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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Estimating soil N 2 O emissions induced by organic and inorganic fertilizer inputs using a Tier-2, regression-based meta-analytic approach for U.S. agricultural lands

Consistent methods are essential for generating country and region-specific estimates of greenhouse gas (GHG) emissions used for reporting and policymaking. The estimates of direct N 2 O emissions from U.S. agricultural soils have primarily relied on the use of emission factors (EFs, Tier-1) and process-based models (Tier-3). However, Tier-1 estimates are relatively crude while Tier-3 calculations can be costly. This work addressed this gap by developing a Tier-2, regression-based approach by leveraging a meta-database containing 1883 field N 2 O observations together with environmental and management covariates from 139 studies. Our results estimated higher monthly soil N 2 O emissions (N 2 O m , kg N/ha) during the growing season (0.38) than the fallow period (0.15), highlighting the importance of considering measurement periods when utilizing meta-databases for analyzing N 2 O drivers. Significantly different N 2 O m were found for tillage practices (conventional > no-till: 0.42 > 0.27), fertilizer type (liquid > solid manure: 0.55 > 0.32), and soil texture (fine > coarse: 0.36 > 0.22). The comparisons of the influence of crop type and rotation, water management, and soil order on N 2 O emissions are complicated by regional data availability and interactions among different factors. Additionally, the finding that N 2 O emissions reported based on area (N 2 O m ), N input rate (EF), or yield can alter treatment rankings underscores the need to establish transparent criteria for rewarding or discouraging regionally-based management practices using N 2 O metrics. Finally, we show how General Linear Models (GLMs) can be used to estimate country and regional Tier-2 N 2 O m using a suite of covariates. Our GLMs identified tillage, water management, N input type and rate, soil properties, and elevation as the most influential covariates for the conterminous U.S. The limited accuracy of regional-scale GLMs, however, suggests the need to further improve the quality and availability of GHG and covariate data through concerted efforts in data collection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization

Abstract Background Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. Animals No live animals were used. Methods The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence–readiness. Results VBO is an open, community-driven ontology representing over 19 500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. Conclusion and Clinical Importance The adoption of VBO as a standard for breed names in databases and veterinary electronic health records enhances veterinary data interoperability and computability, supporting precision medicine.

Veterinary Sciences↗
DOE OSTI2016

SU-F-T-241: Reduction in Planning Errors Via a Process Control Developed Using the Eclipse Scripting API

Purpose: Errors found during initial physics plan checks frequently require replanning and reprinting, resulting decreased departmental efficiency. Additionally, errors may be missed during physics checks, resulting in potential treatment errors or interruption. This work presents a process control created using the Eclipse Scripting API (ESAPI) enabling dosimetrists and physicists to detect potential errors in the Eclipse treatment planning system prior to performing any plan approvals or printing. Methods: Potential failure modes for five categories were generated based on available ESAPI (v11) patient object properties: Images, Contours, Plans, Beams, and Dose. An Eclipse script plugin (PlanCheck) was written in C# to check errors most frequently observed clinically in each of the categories. The PlanCheck algorithms were devised to check technical aspects of plans, such as deliverability (e.g. minimum EDW MUs), in addition to ensuring that policy and procedures relating to planning were being followed. The effect on clinical workflow efficiency was measured by tracking the plan document error rate and plan revision/retirement rates in the Aria database over monthly intervals. Results: The number of potential failure modes the PlanCheck script is currently capable of checking for in the following categories: Images (6), Contours (7), Plans (8), Beams (17), and Dose (4). Prior to implementation of the PlanCheck plugin, the observed error rates in errored plan documents and revised/retired plans in the Aria database was 20% and 22%, respectively. Error rates were seen to decrease gradually over time as adoption of the script improved. Conclusion: A process control created using the Eclipse scripting API enabled plan checks to occur within the planning system, resulting in reduction in error rates and improved efficiency. Future work includes: initiating full FMEA for planning workflow, extending categories to include additional checks outside of ESAPI via Aria database queries, and eventual automated plan checks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response

Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response, is still incomplete. Recent proteomic studies of plant peroxisomes significantly increased the number of known peroxisomal proteins and greatly facilitated the study of peroxisomes at the systems level. The objectives of this study were to determine whether genes that encode peroxisomal proteins with related functions are co-expressed in Arabidopsis and identify peroxisomal proteins involved in stress response using in silico analysis and mutant screens. Using microarray data from online databases, we performed hierarchical clustering analysis to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiotic and biotic stress conditions. Many genes involved in the same metabolic pathways exhibited co-expression, some genes known to be involved in stress response are regulated by the corresponding stress conditions, and function of some peroxisomal proteins could be predicted based on their coexpression pattern. Since drought caused expression changes to the highest number of genes that encode peroxisomal proteins, we subjected a subset of Arabidopsis peroxisomal mutants to a drought stress assay. Mutants of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) showed enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Lastly, our study provided a global view of how genes that encode peroxisomal proteins respond to developmental and environmental cues and began to reveal additional peroxisomal proteins involved in stress response, thus opening up new avenues to investigate the role of peroxisomes in plant adaptation to environmental stresses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Analysis of a Uranium Oxide Sample Interdicted in Slovakia (FSC 12-3-1)

We provide a concise summary of analyses of a natural uranium sample seized in Slovakia in November 2007. Results are presented for compound identification, water content, U assay, trace element abundances, trace organic compounds, isotope compositions for U, Pb, Sr and O, and age determination using the 234 U – 230 Th and 235 U – 231 Pa chronometers. The sample is a mixture of two common uranium compounds - schoepite and uraninite. The uranium isotope composition is indistinguishable from natural; 236 U was not detected. The O, Sr and Pb isotope compositions and trace element abundances are unremarkable. The 234 U – 230 Th chronometer gives an age of 15.5 years relative to the date of analysis, indicating the sample was produced in January 1997. A comparison of the data for this sample with data in the Uranium Sourcing database failed to find a match, indicating the sample was not produced at a facility represented in the database.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1989

Image databases: Problems and perspectives

With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined.

Gudivada, V. Naidu↗
NASA NTRS1999

Remote Sensing of Rain

The first problem addressed concerns passive-microwave rain retrievals. Most current approaches start by building off-line a cloud-model-derived database. Given data, the retrieval algorithms search the database for the microwave temperatures "closest" to the observed data, then after some fine-tuning (performed in different ways by different implementations) the rain is estimated to be that which corresponds to the selected (and fine-tuned) set of database temperatures. These approaches have three drawbacks: they cannot properly take into account the ambiguities which arise from the fact that several rain scenarios can produce the same observed temperatures; they are quite inefficient since they require manipulating a large database along with often complex "fine-tuning" procedures; and they cannot refine their estimates if additional data is available. This past year we have derived closed formulae relating observed microwave brightness temperatures, T(sub b), and the underlying rain rates, R: average T(sub b) =f (rain) and average rain = g (T(sub b)), along with the corresponding covariance matrices. These results are sufficient to describe the conditional probabilities p(R/T(sub b)) and p(T(sub b)/R) to second order. Progress has also been made towards deriving a robust description of the rain drop size distribution (DSD). The widespread approach consisting in parameterizing the DSD as a gamma-distribution in terms of the drop diameter D suffers from the facts that, in reality, the DSD is not a smooth function of D and that the largely arbitrary Gamma model imposes unintended behavior, which has implications on any quantities derived from the DSD model. We have therefore developed a non-parametric yet practical description of the DSD, which is particularly well-suited for use in remote-sensing applications. The diagram on the left shows a comparison between an actual DSD sample and the truncated non-parametric representation. One figure shows the relation between radar reflectivity and rain rate derived using this representation. Validation of the Tropical Rainfall Measuring Mission (TRMM) radar-radiometer combined R and DSD algorithm is underway. This algorithm was designed to make optimal use of the instantaneous reflectivity profiles measured by the TRMM radar and the microwave brightness temperatures measured by the TRMM passive radiometer. So far, it appears to be the most reliable TRMM rain algorithm.

Haddad, Ziad S.↗
NASA NTRS2007

Flood and Landslide Applications of Near Real-time Satellite Rainfall Products

Floods and associated landslides are one of the most widespread natural hazards on Earth, responsible for tens of thousands of deaths and billions of dollars in property damage every year. During 1993-2002, over 1000 of the more than 2,900 natural disasters reported were due to floods. These floods and associated landslides claimed over 90,000 lives, affected over 1.4 billion people and cost about $210 billion. The impact of these disasters is often felt most acutely in less developed regions. In many countries around the world, satellite-based precipitation estimation may be the best source of rainfall data due to lack of surface observing networks. Satellite observations can be of essential value in improving our understanding of the occurrence of hazardous events and possibly in lessening their impact on local economies and in reducing injuries, if they can be used to create reliable warning systems in cost-effective ways. This article addressed these opportunities and challenges by describing a combination of satellite-based real-time precipitation estimation with land surface characteristics as input, with empirical and numerical models to map potential of landslides and floods. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg. By careful integration of remote sensing and in-situ observations, and assimilation of these observations into hydrological and landslide/debris flow models with surface topographic information, prediction of useful probabilistic maps of landslide and floods for emergency management in a timely manner is possible. Early results shows that the potential exists for successful application of satellite precipitation data in improving/developing global monitoring systems for flood/landslide disaster preparedness and management. The scientific and technological prototype can be first applied in a representative test-bed and then the information deliverables for the region can be tailored to the societal and economic needs of the represented affected countries.

Hong, Yang↗
NASA NTRS2015

Integrated Medical Model (IMM) Project Verification, Validation, and Credibility (VVandC)

The Integrated Medical Model (IMM) Project supports end user requests by employing the Integrated Medical Evidence Database (iMED) and IMM tools as well as subject matter expertise within the Project. The iMED houses data used by the IMM. The IMM is designed to forecast relative changes for a specified set of crew health and mission success risk metrics by using a probabilistic model based on historical data, cohort data, and subject matter expert opinion. A stochastic approach is taken because deterministic results would not appropriately reflect the uncertainty in the IMM inputs. Once the IMM was conceptualized, a plan was needed to rigorously assess input information, framework and code, and output results of the IMM, and ensure that end user requests and requirements were considered during all stages of model development and implementation, as well as lay the foundation for external review and application. METHODS: In 2008, the Project team developed a comprehensive verification and validation (VV) plan, which specified internal and external review criteria encompassing 1) verification of data and IMM structure to ensure proper implementation of the IMM, 2) several validation techniques to confirm that the simulation capability of the IMM appropriately represents occurrences and consequences of medical conditions during space missions, and 3) credibility processes to develop user confidence in the information derived from the IMM. When the NASA-STD-7009 (7009) [1] was published, the Project team updated their verification, validation, and credibility (VVC) project plan to meet 7009 requirements and include 7009 tools in reporting VVC status of the IMM. Construction of these tools included meeting documentation and evidence requirements sufficient to meet external review success criteria. RESULTS: IMM Project VVC updates are compiled recurrently and include updates to the 7009 Compliance and Credibility matrices. Reporting tools have evolved over the lifetime of the IMM Project to better communicate VVC status. This has included refining original 7009 methodology with augmentation from the HRP NASA-STD-7009 Guidance Document working group and the NASA-HDBK-7009 [2]. End user requests and requirements are being satisfied as evidenced by ISS Program acceptance of IMM risk forecasts, transition to an operational model and simulation tool, and completion of service requests from a broad end user consortium including operations, science and technology planning, and exploration planning. IMM v4.0 is slated for operational release in the FY015 and current VVC assessments illustrate the expected VVC status prior to the completion of customer lead external review efforts. CONCLUSIONS: The VVC approach established by the IMM Project of incorporating Project-specific recommended practices and guidelines for implementing the 7009 requirements is comprehensive and includes the involvement of end users at every stage in IMM evolution. Methods and techniques used to quantify the VVC status of the IMM Project represented a critical communication tool in providing clear and concise suitability assessments to IMM customers. These processes have not only received approval from the local NASA community but have also garnered recognition by other federal agencies seeking to develop similar guidelines in the medical modeling community.

Walton, M.↗
NASA NTRS2019

Experimental Aerodynamic Simulation of Scallop Ice Accretion on a Swept Wing

Understanding the aerodynamic impact of swept-wing ice accretions is a crucial component of the design of modern aircraft. Computer-simulation tools are commonly used to approximate ice shapes, so the necessary level of detail or fidelity of those simulated ice shapes must be understood relative to high-fidelity representations of the ice. Previous tests were performed in the NASA Icing Research Tunnel to acquire high-fidelity ice shapes. From this database, full-span artificial ice shapes were designed and manufactured for both an 8.9%-scale and 13.3%-scale semispan wing model of the CRM65 which has been established as the full-scale baseline for this swept-wing project. These models were tested in the Walter H. Beech wind tunnel at Wichita State University and at the ONERA F1 facility, respectively. The data collected in the Wichita St. University wind tunnel provided a low-Reynolds number baseline study while the pressurized F1 facility produced data over a wide range of Reynolds and Mach numbers with the highest Reynolds number studied being approximately Re=11.9x106. Past work focused on only three different fidelity variations for ice shapes based on multiple icing conditions. This work presents a more detailed investigation into several fidelity representations of a single highly three-dimensional scallop ice accretion. Sensitivity to roughness size and application technique on a low-fidelity smooth ice shape is described. The data indicate that the aerodynamic performance is not especially sensitive to the grit variations. An ice accretion code was also used to generate ice shapes for aerodynamic testing and comparisons. These ice shapes have a general appearance like the low-fidelity smooth ice shapes, but in this case, the computer-generated ice shape is significantly smaller. As such, the impact of that ice shape on the aerodynamic performance of the wing is reduced compared to the smooth ice shape based on the icing experiment for those same conditions. Spanwise discontinuities were also introduced to a low-fidelity ice shape in an attempt to quantify the impact of those variation in the high-fidelity ice shape. While the lift data indicate good agreement between the high-fidelity ice shapes and the low-fidelity ice shapes and the low-fidelity ice shapes with spanwise discontinuities, a closer investigation of the data suggests potential, significant differences in the flowfield. These results were similar at both facilities over the wide range of test conditions utilized.

Woodard, Brian↗
DOE OSTI2011

Review of Recent Literature Relevant to the Environmental Effects of Marine and Hydrokinetic Energy Devices, Task 2.1.3: Effects on Aquatic Organisms – Fiscal Year 2011 Progress Report Environmental Effects of Marine and Hydrokinetic Energy

A literature search was conducted by using the Web of Science® Databases component of the ISI Web of KnowledgeSM to identify recent articles that would be useful to help assess the potential environmental effects of renewable energy development in the ocean, with emphasis on marine mammals, seabirds, and fish. Several relatively recent general review articles that included possible effects of marine renewable energy devices on marine mammals and seabirds were examined to begin the search process (e.g., Boehlert et al. 2008; Thompson et al. 2008; Simas et al. 2009). From these articles, several general topics of potential environmental effects on marine mammals, seabirds, and fish were derived. These topics were used as the primary search factors. Searches were conducted with reference to the potential effects of offshore wind farms and MHK devices on marine mammals, seabirds, and fish. Additional sources were identified by cross-checking the Web of Science databases for articles that cited the review articles. It also became clear that often the potential effects were offered as hypotheses that often were not supported by the presentation of appropriate documentation. Therefore, the search was refined and focused on trying to obtain the necessary information to support or challenge a proposed potential effect to a specific concern. One of the expressed concerns regarding MHK devices is that placing wave parks in coastal waters could compromise the migration patterns of whales. Disruption of the annual migration of the gray whale (Eschrichtius robustus), which swims at least 30,000 km on its round trip from breeding grounds in Baja California to feeding areas in the Bering Sea, is of particular concern. Among the hypothesized effects on the migrating gray whales are increased predation risk by constricting migration corridor to between array and shore or by forcing the whales to swim into deeper waters, increased metabolic energy costs and delays in reaching the destinations, and interrupting feeding by blocking access to benthic areas under arrays. The literature search focused on identifying published studies that could provide information to evaluate these concerns. The results were developed into a case study that evaluated the potential effects of the placement of wave parks in coastal waters along the migration route of the gray whale. Wave parks and other MHK arrays may have additional effects on gray whales and other marine mammals, including entanglement in mooring lines and interference with communications among other effects, that were not included in this case study. The case study results were rewritten into a simpler form that would be suitable for placement on a web blog

Kropp, Roy K.↗
DOE OSTI2017

Analysis of transient fission gas behaviour in oxide fuel using BISON and TRANSURANUS

The modelling of fission gas behaviour is a crucial aspect of nuclear fuel analysis in view of the related effects on the thermo-mechanical performance of the fuel rod, which can be particularly significant during transients. Experimental observations indicate that substantial fission gas release (FGR) can occur on a small time scale during transients (burst release). To accurately reproduce the rapid kinetics of burst release in fuel performance calculations, a model that accounts for non-diffusional mechanisms such as fuel micro-cracking is needed. In this work, we present and assess a model for transient fission gas behaviour in oxide fuel, which is applied as an extension of diffusion-based models to allow for the burst release effect. The concept and governing equations of the model are presented, and the effect of the newly introduced parameters is evaluated through an analytic sensitivity analysis. Then, the model is assessed for application to integral fuel rod analysis. The approach that we take for model assessment involves implementation in two structurally different fuel performance codes, namely, BISON (multi-dimensional finite element code) and TRANSURANUS (1.5D semi-analytic code). The model is validated against 19 Light Water Reactor fuel rod irradiation experiments from the OECD/NEA IFPE (International Fuel Performance Experiments) database, all of which are simulated with both codes. The results point out an improvement in both the qualitative representation of the FGR kinetics and the quantitative predictions of integral fuel rod FGR, relative to the canonical, purely diffusion-based models, with both codes. The overall quantitative improvement of the FGR predictions in the two codes is comparable. Furthermore, calculated radial profiles of xenon concentration are investigated and compared to experimental data, demonstrating the representation of the underlying mechanisms of burst release by the new model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Analysis of historic fires to determine most frequent challenging events

The fire probabilistic risk assessment framework for nuclear power plants relies on experimental data to determine expected fire behavior or to validate models to predict fire conditions in the plant. To support reducing the uncertainty in this experimental data, a research effort was conducted to identify the most frequent and challenging fire scenarios using historic fire data from nuclear power plants in the United States. To support this effort, an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute was produced resulting in data on 2111 fire events, 540 events were labelled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. In conclusion, of these fire types, electrical and electronic equipment, transient combustibles, and liquid fires were the most frequent of the challenging fires. The fire scenario specifics were characterized for each of the eleven selected types and then related to existing fire experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

In-Memory Graph Databases for Web-Scale Data

RDF databases have emerged as one of the most relevant way for organizing, integrating, and managing expo- nentially growing, often heterogeneous, and not rigidly structured data for a variety of scientific and commercial fields. In this paper we discuss the solutions integrated in GEMS (Graph database Engine for Multithreaded Systems), a software framework for implementing RDF databases on commodity, distributed-memory high-performance clusters. Unlike the majority of current RDF databases, GEMS has been designed from the ground up to primarily employ graph-based methods. This is reflected in all the layers of its stack. The GEMS framework is composed of: a SPARQL-to-C++ compiler, a library of data structures and related methods to access and modify them, and a custom runtime providing lightweight software multithreading, network messages aggregation and a partitioned global address space. We provide an overview of the framework, detailing its component and how they have been closely designed and customized to address issues of graph methods applied to large-scale datasets on clusters. We discuss in details the principles that enable automatic translation of the queries (expressed in SPARQL, the query language of choice for RDF databases) to graph methods, and identify differences with respect to other RDF databases.

GEMS↗
DOE OSTI2012

Algal functional annotation tool

Abstract BACKGROUND: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. DESCRIPTION: The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion. CONCLUSIONS: The Algal Functional Annotation Tool aims to provide an integrated data-mining environment for algal genomics by combining data from multiple annotation databases into a centralized tool. This site is designed to expedite the process of functional annotation and the interpretation of gene lists, such as those derived from high-throughput RNA-seq experiments. The tool is publicly available at http://pathways.mcdb.ucla.edu.

Source record↗
DOE OSTI2024

Estimating UV-B, UV-Erithemic, and UV-A Irradiances From Global Horizontal Irradiance and MERRA-2 Ozone Column Information

The ground ultraviolet (UV) solar radiation is relevant due to its impacts on plastics degradation (mainly UVA) and on human health (UVB and erithemic UV (UVE)). UV ground measurements are not as ubiquitous as the relatively common global horizontal irradiance (GHI) measurements. Three simple models that estimate the UVA, UVB, and UVE components of solar irradiance from GHI and ozone column information are locally adjusted and validated. Five one-minute datasets from three sites in southeastern South America and two in the United States are used for simultaneous solar irradiance and UV data. All sites correspond to temperate mid-latitude regions. Simultaneous atmospheric total ozone column information is obtained from the reanalysis modern-era retrospective analysis for research and applications (MERRA-2) database for each site. Aside from locally adjusted models, average models with a single set of coefficients are also evaluated. For instance, the best average model is able to estimate UVE with a typical uncertainty below 12% and mean biases between +-3%, relative to the average of the measurements. Similar results are reported for the UVB and UVA components. These results, which can be useful in regions with similar climate and geography, provide a simple way to estimate UV irradiance under all-sky conditions with known uncertainty. This is an alternative to global satellite-based UV estimates, which can have high uncertainties at specific locations. Because MERRA-2 information has a global coverage, when coupled with good satellite-based estimates for GHI, UV irradiances can be estimated by this method over a large territory.

environmental UV radiation↗
DOE OSTI2012

Morphological State as a Predictor for Reintervention and Mortality After EVAR for AAA

Purpose: This study was designed to assess aorto-iliac morphological characteristics in relation to reintervention and all-cause long-term mortality in patients undergoing standard EVAR for infrarenal AAA. Methods: Patients treated with EVAR (Zenith{sup Registered-Sign} Stentgrafts, Cook) between May 1998 and February 2006 were prospectively enrolled in a computerized database where comorbidities and preoperative aneurysm morphology were entered. Reinterventions and mortality were checked until December 1, 2010. Median follow-up time was 68 months. Results: A total of 304 patients were included, of which 86% were men. Median age was 74 years. The reintervention rate was 23.4% (71/304). A greater diameter of the common iliac artery (p = 0.037; hazard ratio (HR) 1.037 [1.002-1.073]) was an independent factor for an increased number of reinterventions. The 30-day mortality rate was 3.0% (9/304). Aneurysm-related deaths due to AAA occurred in 4.9% (15/304). Five patients died due to a concomitant ruptured thoracic aortic aneurysm. The mortality until end of follow-up was 54.3% (165/304). The proportion of deaths caused by vascular diseases was 61.6%. The severity of angulation of the iliac arteries (p = 0.014; HR 1.018 [95% confidence interval (CI) 1.004-1.033]) and anemia (p = 0.044; HR 2.79 [95% CI 1.029-7.556]) remained as independent factors associated with all-cause long-term mortality. The crude reintervention-free survival rate at 1, 3, and 5 years was 84.5%, 64.8%, and 51.6%, respectively. Conclusions: The initial aorto-iliac morphological state in patients scheduled for standard EVAR for AAA seems to be strongly related to the need for reinterventions and long-term mortality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗