Free energy simulations: Applications to the study of liquid water,hydrophobic interactions and solvent effects on conformational stability

Free energy simulations using the Metropolis Monte Carlo method and the coupling parameter approach with umbrella sampling are described for several problems of interest in structural biochemistry: the liquid water, the hydrophobic interaction of alkyl and phenyl groups in water, and solvent effects on the conformational stability of the alanine dipeptide and the dimethyl phosphate anion in water. Proximity analysis of the results is employed to identify stabilizing factors. Implications of the result with respect to the structural chemistry of proteins and nucleic acids is considered.     

Reliability modelling incorporating load share and frailty

The stochastic behaviour of lifetimes of a two component system is often primarily influenced by the system structure and by the covariates shared by the components. Any meaningful attempt to model the lifetimes must take into consideration the factors affecting their stochastic behaviour. In particular, for a load share system, we describe a reliability model incorporating both the load share dependence and the effect of observed and unobserved covariates. The model includes a bivariate Weibull to characterize load share, a positive stable distribution to describe frailty, and also incorporates effects of observed covariates. We investigate various interesting reliability properties of this model using cross ratio functions and conditional survivor functions. We implement maximum likelihood estimation of the model parameters and discuss model adequacy and selection. We illustrate our approach using a simulation study. For a real data situation, we demonstrate the superiority of the proposed model that incorporates both load share and frailty effects over competing models that incorporate just one of these effects. An attractive and computationally simple cross‐validation technique is introduced to reconfirm the claim. We conclude with a summary and discussion.     

Additive Positive Stable Frailty Models

In this article, we describe an additive stable frailty model for multivariate times to events data using a flexible baseline hazard, and assuming that the frailty component for each individual is described by additive functions of independent positive stable random variables with possibly different stability indices. Dependence properties of this frailty model are investigated. To carry out inference, the likelihood function is derived by replacing high-dimensional integration by Monte Carlo simulation. Markov chain Monte Carlo algorithms enable estimation and model checking in the Bayesian framework.      

Clustering Nonlinear,Nonstationary Time Series Using BSLEX

Accurate clustering of time series is a challenging problem for data arising from areas such as financial markets, biomedical studies, and environmental sciences, especially when some, or all, of the series exhibit nonlinearity and nonstationarity. When a subset of the series exhibits nonlinear characteristics, frequency domain clustering methods based on higher-order spectral properties, such as the bispectra or trispectra are useful. While these methods address nonlinearity, they rely on the assumption of series stationarity. We propose the Bispectral Smooth Localized Complex EXponential (BSLEX) approach for clustering nonlinear and nonstationary time series. BSLEX is an extension of the SLEX approach for linear, nonstationary series, and overcomes the challenges of both nonlinearity and nonstationarity through smooth partitions of the nonstationary time series into stationary subsets in a dyadic fashion. The performance of the BSLEX approach is illustrated via simulation where several nonstationary or nonlinear time series are clustered, as well as via accurate clustering of the records of 16 seismic events, eight of which are earthquakes and eight are explosions. We illustrate the utility of the approach by clustering S&P 100 financial returns.     

Synthesis and biological evaluation of some novel-3-(5-substituted benzimidazol-2-yl)-5-arylisoxazolines

<正>The synthesis of a new series of 3-(5-substituted benzimidazol-2-yl)-5-arylisoxazolines(6a-h) was achieved in excellent yields by the condensation of 1-(1H-benzimidazol-2-yl)-3-(substituted phenyl)prop-2-en-1-ones(5a-h) with hydroxylamine at room temperature.These 1-(1H-benzimidazol-2-yl)-3-(substituted phenyl)prop-2-en-1-ones(5a-h) were obtained by the condensation of 2-acetyl benzimidazoles(4a-d) with different aromatic aldehydes,which in turn were obtained by the oxidation of 2-(α-hydroxy) ethyl benzimidazoles(3a-d) prepared by the reaction of o-phenylenediamines(1a-d) withα-hydroxy propionic acid 2. The synthesized compounds were characterized by their IR,~1H NMR and MS analyses.These compounds were screened for their antibacterial and antifungal activity by standard methods and found some of them active.     

Core–shell nanophosphor with enhanced NIR–visible upconversion as spectrum modifier for enhancement of solar cell efficiency

A distinct enhancement of upconversion luminescence from core to core/shell (C/S) structure under low flux near infrared (NIR) excitation at 976 nm has been achieved in lanthanide (Er³⁺, Yb³⁺)-doped NaYF₄ core with undoped NaYF₄ shell nanoparticles (NP). A green chemistry approach has been taken to synthesize monodisperse monophasic C/S NP with the core (~20 nm) and shell (~5 nm) crystallizing into cubic phase. Hydrophobic C/S NP have been further made hydrophilic by coating a transparent SHMP layer without affecting luminescence. C/S (NaYF₄: Er, Yb/NaYF₄) NP integrated dye-sensitized solar cell indicated 11.9% enhancement in overall conversion efficiency under AM 1.5 conditions, due to NIR–visible spectrum modification by fluorescent NPs. The results indicate great potential of such upconverting C/S nanophosphor in solar cell applications.     

NHPP models for categorized software defects

We develop NHPP models to characterize categorized event data, with application to modelling the discovery process for categorized software defects. Conditioning on the total number of defects, multivariate models are proposed for modelling the defects by type. A latent vector autoregressive structure is used to characterize dependencies among the different types. We show how Bayesian inference can be achieved via MCMC procedures, with a posterior prediction‐based L‐measure used for model selection. The results are illustrated for defects of different types found during the System Test phase of a large operating system software development project. Copyright © 2005 John Wiley & Sons, Ltd.     

Palladium catalysed bis- and tris-cyclisations furnishing fused cyclopropyl carbo/heterocycles

Catalytic bis- and tris-cyclisation of a series of acyclic carbo- and heterocyclic precursors results in formation of two or three rings, two or three C-C bonds and two asymmetric tetrasubstituted C-centres regio- and stereoselectively in excellent yield.