Adaptive Multiresolution Methods for the Simulation of Waves in Excitable Media

We present fully adaptive multiresolution methods for a class of spatially two-dimensional reaction-diffusion systems which describe excitable media and often give rise to the formation of spiral waves. A novel model ingredient is a strongly degenerate diffusion term that controls the degree of spatial coherence and serves as a mechanism for obtaining sharper wave fronts. The multiresolution method is formulated on the basis of two alternative reference schemes, namely a classical finite volume method, and Barkley’s approach (Barkley in Phys. D 49:61–70, 1991), which consists in separating the computation of the nonlinear reaction terms from that of the piecewise linear diffusion. The proposed methods are enhanced with local time stepping to attain local adaptivity both in space and time. The computational efficiency and the numerical precision of our methods are assessed. Results illustrate that the fully adaptive methods provide stable approximations and substantial savings in memory storage and CPU time while preserving the accuracy of the discretizations on the corresponding finest uniform grid.     

Long-term behaviour of a two-stage CW system regarding nitrogen removal

In the first two years of operation a nitrogen removal efficiency of 53% and a high average elimination rate of 1,000 g N m(-2) yr(-1) could be observed for a two-stage vertical flow (VF) constructed wetland (CW) system. The two-stage system consists of two VF beds with intermittent loading operated in series, each stage having a surface area of 10 m2. The first stage uses sand with a grain size of 2-3.2 mm for the 50 cm main layer and has a drainage layer that is impounded; the second stage sand with a grain size of 0.06-4 mm and a conventional drainage layer (with free drainage). The two-stage VF system was designed for and operated with an organic load of 40 g COD m(-2) d(-1) (i.e. 2 m2 per person equivalent). Data from the following years of operation showed that from the third year nitrogen elimination increased and stabilized. The median values of the nitrogen elimination rate in the first five years of operation have been 3.51, 2.76, 4.20, 3.84 and 4.07 g N m(-2) d(-1), the median value of the last three years being 3.8 g N m(-2) d(-1) and 1,380 g N m(-2) yr(-1), respectively, and the nitrogen removal > 60%. It can be assumed that the vegetation as well as the biofilm development in the two-stage VF CW system plays the major role for the enhancement of the nitrogen elimination rate.     

Mixed hierarchical-functional fault models for targeting sequential cores

Current work presents a set of fault models allowing high coverage for sequential cores in systems-on-a-chip. We propose a novel approach combining a hierarchical fault model for functional blocks, a functional fault model for multiplexers and a mixed hierarchical-functional fault model for comparison operators, respectively. The fault models are integrated into a fast high-level decision diagram based test path activation tool. According to the experiments, the proposed method significantly outperforms state-of-the-art test pattern generation tools. The main new contribution of this paper is a formal definition of high-level decision diagram representations and the combination of the three fault models in order to target high gate-level stuck-at fault coverage for sequential cores.     

A Framework for Trust and Reputation in Grid Environments

This paper examines the role of trust and reputation in Grid environments. As Grid technology becomes standardized and stable, business models are invented and increasingly applied, and economic implications can be observed. Asymmetrically distributed information may allow for opportunistic behavior of service providers or users who opportunistically exploit the information gap between providers and consumers on the quality of services. The paper takes up these economic issues by proposing a reputation-based conceptual framework for enabling future open Grid markets, to recommend the most promising Grid architecture and a corresponding reputation approach in a particular case.     

Neuroproteomics in stem cell differentiation

The term "proteome" is used to describe the entire complement of proteins in a given organism or in a system at a given time. Proteome analysis in neuroscience, also called "neuroproteomics" or "neuromics" is in its initial stage, and shows a deficit of studies in the context of brain development. It is the main objective of this review to illustrate the potential of neuroproteomics as a tool to unravel the differentiation of neural stem or progenitor cells to terminally differentiated neurons. Experimental results regarding the rat striatal progenitor model cell line ST14A are presented to illustrate the large rearrangements of the proteome during the differentiation process of neural progenitor cells and their modification by neurotrophic factors like the glial cell line-derived neurotrophic factor (GDNF). Thereby native stem cells and cells transfected with GDNF gene were investigated at the proliferative state and at seven time points up to 72?h after induction of differentiation. In addition, the immortalized human fetal midbrain stem cell line ReNcell VM was analyzed in order to detect stem cell differentiation associated changes of the protein profile. This review gives also an outlook on technical improvements and perspectives of application of neural stem cell proteomics.     

A study on design of object sorting algorithms in the industrial application using hyperspectral imaging

Many industrial object-sorting applications leverage benefits of hyperspectral imaging technology. Design of object sorting algorithms is a challenging pattern recognition problem due to its multi-level nature. Objects represented by sets of pixels/spectra in hyperspectral images are to be allocated into pre-specified sorting categories. Sorting categories are often defined in terms of lower-level concepts such as material or defect types. This paper illustrates the design of two-stage sorting algorithms, learning to discriminate individual pixels/spectra and fusing the per-pixel decisions into a single per-object outcome. The paper provides a case-study on algorithm design in a real-world industrial sorting problem. Four groups of algorithms are studied varying the level of prior knowledge about the sorting problem. Apart of the sorting accuracy, the algorithm execution speed is estimated assuming an ideal implementation. Relating these two performance criteria allows us to discuss the accuracy/speed trade-off of different algorithms.

Effects of Pre‐Processing on Thixoformability of Steel Grade 100Cr6

Thixoforming is a new manufacturing technology which has been widely investigated for aluminium alloys. The thixoformability of steel and especially the impact of different pre‐processing is subject of this paper. For the thixoforming process it is of special interest to obtain the required fraction liquid content between 20 and 40%, a globulitic microstructure and low process temperatures. Therefore, steel primary material from three different processing routes was compared. The primary materials are rolled bars, laboratory cast billets and laboratory cast billets with liquid core reduction. The melting behaviour of the different materials was investigated by using Differential Thermal Analysis (DTA). Furthermore the materials were reheated into the solid‐liquid range and quenched to monitor the development of the microstructure. No significant differences between the three different pre‐processing routes could be determined with regard to thixoforming. Thus it seems possible to start thixoforming with as‐cast primary material.     

Fully employing software inspections data

Software inspections provide a proven approach to quality assurance for software products of all kinds, including requirements, design, code, test plans, among others. Common to all inspections is the aim of finding and fixing defects as early as possible, and thereby providing cost savings by minimizing the amount of rework necessary later in the life cycle. Measurement data, such as the number and type of found defects and the effort spent by the inspection team, provide not only direct feedback about the software product to the project team, but are also valuable for process improvement activities. In this paper, we discuss NASA??s use of software inspections and the rich set of data that has resulted. In particular, we present results from analysis of inspection data that illustrate the benefits of fully utilizing that data for process improvement at several levels. Examining such data across multiple inspections or projects allows team members to monitor and trigger cross project improvements. Such improvements may focus on the software development processes of the whole organization as well as improvements to the applied inspection process itself.     

Design Error Diagnosis with Re-Synthesis in Combinational Circuits

A new approach is proposed for removing design errors from digital circuits, which does not use any error model. Based on a diagnostic pre-analysis of the circuit, a subcircuit suspected to be erroneous is extracted. Opposite to other known works, re-synthesis of the subcircuit need not be applied to the whole function of the erroneous internal signal in terms of primary inputs, it may stop at arbitrary nodes inside the circuit. As the subcircuits to be redesigned are kept as small as possible, the speed of the whole procedure of diagnosis and re-synthesis can be significantly increased. A formal algorithm is proposed for the whole procedure. Experimental data show the efficiency of the diagnostic pre-analysis.