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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Elastic knowledge base of bcc Ti alloys from first-principles calculations and CALPHAD-based modeling

Here, titanium alloys are being investigated as suitable materials for load-bearing implants because of their biocompatibility and mechanical properties. Stress shielding, a common issue with the current load-bearing implant materials, occurs due to a Young’s modulus (E) mismatch between bone (~10–40 GPa) and implants (such as Ti-6Al-4V ~ 110 GPa), which leads to bone dying around the implant and ultimately implant failure. Reducing the Young’s modulus of Ti alloys may overcome the issues of stress shielding and improve implant materials. In the present work, first-principles calculations have been used to predict the single crystal elastic stiffness coefficients (c ij ’s) for the Ti-containing ternary alloys Ti-X-Y(X ≠ Y = Mo, Nb, Sn, Ta, Zr) in the bcc lattice. It is found that the ternary Ti-X-Y (X ≠ Y = Mo, Nb, Ta) alloys behave similarly; so do the ternary Ti-X-Sn (X = Mo, Nb, Ta) alloys and the Ti-X-Zr (X = Mo, Nb, Ta) alloys. This is expected due to the similarity between the Mo, Nb and Ta elements. The results also show that the Ti-Zr-X alloys stabilized the bcc phase at lower alloying concentrations. The polycrystalline aggregate properties are also estimated from the c ij ’s, including bulk modulus, shear modulus and Young’s modulus. The results show that Ti-alloys with compositions close to the bcc stability limit have the lowest E. In combination with previous predictions, a complete elastic database has been established using theCALPHAD (CALculation of PHAse Diagram) based modeling approach. The database results are compared with the E of higher order Ti alloys and shown to be able to predict the E accurately. This complete data-base forms a foundation to tailor Ti alloys for desired elastic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Dynamic analysis environment for nuclear forensic analyses

We report a Dynamic Analysis Environment (DAE) software package is introduced to facilitate group inclusion/exclusion method testing, evaluation and comparison for pre-detonation nuclear forensics applications. Employing DAE, the multivariate signatures of a questioned material can be compared to the signatures for different, known groups, enabling the linking of the questioned material to its potential process, location, or fabrication facility. Advantages of using DAE for group inclusion/exclusion include built-in query tools for retrieving data of interest from a database, the recording and documentation of all analysis steps, a clear visualization of the analysis steps intelligible to a non-expert, and the ability to integrate analysis tools developed in different programming languages. Two group inclusion/exclusion methods are implemented in DAE: principal component analysis, a parametric feature extraction method, and k nearest neighbors, a nonparametric pattern recognition method. Spent Fuel Isotopic Composition (SFCOMPO), an open source international database of isotopic compositions for spent nuclear fuels (SNF) from 14 reactors, is used to construct PCA and KNN models for known reactor groups, and 20 simulated SNF samples are utilized in evaluating the performance of these group inclusion/exclusion models. For all 20 simulated samples, PCA in conjunction with the Q statistic correctly excludes a large percentage of reactor groups and correctly includes the true reactor of origination. As a result, employing KNN, 14 of the 20 simulated samples are classified to their true reactor of origination.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Python Group Additivity (pGrAdd) software for estimating species thermochemical properties

ncreasingly complex chemistry models require thermochemical data for many species often estimated from costly first-principles DFT computations. Here we introduce the Python Group Additivity software (pGrAdd) that implements comprehensive group additivity in a simple, modular, lightweight Python package that is extensible and easy to implement. It includes 6 group additivity databases for gas species and Pt(111) adsorbates allowing users to immediately compute thermochemical properties for a wide range of molecules and build new databases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

EnZymClass: Substrate specificity prediction tool of plant acyl-ACP thioesterases based on ensemble learning

Characterizing the functional properties of plant acyl-ACP thioesterases (TEs), a key enzyme class used in the production of renewable oleochemicals in microbial hosts, experimentally, can be an expensive and time consuming process since it requires manual screening of thousands of candidates in a database. Using amino acid sequence to computationally predict an enzyme’s function might accelerate this process; however obtaining the necessary amount of information on previously characterized enzymes and their respective sequences required by standard Machine Learning (ML) based approaches to accurately infer sequence-function relationships can be prohibitive, especially with a low-throughput testing cycle. Experimental noise, unbalanced dataset where high sequence similarity does not always imply identical functional properties will further prevent robust prediction performance. Herein we present a ML method, Ensemble method for enZyme Classification (EnZymClass), that is specifically designed to address these issues. We used EnZymClass to classify TEs into short, long and mixed free fatty acid substrate specificity categories. While general guidelines for inferring substrate specificity have been proposed before, prediction of chain-length preference from primary sequence has remained elusive for plant acyl-ACP TEs. By applying EnZymClass to a subset of TEs in the ThYme database, we identified two medium chain TEs, ClFatB3 and CwFatB2, with previously uncharacterized activity in E. coli fatty acid production hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Dataset describing two reference models for full-spectral lighting and daylight simulations together with implementations for two software systems

A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained from an online spectral materials database. Glazing transmittance was derived from IGDB data using LBNL Optics/WINDOW. BSDFs for venetian blinds at various tilt angles, and for a diffusing pane adapted from the Complex Glazing Database, were generated in WINDOW. Luminaires in both models are specified with photometric files (Eulumdat/IES) and lamp spectra (Fluorescent 840, 4000 K LED). The provided example implementations (Radiance, OWL) include prepared input data and scripts to run first spectral simulations; example results are also included. The dataset is prepared to support reuse by researchers, designers and software developers for method validation, software engineering and comparison, and development of spectral metrics and controls.

Geisler-Moroder, David↗
DOE OSTI2018

Particulate sulfur-containing lipids: Production and cycling from the epipelagic to the abyssopelagic zone

There are major gaps in our understanding of the distribution and role of lipids in the open ocean especially with regard to sulfur-containing lipids (S-lipids). In this study, we employ a powerful analytical approach based on high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to elucidate depth-related S-lipid production and molecular transformations in suspended particulate matter from the Northeast Atlantic Ocean in this depth range. We show that within the open-ocean environment S-lipids contribute up to 4.2% of the particulate organic carbon, and that up to 95% of these compounds have elemental compositions that do not match those found in the Nature Lipidomics Gateway database (termed “novel”). Among the remaining 5% of lipids that match the database, we find that sulphoquinovosyldiacylglycerol (SQDG) are efficiently removed while sinking through the mesopelagic zone. The relative abundance of other assigned lipids (sulphoquinovosylmonoacylglycerol (SQMG), sulfite and sulfate lipids, Vitamin D2 and D3 derivatives, and sphingolipids) did not change substantially with depth. The novel S-lipids, represented by hundreds of distinct elemental compositions (160–300 molecules at any one depth), contribute increasingly to the lipid and particulate organic matter pools with increased depth. Depth-related transformations cause (i) incomplete degradation/transformation of unsaturated S-lipids which leads to the depth-related accumulation of the refractory saturated compounds with reduced molecular weight (average 455 Da) and (ii) formation of highly unsaturated S-lipids (average abyssopelagic molecular double bond equivalents, DBE=7.8) with lower molecular weight (average 567 Da) than surface S-lipids (average 592 Da). A depth-related increase in molecular oxygen content is observed for all novel S-lipids and indicates that oxidation has a significant role in their transformation while (bio)hydrogenation possibly impacts the formation of saturated compounds. The instrumentation approach applied here represents a step change in our comprehension of marine S-lipid diversity and the potential role of these compounds in the oceanic carbon cycle. We describe a very much higher number of compounds than previously reported, albeit at the level of elemental composition and fold-change quantitation with depth, rather than isomeric confirmation and absolute quantitation of individual lipids. We emphasize that saturated S-lipids have the potential to transfer carbon from the upper ocean to depth and hence are significant vectors for carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A reporting format for field measurements of soil respiration

Field observations of the soil-to-atmosphere CO2 flux–soil respiration, RS–are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and novel syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the field as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, and optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g. FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. Finally, this proposed RS reporting format is available online, and is intended to be a dynamic document, subject to further community feedback and/or change in the future.

Bond-Lamberty, Benjamin↗
DOE OSTI2017

Industrial CO 2 and Carbon Capture: Near-term Benefit, Long-term Necessity

Industry emits approximately 1 billion tonnes of CO 2 each year (1 GTCO 2 /yr) in the United States–one-third of US stationary emissions–and an even greater amount in industry-heavy China. We hypothesize that capturing industrial CO 2 offers a near-term pathway to jumpstart CO 2 capture and storage (CCS) and is a long-term necessity to stabilize atmospheric CO 2 in order to avoid catastrophic climate impacts. We then explore this proposition using several new CO 2 emissions and storage databases for the United States, as well as emerging research including the economics of industrial CO 2 capture. We refer to our new “sources of CO 2 that are not electricity” database as SCO 2 NE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Monitoring: The missing piece

The U.S. National Environmental Policy Act (NEPA) of 1969 heralded in an era of more robust attention to environmental impacts resulting from larger scale federal projects. The number of other countries that have adopted NEPA's framework is evidence of the appeal of this type of environmental legislation. Mandates to review environmental impacts, identify alternatives, and provide mitigation plans before commencement of the project are at the heart of NEPA. Such project reviews have resulted in the development of a vast number of reports and large volumes of project-specific data that potentially can be used to better understand the components and processes of the natural environment and provide guidance for improved and efficient environmental protection. However, the environmental assessment (EA) or the more robust and intensive environmental impact statement (EIS) that are required for most major projects more frequently than not are developed to satisfy the procedural aspects of the NEPA legislation while they fail to provide the needed guidance for improved decision-making. While NEPA legislation recommends monitoring of project activities, this activity is not mandated, and in those situations where it has been incorporated, the monitoring showed that the EIS was inaccurate in direction and/or magnitude of the impact. Many reviews of NEPA have suggested that monitoring all project phases, from the design through the decommissioning, should be incorporated. Information gathered though a well-developed monitoring program can be managed in databases and benefit not only the specific project but would provide guidance how to better design and implement future activities designed to protect and enhance the natural environment. -- Highlights: • NEPA statutes created profound environmental protection legislative framework. • Contrary to intent, NEPA does not provide for definitive project monitoring. • Robust project monitoring is essential for enhanced environmental management. • Adaptive database framework is needed to accommodate project-monitoring data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Adaptation of methodology to select structural alternatives of one-way slab in residential building to the guidelines of the European Committee for Standardization (CEN/TC 350)

The European Committee for Standardization (CEN) through its Technical Committee CEN/TC-350 is developing a series of standards for assessing the building sustainability, at both product and building levels. The practical application of the selection (decision making) of structural alternatives made by one-way slabs leads to an intermediate level between the product and the building. Thus the present study addresses this problem of decision making, following the CEN guidelines and incorporating relevant aspects of architectural design into residential construction. A life cycle assessment (LCA) is developed in order to obtain valid information for the decision making process (the LCA was developed applying CML methodology although Ecoindicator99 was used in order to facilitate the comparison of the values); this information (the carbon footprint values) is contrasted with other databases and with the information from the Environmental Product Declaration (EPD) of one of the lightening materials (expanded polystyrene), in order to validate the results. Solutions of different column disposition and geometries are evaluated in the three pillars of sustainable construction on residential construction: social, economic and environmental. The quantitative analysis of the variables used in this study enables and facilitates an objective comparison in the design stage by a responsible technician; the application of the proposed methodology reduces the possible solutions to be evaluated by the expert to 12.22% of the options in the case of low values of the column index and to 26.67% for the highest values. - Highlights: • Methodology for selection of structural alternatives in buildings with one-way slabs • Adapted to CEN guidelines (CEN/TC-350) for assessing the building sustainability • LCA is developed in order to obtain valid information for the decision making process. • Results validated comparing carbon footprint, databases and Env. Product Declarations • The proposal reduces the solutions to be evaluated to between 12.22 and 26.67%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Using E-PRTR data on point source emissions to air and water—First steps towards a national chemical footprint

There is a great need for indicators to monitor the use and potential impacts of hazardous chemicals. Today there is a huge lack of data, methods and results and method development and studies should be given urgent priority. The aim of this paper was to develop and test an approach to calculate the potential environmental impacts of chemicals for a whole country using the E-PRTR (European Pollutant Release and Transfer Register) as a database and Sweden as an example. Swedish data from 2008 on emissions to air and water for 54 substances from point sources were retrieved from an open database. The data were transformed and aggregated using USEtox, a life-cycle impact assessment (LCIA) method for calculating potential human toxicity and ecotoxicity, both from industrial emissions directly and after input–output analysis (IO analysis) to reallocate emissions to product categories. Zinc to air and water contributed most to human toxicity followed by mercury to air. The largest contribution by industry to potential human toxicity came from the metal industry, followed by the paper and paper product industry. For potential ecotoxicity, zinc, fluoranthene and copper contributed the most. The largest contributions by industry came from the paper and paper products manufacturing sector, followed by the basic metals manufacturing sector. The approach used here can be seen as the first step towards a chemical footprint for nations. By adding data from other countries and other sources, a more complete picture can be gained in line with other footprint calculations. Furthermore, diffuse emissions from, for example, transport or emissions of pesticides could also be added for a more holistic assessment. Since the area of chemicals is complicated, it is probably necessary to develop and use several indicators that complement each other. It is suggested that the approach outlined here could be useful in developing a method for establishing a national chemical footprint. - Highlights: • European Pollutant and Transfer Register (E-PRTR) used to develop indicators • Study combined emissions to air and water from E-PRTR with USEtox and IO analysis • Metals and especially zinc contributed most to potential human toxicity and ecotoxicity • Paper and metal industries contribute most to potential human toxicity and ecotoxicity • This new assessment could be used by many countries and can be developed further.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mapping thermal energy storage technologies with advanced nuclear reactors

Advanced nuclear power plants (NPPs) will potentially need to operate in environments where power generation flexibility is more highly valued than the stability or baseload generation capability for conventional demand curves. Thermal energy storage (TES) systems would enable NPPs to respond nimbly to market variability and could also position advanced NPPs to participate differently in restructured markets, thus further enhancing their economic competitiveness. TES systems could also benefit the electric grid by eliminating the need for peaking plants, as well as by improving the economic performance of baseload NPPs. While TES technologies afford a unique opportunity to address many of these challenges, the applicability of these systems is also complicated by the fact that various advanced NPPs are designed differently, each with its own temperature range, size, operating fluids, and operating conditions. Hence, TES systems face significant barriers to investment, as more information on their compatibility and performance metrics is needed to quantify the advantages provided by each, as well as the challenges these technologies might face if coupled with a particular type of advanced NPP. This study explores the possibility of integrating a wide variety of TES technologies with various categories of advanced NPPs, based on their operating characteristics. To help decision makers, users and developers decide which TES technology is best suited to a particular category of advanced NPPs, this research present a Phenomena Identification and Ranking Table (PIRT) analysis of 10 TES systems that could potentially be coupled with advanced NPPs, which themselves are divided into nine categories based on their operating conditions. Then, each advanced NPP category is evaluated for compatibility with the 10 TES systems by assembling and discussing a database of information concerning 10 engineering questions, defined herein in as figures of merit (FOMs), such as: technology readiness level (TRL), temperature compatibility, energy density, size, cycle frequency, ramp time, realignment frequency, geographic needs, environmental impact, and interventions. By assembling a database of information concerning the TES technologies' compatibility with various advanced NPP systems, this study can help developers acquaint themselves with a particular TES technology before choosing to build a new integrated installation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF)

The bioconcentration factor (BCF) is an important bioaccumulation hazard assessment metric in many regulatory contexts. Its assessment is required by the REACH regulation (Registration, Evaluation, Authorization and Restriction of Chemicals) and by CLP (Classification, Labeling and Packaging). We challenged nine well-known and widely used BCF QSAR models against 851 compounds stored in an ad-hoc created database. The goodness of the regression analysis was assessed by considering the determination coefficient (R{sup 2}) and the Root Mean Square Error (RMSE); Cooper's statistics and Matthew's Correlation Coefficient (MCC) were calculated for all the thresholds relevant for regulatory purposes (i.e. 100 L/kg for Chemical Safety Assessment; 500 L/kg for Classification and Labeling; 2000 and 5000 L/kg for Persistent, Bioaccumulative and Toxic (PBT) and very Persistent, very Bioaccumulative (vPvB) assessment) to assess the classification, with particular attention to the models' ability to control the occurrence of false negatives. As a first step, statistical analysis was performed for the predictions of the entire dataset; R{sup 2}>0.70 was obtained using CORAL, T.E.S.T. and EPISuite Arnot–Gobas models. As classifiers, ACD and log P-based equations were the best in terms of sensitivity, ranging from 0.75 to 0.94. External compound predictions were carried out for the models that had their own training sets. CORAL model returned the best performance (R{sup 2}{sub ext}=0.59), followed by the EPISuite Meylan model (R{sup 2}{sub ext}=0.58). The latter gave also the highest sensitivity on external compounds with values from 0.55 to 0.85, depending on the thresholds. Statistics were also compiled for compounds falling into the models Applicability Domain (AD), giving better performances. In this respect, VEGA CAESAR was the best model in terms of regression (R{sup 2}=0.94) and classification (average sensitivity>0.80). This model also showed the best regression (R{sup 2}=0.85) and sensitivity (average>0.70) for new compounds in the AD but not present in the training set. However, no single optimal model exists and, thus, it would be wise a case-by-case assessment. Yet, integrating the wealth of information from multiple models remains the winner approach. - Highlights: • REACH encourages the use of in silico methods in the assessment of chemicals safety. • The performances of nine BCF models were evaluated on a benchmark database of 851 chemicals. • We compared the models on the basis of both regression and classification performance. • Statistics on chemicals out of the training set and/or within the applicability domain were compiled. • The results show that QSAR models are useful as weight-of-evidence in support to other methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Identification of mycotoxins by UHPLC–QTOF MS in airborne fungi and fungi isolated from industrial paper and antique documents from the Archive of Bogotá

Mold deterioration of historical documents in archives and libraries is a frequent and complex phenomenon that may have important economic and cultural consequences. In addition, exposure to toxic fungal metabolites might produce health problems. In this work, samples of broths of fungal species isolated from the documentary material and from indoor environmental samples of the Archive of Bogotá have been analyzed to investigate the presence of mycotoxins. High resolution mass spectrometry made possible to search for a large number of mycotoxins, even without reference standards available at the laboratory. For this purpose, a screening strategy based on ultra-high pressure liquid chromatography coupled to quadrupole-time of flight mass spectrometry (UHPLC–QTOF MS) under MS{sup E} mode was applied. A customized home-made database containing elemental composition for around 600 mycotoxins was compiled. The presence of the (de)protonated molecule measured at its accurate mass was evaluated in the samples. When a peak was detected, collision induced dissociation fragments and characteristic isotopic ions were also evaluated and used for tentative identification, based on structure compatibility and comparison with literature data (if existing). Up to 44 mycotoxins were tentatively identified by UHPLC–QTOF MS. 34 of these tentative compounds were confirmed by subsequent analysis using a targeted LC–MS/MS method, supporting the strong potential of QTOF MS for identification/elucidation purposes. The presence of mycotoxins in these samples might help to reinforce safety measures for researchers and staff who work on reception, restoration and conservation of archival material, not only at the Archive of Bogotá but worldwide. - Highlights: • Mold deterioration of historical documents is a frequent and complex phenomenon. • Samples of broths of fungal species isolated from Archive of Bogotá analyzed. • UHPLC–QTOF MS (MS{sup E}) applied for mycotoxins screening, without reference standards. • Customized home-made database for around 600 mycotoxins compiled. • 44 mycotoxins tentatively identified, 34 of which confirmed by LC–MS/MS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Association of UV radiation with Parkinson disease incidence: A nationwide French ecologic study

Background: Vitamin D is thought to contribute to brain health, but it is unclear whether low vitamin D levels are associated with increased incidence of Parkinson's disease (PD). Using ultraviolet B (UV-B) as a surrogate for vitamin D levels, we conducted a nationwide ecologic study in France in order to examine the association of UV-B with PD incidence. Methods: We used French national drug claims databases to identify PD cases using a validated algorithm. UV-B data from the solar radiation database were derived from satellite images. We estimated PD incidence (2010–2012) at the canton level (small administrative French unit) and used multilevel Poisson regression to examine its association with UV-B (2005 annual average), after adjustment for age, sex, deprivation index, density of neurologists, smoking, proportion of agricultural land, and vitamin D supplementation. Results: Analyses are based on 69,010 incident PD patients. The association between UV-B and PD incidence was quadratic (P<0.001) and modified by age (P<0.001). Below 70y, incidence was higher in the bottom quintile (relative risk, RR{sub Q1:45-49y}=1.18, 95% CI=1.08–1.29) compared with the middle UV-B quintile, and lower in the top quintile (RR{sub Q5:45-49y}=0.85 [0.77–0.94]). An opposite pattern was observed in older subjects (RR{sub Q1:85-89y}=0.92 [0.89–0.96]; RR{sub Q5:85-89y}=1.06 [1.02–1.11]). Analysis based on continuous UV-B yielded similar conclusions. Conclusions: In this nationwide study, there was an age-dependent quadratic association between UV-B and PD incidence. This study suggests that reasonable UV-B exposure is associated with lower PD risk in younger persons and that future studies should examine dose-response relations and take age into account. - Highlights: • There is an age-dependent quadratic association between UV-B and PD incidence. • Reasonable UV-B exposure is beneficial in younger persons for the risk of PD. • Our findings are consistent with a role of vitamin D in PD, especially at younger ages. • Future studies should examine dose-effect relations and take age into account.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

A Scientific Data Processing Framework for Time Series NetCDF Data

ARM Data Integrator (ADI) is a framework to streamline the development of scientific algorithms that analyze time-series NetCDF data, and to improve the content and consistency of the output data products produced by these algorithms. ADI achieves these goals by automating the process of retrieving and preparing data for analysis, supporting the definition of output data products through a graphical interface, and providing a modular, flexible software development architecture. The input data, preprocessing, and output data specifications are defined through a graphical interface and stored in a database. ADI also includes a workflow for data integration, a library of software modules to support the workflow, and a source code generator that produces C, IDL and Python templates. Data preparation support includes automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog. The variable and attribute definitions of the existing data products can be used to build new output data products. In addition, the rules that make up the ARM archive’s data standards are laid on top of the view of the new data product providing the user with a visual cue indicating where their output violates an archive standard. The necessary configurations are stored in a database that is accessed by the ADI libraries. This paper discusses the ADI framework, its supporting components, and how ADI can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Atmospheric Science↗
DOE OSTI2014

Constructing compact and effective graphs for recommender systems via node and edge aggregations

Exploiting graphs for recommender systems has great potential to flexibly incorporate heterogeneous information for producing better recommendation results. As our baseline approach, we first introduce a naive graph-based recommendation method, which operates with a heterogeneous log-metadata graph constructed from user log and content metadata databases. Although the na ve graph-based recommendation method is simple, it allows us to take advantages of heterogeneous information and shows promising flexibility and recommendation accuracy. However, it often leads to extensive processing time due to the sheer size of the graphs constructed from entire user log and content metadata databases. In this paper, we propose node and edge aggregation approaches to constructing compact and e ective graphs called Factor-Item bipartite graphs by aggregating nodes and edges of a log-metadata graph. Furthermore, experimental results using real world datasets indicate that our approach can significantly reduce the size of graphs exploited for recommender systems without sacrificing the recommendation quality.

97 MATHEMATICS AND COMPUTING↗