Investigation of the Interior of Colored Black Holes and the Extendability of Solutions of the Einstein-Yang/Mills Equations

We prove that any asymptotically flat solution to the spherically symmetric SU(2) Einstein-Yang/Mills equations is globally defined. This result applies in particular to the interior of colored black holes.Comment: Latex, 8 gif figure

Social Requirements for Virtual Organization Breeding Environments

The creation of Virtual Breeding Environments (VBE) is a topic which has received too little attention: in most former works, the existence of the VBE is either assumed, or is considered as the result of the voluntary, participatory gathering of a set of candidate companies. In this paper, the creation of a VBE by a third authority is considered: chambers of commerce, as organizations whose goal is to promote and facilitate business interests and activity in the community, could be good candidates for exogenous VBE creators. During VBE planning, there is a need to specify social requirements for the VBE. In this paper, SNA metrics are proposed as a way for a VBE planner to express social requirements for a VBE to be created. Additionally, a set of social requirements for VO planners, VO brokers, and VBE members are proposed.Comment: 10 pages, 2 figure

Reissner-Nordstrom-like solutions of the SU(2) Einstein-Yang/Mills (EYM) equations

In this paper we study a new type of solution of the spherically symmetric, Einstein-Yang/Mills (EYM) equations with SU(2) gauge group. These solutions are well-behaved in the far-field, and have a Reissner-Nordstrom type essential singularity at the origin. These solutions display some novel features which are not present in particle-like, or black-hole solutions. Any spherically symmetric solution to the EYM equations, defined in the far-field, is either a particle-like solution, a black-hole solution, or one of these RNL solutions.Comment: 5 pages, latex, no figures, Submitted to Comm. Math. Phys. January 15, 199

Strong absorption and selective thermal emission from a mid-infrared metamaterial

We demonstrate thin-film metamaterials with resonances in the mid-infrared wavelength range. Our structures are numerically modeled and experimentally characterized by reflection and angularly-resolved thermal emission spectroscopy. We demonstrate strong and controllable absorption resonances across the mid-infrared wavelength range. In addition, the polarized thermal emission from these samples is shown to be highly selective and largely independent of emission angles from normal to 45 degrees. Experimental results are compared to numerical models with excellent agreement. Such structures hold promise for large-area, low-cost metamaterial coatings for control of gray- or black-body thermal signatures, as well as for possible mid-IR sensing applications.Comment: The following article has been submitted to Appl. Phys. Lett. After it is published, it will be found at http://apl.aip.org/. 14 pages including 4 figure page

The Pharmacology of Newer Diuretics

There are now a number of different classes of diuretics with different pharmacologic effects. Several considerations dictate the choice of diuretic: 1. The responsiveness of the patient is of prime importance. If the patient is not known to be resistant to diuretic therapy, thiazides should be tried first. 2. The danger of alterations of volume and of electrolytes in the specific patient must be considered. Patients receiving digitalis will be subjected to much greater danger by the induction of hypokalemia than patients not receiving cardiac glycosides. 3. The pharmacologic effects of the specific diuretics must be understood for now the physician has available agents of differing potency, efficacy, and especially differing mechanisms of action

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives

Nonparametric two sample testing deals with the question of consistently deciding if two distributions are different, given samples from both, without making any parametric assumptions about the form of the distributions. The current literature is split into two kinds of tests - those which are consistent without any assumptions about how the distributions may differ (\textit{general} alternatives), and those which are designed to specifically test easier alternatives, like a difference in means (\textit{mean-shift} alternatives). The main contribution of this paper is to explicitly characterize the power of a popular nonparametric two sample test, designed for general alternatives, under a mean-shift alternative in the high-dimensional setting. Specifically, we explicitly derive the power of the linear-time Maximum Mean Discrepancy statistic using the Gaussian kernel, where the dimension and sample size can both tend to infinity at any rate, and the two distributions differ in their means. As a corollary, we find that if the signal-to-noise ratio is held constant, then the test's power goes to one if the number of samples increases faster than the dimension increases. This is the first explicit power derivation for a general nonparametric test in the high-dimensional setting, and also the first analysis of how tests designed for general alternatives perform when faced with easier ones.Comment: 25 pages, 5 figure

On the Decreasing Power of Kernel and Distance based Nonparametric Hypothesis Tests in High Dimensions

This paper is about two related decision theoretic problems, nonparametric two-sample testing and independence testing. There is a belief that two recently proposed solutions, based on kernels and distances between pairs of points, behave well in high-dimensional settings. We identify different sources of misconception that give rise to the above belief. Specifically, we differentiate the hardness of estimation of test statistics from the hardness of testing whether these statistics are zero or not, and explicitly discuss a notion of "fair" alternative hypotheses for these problems as dimension increases. We then demonstrate that the power of these tests actually drops polynomially with increasing dimension against fair alternatives. We end with some theoretical insights and shed light on the \textit{median heuristic} for kernel bandwidth selection. Our work advances the current understanding of the power of modern nonparametric hypothesis tests in high dimensions.Comment: 19 pages, 9 figures, published in AAAI-15: The 29th AAAI Conference on Artificial Intelligence (with author order reversed from ArXiv