Optimized Monte Carlo Method for glasses

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other optimized Monte Carlo methods. Using the algorithm, we obtain finite size effects in the specific heat. This effect points to the existence of a large correlation length measurable in equal time correlation functions.Comment: Proceedings of "X International workshop on Disordered Systems" held in Molveno (Italy), March 200

Finite size effects in the specific heat of glass-formers

We report clear finite size effects in the specific heat and in the relaxation times of a model glass former at temperatures considerably smaller than the Mode Coupling transition. A crucial ingredient to reach this result is a new Monte Carlo algorithm which allows us to reduce the relaxation time by two order of magnitudes. These effects signal the existence of a large correlation length in static quantities.Comment: Proceeding of "3rd International Workshop on Complex Systems". Sendai (Japan). To appear on AIP Conference serie

On the critical behavior of the specific heat in glass-formers

We show numeric evidence that, at low enough temperatures, the potential energy density of a glass-forming liquid fluctuates over length scales much larger than the interaction range. We focus on the behavior of translationally invariant quantities. The growing correlation length is unveiled by studying the Finite Size effects. In the thermodynamic limit, the specific heat and the relaxation time diverge as a power law. Both features point towards the existence of a critical point in the metastable supercooled liquid phase.Comment: Version to be published in Phys. Rev.

Toxicology of Biomedical Polymers

This paper deals with the various types of polymers, used in the fabrication of medical devices, their diversity of applications and toxic hazards which may arise out of their application. The potential toxicity of monomers and the various additives used in the manufacture of biomedical polymers have been discussed along with hazards which may arise out of processing of devices such as sterilization. The importance of quality control and stringent toxicity evaluation methods have been emphasised since in our country, at present, there are no regulations covering the manufacturing and marketing of medical devices. Finally the question of the general and subtle long term systemic toxicity of biomedical polymers have been brought to attention with the suggestion that this question needs to be resolved permanently by appropriate studies

Optimal detection of changepoints with a linear computational cost

We consider the problem of detecting multiple changepoints in large data sets. Our focus is on applications where the number of changepoints will increase as we collect more data: for example in genetics as we analyse larger regions of the genome, or in finance as we observe time-series over longer periods. We consider the common approach of detecting changepoints through minimising a cost function over possible numbers and locations of changepoints. This includes several established procedures for detecting changing points, such as penalised likelihood and minimum description length. We introduce a new method for finding the minimum of such cost functions and hence the optimal number and location of changepoints that has a computational cost which, under mild conditions, is linear in the number of observations. This compares favourably with existing methods for the same problem whose computational cost can be quadratic or even cubic. In simulation studies we show that our new method can be orders of magnitude faster than these alternative exact methods. We also compare with the Binary Segmentation algorithm for identifying changepoints, showing that the exactness of our approach can lead to substantial improvements in the accuracy of the inferred segmentation of the data.Comment: 25 pages, 4 figures, To appear in Journal of the American Statistical Associatio