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Modern GPUs come with dedicated hardware to perform ray/triangle intersections and bounding volume hierarchy (BVH) traversal. While the primary use case for this hardware is photorealistic 3D computer graphics, with careful algorithm design scientists can also use this special-purpose hardware to accelerate general-purpose computations such as point containment queries. This article explains the principles behind these techniques and their application to vector field visualization of large simulation data using particle tracing.
When the Artemis missions launch, NASA's Orion spacecraft (and crew as of the Artemis II mission) will be exposed to the deep space radiation environment beyond the protection of Earth's magnetosphere. Hence, it is essential to characterize the effects of space radiation, microgravity, and the combination thereof on cells and organisms, i.e., to quantify any correlations between the deep space radiation environment, genetic variation, and induced genetic changes in cells. To address this, the Artemis I mission will include the Peristaltic Laboratory for Automated Science with Multigenerations (PLASM) hardware containing the Deep Space Radiation Genomics (DSRG) experiment. The scientific aims of DSRG are (i) to identify the metabolic and genomic pathways in yeast affected by microgravity, space radiation, and their combination, and (ii) to differentiate between gravity and radiation exposure on single-gene deletion/overexpressing strains' ability to thrive in the spaceflight environment. Yeast is used as a model system because 70% of its essential genes have a human homolog, and over half of these homologs can functionally replace their human counterpart. As part of the experiment preparation towards spaceflight, an Experiment Verification Test (EVT) was performed at the Kennedy Space Center to verify that the experiment design, hardware, and approach to automated operations will enable achieving the scientific aims. For the EVT, fluidic systems were assembled, sterilized, loaded, and acceptance-tested, and subsequently integrated with the engineering parts to produce a flight-like PLASM unit. Each fluidic system consisted of (i) a Media Bag, (ii) four Culture Bags loaded with Saccharomyces cerevisiae (two with deletion series and the remaining two with overexpression series), and (iii) tubing and check valves. The EVT PLASM unit was put under a temperature profile replicating the anticipated different phases of flight, including handover to launch, spaceflight, and splashdown to handover back to the science team, for a 58-day period. At EVT completion, the rate of activation, cellular growth, RNA integrity, and sample contamination were interrogated. All of the experiment's success criteria were satisfied, encouraging our efforts to perform this investigation on Artemis I. This manuscript thus describes the process of spaceflight experiment design maturation with a focus on the EVT, its results, DSRG's preparation for its planned launch on Artemis I in 2022, and how the PLASM hardware can enable other scientific goals on future Artemis missions and/or the Lunar Orbital Platform – Gateway.
Error analysis in a high accuracy sampled-data velocity stabilising system using Volterra series
(2015)
Extremophiles are optimal models in experimentally addressing questions about the effects of cosmic radiation on biological systems. The resistance to high charge energy (HZE) particles, and helium (He) ions and iron (Fe) ions (LET at 2.2 and 200 keV/µm, respectively, until 1000 Gy), of spores from two thermophiles, Bacillushorneckiae SBP3 and Bacilluslicheniformis T14, and two psychrotolerants, Bacillus sp. A34 and A43, was investigated. Spores survived He irradiation better, whereas they were more sensitive to Fe irradiation (until 500 Gy), with spores from thermophiles being more resistant to irradiations than psychrotolerants. The survived spores showed different germination kinetics, depending on the type/dose of irradiation and the germinant used. After exposure to He 1000 Gy, D-glucose increased the lag time of thermophilic spores and induced germination of psychrotolerants, whereas L-alanine and L-valine increased the germination efficiency, except alanine for A43. FTIR spectra showed important modifications to the structural components of spores after Fe irradiation at 250 Gy, which could explain the block in spore germination, whereas minor changes were observed after He radiation that could be related to the increased permeability of the inner membranes and alterations of receptor complex structures. Our results give new insights on HZE resistance of extremophiles that are useful in different contexts, including astrobiology.
We present GEM-NI -- a graph-based generative-design tool that supports parallel exploration of alternative designs. Producing alternatives is a key feature of creative work, yet it is not strongly supported in most extant tools. GEM-NI enables various forms of exploration with alternatives such as parallel editing, recalling history, branching, merging, comparing, and Cartesian products of and for alternatives. Further, GEM-NI provides a modal graphical user interface and a design gallery, which both allow designers to control and manage their design exploration. We conducted an exploratory user study followed by in-depth one-on-one interviews with moderately and highly skills participants and obtained positive feedback for the system features, showing that GEM-NI supports creative design work well.
We present a new interface for interactive comparisons of more than two alternative documents in the context of a generative design system that uses generative data-flow networks defined via directed acyclic graphs. To better show differences between such networks, we emphasize added, deleted, (un)changed nodes and edges. We emphasize differences in the output as well as parameters using highlighting and enable post-hoc merging of the state of a parameter across a selected set of alternatives. To minimize visual clutter, we introduce new difference visualizations for selected nodes and alternatives using additive and subtractive encodings, which improve readability and keep visual clutter low. We analyzed similarities in networks from a set of alternative designs produced by architecture students and found that the number of similarities outweighs the differences, which motivates use of subtractive encoding. We ran a user study to evaluate the two main proposed difference visualization encodings and found that they are equally effective.
In den Medien wird momentan immer mehr die Rolle von klein- und mittelständischen Betrieben, als "Jobmotor" für Deutschland betont. Darunter fallen auch Neugründungen. Wirtschaftspolitisch interessant sind deswegen vor allem innovative, wachstumsstarke Existenzgründungen. Verschiedene Untersuchungen geben Grund zu der Annahme, dass vornehmlich Hochschulabsolventen solche Unternehmen gründen. "Unternehmerisches Denken" ist eine Schlüsselqualifikation geworden, die für die berufliche Zukunft von Hochschulabsolventen von steigender Bedeutung ist. Unternehmern zugesprochene Eigenschaften, wie Eigeninitiative, Übernahme von Verantwortung, Führungsqualität und Belastbarkeit auch in besonderen Stresssituationen sind für viele etablierte Unternehmen als Einstellungskriterium für Akademiker stärker in den Vordergrund gerückt.
The increasing complexity of tasks that are required to be executed by robots demands higher reliability of robotic platforms. For this, it is crucial for robot developers to consider fault diagnosis. In this study, a general non-intrusive fault diagnosis system for robotic platforms is proposed. A mini-PC is non-intrusively attached to a robot that is used to detect and diagnose faults. The health data and diagnosis produced by the mini-PC is then standardized and transmitted to a remote-PC. A storage device is also attached to the mini-PC for data logging of health data in case of loss of communication with the remote-PC. In this study, a hybrid fault diagnosis method is compared to consistency-based diagnosis (CBD), and CBD is selected to be deployed on the system. The proposed system is modular and can be deployed on different robotic platforms with minimum setup.
This work presents the preliminary research towards developing an adaptive tool for fault detection and diagnosis of distributed robotic systems, using explainable machine learning methods. Autonomous robots are complex systems that require high reliability in order to operate in different environments. Even more so, when considering distributed robotic systems, the task of fault detection and diagnosis becomes exponentially difficult.
To diagnose systems, models representing the behaviour under investigation need to be developed, and with distributed robotic systems generating large amount of data, machine learning becomes an attractive method of modelling especially because of its high performance. However, with current day methods such as artificial neural networks (ANNs), the issue of explainability arises where learnt models lack the ability to give explainable reasons behind their decisions.
This paper presents current trends in methods for data collection from distributed systems, inductive logic programming (ILP); an explainable machine learning method, and fault detection and diagnosis.
Intention: Within the research project EnerSHelF (Energy-Self-Sufficiency for Health Facilities in Ghana), i. a. energy-meteorological and load-related measurement data are collected, for which an overview of the availability is to be presented on a poster.
Context: In Ghana, the total electricity consumed has almost doubled between 2008 and 2018 according to the Energy Commission of Ghana. This goes along with an unstable power grid, resulting in power outages whenever electricity consumption peaks. The blackouts called "dumsor" in Ghana, pose a severe burden to the healthcare sector. Innovative solutions are needed to reduce greenhouse gas emissions and improve energy and health access.
Orešković and Porsdam Mann draw a distinction between ‘fast’ and ‘slow’ science. Whereas the latter involves rigorous and laborious adherence to the scientific method, the former represents the reality that much scientific work faces time pressures which at times force shortcuts. The distinction can be seen to operate in contemporary research into the coronavirus pandemic: whereas the development of vaccines and treatments usually requires years of meticulous laboratory work and several more years of clinical testing, the many millions suffering from the disease need a treatment now. However, by taking too many safeguards off the treatment discovery and testing pipelines, or by refusing to act in accordance with scientific advice, governments risk sacrificing the public’s trust not only in the government’s scientific bona fides but in the scientific process itself. This is a heavy price to pay, argue Orešković and Porsdam Mann, and point to evidence indicating that the success of Germany and Japan in combating COVID-19 can be traced to public trust in science and government, as well as scientifically-informed and respectful national leadership.