Geometrothermodynamics of five dimensional black holes in Einstein–Gauss–Bonnet theory

We investigate the thermodynamic properties of 5D static and spherically symmetric black holes in (i) Einstein–Maxwell–Gauss–Bonnet theory, (ii) Einstein–Maxwell–Gauss–Bonnet theory with negative cosmological constant, and in (iii) Einstein–Yang–Mills–Gauss–Bonnet theory. To formulate the thermodynamics of these black holes we use the Bekenstein–Hawking entropy relation and, alternatively, a modified entropy formula which follows from the first law of thermodynamics of black holes. The results of both approaches are not equivalent. Using the formalism of geometrothermodynamics, we introduce in the manifold of equilibrium states a Legendre invariant metric for each black hole and for each thermodynamic approach, and show that the thermodynamic curvature diverges at those points where the temperature vanishes and the heat capacity diverges.     

The fused heterocycle 2‐benzyl‐3‐methyl‐1‐phenyl‐4‐phenyl­sulfonyl‐2H,4H‐pyrrolo­[3,4‐b]­indole

Crystal structure determination of the title mol­ecule, C₃₀H₂₄N₂O₂S, reveals that the pyrrole ring in this fused heterocycle, although presumably strained and reactive in cyclo­addition reactions, does not differ appreciably from N‐methyl­pyrrole except for a shorter C—C single bond [1.409 (4) Å] in the pyrrole ring.     

铁基非晶丝样低频涡流损耗分析

以非晶丝的芯-壳(core-shell)结构模型为基础,对铁基非晶丝考虑其芯内存在一沿轴向的应力磁各向异性K_c, 而壳内是沿径向的应力磁各向异性K_s(K_c和K_s均为应力能常量λ_sσ₀的函数),导出了样品的交流环向磁导率μ_φ(r).由Maxwell方程和Ohm定律计算出此模型下的低频经典涡流损耗反常因子为η＝2．2.理论值与实验结果的比较表明,铁基非晶丝的 关键词： 非晶丝 芯壳结构 涡流损耗反常因子     

Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals

In some applications, it is important to compare the stochastic properties of two multivariate time series that have unequal dimensions. A new method is proposed to compare the spread of spectral information in two multivariate stationary processes with different dimensions. To measure discrepancies, a frequency specific spectral ratio (FS-ratio) statistic is proposed and its asymptotic properties are derived. The FS-ratio is blind to the dimension of the stationary process and captures the proportion of spectral power in various frequency bands. Here we develop a technique to automatically identify frequency bands that carry significant spectral power. We apply our method to track changes in the complexity of a 32-channel local field potential (LFP) signal from a rat following an experimentally induced stroke. At every epoch (a distinct time segment from the duration of the experiment), the nonstationary LFP signal is decomposed into stationary and nonstationary latent sources and the complexity is analyzed through these latent stationary sources and their dimensions that can change across epochs. The analysis indicates that spectral information in the Beta frequency band (12–30 Hertz) demonstrated the greatest change in structure and complexity due to the stroke.