Chlorinated phenols in human milk

The paper deals with the contamination of human milk with chlorinated phenols. The average and median concentrations of the chlorophenols investigated ranged from 0.75 to 9.74 g.kg^–1 and from being not detectable to 5.62 g.kg^–1, respectively, for the different compounds. The highest average and median levels were found for pentachlorophenol and 2,4,5-trichlorophenol. The concentrations determined were below the permissible levels.     

Discrete element analysis of experiments on mixing and stoking of monodisperse spheres on a grate

Understanding the details of the mixing and stoking process on grate firing systems is crucial for the optimization of the combustion process in waste or biomass incineration plants. The Discrete Element Method (DEM) can help to obtain further information on the mixing process within a bed of fuel particles. Especially the influence of a change in operational parameters can be examined avoiding large experimental effort. In the current paper five simulations for a generic grate are compared with the corresponding experiments. The experiments were carried out throughout an anterior parameter study on mixing and stoking on a grate [Sudbrock F.; Simsek E.; Wirtz S.; Scherer V.: “An experimental analysis of the influence of operational parameters on mixing and stoking of a monodisperse granulate on a grate”, Powder Technology 198, Issue 1, 29-37, 2010] [19]. The system considered is equipped with vertically moving bars which induce stoking. In a first approach monodisperse plastic spheres are used. The grate is encased by a transparent polycarbonate housing which provides optical access to the movement of the particles in the wall planes. The mixing process is measured and quantified by image analysis of the front wall of the grate. The mixing behaviour of the particle assembly observed in experiments and simulation appears to be very similar indicating that DEM is able to predict the particle mixing in the bed. In order to quantify the visual observations the mixing behaviour has been evaluated by different mixing parameters. They are compared in dependence of the number of strokes of the grate bars. A good agreement between measurements and simulations could be observed.     

Applying Petri Nets to Modeling of Many-Core Processor Self-Testing when Tests are Performed Randomly

Today’s many-core processors are manufactured in inherently unreliable technologies. Massively defective technologies used for production of many-core processors are the direct consequence of the feature size shrinkage in today’s CMOS (complementary metal-oxide-semiconductor) technology. Due to these reliability problems, fault-tolerance of many-core processors becomes one of the major challenges. To reduce the probability of failures of many-core processors various fault tolerance techniques can be applied. The most preferable and promising techniques are the ones that can be easily implemented and have minimal cost while providing high level of processor fault tolerance. One of the promising techniques for detection of faulty cores, and consequently, for performing the first step in providing many-core processor fault tolerance is mutual testing among processor cores. Mutual testing can be performed either in a random manner or according to a deterministic scheduling policy. In the paper we deal with random execution of mutual tests. Effectiveness of such testing can be evaluated through its modeling. In the paper, we have shown how Stochastic Petri Nets can be used for this purpose and have obtained some results that can be useful for developing and implementation of testing procedure in many-core processors.     

EELS microanalysis of polycrystalline silicon thin films for solar cells grown at low temperatures

The aim of this work is the quantitative chemical analysis of polycrystalline silicon thin films grown on glass substrates at temperatures <600°C by means of transmission electron microscopy (TEM) and electron energy-loss spectrometry (EELS). Specimens produced with two different methods were investigated. We found significant differences in grain size and morphology, as well as in the distribution of oxygen. A surprisingly high amount of Ba diffusion from the subtrate was detected.     

Zur Querkraftbemessung von Stahlbetonträgern

Shear Design of Structural Concrete Girders Today, shear design is carried out using uniform models; the basis for this was laid 100 years ago and since the 1960's theoretically substantiated by the work in the field of the theory of plasticity. In recent investigations the models were extended with respect to compatibility of deformations as well as to the determination of the effective concrete compressive strength. This contribution gives an overview on these developments and demonstrates how the models can be used in design and detailing.     

Dispirooxindole-β-Lactams: Synthesis via Staudinger Ketene-Imine Cycloaddition and Biological Evaluation

In this work, we present the first synthesis of dispirooxindole-β-lactams employing optimized methodology of one-pot Staudinger ketene-imine cycloaddition with N-aryl-2-oxo-pyrrolidine-3-carboxylic acids as the ketene source. Spiroconjugation of indoline-2-one with β-lactams ring is considered to be able to provide stabilization and wide scope of functionalization to resulting scaffolds. The dispipooxindoles obtained demonstrated medium cytotoxicity in the MTT test on A549, MCF7, HEK293, and VA13 cell lines, and one of the compounds demonstrated antibacterial activity against E. coli strain LPTD.     

Data Parallel Implementation of Belief Propagation in Factor Graphs on Multi-core Platforms

We investigate data parallel techniques for belief propagation in acyclic factor graphs on multi-core systems. Belief propagation is a key inference algorithm in factor graph, a probabilistic graphical model that has found applications in many domains. In this paper, we explore data parallelism for basic operations over the potential tables in belief propagation. Data parallel techniques for these table operations are developed for shared memory platforms. We then propose a complete belief propagation algorithm using these table operations to perform exact inference in factor graphs. The proposed algorithms are implemented on state-of-the-art multi-socket multi-core systems with additional NUMA-aware optimizations. Our proposed algorithms exhibit good scalability using a representative set of factor graphs. On a four-socket Intel Westmere-EX system with 40 cores, we achieve 39.5 $\times $ speedup for the table operations and 39 $\times $ speedup for the complete algorithm using factor graphs with large potential tables.     

Machine learning for human movement understanding

Main purpose of this project is to develop fundamental technology for assist robots to recover and maintain human motor skill and to extend scope of human activity. Our goal is to provide a system that adapts to its user’s personal behavior patterns in real-time. We aim to develop a continuous collaboration system between the assist robots and the user where both alternatively adjust to each other to maximize the system’s utility. To understand human movement, we recorded motion sequence of several tasks for different subjects using motion capture system. Through analysis of human motion data, we extracted a general model by rule-based approach. On the other hand, since such tasks are not feasible with static models, we investigate the potential benefit of supervised online learning in the task of online action classi?cation and Deep Learning in the task of acquiring human motion. Finally, developed system was extended to show its potential effect in ergonomics and in assist robotics.