High Carb— Erhöhung der Anlassbeständigkeit beim Einsatzhärten

Case hardening is the most important heat treatment process for highly stressed components in engines, gear boxes, machines, etc. Nevertheless some disadvantages prevail, e.g. distortion due to oil quenching, internal oxidation and limited temper resistance up to 200°C in combination with standard case hardening steel grades such as 16MnCr5. In the past efforts were made to remove at least some of the disadvantages mentioned above. The only way to achieve tempering restistance beyond 300°C is swapping to significantly higher alloyed and therefore more expensive case hardening steels (e.g. 15NiMoCr10). Rübig was confronted with numerous customer inquiries regarding possiblities to increase temper restistance by means of case hardening in combination with standard case hardening steel grades like 16MnCr5. As a resul of HighCarb the case hardening steel grade 16MnCr5 yields a surface hardness after tempering at 300°C of approx. 60.5 HRC. An additional benefit is, that HighCarb-treated parts show a very fine grain, no discernible retained austenite (by means of light microscopy) and very little internal oxidation.     

Investigating polymer crystallization by time-dependent light scattering: a direct approach in the data analysis applied for s-polypropylene

We developed a procedure for a direct evaluation of light scattering patterns registered during an isothermal crystallization of s-polypropylene. Analysis is based on the determination of three parameters of the scattering curve for both, polarized and depolarized measuring conditions: (i) the forward scattering intensity I(q→0) (ii) the width Δq of the intensity distribution (iii) the integral intensity in the registration plane, Q₂. We derive equations for these parameters and relate them to the size and the inner structure of the hedrites which develop in s-polypropylene during a crystallization.     

Application of artificial neural networks for classifying lake eutrophication status

Several artificial neural network architectures were ‘trained’ on data from the Eastern Lake Survey – Phase I of the Environmental Protection Agency's National Surface Water Survey in order to investigate which physical–chemical parameters are possibly of greatest importance in determining the eutrophication status of lakes. From the 110 available lake parameters in the Survey, 60 were chosen as input to the neural networks. The traditional eutrophication classification scheme of Vollenweider was used for comparative purposes. The various artificial neural network simulations showed that, in addition to total phosphorus and inorganic nitrogen, turbidity, specific conductance, lake elevation and hydrogen ion concentration were identified as the most significant parameters affecting the classification of lakes in regard to their eutrophication status. These results suggest a conceivable association between these parameters and lake eutrophication, thereby indicating a need for further study on these relationships. A model simulation utilizing an unsupervised neural network did not provide much insight into the lake eutrophication status, but did show that the available physical–chemical lake data could be categorized according to physical region, thereby providing an indication that the lake data used in this study were region‐dependent.     

Unbiased split selection for classification trees based on the Gini Index

Classification trees are a popular tool in applied statistics because their heuristic search approach based on impurity reduction is easy to understand and the interpretation of the output is straightforward. However, all standard algorithms suffer from a major problem: variable selection based on standard impurity measures as the Gini Index is biased. The bias is such that, e.g., splitting variables with a high amount of missing values—even if missing completely at random (MCAR)—are artificially preferred. A new split selection criterion that avoids variable selection bias is introduced. The exact distribution of the maximally selected Gini gain is derived by means of a combinatorial approach and the resulting p-value is suggested as an unbiased split selection criterion in recursive partitioning algorithms. The efficiency of the method is demonstrated in simulation studies and a real data study from veterinary gynecology in the context of binary classification and continuous predictor variables with different numbers of missing values. The proposed method is extendible to categorical and ordinal predictor variables and to other split selection criteria such as the cross-entropy.     

Maximally selected Chi-squared statistics and non-monotonic associations: An exact approach based on two cutpoints

Binary outcomes that depend on an ordinal predictor in a non-monotonic way are common in medical data analysis. Such patterns can be addressed in terms of cutpoints: for example, one looks for two cutpoints that define an interval in the range of the ordinal predictor for which the probability of a positive outcome is particularly high (or low). A Chi-squared test may then be performed to compare the proportions of positive outcomes in and outside this interval. However, if the two cutpoints are chosen to maximize the Chi-squared statistic, referring the obtained Chi-squared statistic to the standard Chi-squared distribution is an inappropriate approach. It is then necessary to correct the p-value for multiple comparisons by considering the distribution of the maximally selected Chi-squared statistic instead of the nominal Chi-squared distribution. The exact distribution of the Chi-squared statistic obtained with the two optimal cutpoints is derived based on combinatorial considerations. This approach is illustrated by a simulation study and an application to varicella data.     

Pattern formation in a horizontally shaken granular submonolayer

We study the mechanism leading to the formation of stripe-like patterns in a rectangular container filled with a sub-monolayer of frictional spherical particles when it is subjected to horizontal oscillations. By means of Molecular Dynamics simulations we could reproduce the experimental results. Systematic simulations allow to identify friction to be responsible for the pattern formation, that is, the tangential interaction between contacting particles and between the particles and the floor of the container. When particles are in contact with the floor and other adjacent particles simultaneously, there emerges a frustrated situation in which the particles are prevented from rolling on the floor. This effect leads to local jamming and eventually to stripe-like pattern formation. In the long time evolution, the stripes are unstable. Stripes may merge as well as disintegrate.     

The 2.2 A crystal structure of human chymase in complex with succinyl-Ala-Ala-Pro-Phe-chloromethylketone: structural explanation for its dipeptidyl carboxypeptidase specificity

Human chymase (HC) is a chymotrypsin-like serine proteinase expressed by mast cells. The 2.2 A crystal structure of HC complexed to the peptidyl inhibitor, succinyl-Ala-Ala-Pro-Phe-chloromethylketone (CMK), was solved and refined to a crystallographic R-factor of 18.4 %. The HC structure exhibits the typical folding pattern of a chymotrypsin-like serine proteinase, and shows particularly similarity to rat chymase 2 (rat mast cell proteinase II) and human cathepsin G. The peptidyl-CMK inhibitor is covalently bound to the active-site residues Ser195 and His57; the peptidyl moiety juxtaposes the S1 entrance frame segment 214-217 by forming a short antiparallel beta-sheet. HC is a highly efficient angiotensin-converting enzyme. Modeling of the chymase-angiotensin I interaction guided by the geometry of the bound chloromethylketone inhibitor indicates that the extended substrate binding site contains features that may generate the dipeptidyl carboxypeptidase-like activity needed for efficient cleavage and activation of the hormone. The C-terminal carboxylate group of angiotensin I docked into the active-site cleft, with the last two residues extending beyond the active site, is perfectly localized to make a favorable hydrogen bond and salt bridge with the amide nitrogen of the Lys40-Phe41 peptide bond and with the epsilon-ammonium group of the Lys40 side-chain. This amide positioning is unique to the chymase-related proteinases, and only chymases from primates possess a Lys residue at position 40. Thus, the structure conveniently explains the preferred conversion of angiotensin I to angiotensin II by human chymase.     

Multinationals and regional indigenous development

We investigate in how far foreign multinationals have fostered regional indigenous development in Ireland. Specifically, we examine whether foreign presence has induced indigenous plant entry within the same regions and in bordering regions. To this end we employ an entry rate model on an exhaustive panel level data set for Irish manufacturing plants. Our results show that multinationals can foster local development both within and in surrounding regions, although the extent of these effects varies between policy preferential and non-preferential regions.Received: December 2002/Accepted: January 2004This research has benefited from financial support through the RTN research project Specialization versus diversification: the microeconomics of regional development and the spatial propagation of macroeconomic shocks in Europe of the European Commission (grant No. HPRN-CT-2000-00072). We would like to thank Rosella Nicolini for helpful comments. The second author gratefully acknowledges financial support from the Belgian FNRS and the third author acknowledges support from a Marie Curie grant. Usual disclaimers apply.     

The generation of SAR layover and shadow maps from digitalelevation models

As almost fully automated techniques as well as expert systems obtain more and more importance in the geocoding of synthetic aperture radar (SAR) images, the solution to the problem of the identification of homologue points between the SAR image and reference system moves into the fields of pattern recognition and feature matching. Shadow regions, which appear as dark regions in the SAR image, are independent from the backscattering of the imaged terrain. Due to the multiplicity of signals, layover regions appear brighter than the surrounding regions. Hence, the phenomena of layover and shadow are stressed in the present paper. The reasons for their occurrence are studied through the digital elevation model representing the Earth's surface. An algorithm to define layover and shadow regions directly in the geometry of the digital elevation model is presented. The results are given in a so-called layover and shadow map     

Social and Individual Coping With Threats: Outlines of an Interdisciplinary Approach.

Referring to a general conception of coping as an adaptive reaction to a perceived is-ought discrepancy, the authors present an interdisciplinary perspective on coping processes. Based on systems theory, a psychological view is compared with a sociological perspective, focusing structural equivalencies between social and individual adaptational processes. Defensive, proactive, and accommodative reactions are discussed as 3 general modes of coping. It is argued that all of these coping reactions in both individuals and social systems have specific costs and benefits, which are particularly visible if the interaction and "interpenetration" between the coping strategies of individuals and social systems are observed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)