Fast TPC Online Tracking on GPUs and Asynchronous Data Processing in the ALICE HLT to facilitate Online Calibration

ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN, which is today the most powerful particle accelerator worldwide. The High Level Trigger (HLT) is an online compute farm of about 200 nodes, which reconstructs events measured by the ALICE detector in real-time. The HLT uses a custom online data-transport framework to distribute data and workload among the compute nodes. ALICE employs several calibration-sensitive subdetectors, e.g. the TPC (Time Projection Chamber). For a precise reconstruction, the HLT has to perform the calibration online. Online-calibration can make certain Offline calibration steps obsolete and can thus speed up Offline analysis. Looking forward to ALICE Run III starting in 2020, online calibration becomes a necessity. The main detector used for track reconstruction is the TPC. Reconstructing the trajectories in the TPC is the most compute-intense step during event reconstruction. Therefore, a fast tracking implementation is of great importance. Reconstructed TPC tracks build the basis for the calibration making a fast online-tracking mandatory. We present several components developed for the ALICE High Level Trigger to perform fast event reconstruction and to provide features required for online calibration. As first topic, we present our TPC tracker, which employs GPUs to speed up the processing, and which bases on a Cellular Automaton and on the Kalman filter. Our TPC tracking algorithm has been successfully used in 2011 and 2012 in the lead-lead and the proton-lead runs. We have improved it to leverage features of newer GPUs and we have ported it to support OpenCL, CUDA, and CPUs with a single common source code. This makes us vendor independent. As second topic, we present framework extensions required for online calibration. ...Comment: 8 pages, 6 figures, contribution to CHEP 2015 conferenc

Workload-sensitive Timing Behavior Analysis for Fault: Localization in Software Systems

Software timing behavior measurements, such as response times, often show high statistical variance. This variance can make the analysis difficult or even threaten the applicability of statistical techniques. This thesis introduces a method for improving the analysis of software response time measurements that show high variance. Our approach can find relations between timing behavior variance and both trace shape information and workload intensity information. This relation is used to provide timing behavior measurements with virtually less variance. This can make timing behavior analysis more robust (e.g., improved confidence and precision) and faster (e.g., less simulation runs and shorter monitoring period). The thesis contributes TracSTA (Trace-Context-Sensitive Timing Behavior Analysis) and WiSTA (Workload-Intensity-Sensitive Timing Behavior Analysis). TracSTA uses trace shape information (i.e., the shape of the control flow corresponding to a software operation execution) and WiSTA uses workload intensity metrics (e.g., the number of concurrent software executions) to create context-specific timing behavior profiles. Both the applicability and effectiveness are evaluated in several case studies and field studies. The evaluation shows a strong relation between timing behavior and the metrics considered by TracSTA and WiSTA. Additionally, a fault localization approach for enterprise software systems is presented as application scenario. It uses the timing behavior data provided by TracSTA and WiSTA for anomaly detection.Die Analyse von Zeitverhalten wie z.B. Antwortzeiten von Software-Operationen ist oft schwierig wegen der hohen statistischen Varianz. Diese Varianz gefährdet sogar die Anwendbarkeit von statistischen Verfahren. In dieser Arbeit wird eine Methode zur Verbesserung der Analyse von Antwortzeiten mit hoher statistischer Varianz vorgestellt. Der vorgestellte Ansatz ist in der Lage, einen Teil der Varianz aus dem gemessenen Zeitverhalten anhand von Aufrufsequenzen und Schwankungen in der Nutzungsintensität zu erklären. Dadurch kann praktisch Varianz aus den Messdaten entfernt werden, was die Anwendbarkeit von statistischen Analysen in Bezug auf Verlässlichkeit, Präzision und Geschwindigkeit (z.B. kürzere Messperiode und Simulationsdauer) verbessern kann. Der Hauptbeitrag dieser Arbeit liegt in den zwei Verfahren TracSTA (Trace-Context-Sensitive Timing Behavior Analysis) und WiSTA (Workload-Intensity-Sensitive Timing Behavior Analysis). TracSTA verwendet die Form des Aufrufflusses (d.h. die Form der Aufrufsequenz, in die ein Methodenaufruf eingebettet ist). WiSTA wertet die Nutzungsintensität aus (z.B. Anzahl gleichzeitig ausgeführter Methoden). Dies resultiert in kontextspezifischen Antwortzeitprofilen. In mehreren Fall- und Feldstudien wird die Anwendbarkeit und die Wirksamkeit evaluiert. Es zeigt sich ein deutlicher Zusammenhang zwischen dem Zeitverhalten und den von TracSTA und WiSTA betrachteten Einflussfaktoren. Zusätzlich wird als Anwendungsszenario ein Ansatz zur Fehlerlokalisierung vorgestellt, welcher von TracSTA und WiSTA bereitgestellte Antwortzeiten zur Anomalieerkennung verwendet

Bond Breaking and Bond Formation: How Electron Correlation is Captured in Many-Body Perturbation Theory and Density-Functional Theory

For the paradigmatic case of H2-dissociation we compare state-of-the-art many-body perturbation theory (MBPT) in the GW approximation and density-functional theory (DFT) in the exact-exchange plus random-phase approximation for the correlation energy (EX+cRPA). For an unbiased comparison and to prevent spurious starting point effects both approaches are iterated to full self-consistency (i.e. sc-RPA and sc-GW). The exchange-correlation diagrams in both approaches are topologically identical, but in sc-RPA they are evaluated with non-interacting and in sc-GW with interacting Green functions. This has a profound consequence for the dissociation region, where sc-RPA is superior to sc-GW. We argue that for a given diagrammatic expansion, the DFT framework outperforms the many-body framework when it comes to bond-breaking. We attribute this to the difference in the correlation energy rather than the treatment of the kinetic energy.Comment: 6 pages, 4 figure

Zebrafish hhex, nk2.1a, and pax2.1 regulate thyroid growth and differentiation downstream of Nodal-dependent transcription factors

AbstractDuring zebrafish development, the thyroid primordium initiates expression of molecular markers such as hhex and nk2.1a in the endoderm prior to pharynx formation. As expected for an endodermally derived organ, initiation of thyroid development depends on Nodal signalling. We find that it also depends on three downstream effectors of Nodal activity, casanova (cas), bonnie and clyde (bon), and faust (fau)/gata5. Despite their early Nodal-dependent expression in the endoderm, both hhex and nk2.1a are only required relatively late during thyroid development. In hhex and nk2.1a loss-of-function phenotypes, thyroid development is initiated and arrests only after the primordium has evaginated from the pharyngeal epithelium. Thus, like pax2.1, both hhex and nk2.1a have similarly late roles in differentiation or growth of thyroid follicular cells, and here, we show that all three genes act in parallel rather than in a single pathway. Our functional analysis suggests that these genes have similar roles as in mammalian thyroid development, albeit in a different temporal mode of organogenesis

Uniaxial strain-induced phase transition in the 2D topological semimetal IrTe2

Strain is ubiquitous in solid-state materials, but despite its fundamental importance and technological relevance, leveraging externally applied strain to gain control over material properties is still in its infancy. In particular, strain control over the diverse phase transitions and topological states in two-dimensional transition metal dichalcogenides remains an open challenge. Here, we exploit uniaxial strain to stabilize the long-debated structural ground state of the 2D topological semimetal IrTe$_{2}$, which is hidden in unstrained samples. Combined angle-resolved photoemission spectroscopy and scanning tunneling microscopy data reveal the strain-stabilized phase has a 6 × 1 periodicity and undergoes a Lifshitz transition, granting unprecedented spectroscopic access to previously inaccessible type-II topological Dirac states that dominate the modified inter-layer hopping. Supported by density functional theory calculations, we show that strain induces an Ir to Te charge transfer resulting in strongly weakened inter-layer Te bonds and a reshaped energetic landscape favoring the 6×1 phase. Our results highlight the potential to exploit strain-engineered properties in layered materials, particularly in the context of tuning inter-layer behavior

PIDDosome-induced p53-dependent ploidy restriction facilitates hepatocarcinogenesis

Polyploidization frequently precedes tumorigenesis but also occurs during normal development in several tissues. Hepatocyte ploidy is controlled by the PIDDosome during development and regeneration. This multi-protein complex is activated by supernumerary centrosomes to induce p53 and restrict proliferation of polyploid cells, otherwise prone for chromosomal instability. PIDDosome deficiency in the liver results in drastically increased polyploidy. To investigate PIDDosome-induced p53-activation in the pathogenesis of liver cancer, we chemically induced hepatocellular carcinoma (HCC) in mice. Strikingly, PIDDosome deficiency reduced tumor number and burden, despite the inability to activate p53 in polyploid cells. Liver tumors arise primarily from cells with low ploidy, indicating an intrinsic pro-tumorigenic effect of PIDDosome-mediated ploidy restriction. These data suggest that hyperpolyploidization caused by PIDDosome deficiency protects from HCC. Moreover, high tumor cell density, as a surrogate marker of low ploidy, predicts poor survival of HCC patients receiving liver transplantation. Together, we show that the PIDDosome is a potential therapeutic target to manipulate hepatocyte polyploidization for HCC prevention and that tumor cell density may serve as a novel prognostic marker for recurrence-free survival in HCC patients

Classical homeopathy in the treatment of cancer patients - a prospective observational study of two independent cohorts

BACKGROUND: Many cancer patients seek homeopathy as a complementary therapy. It has rarely been studied systematically, whether homeopathic care is of benefit for cancer patients. METHODS: We conducted a prospective observational study with cancer patients in two differently treated cohorts: one cohort with patients under complementary homeopathic treatment (HG; n = 259), and one cohort with conventionally treated cancer patients (CG; n = 380). For a direct comparison, matched pairs with patients of the same tumour entity and comparable prognosis were to be formed. Main outcome parameter: change of quality of life (FACT-G, FACIT-Sp) after 3 months. Secondary outcome parameters: change of quality of life (FACT-G, FACIT-Sp) after a year, as well as impairment by fatigue (MFI) and by anxiety and depression (HADS). RESULTS: HG: FACT-G, or FACIT-Sp, respectively improved statistically significantly in the first three months, from 75.6 (SD 14.6) to 81.1 (SD 16.9), or from 32.1 (SD 8.2) to 34.9 (SD 8.32), respectively. After 12 months, a further increase to 84.1 (SD 15.5) or 35.2 (SD 8.6) was found. Fatigue (MFI) decreased; anxiety and depression (HADS) did not change. CG: FACT-G remained constant in the first three months: 75.3 (SD 17.3) at t0, and 76.6 (SD 16.6) at t1. After 12 months, there was a slight increase to 78.9 (SD 18.1). FACIT-Sp scores improved significantly from t0 (31.0 - SD 8.9) to t1 (32.1 - SD 8.9) and declined again after a year (31.6 - SD 9.4). For fatigue, anxiety, and depression, no relevant changes were found. 120 patients of HG and 206 patients of CG met our criteria for matched-pairs selection. Due to large differences between the two patient populations, however, only 11 matched pairs could be formed. This is not sufficient for a comparative study. CONCLUSION: In our prospective study, we observed an improvement of quality of life as well as a tendency of fatigue symptoms to decrease in cancer patients under complementary homeopathic treatment. It would take considerably larger samples to find matched pairs suitable for comparison in order to establish a definite causal relation between these effects and homeopathic treatment

Long-term residential exposure to PM2.5 constituents and mortality in a Danish cohort

Studies on health effects of long-term exposure to specific PM2.5 constituents are few. Previous studies have reported an association between black carbon (BC) exposure and cardiovascular diseases (CVD) and a few studies have found an association between sulfate exposure and mortality. These studies, however, relied mainly on exposure data from centrally located air-monitoring stations, which is a crude approximation of personal exposure. We focused on specific chemical constituents of PM2.5, i.e. elemental and primary organic carbonaceous particles (BC/OC), sea salt, secondary inorganic aerosols (SIA, i.e. NO3–, NH4+, and SO42-), and secondary organic aerosols (SOA), in relation to all-cause, CVD and respiratory disease mortality. We followed a Danish cohort of 49,564 individuals from enrollment in 1993–1997 through 2015. We combined residential address history from 1979 onwards with mean annual air pollution concentrations obtained by the AirGIS air pollution modelling system, lifestyle information from baseline questionnaires and socio-demography obtained by register linkage. During 895,897 person-years of follow-up, 10,193 deaths from all causes occurred – of which 2319 were CVD-related and 870 were related to respiratory disease. The 15-year time-weighted average concentrations of PM2.5, BC/OC, sea salt, SIA and SOA were 13.8, 2.8, 3.4, 4.9, and 0.3 µg/m3, respectively. For all-cause mortality, a higher risk was observed with higher exposure to PM2.5, BC/OC and SOA with adjusted hazard ratios of 1.03 (95% confidence intervals: 1.01, 1.05), 1.06 (1.03, 1.09), and 1.08 (1.03, 1.13) per interquartile range, respectively. The associations for BC/OC and SOA remained after adjustment for PM2.5 in two-pollutant models. For CVD mortality, we observed elevated risks with higher exposure to PM2.5, BC/OC and SIA. The results showed no clear relationship between sea salt and mortality. In this study, we observed a relationship between long-term exposure to PM2.5, BC/OC, and SOA and all-cause mortality and between PM2.5, BC/OC, and SIA and CVD mortality.</p

In Vivo Conditions to Identify Prkci Phosphorylation Targets Using the Analog-Sensitive Kinase Method in Zebrafish

Protein kinase C iota is required for various cell biological processes including epithelial tissue polarity and organ morphogenesis. To gain mechanistic insight into different roles of this kinase, it is essential to identify specific substrate proteins in their cellular context. The analog-sensitive kinase method provides a powerful tool for the identification of kinase substrates under in vivo conditions. However, it has remained a major challenge to establish screens based on this method in multicellular model organisms. Here, we report the methodology for in vivo conditions using the analog-sensitive kinase method in a genetically-tractable vertebrate model organism, the zebrafish. With this approach, kinase substrates can uniquely be labeled in the developing zebrafish embryo using bulky ATPγS analogs which results in the thiophosphorylation of substrates. The labeling of kinase substrates with a thiophosphoester epitope differs from phosphoesters that are generated by all other kinases and allows for an enrichment of thiophosphopeptides by immunoaffinity purification. This study provides the foundation for using the analog-sensitive kinase method in the context of complex vertebrate development, physiology, or disease