Generalized database index structures on massively parallel processor architectures

Height-balanced search trees are ubiquitous in database management systems as well as in other applications that require efficient access methods in order to identify entries in large data volumes. They can be configured with various strategies for structuring the search space for a given data set and for pruning it when different kinds of search queries are answered. In order to facilitate the development of application-specific tree variants, index frameworks, such as GiST, exist that provide a reusable library of commonly shared tree management functionality. By specializing internal data organization strategies, the framework can be customized to create an index that is efficient for an application's data access characteristics. Because the majority of the framework's code can be reused development and testing efforts are significantly lower, compared to an implementation from scratch. However, none of the existing frameworks supports the execution of index operations on massively parallel processor architectures, such as GPUs. Enabling the use of such processors for generalized index frameworks is the goal of this thesis. By compiling state-of-the-art techniques from a wide range of CPU- and GPU-optimized indexes, a GiST extension is developed that abstracts the physical execution aspect of generic, tree-based search queries. Tree traversals are broken-down into vectorized processing primitives that can be scheduled to one of the available (co-)processors for execution. Further, a CPU-based implementation is provided as well as a new GPU-based algorithm that, unlike prior art in this area, does not require that the index is fully stored inside a GPU's main memory buffer. The applicability of the extended framework is assessed for image rendering engines and, based on microbenchmarks, the parallelized algorithm performance is compared for different CPU and GPU generations. It will be shown that cases exist, where the GPU clearly outperforms the CPU and vice versa. In order to leverage the strengths of each processor type, an adaptive scheduler is presented that can be calibrated to schedule index operations to the best-fitting device in a hybrid system. With the help of a tree traversal simulation different scheduling strategies are evaluated and it will be shown that the adaptive scheduler can be used to make near-optimal decisions.Suchbäume sind allgegenwärtig in Datenbanksystemen und anderen Anwendungen, die eine effiziente Möglichkeit benötigen um in großen Datensätzen nach Einträgen zu suchen, die bestimmte Suchkriterien erfüllen. Sie können mit verschiedenen Strategien konfiguriert werden um den Suchraum zu strukturieren und die für ein Suchergebnis irrelevante Bereiche von der Bearbeitung auszuschließen. Die Entwicklung von anwendungsspezifischen Indexen wird durch Frameworks wie GiST unterstützt. Jedoch unterstützt keines der heute bereits existierenden Frameworks die Verwendung von hochgradig parallelen Prozessorarchitekturen wie GPUs. Solche Prozessoren für generische Index Frameworks nutzbar zu machen, ist Ziel dieser Arbeit. Dazu werden Techniken aus verschiedensten CPU- und GPU-optimierten Indexen analysiert und für die Entwicklung einer GiST-Erweiterung verwendet, welche die für eine Suche in Suchbäumen nötigen Berechnungen abstrahiert. Traversierungsoperationen werden dabei auf vektorisierte Primitive abgebildet, die auf parallelen Prozessoren implementiert werden können. Die Verwendung dieser Erweiterung wird beispielhaft an einem CPU Algorithmus demonstriert. Weiterhin wird ein neuer GPU-basierter Algorithmus vorgestellt, der im Vergleich zu bisherigen Verfahren, ein dynamisches Nachladen der Index Daten in den Hauptspeicher der GPU unterstützt. Die Praktikabilität des erweiterten Frameworks wird am Beispiel von Anwendungen aus der Computergrafik untersucht und die Performanz der verwendeten Algorithmen mit Hilfe eines Benchmarks auf verschiedenen CPU- und GPU-Modellen analysiert. Dabei wird gezeigt, unter welchen Bedingungen die parallele GPU-basierte Ausführung schneller ist als die CPU-basierte Variante - und umgekehrt. Um die Stärken beider Prozessortypen in einem hybriden System ausnutzen zu können, wird ein Scheduler entwickelt, der nach einer Kalibrierungsphase für eine gegebene Operation den geeignetsten Prozessor wählen kann. Mit Hilfe eines Simulators für Baumtraversierungen werden verschiedenste Scheduling Strategien verglichen. Dabei wird gezeigt, dass die Entscheidungen des Schedulers kaum vom Optimum abweichen und, abhängig von der simulierten Last, die erzielbaren Durchsätze für die parallele Ausführung mehrerer Suchoperationen durch hybrides Scheduling um eine Größenordnung und mehr erhöht werden können

Learning event patterns for gesture detection

Usability often plays a key role when software is brought to market, including clearly structured workows, the way of presenting information to the user, and, last but not least, how he interacts with the application. In this context, input devices as 3D cameras or (multi-)touch displays became omnipresent in order to define new intuitive ways of user interaction. State-of-the-art systems tightly couple application logic with separate gesture detection components for supported devices. Hard-coded rules or static models obtained by applying machine learning algorithms on many training samples are used in order to robustly detect a pre defined set of gesture patterns. If possible at all, it becomes difficcult to extend these sets with new patterns or to modify existing ones difficult for both, application developers and end users. Further, adding gesture support for legacy software or for additional devices becomes dificult with this hardwired approach. In previous research we demonstrated how the database community can contribute to this challenge by leveraging complex event processing on data streams to express gesture patterns. While this declarative approach decouples application logic from gesture detection components, its major drawback was the non-intuitive definition of gesture queries. In this paper, we present an approach that is related to density-based clustering in order to find declarative gesture descriptions using only a few samples. We demonstrate the algorithms on mining definitions for multi-dimensional gestures from the sensor data stream that is delivered by a Microsoft Kinect 3D camera, and provide a way for non-expert users to intuitively customize gesturecontrolled user interfaces even during runtime

Extending database accelerators for data transformations and predictive analytics

The IBM DB2 Analytics Accelerator (IDAA) integrates the strong OLTP capabilities of DB2 for z/OS with very fast processing of OLAP workloads using Netezza technology. The accelerator is attached to DB2 as analytical process- ing resource { completely transparent for user applications. But all data modi_cations must be carried out by DB2 and are replicated to the accelerator internally. However, this behavior is not optimized for ELT processing and predic- tive analytics or data mining workloads where multi-staged data transformations are involved. We present our work for extending IDAA with accelerator-only tables, which enable direct data transformations without any necessary interven- tions by DB2. Further, we present a framework for executing arbitrary in-database analytics operations on the accelerator while ensuring data governance aspects like privilege man- agement on DB2 and allowing to ingest data from any other source directly to the accelerator to enrich analytics e. g., with social media data. The evolutionary framework design maintains compatibility with existing infrastructure and ap- plications, a must-have for the majority of customers, while allowing complex analytics beyond read-only reporting

The submarine Azores Plateau : Evidence for a waning mantle plume?

The submarine Azores Plateau in the Central Northern Atlantic has generally been considered to represent a large igneous plateau formed some 10 Ma by widespread volcanism, however a lack of age progression amongst the younger submarine and subaerial volcanism, an irregular distribution of platform-related magmas east and west of the Mid-Atlantic Ridge, a strong tectonic stress regime, and a lack of abundant tholeiitic compositions that reflect initial, high degrees of melting is not easily explainable in the framework of a classic, long-lived mantle plume model. Here, we present new bathymetric and seismic data from the submarine Azores Plateau obtained during cruises M113/1 and M128 with the German R/V Meteor. Our new data combined with prior geochemical and petrological studies indicate that the majority of the western Azores Plateau may indeed have formed during the arrival of a short-lived mantle melting anomaly at 10 Ma. However, our new data also indicate that volcanismPeer reviewe

Negative Regulation of Bone Formation by the Transmembrane Wnt Antagonist Kremen-2

Wnt signalling is a key pathway controlling bone formation in mice and humans. One of the regulators of this pathway is Dkk1, which antagonizes Wnt signalling through the formation of a ternary complex with the transmembrane receptors Krm1/2 and Lrp5/6, thereby blocking the induction of Wnt signalling by the latter ones. Here we show that Kremen-2 (Krm2) is predominantly expressed in bone, and that its osteoblast-specific over-expression in transgenic mice (Col1a1-Krm2) results in severe osteoporosis. Histomorphometric analysis revealed that osteoblast maturation and bone formation are disturbed in Col1a1-Krm2 mice, whereas bone resorption is increased. In line with these findings, primary osteoblasts derived from Col1a1-Krm2 mice display a cell-autonomous differentiation defect, impaired canonical Wnt signalling and decreased production of the osteoclast inhibitory factor Opg. To determine whether the observed effects of Krm2 on bone remodeling are physiologically relevant, we analyzed the skeletal phenotype of 24 weeks old Krm2-deficient mice and observed high bone mass caused by a more than three-fold increase in bone formation. Taken together, these data identify Krm2 as a regulator of bone remodeling and raise the possibility that antagonizing KRM2 might prove beneficial in patients with bone loss disorders

Seismogenic faults, landslides, and associated tsunamis off southern Italy - Cruise No. M86/2, December 27, 2011 - January 17, 2012, Cartagena (Spain) - Brindisi (Italy)

Summary The continental margins of southern Italy are located along converging plate boundaries, which are affected by intense seismicity and volcanic activity. Most of the coastal areas experienced severe earthquakes, landslides, and tsunamis in historical and/or modern times. The most prominent example is the Messina earthquake of Dec. 28, 1908 (Ms=7.3; 80,000 casualties), which was characterized by the worst tsunami Italy experienced in the historical time (~2000 casualties). It is, however, still unclear, whether this tsunami was triggered by a sudden vertical movement along a major fault during the earthquake or as a result of a giant marine slide initiated by the earthquake. The recurrence rates of major landslides and therefore the risk associated with landslides is also unknown. Based on detailed bathymetric data sets collected by Italian colleagues in the frame of the MaGIC Project (Marine Geohazards along the Italian Coast), we collected seismic data (2D and 3D) and gravity cores in three working areas (The Messina Straits, off Eastern Sicily, the Gioia Basin). A dense grid of new 2D-seismic data in the Messina Straits will allow to map fault patterns in great detail. One interesting outcome in this context is the identification of a set of normal faults striking in an EW-direction, which is almost perpendicular to the previously postulated faults. This EW-striking faults seem to be active. The area off eastern Sicily is characterized by numerous landslides and a complex deformation pattern. A 3D-seismic data set has been collected during the cruise using the so called P-cable in order to investigate these deformation patterns in detail. The new data will be the basis for a risk assessment in the working areas

The Effect of Map Boundary on Estimates of Landscape Resistance to Animal Movement

BACKGROUND: Artificial boundaries on a map occur when the map extent does not cover the entire area of study; edges on the map do not exist on the ground. These artificial boundaries might bias the results of animal dispersal models by creating artificial barriers to movement for model organisms where there are no barriers for real organisms. Here, we characterize the effects of artificial boundaries on calculations of landscape resistance to movement using circuit theory. We then propose and test a solution to artificially inflated resistance values whereby we place a buffer around the artificial boundary as a substitute for the true, but unknown, habitat. METHODOLOGY/PRINCIPAL FINDINGS: We randomly assigned landscape resistance values to map cells in the buffer in proportion to their occurrence in the known map area. We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data. We tested the sensitivity of the randomized buffer to the possibility that the composition of the real but unknown buffer is biased toward high or low quality. We found that artificial boundaries result in an overestimate of landscape resistance. CONCLUSIONS/SIGNIFICANCE: Artificial map boundaries overestimate resistance values. We recommend the use of a buffer composed of randomized habitat data as a solution to this problem. We found that resistance estimated using the randomized buffer did not differ from estimates using the real data, even when the composition of the real data was varied. Our results may be relevant to those interested in employing Circuitscape software in landscape connectivity and landscape genetics studies

Development of Randomized Trials in Adults with Medulloblastoma—The Example of EORTC 1634-BTG/NOA-23

From MDPI via Jisc Publications RouterHistory: accepted 2021-07-08, pub-electronic 2021-07-09Publication status: PublishedFunder: Deutsche Krebshilfe; Grant(s): 70113453Funder: Cancer Australia; Grant(s): 1165910Funder: CanTeen; Grant(s): noneFunder: KWF Kankerbestrijding; Grant(s): 2021-1/13555Funder: Ministère des Affaires Sociales et de la Santé; Grant(s): PHRC-K20-179Funder: Swiss Brain Tumor Foundation; Grant(s): none, none, noneMedulloblastoma is a rare brain malignancy. Patients after puberty are rare and bear an intermediate prognosis. Standard treatment consists of maximal resection plus radio-chemotherapy. Treatment toxicity is high and produces disabling long-term side effects. The sonic hedgehog (SHH) subgroup is highly overrepresented in the post-pubertal and adult population and can be targeted by smoothened (SMO) inhibitors. No practice-changing prospective randomized data have been generated in adults. The EORTC 1634-BTG/NOA-23 trial will randomize patients between standard-dose vs. reduced-dosed craniospinal radiotherapy and SHH-subgroup patients between the SMO inhibitor sonidegib (OdomzoTM, Sun Pharmaceuticals Industries, Inc., New York, USA) in addition to standard radio-chemotherapy vs. standard radio-chemotherapy alone to improve outcomes in view of decreased radiotherapy-related toxicity and increased efficacy. We will further investigate tumor tissue, blood, and cerebrospinal fluid as well as magnetic resonance imaging and radiotherapy plans to generate information that helps to further improve treatment outcomes. Given that treatment side effects typically occur late, long-term follow-up will monitor classic side effects of therapy, but also health-related quality of life, cognition, social and professional outcome, and reproduction and fertility. In summary, we will generate unprecedented data that will be translated into treatment changes in post-pubertal patients with medulloblastoma and will help to design future clinical trials

Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis

Summary Background A third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME. Methods We performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed – last updated on March 11, 2021 – including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/). Findings  368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an average internal-external cross-validation concordance-statistic of 0·70 (95%CI 0·68–0·73). Interpretation We were able to predict and validate clinically relevant personalised treatment outcomes for people with JME. Individualised predictions are accessible as nomograms and web-based tools. Funding MING fonds

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions