Studying Aggregate in Lysozyme Solution by Atomic Force Microscope

The aggregates in lysozyme solution with different NaCl concentration were investigated by Atomic Force Microscope (AFM). The AFM images show that there exist lysozyme monomers, n-mers and clusters in lysozyme solution when the conditions are not suitable for crystal growth. In favorable conditions for crystal growth, the lysozyme clusters disappear and almost only monomers exist in solution.

Tractable nonparametric bayesian inference in poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finitedimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets. Copyright 2009.

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finite-dimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets.

Bayesian learning of noisy Markov decision processes

This work addresses the problem of estimating the optimal value function in a Markov Decision Process from observed state-action pairs. We adopt a Bayesian approach to inference, which allows both the model to be estimated and predictions about actions to be made in a unified framework, providing a principled approach to mimicry of a controller on the basis of observed data. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from theposterior distribution over the optimal value function. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.

Progress In Modeling Of Fluid Flows In Crystal Growth Processes

Modeling of fluid flows in crystal growth processes has become an important research area in theoretical and applied mechanics. Most crystal growth processes involve fluid flows, such as flows in the melt, solution or vapor. Theoretical modeling has played an important role in developing technologies used for growing semiconductor crystals for high performance electronic and optoelectronic devices. The application of devices requires large diameter crystals with a high degree of crystallographic perfection, low defect density and uniform dopant distribution. In this article, the flow models developed in modeling of the crystal growth processes such as Czochralski, ammonothermal and physical vapor transport methods are reviewed. In the Czochralski growth modeling, the flow models for thermocapillary flow, turbulent flow and MHD flow have been developed. In the ammonothermal growth modeling, the buoyancy and porous media flow models have been developed based on a single-domain and continuum approach for the composite fluid-porous layer systems. In the physical vapor transport growth modeling, the Stefan flow model has been proposed based on the flow-kinetics theory for the vapor growth. In addition, perspectives for future studies on crystal growth modeling are proposed. (c) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

Concentrated-Mass Cantilever Enhances Multiple Harmonics In Tapping-Mode Atomic Force Microscopy

The natural frequencies of a cantilever probe can be tuned with an attached concentrated mass to coincide with the higher harmonics generated in a tapping-mode atomic force microscopy by the nonlinear tip-sample interaction force. We provide a comprehensive map to guide the choice of the mass and the position of the attached particle in order to significantly enhance the higher harmonic signals containing information on the material properties. The first three eigenmodes can be simultaneously excited with only one carefully positioned particle of specific mass to enhance multiple harmonics. Accessing the interaction force qualitatively based on the high-sensitive harmonic signals combines the real-time material characterization with the imaging capability. (C) 2008 American Institute of Physics.

Energy Dissipation In Fracture Of Bulk Metallic Glasses Via Inherent Competition Between Local Softening And Quasi-Cleavage

Compression, tension and high-velocity plate impact experiments were performed on a typical tough Zr41.2Ti13.8Cu10Ni12.5Be22.5 (Vit 1) bulk metallic glass (BMG) over a wide range of strain rates from similar to 10(-4) to 10(6) s(-1). Surprisingly, fine dimples and periodic corrugations on a nanoscale were also observed on dynamic mode I fracture surfaces of this tough Vit 1. Taking a broad overview of the fracture patterning of specimens, we proposed a criterion to assess whether the fracture of BMGs is essentially brittle or plastic. If the curvature radius of the crack tip is greater than the critical wavelength of meniscus instability [F. Spaepen, Acta Metall. 23 615 (1975); A.S. Argon and M. Salama, Mater. Sci. Eng. 23 219 (1976)], microscale vein patterns and nanoscale dimples appear on crack surfaces. However, in the opposite case, the local quasi-cleavage/separation through local atomic clusters with local softening in the background ahead of the crack tip dominates, producing nanoscale periodic corrugations. At the atomic cluster level, energy dissipation in fracture of BMGs is, therefore, determined by two competing elementary processes, viz. conventional shear transformation zones (STZs) and envisioned tension transformation zones (TTZs) ahead of the crack tip. Finally, the mechanism for the formation of nanoscale periodic corrugation is quantitatively discussed by applying the present energy dissipation mechanism.