Gravitational Capture of Cosmic Strings by a Black Hole

The gravitational interaction of an infinitely long cosmic string with a Schwarzschild black hole is studied. We consider a straight string that is initially at a great distance and moving at some initial velocity v (0 < v < c) towards the black hole. The equations of motion of the string are solved numerically to obtain the dependence of the capture impact parameter on the initial velocity.Comment: 15 pages, 2 figures, submitted to Phys Rev

Effect of reinforcing submicron SiC particles on the wear of electrolytic NiP coatings Part 2: Bi-directional sliding

As-plated and heat-treated electrodeposited NiP and composite NiP-SiC coatings were investigated in bi-directional ball-on-disc sliding tests. All tests were performed under gross slip conditions. Heat treatment decreases the wear volume loss during fretting in ambient air for all coatings investigated. Heat-treated NiP coating has a lower wear volume loss compared to composite NiP-SiC coatings for all sliding tests. The wear rate at the bi-directional sliding test was found to be lower relative to the wear rate at uni-directional sliding test

Effect of reinforcing submicron SiC particles on the wear of electrolytic NiP coatings Part 1. Uni-directional sliding

As-plated and annealed NiP coatings and composite NiP-SiC coatings were investigated in uni-directional ball-on-disc sliding tests. Abrasive wear was noticed in the case of composite NiP coatings containing submicron SiC particles, whereas in NiP coatings oxidational wear was active. The addition of submicron SiC particles not only increases the hardness of these electrolytic coatings but also hinders the formation of an oxide film in the sliding wear track. As a consequence, the wear loss on as-plated NiP coatings is not markedly reduced by the addition of SiC particles. On the contrary, a heat treatment at 420 °C for 1 h decreases the wear loss on both pure NiP and composite NiP-SiC coatings. During that heat treatment, Ni3P precipitates are formed in the NiP matrix and owing to this fact, the hardness of both pure NiP and composite NiP-SiC coatings increases. However, the heat treatment of composite NiP-SiC coatings induces the sensitivity for crack formation in the NiP matrix around these SiC particles. As a result, the pull out of SiC particles in the wear track occurs easily during sliding, and the wear loss of composite NiP-SiC coatings remains above the wear loss on NiP coatings

Efficient learning in ABC algorithms

Approximate Bayesian Computation has been successfully used in population genetics to bypass the calculation of the likelihood. These methods provide accurate estimates of the posterior distribution by comparing the observed dataset to a sample of datasets simulated from the model. Although parallelization is easily achieved, computation times for ensuring a suitable approximation quality of the posterior distribution are still high. To alleviate the computational burden, we propose an adaptive, sequential algorithm that runs faster than other ABC algorithms but maintains accuracy of the approximation. This proposal relies on the sequential Monte Carlo sampler of Del Moral et al. (2012) but is calibrated to reduce the number of simulations from the model. The paper concludes with numerical experiments on a toy example and on a population genetic study of Apis mellifera, where our algorithm was shown to be faster than traditional ABC schemes

(Weak) G_2 Holonomy from Self-duality, Flux and Supersymmetry

The aim of this paper is two-fold. First, we provide a simple and pedagogical discussion of how compactifications of M-theory or supergravity preserving some four-dimensional supersymmetry naturally lead to reduced holonomy or its generalization, reduced weak holonomy. We relate the existence of a (conformal) Killing spinor to the existence of certain closed and co-closed p-forms, and to the metric being Ricci flat or Einstein. Then, for seven-dimensional manifolds, we show that octonionic self-duality conditions on the spin connection are equivalent to G_2 holonomy and certain generalized self-duality conditions to weak G_2 holonomy. The latter lift to self-duality conditions for cohomogeneity-one spin(7) metrics. To illustrate the power of this approach, we present several examples where the self-duality condition largely simplifies the derivation of a G_2 or weak G_2 metric.Comment: references added, 25 pages, no figures, Late

Financial Liberalization: Commercial Bank's Blessing or Curse?

The purpose of the paper is to evaluate and measure the effect of financial liberalization (FL) on bank risk exposure. We pursue these questions by assessing the changes in market-based asset values and risk exposure measures for commercial banks (CB) before and during a FL program. We do this for a sample of three countries: Malaysia, Taiwan and Thailand. We use a model based on the options pricing theory. We obtain estimates of the first and second moment of bank returns using an asset pricing model in which these two moments are a linear projection of a set of conditioning variables. This model was estimated using a GMM statistical procedure. Then we perform regressions explaining the evolution of bank risk measure around the FL event. The analysis and statistical test indicate that risk exposure of banks increases following a FL program, and this as a result of macroeconomic policy as well as changes in management controlled variables. This is so even for banks operating in countries that have undertaken very cautious FL processes such as Thailand and Malaysia. The results tend to support the proposition that moral hazard and bank risk taking may increase following FL. The results also suggest that banking crisis that often have followed FL may be more due to the behavior of banks managers than previously reported in the FL literature.

Approximate Bayesian Computational methods

Also known as likelihood-free methods, approximate Bayesian computational (ABC) methods have appeared in the past ten years as the most satisfactory approach to untractable likelihood problems, first in genetics then in a broader spectrum of applications. However, these methods suffer to some degree from calibration difficulties that make them rather volatile in their implementation and thus render them suspicious to the users of more traditional Monte Carlo methods. In this survey, we study the various improvements and extensions made to the original ABC algorithm over the recent years.Comment: 7 figure