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Many applications in computational science and engineering require the computation of eigenvalues and vectors of dense symmetric or Hermitian matrices. For example, in DFT (density functional theory) calculations on modern supercomputers 10% to 30% of the eigenvalues and eigenvectors of huge dense matrices have to be calculated. Therefore, performance and parallel scaling of the used eigensolvers is of upmost interest. In this article different routines of the linear algebra packages ScaLAPACK and Elemental for parallel solution of the symmetric eigenvalue problem are compared concerning their performance on the BlueGene/P supercomputer. Parameters for performance optimization are adjusted for the different data distribution methods used in the two libraries. It is found that for all test cases the new library Elemental which uses a two-dimensional element by element distribution of the matrices to the processors shows better performance than the old ScaLAPACK library which uses a block-cyclic distribution.
Temperature-dependent ranges of coexistence in a model of a two-prey-one-predator microbial food web
(2012)
The objective of our study was to analyze the effects of temperature on the population dynamics of a three-species food web consisting of two prey bacteria (Pedobacter sp. and Acinetobacter johnsonii) and a protozoan predator (Tetrahymena pyriformis) as model organisms. We assessed the effects of temperature on the growth rates of all three species with the objective of developing a model with four differential equations based on the experimental data. The following hypotheses were tested at a theoretical level: Firstly, temperature changes can affect the dynamic behavior of a system by temperature-dependent parameters and interactions and secondly, food web response to temperature cannot be derived from the single species temperature response. The main outcome of the study is that temperature changes affect the parameter range where coexistence is possible within all three species. This has significant consequences on our ideas regarding the evaluation of effects of global warming.
Bioconjugates containing the GnRH-III hormone decapeptide as a targeting moiety are able to deliver chemotherapeutic agents specifically to cancer cells expressing GnRH receptors, thereby increasing their local efficacy while limiting the peripheral toxicity. However, the number of GnRH receptors on cancer cells is limited and they desensitize under continuous hormone treatment. A possible approach to increase the receptor mediated tumor targeting and consequently the cytostatic effect of the bioconjugates would be the attachment of more than one chemotherapeutic agent to one GnRH-III molecule. Here we report on the design, synthesis and biochemical characterization of multifunctional bioconjugates containing GnRH-III as a targeting moiety and daunorubicin as a chemotherapeutic agent. Two different drug design approaches were pursued. The first one was based on the bifunctional [4Lys]-GnRH-III (Glp-His-Trp-Lys-His-Asp-Trp-Lys-Pro-Gly-NH2) containing two lysine residues in positions 4 and 8, whose ϵ-amino groups were used for the coupling of daunorubicin. In the second drug design, the native GnRH-III (Glp-His-Trp-Ser-His-Asp-Trp-Lys-Pro-Gly-NH2) was used as a scaffold; an additional lysine residue was coupled to the ϵ-amino group of 8Lys in order to generate two free amino groups available for conjugation of daunorubicin. The in vitro stability/degradation of all synthesized compounds was investigated in human serum, as well as in the presence of rat liver lysosomal homogenate. Their cellular uptake was determined on human breast cancer cells and the cytostatic effect was evaluated on human breast, colon and prostate cancer cell lines. Compared with a monofunctional compound, both drug design approaches resulted in multifunctional bioconjugates with increased cytostatic effect.
In this article, we report on the heat-transfer resistance at interfaces as a novel, denaturation-based method to detect single-nucleotide polymorphisms in DNA. We observed that a molecular brush of double-stranded DNA grafted onto synthetic diamond surfaces does not notably affect the heat-transfer resistance at the solid-to-liquid interface. In contrast to this, molecular brushes of single-stranded DNA cause, surprisingly, a substantially higher heat-transfer resistance and behave like a thermally insulating layer. This effect can be utilized to identify ds-DNA melting temperatures via the switching from low- to high heat-transfer resistance. The melting temperatures identified with this method for different DNA duplexes (29 base pairs without and with built-in mutations) correlate nicely with data calculated by modeling. The method is fast, label-free (without the need for fluorescent or radioactive markers), allows for repetitive measurements, and can also be extended toward array formats. Reference measurements by confocal fluorescence microscopy and impedance spectroscopy confirm that the switching of heat-transfer resistance upon denaturation is indeed related to the thermal on-chip denaturation of DNA.
In this paper we consider low Péclet number flow in bead packs. A series of relaxation exchange experiments has been conducted and evaluated by ILT analysis. In the resulting correlation maps, we observed a collapse of the signal and a translation towards smaller relaxation times with increasing flow rates, as well as a signal tilt with respect to the diagonal. In the discussion of the phenomena we present a mathematical theory for relaxation exchange experiments that considers both diffusive and advective transport. We perform simulations based on this theory and discuss them with respect to the conducted experiments.
This paper describes the implementation of topographic curvature effects within the RApid Mass MovementS (RAMMS) snow avalanche simulation toolbox. RAMMS is based on a model similar to shallow water equations with a Coulomb friction relation and the velocity dependent Voellmy drag. It is used for snow avalanche risk assessment in Switzerland. The snow avalanche simulation relies on back calculation of observed avalanches. The calibration of the friction parameters depends on characteristics of the avalanche track. The topographic curvature terms are not yet included in the above mentioned classical model. Here, we fundamentally improve this model by mathematically and physically including the topographic curvature effects. By decomposing the velocity dependent friction into a topography dependent term that accounts for a curvature enhancement in the Coulomb friction, and a topography independent contribution similar to the classical Voellmy drag, we construct a general curvature dependent frictional resistance, and thus propose new extended model equations. With three site-specific examples, we compare the apparent frictional resistance of the new approach, which includes topographic curvature effects, to the classical one. Our simulation results demonstrate substantial effects of the curvature on the flow dynamics e.g., the dynamic pressure distribution along the slope. The comparison of resistance coefficients between the two models demonstrates that the physically based extension presents an improvement to the classical approach. Furthermore a practical example highlights its influence on the pressure outline in the run out zone of the avalanche. Snow avalanche dynamics modeling natural terrain curvature centrifugal force friction coefficients.
Often, detailed simulations of heat conduction in complicated, porous media have large runtimes. Then homogenization is a powerful tool to speed up the calculations by preserving accurate solutions at the same time. Unfortunately real structures are generally non-periodic, which requires unpractical, complicated homogenization techniques. We demonstrate in this paper, that the application of simple, periodic techniques to realistic media, that are just close to periodic, gives accurate, approximative solutions. In order to obtain effective parameters for the homogenized heat equation, we have to solve a so called “cell problem”. In contrast to periodic structures it is not trivial to determine a suitable unit cell, which represents a non-periodic media. To overcome this problem, we give a rule of thumb on how to choose a good cell. Finally we demonstrate the efficiency of our method for virtually generated foams as well as real foams and compare these results to periodic structures.
Although Selective Laser Melting (SLM) process is an innovative manufacturing method, there are challenges such as inferior mechanical properties of fabricated objects. Regarding this, buckling deformation which is caused by thermal stress is one of the undesired mechanical properties which must be alleviated. As buckling deformation is more observable in hard to process materials, silver is selected to be studied theoretically and experimentally for this paper. Different scanning strategies are utilized and a Finite Element Method (FEM) is applied to calculate the temperature gradient in order to determine its effect on the buckling deformation of the objects from experiments.
As part of a novel approach to automatic sewer inspection, this paper presents a robust algorithm for automatic flow line detection. A large image repository is obtained from about 50,000 m sewers to represent the high variability of real world sewer systems. Automatic image processing combines Canny edge detection, Hough transform for straight lines and cost minimization using Dijkstra's shortest path algorithm. Assuming that flow lines are mostly smoothly connected horizontal structures, piecewise flow line delineation is reduced to a process of selecting adjacent line candidates. Costs are derived from the gap between adjacent candidates and their reliability. A single parameter α enables simple control of the algorithm. The detected flow line may precisely follow the segmented edges (α = 0.0) or minimize gaps at joints (α = 1.0). Both, manual and ground truth-based analysis indicate that α = 0.8 is optimal and independent of the sewer's material. The algorithm forms an essential step to further automation of sewer inspection.
In industrial processes there is a variety of heavy metals (e.g., copper, zinc, cadmium, and lead) in use for wires, coatings, paints, alloys, batteries, etc. Since the application of these transition metals for industry is inevitable, it is a vital task to develop proper analytical techniques for their monitoring at low activity levels, especially because most of these elements are acutely toxic for biological organisms. The determination of ions in solution by means of a simple and inexpensive sensor array is, therefore, a promising task. In this work, a sensor array with heavy metal-sensitive chalcogenide glass membranes for the simultaneous detection of the four ions Ag⁺, Cu2⁺, Cd2⁺, and Pb2⁺ in solution is realized. The results of the physical characterization by means of microscopy, profilometry, Rutherford backscattering spectroscopy (RBS), and scanning electron microscopy (SEM) as well as the electrochemical characterization by means of potentiometric measurements are presented. Additionally, the possibility to expand the sensor array by polymeric sensor membranes is discussed.