Auditory system plasticity in children after long periods of complete deafness

Separation and identification of proteins by two-dimensional (2-D) electrophoresis can be used for protein-based gene expression analysis. In this report single protein spots, from polyvinylidene difluoride blots of micropreparative E. coli 2-D gels, were rapidly and economically identified by matching their amino acid composition, estimated pI and molecular weight against all E. coli entries in the SWISS-PROT database. Thirty proteins from an E. coli 2-D map were analyzed and identities assigned. Three of the proteins were unknown. By protein sequencing analysis, 20 of the 27 proteins were correctly identified. Importantly, correct identifications showed unambiguous "correct" score patterns. While incorrect protein identifications also showed distinctive score patterns, indicating that protein must be identified by other means. These techniques allow large-scale screening of the protein complement of simple organisms, or tissues in normal and disease states. The computer program described here is accessible via the World Wide Web at URL address (http:@expasy.hcuge.ch/).     

Induced candidosis in mice with artificially established oral flora

The aim of this study was to gauge the effect of an artificially established flora, unnatural for mice, on the induction of oral candidosis in mice. Four groups of BALB/c mice were compared; conventional Candida albicans-free mice, "germ-free" mice which had been inoculated with Candida-free human saliva, germ-free mice which had been exposed to a cocktail of Streptococcus mitis, S. sobrinus and S. sanguis, and uncontaminated germ-free mice. After exposure to C. albicans via drinking water, the four groups of mice were killed and their oral cavities examined for candidal growth and oral lesions. Conventional mice yielded significantly less candidal growth and exhibited significantly fewer oral lesions than the other three groups. Candidal lesions in the two groups of contaminated germ-free mice were significantly fewer than in the uncontaminated germ-free mice. The latter exhibited extensive candidal lesions with little inflammatory infiltrate. It is concluded that mice with human oral micro-organisms have some resistance against candidal infection albeit at a reduced level, that mice with natural oral flora are highly resistant, and that germ-free mice are extremely susceptible to C. albicans infection.     

Yearly stepwise increments of the growth hormone dose results in a better growth response after four years in girls with Turner syndrome. Dutch Working Group on Growth Hormone

To optimize the growth promoting effect of growth hormone (GH), 65 previously untreated girls with Turner syndrome (TS), chronological age (CA) 2-11 yr, were randomized into 3 dosage regimen groups: A, B, and C, with a daily recombinant-human GH dose during 4 study years of 4-4-4-4, 4-6-6-6, and 4-6-8-8 IU/m2 b.s. The first GH dosage increase in groups B and C resulted in a significantly higher mean height velocity (HV) compared with constant dose group A. During the third year, when the dose was raised again only in group C, mean HV was significantly higher in groups B and C than in group A, and in group C compared with group B. In year 4 only group C mean HV remained significantly higher than group A. The pattern of change in HSDSCA (Dutch-Swedish-Danish Turner references) was identical; however, in year 4 mean delta HSDSCA in group B also remained significantly higher than group A. After 4 yr GH treatment, the following was determined. 1) The mean delta HSDSCA was significantly higher for groups B and C compared with group A, but not significantly different between groups B and C. 2) Although significantly higher compared with estimated values for untreated Dutch girls with TS, bone maturation of the GH treated girls was not significantly different between groups. 3) It was positively related with the degree of bone age (BA) retardation at start of study and negatively with baseline CA. 4) Both the modified Index of Potential Height (mIPHRUS) and a recently developed Turner-specific final height (FH) prediction method (PTSRUS), based on regression coefficients for H, CA, and bone age, showed significant increases in mean FH prediction, without significant differences between groups. PTSRUS values were markedly higher than the mIPHRUS values. Dose dependency could be shown for the area under the curve (AUC) for GH, but delta HSDSCA was not linearly related with AUC. Baseline GH binding protein (BP) levels were in 84% of the cases within the normal age range; the decrease in mean levels after 6 months GH was not significant. Mean insulin-like growth factor I (IGF-I) and IGFBP-3 plasma levels increased significantly, without significant differences between groups. delta HSDSCA during GH was dependent on IGF-I plasma levels at baseline and during the study period, beta-0.002 and beta-0.0004. Thus, a stepwise GH-dosing approach reduced the "waning" effect of the growth response after 4 yr treatment without undue bone maturation. FH prediction was not significantly different between treatment groups. Irrespective of the GH dose used, initiation of GH treatment at a younger age was beneficial after 4 yr GH when expressed as actual cm gained or as gain in FH prediction, but was not statistically significant when expressed as delta HSDSCA over the study period.     

Nested multigrid methods for time-periodic,parabolic optimal control problems

We present a nested multigrid method to optimize time-periodic, parabolic, partial differential equations (PDE). We consider a quadratic tracking objective with a linear parabolic PDE constraint. The first order optimality conditions, given by a coupled system of boundary value problems can be rewritten as an Fredholm integral equation of the second kind, which is solved by a multigrid of the second kind. The evaluation of the integral operator consists of solving sequentially a boundary value problem for respectively the state and the adjoints. Both problems are solved efficiently by a time-periodic space-time multigrid method.     

Ensemble classification based on generalized additive models

Generalized additive models (GAMs) are a generalization of generalized linear models (GLMs) and constitute a powerful technique which has successfully proven its ability to capture nonlinear relationships between explanatory variables and a response variable in many domains. In this paper, GAMs are proposed as base classifiers for ensemble learning. Three alternative ensemble strategies for binary classification using GAMs as base classifiers are proposed: (i) GAMbag based on Bagging, (ii) GAMrsm based on the Random Subspace Method (RSM), and (iii) GAMens as a combination of both. In an experimental validation performed on 12 data sets from the UCI repository, the proposed algorithms are benchmarked to a single GAM and to decision tree based ensemble classifiers (i.e. RSM, Bagging, Random Forest, and the recently proposed Rotation Forest). From the results a number of conclusions can be drawn. Firstly, the use of an ensemble of GAMs instead of a single GAM always leads to improved prediction performance. Secondly, GAMrsm and GAMens perform comparably, while both versions outperform GAMbag. Finally, the value of using GAMs as base classifiers in an ensemble instead of standard decision trees is demonstrated. GAMbag demonstrates performance comparable to ordinary Bagging. Moreover, GAMrsm and GAMens outperform RSM and Bagging, while these two GAM ensemble variations perform comparably to Random Forest and Rotation Forest. Sensitivity analyses are included for the number of member classifiers in the ensemble, the number of variables included in a random feature subspace and the number of degrees of freedom for GAM spline estimation.     

Information and communication technologies in the life of university freshmen: An analysis of change

The passage from secondary school to university puts students in an environment with different expectations. Not only the expectations towards learning might change, but also towards ICT competences and computer use. The purpose of this article is to find out whether freshmen, after 6 months at the university, changed their self-perception of ICT competences and computer use in comparison with their behaviour at secondary school, and what factors can explain the self-perception of ICT competences and computer use in secondary school, in the university and their possible change. Based on a panel research among 714 freshmen of a large university, this article answers the following questions: (1) What is the self-perception of ICT competences among freshmen and is there a change in this self-perception 6 months after entering the university? (2) How often and for what purpose do freshmen use a computer and is there a change in the frequency of the use of a computer? (3) What factors might influence this attitude, behaviour, and possible change? In function of the basic components of Unified Theory of Acceptance and Use of Technology (Venkatesh, Morris, Davis, & Davis, 2003) hypotheses was developed and tested to answer these questions. Students who consider the computer to be a useful instrument, have control over the computer, possess a certain level of Internet competence, and are at ease with computers are more likely to have the skills needed to maintain a computer, to develop a web site, and to use basic ICT skills. The predictors have little influence on Internet usage. The same predictors contribute modestly to the explanation of the different frequencies of computer use, and a few of the predictors explain parts of change in ICT skills and frequency of computer use.     

Illustrative stream surfaces

Stream surfaces are an intuitive approach to represent 3D vector fields. In many cases, however, they are challenging objects to visualize and to understand, due to a high degree of self-occlusion. Despite the need for adequate rendering methods, little work has been done so far in this important research area. In this paper, we present an illustrative rendering strategy for stream surfaces. In our approach, we apply various rendering techniques, which are inspired by the traditional flow illustrations drawn by Dallmann and Abraham \& Shaw in the early 1980s. Among these techniques are contour lines and halftoning to show the overall surface shape. Flow direction as well as singularities on the stream surface are depicted by illustrative surface streamlines. ;To go beyond reproducing static text book images, we provide several interaction features, such as movable cuts and slabs allowing an interactive exploration of the flow and insights into subjacent structures, e.g., the inner windings of vortex breakdown bubbles. These methods take only the parameterized stream surface as input, require no further preprocessing, and can be freely combined by the user. We explain the design, GPU-implementation, and combination of the different illustrative rendering and interaction methods and demonstrate the potential of our approach by applying it to stream surfaces from various flow simulations. ;     

Automated bidding in computational markets: an application in market-based allocation of computing services

Autonomous agents are widely applied to automate interactions in robotics, e.g. for selling and purchasing goods on eBay, and in financial markets, e.g. in the form of quote machines and algorithmic traders. Current research investigates efficient economic mechanisms that fully automate the provisioning and usage processes of Grid-based services. On the one hand, consumers want to allocate resources on demand for their various applications, e.g. data sharing, stream processing, email, business applications and simulations. On the other hand, providers of Grid services want to govern business policies to meet their utilization and profit goals. The above-mentioned processes are not manually manageable, however, because decisions need to be taken within milliseconds. Therefore, such processes have to be automated to minimize human interactions. Hence, market mechanisms and strategic behavior play important roles when it comes to achieving automated and efficient allocation of Grid services. The paper begins by presenting a framework for automated bidding, providing a methodology for the design and implementation of configurable bidding strategies. Second, it presents a novel bidding strategy based on a reinforcement learning technique. This strategy is designed to automate the bid generation processes of consumers and providers in various market mechanisms. Third, the behavior and convergence of the strategy is evaluated in a centralized Continuous Double Auction and a decentralized on-line machine scheduling mechanism against selected benchmark bidding strategies. Fourth, we define a bidding language for communicating consumer and provider preferences to the market as well as report back the match of the market-based allocation process.     

Miniaturized ceramic differential scanning calorimeter with integrated oven and crucible in LTCC technology

A miniaturized ceramic differential scanning calorimeter (MC-DSC) with integrated oven and crucible is presented. Despite its small size of only 11 mm × 39 mm × 1.5 mm, all functions of a conventional DSC apparatus are integrated in this novel device - including the oven. The MC-DSC is fully manufactured in thick-film and green glass ceramic tape-based low temperature co-fired ceramics (LTCC) technology. Therefore, production costs are considered to be low. Initial results using indium as a sample material show a good dynamic performance of the MC-DSC. Full width at half maximum of the melting peak is 2.4 °C (sample mass approx. 11 mg, heating rate approx. 50 °C/min). Repeatability of the indium melting point is within ±0.02 °C. The melting peak area increases linearly with the sample mass up to at least 26 mg. Simulations of a strongly simplified finite element model of the MC-DSC are in a good agreement with measurement results allowing a model-based prediction of its basic characteristics.