Decomposition of multicomponent mass spectra using Bayesian probability theory

We present a method for the decomposition of mass spectra of mixture gases using Bayesian probability theory. The method works without any calibration measurement and therefore applies also to the analysis of spectra containing unstable species. For the example of mixtures of three different hydrocarbon gases the algorithm provides concentrations and cracking coefficients of each mixture component as well as their confidence intervals. The amount of information needed to obtain reliable results and its relation to the accuracy of our analysis are discussed

The determination and distribution of precise time

Methods for time determination including atomic clocks and distribution of timing signal

Steady, oscillatory, and unsteady subsonic Aerodynamics, production version 1.1 (SOUSSA-P1.1). Volume 2: User/programmer manual

A user/programmer manual for the computer program SOUSSA P 1.1 is presented. The program was designed to provide accurate and efficient evaluation of steady and unsteady loads on aircraft having arbitrary shapes and motions, including structural deformations. These design goals were in part achieved through the incorporation of the data handling capabilities of the SPAR finite element Structural Analysis computer program. As a further result, SOUSSA P possesses an extensive checkpoint/ restart facility. The programmer's portion of this manual includes overlay/subroutine hierarchy, logical flow of control, definition of SOUSSA P 1.1 FORTRAN variables, and definition of SOUSSA P 1.1 subroutines. Purpose of the SOUSSA P 1.1 modules, input data to the program, output of the program, hardware/software requirements, error detection and reporting capabilities, job control statements, a summary of the procedure for running the program and two test cases including input and output and listings are described in the user oriented portion of the manual

Evolutionary support vector machines and their application for classification

We propose a novel learning technique for classification as result of the hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the classification task as in support vector machines but use evolutionary algorithms to solve the optimization problem of determining the decision function. They can acquire the coefficients of the separating hyperplane, which is often not possible within classical techniques. More important, ESVMs obtain the coefficients directly from the evolutionary algorithm and can refer them at any point during a run. The concept is furthermore extended to handle large amounts of data, a problem frequently occurring e.g. in spam mail detection, one of our test cases. Evolutionary support vector machines are validated on this and three other real-world classification tasks; obtained results show the promise of this new technique

The spectral weight of the Hubbard model through cluster perturbation theory

We calculate the spectral weight of the one- and two-dimensional Hubbard models, by performing exact diagonalizations of finite clusters and treating inter-cluster hopping with perturbation theory. Even with relatively modest clusters (e.g. 12 sites), the spectra thus obtained give an accurate description of the exact results. Thus, spin-charge separation (i.e. an extended spectral weight bounded by singularities) is clearly recognized in the one-dimensional Hubbard model, and so is extended spectral weight in the two-dimensional Hubbard model.Comment: 4 pages, 5 figure

The influence of the strength of bone on the deformation of acetabular shells : a laboratory experiment in cadavers

Date of Acceptance: 24/08/2014 ©2015 The British Editorial Society of Bone & Joint Surgery. The authors would like to thank N. Taylor (3D Measurement Company) for his work with regard to data acquisition and processing of experimental data. We would also like to thank Dr A. Blain of Newcastle University for performing the statistical analysis The research was supported by the NIHR Newcastle Biomedical Research Centre. The authors P. Dold, M. Flohr and R. Preuss are employed by Ceramtec GmbH. Martin Bone received a salary from the joint fund. The author or one or more of the authors have received or will receive benefits for personal or professional use from a commercial party related directly or indirectly to the subject of this article. This article was primary edited by G. Scott and first proof edited by J. Scott.Peer reviewedPostprin

On Doppler tracking in cosmological spacetimes

We give a rigorous derivation of the general-relativistic formula for the two-way Doppler tracking of a spacecraft in Friedmann-Lemaitre-Robertson-Walker and in McVittie spacetimes. The leading order corrections of the so-determined acceleration to the Newtonian acceleration are due to special-relativistic effects and cosmological expansion. The latter, although linear in the Hubble constant, is negligible in typical applications within the Solar System.Comment: 10 pages, 1 figure. Journal versio

Lessons from LIMK1 enzymology and their impact on inhibitor design

LIM domain kinase 1 (LIMK1) is a key regulator of actin dynamics. It is thereby a potential therapeutic target for the prevention of fragile X syndrome and amyotrophic lateral sclerosis. Herein, we use X-ray crystallography and activity assays to describe how LIMK1 accomplishes substrate specificity, to suggest a unique ‘rock-and-poke’ mechanism of catalysis and to explore the regulation of the kinase by activation loop phosphorylation. Based on these findings, a differential scanning fluorimetry assay and a RapidFire mass spectrometry activity assay were established, leading to the discovery and confirmation of a set of small-molecule LIMK1 inhibitors. Interestingly, several of the inhibitors were inactive towards the closely related isoform LIMK2. Finally, crystal structures of the LIMK1 kinase domain in complex with inhibitors (PF-477736 and staurosporine, respectively) are presented, providing insights into LIMK1 plasticity upon inhibitor binding