DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines—that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring—become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used—increasingly heterogeneous—hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results

Innovative Visualizations Shed Light on Avian Nocturnal Migration

We acknowledge the support provided by COST–European Cooperation in Science and Technology through the Action ES1305 ‘European Network for the Radar Surveillance of Animal Movement’ (ENRAM) in facilitating this collaboration. We thank ENRAM members and researchers attending the EOU round table discussion ‘Radar aeroecology: unravelling population scale patterns of avian movement’ for feedback on the visualizations. We thank Arie Dekker for his feedback as jury member of the bird migration visualization challenge & hackathon hosted at the University of Amsterdam, 25–27 March 2015. We thank Willem Bouten and Kevin Winner for discussion of methodological design. We thank Kevin Webb and Jed Irvine for assistance with downloading, managing, and reviewing US radar data. We thank the Royal Meteorological Institute of Belgium for providing weather radar data.Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals’ life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human–wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement.Yeshttp://www.plosone.org/static/editorial#pee

Interactive Volumetry Of Liver Ablation Zones

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm’s results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.Peer reviewe

Small molecule-mediated rapid maturation of human induced pluripotent stem cell-derived cardiomyocytes

Background: Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iPSC-CMs) do not display all hallmarks of mature primary cardiomyocytes, especially the ability to use fatty acids (FA) as an energy source, containing high mitochondrial mass, presenting binucleation and increased DNA content per nuclei (polyploidism), and synchronized electrical conduction. This immaturity represents a bottleneck to their application in (1) disease modelling—as most cardiac (genetic) diseases have a middle-age onset—and (2) clinically relevant models, where integration and functional coupling are key. So far, several methods have been reported to enhance iPSC-CM maturation; however, these protocols are laborious, costly, and not easily scalable. Therefore, we developed a simple, low-cost, and rapid protocol to promote cardiomyocyte maturation using two small molecule activators of the peroxisome proliferator-activated receptor β/δ and gamma coactivator 1-alpha (PPAR/PGC-1α) pathway: asiatic acid (AA) and GW501516 (GW). Methods and Results: Monolayers of iPSC-CMs were incubated with AA or GW every other day for ten days resulting in increased expression of FA metabolism-related genes and markers for mitochondrial activity. AA-treated iPSC-CMs responsiveness to the mitochondrial respiratory chain inhibitors increased and exhibited higher flexibility in substrate utilization. Additionally, structural maturity improved after treatment as demonstrated by an increase in mRNA expression of sarcomeric-related genes and higher nuclear polyploidy in AA-treated samples. Furthermore, treatment led to increased ion channel gene expression and protein levels. Conclusions: Collectively, we developed a fast, easy, and economical method to induce iPSC-CMs maturation via PPAR/PGC-1α activation. Treatment with AA or GW led to increased metabolic, structural, functional, and electrophysiological maturation, evaluated using a multiparametric quality assessment

DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines—that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring—become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used—increasingly heterogeneous—hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results

Summary of migration flow visualizations.

<p>Information on user control functionality and terminology used in web interface in parentheses. Hyperlinks to online visualizations are provided.</p

Schematic representation of the bird migration flow visualization.

<p>For each radar (Radar 1 & 2), the application will calculate a two-dimensional vector representing the <i>u</i> and <i>v</i> components of the detected ground speed of migration for that radar, altitude band and time interval (T0). Using the x and y positions of the radars, these vectors are interpolated using inverse squared distance weighting to create a vector field of interpolated ground speeds, expressed in pixels. Once the vector field is calculated, the animation starts. At animation frame 1, a streamline A (blue line) is initiated at a random position (blue dot) and the interpolated ground speed at that position is used to draw a line to a new position. This is repeated for each animation frame (2, 3, 4), creating a streamline through the vector field. At animation frame 3 an additional streamline B is initiated. After a fixed number of frames, the application will retrieve data from a new time interval (T1) and update the vector field, influencing the direction and speed of the streamlines.</p