New Finite Element Models and Seismic Analyses of the Telescopes at WM Keck Observatory

On 15 October 2006 a large earthquake damaged both telescopes at Keck observatory resulting in weeks of observing downtime. A significant portion of the downtime was attributed to recovery efforts repairing damage to telescope bearing journals, radial pad support structures and encoder subsystems. Inadequate damping and strength in the seismic restraint design and the lack of break-away features on the azimuth radial pads are key design deficiencies. In May, 2011 a feasibility study was conducted to review several options to enhance the protection of the telescopes with the goal to minimize the time to bring the telescopes back into operation after a large seismic event. At that time it was determined that new finite element models of the telescope structures were required to better understand the telescope responses to design earthquakes required by local governing building codes and the USGS seismic data collected at the site on 15 October 2006. These models were verified by comparing the calculated natural frequencies from the models to the measured frequencies obtained from the servo identification study and comparing the time history responses of the telescopes to the October 2006 seismic data to the actual observed damages. The results of two finite element methods, response spectrum analysis and time history analysis, used to determine seismic demand forces and seismic response of each telescope to the design earthquakes were compared. These models can be used to evaluate alternate seismic restraint design options for both Keck telescopes

Provenance-Centered Dataset of Drug-Drug Interactions

Over the years several studies have demonstrated the ability to identify potential drug-drug interactions via data mining from the literature (MEDLINE), electronic health records, public databases (Drugbank), etc. While each one of these approaches is properly statistically validated, they do not take into consideration the overlap between them as one of their decision making variables. In this paper we present LInked Drug-Drug Interactions (LIDDI), a public nanopublication-based RDF dataset with trusty URIs that encompasses some of the most cited prediction methods and sources to provide researchers a resource for leveraging the work of others into their prediction methods. As one of the main issues to overcome the usage of external resources is their mappings between drug names and identifiers used, we also provide the set of mappings we curated to be able to compare the multiple sources we aggregate in our dataset.Comment: In Proceedings of the 14th International Semantic Web Conference (ISWC) 201

Prebiotic Synthesis of Methionine and Other Sulfur-Containing Organic Compounds on the Primitive Earth: A Contemporary Reassessment Based on an Unpublished 1958 Stanley Miller Experiment

Original extracts from an unpublished 1958 experiment conducted by the late Stanley L. Miller were recently found and analyzed using modern state-of-the-art analytical methods. The extracts were produced by the action of an electric discharge on a mixture of methane (CH4), hydrogen sulfide (H2S), ammonia (NH3), and carbon dioxide (CO2). Racemic methionine was formed in significant yields, together with other sulfur-bearing organic compounds. The formation of methionine and other compounds from a model prebiotic atmosphere that contained H2S suggests that this type of synthesis is robust under reducing conditions, which may have existed either in the global primitive atmosphere or in localized volcanic environments on the early Earth. The presence of a wide array of sulfur-containing organic compounds produced by the decomposition of methionine and cysteine indicates that in addition to abiotic synthetic processes, degradation of organic compounds on the primordial Earth could have been important in diversifying the inventory of molecules of biochemical significance not readily formed from other abiotic reactions, or derived from extraterrestrial delivery

Extraterrestrial Amino Acids in the Almahata Sitta Meteorite

Amino acid analysis of a meteorite fragment of asteroid 2008 TC3 called Almahata Sitta was carried out using reverse-phase liquid chromatography coupled with UV fluorescence detection and time-of-flight mass spectrometry (LC-FD/ToF-MS) as part of a sample analysis consortium. LC-FD/ToF-MS analyses of hot-water extracts from the meteorite revealed a complex distribution of two- to seven-carbon aliphatic amino acids and one- to three-carbon amines with abundances ranging from 0.5 to 149 parts-per-billion (ppb). The enantiomeric ratios of the amino acids alanine, R-amino-n-butyric acid (beta-ABA), 2-amino-2-methylbutanoic acid (isovaline), and 2-aminopentanoic acid (norvaline) in the meteorite were racemic (D/L approximately 1), indicating that these amino acids are indigenous to the meteorite and not terrestrial contaminants. Several other non-protein amino acids were also identified in the meteorite above background levels including alpha-aminoisobutyric acid (alpha-AIB), 4-amino-2- methylbutanoic acid, 4-amino-3-methylbutanoic acid, and 3-, 4-, and 5-aminopentanoic acid. The total abundances of isovaline and alpha-AIB in Almahata Sitta are 1000 times lower than the abundances of these amino acids found in the CM carbonaceous chondrite Murchison. The extremely low abundances and unusual distribution of five carbon amino acids in Almahata Sitta compared to Cl, CM, and CR carbonaceous chondrites may reflect extensive thermal alteration of amino acids on the parent asteroid by partial melting during formation or subsequent impact shock heating. It is also possible that amino acids were synthesized by catalytic reactions on the parent body after asteroid 2008 TC3 cooled to lower temperatures

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches