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At least 37 records · Page 2

Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction

article presents an auto-generated database of 39,822 records containing chemical compounds and their associated Curie and Néel magnetic phase transition temperatures. The database was produced using natural language processing and semi-supervised quaternary relationship extraction, applied to a corpus of 68,078 chemistry and physics articles. Evaluation of the database shows an estimated overall precision of 73%. Therein, records processed with the text-mining toolkit, ChemDataExtractor, were assisted by a modified Snowball algorithm, whose original binary relationship extraction capabilities were extended to quaternary relationship extraction. Consequently, its machine learning component can now train with ≤500 seeds, rather than the 4,000 originally used. Data processed with the modified Snowball algorithm affords 82% precision. Database records are available in MongoDB, CSV and JSON formats which can easily be read using Python, R, Java and MatLab. As a result, this makes the database easy to query for tackling big-data materials science initiatives and provides a basis for magnetic materials discovery.

36 MATERIALS SCIENCE↗

Grounding annotations in published literature with an emphasis on the functional roles used in metabolic models

Accurate genome annotations in databases are a critical resource available to the scientific community for analysis and research. Inaccurate and inconsistent annotations exist as a result of errors generated from mass automated annotation, and currently act as a barrier to the application of bioinformatics. The purpose of this effort was to improve the SEED by improving the connection of functional roles to literature references. Direct literature references (DLits), found through searches of PubMed and other online databases such as SwissProt, were attached to protein sequences within the PubSEED to provide literature support for the roughly 2,500 distinct functional roles used to construct metabolic models within the Model SEED. Only DLits in which a researcher asserted the function of a protein were attached to sequences. Starting from a list of 1,072 functional roles that did not previously have DLit support, we were able to connect sequences to literature for 655 functional roles, at least 484 of which were in the original list of unsupported roles. When added to the existing set of sequences having DLits, the resulting set of DLit-sequence pairs (the foundation set) now connects approximately 4,300 DLits to approximately 5,600 distinct protein sequences obtained from approximately 16,000 genes (some of these genes have identical protein sequences). From the foundation set, we construct projection sets such that each set contains one member of the foundation set and projections of its functional role onto similar genes. The projection sets revealed 120 inconsistent annotations within the SEED. Two types of inconsistencies were corrected through manual annotation in the PubSEED: instances in which two identical protein sequences had been annotated with different functions, and instances when projected functions contradicted previous annotations. 26,785 changes to gene function assignment, 219 of which were to previously uncharacterized proteins, resulted in a more consistent and accurate set of input data from which to construct revised metabolic models within the Model SEED.

59 BASIC BIOLOGICAL SCIENCES↗

Response network analysis of differential gene expression in human epithelial lung cells during avian influenza infections

Background: The recent emergence of the H5N1 influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily infect humans. We analyzed differential gene expression of lung epithelial cells to compare the response to H5N1 infection with a more benign infection with Respiratory Syncytial Virus (RSV). These gene expression data are then used as seeds to find important nodes by using a novel combination of the Gene Ontology database and the Human Network of gene interactions. Additional analysis of the data is conducted by training support vector machines (SVM) with the data and examining the orientations of the optimal hyperplanes generated. Results: Analysis of gene clustering in the Gene Ontology shows no significant clustering of genes unique to H5N1 response at 8 hours post infection. At 24 hours post infection, however, a number of significant gene clusters are found for nodes representing “immune response” and “response to virus” terms. There were no significant clusters of genes in the Gene Ontology for the control (Mock) or RSV experiments that were unique relative to the H5N1 response. The genes found to be most important in distinguishing H5N1 infected cells from the controls using SVM showed a large degree of overlap with the list of significantly regulated genes. However, though none of these genes were members of the GO clusters found to be significant. Conclusions: Characteristics of H5N1 infection compared to RSV infection show several immune response factors that are specific for each of these infections. These include faster timescales within the cell as well as a more focused activation of immunity factors. Many of the genes that are found to be significantly expressed in H5N1 response relative to the control experiments are not found to cluster significantly in the Gene Ontology. These genes are, however, often closely linked to the clustered genes through the Human Network. This may suggest the need for more diverse annotations of these genes and verification of their action in immune response.

59 BASIC BIOLOGICAL SCIENCES↗

Investigation of divertor detachment induced through neon seeding and density ramp on HL-3

A new self-consistent 1D scrape-off layer model has been recently developed in BOUT++ framework, named SD1D, which includes equations for various particle species (e.g. main plasma, neutrals and impurities) and couples open databases like ADAS and AMJUEL. It is able to quickly and effectively simulate divertor detachment experiments. In this work, a typical detachment experiment (shot #6270) on HL-3 with neon seeding is simulated using the SD1D code. It is found that the target electron temperature and the target ion saturation current in the simulations are consistent with experimental results measured by Langmuir probes on the target plate. The variation of D α radiation intensity in the divertor is qualitatively similar to the measured D α signal. Following the experimental validations, different upstream densities are set in the simulations to study the impurity distribution under different plasma density conditions. It is found that increasing upstream density can be helpful for the control of the neon radiation front (closer to the target). In this work we also compare two detachment regimes in simulations. Based on the same initial experimental parameters (shot #6270) on HL-3, a scan of upstream density and a scan of neon seeding rate are carried out respectively. It is found that the role of atomic and molecular processes is different in the two detachment regimes. The current density roll-over is ascribed to a drop in the divertor ion source, and the variation of D α radiation intensity via different excitation channels is associated with the relevant collisional reaction sources.

BOUT++↗

Constructing a Tandem Mass Spectral Library for Forensic Ricin Identification

Ricin, a protein found in castor seeds, is a lethal toxin that is designated as a category 2 select agent. Because castor seeds are easy to obtain and the toxin can be easily extracted, cases of attempted ricin poisoning are relatively common. A shotgun proteomics method for ricin identification has recently been developed (manuscript in preparation), in which ricin peptides are identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by proteomics database search, and peptide-spectrum matches are verified and compared to standard spectra by a human expert. To make this process more reproducible, objective, and high-throughput, we have created a ricin spectral library for peptide identification to supplement the human review step. To construct these spectral libraries, two pure ricin samples (from a proposed standard reference material) and crude castor seed extracts were digested with trypsin and analyzed using a standard shotgun LC-MS/MS protocol. Spectral libraries were created from the filtered search results from four database search tools. The library was then used in a search using SpectraST on samples from castor seeds. Analysis showed that the spectral library search resulted in more peptides identified from crude castor seed samples compared to MS-GF+ and Sequest plus Percolator. These results suggest that computational comparison of putative ricin peptide spectra to library spectra can be an effective method of confirming the presence of ricin, and that spectral library search may be suitable to augment the more manual and subjective aspects of the currently recommended human expert review.

Spectral Library, Ricin, forensic, proteomic↗

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome

Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location: Tundra biome. Time period: Data collected between 1964 and 2016. Major taxa studied: 295 tundra vascular plant species. Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post-hoc clustering of species-level traits. Results: Traditional functional groups explained significant differences in trait expression, particularly among traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post-hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. Main conclusion: Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra ecosystem change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insight for ecological prediction and modelling.

59 BASIC BIOLOGICAL SCIENCES↗

The root cause of disruptive NTMs and paths to stable operation in DIII-D ITER baseline scenario plasmas

Analyses of the DIII-D ITER Baseline Scenario database support that the disruptive m,n=2,1 magnetic islands are pressure gradient driven, non-linear instabilities seeded in a sequence of stochastic transient magnetic perturbations, and that the current profile relaxation does not affect the m,n=2,1 island onset rate. At low torque, these Neoclassical Tearing Modes are most commonly seeded by non-linear 3-wave coupling when the differential rotation between the q=1 & q=2 rational surfaces approaches zero. Lack of statistically significant difference between the current profiles of stable and unstable states, as well as lack of correlation between the tearing mode onset rate and the current profile relaxation both reject causality between the current profile evolution and the 2,1 magnetic island onsets in these plasmas. These support that preserving the differential rotation between the q=1 and q=2 rational surfaces is key to long pulse stable operation in the plasma scenario planned for ITER, while optimization of the current profile within the explored parameter space may lead to much weaker improvements than sustaining the differential rotation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, business investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Environmental resource deficit may drive the evolution of intraspecific trait variation in invasive plant populations

Intraspecific trait variation within natural populations (i.e. intra-population trait variation, IPTV) is the basic source for selection and can have significant ecological consequences. Higher IPTV may increase a population's niche breath and benefit interspecies competition under a resource-limited environment, thus affecting the ability of a species to move into novel habitats. However, the reciprocal influences of variation in environmental conditions and phenotypic trait expression in spreading plant populations are not clearly defined. Here, we propose that during invasion, IPTV and its relative change in response to key resource enrichment may increase with the resource deficit of invaded sites, and that this relationship may facilitate plant invasions into resource-limited environments. We analyzed the invasion trend, IPTV and its response to water enrichment, and moisture variability among populations of an annual grass Brachypodium hybridum in California, United States. We incorporated a genotyping-by-sequencing approach, a common garden experiment that had two water level treatments, and public plant and climate databases. Our hypothesis was supported by the observation that for populations that invaded sites with higher spring moisture deficit, both their seed biomass IPTV (for the water-enriched treatment only) and relative change of the IPTV across water treatments were larger when examined in the common garden experiment. A generally north to south spreading direction was found in these B. hybridum populations, towards a drier and warmer climate exhibiting higher moisture deficit for plant growth. Our results suggest a role for interactions between IPTV (rather than trait means) and environmental resource availability in promoting plant invasions, providing new insights into the significance of IPTV in shaping plant geographic distributions.

54 ENVIRONMENTAL SCIENCES↗

Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01

Background. A landmark in soybean research, Glyma1.01, the first whole genome sequence of variety Williams 82 (Glycine max L. Merr.) was completed in 2010 and is widely used. However, because the assembly was primarily built based on the linkage maps constructed with a limited number of markers and recombinant inbred lines (RILs), the assembled sequence, especially in some genomic regions with sparse numbers of anchoring markers, needs to be improved. Molecular markers are being used by researchers in the soybean community, however, with the updating of the Glyma1.01 build based on the high-resolution linkage maps resulting from this research, the genome positions of these markers need to be mapped. Results. Two high density genetic linkage maps were constructed based on 21,478 single nucleotide polymorphism loci mapped in the Williams 82 x G. soja (Sieb. & Zucc.) PI479752 population with 1083 RILs and 11,922 loci mapped in the Essex x Williams 82 population with 922 RILs. There were 37 regions or single markers where marker order in the two populations was in agreement but was not consistent with the physical position in the Glyma1.01 build. In addition, 28 previously unanchored scaffolds were positioned. Map data were used to identify false joins in the Glyma1.01 assembly and the corresponding scaffolds were broken and reassembled to the new assembly, Wm82.a2.v1. Based upon the plots of the genetic on physical distance of the loci, the euchromatic and heterochromatic regions along each chromosome in the new assembly were delimited. Genomic positions of the commonly used markers contained in BARCSOYSSR_1.0 database and the SoySNP50K BeadChip were updated based upon the Wm82.a2.v1 assembly. Conclusions. The information will facilitate the study of recombination hot spots in the soybean genome, identification of genes or quantitative trait loci controlling yield, seed quality and resistance to biotic or abiotic stresses as well as other genetic or genomic research.

59 BASIC BIOLOGICAL SCIENCES↗

Electron cyclotron emission detection of neoclassical tearing modes for control for ITER

Successful operation of ITER requires control of magnetic instabilities including neoclassical tearing modes (NTMs) that can degrade confinement and lead to disruption. Low latency detection by electron cyclotron emission (ECE) diagnostics has been demonstrated in a few current experiments. Using a synthetic diagnostic, we demonstrate low latency NTM detection for ITER with plasmas described by ITER IMAS database scenarios and with realistic limitations imposed on the instrumentation by these high temperature scenarios. 2/1 NTMs are detected 430 ms after magnetic island seeding and before island locking. The radiometer configuration was optimized using simulation, and the smallest detectable island size was explored. Island sizes of ∼3 cm are detectable at the 2/1 surface. The simulated signals incorporate recent physics models for island growth and rotation, which show early locking and continued island growth after locking and before disruption. This work determines limits for ITER ECE spatial resolution imposed by relativistic broadening of channels, which informs hardware design. Real-time detection is demonstrated in hardware that is required by ITER, including on an NI PXI-7853R FPGA system. Development of a synthetic diagnostic and details of the hardware will be discussed.

Cyclotron radiation↗

Final Report. Grant DOE DE-FG02-04ER54768

The magnetized spherical implosion campaign funded by this grant is summarized in this progress report. The main goal of this grant was to improve the seed eld generator MIFEDS (Magneto- Inertial Fusion Energy Delivery System) on the OMEGA laser to enable experiments at high elds (> 8 T) and to carry out magnetized spherical implosion experiments to study the e ect of magnetic elds on the fusion yield. New experiments were carried out in the last budget period to study the e ect of higher elds and shaped laser pulses. These new experiments improved the magnetized implosion database and allowed us to improve the con dence of our conclusions with respect to the e ect of magnetic elds on implosion performance. The main conclusion is that adding magnetic eld leads to a 30% higher neutron yield, but using seed magnetic eld higher than 8 T does not further increase the neutron yield. A further conclusion is that the yield enhancement due to the magnetic eld is approximately independent of the laser pulse shape.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Standard Energy Efficiency Data Platform

The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.

Cheifetz, D.Magnus↗

Standard Energy Efficiency Data Platform

The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.

Cheifetz, D. Magnus↗

Direct cross section measurement of 102 Pd ⁢(𝛾,𝑝) and 102 Pd ⁢(𝛾,𝛼) for the astrophysical 𝑝 process

Background: A handful of neutron-deficient stable nuclei, known as the “p nuclei,” cannot be produced through astrophysical neutron capture processes. Instead, some of these nuclei are proposed to be produced by 𝛾-induced reactions on existing r- and s-process seeds. The specific astrophysical site or sites are not yet identified, however, with uncertainties in the cross sections of these 𝛾-induced reactions playing a role. Databases of reaction rates for astrophysical simulations often rely on theoretical statistical model calculations, such as Hauser-Feshbach, for rates where no experimental information is known. However, reasonable variations in the choice of parametrizations of various nuclear properties can create order-of-magnitude variations in the final predicted cross sections and reaction rates, which are then propagated through the models to the predicted final abundances. Purpose: To better constrain these statistical model calculations and ultimately reduce the uncertainties from the nuclear physics on our understanding of the p nuclei, a measurement of the cross sections of 𝛾-induced reactions on the p-nucleus 102 Pd was undertaken. This work represents the first measurement of its kind, using segmented silicon detectors to measure prompt charged particle emission from 𝛾-induced reactions. Methods: Quasimonoenergetic gamma beams from the High Intensity 𝛾 Source facility bombarded an enriched 102 Pd target. A segmented silicon array was arranged to detect the particles emitted from (𝛾,𝑝) and (𝛾,𝛼) reactions. Results: Reaction cross sections were deduced at multiple 𝛾-beam energies between 10 and 19 MeV, and compared to statistical model calculations using talys-1.96. The 102 Pd ⁢(𝛾,𝑝)⁢ 101 Rh reaction cross section was reasonably well reproduced by a subset of photon strength functions and level densities, though the strength to the ground state of 101 Rh was underestimated at higher incident gamma energies. The 102 Pd ⁢(𝛾,𝛼)⁢ 98 Ru was in general overpredicted by the various alpha-nucleus optical model potentials. Conclusions: While the theoretical cross sections used to model the (𝛾,𝑝) reactions for the p process may be reasonable, a more careful approach is needed in the case of (𝛾,𝛼). Further work to probe gamma-induced reaction cross sections at and near the p nuclei is warranted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Robustness of trait connections across environmental gradients and growth forms

Abstract Aim Plant trait databases often contain traits that are correlated, but for whom direct (undirected statistical dependency) and indirect (mediated by other traits) connections may be confounded. The confounding of correlation and connection hinders our understanding of plant strategies, and how these vary among growth forms and climate zones. We identified the direct and indirect connections across plant traits relevant to competition, resource acquisition and reproductive strategies using a global database and explored whether connections within and between traits from different tissue types vary across climates and growth forms. Location Global. Major taxa studied Plants. Time period Present. Methods We used probabilistic graphical models and a database of 10 plant traits (leaf area, specific leaf area, mass‐ and area‐based leaf nitrogen and phosphorous content, leaf life span, plant height, stem specific density and seed mass) with 16,281 records to describe direct and indirect connections across woody and non‐woody plants across tropical, temperate, arid, cold and polar regions. Results Trait networks based on direct connections are sparser than those based on correlations. Land plants had high connectivity across traits within and between tissue types; leaf life span and stem specific density shared direct connections with all other traits. For both growth forms, two groups of traits form modules of more highly connected traits; one related to resource acquisition, the other to plant architecture and reproduction. Woody species had higher trait network modularity in polar compared to temperate and tropical climates, while non‐woody species did not show significant differences in modularity across climate regions. Main conclusions Plant traits are highly connected both within and across tissue types, yet traits segregate into persistent modules of traits. Variation in the modularity of trait networks suggests that trait connectivity is shaped by prevailing environmental conditions and demonstrates that plants of different growth forms use alternative strategies to cope with local conditions.

Flores‐Moreno, Habacuc↗

The global spectrum of plant form and function: enhanced species-level trait dataset

Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

54 ENVIRONMENTAL SCIENCES↗

In search of genome annotation consistency: solid gene clusters and how to use them

Maintaining consistency in genome annotations is important for supporting many computational tasks, particularly metabolic modeling. The SEED project has implemented a process that improves annotation consistencies across microbial genomes for proteins with conserved sequences and genomic context. In this research report, we describe this process and show how this effort has resulted in improvements to microbial genome annotations in the SEED. We also compare SEED annotation consistencies with other commonly used resources such as IMG (the Joint Genome Institute’s Integrated Microbial Genomes system), RefSeq (the National Center for Biotechnology Information’s Reference Sequence Database), Swiss-Prot (the annotated protein sequence database of the Swiss Institute of Bioinformatics, European Molecular Biology Laboratory and the European Bioinformatics Institute) and TrEMBL (Translated European Molecular Biology Laboratory nucleotide sequence data Library). Our analysis indicates that manual and computational efforts are paying off for the databases where consistency is a major goal.

59 BASIC BIOLOGICAL SCIENCES↗