Palatini formulation of f(R,T)f(R,T) gravity theory, and its cosmological implications

We consider the Palatini formulation of $f(R,T)$ gravity theory, in which a nonminimal coupling between the Ricci scalar and the trace of the energy-momentum tensor is introduced, by considering the metric and the affine connection as independent field variables. The field equations and the equations of motion for massive test particles are derived, and we show that the independent connection can be expressed as the Levi-Civita connection of an auxiliary, energy-momentum trace dependent metric, related to the physical metric by a conformal transformation. Similarly to the metric case, the field equations impose the non-conservation of the energy-momentum tensor. We obtain the explicit form of the equations of motion for massive test particles in the case of a perfect fluid, and the expression of the extra-force, which is identical to the one obtained in the metric case. The thermodynamic interpretation of the theory is also briefly discussed. We investigate in detail the cosmological implications of the theory, and we obtain the generalized Friedmann equations of the $f(R,T)$ gravity in the Palatini formulation. Cosmological models with Lagrangians of the type $f=R-\alpha ^2/R+g(T)$ and $f=R+\alpha ^2R^2+g(T)$ are investigated. These models lead to evolution equations whose solutions describe accelerating Universes at late times.Comment: 22 pages, no figures, accepted for publication in EPJC; references adde

Multichannel topological Kondo effect

A Coulomb blockaded $M$-Majorana island coupled to normal metal leads realizes a novel type of Kondo effect where the effective impurity "spin" transforms under the orthogonal group $SO(M)$. The impurity spin stems from the non-local topological ground state degeneracy of the island and thus the effect is known as the topological Kondo effect. We introduce a physically motivated $N$-channel generalization of the topological Kondo model. Starting from the simplest case $N=2$, we conjecture a stable intermediate coupling fixed point and evaluate the resulting low-temperature impurity entropy. The impurity entropy indicates that an emergent Fibonacci anyon can be realized in the $N=2$ model. We also map the case $N=2$, $M=4$ to the conventional 4-channel Kondo model and find the conductance at the intermediate fixed point. By using the perturbative renormalization group, we also analyze the large-$N$ limit, where the fixed point moves to weak coupling. In the isotropic limit, we find an intermediate stable fixed point, which is stable to "exchange" coupling anisotropies, but unstable to channel anisotropy. We evaluate the fixed point impurity entropy and conductance to obtain experimentally observable signatures of our results. In the large-$N$ limit we evaluate the full cross over function describing the temperature-dependent conductance.Comment: 15 pages, 4 figures, improved version, accepted in PR

Stabilization via delay feedback for highly nonlinear stochastic time-varying delay systems with Markovian switching and Poisson jump

Little work seems to be known about stabilization results of highly nonlinear stochastic time-varying delay systems (STVDSs) with Markovian switching and Poisson jump. This paper is concerned with the stabilization problem for a class of STVDSs with Markovian switching and Poisson jump. The coefficients of such systems do not satisfy the conventional linear growth conditions, but are subject to high nonlinearity. The aim of this paper is to design a delay feedback controller to make an unstable highly nonlinear STVDSs with Markovian switching and Poisson jump H∞-stable and asymptotically stable. Besides, an illustrative example is provided to support the theoretical results

Coordinate Channel-Aware Page Mapping Policy and Memory Scheduling for Reducing Memory Interference Among Multimedia Applications

"© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."[EN] In a modern multicore system, memory is shared among more and more concurrently running multimedia applications. Therefore, memory contention and interference are more andmore serious, inducing system performance degradation significantly, the performance degradation of each thread differently, unfairness in resource sharing, and priority inversion, even starvation. In this paper, we propose an approach of coordinating channel-aware page mapping policy and memory scheduling (CCPS) to reduce intermultimedia application interference in a memory system. The idea is to map the data of different threads to different channels, together with memory scheduling. The key principles of the policies of page mapping and memory scheduling are: 1) the memory address space, the thread priority, and the load balance; and 2) prioritizing a low-memory request thread, a row-buffer hit access, and an older request. We evaluate the CCPS on a variety of mixed single-thread and multithread benchmarks and system configurations, and we compare them with four previously proposed state-of-the-art interference-reducing policies. Experimental results demonstrate that the CCPS improves the performance while reducing the energy consumption significantly; moreover, the CCPS incurs a much lower hardware overhead than the current existing policies.This work was supported in part by the Qing Lan Project; by the National Science Foundation of China under Grant 61003077, Grant 61100193, and Grant 61401147; and by the Zhejiang Provincial Natural Science Foundation under Grant LQ14F020011.Jia, G.; Han, G.; Li, A.; Lloret, J. (2017). Coordinate Channel-Aware Page Mapping Policy and Memory Scheduling for Reducing Memory Interference Among Multimedia Applications. IEEE Systems Journal. 11(4):2839-2851. https://doi.org/10.1109/JSYST.2015.2430522S2839285111

The horizon effect of stock return predictability and model uncertainty on portfolio choice: UK evidence

We study how stock return’s predictability and model uncertainty affect a rational buy-and-hold investor’s decision to allocate her wealth for different lengths of investment horizons in the UK market. We consider the FTSE All-Share Index as the risky asset, and the UK Treasury bill as the risk free asset in forming the investor’s portfolio. We identify the most powerful predictors of the stock return by accounting for model uncertainty. We find that though stock return predictability is weak, it can still affect the invesor’s optimal portfolio decision over different investment horizons

Consistent estimation, model selection and averaging of dynamic panel data models with fixed effect

In the context of an autoregressive panel data model with fixed effect, we examine the relationship between consistent parameter estimation and consistent model selection. Consistency in parameter estimation is achieved by using the tansformation of the fixed effect proposed by Lancaster (2002). We find that such transformation does not necessarily lead to consistent estimation of the autoregressive coefficient when the wrong set of exogenous regressors are included. To estimate our model consistently and to measure its goodness of fit, we argue for comparing different model specifications using the Bayes factor rather than the Bayesian information criterion based on the biased maximum likelihood estimates. When the model uncertainty is substantial, we recommend the use of Bayesian Model Averaging. Finally, we apply our method to study the relationship between financial development and economic growth. Our findings reveal that stock market development is positively related to economic growth, while the effect of bank development is not as significant as the classical literature suggests

Financial development, structure and growth: new data, method and results

The existing weight of evidence suggests that financial structure (the classification of a financial system as bank-based versus market-based) is irrelevant for economic growth. This contradicts the common belief that the institutional structure of a financial system matters. We re-examine this issue using a novel dataset covering 69 countries over 1989-2011 in a Bayesian framework. Our results are conformable to the belief - a market-based system is relevant - with sizable economic effects for the high-income but not for the middle-and-low-income countries. Our findings provide a counterexample to the weight of evidence. We also identify a regime shift in 2008

Socialized healthcare service recommendation using deep learning

© 2018, The Natural Computing Applications Forum. Socialized recommender system recommends reliable healthcare services for users. Ratings are predicted on the healthcare services by merging recommendations given by users who has social relations with the active users. However, existing works did not consider the influence of distrust between users. They recommend items only based on the trust relations between users. We therefore propose a novel deep learning-based socialized healthcare service recommender model, which recommends healthcare services with recommendations given by recommenders with both trust relations and distrust relations with the active users. The influences of recommenders, considering both the node information and the structure information, are merged via the deep learning model. Experimental results show that the proposed model outperforms the existing works on prediction accuracy and prediction coverage simultaneously, even for cold start users or users with very sparse trust relations. It is also computational less expensive