The NASA Cubesat Missions Flying on Artemis-1

In 2021, the Space Launch Services (SLS) Artemis-1 mission will carry thirteen 6U CubeSats into deep space. Three of those payloads are NASA missions performing a variety of unique deep-space science experiments. The three NASA CubeSat missions are BioSentinel, Lunar Flashlight and NEAScout. The BioSentinel mission will measure deep-space radiation effects on DNA using yeast organisms. It is a six-month mission in a heliocentric orbit. BioSentinel was designed, built, tested and operated out of NASA Ames Research Center. Lunar Flashlight’s mission is to look for surface water ice in the permanently shadowed regions near the south pole of the Moon and test out new small spacecraft technologies. The spacecraft was developed at the Jet Propulsion Laboratory as a technology demonstration mission with support from the Marshall Space Flight Center, the Goddard Space Flight Center and Georgia Institute of Technology. NEA Scout’s mission is twofold: to demonstrate solar sail deployment and spacecraft navigation using the sail to detect, track, fly by, and characterize a near earth asteroid. NEA Scout was developed by NASA’s Marshall Space Flight Center in partnership with the Jet Propulsion Laboratory, and support from the Goddard Space Flight Center, Lyndon B. Johnson Space Center, and Langley Research Center

Attention: A review

Attention: A revie

Paper Session II-C - Data Access and Procedure Generation for the International Space Station

The Intelligent Virtual Station (IVS) has been developed by the Smart Systems Research Laboratory at the NASA Ames Research Center as a solution to some of the training and operations challenges faced by organizations like the International Space Station training facilities and Mission Control engineering teams. At present, astronaut crews are constrained by limited access to physical mockups, which themselves have a built-in 1-g limitation. Mission operations teams are faced with the daunting task of controlling the operations and maintenance of an ever-changing Station in space. Many operations teams create and follow textual procedures without the ability to visualize the given actions or alternatives. The IVS allows users to easily generate and view procedures to enhance training and operations. Because training and mission operations are of crucial importance to the International Space Station and other similarly sophisticated programs, this paper is focused on the IVS integrated procedure tool

Starling1 - Mission Technologies Overview

The Starling series of demonstration missions will test technologies required to achieve affordable, distributed spacecraft ("swarm") missions that: are scalable to at least 100 spacecraft for applications that include synchronized multipoint measurements; involve closely coordinated ensembles of two or more spacecraft operating as a single unit for interferometric, synthetic aperture, or similar sensor architectures; or use autonomous or semi-autonomous operation of multiple spacecraft functioning as a unit to achieve science or other mission objectives with low-cost small spacecraft.Starling1 will focus on developing technologies that enable scalability and deep space application. The mission goals include the demonstration of a Mobile Ad-hoc NETwork (MANET) through an in-space communication experiment, vision based relative navigation through the Starling Formation-flying Optical eXperiment (StarFOX), and demonstration of autonomous spacecraft reconfiguration using technologies developed by the Distributed System Autonomy (DSA) project

Improving Situational Awareness for First Responders via Mobile Computing

This project looks to improve first responder incident command, and an appropriately managed flow of situational awareness using mobile computing techniques. The prototype system combines wireless communication, real-time location determination, digital imaging, and three-dimensional graphics. Responder locations are tracked in an outdoor environment via GPS and uploaded to a central server via GPRS or an 802. II network. Responders can also wireless share digital images and text reports, both with other responders and with the incident commander. A pre-built three dimensional graphics model of the emergency scene is used to visualize responder and report locations. Responders have a choice of information end points, ranging from programmable cellular phones to tablet computers. The system also employs location-aware computing to make responders aware of particular hazards as they approach them. The prototype was developed in conjunction with the NASA Ames Disaster Assistance and Rescue Team and has undergone field testing during responder exercises at NASA Ames

SSRL Emergency Response Shore Tool

The SSRL Emergency Response Shore Tool (wherein SSRL signifies Smart Systems Research Laboratory ) is a computer program within a system of communication and mobile-computing software and hardware being developed to increase the situational awareness of first responders at building collapses. This program is intended for use mainly in planning and constructing shores to stabilize partially collapsed structures. The program consists of client and server components, runs in the Windows operating system on commercial off-the-shelf portable computers, and can utilize such additional hardware as digital cameras and Global Positioning System devices. A first responder can enter directly, into a portable computer running this program, the dimensions of a required shore. The shore dimensions, plus an optional digital photograph of the shore site, can then be uploaded via a wireless network to a server. Once on the server, the shore report is time-stamped and made available on similarly equipped portable computers carried by other first responders, including shore wood cutters and an incident commander. The staff in a command center can use the shore reports and photographs to monitor progress and to consult with structural engineers to assess whether a building is in imminent danger of further collapse

Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0

Reconstructing ‘the Alcoholic’: Recovering from Alcohol Addiction and the Stigma this Entails

Public perception of alcohol addiction is frequently negative, whilst an important part of recovery is the construction of a positive sense of self. In order to explore how this might be achieved, we investigated how those who self-identify as in recovery from alcohol problems view themselves and their difficulties with alcohol and how they make sense of others’ responses to their addiction. Semi-structured interviews with six individuals who had been in recovery between 5 and 35 years and in contact with Alcoholics Anonymous were analysed using Interpretative Phenomenological Analysis. The participants were acutely aware of stigmatising images of ‘alcoholics’ and described having struggled with a considerable dilemma in accepting this identity themselves. However, to some extent they were able to resist stigma by conceiving of an ‘aware alcoholic self’ which was divorced from their previously unaware self and formed the basis for a new more knowing and valued identity

Nonequilibrium clumped isotope signals in microbial methane

Methane is a key component in the global carbon cycle with a wide range of anthropogenic and natural sources. Although isotopic compositions of methane have traditionally aided source identification, the abundance of its multiply-substituted “clumped” isotopologues, e.g., 13CH3D, has recently emerged as a proxy for determining methane-formation temperatures; however, the impact of biological processes on methane’s clumped isotopologue signature is poorly constrained. We show that methanogenesis proceeding at relatively high rates in cattle, surface environments, and laboratory cultures exerts kinetic control on 13CH3D abundances and results in anomalously elevated formation temperature estimates. We demonstrate quantitatively that H2 availability accounts for this effect. Clumped methane thermometry can therefore provide constraints on the generation of methane in diverse settings, including continental serpentinization sites and ancient, deep groundwaters.National Science Foundation (U.S.) (EAR-1250394)National Science Foundation (U.S.) (EAR-1322805)Deep Carbon Observatory (Program)Natural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft (Gottfried Wilhelm Leibniz Program)United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship)Neil & Anna Rasmussen FoundationGrayce B. Kerr Fund, Inc. (Fellowship)MIT Energy Initiative (Shell-MITEI Graduate Fellowship)Shell International Exploration and Production B.V. (N. Braunsdorf and D. Smit of Shell PTI/EG grant

Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study:A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments

Grant information: STRADL is supported by the Wellcome Trust through a Strategic Award (104036/Z/14/Z). GS:SFHS received core support from the CSO of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). ADM is supported by Innovate UK, the European Commission, the Scottish Funding Council via the Scottish Imaging Network SINAPSE, and the CSO. HCW is supported by a JMAS SIM Fellowship from the Royal College of Physicians of Edinburgh, by an ESAT College Fellowship from the University of Edinburgh, and has received previous funding from the Sackler Trust. LR has previously received financial support from Pfizer (formerly Wyeth) in relation to imaging studies of people with schizophrenia and bipolar disorder. JDH is supported by the MRC. DJM is an NRS Clinician, funded by the CSO. RMR is supported by the British Heart Foundation. ISP-V and MRM are supported by the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health; and MRM is also supported by the MRC MC_UU_12013/6). JMW is supported by MRC UK Dementia Research Institute and MRC Centre and project grants, EPSRC, Fondation Leducq, Stroke Association, British Heart Foundation, Alzheimer Society, and the European Union H2020 PHC-03-15 SVDs@Target grant agreement (666881). DJP is supported by Wellcome Trust Longitudinal Population Study funding (216767/Z/19/Z) the Eva Lester bequest to the University of Edinburgh. AMM is additionally supported by the MRC (MC_PC_17209, MC_PC_MR/R01910X/1, MR/S035818/1), The Wellcome Trust (216767/Z/19/Z ), The Sackler Trust, and has previously received research funding from Pfizer, Eli Lilly, and Janssen. Both AMM and IJD are members of The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1); funding from the BBSRC and MRC is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptPeer reviewedPublisher PD