Exact N-wave solutions of generalized Burgers equations

Exact N-wave solutions for the generalized Burgers equation u(t) + u(n)u(x) + (j/2t + alpha) u + (beta + gamma/x) u(n+1) = delta/2u(xx),where j, alpha, beta, and gamma are nonnegative constants and n is a positive integer, are obtained. These solutions are asymptotic to the (linear) old-age solution for large time and extend the validity of the latter so as to cover the entire time regime starting where the originally sharp shock has become sufficiently thick and the viscous effects are felt in the entire N wave.

A New Tetrahydrofurannulation Via Tandem Radical Cyclization Reaction-Reductive Deoxygenation Sequence

Treatment of bromoketals 2, derived from allyl alcohols 1, with tributyltin chloride, sodium cyanoborohydride and AIBN furnishes the tetrahydrofurannulated products 3 via a 5-exo-trig radical cyclisation reaction followed by reductive cleavage of ketal 4.

Homology between jacalin and artocarpin from jackfruit (Artocarpus integrifolia) seeds. Partial sequence and preliminary crystallographic studies of artocarpin

Jacalin and artocarpin, the two lectins from jackfruit (Artocarpus integrifolia) seeds, have different physicochemical properties and carbohydrate-binding specificities. However, comparison of the partial amino-acid sequence of artocarpin with the known sequence of jacalin indicates close to 50% sequence identity. Artocarpin crystallizes in two forms, both monoclinic P2(1), with one and two tetramic molecules, respectively, in the asymmetric units of form I (a = 69.9, b = 73.7, c = 60.6 Angstrom and beta = 95.1 degrees) and form II (a = 87.6, b = 72.2, c = 92.6 Angstrom and beta = 101.1 degrees). Both the crystal structures have been solved by the molecular replacement method using the known structure of jacalin as the search model and ope of them partially refined, confirming that the two lectins are indeed homologous.

A Quasi-Newton Adaptive Algorithm for Generalized Symmetric Eigenvalue Problem

In this paper, we first recast the generalized symmetric eigenvalue problem, where the underlying matrix pencil consists of symmetric positive definite matrices, into an unconstrained minimization problem by constructing an appropriate cost function, We then extend it to the case of multiple eigenvectors using an inflation technique, Based on this asymptotic formulation, we derive a quasi-Newton-based adaptive algorithm for estimating the required generalized eigenvectors in the data case. The resulting algorithm is modular and parallel, and it is globally convergent with probability one, We also analyze the effect of inexact inflation on the convergence of this algorithm and that of inexact knowledge of one of the matrices (in the pencil) on the resulting eigenstructure. Simulation results demonstrate that the performance of this algorithm is almost identical to that of the rank-one updating algorithm of Karasalo. Further, the performance of the proposed algorithm has been found to remain stable even over 1 million updates without suffering from any error accumulation problems.

Solution of a System of Generalized Abel Integral Equations Using Fractional Calculus

A method is presented for obtaining useful closed form solution of a system of generalized Abel integral equations by using the ideas of fractional integral operators and their applications. This system appears in solving certain mixed boundary value problems arising in the classical theory of elasticity.

Structural and Sequence Characteristics of Long alpha Helices in Globular Proteins

Elucidation of the detailed structural features and sequence requirements for iv helices of various lengths could be very important in understanding secondary structure formation in proteins and, hence. in the protein folding mechanism. An algorithm to characterize the geometry of an alpha helix from its C-alpha coordinates has been developed and used to analyze the structures of long cu helices (number of residues greater than or equal to 25) found in globular proteins, the crystal structure coordinates of which are available from the Brookhaven Protein Data Bank, Ail long a helices can be unambiguously characterized as belonging to one of three classes: linear, curved, or kinked, with a majority being curved. Analysis of the sequences of these helices reveals that the long alpha helices have unique sequence characteristics that distinguish them from the short alpha helices in globular proteins, The distribution and statistical propensities of individual amino acids to occur in long alpha heices are different from those found in short alpha helices, with amino acids having longer side chains and/or having a greater number of functional groups occurring more frequently in these helices, The sequences of the long alpha helices can be correlated with their gross structural features, i.e., whether they are curved, linear, or kinked, and in case of the curved helices, with their curvature.

Similarities in the Genomic Sequence and Coat Protein-Structure of Plant Viruses

The genomic sequences of several RNA plant viruses including cucumber mosaic virus, brome mosaic virus, alfalfa mosaic virus and tobacco mosaic virus have become available recently. The former two viruses are icosahedral while the latter two are bullet and rod shaped, respectively in particle morphology. The non-structural 3a proteins of cucumber mosaic virus and brome mosaic virus have an amino acid sequence homology of 35% and hence are evolutionarily related. In contrast, the coat proteins exhibit little homology, although the circular dichroism spectrum of these viruses are similar. The non-coding regions of the genome also exhibit variable but extensive homology. Comparison of the brome mosaic virus and alfalfa mosaic virus sequences reveals that they are probably related although with a much larger evolutionary distance. The polypeptide folds of the coat protein of three biologically distinct isometric plant viruses, tomato bushy stunt virus, southern bean mosaic virus and satellite tobacco necrosis virus have been shown to display a striking resemblance. All of them consist of a topologically similar 8-standard β-barrel. The implications of these studies to the understanding of the evolution of plant viruses will be discussed.

In vivo positive contrast IRON sequence and quantitative T2* measurement confirms inflammatory burden in a patient with asymptomatic carotid atheroma after USPIO-enhanced MR Imaging

The authors report an in vivo human examination of carotid atheroma by using the inversion-recovery ON resonance (IRON) sequence, which is able to produce positive contrast after the infusion of an ultrasmall super paramagnetic iron oxide (USPIO) contrast medium. This technique provides a method of potentially identifying inflammatory burden within carotid atheroma. This may be particularly useful in patients who currently do not meet criteria for intervention (ie, moderate symptomatic stenosis or <70% asymptomatic stenosis) to further risk-stratify this important patient cohort. A 63-year-old man was imaged at 1.5 T before and 36 hours after USPIO infusion by using the IRON sequence. Regions of interest showing profound signal loss at T2*-weighted imaging corresponded well with regions of positive contrast at IRON imaging after the administration of USPIO. These regions also showed a profound decrease in T2* measurements after USPIO infusion, whereas surrounding tissue did not. It has been shown that such strong signal loss on T2*-weighted images after USPIO infusion is indicative of USPIO uptake.

Analysis of word embeddings and sequence features for clinical information extraction

This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

Working covariance model selection for generalized estimating equations

We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice.

Discussion of “Generalized estimating equations: Notes on the choice of the working correlation matrix”

Objective To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens "Generalized Estimating Equations. Notes on the Choice of the Working Correlation Matrix". Methods Inviting an international group of experts to comment on this paper. Results Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data Applied statisticians; commented on practical aspects in data analysis. Conclusions In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations, (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data This particularly applies to the situation when data are missing at random.

Working-correlation-structure identification in generalized estimating equations

Selecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well-known criterion of QIC for selecting a working correlation Structure. and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads LIS to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study.

Generalized Query-By-Rule: a heterogeneous database query language

This paper describes the design and implementation of a high-level query language called Generalized Query-By-Rule (GQBR) which supports retrieval, insertion, deletion and update operations. This language, based on the formalism of database logic, enables the users to access each database in a distributed heterogeneous environment, without having to learn all the different data manipulation languages. The compiler has been implemented on a DEC 1090 system in Pascal.

A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery

The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.

Depositional model for the early Miocene turbidite sequence, the Whakataki Formation, NZ

This research examined the influence of tectonic activity on submarine sedimentation processes, through a deposit-based analysis of turbidites in outcrop. A comprehensive field study of the Miocene Whakataki Formation yielded significant data that was analysed using methods of process-sedimentology, stratigraphy, and ichnology. Signatures of the tectonically active depositional environment were identifiable at very high resolution, from grain composition and texture to trace-fossil assemblages, as well as on a broader-scale in stratigraphic stacking patterns and structural deformation. From these results and environmental interpretations, an original facies characterisation and conceptual depositional model have been established.