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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 307 records · Page 17

Exploiting algal NADPH oxidase for biophotovoltaic energy

Summary Photosynthetic microbes exhibit light‐dependent electron export across the cell membrane, which can generate electricity in biological photovoltaic (BPV) devices. How electrons are exported remains to be determined; the identification of mechanisms would help selection or generation of photosynthetic microbes capable of enhanced electrical output. We show that plasma membrane NADPH oxidase activity is a significant component of light‐dependent generation of electricity by the unicellular green alga Chlamydomonas reinhardtii . NADPH oxidases export electrons across the plasma membrane to form superoxide anion from oxygen. The C. reinhardtii mutant lacking the NADPH oxidase encoded by RBO1 is impaired in both extracellular superoxide anion production and current generation in a BPV device. Complementation with the wild‐type gene restores both capacities, demonstrating the role of the enzyme in electron export. Monitoring light‐dependent extracellular superoxide production with a colorimetric assay is shown to be an effective way of screening for electrogenic potential of candidate algal strains. The results show that algal NADPH oxidases are important for superoxide anion production and open avenues for optimizing the biological component of these devices.

59 BASIC BIOLOGICAL SCIENCES↗

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

An integrated landscape designed for commodity and bioenergy crops for a tile-drained agricultural watershed

Here, locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO 3 –N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas and 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass ( Panicum virgatum L.), willow ( Salix spp.), and big bluestem ( Andropogon gerardi Vitman) in these subfield areas on annual grain yields, NO 3 –N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant (p ≤ 0.05) impact on grain production and reduced NO 3 –N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO 3 –N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly (p ≤ 0.01) lower reductions in annual NO 3 –N export (18.0 vs. 26.0%).

09 BIOMASS FUELS↗

Infrared Imaging Camera Final Report CRADA No. TC02061.0

This was a collaborative effort between the University of California, Lawrence Livermore National Laboratory (LLNL) and Cordin Company (Cordin) to enhance the U.S. ability to develop a commercial infrared camera capable of capturing high-resolution images in a l 00 nanoseconds (ns) time frame. The Department of Energy (DOE), under an Initiative for Proliferation Prevention (IPP) project, funded the Russian Federation Nuclear Center All-Russian Scientific Institute of Experimental Physics (RFNC-VNIIEF) in Sarov. VNIIEF was funded to develop a prototype commercial infrared (IR) framing camera and to deliver a prototype IR camera to LLNL. LLNL and Cordin were partners with VNIIEF on this project. A prototype IR camera was delivered by VNIIEF to LLNL in December 2006. In June of 2007, LLNL and Cordin evaluated the camera and the test results revealed that the camera exceeded presently available commercial IR cameras. Cordin believes that the camera can be sold on the international market. The camera is currently being used as a scientific tool within Russian nuclear centers. This project was originally designated as a two year project. The project was not started on time due to changes in the IPP project funding conditions; the project funding was re-directed through the International Science and Technology Center (ISTC), which delayed the project start by over one year. The project was not completed on schedule due to changes within the Russian government export regulations. These changes were directed by Export Control regulations on the export of high technology items that can be used to develop military weapons. The IR camera was on the list that export controls required. The ISTC and Russian government, after negotiations, allowed the delivery of the camera to LLNL. There were no significant technical or business changes to the original project.

47 OTHER INSTRUMENTATION↗

Mechanistic Insights Revealed by YbtPQ in the Occluded State

Recently, several ATP-binding cassette (ABC) importers have been found to adopt the typical fold of type IV ABC exporters. Presumably, these importers would function under the transport scheme of “alternating access” like those exporters, cycling through inward-open, occluded, and outward-open conformations. Understanding how the exporter-like importers move substrates in the opposite direction requires structural studies on all the major conformations. To shed light on this, here we report the structure of yersiniabactin importer YbtPQ from uropathogenic Escherichia coli in the occluded conformation trapped by ADP-vanadate (ADP-Vi) at a 3.1 Å resolution determined by cryo-electron microscopy. The structure shows unusual local rearrangements in multiple helices and loops in its transmembrane domains (TMDs). In addition, the dimerization of the nucleotide-binding domains (NBDs) promoted by the vanadate trapping is highlighted by the “screwdriver” action at one of the two hinge points. These structural observations are rare and thus provide valuable information to understand the structural plasticity of the exporter-like ABC importers.

59 BASIC BIOLOGICAL SCIENCES↗

A simulation analysis of the fate of phytoplankton within the mid-Atlantic bight

A time-dependent, three-dimensional simulation model of wind-induced changes of the circulation field, of light and nutrient regulation of photosynthesis, of vertical mixing as well as algal sinking, and of herbivore grazing stress, is used to analyze the seasonal production, consumption, and transport of the spring bloom within the mid-Atlantic Bight. The particular case (c) of a 58-day period in February-April 1979, simulated primary production, based on both nitrate and recycled nitrogen, with a mean of 0.62 g C sq m/day over the whole model domain, and an export at the shelf-break off Long Island of 2.60 g ch1 sq m/day within the lower third of the water column. About 57% of the carbon fixation was removed by herbivores, with 21% lost as export, either downshelf or offshore to slope waters, after the first 58 days of the spring bloom. Extension of the model for another 22 days of case (c) increased the mean export to 27%, while variation of the model's parameters in 8 other cases led to a range in export from 8% to 38% of the average primary production. Spatial and temporal variations of the simulated albal biomass, left behind in the shelf water column, reproduced chlorophyll fields sensed by satellite, shipboard, and in situ instruments.

Walsh, J. J.↗

An Arctic source for the Great Salinity Anomaly - A simulation of the Arctic ice-ocean system for 1955-1975

The paper employs a fully prognostic Arctic ice-ocean model to study the interannual variability of sea ice during the period 1955-1975 and to explain the large variability of the ice extent in the Greenland and Iceland seas during the late 1960s. The model is used to test the contention of Aagaard and Carmack (1989) that the Great Salinity Anomaly (GSA) was a consequence of the anomalously large ice export in 1968. The high-latitude ice-ocean circulation changes due to wind field changes are explored. The ice export event of 1968 was the largest in the simulation, being about twice as large as the average and corresponding to 1600 cu km of excess fresh water. The simulations suggest that, besides the above average ice export to the Greenland Sea, there was also fresh water export to support the larger than average ice cover. The model results show the origin of the GSA to be in the Arctic, and support the view that the Arctic may play an active role in climate change.

Hakkinen, Sirpa↗

Data Model Management for Space Information Systems

The Reference Architecture for Space Information Management (RASIM) suggests the separation of the data model from software components to promote the development of flexible information management systems. RASIM allows the data model to evolve independently from the software components and results in a robust implementation that remains viable as the domain changes. However, the development and management of data models within RASIM are difficult and time consuming tasks involving the choice of a notation, the capture of the model, its validation for consistency, and the export of the model for implementation. Current limitations to this approach include the lack of ability to capture comprehensive domain knowledge, the loss of significant modeling information during implementation, the lack of model visualization and documentation capabilities, and exports being limited to one or two schema types. The advent of the Semantic Web and its demand for sophisticated data models has addressed this situation by providing a new level of data model management in the form of ontology tools. In this paper we describe the use of a representative ontology tool to capture and manage a data model for a space information system. The resulting ontology is implementation independent. Novel on-line visualization and documentation capabilities are available automatically, and the ability to export to various schemas can be added through tool plug-ins. In addition, the ingestion of data instances into the ontology allows validation of the ontology and results in a domain knowledge base. Semantic browsers are easily configured for the knowledge base. For example the export of the knowledge base to RDF/XML and RDFS/XML and the use of open source metadata browsers provide ready-made user interfaces that support both text- and facet-based search. This paper will present the Planetary Data System (PDS) data model as a use case and describe the import of the data model into an ontology tool. We will also describe the current effort to provide interoperability with the European Space Agency (ESA)/Planetary Science Archive (PSA) which is critically dependent on a common data model.

RDF↗

Annual Cycles of Multiyear Sea Ice Coverage of the Arctic Ocean: 1999-2003

For the years 1999-2003, we estimate the time-varying perennial ice zone (PIZ) coverage and construct the annual cycles of multiyear (MY, including second year) ice coverage of the Arctic Ocean using QuikSCAT backscatter, MY fractions from RADARSAT, and the record of ice export from satellite passive microwave observations. An area balance approach extends the winter MY coverage from QuikSCAT to the remainder of the year. From these estimates, the coverage of MY ice at the beginning of each year is 3774 x 10(exp 3) sq km (2000), 3896 x 10(exp 3) sq km (2001), 4475 x 10(exp 3) sq km (2002), and 4122 x 10(exp 3) sq km (2003). Uncertainties in coverage are approx.150 x 10(exp 3) sq km. In the mean, on 1 January, MY ice covers approx.60% of the Arctic Ocean. Ice export reduces this coverage to approx.55% by 1 May. From the multiple annual cycles, the area of first-year (FY) ice that survives the intervening summers are 1192 x 10(exp 3) sq km (2000), 1509 x 10(exp 3) sq km (2001), and 582 x 10(exp 3) sq km (2002). In order for the MY coverage to remain constant from year to year, these replenishment areas must balance the overall area export and melt during the summer. The effect of the record minimum in Arctic sea ice area during the summer of 2002 is seen in the lowest area of surviving FY ice of the three summers. In addition to the spatial coverage, the location of the PIZ is important. One consequence of the unusual location of the PIZ at the end of the summer of 2002 is the preconditioning for enhanced export of MY ice into the Barents and Kara seas. Differences between the minimums in summer sea ice coverage from our estimates and passive microwave observations are discussed.

Arctic Ocean↗

Surface and Lightning Sources of Nitrogen Oxides over the United States: Magnitudes, Chemical Evolution, and Outflow

We use observations from two aircraft during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) campaign over the eastern United States and North Atlantic during summer 2004, interpreted with a global 3-D model of tropospheric chemistry (GEOS-Chem) to test current understanding of the regional sources, chemical evolution, and export of nitrogen oxides. The boundary layer NO(x) data provide top-down verification of a 50% decrease in power plant and industry NO(x) emissions over the eastern United States between 1999 and 2004. Observed 8-12 8 km NO(x) concentrations in ICARTT were 0.55 +/- 36 ppbv, much larger than in previous United States aircraft campaigns (ELCHEM, SUCCESS, SONEX). We show that regional lightning was the dominant source of this NO(x) and increased upper tropospheric ozone by 10 ppbv. Simulating the ICARTT upper tropospheric NO(x) observations with GEOS-Chem require a factor of 4 increase in the model NO(x) yield per flash (to 500 mol/flash). Observed OH concentrations were a factor of 2 lower than can be explained from current photochemical models, and if correct would imply a broader lightning influence in the upper troposphere than presently thought.An NO(y)-CO correlation analysis of the fraction f of North American NO(x) emissions vented to the free troposphere as NO(y) (sum of NO(x) and its oxidation products PAN and HNO3) s shows observed f=16+/-10 percent and modeled f=14 +/- 8 percent, consistent with previous studies. Export to the lower free troposphere is mostly HNO3 but at higher altitudes is mostly PAN. The model successfully simulates NO(y) export efficiency and speciation, supporting previous model estimates of a large U.S. contribution to tropospheric ozone through NO(x) and PAN export.

Hudman, Rynda C.↗

Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice.

Antarctic Ocean↗

Estuarine Dissolved Organic Carbon Flux from Space: With Application to Chesapeake and Delaware Bays

This study uses a neural network model trained with in situ data, combined with satellite data and hydrodynamic model products, to compute the daily estuarine export of dissolved organic carbon (DOC) at the mouths of Chesapeake Bay (CB) and Delaware Bay (DB) from 2007 to 2011. Both bays show large flux variability with highest fluxes in spring and lowest in fall as well as interannual flux variability (0.18 and 0.27 Tg C/year in 2008 and 2010 for CB; 0.04 and 0.09 Tg C/year in 2008 and 2011 for DB). Based on previous estimates of total organic carbon (TOCexp) exported by all Mid-Atlantic Bight estuaries (1.2 Tg C/year), the DOC export (CB + DB) of 0.3 Tg C/year estimated here corresponds to 25% of the TOCexp. Spatial and temporal covariations of velocity and DOC concentration provide contributions to the flux, with larger spatial influence. Differences in the discharge of fresh water into the bays (74 billion m(exp3)/year for CB and 21 billion m9exp3)/year for DB) and their geomorphologies are major drivers of the differences in DOC fluxes for these two systems. Terrestrial DOC inputs are similar to the export of DOC at the bay mouths at annual and longer time scales but diverge significantly at shorter time scales (days to months). Future efforts will expand to the Mid-Atlantic Bight and Gulf of Maine, and its major rivers and estuaries, in combination with coupled terrestrial-estuarine-ocean biogeochemical models that include effects of climate change, such as warming and CO2 increase.

Signorini, Sergio↗

Broader Impacts and Outreach Videos on Ocean Physics and Biogeochemistry

This is just a preliminary NF1676 in advance of filming for a project....A convergent team of experts in biology, chemistry, physics, engineering, mathematics, and computational modeling examine how dynamic and coupled phytoplankton-pathogen-particle-predator linkages coalesce to explain the observed high spatial variability in the efficiency of the export of particulate organic carbon (POC) to the deep ocean. They elucidate and quantify the linkages between viruses and ballast minerals to increase understanding of carbon cycling in the oceanic biological carbon pump and the impact of viruses within it. By providing knowledge than can be used to improve the parameterization of carbon export in Earth system models, the project will help reduce uncertainty in regional marine biogeochemical projections, potentially improving marine ecosystem and fisheries management on timescales from seasons to decades. The project includes activities that provide teaching resources and hands-on training to educators within a ‘Tools of Science’ program that provides a simple and succinct way to communicate the process of scientific research to students in a way that is useful to teachers. The project couples laboratory-based experiments on model host-virus-grazer systems with extensive field based observational and manipulative studies on natural populations of diatoms and coccolithophores, the two phytoplankton groups that account for most of the estimated particulate organic matter flux to the deep ocean. Experiments and measurements integrate diagnostic biological and chemical controls on infection and particle coagulation theory with microscale physics and grazing to quantify links to each hypothesized export mechanism under field-relevant turbulent conditions. Cutting-edge engineering and analytical tools are used to diagnose and track infection dynamics while characterizing and quantifying particle aggregation and disaggregation, mineral dissolution, sinking dynamics, grazing rates, and fecal pellet production at unprecedented resolution and under well-defined, microscale physical regimes. Field campaigns elucidate the relative efficiency of hypothesized mechanisms in stimulating POC export in natural blooms, while providing bulk and size-resolved estimates of POC flux.

Daniel B Whitt↗

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗

SIGNATURES OF ILLICIT NUCLEAR PROCUREMENT NETWORKS: AN OVERVIEW OF PRELIMINARY APPROACHES AND RESULTS

The illicit trafficking of strategic nuclear commodities (defined here as the goods needed for a covert nuclear program excluding special nuclear materials) poses a significant challenge to the international nuclear nonproliferation community. Export control regulations, both domestically and internationally, seek to inhibit the spread of strategic nuclear commodities by restricting their sale to parties that may use them for nefarious purposes. However, export controls alone are not sufficient for preventing the illicit transfer of strategic nuclear goods. There are two major pitfalls to relying solely on export control regulations for the deterrence of proliferation of strategic goods. First, export control enforcement today relies heavily on the honesty and willingness of participants to adhere to the legal framework already in place. Secondly, current practices focus on the evaluation of single records which allow for the necessary goods to be purchased separately and hidden within the thousands of legitimate commerce transactions that occur each day, disregarding strategic information regarding several purchases. Our research presents two preliminary data-centric approaches for investigating procurement networks of strategic nuclear commodities. Pacific Northwest National Laboratory (PNNL) has been putting significant effort into nonproliferation activities as an institution, both in terms of the classical nuclear material focused approach and in the examination of other strategic goods necessary to implement a nuclear program. In particular, the PNNL Signature Discovery Initiative (SDI) has codified several scientific methodologies for the detection, characterization, and prediction of signatures that are indicative of a phenomenon of interest. The methodologies and tools developed under SDI have already been applied successfully to problems in bio-forensics, cyber security and power grid balancing efforts and they have now made the nonproliferation of strategic goods into a challenge problem for testing their methodology and tools. As a first step towards the detection and characterization of illicit procurement networks, our research examines procurement networks as defined by a system of entities (people or companies) that enter into transactions of specific items with one another. Once we have defined such networks, we are interested in answering questions about the behavior and characterization of such networks. The questions we wish to answer regarding procurement networks are, first, “Can we detect networks within large, noisy datasets?” and second, “To what extent can we compare multiple networks and identify their similarities?” As procurement networks can be naturally viewed as a graph, we have employed several graph analytic tools to aid in these tasks. In particular, Graphscape, an SDI tool, uses a novel method to approximate edit distance, a graph distance measure based on the number of changes needed to transform one graph into another, in order to measure how similar two given graphs are to each other. Given a set of graphs where vertices represent companies and edges represent a shipment from company A to company B, we can calculate an all-for-all comparison of graphs. In this way, we are able to determine which graphs are most similar, and which require more changes to transform one into the other. The set of graphs to be compared can be further specialized to provide more insight, e.g., using different time periods to explore events in a company life cycle.

graph analysis↗

A Visual Atlas on Strategic Trade

Strategic trade concerns global trade flows of items with strategic military value. Items include goods with exclusive military use, but also dual-use items that can have both military and civil uses. Many countries require licenses for trade in strategic items as a measure of non-proliferation. For example, items listed for trade control by multilateral export control arrangements, such as the Nuclear Suppliers Group (NSG), typically are considered strategic goods. Analysts and officials involved in strategic trade control often lack quantitative global understanding of relevant trade patterns that would help them focus control and enforcement efforts, select companies for outreach and audit, target transactions for verification and inspection, and assess the potential economic impact of trade control policies. Many are unaware of available open source data on international trade that can inform these issues. Many do not know how to make use of such data or lack the tools necessary to do so. A book of charts dubbed a ‘Strategic Trade Atlas’ was developed to illustrate global trade flows of strategic goods and raise awareness of the availability and utility of open source trade data. The Atlas was prepared for the World Customs Organization (WCO) and its Member States to support their planning and execution of Strategic Trade Control Enforcement (STCE) operations. It offers macroscopic graphical representations of global trade flows classified under Harmonized System (HS) codes associated by the WCO with commodities described in its STCE Implementation Guide. While these HS codes are understood to also encompass many non-strategic items, they nevertheless provide a good overview of potentially strategic trade flows. These include HS codes covering nuclear and nuclear-related commodities listed by the NSG, such as uranium, heavy water, graphite, carbon fiber, nickel powder, beryllium, aluminum tubes, vacuum pumps, valves, machine tools, cameras, and many others. The Atlas uses trade data from the Base pour l’Analyse du Commerce International (BACI), a statistical elaboration of public UN Comtrade data. BACI data reconciles trade flows, taking into account asymmetries in import and export trade valuation. The data visualization approach facilitates rapid sense making, pattern recognition, and anomaly detection. Country-based profiles summarize vast amounts of data into readily understandable graphical representations of each country’s primary strategic imports and exports and their main trading partners. Commodity-based profiles provide a global view of major exporters, importers, and trade patterns for each commodity. These insights can inform the risk management approach employed by customs to allocate enforcement and compliance efforts.

customs controls↗

Exploiting nonionic surfactants to enhance fatty alcohol production in Rhodosporidium toruloides

Fatty alcohols (FOHs) are important feedstocks in the chemical industry to produce detergents, cosmetics, and lubricants. Microbial production of FOHs has become an attractive alternative to production in plants and animals due to growing energy demands and environmental concerns. However, inhibition of cell growth caused by intracellular FOH accumulation is one major issue that limits FOH titers in microbial hosts. In addition, identification of FOH-specific exporters remains a challenge and previous studies towards this end are limited. To alleviate the toxicity issue, we exploited nonionic surfactants to promote the export of FOHs in Rhodosporidium toruloides, an oleaginous yeast that is considered an attractive next-generation host for the production of fatty acid-derived chemicals. Our results showed FOH export efficiency was dramatically improved and the growth inhibition was alleviated in the presence of small amounts of tergitol and other surfactants. As a result, FOH titers increase by 4.3-fold at bench scale to 352.6 mg/L. With further process optimization in a 2-L bioreactor, the titer was further increased to 1.6 g/L. The method we show here can potentially be applied to other microbial hosts and may facilitate the commercialization of microbial FOH production.

59 BASIC BIOLOGICAL SCIENCES↗

ABCB10 depletion reduces unfolded protein response in mitochondria

Mitochondria have many functions, including ATP generation. The electron transport chain (ETC) and the coupled ATP synthase generate ATP by consuming oxygen. Reactive oxygen species (ROS) are also produced by ETC, and ROS damage deoxyribonucleic acids, membrane lipids and proteins. Recent analysis indicate that mitochondrial unfolded protein response (UPR{sup mt}), which enhances expression of mitochondrial chaperones and proteases to remove damaged proteins, is activated when damaged proteins accumulate in the mitochondria. In Caenorhabditis elegans, HAF-1, a putative ortholog of human ABCB10, plays an essential role in signal transduction from mitochondria to nuclei to enhance UPR{sup mt}. Therefore, it is possible that ABCB10 has a role similar to that of HAF-1. However, it has not been reported whether ABCB10 is a factor in the signal transduction pathway to enhance UPR{sup mt}. In this study, ABCB10 was depleted in HepG2 cells using small interfering RNA (siRNA), and the effect was examined. ABCB10 depletion upregulated ROS and the expression of ROS-detoxifying enzymes (SOD2, GSTA1, and GSTA2), and SESN3, a protein induced by ROS to protect the cell from oxidative stress. In addition, ABCB10 depletion significantly decreased expression of UPR{sup mt}-related mitochondrial chaperones (HSPD1 and DNAJA3), and a mitochondrial protease (LONP1). However, the putative activity of ABCB10 to export peptides from mitochondria was not lost by ABCB10 depletion. Altogether, these data suggest that ABCB10 is involved in UPR{sup mt} signaling pathway similar to that of HAF-1, although ABCB10 probably does not participate in peptide export from mitochondria. - Highlights: • ABCB10-KD upregulated ROS and the expression of ROS-detoxifying enzymes and SESN3. • ABCB10 is involved in UPR{sup mt} signaling pathway. • ABCB10 probably does not participate in peptide export from mitochondria.

60 APPLIED LIFE SCIENCES↗