Радіолокаційно-вихрострумовий метод виявлення металів

Сучасний георадар – це складний геофізичний прилад для неруйнівного контролю неоднорідностей середовища. В основі роботи георадару лежить підповерхневе зондуванняявище відбивання електромагнітної хвилі від межі поділу шарів з різною діелектричною чи магнітною проникністю. Такими межами є локальні неоднорідності різної природи. Георадари з великою вірогідністю визначають цю неоднорідність та глибину її залягання, але не можуть визначити склад неоднорідності, наприклад, це сталь чи золото. Тому виникла необхідність у створенні георадару без цього недоліку

Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism

The human physiological system is stressed to its limits during endurance sports competition events. We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We calculated heat transfer by conduction and blood flow inside the body, and heat transfer from the skin by radiation, convection and sweat evaporation, resulting in temperature changes in 25 body compartments. We simulated a mountain time trial to Alpe d'Huez during the Tour de France. To approach the time realized by Lance Armstrong in 2004, very high oxygen uptake must be sustained by the simulated cyclist. Temperature was predicted to reach 39°C in the brain, and 39.7°C in leg muscle. In addition to the macroscopic simulation, we analysed the buffering of bursts of high adenosine triphosphate hydrolysis by creatine kinase during cyclical muscle activity at the biochemical pathway level. To investigate the low oxygen to carbohydrate ratio for the brain, which takes up lactate during exercise, we calculated the flux distribution in cerebral energy metabolism. Computational modelling of the human body, describing heat exchange and energy metabolism, makes simulation of endurance sports events feasible

Der diskrete Charme der Bourgeoisie - Ein Beitrag zur Soziologie des modernen Wirtschaftsbürgertums

Entgegen der These der Auflösungserscheinungen des Bürgertums stellt der Autor die Annahme auf den Prüfstand, dass wir es nach wie vor mit gesellschaftlichen Fraktionierungen bürgerlicher Lebensweisen zu tun haben. Am Beispiel autobiographischer Schriften von deutschen Topmanagern stellt der Text ein modernes Verständnis des Wirtschaftsbürgertums vor, das organisational (durch die Karrieremechanismen der Organisation) und institutionell (im Feld der Wirtschaft) verankert ist. Die moderne Sozialformation des Wirtschaftsbürgertums ist nur noch auf der Grundlage von Organisationen denkbar. Sie lässt sich, jenseits von Klasse und Stand, als Positionselite beschreiben. Anhand der Autobiographien lässt sich die Reproduktion dieser Elite auf Basis einer engen Verknüpfung zwischen familialer Herkunft, an organisationale Karrieren gebundene Leistungsbereitschaft und hoher formaler Bildung nachzeichnen. Die Abgrenzung in der Statusreproduktion zwischen Bildungs- und Wirtschaftsbürgertum weist der Autor am jeweiligen Verhältnis zur Bildung nach; zwar können beide einen hohen Bildungsgrad in Form von Bildungspatenten nachweisen, doch im Falle des Wirtschaftsbürgertums herrscht ein instrumentelles Verhältnis zur Bildung vor. Der hohe Bildungsgrad folgt hier dem Bedürfnis, den Status mittels formaler Bildung abzusichern und damit die Gefahr der eigenen Austauschbarkeit - als Personal der Organisation - zu kompensieren. Der Text macht außerdem generationale Effekte sichtbar; insbesondere indem er darlegt, inwieweit der "moderne Manager" einerseits in der Betonung seines Status seinen Vorgängern gleicht und sich doch gleichzeitig in der Art der Unternehmensführung abgrenzt - indem er bspw. die Managementkonzepte seiner Zeit aufgreift

Highlights from the 6th International Society for Computational Biology Student Council Symposium at the 18th Annual International Conference on Intelligent Systems for Molecular Biology

This meeting report gives an overview of the keynote lectures and a selection of the student oral and poster presentations at the 6th International Society for Computational Biology Student Council Symposium that was held as a precursor event to the annual international conference on Intelligent Systems for Molecular Biology (ISMB). The symposium was held in Boston, MA, USA on July 9th, 2010

Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies

Background: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue samples is desirable. Taking tissue biopsies after infusion of substrates labeled with stable carbon isotopes makes this possible in animal experiments. However, the appreciable noise level in NMR spectra of extracted tissue samples makes computational estimation of metabolic fluxes challenging and a good method to define confidence regions was not yet available.Results: Here we present a computational analysis method for nuclear magnetic resonance (NMR) measurements of tricarboxylic acid (TCA) cycle metabolites. The method was validated using measurements on extracts of single tissue biopsies taken from porcine heart in vivo. Isotopic enrichment of glutamate was measured by NMR spectroscopy in tissue samples taken at a single time point after the timed infusion of 13C labeled substrates for the TCA cycle. The NMR intensities for glutamate were analyzed with a computational model describing carbon transitions in the TCA cycle and carbon exchange with amino acids. The model dynamics depended on five flux parameters, which were optimized to fit the NMR measurements. To determine confidence regions for the estimated fluxes, we used the Metropolis-Hastings algorithm for Markov chain Monte Carlo (MCMC) sampling to generate extensive ensembles of feasible flux combinations that describe the data within meas

The brain as 'immunoprecipitator' of serum autoantibodies against N-Methyl-D-Aspartate receptor subunit NR1

Autoantibodies (AB) against N-methyl-D-aspartate receptor subunit NR1 (NMDAR1) are highly seroprevalent in health and disease. Symptomatic relevance may arise upon compromised blood-brain barrier (BBB). However, it remained unknown whether circulating NMDAR1 AB appear in the cerebrospinal fluid (CSF). Of n5271 subjects with CSF-serum pairs, 26 were NMDAR1 AB seropositive, but only 1 was CSF positive. Contrariwise, tetanus AB (non-brain-binding) were present in serum and CSF of all subjects, with CSF levels higher upon BBB dysfunction. Translational mouse experiments proved the hypothesis that the brain acts as an 'immunoprecipitator'; simultaneous injection of NMDAR1 AB and the non-brain-binding green fluorescent protein AB resulted in high detectability of the former in brain and the latter in CSF

Toward a Self-Updating Platform for Estimating Rates of Speciation and Migration, Ages, and Relationships of Taxa.

Rapidly growing biological data-including molecular sequences and fossils-hold an unprecedented potential to reveal how evolutionary processes generate and maintain biodiversity. However, researchers often have to develop their own idiosyncratic workflows to integrate and analyze these data for reconstructing time-calibrated phylogenies. In addition, divergence times estimated under different methods and assumptions, and based on data of various quality and reliability, should not be combined without proper correction. Here we introduce a modular framework termed SUPERSMART (Self-Updating Platform for Estimating Rates of Speciation and Migration, Ages, and Relationships of Taxa), and provide a proof of concept for dealing with the moving targets of evolutionary and biogeographical research. This framework assembles comprehensive data sets of molecular and fossil data for any taxa and infers dated phylogenies using robust species tree methods, also allowing for the inclusion of genomic data produced through next-generation sequencing techniques. We exemplify the application of our method by presenting phylogenetic and dating analyses for the mammal order Primates and for the plant family Arecaceae (palms). We believe that this framework will provide a valuable tool for a wide range of hypothesis-driven research questions in systematics, biogeography, and evolution. SUPERSMART will also accelerate the inference of a "Dated Tree of Life" where all node ages are directly comparable. [Bayesian phylogenetics; data mining; divide-and-conquer methods; GenBank; multilocus multispecies coalescent; next-generation sequencing; palms; primates; tree calibration.]

CGHnormaliter: a bioconductor package for normalization of array CGH data with many CNAs.

Summary: CGHnormaliter is a package for normalization of array comparative genomic hybridization (aCGH) data. It uses an iterative procedure that effectively eliminates the influence of imbalanced copy numbers. This leads to a more reliable assessment of copy number alterations (CNAs). CGHnormaliter is integrated in the Bioconductor environment allowing a smooth link to visualization tools and further data analysis. Availability and Implementation: The CGHnormaliter package is implemented in R and under GPL 3.0 license available at Bioconductor: http://www.bioconductor.org. Contact: [email protected]. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]

Robust modelling, measurement and analysis of human and animal metabolic systems

Modelling human and animal metabolism is impeded by the lack of accurate quantitative parameters and the large number of biochemical reactions. This problem may be tackled by: (i) study of modules of the network independently; (ii) ensemble simulations to explore many plausible parameter combinations; (iii) analysis of 'sloppy' parameter behaviour, revealing interdependent parameter combinations with little influence; (iv) multiscale analysis that combines molecular and whole network data; and (v) measuring metabolic flux (rate of flow) in vivo via stable isotope labelling. For the latter method, carbon transition networks were modelled with systems of ordinary differential equations, but we show that coloured Petri nets provide a more intuitive graphical approach. Analysis of parameter sensitivities shows that only a few parameter combinations have a large effect on predictions. Model analysis of high-energy phosphate transport indicates that membrane permeability, inaccurately known at the organellar level, can be well determined from whole-organ responses. Ensemble simulations that take into account the imprecision of measured molecular parameters contradict the popular hypothesis that high-energy phosphate transport in heart muscle is mostly by phosphocreatine. Combining modular, multiscale, ensemble and sloppy modelling approaches with in vivo flux measurements may prove indispensable for the modelling of the large human metabolic system. © 2009 The Royal Society

Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies

Background: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue samples is desirable. Taking tissue biopsies after infusion of substrates labeled with stable carbon isotopes makes this possible in animal experiments. However, the appreciable noise level in NMR spectra of extracted tissue samples makes computational estimation of metabolic fluxes challenging and a good method to define confidence regions was not yet available.Results: Here we present a computational analysis method for nuclear magnetic resonance (NMR) measurements of tricarboxylic acid (TCA) cycle metabolites. The method was validated using measurements on extracts of single tissue biopsies taken from porcine heart in vivo. Isotopic enrichment of glutamate was measured by NMR spectroscopy in tissue samples taken at a single time point after the timed infusion o