A computational study of shock speeds in high-performance shock tubes

This paper describes U2DE, a finite-volume code that numerically solves the Euler equations. The code was used to perform multi-dimensional simulations of the gradual opening of a primary diaphragm in a shock tube. From the simulations, the speed of the developing shock wave was recorded and compared with other estimates. The ability of U2DE to compute shock speed was confirmed by comparing numerical results with the analytic solution for an ideal shock tube. For high initial pressure ratios across the diaphragm, previous experiments have shown that the measured shock speed can exceed the shock speed predicted by one-dimensional models. The shock speeds computed with the present multi-dimensional simulation were higher than those estimated by previous one-dimensional models and, thus, were closer to the experimental measurements. This indicates that multi-dimensional flow effects were partly responsible for the relatively high shock speeds measured in the experiments.

A consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements

To translate and transfer solution data between two totally different meshes (i.e. mesh 1 and mesh 2), a consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements is presented in this paper. The proposed algorithm has the following significant advantages: (1) The use of a point-searching strategy allows a point in one mesh to be accurately related to an element (containing this point) in another mesh. Thus, to translate/transfer the solution of any particular point from mesh 2 td mesh 1, only one element in mesh 2 needs to be inversely mapped. This certainly minimizes the number of elements, to which the inverse mapping is applied. In this regard, the present algorithm is very effective and efficient. (2) Analytical solutions to the local co ordinates of any point in a four-node quadrilateral element, which are derived in a rigorous mathematical manner in the context of this paper, make it possible to carry out an inverse mapping process very effectively and efficiently. (3) The use of consistent interpolation enables the interpolated solution to be compatible with an original solution and, therefore guarantees the interpolated solution of extremely high accuracy. After the mathematical formulations of the algorithm are presented, the algorithm is tested and validated through a challenging problem. The related results from the test problem have demonstrated the generality, accuracy, effectiveness, efficiency and robustness of the proposed consistent point-searching algorithm. Copyright (C) 1999 John Wiley & Sons, Ltd.

Metal Clips Induce Folding of a Short Unstructured Peptide into an a-Helix via Turn Conformations in Water. Kinetic versus Thermodynamic Products

Short peptides corresponding to two to four a-helical turns of proteins are not thermodynamically stable helices in water. Unstructured octapeptide Ac-His1*-Ala2-Ala3-His4*-His5*-Glu6-Leu7-His8*-NH2 (1) reacts with two [Pd ((NH2)-N-15(CH2)(2) (NH2)-N-15)(NO3)(2)] in water to form a kinetically stable intermediate, [{Pden}(2)-{(1,4)(5,8)-peptide}](2), in which two 19-membered metallocyclic rings stabilize two peptide turns. Slow subsequent folding to a thermodynamically more stable two-turn a-helix drives the equilibrium to [{Pden}(2)-{(1,5)(4,8)-peptide}] (3), featuring two 22-membered rings. This transformation from unstructured peptide via turns to an a-helix suggests that metal clips might be useful probes for investigating peptide folding.

Numerical Study of Hypersonic Leeward Flow over a Blunt Nosed Delta Wing

A kinetic theory based Navier-Stokes solver has been implemented on a parallel supercomputer (Intel iPSC Touchstone Delta) to study the leeward flowfield of a blunt nosed delta wing at 30-deg incidence at hypersonic speeds (similar to the proposed HERMES aerospace plane). Computational results are presented for a series of grids for both inviscid and laminar viscous flows at Reynolds numbers of 225,000 and 2.25 million. In addition, comparisons are made between the present and two independent calculations of the some flows (by L. LeToullec and P. Guillen, and S. Menne) which were presented at the Workshop on Hypersonic Flows for Re-entry Problems, Antibes, France, 1991.

Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Using the level set method to model endogenous lava dome growth

Modeling volcanic phenomena is complicated by free-surfaces often supporting large rheological gradients. Analytical solutions and analogue models provide explanations for fundamental characteristics of lava flows. But more sophisticated models are needed, incorporating improved physics and rheology to capture realistic events. To advance our understanding of the flow dynamics of highly viscous lava in Peléean lava dome formation, axi-symmetrical Finite Element Method (FEM) models of generic endogenous dome growth have been developed. We use a novel technique, the level-set method, which tracks a moving interface, leaving the mesh unaltered. The model equations are formulated in an Eulerian framework. In this paper we test the quality of this technique in our numerical scheme by considering existing analytical and experimental models of lava dome growth which assume a constant Newtonian viscosity. We then compare our model against analytical solutions for real lava domes extruded on Soufrière, St. Vincent, W.I. in 1979 and Mount St. Helens, USA in October 1980 using an effective viscosity. The level-set method is found to be computationally light and robust enough to model the free-surface of a growing lava dome. Also, by modeling the extruded lava with a constant pressure head this naturally results in a drop in extrusion rate with increasing dome height, which can explain lava dome growth observables more appropriately than when using a fixed extrusion rate. From the modeling point of view, the level-set method will ultimately provide an opportunity to capture more of the physics while benefiting from the numerical robustness of regular grids.

Solution structure of amyloid beta-peptide(1-40) in a water-micelle environment. Is the membrane-spanning domain where we think it is?

The three-dimensional solution structure of the 40 residue amyloid beta-peptide, A beta(1-40), has been determined using NMR spectroscopy at pH 5.1, in aqueous sodium dodecyl sulfate (SDS) micelles, In this environment, which simulates to some extent a water-membrane medium, the peptide is unstructured between residues 1 and 14 which are mainly polar and likely solvated by water. However, the rest of the protein adopts an alpha-helical conformation between residues 15 and 36 with a kink or hinge at 25-27. This largely hydrophobic region is likely solvated by SDS. Based on the derived structures, evidence is provided in support of a possible new location for the transmembrane domain of A beta within the amyloid precursor protein (APP). Studies between pH 4.2 and 7.9 reveal a pH-dependent helix-coil conformational switch. At the lower pH values, where the carboxylate residues are protonated, the helix is uncharged, intact, and lipid-soluble. As the pH increases above 6.0, part of the helical region (15-24) becomes less structured, particularly near residues E22 and D23 where deprotonation appears to facilitate unwinding of the helix. This pH-dependent unfolding to a random coil conformation precedes any tendency of this peptide to aggregate to a beta-sheet as the pH increases. The structural biology described herein for A beta(1-40) suggests that (i) the C-terminal two-thirds of the peptide is an alpha-helix in membrane-like environments, (ii) deprotonation of two acidic amino acids in the helix promotes a helix-coil conformational transition that precedes aggregation, (iii) a mobile hinge exists in the helical region of A beta(1-40) and this may be relevant to its membrane-inserting properties and conformational rearrangements, and (iv) the location of the transmembrane domain of amyloid precursor proteins may be different from that accepted in the Literature. These results may provide new insight to the structural properties of amyloid beta-peptides of relevance to Alzheimer's disease.

Behavior and interactions of children in cooperative groups in lower and middle elementary grades

The study investigated the behaviors and interactions of children in structured and unstructured groups as they worked together on a 6-week social studies activity each term for 3 school terms. Two hundred and twelve children in Grade 1 and 184 children in Grade 3 participated in the study. Stratified random assignment occurred so that each gender-balanced group consisted of 1 high-, 2 medium-, and 1 low-ability student. The results show that the children in the structured groups were consistently more cooperative and they provided more elaborated and nonelaborated help than did their peers in the unstructured groups. The children in the structured groups in Grade 3 obtained higher reading and learning outcome scores than their peers in the unstructured groups.

Identification of initiation sites for T4 lysozyme folding using CD and NMR spectroscopy of peptide fragments

Using CD and 2D H-1 NMR spectroscopy, we have identified potential initiation sites for the folding of T4 lysozyme by examining the conformational preferences of peptide fragments corresponding to regions of secondary structure. CD spectropolarimetry showed most peptides were unstructured in water, but adopted partial helical conformations in TFE and SDS solution. This was also consistent with the H-1 NMR data which showed that the peptides were predominantly disordered in water, although in some cases, nascent or small populations of partially folded conformations could be detected. NOE patterns, coupling constants, and deviations from random coil Her chemical shift values complemented the CD data and confirmed that many of the peptides were helical in TFE and SDS micelles. In particular, the peptide corresponding to helix E in the native enzyme formed a well-defined helix in both TFE and SDS, indicating that helix E potentially forms an initiation site for T4 lysozyme folding. The data for the other peptides indicated that helices D, F, G, and H are dependent on tertiary interactions for their folding and/or stability. Overall, the results from this study, and those of our earlier studies, are in agreement with modeling and IID-deuterium exchange experiments, and support an hierarchical model of folding for T4 lysozyme.

Solution structures in aqueous SDS micelles of two amyloid beta peptides of A beta(1-28) mutated at the alpha-secretase cleavage site (K16E, K16F)

NMR solution structures are reported for two mutants (K16E, K16F) of the soluble amyloid beta peptide A beta(1-28). The structural effects of these mutations of a positively charged residue to anionic and hydrophobic residues at the alpha-secretase cleavage site (Lys16-Leu17) were examined in the membrane-simulating solvent aqueous SDS micelles. Overall the three-dimensional structures were similar to that for the native A beta(1-28) sequence in that they contained an unstructured N-terminus and a helical C-terminus. These structural elements are similar to those seen in the corresponding regions of full-length A beta peptides A beta(1-40) and A beta(1-42), showing that the shorter peptides are valid model systems. The K16E mutation, which might be expected to stabilize the macrodipole of the helix, slightly increased the helix length (residues 13-24) relative to the K16F mutation, which shortened the helix to between residues 16 and 24. The observed sequence-dependent control over conformation in this region provides an insight into possible conformational switching roles of mutations in the amyloid precursor protein from which A beta peptides are derived. In addition, if conformational transitions from helix to random coil to sheet precede aggregation of A beta peptides in vivo, as they do in vitro, the conformation-inducing effects of mutations at Lys16 may also influence aggregation and fibril formation. (C) 2000 Academic Press.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

ASRIS: the database

The Australian Soil Resources Information System (ASRIS) database compiles the best publicly available information available across Commonwealth, State, and Territory agencies into a national database of soil profile data, digital soil and land resources maps, and climate, terrain, and lithology datasets. These datasets are described in detail in this paper. Most datasets are thematic grids that cover the intensively used agricultural zones in Australia.