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At least 127 records · Page 7

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗

Effects of angiotensin, vasopressin and atrial natriuretic peptide on intraocular pressure in anesthetized rats

The effects of atrial natriuretic peptide (ANP), vasopressin (AVP) and angiotensin (ANG) on blood and intraocular pressures of pentobarbital anesthetized rats were evaluated following intravenous, intracerebroventricular or anterior chamber routes of administration. Central injections did not affect intraocular pressure. Equipressor intravenous infusions of ANG raised, whereas AVP decreased, intraocular pressure. Direct infusions of a balanced salt solution (0.175 microliter/min) raised intraocular pressure between 30 and 60 min. Adding ANG or ANP slightly reduced this solvent effect but AVP was markedly inhibitory. An AVP-V1 receptor antagonist reversed the blunting of the solvent-induced rise by the peptide, indicating receptor specificity. Acetazolamide pretreatment lowered intraocular pressure, but the solvent-induced rise in intraocular pressure and inhibition by AVP still occurred without altering the temporal pattern. Thus, these effects appear unrelated to aqueous humor synthesis rate. The data support the possibility of intraocular pressure regulation by peptides acting from the blood and aqueous humor.

NASA Discipline Number 14-10↗

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

Incorporation of polarimetric radar images into multisensor data sets

A technique is presented for registering polarimetric SAR data to other aircraft and spaceborne data sets. Resampling is done on the full Stokes matrix, allowing full polarization synthesis on the coregistered data set. Analysis of data acquired over Pisgah Crater in the Mojave Desert, CA, as part of the Mojave Field Experiment shown that the resampling does not seriously affect the pedestal heights of polarization signatures or affect estimates of RMS heights for smooth to moderately rough surfaces.

Evans, Diane L.↗

The Role of Mesoscale Variability on Plankton Dynamics in the North Atlantic

The intensive field observational phase of JGOFS in the North Atlantic Ocean has shown the importance of oceanic mesoscale variability on biogeochemical cycles and on the strength of the ocean biological pump. Mesoscale physical dynamics govern the major time/space scales of bulk biological variability (biomass, production, and export). Mesoscale eddies seem to have a strong impact on the ecosystem structure and functioning, but observational evidence is rather limited. For the signature of the mesoscale features to exist in the ecosystem, the comparison of temporal scales of formation and evolution of mesoscale features and reaction of the ecosystem is a key factor. Biological patterns are driven by active changes in biological source and sink terms rather than simply by passive turbulent mixing. A first modelling assessment of the regional balances between horizontal and vertical eddy-induced nutrient supplies in the euphotic zone shows that the horizontal transport predominates over the vertical route in the subtropical gyre, whereas the reverse holds true for the other biogeochemical provinces of the North Atlantic. Presently, despite some difference in numbers, the net impact of modelled eddies yields an enhancement of the biological productivity in most provinces of the North Atlantic Ocean. Key issues remaining include variation on the mesoscale of subsurface particle and dissolved organic matter remineralization, improved knowledge of the ecological response to patterns of variability, synopticity in mesoscale surveys along with refining measures of biogeochemical time/space variability. Eventual success of assimilation of in situ and satellite data, still in its infancy in coupled physical/biogeochemical models, will be crucial to achieve JGOFS synthesis in answering which data are most informative, standing stocks or rates, and which ones are relevant. Depending on which end of the spectrum quantification of the effect of mesoscale features on production and community structure is required, complementary strategies are offered. Either one may choose to increase resolution of models up to the very fine mesoscale features scale (a few kms) for the high end, or to include a parametric representation of eddies for the low end.

Garcon, Veronique C.↗

The Role of Mesoscale Variability on Plankton Dynamics in the North Atlantic

The intensive field observational phase of JGOFS in the North Atlantic Ocean has shown the importance of oceanic mesoscale variability on biogeochemical cycles and on the strength of the ocean biological pump. Mesoscale physical dynamics govern the major time/space scales of bulk biological variability (biomass, production and export). Mesoscale eddies seem to have a strong impact on the ecosystem structure and functioning, but observational evidence is rather limited. For the signature of the mesoscale features to exist in the ecosystem, the comparison of temporal scales of formation and evolution of mesoscale features and reaction of the ecosystem is a key factor. Biological patterns are driven by active changes in biological source and sink terms rather than simply by passive turbulent mixing. A first modelling assessment of the regional balances between horizontal and vertical eddy-induced nutrient supplies in the euphotic zone shows that the horizontal transport predominates over the vertical route in the subtropical gyre, whereas the reverse holds true for the other biogeochemical provinces of the North Atlantic. Presently. despite some difference in numbers, the net impact of modelled eddies yields an enhancement of the biological productivity in most provinces of the North Atlantic Ocean. Key issues remaining include variation on the mesoscale of subsurface particle and dissolved organic matter remineralization, improved knowledge of the ecological response to patterns of variability, synopticity in mesoscale surveys along with refining measures of biogeochemical time/space variability. Eventual success of assimilation of in situ and satellite data, still in its infancy in coupled physical/biogeochemical models, will be crucial to achieve JGOFS synthesis in answering which data are most informative, standing stocks or rates, and which ones are relevant. Depending on which end of the spectrum quantification of the effect of mesoscale features on production and community structure is required, complementary strategies are offered. Either one may choose to increase resolution of models up to the very fine mesoscale features scale (a few kms) for the high end, or to include a parametric representation of eddies for the low end.

Garcon, Veronique, C.↗

Amino acids of the Murchison meteorite. II - Five carbon acyclic primary beta-, gamma-, and delta-amino alkanoic acids

The five-carbon acyclic primary beta, gamma, and delta amino alkanoic acids of the Murchison meteorite are studied using gas chromatography-mass spectrometry and ion exchange chromatography. The chromatograms reveal that alpha is the most abundant monoamino alkanoic acid followed by gamma and beta, and an exponential increase in the amount of amino acid is observed as the carbon number increases in the homologous series. The influence of frictional heating, spontaneous thermal decomposition, and radiation of the synthesis of amino acids is examined. The data obtained support an amino acid synthesis process involving random combination of single-carbon precursors.

Cronin, J. R.↗

The role of the World Data Centers in handling ocean climate data

The World Data Center System, set up for the International Geophysical Year in 1957, is an international network of data centers that links data contributors to data users in the geosciences. It includes means for the synthesis, analysis, and preparation of data products. It was set up in response to the needs of the international scientific community, and is still overseen by non-governmental scientific organizations. Because it is freely available to researchers in all countries, the World Data Center System has a special role to play in support of ocean climate research and monitoring programs. The World Data Centers face a number of challenges today. Apathy is probably the greatest, since many scientists take the system for granted. There is need to improve access and exploit new technology. The system must establish new links to assure continuity in a world with political changes. The multidisciplinary needs of global change research will demand capabilities for data and information management that go beyond the traditional emphasis on geophysics.

Webster, Ferris↗

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗

The Sensor Management for Applied Research Technologies (SMART) Project

NASA seeks on-demand data processing and analysis of Earth science observations to facilitate timely decision-making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep "learning curve" associated with each sensor, data type, and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output.

Goodman, Michael↗

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

Grecu, Mircea↗

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗

Chemical components of the Apollo 15 regolith

The lunar regolith is a complex mixture of many components. Compositional data is used to identify and estimate the relative importance of the various chemical components of the regolith. The results and conclusions of four methods that were applied to Apollo 15 regolith data were reviewed to determine the important chemical components: graphical techniques, analysis of individual soil particles, factor analysis, and multicomponent mixing models. This synthesis relies heavily on data and conclusions from the literature as well as new analyses on 28 regolith breccia samples, 28 soil samples, and 50 individual 1 to 2 mm particles from soil 15272.

Korotev, R. L.↗

Ocean Surface Vector Wind: Research Challenges and Operational Opportunities

The atmosphere and ocean are joined together over seventy percent of Earth, with ocean surface vector wind (OSVW) stress one of the linkages. Satellite OSVW measurements provide estimates of wind divergence at the bottom of the atmosphere and wind stress curl at the top of the ocean; both variables are critical for weather and climate applications. As is common with satellite measurements, a multitude of OSVW data products exist for each currently operating satellite instrument. In 2012 the Joint Technical Commission on Oceanography and Marine Meteorology (JCOMM) launched an initiative to coordinate production of OSVW data products to maximize the impact and benefit of existing and future OSVW measurements in atmospheric and oceanic applications. This paper describes meteorological and oceanographic requirements for OSVW data products; provides an inventory of unique data products to illustrate that the challenge is not the production of individual data products, but the generation of harmonized datasets for analysis and synthesis of the ensemble of data products; and outlines a vision for JCOMM, in partnership with other international groups, to assemble an international network to share ideas, data, tools, strategies, and deliverables to improve utilization of satellite OSVW data products for research and operational applications.

Joint Technical Commission on Oceanography and Mar↗

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Szuszczewicz, E. P.↗

Retrofitting the AutoBayes Program Synthesis System with Concrete Syntax

AutoBayes is a fully automatic, schema-based program synthesis system for statistical data analysis applications. Its core component is a schema library. i.e., a collection of generic code templates with associated applicability constraints which are instantiated in a problem-specific way during synthesis. Currently, AutoBayes is implemented in Prolog; the schemas thus use abstract syntax (i.e., Prolog terms) to formulate the templates. However, the conceptual distance between this abstract representation and the concrete syntax of the generated programs makes the schemas hard to create and maintain. In this paper we describe how AutoBayes is retrofitted with concrete syntax. We show how it is integrated into Prolog and describe how the seamless interaction of concrete syntax fragments with AutoBayes's remaining legacy meta-programming kernel based on abstract syntax is achieved. We apply the approach to gradually mitigate individual schemas without forcing a disruptive migration of the entire system to a different First experiences show that a smooth migration can be achieved. Moreover, it can result in a considerable reduction of the code size and improved readability of the code. In particular, abstracting out fresh-variable generation and second-order term construction allows the formulation of larger continuous fragments.

Fischer, Bernd↗