Quantum entropy of the Kerr black hole arising from gravitational perturbation

The quantum entropy of the Kerr black hole arising from gravitational perturbation is investigated by using Null tetrad and \'t Hooft\'s brick-wall model. It is shown that effect of the graviton\'s spins on the subleading correction is dependent of the square of the spins and the angular momentum per unit mass of the black hole, and contribution of the logarithmic term to the entropy will be positive, zero, and negative for different value of $a/r_+$.Comment: 8 pages, 1 figure, Latex. to appear in Phys. Rev.

Statistical Entropy of a Stationary Dilaton Black Hole from Cardy Formula

With Carlip's boundary conditions, a standard Virasoro subalgebra with corresponding central charge for stationary dilaton black hole obtained in the low-energy effective field theory describing string is constructed at a Killing horizon. The statistical entropy of stationary dilaton black hole yielded by standard Cardy formula agree with its Bekenstein-Hawking entropy only if we take period $T$ of function $v$ as the periodicity of the Euclidean black hole. On the other hand, if we consider first-order quantum correction then the entropy contains a logarithmic term with a factor $-{1/2}$, which is different from Kaul and Majumdar's one, $-{3/2}$. We also show that the discrepancy is not just for the dilaton black hole, but for any one whose corresponding central change takes the form $\frac{c}{12}= \frac{A_H}{8\pi G}\frac{2\pi}{\kappa T}$.Comment: 11 pages, no figure, RevTex. Accepted for publication in Phys. Rev.

Entropies of the general nonextreme stationary axisymmetric black hole: statistical mechanics and thermodynamics

Starting from metric of the general nonextreme stationary axisymmetric black hole in four-dimensional spacetime, both statistical-mechanical and thermodynamical entropies are studied. First, by means of the "brick wall" model in which the Dirichlet condition is replaced by a scattering ansatz for the field functions at the horizon and with Pauli-Villars regularization scheme, an expression for the statistical-mechanical entropy arising from the nonminimally coupled scalar fields is obtained. Then, by using the conical singularity method Mann and Solodukhin's result for the Kerr-Newman black hole (Phys. Rev. D54, 3932(1996)) is extended to the general stationary black hole and the nonminimally coupled scalar field. We last shown by comparing the two results that the statistical-mechanical entropy and one-loop correction to the thermodynamical entropy are equivalent for coupling $\xi\leq 0$. After renormalization, a relation between the two entropies is given.Comment: 18 pages, Latex, nofigue. Accepted by Phys. Rev.

Entropies of Rotating Charged Black Holes from Conformal Field Theory at Killing Horizons

The covariant phase technique is used to compute the constraint algebra of the stationary axisymmetric charged black hole. A standard Virasoro subalgebra with corresponding central charge is constructed at a Killing horizon with Carlip's boundary conditions. For the Kerr-Newman black hole and the Kerr-Newman-AdS black hole, the density of states determined by conformal fields theory methods yields the statistical entropy which agrees with the Bekenstein-Hawking entropy.Comment: 12 pages, no figure, RevTe

CAM : a Combined Attention Model for natural language inference.

Natural Language Inference (NLI) is a fundamental step towards natural language understanding. The task aims to detect whether a premise entails or contradicts a given hypothesis. NLI contributes to a wide range of natural language understanding applications such as question answering, text summarization and information extraction. Recently, the public availability of big datasets such as Stanford Natural Language Inference (SNLI) and SciTail, has made it feasible to train complex neural NLI models. Particularly, Bidirectional Long Short-Term Memory networks (BiLSTMs) with attention mechanisms have shown promising performance for NLI. In this paper, we propose a Combined Attention Model (CAM) for NLI. CAM combines the two attention mechanisms: intraattention and inter-attention. The model first captures the semantics of the individual input premise and hypothesis with intra-attention and then aligns the premise and hypothesis with inter-sentence attention. We evaluate CAM on two benchmark datasets: Stanford Natural Language Inference (SNLI) and SciTail, achieving 86.14% accuracy on SNLI and 77.23% on SciTail. Further, to investigate the effectiveness of individual attention mechanism and in combination with each other, we present an analysis showing that the intra- and inter-attention mechanisms achieve higher accuracy when they are combined together than when they are independently used

Synergistic Enhancement Properties of a Flexible Integrated PAN/PVDF Piezoelectric Sensor for Human Posture Recognition

The flexible pressure sensor has attracted much attention due to its wearable and conformal advantage. All the same, enhancing its electrical and structural properties is still a huge challenge. Herein, a flexible integrated pressure sensor (FIPS) composed of a solid silicone rubber matrix, composited with piezoelectric powers of polyacrylonitrile/Polyvinylidene fluoride (PAN/PVDF) and conductive silver-coated glass microspheres is first proposed. Specifically, the mass ratio of the PAN/PVDF and the rubber is up to 4:5 after mechanical mixing. The output voltage of the sensor with composite PAN/PVDF reaches 49 V, which is 2.57 and 3.06 times that with the single components, PAN and PVDF, respectively. In the range from 0 to 800 kPa, its linearity of voltage and current are all close to 0.986. Meanwhile, the sensor retains high voltage and current sensitivities of 42 mV/kPa and 0.174 nA/kPa, respectively. Furthermore, the minimum response time is 43 ms at a frequency range of 1–2.5 Hz in different postures, and the stability is verified over 10,000 cycles. In practical measurements, the designed FIPS showed excellent recognition abilities for various gaits and different bending degrees of fingers. This work provides a novel strategy to improve the flexible pressure sensor, and demonstrates an attractive potential in terms of human health and motion monitoring

High-Performance MIM Capacitors for a Secondary Power Supply Application

Microstructure is important to the development of energy devices with high performance. In this work, a three-dimensional Si-based metal-insulator-metal (MIM) capacitor has been reported, which is fabricated by microelectromechanical systems (MEMS) technology. Area enlargement is achieved by forming deep trenches in a silicon substrate using the deep reactive ion etching method. The results indicate that an area of 2.45 × 103 mm2 can be realized in the deep trench structure with a high aspect ratio of 30:1. Subsequently, a dielectric Al2O3 layer and electrode W/TiN layers are deposited by atomic layer deposition. The obtained capacitor has superior performance, such as a high breakdown voltage (34.1 V), a moderate energy density (≥1.23 mJ/cm2) per unit planar area, a high breakdown electric field (6.1 ± 0.1 MV/cm), a low leakage current (10−7 A/cm2 at 22.5 V), and a low quadratic voltage coefficient of capacitance (VCC) (≤63.1 ppm/V2). In addition, the device’s performance has been theoretically examined. The results show that the high energy supply and small leakage current can be attributed to the Poole–Frenkel emission in the high-field region and the trap-assisted tunneling in the low-field region. The reported capacitor has potential application as a secondary power supply