High Order Multi-Moment Constrained Finite Volume Method. Part I: Basic Formulation

A new high-order finite volume method based on local reconstruction is presented in this paper. The method, so-called the multi-moment constrained finite volume (MCV) method, uses the point values defined within single cell at equally spaced points as the model variables (or unknowns). The time evolution equations used to update the unknowns are derived from a set of constraint conditions imposed on multi kinds of moments, i.e. the cell-averaged value and the point-wise value of the state variable and its derivatives. The finite volume constraint on the cell-average guarantees the numerical conservativeness of the method. Most constraint conditions are imposed on the cell boundaries, where the numerical flux and its derivatives are solved as general Riemann problems. A multi-moment constrained Lagrange interpolation reconstruction for the demanded order of accuracy is constructed over single cell and converts the evolution equations of the moments to those of the unknowns. The presented method provides a general framework to construct efficient schemes of high orders. The basic formulations for hyperbolic conservation laws in 1- and 2D structured grids are detailed with the numerical results of widely used benchmark tests. (C) 2009 Elsevier Inc. All rights reserved.

A global shallow water model using high order multi-moment constrained finite volume method and icosahedral grid

A novel accurate numerical model for shallow water equations on sphere have been developed by implementing the high order multi-moment constrained finite volume (MCV) method on the icosahedral geodesic grid. High order reconstructions are conducted cell-wisely by making use of the point values as the unknowns distributed within each triangular cell element. The time evolution equations to update the unknowns are derived from a set of constrained conditions for two types of moments, i.e. the point values on the cell boundary edges and the cell-integrated average. The numerical conservation is rigorously guaranteed. in the present model, all unknowns or computational variables are point values and no numerical quadrature is involved, which particularly benefits the computational accuracy and efficiency in handling the spherical geometry, such as coordinate transformation and curved surface. Numerical formulations of third and fourth order accuracy are presented in detail. The proposed numerical model has been validated by widely used benchmark tests and competitive results are obtained. The present numerical framework provides a promising and practical base for further development of atmospheric and oceanic general circulation models. (C) 2009 Elsevier Inc. All rights reserved.

Privacy-Protected Facial Biometric Verification via Fuzzy Forest Learning

Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacyrelated applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.

Disease-Gene Association Using Genetic Programming

As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.

A model for computing vibration induced stresses of electronic components in a general flexible mounting

This paper develops a novel full analytic model for vibration analysis of solid-state electronic components. The model is just as accurate as finite element models and numerically light enough to permit for quick design trade-offs and statistical analysis. The paper shows the development of the model, comparison to finite elements and an application to a common engineering problem. A gull-wing flat pack component was selected as the benchmark test case, although the presented methodology is applicable to a wide range of component packages. Results showed very good agreement between the presented method and finite elements and demonstrated the usefulness of the method in how to use standard test data for a general application. © 2013 Elsevier Ltd.

Enantioselektive Organokatalyse in Epoxidierungen und Cyanhydrinbildungen

In der vorliegenden Arbeit mit dem Titel „Enantioselektive Organokatalyse in Epoxidierungen und Cyanhydrinbildungen“ wurde die Synthese zweier Cyclophan-carbaldimine durchgeführt. Beide Verbindungen bestehen aus einem Glykosyl-Baustein und einem Paracyclophan-Baustein, die über eine Imin-Bindung verbrückt sind. Die Cyclophan-carbaldimine wurden dann als Katalysatoren in einer Reihe von enantioselektiven Reaktionen verwendet. Enantioselektive Reaktionen bilden von zwei spiegelbildlichen Produkten stets eines im Überschuss. Zu diesen Reaktionen zählen die in dieser Arbeit durchgeführten enantioselektiven Epoxidierungen und enantioselektiven Cyanhydrinsynthesen. Die enantioselektiven Epoxidierungen waren dabei als Teil der Totalsynthesen der Naturstoffe Dasyscyphin D und Caripyrin geplant. Diese beiden Naturstoffe zeigten in biologischen Tests am Institut für Biotechnologie und Wirkstoffforschung (IBWF) in Kaiserslautern Aktivität gegen den Reisbrand-Pilz Magnaporthe grisea, der für Ernteverluste in beträchtlichem Ausmaß verantwortlich ist. Das Caripyrin selbst beinhaltet eine Epoxidstruktur. Mittels der oben angeführten Katalysatoren wurde versucht, diese Epoxidstruktur selektiv einzuführen. Dies gelang nicht, aber der Naturstoff konnte mittels Epoxidierung durch m-Chlorperbenzoesäure erstmals dargestellt werden. In mehreren biologischen Vergleichstests am IBWF Kaiserslautern zeigte auch das synthetische Caripyrin mit dem natürlichen Caripyrin vergleichbare biologische Aktivität.rnDas Dasyscyphin D an sich trägt keine Epoxidfunktion. Dennoch spielt sie auch hier eine wichtige Rolle. Innerhalb der geplanten Totalsynthese von Dasyscyphin D sollte die Farnesylseitenkette eines aromatischen Ringes selektiv epoxidiert werden. Durch einen elektrophilen Angriff an dieses Epoxid sollte im Anschluss eine Cyclisierung zum Dasyscyphin-Grundgerüst eingeleitet werden, aus dem dann Dasyscyphin D dargestellt werden sollte. Im Gegensatz zur Caripyrin-Synthese, bei der die selektive Epoxidierung nicht gelang, scheint sie in der Synthese von Dasyscyphin D sattgefunden zu haben, allerdings ist eine Isolierung des Reaktionsproduktes noch nicht gelungen. Folglich konnte das Dasyscyphin D noch nicht erfolgreich synthetisiert werden.rnDie Versuche zur enantioselektiven Cyanhydrin-Synthese waren nicht Bestandteil einer Totalsynthese. Die Cyanhydrine wurden zuerst als Racemate synthetisiert und gaschromatographisch vermessen, um auf diese Weise die exakten Retentionszeiten der einzelnen Enantiomere zu ermitteln. Anschließend wurden die Cyanhydrine dann enantioselektiv dargestellt und ebenfalls gaschromatographisch vermessen. Durch den Vergleich mit den racemischen Cyanhydrinen konnte dabei direkt aus der Reaktionslösung gemessen werden, was erforderlich war, da eine Isolierung der Cyanhydrine unter den gewählten Reaktionsbedingen nicht gelang. Aus den gaschromatographischen Messungen konnten Enantiomerenüberschüsse von bis zu 95 % ermittelt werden. Weiterhin ergaben die Messungen, dass der Arabinosyl-Katalysator im Vergleich mit dem Galactosyl-Katalysator eine geringere Enantioselektivität induziert, was vermutlich auf leichte räumliche Differenzen der beiden Katalysatoren zurückzuführen ist. Ein weiteres wichtiges Ergebnis war, dass beide Katalysatoren, wie geplant, unterschiedliche Enantiomere im Überschuss bilden. Die Glykosyl- und Paracyclophan-Bausteine der beiden Katalysatoren waren so gewählt worden, dass beide Katalysatoren pseudo-Enantiomere bilden. Auf diese Weise sollte eine Einflussnahme auf das gebildete Enantiomer durch die Wahl des entsprechenden Cyclophan-carbaldimin-Katalysators möglich gemacht werden, was, wie bereits erwähnt, gelang.rn

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

Matrix models for quantifying competitive intransitivity from species abundance data

In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.

Behaviour of Concrete Structural Members Subjected to Air Blast Loading

Numerical analysis is a suitable tool in the design of complex reinforced concrete structures under extreme impulsive loadings such as impacts or explosions at close range. Such events may be the result of terrorist attacks. Reinforced concrete is commonly used for buildings and infrastructures. For this reason, the ability to accurately run numerical simulations of concrete elements subjected to blast loading is needed. In this context, reliable constitutive models for concrete are of capital importance. In this research numerical simulations using two different constitutive models for concrete (Continuous Surface Cap Model and Brittle Damage Model) have been carried out using LS-DYNA. Two experimental benchmark tests have been taken as reference. The results of the numerical simulations with the aforementioned constitutive models show different abilities to accurately represent the structural response of the reinforced concrete elements studied.

Наука и Изкуство: История на взаимно вдъхновение

Science and art are considered as two distinct areas in the spectrum of human activities. Many scientists are inspired by art and many artists embed science in their work. This paper presents a one-year experiment, which started with benchmark tests of a compiler, passed through dynamic systems based on complex numbers and ended as a scientific art exhibition. The paper demonstrates that it is possible to blend science and art in a mutually beneficial way. It also shows how science can inspire the creation of artistic works, as well as how these works can inspire further scientific research.

Effect of ray and speed perturbations on ionospheric tomography by over-the-horizon radar: A new method

International audience

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Seismic analyses of shallow tunnels by dynamic centrifuge tests and finite elements

The increments of internal forces induced in a tunnel lining during earthquakes can be assessed with several procedures at different levels of complexity. However, the substantial lack of well-documented case histories still represents a difficulty in order to validate any of the methods proposed in literature. To bridge this gap, centrifuge model tests were carried out on a circular aluminium tunnel located at two different depths in dense and loose dry sand. Each model has been instrumented for measuring soil motion and internal loads in the lining and tested under several dynamic input signals. The tests performed represented an experimental benchmark to calibrate dynamic analyses with different approaches to account for soil-tunnel kinematic interaction. © 2009 IOS Press.

Tests of MULTIMODE calculations of rovibrational energies of CH4

We report variational calculations of rovibrational energies of CH4 using the code MULTIMODE and an ab initio force field of Schwenke and Partridge. The systematic convergence of the energies with respect to the level of mode coupling is presented. Converged vibrational energies calculated using the five-mode representation of the potential for zero total angular momentum are compared with previous, benchmark calculations based on Radau coordinates using this force field for zero total angular momentum and for J = 1. Very good agreement with the previous benchmark calculations is found. (c) 2006 Elsevier B.V. All rights reserved.