Investigations on the damage caused by ion etching of SiO2 layers at low energy and high dose

The radiation damage caused by argon ion bombardment during ion etching of thermally grown SiO₂ films at an energy below 1 keV and a dose of about 10¹⁸ cm^?2 has been studied by evaluating MOS C-V curves, FET characteristics, as well as Rutherford ion backscattering spectra. The bombarded samples revealed that ion beam etching in this energy range causes a damaged layer of 5–10 nm thickness at the single crystal silicon surface. Moreover, traces of metal atoms are found in the damaged layer together with argon atoms (≈ 10²¹cm^?3).     

Superconductors with crystalline-field split impurities: Upper critical field and specific heat

We continue the investigation of crystalline-field effects on the properties of superconductors containing rare-earth impurities. Attention is focused on impurities with a nonmagnetic ground state. We calculate the upper critical fieldH _{c 2} and the jump of the specific heat at the phase transition.     

Ermittlung der Sequenzverteilung und Taktizität bei Acrylnitrill/Vinylidenchlorid-Copolymeren

An acrylonitrile/vinylidene chloride copolymer prepared by continuous suspension polymerization in aqueous medium was examined by carbon magnetic resonance at 90.52 MHz. The sequence distribution was evaluated from the diad and tetrad distribution of the methylene carbon regions and from the triad distributions of the other carbon atoms. The stereochemical configuration of the acrylonitrile units was determined from the peaks of the methine and the nitrile carbons which showed a low preference of the isotactic triad against the syndiotactic triad in agreement with freeradical polymerized polyacrylonitrile.     

The molecular mechanism of membrane proteins probed by evanescent infrared waves

The catalytic action of membrane proteins is vital to many cellular processes. Yet the molecular mechanisms remain poorly understood. We describe here the technique of evanescent infrared difference spectroscopy as a tool to decipher the structural changes associated with the enzymatic action of membrane proteins. Functional changes as minute as the protonation state of individual amino acid side chains can be observed and linked to interactions with a ligand, agonist, effector, or redox partner.     

New approaches to biomaterials design

The adoption of combinatorial and computational methods in biomaterials design is a highway towards the discovery and realization of tailored polymeric materials to satisfy the specific requirements of many diverse biomedical or prosthetic applications.     

Conceptual issues in the study of dynamic hazard warnings

This paper presents a conceptual analysis of dynamic hazard warning systems. The normative aspects of responses to warnings are analyzed, and a distinction is made between two forms of responses to a warning system, referred to as compliance and reliance. Determinants of the responses to warnings are identified, and they are broadly classified into normative, task, and operator factors. Existing research on warnings and automation is assessed in view of this conceptual framework, and directions for future research are discussed. Some implications of this analysis for practitioners, designers, and researchers are indicated. Actual or potential applications of this research include recommendations for the analysis, design, and study of dynamic warning systems.     

Stability-based validation of clustering solutions

Data clustering describes a set of frequently employed techniques in exploratory data analysis to extract "natural" group structure in data. Such groupings need to be validated to separate the signal in the data from spurious structure. In this context, finding an appropriate number of clusters is a particularly important model selection question. We introduce a measure of cluster stability to assess the validity of a cluster model. This stability measure quantifies the reproducibility of clustering solutions on a second sample, and it can be interpreted as a classification risk with regard to class labels produced by a clustering algorithm. The preferred number of clusters is determined by minimizing this classification risk as a function of the number of clusters. Convincing results are achieved on simulated as well as gene expression data sets. Comparisons to other methods demonstrate the competitive performance of our method and its suitability as a general validation tool for clustering solutions in real-world problems.     

Start-up activities,individual characteristics,and the regional milieu: Lessons for entrepreneurship support policies from German micro data

This paper contributes to empirical research on the role of regional policy for entrepreneurship by focusing on the link between two stylized facts that emerged from a number of studies for Germany and other countries: Entry rates differ between regions, and the propensity to become an entrepreneur is influenced by socio-demographic variables and attitudes. We develop a theoretical framework to discuss this link, and we test whether for a person of a given age, degree of schooling, attitude towards risk etc. regional variables and, therefore, regional policies, do matter for the decision to start a new business ceteris paribus. Our econometric study is based on data for 10.000 persons from a recent representative survey of the population in ten German planning regions, the Regional Entrepreneurship Monitor (REM). We use a version of the probit model that takes care of the regional stratification of the data, and the results of the nonlinear models are carefully interpreted and illustrated. We find that the propensity to step into self-employment is, among others, higher for males, unemployed, people with contacts to a role model, and with past entrepreneurial experience, who live in more densely populated and faster growing regions with higher rates of new firm formation, while risk aversion and high prices of land have the opposite impact. Interestingly, it does not matter whether the region has a left or right government. However, many implications for entrepreneurship supporting policies in German regions are discussed in the final section.Research for this paper was done as part of the project Regional Entrepreneurship Monitor REM Germany financially supported by the German Research Foundation (DFG STE 628/7-1/2 and WA 610/2-1/2). We thank two anonymous referees and the guest editors of this issue for comments that led to an extensive revision of an earlier version.     

A phenomenological model for the dynamic response of wind turbines to turbulent wind

To predict the average power output of a wind turbine, a response model is proposed which takes into account: (i) the delayed response to the longitudinal wind speed fluctuations; (ii) a response function of the turbine with arbitrary frequency dependence; (iii) wind fields of arbitrary turbulence intensity. In the limit of low turbulence intensity, the dynamical ansatz as proposed in 1992 by Rosen and Sheinman is reproduced. It is shown, how the response function of the turbine can be obtained from simulation experiments of a specific wind turbine. For two idealized situations the dynamic effect of fluctuating wind is estimated at turbulence intensities 0?I_u?0.5. At the special mean wind speed , the turbine response function is determined from simulation data published by Sheinman and Rosen in 1992 and 1994.