Characteristic value determination from small samples

The paper deals with the characteristic value determination from relatively small samples. When the distribution and its parameters of a random variable are known, the characteristic value is deterministic quantity. However, in practical problems the parameters of distribution are unknown and can only be estimated from random samples. Therefore the characteristic value is by itself a random variable. The estimates of characteristic values are strongly dependant on the distribution of random variable. In the paper we show the analytical solution for characteristic value determination from random samples of normal and lognormal random variables. The confirmation of analytical results is accomplished by the use of computer simulations. For Gumbel, and Weibull distribution the characteristic value estimates are obtained numerically by combination of simulations and bisection method. In the paper the numerical results are presented for 5% characteristic values with 75% confidence interval, which is in accord with the majority of European building standards. The proposed approach is demonstrated on the data of experimentally obtained bending strengths of finger jointed wooden beams. (C) 2006 Elsevier Ltd. All rights reserved

Reconstructing Surfaces Using Anisotropic Basis Functions

Point sets obtained from computer vision techniques are often noisy and non-uniform. We present a new method of surface reconstruction that can handle such data sets using anisotropic basis functions. Our reconstruction algorithm draws upon the work in variational implicit surfaces for constructing smooth and seamless 3D surfaces. Implicit functions are often formulated as a sum of weighted basis functions that are radially symmetric. Using radially symmetric basis functions inherently assumes, however that the surface to be reconstructed is, everywhere, locally symmetric. Such an assumption is true only at planar regions, and hence, reconstruction using isotropic basis is insufficient to recover objects that exhibit sharp features. We preserve sharp features using anisotropic basis that allow the surface to vary locally. The reconstructed surface is sharper along edges and at corner points. We determine the direction of anisotropy at a point by performing principal component analysis of the data points in a small neighborhood. The resulting field of principle directions across the surface is smoothed through tensor filtering. We have applied the anisotropic basis functions to reconstruct surfaces from noisy synthetic 3D data and from real range data obtained from space carving

Reconstructing Surfaces by Volumetric Regularization Using Radial Basis Functions

We present a new method of surface reconstruction that generates smooth and seamless models from sparse, noisy, nonuniform, and low resolution range data. Data acquisition techniques from computer vision, such as stereo range images and space carving, produce 3D point sets that are imprecise and nonuniform when compared to laser or optical range scanners. Traditional reconstruction algorithms designed for dense and precise data do not produce smooth reconstructions when applied to vision-based data sets. Our method constructs a 3D implicit surface, formulated as a sum of weighted radial basis functions. We achieve three primary advantages over existing algorithms: (1) the implicit functions we construct estimate the surface well in regions where there is little data, (2) the reconstructed surface is insensitive to noise in data acquisition because we can allow the surface to approximate, rather than exactly interpolate, the data, and (3) the reconstructed surface is locally detailed, yet globally smooth, because we use radial basis functions that achieve multiple orders of smoothness

Appearance of the Single Gyroid Network Phase in Nuclear Pasta Matter

Nuclear matter under the conditions of a supernova explosion unfolds into a rich variety of spatially structured phases, called nuclear pasta. We investigate the role of periodic network-like structures with negatively curved interfaces in nuclear pasta structures, by static and dynamic Hartree-Fock simulations in periodic lattices. As the most prominent result, we identify for the first time the {\it single gyroid} network structure of cubic chiral $I4_123$ symmetry, a well known configuration in nanostructured soft-matter systems, both as a dynamical state and as a cooled static solution. Single gyroid structures form spontaneously in the course of the dynamical simulations. Most of them are isomeric states. The very small energy differences to the ground state indicate its relevance for structures in nuclear pasta.Comment: 7 pages, 4 figure

Contaminant removal from enclosed atmospheres by regenerable adsorbents

A system for removing contaminants from spacecraft atmospheres was studied, which utilizes catalyst-impregnated activated carbon followed by in-situ regeneration by low-temperature catalytic oxidation of the adsorbed contaminants. Platinum was deposited on activated carbon by liquid phase impregnation with chloroplatinic acid, followed by drying and high-temperature reduction. Results were obtained for the seven selected spacecraft contaminants by means of three experimental test systems. The results indicate that the contaminants could be removed by oxidation with very little loss in adsorptive capacity. The advantages of a catalyst-impregnated carbon for oxidative regeneration are found to be significant enough to warrent its use

Non-invasive in vivo imaging of tumour-associated cathepsin B by a highly selective inhibitory DARPin

Cysteine cathepsins often contribute to cancer progression due to their overexpression in the tumour microenvironment and therefore present attractive targets for non-invasive diagnostic imaging. However, the development of highly selective and versatile small molecule probes for cathepsins has been challenging. Here, we targeted tumour-associated cathepsin B using designed ankyrin repeat proteins (DARPins). The selective DARPin 8h6 inhibited cathepsin B with picomolar affinity (Ki = 35 pM) by binding to a site with low structural conservation in cathepsins, as revealed by the X-ray structure of the complex. DARPin 8h6 blocked cathepsin B activity in tumours ex vivo and was successfully applied in in vivo optical imaging in two mouse breast cancer models, in which cathepsin B was bound to the cell membrane or secreted to the extracellular milieu by tumour and stromal cells. Our approach validates cathepsin B as a promising diagnostic and theranostic target in cancer and other inflammation-associated diseases

Minkowski Tensors of Anisotropic Spatial Structure

This article describes the theoretical foundation of and explicit algorithms for a novel approach to morphology and anisotropy analysis of complex spatial structure using tensor-valued Minkowski functionals, the so-called Minkowski tensors. Minkowski tensors are generalisations of the well-known scalar Minkowski functionals and are explicitly sensitive to anisotropic aspects of morphology, relevant for example for elastic moduli or permeability of microstructured materials. Here we derive explicit linear-time algorithms to compute these tensorial measures for three-dimensional shapes. These apply to representations of any object that can be represented by a triangulation of its bounding surface; their application is illustrated for the polyhedral Voronoi cellular complexes of jammed sphere configurations, and for triangulations of a biopolymer fibre network obtained by confocal microscopy. The article further bridges the substantial notational and conceptual gap between the different but equivalent approaches to scalar or tensorial Minkowski functionals in mathematics and in physics, hence making the mathematical measure theoretic method more readily accessible for future application in the physical sciences

Second order analysis of geometric functionals of Boolean models

This paper presents asymptotic covariance formulae and central limit theorems for geometric functionals, including volume, surface area, and all Minkowski functionals and translation invariant Minkowski tensors as prominent examples, of stationary Boolean models. Special focus is put on the anisotropic case. In the (anisotropic) example of aligned rectangles, we provide explicit analytic formulae and compare them with simulation results. We discuss which information about the grain distribution second moments add to the mean values.Comment: Chapter of the forthcoming book "Tensor Valuations and their Applications in Stochastic Geometry and Imaging" in Lecture Notes in Mathematics edited by Markus Kiderlen and Eva B. Vedel Jensen. (The second version mainly resolves minor LaTeX problems.

The Birth of a Galaxy - III. Propelling reionisation with the faintest galaxies

Starlight from galaxies plays a pivotal role throughout the process of cosmic reionisation. We present the statistics of dwarf galaxy properties at z > 7 in haloes with masses up to 10^9 solar masses, using a cosmological radiation hydrodynamics simulation that follows their buildup starting with their Population III progenitors. We find that metal-enriched star formation is not restricted to atomic cooling ($T_{\rm vir} \ge 10^4$ K) haloes, but can occur in haloes down to masses ~10^6 solar masses, especially in neutral regions. Even though these smallest galaxies only host up to 10^4 solar masses of stars, they provide nearly 30 per cent of the ionising photon budget. We find that the galaxy luminosity function flattens above M_UV ~ -12 with a number density that is unchanged at z < 10. The fraction of ionising radiation escaping into the intergalactic medium is inversely dependent on halo mass, decreasing from 50 to 5 per cent in the mass range $\log M/M_\odot = 7.0-8.5$. Using our galaxy statistics in a semi-analytic reionisation model, we find a Thomson scattering optical depth consistent with the latest Planck results, while still being consistent with the UV emissivity constraints provided by Ly$\alpha$ forest observations at z = 4-6.Comment: 21 pages, 15 figures, 4 tables. Accepted in MNRA

How bees and foams respond to curved confinement:Level set boundary representations in the Surface Evolver

We investigate the equilibrium properties of a single area-minimising bubble trapped between two narrowly-separated parallel curved plates. We begin with the simple case of a bubble trapped between concentric spherical plates. We develop a model that shows that the surface tension energy of the bubble is lower when confined between spherical plates as compared to a bubble trapped between flat plates. We confirm our findings by comparing against Surface Evolver simulations. Next, we derive a simple model for a bubble between arbitrarily curved parallel plates. The energy is found to be higher when the local Gaussian curvature of the plates is negative and lower when the curvature is positive. To check the validity of the model we consider a bubble trapped between concentric tori. In the toroidal case we find that the sensitivity of the bubble's energy to the local curvature acts as a geometric potential capable of driving bubbles from regions with negative to positive curvature