Newly Isolated Animal Pathogen Corynebacterium silvaticum Is Cytotoxic to Human Epithelial Cells

Corynebacterium silvaticum is a newly identified animal pathogen of forest animals such as roe deer and wild boars. The species is closely related to the emerging human pathogen Corynebacterium ulcerans and the widely distributed animal pathogen Corynebacterium pseudotuberculosis. In this study, Corynebacterium silvaticum strain W25 was characterized with respect to its interaction with human cell lines. Microscopy, measurement of transepithelial electric resistance and cytotoxicity assays revealed detrimental effects of C. silvaticum to different human epithelial cell lines and to an invertebrate animal model, Galleria mellonella larvae, comparable to diphtheria toxin-secreting C. ulcerans. Furthermore, the results obtained may indicate a considerable zoonotic potential of this newly identified species.     

The Nexus of Corporate Entrepreneurship and Radical Innovation

This paper explores the linkage between the entrepreneurial orientation of established firms and the development of radical innovation. Through five case studies in firms involved in radical innovation, three propositions are developed, suggesting that proactiveness, risk‐taking and autonomy stimulate the development of radical innovation, whereas competitive aggressiveness does not necessarily do so, as radical innovations are directed towards the creation of entirely new arenas of business, where existing competitors are not present.     

Three-dimensional MHD high-resolution computations with CWENO employing adaptive mesh refinement

Until recently, numerical simulations of discontinuities in highly super-Alfvénic plasmas have been severely limited by comparatively crude resolution and accuracy. Significant progress in the numerical simulation of such plasmas was achieved with the recently implemented Central Weighted Essentially Non-Oscillatory (CWENO) scheme. Combining this technique with that of adaptive mesh refinement (AMR), we have developed a third-order numerical scheme, which is able to efficiently capture strong gradients on spatial scales being small compared to the overall scale of the plasma system considered. Here, we first describe important algorithmic aspects of the scheme as well as the physics included in it. Second, we present the results of various performance tests. And, third, we illustrate its application to ‘real world problems’ using the example of the dynamics of a Sedov-type explosion.     

Probability-based current dipole localization from biomagneticfields

Focal biomagnetic sources are described as pointlike current dipoles. The dipole parameters, position, and moment coordinates are commonly determined from biomagnetic data using iterative nonlinear optimization algorithms such as the Levenberg-Marquardt algorithm. However, even for single-dipole sources, mislocalizations can occur due to side minima of the cost function or due to a wrong choice of the start vector. This can be shown by introducing a cost function where the independent variables are only the position coordinates instead of position and moment coordinates. This dimensional reduction-which is also possible for multiple dipole sources-is achieved by calculating the cost function at each position with the position and data-dependent, optimum dipole moments. The authors call these dipoles with-in a least squares sense-optimum moments, locally optimal dipoles. The visualization of such a single-dipole cost function and of the iteration steps of the Levenberg-Marquardt algorithm show why mislocalizations cannot be avoided. Therefore, the authors propose an alternative noniterative localization algorithm for single-dipole sources without this drawback. It uses localization probabilities calculated by means of the locally optimal dipoles. Besides the determination of the dipole parameters, the proposed algorithm furnishes a reliable error for each localization. Its effectiveness is shown with simulated and real patient data     

Cutting stress off at the pass: Reducing vigilance and responsiveness to social threat by manipulating attention.

Personality processes relating to social perception have been shown to play a significant role in the experience of stress. In 5 studies, the authors demonstrate that early stage attentional processes influence the perception of social threat and modify the human stress response. The authors first show that cortisol release in response to a stressful situation correlates with selective attention toward social threat. Second, the authors show in 2 laboratory studies that this attentional pattern, most evident among individuals with low self-esteem, can be modified with a repetitive training task. Next, in a field study, students trained to modify their attentional pattern to reduce vigilance for social threat showed lower self-reported stress related to their final exam. In a final field study with telemarketers, the attentional training task led to increased self-esteem, decreased cortisol and perceived stress responses, higher confidence, and greater work performance. Taken together, these results demonstrate the impact of antecedent-focused strategies on the late-stage consequences of social stress. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Isolation and Spectroscopic Characterization of Eu@C72

A new Eu-endohedral fullerene cage, namely, Eu@C₇₂, was synthesized, separated, and a single isomer, Eu@C₇₂-I, has been isolated by multi-step HPLC for the first time and characterized by LDI-TOF mass spectrometry, UV-Vis and EPR spectroscopy. Additionally, a second isomer, Eu@C₇₂-II, has been separated by HPLC and identified by LDI-TOF mass spectrometry.     

Numerical simulation model for exhaust gas transportation of dust in the BOF

During the BOF process for the production of crude steel, the specific amount of dust emitted is of the order of 2 % of the steel weight at turn down. The process gas conveys the dust through the boiler system into the primary and secondary dust catchers. The transportation of dust particles is influenced by blowing parameters; physical properties of process gas and of dust phases; and, type and layout of the converter and the filter system. In this work, a numerical simulation model is developed that simulates the pneumatic conveyance and sedimentation of primarily coarse dust particles in the BOF gas cleaning system. Comparison is then made of predicted coarse dust characteristics with values for dust sampled from an existing plant in order to verify the plausibility of the developed model.