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This paper enhances the voxel-to-voxel radiance shooting, propagation, and scattering algorithm of Max [20]. It reduces the memory requirements by storing the radiance only on the occupied cells of a sparse voxel octree and by sampling only 24 propagation direction bins instead of 96 or more. It gives a modification of the propagation algorithm to compensate for the larger solid angle of the direction bins and allows for position-dependent fully anisotropic scattering. For a volume of $$n^3$$ n 3 voxels, the computation time is $$O(n^3(\mathrm {log}\,n)^{3/2})$$ O ( n 3 ( log n ) 3 / 2 ) .

This dissertation explores the possibility that the phonological grammar manipulates phone representations based on learned distributional class memberships rather than those based on substantive linguistic features. In doing so, this work makes three primary contributions. First, I propose three novel algorithms for learning a phonological class system from the distributional statistics of a language, all of which are based on partitioning graph representations of phone distributions. Second, I propose a new method for fitting Maximum Entropy phonotactic grammars, MaxEntGrams, which offers theoretical complexity improvements over the widely-adopted approach taken by Hayes and Wilson [2008]. Third, I present a series of computational experiments which fit MaxEntGram models built on top of learned phonological class systems to English, Polish, and Korean and evaluate the extent to which the resulting grammars predict existing experimental results on sonority projection. The results of these computational experiments suggest that the models with learned class systems predict human-like sonority projection behavior as well as the standard approach using traditional linguistic feature specification in both English and Korean, and better than the traditional approach in Polish. This success is attributed, in part, to the fact that the combination of phonological class learning and MaxEntGrams eliminates the need for constraint-induction heuristics. All together, none of the tested cases provide evidence that phonotactic models built using traditional, substantive linguistic feature systems predict human behavior better than models that make use of distributionally-defined phone representations.

Building a highly accurate model for photovoltaic (PV) cells based on actual sampled data is essential for the simulation, optimization, evaluation, and control of photovoltaic power generation systems. But finding globally optimal model parameters, which give the best fit to experimental data, is a great challenge. In this paper, a new optimization algorithm, called the micro-charge field effect P systems optimization algorithm (MFE-POA) is proposed. Though the analysis of the interaction among ionic substances inside a living cell membrane and considering the algorithm’s dual needs of exploration and convergence accuracy, combined with the law of interaction between charges, we designed a novel micro-charge interaction rule based on distance, force characteristics, spatial location, and percentage of search completion, and embedded it into our existing P systems optimization algorithm (POA). Numerical studies and results analysis on some benchmark test functions demonstrate that MFE-POA can produce solutions of high quality and has great stability. The proposed method is applied to the model parameter estimation of the two types of PV cell models and multi-cell PV modules in different environmental conditions. The experimental results clearly argue the effectiveness of our proposed MFE-POA. Comparisons with other methods are presented and the results show that the proposed optimization algorithm is helpful and worth great promoting for parameter estimation in renewable energy modeling and prediction.

Computational models of phonotactics share much in common with language models, which assign probabilities to sequences of words. While state of the art language models are implemented using neural networks, phonotactic models have not followed suit. We present several neural models of phonotactics, and show that they perform favorably when compared to existing models. In addition, they provide useful insights into the role of representations on phonotactic learning and generalization. This work provides a promising starting point for future modeling of human phonotactic knowledge.

The ocean surface is highly dynamic. It moves rapidly and thus its shading changes rapidly as well. Usually, this doesn't pose any problems if the shading is smooth. However, for a surface that has a strong highlight or bright reflection moving rapidly, it causes an inaccurate and unnatural flickering. In the traditional rendering algorithms, each frame is rendered independently at a discrete time, resulting in serious temporal aliasing artifacts. Particularly, for a wavy water surface, reflection vectors may not hit the light source even though they actually hit for part of the frame time. Removing such aliasing in real-time is an active research area and many methods have been proposed [Jimenez et al. 2011]. They can improve the fidelity and efficiency of the rendering method. However, their focus is on spatial anti-aliasing and most of them do not address the temporal aliasing problem, particularly the one observed in rendering a reflected image of a light source on the water surface.

How to select and combine good traits of rice to get high-production individuals is one of the key points in developing crop ideotype cultivation technologies. Existing cultivation methods for producing ideal plants, such as field trials and crop modeling, have some limits. In this paper, we propose a method based on a genetic algorithm (GA) and a functional-structural plant model (FSPM) to optimize plant types of virtual rice by dynamically adjusting phenotypical traits. In this algorithm, phenotypical traits such as leaf angles, plant heights, the maximum number of tiller, and the angle of tiller are considered as input parameters of our virtual rice model. We evaluate the photosynthetic output as a function of these parameters, and optimized them using a GA. This method has been implemented on GroIMP using the modeling language XL (eXtended L-System) and RGG (Relational Growth Grammar). A double haploid population of rice is adopted as test material in a case study. Our experimental results show that our method can not only optimize the parameters of rice plant type and increase the amount of light absorption, but can also significantly increase crop yield.

© 2017, Springer-Verlag Berlin Heidelberg. Scenes in computer animation can have extreme complexity, especially when high resolution objects are placed in the distance and occupy only a few pixels. A useful technique for level of detail in these cases is to use a sparse voxel octree containing both hard surfaces and a participating medium consisting of microflakes. In this paper, we discuss three different methods for approximating the distribution of normals of the microflakes, which is needed to compute extinction, inscattering of attenuated direct illumination, and multiple scattering in the participating medium. Specifically, we consider (a) k means approximation with k weighted representatives, (b) expansion in spherical harmonics, and (c) the distribution of the normals of a specific ellipsoid. We compare their image quality, data size, and computation time.

With increasing computing power, it is possible to process more complex fluid simulations. However, a gap between increasing data size and our ability to visualize them still remains. Despite the great amount of progress that has been made in the field of flow visualization over the last two decades, a number of challenges remain. While the visualization of 2D flow has many good solutions, the visualization of 3D flow still poses many problems. Challenges such as domain coverage, speed of computation, and perception remain key directions for further research. Flow visualization with a focus on surface-based techniques forms the basis of this literature survey, including surface construction techniques and visualization methods applied to surfaces. We detail our investigation into these algorithms with discussions of their applicability and their relative strengths and drawbacks. We review the most important challenges when considering such visualizations. The result is an up-to-date overview of the current state-of-the-art that highlights both solved and unsolved problems in this rapidly evolving branch of research.

This paper presents a finite element method-based framework for an object withering simulation modeled with heterogeneous material, such as fruits drying or decay. We introduce diffusion procedures for both the moisture content and decay spread, which are solved directly on a tetrahedral mesh representation of the fruit flesh. Then, we use the moisture content to control shrinkage through the initial strain, which is integrated into the Lagrangian dynamic equation, and solved with the finite element method. For the complex structure of the object, another fine triangle mesh is used to represent the skin, and its deformation is solved by a thin shell technique. To couple the motion between different layers of the fruit, a tracking force is used to pull the skin and drive its deformation together with the volume mesh. In comparison with the previous work, our method provides temporally and spatially varying parameters to model the complex phenomena of object withering. Moreover, the water diffusivity can also be given by user input to present various material properties of the cut section and skin-covered area. Our algorithm is easy to implement and highly efficient in generating a realistic appearance for the withering effect. For a medium-scale model, we can achieve interactive simulation. Copyright © 2012 John Wiley & Sons, Ltd. (On the basis of a finite element method framework, the dynamic withering procedure is computed with diffusion of moisture content and decay spread. The material properties are controlled by moisture content, and the shrinkage also depends on moisture content through the initial strain. The heterogeneous deformation is simulated realistically and efficiently with our approach.)

Most 3D vector field visualization techniques suffer from the problem of visual clutter, and it remains a challenging task to effectively convey both directional and structural information of 3D vector fields. In this paper, we present a novel visualization framework that combines the advantages of clustering methods and illustrative rendering techniques to generate a concise and informative depiction of complex flow structures. Given a 3D vector field, we first generate a number of streamlines covering the important regions based on an entropy measurement. Then we decompose the streamlines into different groups based on a categorization of vector information, wherein the streamline pattern in each group is ensured to be coherent or nearly coherent. For each group, we select a set of representative streamlines and render them in an illustrative fashion to enhance depth cues and succinctly show local flow characteristics. The results demonstrate that our approach can generate a visualization that is relatively free of visual clutter while facilitating perception of salient information of complex vector fields.

The three-dimensional structure of a protein is organized around the packing of its secondary structure elements. Predicting the topology and constructing the geometry of structural motifs involving α-helices and/or β-strands are therefore key steps for accurate prediction of protein structure. While many efforts have focused on how to pack helices and on how to sample exhaustively the topologies and geometries of multiple strands forming a β-sheet in a protein, there has been little progress on generating native-like packings of helices on sheets. We describe a method that can generate the packing of multiple helices on a given β-sheet for αβα sandwich type protein folds. This method mines the results of a statistical analysis of the conformations of αβ2 motifs in protein structures to provide input values for the geometric attributes of the packing of a helix on a sheet. It then proceeds with a geometric builder that generates multiple arrangements of the helices on the sheet of interest by sampling through these values and performing consistency checks that guarantee proper loop geometry between the helices and the strands, minimal number of collisions between the helices, and proper formation of a hydrophobic core. The method is implemented as a module of ProteinShop. Our results show that it produces structures that are within 4–6 A RMSD of the native one, regardless of the number of helices that need to be packed, though this number may increase if the protein has several helices between two consecutive strands in the sequence that pack on the sheet formed by these two strands. Proteins 2011; Published 2011 Wiley-Liss, Inc.

Strange attractors of 3D vector field flows sometimes have a fractal geometric structure in one dimension, and smooth surface behavior in the other two. General flow visualization methods show the flow dynamics well, but not the fractal structure. Here we approximate the attractor by polygonal surfaces, which reveal the fractal geometry. We start with a polygonal approximation which neglects the fractal dimension, and then deform it by the flow to create multiple sheets of the fractal structure. We use adaptive subdivision, mesh decimation, and retiling methods to preserve the quality of the polygonal surface in the face of extreme stretching, bending, and creasing caused by the flow. A GPU implementation provides efficient visualization, which we also apply to other turbulent flows.

Isosurfaces are fundamental volumetric visualization tools and are generated by approximating contours of trilinearly interpolated scalar fields. While a complete set of cases has recently been published by Nielson, the formal proof that these cases are the only ones possible and that they are topologically correct is difficult to follow. We present a more straightforward proof of the correctness and completeness of these cases based on a variation of the Dividing Cubes algorithm. Since this proof is based on topological arguments and a divide-and-conquer approach, this also sets the stage for developing tessellation cases for higher order interpolants and the quadrilinear interpolant in four dimensions. We also demonstrate that apart from degenerate cases, Nielson's cases are, in fact, subsets of two basic configurations of the trilinear interpolant.

We have simulated a time varying wind field using the lattice Boltzmann model, and its effect on blades of grass with a simple mass-spring model. We present a global illumination model for multiple scattering of incident sun and sky illumination within the field of grass. We model the grass as a continuous distribution of infinitesimal colored scattering flakes and solve a system of differential equations for the radiance transport. We repeat this for a collection of grass bending directions and amounts, and then interpolate the solutions when rendering animations of blowing grass.

We describe a method that can thoroughly sample a protein conformational space given the protein primary sequence of amino acids and secondary structure predictions. Specifically, we target proteins with β-sheets because they are particularly challenging for ab initio protein structure prediction because of the complexity of sampling long-range strand pairings. Using some basic packing principles, inverse kinematics (IK), and β-pairing scores, this method creates all possible β-sheet arrangements including those that have the correct packing of β-strands. It uses the IK algorithms of ProteinShop to move α-helices and β-strands as rigid bodies by rotating the dihedral angles in the coil regions. Our results show that our approach produces structures that are within 4–6 A RMSD of the native one regardless of the protein size and β-sheet topology although this number may increase if the protein has long loops or complex α-helical regions. Proteins 2010. © Published 2009 Wiley-Liss, Inc.

This paper presents a method to accelerate algorithms that need a correct and complete visibility ordering of their data for rendering. The technique works by pre-sorting primitives in object-space using three lists (one for each axis: X, Y and Z), and then combining the lists using graphics hardware by rendering each list to a texture and merging the textures in the end. We validate our algorithm by applying it to the splatting technique using several types of rendering, including point-based rendering and volume rendering. We also detail our hardware implementation for volume rendering using point sprites.

It is known that the pure light field approach for view synthesis relies on a large number of image samples to produce anti-aliased renderings. Otherwise, the insufficiency of image sampling needs to be compensated for by geometry sampling. Currently, geometry estimation is done either offline or using dedicated hardware. Our solution to this dilemma is based on three key ideas: a formal analysis of the equivalency between light field rendering and plane-based warping, multi focus imaging in a multi camera system by plane sweeping, and the fusion of the multi focus image using multi view stereo. The essence of our method is to perform necessary depth estimation up to the level required by the minimal joint image-geometry sampling rate using off-the-shelf graphics hardware. As a result, real-time anti-aliased light field rendering is achieved even if the image samples are insufficient.

This paper presents a method of dividing into triangle fans the most common projections of hexahedra from curvilinear meshes, so that they can be volume rendered in hardware, with a fragment progra...

The SciDAC Institute for Ultrascale Visualization brought together leading experts from visualization, high-performance computing, and science application areas to make advanced visualization solutions for SciDAC scientists and the broader community. Over the five-year project, the Institute introduced many new enabling visualization techniques, which have significantly enhanced scientists’ ability to validate their simulations, interpret their data, and communicate with others about their work and findings. This Institute project involved a large number of junior and student researchers, who received the opportunities to work on some of the most challenging science applications and gain access to the most powerful high-performance computing facilities in the world. They were readily trained and prepared for facing the greater challenges presented by extreme-scale computing. The Institute’s outreach efforts, through publications, workshops and tutorials, successfully disseminated the new knowledge and technologies to the SciDAC and the broader scientific communities. The scientific findings and experience of the Institute team helped plan the SciDAC3 program.

Images synthesized by light field rendering exhibit aliasing artifacts when the light field is undersampled; adding new light field samples improves the image quality and reduces aliasing but new samples are expensive to acquire. Light field rays are traditionally gathered directly from the source images, but new rays can also be inferred through geometry estimation. This paper describes a light field rendering approach based on this principle that estimates geometry from the set of source images using multi-baseline stereo reconstruction to supplement the existing light field rays to meet the minimum sampling requirement. The rendering and reconstruction steps are computed over a set of planes in the scene volume, and output images are synthesized by compositing results from these planes together. The planes are each processed independently and the number of planes can be adjusted to scale the amount of computation to achieve the desired frame rate. The reconstruction fidelity (and by extension image quality) is improved by a library of matching templates to support matches along discontinuities in the image or geometry (e.g. object profiles and concavities). Given a set of silhouette images, the visual hull can be constructed and applied to further improve reconstruction by removing outlier matches. The algorithm is efficiently implemented by a set of image filter operations on commodity graphics hardware and achieves image synthesis at interactive rates.

Visualization of observed data or simulation output is important to science and engineering. I have been particularly interested in visualizing 3-D structures, and report here my personal impressions on progress in the last 20 years in visualizing molecules, scalar fields, and vector fields and their associated flows. I have tried to keep the survey and list of references manageable, so apologize to those authors whose techniques I have not mentioned, or have described without a reference citation.

Most existing light-field rendering methods rely on images that record the color of the rays. In this paper, we present a new approach that instead uses colored point clouds, which are the source of the rays. Furthermore, we study the light field from a dual-space viewpoint, where 3D scene points appear as geometry hyperlines, and rays appear as hyperpoints located on the hyperlines. Rendering the light field reduces to finding and blending the closest hyperlines to the hyperpoints corresponding to the virtual rays. Occlusion is dealt with by clustering nearby hyperlines according to their slope. Hole filling is dealt with by increasing the range of contribution of the hyperlines by a given threshold. We also propose the concept of local ray space, and show that it improves the rendering quality and removes the restriction on virtual camera position that is associated with the global ray space scheme. Finally, we show how to deal with uncertain geometric information in our framework.

Projection methods for volume rendering unstructured data work by projecting, in visibility order, the polyhedral cells of the mesh onto the image plane, and incrementally compositing each cell's color and opacity into the final image. Normally, such methods require an algorithm to determine a visibility order of the cells. The Meshed Polyhedra Visibility Order (MPVO) algorithm can provide such an order for convex meshes by considering the implications of local ordering relations between cells sharing a common face. However, in nonconvex meshes, one must also consider ordering relations along viewing rays which cross empty space between cells. In order to include these relations, the algorithm described in this paper, the scanning exact meshed polyhedra visibility ordering (SXMPVO) algorithm, scan-converts the exterior faces of the mesh and saves the ray-face intersections in an A-Buffer data structure which is then used for retrieving the extra ordering relations. The image which SXMPVO produces is the same as would be produced by ordering the cells exactly, even though SXMPVO does not compute an exact visibility ordering. This is because the image resolution used for computing the visibility ordering relations is the same as that which is used for the actual volume rendering and we choose our A-Buffer rays at the same sample points that are used to establish a polygon's pixel coverage during hardware scan conversion. Thus, the algorithm is image-space correct. The SXMPVO algorithm has several desirable features; among them are speed, simplicity of implementation, and no extra (i.e., with respect to MPVO) preprocessing.

We describe ProteinShop, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds. ProteinShop may be used at different stages of a protein structure prediction process. First, it can create protein configurations containing secondary structures specified by the user. Second, it can interactively manipulate protein fragments to achieve desired folds by adjusting the dihedral angles of selected coil regions using an Inverse Kinematics method. Last, it serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine. ProteinShop was used to create initial configurations for a protein structure prediction method developed by a team that competed in CASP5. ProteinShop's use accelerated the process of generating initial configurations, reducing the time required from days to hours. This paper describes the structure of ProteinShop and discusses its main features.

One step in the reconstruction pipeline for creating scene geometry from multiple camera views is the fitting of 3-D planes to image segments. We optimize the four homogeneous coefficients of the equation of a plane, so that the homography it induces on a source image segment minimizes a cost function with photo consistency and edge consistency terms. The photo consistency term for a segment is defined as the summed squared pixel color differences with all target images in which it is visible. For the edges we find a set of sub pixel-precise Canny edge points from the source image. The edge consistency term considers all pairs of segments which are adjacent in 3D, and sums the squared 2D distances of the appropriate Canny edge points to the projection of the line in which the two segment planes intersect. We apply the L-BFGS non-linear optimization algorithm, which uses derivatives of the cost function with respect to the plane equation coefficients, and we derive analytic formulas for these derivatives for both terms in the cost function. An alternate optimization method uses the sparse Hessian matrix of second derivatives, and we compute these second derivatives as well. We test these plane optimizations on both synthetic and real image sequences.

A method to compute the similarity between different plants is proposed, using features of a plant׳s topological structure and peripheral contour, as well as its geometry. The topological structures are described using tree graphs, and their similarity can be calculated based on the edit distance of these graphs. The peripheral contour of a plant is abstracted by its three-dimensional convex hull, which is projected in several directions. The similarity of the different projections is calculated by an algorithm to compute the similarity of two-dimensional shapes. The similarity of the geometrical detail is computed by considering the geometrical properties of different level branches. Finally the overall similarity between different plants is calculated by combining these different similarity measures. The validity of proposed method is evaluated by detailed experiments.

Automatic fusion of aerial optical imagery and untextured LiDAR data has been of significant interest for generating photo-realistic 3D urban models in recent years. However, unsupervised, robust registration still remains a challenge. This paper presents a new registration method that does not require priori knowledge such as GPS/INS information. The proposed algorithm is based on feature correspondence between a LiDAR depth map and a depth map from an optical image. Each optical depth map is generated from edge-preserving dense correspondence between the image and another optical image, followed by ground plane estimation and alignment for depth consistency. Our two-pass RANSAC with Maximum Likelihood estimation incorporates 2D-2D and 2D-3D correspondences to yield robust camera pose estimation. Experiments with a LiDAR-optical imagery dataset show promising results, without using initial pose information.

A hardware polygon rendering pipeline can be used with hardware compositing to volume render arbitrary unstructured grids composed of convex polyhedral cells. This technique is described, together with the global sorting necessary for back-to-front compos- iting, and the modifications that must be made to approximate cur- vilinear cells, whose faces may not be planar. © 2000 John Wiley & Sons

Direct volume rendering based on projective methods works by projecting, in visibility order, the polyhedral cells of a mesh onto the image plane, and incrementally compositing the cell’s color and opacity into the final image. Crucial to this method is the computation of a visibility ordering of the cells. If the mesh is “well-behaved” (acyclic and convex), then the MPVO method of Williams provides a very fast sorting algorithm; however, this method only computes an approximate ordering in general datasets, resulting in visual artifacts when rendered. A recent method of Silva et al. removed the assumption that the mesh is convex, by means of a sweep algorithm used in conjunction with the MPVO method; their algorithm is substantially faster than previous exact methods for general meshes. In this paper we propose a new technique, which we call BSP-XMPVO, which is based on a fast and simple way of using binary space partitions on the boundary elements of the mesh to augment the ordering produced by MPVO. Our results are shown to be orders of magnitude better than previous exact methods of sorting cells.

Author(s): Wang, Wencheng; Wu, En-Hua; Max, Nelson | Abstract: Selective visualization is a solution for visualizing data of large size and dimensionality. In this paper a new method is proposed for effectively rendering certain chosen parts among the full set of data in terms of a colour buffer, referred to as the virtual plane, for storing intermediate results. By this method, scientists may concentrate their attention on the contents of data in which they are interested. Besides, the method could be easily integrated with all the current direct volume rendering techniques, especially progressive refinement methods and selective methods.

The intermediate storage and memory access for the first-pass output of the Catmull-Smith two-pass image resampling are eliminated by feeding output directly to the second pass as soon as it is computed. The algorithm reads input and intermediate data sequentially, so that it is suitable for efficient hardware or software implementation on modern, cache-based computers.

In order to improve the efficiency of virtual plant modeling based on L-systems, a plant morphology modeling system using an evolutionary strategy is designed and implemented. First the axiom and the productions of an L-system are mapped to chromosomes, and then the initial population is designed. Genetic operators are designed to generate the individuals of a new population. The fitness function considers two aspects: the plant outline, and the internal branching. Using the fitness function for evolution, the L-system’s production rules for the target plants can be obtained. Key implementation techniques, function modules, and interfaces of the system are briefly introduced. Finally, the validity of the system is tested in detailed experiments.

This paper presents a multi-view stereo algorithm for piecewise planar scene reconstruction and optimization. Our segmentation-based reconstruction algorithm is iterative to minimize our defined energy function, consisting of reconstruction, refinement and optimization steps. The first step is a plane initialization to allow each segment to have a set of initial plane candidates. Then a plane refinement based on non-linear optimization improves the accuracy of the segment planes. Finally a plane optimization with a segment-adjacency graph leads to optimal segment planes, each of which is chosen among possible plane candidates by evaluating its relationship with adjacent planes in 3D. This algorithm yields better accuracy and performance, compared to the previous algorithms described in this paper. The results show our method is suitable for outdoor or aerial urban scene reconstruction, especially in wide baselines and images with textureless regions.

This tutorial survey paper reviews several different models for light interaction with volume densities of absorbing, glowing, reflecting, and/or scattering material. They are, in order of increasing realism, absorption only, emission only, emission and absorption combined, single scattering of external illumination without shadows, single scattering with shadows, and multiple scattering. For each model the paper provides the physical assumptions, describes the applications for which it is appropriate, derives the differential or integral equations for light transport, presents calculation methods for solving them, and shows output images for a data set representing a cloud. Special attention is given to calculation methods for the multiple scattering model. >

The hemicube estimates of form factors are based on a finite set of sample directions. We obtain several optimal arrangements of sample directions, which minimize the variance of these estimates. They are based on changing the size or shape of the pixels or the shape of the hemicube, or using non-uniform pixel grids. The best reduces the variance by 43%. The variance calculation is based on the assumption that the errors in the estimate are caused by the projections of single polygon edges, and that the positions and orientations of these edges are random. This replaces the infinite dimensional space of possible environments by the two dimensional space of great circles on the unit sphere, making the numerical variance minimization possible. >

BuildBeta is a feature of the ProteinShop software designed to thoroughly sample a protein conformational space given the protein's sequence of amino acids and secondary structure predictions. It targets proteins with beta sheets because they are particularly challenging to predict due to the complexity of sampling long-range strand pairings. Here we discuss some of the most difficult targets in the recent 9th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and show how BuildBeta can leverage some of the most successful methods in the category "template-free modeling" by augmenting their sampling capabilities. We also discuss ongoing efforts to improve the quality of the supersecondary structures it generates.

We present two new techniques for rendering 3D vector fields in scientific visualisation. We also present a new technique called texture splats for rendering these volumes efficiently. >

The three-dimensional structure of a protein is organized around the packing of its secondary structure elements. Predicting the topology and constructing the geometry of structural motifs involving α-helices and/or β-strands are therefore key steps for accurate prediction of protein structure. While many efforts have focused on how to pack helices and on how to sample exhaustively the topologies and geometries of multiple strands forming a β-sheet in a protein, there has been little progress on generating native-like packings of helices on sheets. We describe a method that can generate the packing of multiple helices on a given β-sheet for αβα sandwich type protein folds. This method mines the results of a statistical analysis of the conformations of αβ(2) motifs in protein structures to provide input values for the geometric attributes of the packing of a helix on a sheet. It then proceeds with a geometric builder that generates multiple arrangements of the helices on the sheet of interest by sampling through these values and performing consistency checks that guarantee proper loop geometry between the helices and the strands, minimal number of collisions between the helices, and proper formation of a hydrophobic core. The method is implemented as a module of ProteinShop. Our results show that it produces structures that are within 4-6 Å RMSD of the native one, regardless of the number of helices that need to be packed, though this number may increase if the protein has several helices between two consecutive strands in the sequence that pack on the sheet formed by these two strands.

It is often stated that in the Middle Ages beer was a necessity since drinking water was generally unsafe. It is argued here instead that water was widely drunk (often after having been purified through boiling) and that beer (as well as wine) was an

Techniques for visualizing several climate variables, particularly clouds and wind velocities, are discussed. The techniques are volume rendering, textured contour surfaces, and vector field rendering. The application of these techniques is discussed in the context of a high-definition television (HDTV) animation produced to show global cloud motion during ten simulated days in January. The computational grid is defined by nearly a million grid points-320 evenly spaced longitudes, 160 unevenly spaced latitudes, and 19 unevenly spaced surfaces of constant geopotential. The climate variables at every grid point were output at every hour of simulated time, resulting in 380 MB of data per simulated day. >

We propose a new fast height-field rendering method for Image-Based Lighting. Our approach approximates the environmental illumination using spherical radial basis functions (SRBFs). We approximate the integrand of the rendering equation as a sum of products of the SRBFs and the visibility function. Then we solve the integral by approximating the visibility function of each SRBF as the fraction visible above the height-field. This fraction is precomputed into a 2-Dtexture, as a function of the SRBF size and its angle to the horizon. We use two different approximations of the horizon. The first, called a horizon map, can render more accurate self occlusion. The second, called a cone map, needs only a single RGBA 2D texture but can only render rough self-shadowing. Our approach can quickly render shading and self-shadowing of a height-field from all-frequency environmental lighting.