Decision support in early development phases—A case study from machine engineering

In the case study presented in this paper we consider early development phases of a mechanical product. We want to evaluate different concepts and decide which one(s) to pursue. A problem in early phases is that usually no test runs are available. In our case study, based on a standard, there are ways to compute the lifetime distributions of the components of the different concepts. Some parameters needed for these computations are not known precisely. Unfortunately, the lifetime distributions of the components are highly sensitive to these parameters. Our approach is to equip these parameters with distributions. These distributions would be called prior distributions in Bayesian terminology, but no update is possible since no test runs are available. Our approach implies that the distribution of the system lifetime for each concept is random, i.e. we get random elements in the space of lifetime distributions. Using Monte-Carlo simulations, we demonstrate several ways to compare the random lifetime distributions of the concepts. Some of these comparisons use stochastic orderings. We also introduce a new stochastic ordering which is particularly suitable for reliability purposes. Our case study, consisting of three scenarios, allows us to demonstrate some conclusions that can be reached.     

Quantitative measurement of gas hold-up distribution in a stirred chemical reactor using X-ray cone-beam computed tomography

Cone-beam type X-ray computed tomography (CBCT) is a potential method to measure three-dimensional phase distributions in vessels. An example for that is the measurement of gas profiles in stirred chemical reactors. Such data are highly valuable for the assessment and evaluation of chemical processes, for optimisation of the reactor and stirrer design, and for evaluation of computational fluid dynamics codes used to model the fluid flow and heat transfer in reactive systems. However, there are considerable difficulties for accurate quantitative measurements due to beam hardening and radiation scattering effects. In a theoretical and experimental work we have investigated the non-linear effects of both physical phenomena and developed a suitable measurement setup as well as calibration and software correction methods to achieve a highly accurate measurement of void fraction profiles with CBCT.     

Smaller superconcentrators of density 28

An N-superconcentrator is a directed, acyclic graph with N input nodes and N output nodes such that every subset of the inputs and every subset of the outputs of same cardinality can be connected by node-disjoint paths. It is known that linear-size and bounded-degree superconcentrators exist. Here it is proved that such superconcentrators exist (by a random construction of certain expander graphs as building blocks) having density 28 (where the density is the number of edges divided by N). The best known density before this paper was 34.2 [U. Schöning, Construction of expanders and superconcentrators using Kolmogorov complexity, J. Random Structures Algorithms 17 (2000) 64-77] or 33 [L.A. Bassalygo, Personal communication, 2004].     

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A note on a local twist estimator

For the construction of composite surfaces interpolating a given curve net a new local twist estimator was proposed recently (Farin and Hagen, 1992). Some properties of this estimator—including an explicit representation for Gaussian curvature K at the knots of the curve net—are presented in this note.     

Improving sub-pixel accuracy for long range stereo

Dense stereo algorithms are able to estimate disparities at all pixels including untextured regions. Typically these disparities are evaluated at integer disparity steps. A subsequent sub-pixel interpolation often fails to propagate smoothness constraints on a sub-pixel level.We propose to increase the sub-pixel accuracy in low-textured regions in four possible ways: First, we present an analysis that shows the benefit of evaluating the disparity space at fractional disparities. Second, we introduce a new disparity smoothing algorithm that preserves depth discontinuities and enforces smoothness on a sub-pixel level. Third, we present a novel stereo constraint (gravitational constraint) that assumes sorted disparity values in vertical direction and guides global algorithms to reduce false matches, especially in low-textured regions. Finally, we show how image sequence analysis improves stereo accuracy without explicitly performing tracking. Our goal in this work is to obtain an accurate 3D reconstruction. Large-scale 3D reconstruction will benefit heavily from these sub-pixel refinements.Results based on semi-global matching, obtained with the above mentioned algorithmic extensions are shown for the Middlebury stereo ground truth data sets. The presented improvements, called ImproveSubPix, turn out to be one of the top-performing algorithms when evaluating the set on a sub-pixel level while being computationally efficient. Additional results are presented for urban scenes. The four improvements are independent of the underlying type of stereo algorithm.     

Topology of the moduli space for reachable linear dynamical systems: The complex case

This paper deals with the algebraic topology of the space _n,m of complex reachable linear dynamical systems. Topological invariants such as the singular homology groups of _n,m are explicitly computed and they are shown to coincide with those of a certain Grassmann manifold. From this some new results on the topology of rational transfer matrices with fixed McMillan degree are obtained.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

From Natural Methylation to Versatile Alkylations Using Halide Methyltransferases

Halide methyltransferases (HMTs) enable the enzymatic synthesis of S-adenosyl-l -methionine (SAM) from S-adenosyl-l -homocysteine (SAH) and methyl iodide. Characterisation of a range of naturally occurring HMTs and subsequent protein engineering led to HMT variants capable of synthesising ethyl, propyl, and allyl analogues of SAM. Notably, HMTs do not depend on chemical synthesis of methionine analogues, as required by methionine adenosyltransferases (MATs). However, at the moment MATs have a much broader substrate scope than the HMTs. Herein we provide an overview of the discovery and engineering of promiscuous HMTs and how these strategies will pave the way towards a toolbox of HMT variants for versatile chemo- and regioselective biocatalytic alkylations.