Towards Distributed Task-based Visualization and Data Analysis

To support scientific work with large and complex data the field of scientific visualization emerged in computer science and produces images through computational analysis of the data. Frameworks for combination of different analysis and visualization modules allow the user to create flexible pipelines for this purpose and set the standard for interactive scientific visualization used by domain scientists. Existing frameworks employ a thread-parallel message-passing approach to parallel and distributed scalability, leaving the field of scientific visualization in high performance computing to specialized ad-hoc implementations. The task-parallel programming paradigm proves promising to improve scalability and portability in high performance computing implementations and thus, this thesis aims towards the creation of a framework for distributed, task-based visualization modules and pipelines. The major contribution of the thesis is the establishment of modules for Merge Tree construction and (based on the former) topological simplification. Such modules already form a necessary first step for most visualization pipelines and can be expected to increase in importance for larger and more complex data produced and/or analysed by high performance computing. To create a task-parallel, distributed Merge Tree construction module the construction process has to be completely revised. We derive a novel property of Merge Tree saddles and introduce a novel task-parallel, distributed Merge Tree construction method that has both good performance and scalability. This forms the basis for a module for topological simplification which we extend by introducing novel alternative simplification parameters that aim to reduce the importance of prior domain knowledge to increase flexibility in typical high performance computing scenarios. Both modules lay the groundwork for continuative analysis and visualization steps and form a fundamental step towards an extensive task-parallel visualization pipeline framework for high performance computing.Wissenschaftliche Visualisierung ist eine Disziplin der Informatik, die durch computergestützte Analyse Bilder aus Datensätzen erzeugt, um das wissenschaftliche Arbeiten mit großen und komplexen Daten zu unterstützen. Softwaresysteme, die dem Anwender die Kombination verschiedener Analyse- und Visualisierungsmodule zu einer flexiblen Pipeline erlauben, stellen den Standard für interaktive wissenschaftliche Visualisierung. Die hierfür bereits existierenden Systeme setzen auf Thread-Parallelisierung mit expliziter Kommunikation, sodass das Feld der wissenschaftlichen Visualisierung auf Hochleistungsrechnern meist spezialisierten Direktlösungen überlassen wird. An dieser Stelle scheint Task-Parallelisierung vielversprechend, um Skalierbarkeit und Übertragbarkeit von Lösungen für Hochleistungsrechner zu verbessern. Daher zielt die vorliegende Arbeit auf die Umsetzung eines Softwaresystems für verteilte und task-parallele Visualisierungsmodule und -pipelines ab. Der zentrale Beitrag den die vorliegende Arbeit leistet ist die Einführung zweier Module für Merge Tree Konstruktion und topologische Datenbereinigung. Solche Module stellen bereits einen notwendigen ersten Schritt für die meisten Visualisierungspipelines dar und werden für größere und komplexere Datensätze, die im Hochleistungsrechnen erzeugt beziehungsweise analysiert werden, erwartungsgemäß noch wichtiger. Um eine Task-parallele, verteilbare Konstruktionsmethode für Merge Trees zu entwickeln musste der etablierte Algorithmus grundlegend überarbeitet werden. In dieser Arbeit leiten wir eine neue Eigenschaft für Merge Tree Knoten her und entwickeln einen neuartigen Konstruktionsalgorithmus, der gute Performance und Skalierbarkeit aufweist. Darauf aufbauend entwickeln wir ein Modul für topologische Datenbereinigung, welche wir durch neue, alternative Bereinigungsparameter erweitern, um die Flexibilität im Einstaz auf Hochleistungsrechnern zu erhöhen. Beide Module ermöglichen weiterführende Analyse und Visualisierung und setzen einen Grundstein für die Entwicklung eines umfassenden Task-parallelen Softwaresystems für Visualisierungspipelines auf Hochleistungsrechnern

Koordinierte Makropolitik in der Europäischen Union?

In der Europäischen Union, genauer in den 12 Mitgliedsländern der Euro-Zone, bestimmt die Europäische Zentralbank die Geldpolitik, und die zwölf Mitgliedsländer legen unabhängig voneinander die jeweiligen Fiskalpolitiken fest. Während bei den einen - und dazu zählt Deutschland - eine bemerkenswert hohe Preisniveaustabilität und eine spürbare Wachstumsschwäche zu verzeichnen ist, erfahren andere - wie Irland, Portugal, Spanien - durchaus zufrieden stellende Wachstumsraten bei höheren Preisniveausteigerungen. Die Arbeitslosigkeit ist in der EU insgesamt relativ hoch. Vor diesem Hintergrund ist die Forderung erhoben worden, eine koordinierte Makropolitik in der EU zu betreiben, um entweder mehr Wachstum und Beschäftigung zu erreichen (Hein 2001, Priewe 2001) oder um zumindest auf vorübergehende Nachfrageschwächen bei exogenen Schocks zu reagieren. Im Folgenden geht es darum zu klären, welcher Beitrag von der koordinierten Makropolitik zu leisten ist, und welche institutionellen Voraussetzungen für eine solche zu erfüllen sind. Die Leitthese lautet, dass ausgehend von einem positiven Beitrag koordinierter Makropolitik im neu-keynesianischen Modell momentan nur wenig institutionelles Potential für eine Koordination besteht. Einerseits bildet der Stabilitäts- und Wachstumspakt nur eine regelgebundene Obergrenze für den Einsatz der Fiskalpolitik zum Schutz der gemeinsamen Geldpolitik, andererseits reichen die vorhandenen Institutionen nicht aus, um eine Koordination von Geld- und Fiskalpolitik und möglicherweise weiteren Politikfeldern zu erreichen. Es ist folglich nach neuen Institutionen zu suchen, die eine derartige Aufgabe zu lösen vermögen.

Mesoscale movement and recursion behaviors of Namibian black rhinos.

Background:Understanding rhino movement behavior, especially their recursive movements, holds significant promise for enhancing rhino conservation efforts, and protecting their habitats and the biodiversity they support. Here we investigate the daily, biweekly, and seasonal recursion behavior of rhinos, to aid conservation applications and increase our foundational knowledge about these important ecosystem engineers. Methods:Using relocation data from 59 rhinos across northern Namibia and 8 years of sampling efforts, we investigated patterns in 24-h displacement at dawn, dusk, midday, and midnight to examine movement behaviors at an intermediate scale and across daily behavioral modes of foraging and resting. To understand recursion patterns across animals' short and long-term ranges, we built T-LoCoH time use grids to estimate recursive movement by each individual. Comparing these grids to contemporaneous MODIS imagery, we investigated productivity's influence on short-term space use and recursion. Finally, we investigated patterns of recursion within a year's home range, measuring the time to return to the most intensively used patches. Results:Twenty four-hour displacements at dawn were frequently smaller than 24-h displacements at dusk or at midday and midnight resting periods. Recursion analyses demonstrated that short-term recursion was most common in areas of median rather than maximum NDVI values. Investigated across a full year, recursion analysis showed rhinos most frequently returned to areas within 8-21 days, though visits were also seen separated by months likely suggesting seasonality in range use. Conclusions:Our results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Recursion across larger time scales is also evident, and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna

Towards Packaging Unit Detection for Automated Palletizing Tasks

For various automated palletizing tasks, the detection of packaging units is a crucial step preceding the actual handling of the packaging units by an industrial robot. We propose an approach to this challenging problem that is fully trained on synthetically generated data and can be robustly applied to arbitrary real world packaging units without further training or setup effort. The proposed approach is able to handle sparse and low quality sensor data, can exploit prior knowledge if available and generalizes well to a wide range of products and application scenarios. To demonstrate the practical use of our approach, we conduct an extensive evaluation on real-world data with a wide range of different retail products. Further, we integrated our approach in a lab demonstrator and a commercial solution will be marketed through an industrial partner

Corrosion behavior of carbon steel in presence of sulfate-reducing bacteria in seawater environment

The influence of sulfate-reducing bacteria (SRB)on the corrosion behavior of carbon steel was studiedin a laboratory test-loop, continuously fed with nutrient supplemented North Sea seawater. The mainparts of the test-loop, represented by two separated flow cells, were fitted with steel specimens. The test-loop was operating anoxically for 2200 h and each flow cell was three times inoculated with Desulfovibrioalaskensis or Desulfovibrio desulfuricans species. Additionally, each flow cell was two times perturbed with antimicrobial treatments. Steel specimens exposed in flow cells exhibited comparable appearance andsystems responding similarly to inoculations and antimicrobial treatments. The effect of the inoculations in both flow cells on the steel coupons electrochemical behavior was materialized as lower resistanceto corrosion and higher surface activity or occurrence of localized pitting events. The localized surfaceattacks recognized in both flow cells after inoculations continued to progress with the time, althoughbacterial activity was temporarily suppressed by antimicrobial treatment. Post-exposure sample evalu-ations might suggest that, some particular steel surface areas have been subjected to a dramatic change in the corrosion mechanism from initial localized attack to general corrosion. The long-term exposureof the carbon steel specimens resulted in identifiable formation of biofilms and corrosion products. Cor-rosion deposits were characterized by a specific structure built of iron sulfides (FeS), sulfated green rust(GR(SO42−)), magnetite (Fe3O4), Fe(III) oxyhydroxides (FeOOH), chukanovite (Fe2(OH)2CO3), carbonatedgreen rust (GR(CO32−)) and some calcareous deposits. Presented factual evidence reinforced the idea thatsulfidogenic species in natural seawater environment may cause localized damage with a specific surfacepattern; however, this does not necessarily lead towards significantly elevated corrosion rates

Reexamination of Quantum Bit Commitment: the Possible and the Impossible

Bit commitment protocols whose security is based on the laws of quantum mechanics alone are generally held to be impossible. In this paper we give a strengthened and explicit proof of this result. We extend its scope to a much larger variety of protocols, which may have an arbitrary number of rounds, in which both classical and quantum information is exchanged, and which may include aborts and resets. Moreover, we do not consider the receiver to be bound to a fixed "honest" strategy, so that "anonymous state protocols", which were recently suggested as a possible way to beat the known no-go results are also covered. We show that any concealing protocol allows the sender to find a cheating strategy, which is universal in the sense that it works against any strategy of the receiver. Moreover, if the concealing property holds only approximately, the cheat goes undetected with a high probability, which we explicitly estimate. The proof uses an explicit formalization of general two party protocols, which is applicable to more general situations, and a new estimate about the continuity of the Stinespring dilation of a general quantum channel. The result also provides a natural characterization of protocols that fall outside the standard setting of unlimited available technology, and thus may allow secure bit commitment. We present a new such protocol whose security, perhaps surprisingly, relies on decoherence in the receiver's lab.Comment: v1: 26 pages, 4 eps figures. v2: 31 pages, 5 eps figures; replaced with published version; title changed to comply with puzzling Phys. Rev. regulations; impossibility proof extended to protocols with infinitely many rounds or a continuous communication tree; security proof of decoherence monster protocol expanded; presentation clarifie

Quantum simulation meets nonequilibrium dynamical mean-field theory: exploring the periodically driven, strongly correlated fermi-hubbard model

We perform an ab initio comparison between nonequilibrium dynamical mean-field theory and optical lattice experiments by studying the time evolution of double occupations in the periodically driven Fermi-Hubbard model. For off-resonant driving, the range of validity of a description in terms of an effective static Hamiltonian is determined and its breakdown due to energy absorption close to resonance is demonstrated. For near-resonant driving, we investigate the response to a change in driving amplitude and discover an asymmetric excitation spectrum with respect to the detuning. In general, we find good agreement between experiment and theory, which cross validates the experimental and numerical approaches in a strongly correlated nonequilibrium system

Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants

Metabolomics is an ‘omics’ approach that aims to analyze all metabolites in a biological sample comprehensively. The detailed metabolite profiling of thousands of plant samples has great potential for directly elucidating plant metabolic processes. However, both a comprehensive analysis and a high throughput are difficult to achieve at the same time due to the wide diversity of metabolites in plants. Here, we have established a novel and practical metabolomics methodology for quantifying hundreds of targeted metabolites in a high-throughput manner. Multiple reaction monitoring (MRM) using tandem quadrupole mass spectrometry (TQMS), which monitors both the specific precursor ions and product ions of each metabolite, is a standard technique in targeted metabolomics, as it enables high sensitivity, reproducibility and a broad dynamic range. In this study, we optimized the MRM conditions for specific compounds by performing automated flow injection analyses with TQMS. Based on a total of 61,920 spectra for 860 authentic compounds, the MRM conditions of 497 compounds were successfully optimized. These were applied to high-throughput automated analysis of biological samples using TQMS coupled with ultra performance liquid chromatography (UPLC). By this analysis, approximately 100 metabolites were quantified in each of 14 plant accessions from Brassicaceae, Gramineae and Fabaceae. A hierarchical cluster analysis based on the metabolite accumulation patterns clearly showed differences among the plant families, and family-specific metabolites could be predicted using a batch-learning self-organizing map analysis. Thus, the automated widely targeted metabolomics approach established here should pave the way for large-scale metabolite profiling and comparative metabolomics