Weak-field approximation of effective gravitational theory with local Galilean invariance

We examine the weak-field approximation of locally Galilean invariant gravitational theories with general covariance in a (4+1)-dimensional Galilean framework. The additional degrees of freedom allow us to obtain Poisson, diffusion, and Schrödinger equations for the fluctuation field. An advantage of this approach over the usual (3+1)-dimensional General Relativity is that it allows us to choose an ansatz for the fluctuation field that can accommodate the field equations of the Lagrangian approach to MOdified Newtonian Dynamics (MOND) known as AQUAdratic Lagrangian (AQUAL). We investigate a wave solution for the Schrödinger equations.     

浅议本地电话的普遍服务(下)

通过对本地电话特点的分析和国外普遍服务的情况介绍．对我国本地电话的普遍服务性质及普遍服务工作的改进进行了探讨。     

Constraints on the IR behaviour of gluon and ghost propagator from Ward-Slavnov-Taylor identities

We consider the constraints of the Slavnov-Taylor identity of the IR behaviour of gluon and ghost propagators and their compatibility with solutions of the ghost Dyson-Schwinger equation and with the lattice picture.     

GJS:一种基于反射机制的通用Java服务器

本文研究了一个通用的Java服务器GJS的设计和实现，GJS通过分析了一般基于Socket的客户机服务器工作方式，提供了一个开发的框架，通过这个框架，开发人员可以把开发工作集中于协议本身，从而避免了重复性的工作并降低了维护成本。同时，GJS利用JAVA提供的反射机制，使得GJS可以动态加载新的服务而无须重新编译，在不对其它服务造成影响的同时及时加载新的服务，使得开发成本和维护成本都大大降低。GJS还提供了一个可视化的用户操作界面，使得服务的管理工作非常简单和直观。     

A general law of precise asymptotics for the counting process of record times

This paper achieves a general law of precise asymptotics for the counting process of record times of i.i.d. absolutely continuous random variables. It can describe the relations among the boundary function, weighted function, convergence rate and limit value in studies of complete convergence. This extends and generalizes the corresponding results in Stochastic Process. Appl. 101 (2002) 233-239.     

A well-conditioned estimator for large-dimensional covariance matrices

Many applied problems require a covariance matrix estimator that is not only invertible, but also well-conditioned (that is, inverting it does not amplify estimation error). For large-dimensional covariance matrices, the usual estimator—the sample covariance matrix—is typically not well-conditioned and may not even be invertible. This paper introduces an estimator that is both well-conditioned and more accurate than the sample covariance matrix asymptotically. This estimator is distribution-free and has a simple explicit formula that is easy to compute and interpret. It is the asymptotically optimal convex linear combination of the sample covariance matrix with the identity matrix. Optimality is meant with respect to a quadratic loss function, asymptotically as the number of observations and the number of variables go to infinity together. Extensive Monte Carlo confirm that the asymptotic results tend to hold well in finite sample.     

SCADA系统在供水系统中的应用

本文结合鞍山市供水工程SCADA系统设计的实例,详细介绍了SCADA系统的配置和功能,该供水项目已运行近两年。取得了很大的经济效益和社会效益,积累了丰富的操作使用经验,对今后设计新的给水项目具有很大的指导意义。     

Effects of spatial smoothing on inter-subject correlation based analysis of FMRI

This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, with the traditional general linear model (GLM) based analysis, the effects of smoothing have been studied extensively.     

Space–time transformation acoustics

A recently proposed analogue transformation method has allowed the extension of transformation acoustics to general space–time transformations. We analyze here in detail the differences between this new analogue transformation acoustics (ATA) method and the standard one (STA). We show explicitly that STA is not suitable for transformations that mix space and time. ATA takes as starting point the acoustic equation for the velocity potential, instead of that for the pressure as in STA. This velocity-potential equation by itself already allows for some transformations mixing space and time, but not all of them. We explicitly obtain the entire set of transformations that leave its form invariant. It is for the rest of transformations that ATA shows its true potential, allowing for building a transformation acoustics method that enables the full range of space–time transformations. We provide an example of an important transformation which cannot be achieved with STA. Using this transformation, we design and simulate an acoustic frequency converter via the ATA approach. Furthermore, in those cases in which one can apply both the STA and ATA approaches, we study the different transformational properties of the corresponding physical quantities.     

Inter-model comparison of CFD and neural network analysis of natural convection heat transfer in a partitioned enclosure

CFD analysis of heat and mass flow due to natural convection in partitioned enclosures has recently been the focus of many CFD researchers. In some cases, it was reported in the literature that different CFD solutions (due to different numerical stability characteristics) were obtained for different mesh quality, time step, and discretization order. The objective of this paper is to investigate the feasibility of using neural networks (NNs) as a means lending support to the authenticity of steady-state CFD solutions for such ill-posed problems through inter-model comparisons. Attention is focused on using NNs trained on a database generated by numerically-stable CFD analysis to predict flow variables for the aforementioned ill-posed cases, thereby giving confidence in steady-state CFD results for these cases. Three types of NNs were evaluated and parametric studies were performed to optimize network designs for best predictions of the flow variables.