Quasi-pseudo-metrization of topological preordered spaces

We establish that every second countable completely regularly preordered space (E,T,\leq) is quasi-pseudo-metrizable, in the sense that there is a quasi-pseudo-metric p on E for which the pseudo-metric p\veep^-1 induces T and the graph of \leq is exactly the set {(x,y): p(x,y)=0}. In the ordered case it is proved that these spaces can be characterized as being order homeomorphic to subspaces of the ordered Hilbert cube. The connection with quasi-pseudo-metrization results obtained in bitopology is clarified. In particular, strictly quasi-pseudometrizable ordered spaces are characterized as being order homeomorphic to order subspaces of the ordered Hilbert cube.Comment: Latex2e, 20 pages. v2: minor changes in the proof of theorem 2.

The Ocean Observatories Initiative

Author Posting. © The Oceanography Society, 2018. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 31, no. 1 (2018): 16–35, doi:10.5670/oceanog.2018.105.The Ocean Observatories Initiative (OOI) is an integrated suite of instrumented platforms and discrete instruments that measure physical, chemical, geological, and biological properties from the seafloor to the sea surface. The OOI provides data to address large-scale scientific challenges such as coastal ocean dynamics, climate and ecosystem health, the global carbon cycle, and linkages among seafloor volcanism and life. The OOI Cyberinfrastructure currently serves over 250 terabytes of data from the arrays. These data are freely available to users worldwide, changing the way scientists and the broader community interact with the ocean, and permitting ocean research and inquiry at scales of centimeters to kilometers and seconds to decades.Funding for the OOI is provided by the National Science Foundation through a Cooperative Support Agreement with the Consortium for Ocean Leadership (OCE-1026342)

Performance Data Report: Space Medicine Division, Human Research Program, Behavioural Health and Performance Research Element

This report is the result of a collaborative effort between NASA?s Behavioral Health & Performance (BHP) Research and Operations Group to investigate and determine the availability of data pertaining to behavioral performance (and other pertinent variables) that have been collected by the laboratories at NASA?s Johnson Space Center. BHP?s Operations and Research groups collaborated to systematically identify what types of performance data are needed in relevant BHP performance domains and also to conduct structured interviews with NASA personnel to identify which data do or do not exist currently (and for instances where such data exist, to evaluate the type, quality, accessibility, and confidentiality of those data). The authors defined outcome categories of performance that encapsulate BHP performance domains, mapped BHP Research Risks and Gaps onto those performance outcome categories, and identified and prioritized indicators for each outcome category. The team identified key points of contact (subject matter experts [SMEs]) as potential interviewees, created a template for structured interview questions about sources and accessibility of performance data, and coordinated and conducted structured interviews with the SMEs. The methodology, results, and implications of this effort, as well as forward work needed, are discussed in this report

Space Flight Resource Management for ISS Operations

This slide presentation reviews the International Space Station (ISS) Operations space flight resource management, which was adapted to the ISS from the shuttle processes. It covers crew training and behavior elements

Global Pattern Search at Scale

In recent years, data collection has far outpaced the tools for data analysis in the area of non-traditional GEOINT analysis. Traditional tools are designed to analyze small-scale numerical data, but there are few good interactive tools for processing large amounts of unstructured data such as raw text. In addition to the complexities of data processing, presenting the data in a way that is meaningful to the end user poses another challenge. In our work, we focused on analyzing a corpus of 35,000 news articles and creating an interactive geovisualization tool to reveal patterns to human analysts. Our comprehensive tool, Global Pattern Search at Scale (GPSS), addresses three major problems in data analysis: free text analysis, high volumes of data, and interactive visualization. GPSS uses an Accumulo database for high-volume data storage, and a matrix of word counts and event detection algorithms to process the free text. For visualization, the tool displays an interactive web application to the user, featuring a map overlaid with document clusters and events, search and filtering options, a timeline, and a word cloud. In addition, the GPSS tool can be easily adapted to process and understand other large free-text datasets

Insights into substrate stabilization from snapshots of the peptidyl transferase center of the intact 70S ribosome

Protein synthesis is catalyzed in the peptidyl transferase center (PTC), located in the large (50S) subunit of the ribosome. No high-resolution structure of the intact ribosome has contained a complete active site including both A- and P-site tRNAs. In addition, although past structures of the 50S subunit have found no ordered proteins at the PTC, biochemical evidence suggests that specific proteins are capable of interacting with the 3′ ends of tRNA ligands. Here we present structures, at 3.6-Å and 3.5-Å resolution respectively, of the 70S ribosome in complex with A- and P-site tRNAs that mimic pre- and post-peptidyl-transfer states. These structures demonstrate that the PTC is very similar between the 50S subunit and the intact ribosome. They also reveal interactions between the ribosomal proteins L16 and L27 and the tRNA substrates, helping to elucidate the role of these proteins in peptidyl transfer

The Ocean Observatories Initiative

The Ocean Observatories Initiative (OOI) is an integrated network that enables scientific investigation of interlinked physical, chemical, biological and geological processes throughout the global ocean. With near real-time data delivery via a common Cyberinfrastructure, the OOI instruments two contrasting ocean systems at three scales. The Regional Cabled Array instruments a tectonic plate and overlying ocean in the northeast Pacific, providing a permanent electro-optical cable connecting multiple seafloor nodes that provide high power and bandwidth to seafloor sensors and moorings with instrumented wire crawlers, all with speed-of-light interactive capabilities. Coastal arrays include the Pioneer Array, a relocatable system currently quantifying the New England shelf-break front, and the Endurance Array, a fixed system off Washington and Oregon with connections to the Regional Cabled Array. The Global Arrays host deep-ocean moorings and gliders to provide interdisciplinary measurements of the water column, mesoscale variability, and air-sea fluxes at critical high latitude locations. The OOI has unique aspects relevant to the international ocean observing community. The OOI uses common sensor types, verification protocols, and data formats across multiple platform types in diverse oceanographic regimes. OOI observing is sustained, with initial deployment in 2013 and 25 years of operation planned. The OOI is distributed among sites selected for scientific relevance based on community input and linked by important oceanographic processes. Scientific highlights include real-time observations of a submarine volcanic eruption, time-series observations of methane bubble plumes from Southern Hydrate Ridge off Oregon, observations of anomalous low-salinity pulses off Oregon, discovery of new mechanisms for intrusions of the Gulf Stream onto the shelf in the Middle Atlantic Bight, documentation of deep winter convection in the Irminger Sea, and observations of extreme surface forcing at the most southerly surface mooring in the world ocean

Behavioral Components of NASA's 2017 Astronaut Selection

No abstract availabl