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At least 811 records · Page 45

Co-location Pattern Mining of Geosocial Data to Characterize Urban Functional Spaces

Spatial Co-location Pattern (SCP) mining continues to play a critical role in understanding the morphology of urban functional spaces of world cities. It requires a large amount of fine-granular data and computing efficiency to handle the combinatorial explosion of co-location patterns. To this end, this work has two main contributions - i) We showcase a novel approach to perform SCP mining to characterize intra-city scale structure of urban functionality or co-located activity patterns using geosocial Points-of-Interest (POI) vector data. ii) We present a generalized and optimized parallel/distributed SCP mining algorithm implemented on a Hadoop MapReduce system and demonstrate the utility of our approach using the city of Berlin (Germany) as an example. The SCPs tend to vary across Berlin's municipal boroughs and at different spatial scales. Our findings on Berlin's functional structure conform to existing urban geography models. Such a data-driven exploration of massive urban POIs using distributed computing is first of its kind and can help better understand the changing dynamics of urban functionality, as well as physical, and social network structure around the world.

Masrur, Arif↗

The role of protected areas in land use/land cover change and the carbon cycle in the conterminous United States

Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km2 of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607 Tg C release from land ecosystems to atmosphere. PAs had experienced little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642 Tg C over 1700–2005, or 13.4% of carbon losses in non-PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001–2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large-scale disturbances that would release large amounts of carbon in PAs.

Lu, Xiaoliang↗

Evaluation of the Inclusive Electron Scattering Observables in the Resonance Region from the Experimental Data

The method for evaluation of inclusive electron scattering observables in the resonance region from the experimental data is presented. The computer codes in the web page allow user to evaluate inclusive electron scattering, virtual photon-proton cross sections and the F{sub 1} and F{sub 2} structure functions at the invariant masses of the final hadrons 1.0 < W < 4.0 GeV and at photon virtualities 0.5 < Q {sup 2} < 7.0 GeV{sup 2}. The developed approach is of interest for analyses of the experimental data on exploration of the hadron structure in the experiments with electromagnetic probes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dataset for Biorefinery-specific feedstock price variability, Part 1: Corn stover

This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply. In each of these cases, the supply is modeled first at the farmgate at prices up to $80 per dry ton for five deterministic scenarios. Building on this dataset, a supplementary dataset of delivered supply was modeled for 800k dry ton per year capacity facilities in two facility siting approaches. Results were summarized across delivered supply curves for twelve scenarios. The resulting supply curves are highly elastic, resulting in a range of potential supplies across scenarios at specified prices. Interactive visualization of these data allows exploration into any specified nth plant supply sensitivity to key variables and spatial distribution of stover resources. The analysis is economic supply risk and doesn’t account for disruptions from competing demands, namely livestock feed and bedding markets. Scenario ending in _BC3080 is a reference scenario consistent with BT16 Basecase (BC1), but with corn stover price isolation. Scenario ending in _OHB080 includes high operational efficiency constraints for corn stover. Scenario ending in _OLB080 includes low operational efficiency constraints for corn stover. Scenario ending in _PLB080 includes low opportunity cost. Scenario ending in _PHB080 includes high opportunity cost. No Land Rental costs are applied to these scenarios. All scenarios were under an exogenous price simulation using POLYSYS (v2017).

Agricultural residues, biomass resources, 2018, bi↗

GENESPACE R Package (GENESPACE) v1.0

In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.

Schmutz, Jeremy↗

Lipid Informed Quantitation and Identification

LIQUID (Lipid Informed Quantitation and Identification) is a software program that has been developed to enable users to conduct both informed and high-throughput global liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipidomics analysis. This newly designed desktop application can quickly identify and quantify lipids from LC-MS/MS datasets while providing a friendly graphical user interface for users to fully explore the data. Informed data analysis simply involves the user specifying an electrospray ionization mode, lipid common name (i.e. PE(16:0/18:2)), and associated charge carrier. A stemplot of the isotopic profile and a line plot of the extracted ion chromatogram are also provided to show the MS-level evidence of the identified lipid. In addition to plots, other information such as intensity, mass measurement error, and elution time are also provided. Typically, a global analysis for 15,000 lipid targets.

Crowell, Kevin↗

Factors Influencing Willingness to Pool in Ride-Hailing Trips

In the past decade, transportation network companies (TNCs) such as Uber, Lyft, and Via have established themselves as a viable transportation alternative to other modes. However, the popularity of these services has come with a fair share of criticism for their negative externalities such as increasing vehicle miles traveled and congestion in cities. Pooled ride-hailing trips, in which all or a part of two individual (or group) trips are combined in and served by a single vehicle, have the potential to reduce these externalities. Pooling of rides is an effective solution to reduce congestion and travel cost, but pooled rides still represent a small percentage of the total trips served (and miles driven) by TNCs relative to single-occupancy (and without customer) vehicle miles. Both TNCs and cities alike will benefit from understanding what factors encourage or deter pooling a ride-hailing trip. In this study, newly available Chicago transportation network provider data were explored to identify the extent to which different socioeconomic, spatiotemporal, and trip characteristics affect willingness to pool (WTP) in ride-hailing trips. Furthermore, multivariate linear regression and machine-learning models were employed to understand and predict WTP based on location, time, and trip factors. The results show intuitive trends, with income level at drop-off and pickup locations and airport trips as the most important predictors of WTP. Results from this study can help TNCs and cities devise strategies that increase pooled ride-hailing, thereby reducing adverse transportation and energy impacts from ride-hailing modes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scenario driven data modelling: a method for integrating diverse sources of data and data streams

Background: Biology is rapidly becoming a data intensive, data-driven science. It is essential that data is represented and connected in ways that best represent its full conceptual content and allows both automated integration and data driven decision-making. Recent advancements in distributed multi-relational directed graphs, implemented in the form of the Semantic Web make it possible to deal with complicated heterogeneous data in new and interesting ways. Results: This paper presents a new approach, scenario driven data modelling (SDDM), that integrates multirelational directed graphs with data streams. SDDM can be applied to virtually any data integration challenge with widely divergent types of data and data streams. In this work, we explored integrating genetics data with reports from traditional media. SDDM was applied to the New Delhi metallo-beta-lactamase gene (NDM-1), an emerging global health threat. The SDDM process constructed a scenario, created a RDF multi-relational directed graph that linked diverse types of data to the Semantic Web, implemented RDF conversion tools (RDFizers) to bring content into the Sematic Web, identified data streams and analytical routines to analyse those streams, and identified user requirements and graph traversals to meet end-user requirements. Conclusions: We provided an example where SDDM was applied to a complex data integration challenge. The process created a model of the emerging NDM-1 health threat, identified and filled gaps in that model, and constructed reliable software that monitored data streams based on the scenario derived multi-relational directed graph. The SDDM process significantly reduced the software requirements phase by letting the scenario and resulting multi-relational directed graph define what is possible and then set the scope of the user requirements. Approaches like SDDM will be critical to the future of data intensive, data-driven science because they automate the process of converting massive data streams into usable knowledge.

59 BASIC BIOLOGICAL SCIENCES↗

A review of virulent Newcastle disease viruses in the United States and the role of wild birds in viral persistence and spread

Newcastle disease is caused by virulent strains of Newcastle disease virus (NDV), which causes substantial morbidity and mortality events worldwide in poultry. The virus strains can be differentiated as lentogenic, mesogenic, or velogenic based on a mean death time in chicken embryos. Currently, velogenic strains of NDV are not endemic in United States domestic poultry; however, these strains are present in other countries and are occasionally detected in wild birds in the U.S. A viral introduction into domestic poultry could have severe economic consequences due to the loss of production from sick and dying birds, the cost of control measures such as depopulation and disinfection measures, and the trade restrictions that would likely be imposed as a result of an outbreak. Due to the disease-free status of the U.S. and the high cost of a potential viral incursion to the poultry industry, a qualitative risk analysis was performed to evaluate the vulnerabilities of the U.S. against the introduction of virulent strains of NDV. The most likely routes of virus introduction are explored and data gathered by several federal agencies is provided. Recommendations are ultimately provided for data that would be useful to further understand NDV on the landscape and to utilize all existing sampling opportunities to begin to comprehend viral movement and further characterize the risk of NDV introduction into the U.S.

59 BASIC BIOLOGICAL SCIENCES↗

Geocube

NOTICE: Geocube has been replaced by EDX Spatial, a modern geospatial platform to map, visualize, query and explore spatial data. Online web mapping tool for visualization and simple analysis of Earth-energy data files from public and DOE related sources. Geocube allows users to upload and visualize their own datasets but also comes preloaded with individual spatial datasets as well as spatial data collections that align to topical themes.

carbon storage↗

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las↗

Spreader-Bar Radiation Detection System Enhancements: A Modeling and Simulation Study

An investigation of radiation detectors on crane-mounted platforms was performed to understand the limitations and optimal capability of these types of systems. Crane-mounted systems are primarily focused on crane-mounted radiation detector systems, where the detectors are mounted on a spreader-bar platform. Spreader bars are attached with cables to a crane at seaports to load and unload containers from cargo ships. The bars can spread from 20 feet to 53 feet using hydraulics, allowing a single bar to move a variety of container lengths. Spreader-bars are also used on straddle carriers, which move containers around the laydown yard in the port. Spreader bar radiation detection (SBRD) systems are commercially available from at least two companies. These systems employ a set of spectroscopic sensors placed on the underside of a gantry crane and held near the top of a cargo container for detection. These systems have been previously tested and some issues and limitations observed. Radiation detectors mounted on spreader-bars are single sided systems (observing cargo only from the top) and it is therefore challenging to obtain the same sensitivity as double-sided systems (for example, portal monitors) especially when considering the possible amounts of intervening cargo that could be present. The approximately exponential attenuation of gamma rays in intervening dense cargo presents an inherent limitation to detection. However, SBRD systems hold detectors closer to the container, have a longer dwell time, and may have lower background (over the ship); all of these aspects help mitigate the single-sided issue. In addition, there are operational considerations that make spreader-bar radiation systems attractive. These include scanning for radiation during other operations (loading, unloading or container movement) which minimizes additional time for scanning, incorporating the radiation detection into existing equipment to minimize initial cost, and in the case of ship unloading, scanning the containers before reaching the laydown yard. This study is focused on researching optimized configurations of SBRD systems, including number of detectors, locations, and best use of detector data, to determine a reasonable limit on the capability of these types of systems. The results will help support decisions on where and how these systems might be effectively deployed, and could be used for future specification development for SBRD acquisition. The next phase of this research and investigation into SBRD systems and quantification of the possible improved capability with an enhanced SBRD is the focus of this report. Supporting this investigation, detailed models of an enhanced SBRD system were created using a 3D radiation transport code, and models were run to simulate the data from sources and background for a realistic cargo-loading port environment. The enhanced SBRD had increased detector material (numbers of detectors) compared to the commercial systems, with a distribution providing more uniform coverage. Measurements using small industrial sources were made with an enhanced SBRD system developed by Sandia National Laboratory to support model validation to establish credibility for the simulations of these threat and background scenarios. A significant simulation effort was undertaken to simulate sources of interest within a 40-foot cargo container. In order to estimate the performance of a generalized SBRD system in scenarios including background and cargo, a highly enriched uranium (HEU) test source (with 3x10 -8 232 U by weight) within a wood cargo model was simulated for a 40-foot cargo container. This source was placed at a variety of locations, and the flux from the source was multiplied as necessary to create estimated minimal detectable quantities (MDQ) figures for various quantities of HEU. Simulated data sets were produced corresponding to a complete container offloading scenario for a large number of statistical realizations. Significant work was performed on both the algorithm development and the container cargo distributions entering the US, and the result of this modeling, validation, and simulation effort was a set of estimates of the performance of a variety of radiation detection algorithms in this cargo-screening environment. In the case of algorithms, a variety of contemporary radiation detection and identification approaches were employed, and the optimal approaches to selecting time and location subsets of detector data were explored. In all cases, algorithm performance was compared, and the best approaches were suggested along with the best expected performance from the enhanced SBRD. In general, template-matching schemes employing a limited set of regression parameters tend to provide best results. The improvements of an enhanced SBRD with increased detector material and improved algorithms result in an effective MDQ of 10 kg of HEU in ~50 percent of the imported cargo in 40-foot containers, assuming a random source location. This is approximately two times the capability of the estimated performance of the commercial systems. For an MDQ of the 10 kg HEU source located in the worst location (bottom of the 40-foot container), the volume of cargo scanned drops to 10% for the enhanced SBRD, again a factor of two or more larger than the commercial systems. Enhancing the SBRD systems by adding more detectors, providing a more uniform coverage, and incorporating more advanced algorithms will result in a significant increase in capability. Although this investigation provided some indication of the performance capabilities of an enhanced SBRD system, additional work is needed to estimate the capability for other container configurations, such as the 20 and 45 foot containers. Since the 20-foot container weight limit is similar to the 40-foot, more dense cargo is typically shipped in 20-foot containers. This will result in a smaller percentage of cargo scanned for the 20-foot containers (for a particular source quantity) compared to the 40-foot containers. In addition to other configuration, other source material needs to be investigated to understand the capabilities for the entire threat space, where only HEU is considered in this work.

crane-mounted↗

Research in High Energy Physics at Duke University

This is the Closeout Report for the research grant in experimental elementary particle physics, carried out by the Duke University High Energy Physics (HEP) group. We report on physics results and detector development carried out under this grant, focusing on the recent three-year grant period (2010 to 2013). The Duke HEP group consisted of seven faculty members, two senior scientists, five postdocs and eight graduate students. There were three thrusts of the research program. Measurements at the energy frontier at CDF and ATLAS were used to test aspects of elementary particle theory described by the Standard Model (SM) and to search for new forces and particles beyond those contained within the SM. The neutrino sector was explored using data obtained from a large neutrino detector located in Japan, and R & D was conducted on new experiments to be built in the US. The measurements provided information about neutrino masses and the manner in which neutrinos change species in particle beams. Two years ago we have started a new research program in rare processes based on the Mu2E experiment at Fermilab. This research is motivated by the search for the $\mu \longrightarrow e$ transition with unprecedented sensitivity, a transition forbidden in the standard model but allowed in supersymmetric and other models of new physics. The high energy research program used proton and antiproton colliding beams. The experiments were done at the Fermilab Tevatron (proton-antiproton collisions at a center of mass energy of 1.96 TeV) and at the CERN Large Hadron Collider (proton-proton collisions at 7-8 TeV). The neutrino program used data obtained from the Super-Kamiokande detector. This water-filled Cherenkov counter was used to detect and measure the properties of neutrinos produced in cosmic ray showers, and from neutrino beams produced from accelerators in Japan. The Mu2E experiment will use a special stopped muon beam to be built at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Research in High Energy Physics at Duke University

This is the Closeout Report for the research grant in experimental elementary particle physics, carried out by the Duke University High Energy Physics (HEP) group. We re- port on physics results and detector development carried out under this grant, focussing on the recent three-year grant period (2010 to 2013). The Duke HEP group consisted of seven faculty members, two senior scientists, five postdocs and eight graduate students. There were three thrusts of the research program. Measurements at the energy frontier at CDF and ATLAS were used to test aspects of elementary particle theory described by the Stan- dard Model (SM) and to search for new forces and particles beyond those contained within the SM. The neutrino sector was explored using data obtained from a large neutrino detector located in Japan, and R & D was conducted on new experiments to be built in the US. The measurements provided information about neutrino masses and the manner in which neutri- nos change species in particle beams. Two years ago we have started a new research program in rare processes based on the Mu2E experiment at Fermilab. This research is motivated by the search for the {mu} {yields} e transition with unprecedented sensitivity, a transition forbidden in the standard model but allowed in supersymmetric and other models of new physics. The high energy research program used proton and antiproton colliding beams. The experiments were done at the Fermilab Tevatron (proton-antiproton collisions at a center of mass energy of 1.96 TeV) and at the CERN Large Hadron Collider (proton-proton collisions at 7-8 TeV). The neutrino program used data obtained from the Super-Kamiokande detector. This water-filled Cherenkov counter was used to detect and measure the properties of neutrinos produced in cosmic ray showers, and from neutrino beams produced from acceler- ators in Japan. The Mu2E experiment will use a special stopped muon beam to be built at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Research in Theoretical High-Energy Physics at Southern Methodist University

The SMU Theory group has developed a strong expertise in QCD, PDFs, and incisive comparisons between collider data and theory. The group pursues realistic phenomenological calculations for high-energy processes, the highly demanded research area driven by the LHC physics. Our field has seen major discoveries in recent years from a variety of experiments, large and small, including a number recognized by Nobel Prizes. There is a wealth of novel QCD data to explore. The SMU theory group develops the most advanced and innovative tools for comprehensive analysis in applications ranging from Higgs physics and new physics searches to nuclear scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of Renewable Energy Data for Facilitating the Clean Energy Transition in Vietnam

Vietnam is transforming its power system with an increasing share of variable renewable energy (VRE) in the generation mix and plans to achieve 27% VRE by capacity in 2030 and 42% by capacity in 2045, as indicated by the draft Eighth Power Development Plan for 2020–-2045 (PDP8). Further increase in VRE penetration is possible with data-driven analysis where availability of data, specifically VRE data, becomes critical. NREL has worked with various stakeholders in Vietnam to create high-resolution multi-year VRE data publicly available to all. This paper reviews this new VRE data for Vietnam and how different stakeholders can use this data to inform VRE deployment decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Data Fusion to Enhance Quality Control and Analysis with Instruments at the Marine and Coastal Research Laboratory

Deploying environmental monitoring instruments in the marine environment can be challenging, facing challenges around device survivability, biofouling and corrosion, and consistent data collection. This project explores the use of data fusion – the process of integrating multiple data sources to produce more consistent, accurate, and useful information – to build a consistent long-term monitoring system at the Marine and Coastal Research Laboratory (MCRL) in Sequim, Washington. Unused instruments that had been acquired from past projects were inventoried and deployments planned on the MCRL pier and floating dock. A total of 8 instruments were deployed including a tide gauge, hydrophone, acoustic Doppler current profiler (ADCP), photosynthetically active radiation (PAR) sensors, meteorological station, and three water quality sensors. Deployments were planned to be well-protected around the pier structure and a maintenance schedule was created for cleaning and recalibration. An automated data pipeline was created to aggregate data on edge computers that push data to Amazon Web Services (AWS) cloud storage every 15 minutes, performing automated quality control and data transformations using the Time Series Data Analytical Toolkit (TSDAT). Continued efforts are underway to maintain this system into the future, take a data-driven approach to maintenance scheduling, improve the reliability of the system, and share the data with a variety of end-users.

54 ENVIRONMENTAL SCIENCES↗

Combining Spike Time Dependent Plasticity (STDP) and Backpropagation (BP) for Robust and Data Efficient Spiking Neural Networks (SNN)

National security applications require artificial neural networks (ANNs) that consume less power, are fast and dynamic online learners, are fault tolerant, and can learn from unlabeled and imbalanced data. We explore whether two fundamentally different, traditional learning algorithms from artificial intelligence and the biological brain can be merged. We tackle this problem from two directions. First, we start from a theoretical point of view and show that the spike time dependent plasticity (STDP) learning curve observed in biological networks can be derived using the mathematical framework of backpropagation through time. Second, we show that transmission delays, as observed in biological networks, improve the ability of spiking networks to perform classification when trained using a backpropagation of error (BP) method. These results provide evidence that STDP could be compatible with a BP learning rule. Combining these learning algorithms will likely lead to networks more capable of meeting our national security missions.

97 MATHEMATICS AND COMPUTING↗