasingly difficult to achieve as the characteristic dimensions decrease. Here, we propose and demonstrate an architectural solution to this problem, where thin-film active materials integrate into compliant, open three-dimensional (3D) forms. This approach not only enables efficient thermal impedance matching but also multiplies the heat flow through the harvester, thereby increasing the efficiencies for power conversion. Interconnected arrays of 3D thermoelectric coils built using microscale ribbons of monocrystalline silicon as the active material demonstrate these concepts. Quantitative measurements and simulations establish the basic operating principles and the key design features. The results suggest a scalable strategy for deploying hard thermoelectric thin-film materials in harvesters that can integrate effectively with soft materials systems, including those of the human body

Determination of the source/sink term in a heat equatio

In this work, we consider the problem of determining an unknown parameter in a heat equation with ill-posed nature. Applying Tikhonov regularization, we obtain a stable approximation to the unknown parameter from over-specified data. We also present numerical computations that verify the accuracy of our approximation

Determination of conductivity in a heat equation

We consider the problem of determining the conductivity in a heat equation from overspecified non-smooth data. It is an ill-posed inverse problem. We apply a regularization approach to define and construct a stable approximate solution. We also conduct numerical simulation to demonstrate the accuracy of our approximation

Determination of an unknown coefficient in a nonlinear heat equation

AbstractThe problem of determining an unknown term k(u) in the equation k(u)ut=(k(u)ux)x is considered in this paper. Applying Tikhonov's regularization approach, we develop a procedure to find an approximate stable solution to the unknown coefficient from the overspecified data

Real-time short turning strategy based on passenger choice behavior

This article proposed a real-time short turning strategy based on passenger choice behavior to improve transit service for the stops with larger passenger demand in peak periods. A bi-level model is introduced to integrate the real-time control strategy and passenger choice. The upper-level model is an optimal model with the objective of maximizing the reduced waiting time of passengers with the strategy. The lower-level model is an allocation model to calculate passenger demand accurately. The optimization variables include which buses provide short turning services and the start and end stations of each bus. An algorithm is implemented to solve the problem and the effectiveness of the presented strategy is tested with the data of a transit route in Dalian city of China. The results indicate that the real-time short turning strategy based on passenger choice behavior can yield benefits in term of the reduction of passenger waiting time and even the vehicle capacity up

Associated Clustering Strategy for Wireless Sensor Network

We consider the soil moisture monitoring problem and propose a WSN associated clustering strategy based on spatiotemporal data correlation, which ensures that the nodes within each cluster can share a good data correlation and consequently makes the cluster head do the data fusion more efficiently. As a result, the energy of each node will be saved and the lifetime of the whole sensor network will be extended. In the associated clustering strategy, the different clusters can be divided by the correlation characteristics of nodes data, which is based on a dynamic model and a correlation characteristics model after the correlation coefficient analysis. Simulation results show that our proposed associated clustering strategy works very well in soil moisture measurement. Moreover, as compared with the traditional random clustering, the associated clustering strategy based on data correlation achieves better performance for each cluster, and will be more efficient in data fusion at the cluster heads