Multidimensional scaling with discrimination coefficients for supervised visualization of high-dimensional data

Visualization techniques for high-dimensional data sets play a pivotal role in exploratory analysis in a wide range of disciplines. A particularly challenging problem represents gene expression data based on microarray technology where the number of features (genes) typically exceeds 20,000, whereas the number of samples is frequently below 200. We investigated class-specific discrimination coefficients for each feature and each pair of classes for an effective nonlinear mapping to lower-dimensional space. We applied the technique to three microarray data sets and compared the projections to two-dimensional space with the results from a conventional multidimensional scaling method, a score plot resulting from principal component analysis, and projections from linear discriminant analysis. In the experiments, we observed that the discrimination coefficients allowed for an improved visualization of high-dimensional genomic data.     

Screening for New Inhibitors of Glycine Transporter 1 and 2 by Means of MS Binding Assays

A straightforward screening of a compound library comprising 2439 substances for the identification of new inhibitors for the neurotransmitter transporters GlyT1 and GlyT2 is described. Screening and full-scale competition experiments were performed using recently developed GlyT1 and GlyT2 MS Binding Assays. That way for both targets, GlyT1 and GlyT2, ligands were identified, which exhibited affinities (pK_i values) in the low micromolar to sub-micromolar range. The majority of these binders exhibit new chemical scaffolds in the class of GlyT1 and GlyT2 inhibitors, which could be of interest for the development of new ligands with improved affinities for the target proteins. Additionally, compounds with excellent fluorescent properties were found for GlyT2, which renders them promising compounds for future fluorescence-based techniques. All in all, this study demonstrates that MS Binding Assays represent a powerful technology platform also well suited for the screening of compound libraries in a highly reliable and effective manner.     

Impairment of probabilistic reward-based learning in schizophrenia.

Recent models assume that some symptoms of schizophrenia originate from defective reward processing mechanisms. Understanding the precise nature of reward-based learning impairments might thus make an important contribution to the understanding of schizophrenia and the development of treatment strategies. The present study investigated several features of probabilistic reward-based stimulus association learning, namely the acquisition of initial contingencies, reversal learning, generalization abilities, and the effects of reward magnitude. Compared to healthy controls, individuals with schizophrenia exhibited attenuated overall performance during acquisition, whereas learning rates across blocks were similar to the rates of controls. On the group level, persons with schizophrenia were, however, unable to learn the reversal of the initial reward contingencies. Exploratory analysis of only the subgroup of individuals with schizophrenia who showed significant learning during acquisition yielded deficits in reversal learning with low reward magnitudes only. There was further evidence of a mild generalization impairment of the persons with schizophrenia in an acquired equivalence task. In summary, although there was evidence of intact basic processing of reward magnitudes, individuals with schizophrenia were impaired at using this feedback for the adaptive guidance of behavior. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling mass loading effects in industrial cyclones by a combined Eulerian–Lagrangian approach

Cyclone separation is studied by means of numerical simulations. While the gas flow is modeled by a modified Reynolds stress (RS) model, the behavior of the particles is pictured by a combined Eulerian–Lagrangian approach. A mono-disperse Eulerian particle phase is utilized to account for inter-particle collisions, while the effects of fractional separation and particle-wall collisions are considered by poly-disperse Lagrangian particles. The above particle models interact in two ways. On the one hand, the Lagrangian particles determine the local mean diameter of the substitute Eulerian particle class. On the other hand, especially in regions of high particle concentration, the Eulerian particle phase exerts an additional collisional force onto the Lagrangian particle trajectories. An industrial cyclone is chosen as a test case and the numerical results are evaluated with respect to pressure drop as well as to global and fractional separation efficiency. In this context the influence of the cyclone’s mass loading and wall roughness is highlighted. Simulations indicate that the separation efficiency improves with increasing mass loading until an excess loading is reached while at the same time the pressure drop is reduced. Furthermore, it can be shown that rough walls lead to a reduction of separation efficiency while simultaneously the pressure drop decreases. The simulations results are compared with both an analytic theory of Muschelknautz [Die Berechnung von Zykonabscheidern für Gase. Chem Ing Techn 44, (1+2):63–71, 1972] as well as with real plant measurements.     

Feasibility of particle board production using bone glue

This feasibility study describes a new procedure for bonding particle boards using animal protein glue produced from bone. Making use of the thermoplastic properties of bone glue, particle boards with mechanical properties partly comparable to a MUF-bonded reference board were obtained at laboratory scale.     

Performance of laboratories in speciation analysis in seafood – Case of methylmercury and inorganic arsenic

The international measurement evaluation program (IMEP) has together with the European Reference Laboratory for Heavy Metals in Feed and Food (EU-RL-HM) carried out two interlaboratory comparisons (ILC) in 2010 on the measurement of trace metals, as well as methylmercury and inorganic arsenic in seafood. In IMEP-109 only EU National Reference Laboratories (NRL) took part, while IMEP-30 was open to all laboratories. In this article only methylmercury and inorganic arsenic analysis will be discussed, as these appear generally to be more problematic measurands. They are also particularly interesting to legislators, as no maximum limits have been set yet for them in European legislation. The aim of the two ILCs was to produce more information to help tackling this issue. The results of the two exercises were pooled together, evaluated, and compared with former ILC projects for methylmercury and inorganic arsenic analysis. Results for inorganic arsenic were spread, but not method dependant. The measurand seems to be difficult to analyse in this matrix and possible method issues were identified. Methylmercury results were satisfactory, but not many laboratories perform this type of analysis because it is generally believed that specific instrumentation is needed. As an answer to this presumption, alternatives are suggested.     

Analyzing IT business values – A Dominance based Rough Sets Approach perspective

The impact of information technology (IT) on the business value of a cooperation has been an active research area for more than two decades. Although it is widely agreed that IT has a positive impact on the business values of cooperations an in-depth understanding of the underlying structures is still missing. Especially due to the huge investments in IT, there is still a need to better understand how IT influences the performance of cooperations and business values. Generally, the data collected in IT business value research to be quantitative as well as of qualitative nature. While quantitative data can be examined by classic econometric methods the analysis of qualitative data requires special methods. In the case of ordinal data DRSA – Dominance based Rough Sets Approach has been proposed. DRSA can be applied to induce rules out of a decision table containing ordinal data. This method has already successfully applied to such diverse areas like customer relationship management and satisfaction analysis, or the technical diagnostic of a fleet of vehicles besides others. In this article we apply it for the first time to the analysis of IT business value. We use ordinal data of a survey on IT management strategies of Australian firms conducted by the Australian Department of Communications, Information Technology and the Arts. The induces rules are interpreted and provide important insights into the impact of information technology on the business values of cooperations. Furthermore our study shows the potential of DRSA for information systems research where questionnaire are a widely applied technique to collect ordinal data.     

Thin and Dense Ceramic Coatings by Plasma Spraying at Very Low Pressure

The very low pressure plasma spray (VLPPS) process operates at a pressure range of approximately 100 Pa. At this pressure, the plasma jet interaction with the surrounding atmosphere is very weak. Thus, the plasma velocity is almost constant over a large distance from the nozzle exit. Furthermore, at these low pressures the collision frequency is distinctly reduced and the mean free path is strongly increased. As a consequence, at low pressure the specific enthalpy of the plasma is substantially higher, but at lower density. These particular plasma characteristics offer enhanced possibilities to spray thin and dense ceramics compared to conventional processes which operate in the pressure range between 5 and 20 kPa. This paper presents some examples of gas-tight and electrically insulating coatings with low thicknesses <50 μm for solid oxide fuel cell applications. Furthermore, plasma spraying of oxygen conducting membrane materials such as perovskites is discussed.     

Beitr?ge zur Refraktometrie des Milchserums nach Ackermann

Ohne ZusammenfassungMitteilung aus der K. K. Allgem. Untersuchungsanstalt für Lebensmittel in Innsbruck. (Vorstand: Prof. Dr. Alois Lode.)