Large Crater Clustering tool

NASA Astrophysics Data System (ADS)

Laura, Jason; Skinner, James A.; Hunter, Marc A.

2017-08-01

In this paper we present the Large Crater Clustering (LCC) tool set, an ArcGIS plugin that supports the quantitative approximation of a primary impact location from user-identified locations of possible secondary impact craters or the long-axes of clustered secondary craters. The identification of primary impact craters directly supports planetary geologic mapping and topical science studies where the chronostratigraphic age of some geologic units may be known, but more distant features have questionable geologic ages. Previous works (e.g., McEwen et al., 2005; Dundas and McEwen, 2007) have shown that the source of secondary impact craters can be estimated from secondary impact craters. This work adapts those methods into a statistically robust tool set. We describe the four individual tools within the LCC tool set to support: (1) processing individually digitized point observations (craters), (2) estimating the directional distribution of a clustered set of craters, back projecting the potential flight paths (crater clusters or linearly approximated catenae or lineaments), (3) intersecting projected paths, and (4) intersecting back-projected trajectories to approximate the local of potential source primary craters. We present two case studies using secondary impact features mapped in two regions of Mars. We demonstrate that the tool is able to quantitatively identify primary impacts and supports the improved qualitative interpretation of potential secondary crater flight trajectories.

Importance of the Kinetic Energy Density for Band Gap Calculations in Solids with Density Functional Theory.

PubMed

Tran, Fabien; Blaha, Peter

2017-05-04

Recently, exchange-correlation potentials in density functional theory were developed with the goal of providing improved band gaps in solids. Among them, the semilocal potentials are particularly interesting for large systems since they lead to calculations that are much faster than with hybrid functionals or methods like GW. We present an exhaustive comparison of semilocal exchange-correlation potentials for band gap calculations on a large test set of solids, and particular attention is paid to the potential HLE16 proposed by Verma and Truhlar. It is shown that the most accurate potential is the modified Becke-Johnson potential, which, most noticeably, is much more accurate than all other semilocal potentials for strongly correlated systems. This can be attributed to its additional dependence on the kinetic energy density. It is also shown that the modified Becke-Johnson potential is at least as accurate as the hybrid functionals and more reliable for solids with large band gaps.

Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Aidan Patrick; Schultz, Peter Andrew; Crozier, Paul

2014-09-01

This report summarizes the result of LDRD project 12-0395, titled "Automated Algorithms for Quantum-level Accuracy in Atomistic Simulations." During the course of this LDRD, we have developed an interatomic potential for solids and liquids called Spectral Neighbor Analysis Poten- tial (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projectedmore » on to a basis of hyperspherical harmonics in four dimensions. The SNAP coef- ficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. Global optimization methods in the DAKOTA software package are used to seek out good choices of hyperparameters that define the overall structure of the SNAP potential. FitSnap.py, a Python-based software pack- age interfacing to both LAMMPS and DAKOTA is used to formulate the linear regression problem, solve it, and analyze the accuracy of the resultant SNAP potential. We describe a SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties. Most significantly, in contrast to existing tantalum potentials, SNAP correctly predicts the Peierls barrier for screw dislocation motion. We also present results from SNAP potentials generated for indium phosphide (InP) and silica (SiO 2 ). We describe efficient algorithms for calculating SNAP forces and energies in molecular dynamics simulations using massively parallel computers and advanced processor ar- chitectures. Finally, we briefly describe the MSM method for efficient calculation of electrostatic interactions on massively parallel computers.« less

Pharmacogenomics in diverse practice settings: implementation beyond major metropolitan areas

PubMed Central

Dorfman, Elizabeth H; Trinidad, Susan Brown; Morales, Chelsea T; Howlett, Kevin; Burke, Wylie; Woodahl, Erica L

2015-01-01

Aim The limited formal study of the clinical feasibility of implementing pharmacogenomic tests has thus far focused on providers at large medical centers in urban areas. Our research focuses on small metropolitan, rural and tribal practice settings. Materials & methods We interviewed 17 healthcare providers in western Montana regarding pharmacogenomic testing. Results Participants were optimistic about the potential of pharmacogenomic tests, but noted unique barriers in small and rural settings including cost, adherence, patient acceptability and testing timeframe. Participants in tribal settings identified heightened sensitivity to genetics and need for community leadership approval as additional considerations. Conclusion Implementation differences in small metropolitan, rural and tribal communities may affect pharmacogenomic test adoption and utilization, potentially impacting many patients. PMID:25712186

PCR Amplicon Prediction from Multiplex Degenerate Primer and Probe Sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S. N.

2013-08-08

Assessing primer specificity and predicting both desired and off-target amplification products is an essential step for robust PCR assay design. Code is described to predict potential polymerase chain reaction (PCR) amplicons in a large sequence database such as NCBI nt from either singleplex or a large multiplexed set of primers, allowing degenerate primer and probe bases, with target mismatch annotates amplicons with gene information automatically downloaded from NCBI, and optionally it can predict whether there are also TaqMan/Luminex probe matches within predicted amplicons.

Social epidemiology of a large outbreak of chickenpox in the Colombian sugar cane producer region: a set theory-based analysis.

PubMed

Idrovo, Alvaro J; Albavera-Hernández, Cidronio; Rodríguez-Hernández, Jorge Martín

2011-07-01

There are few social epidemiologic studies on chickenpox outbreaks, although previous findings suggested the important role of social determinants. This study describes the context of a large outbreak of chickenpox in the Cauca Valley region, Colombia (2003 to 2007), with an emphasis on macro-determinants. We explored the temporal trends in chickenpox incidence in 42 municipalities to identify the places with higher occurrences. We analyzed municipal characteristics (education quality, vaccination coverage, performance of health care services, violence-related immigration, and area size of planted sugar cane) through analyses based on set theory. Edwards-Venn diagrams were used to present the main findings. The results indicated that three municipalities had higher incidences and that poor quality education was the attribute most prone to a higher incidence. Potential use of set theory for exploratory outbreak analyses is discussed. It is a tool potentially useful to contrast units when only small sample sizes are available.

Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogens

PubMed Central

Huang, Shan-Han; Tung, Chun-Wei

2017-01-01

The assessment of non-genotoxic hepatocarcinogens (NGHCs) is currently relying on two-year rodent bioassays. Toxicogenomics biomarkers provide a potential alternative method for the prioritization of NGHCs that could be useful for risk assessment. However, previous studies using inconsistently classified chemicals as the training set and a single microarray dataset concluded no consensus biomarkers. In this study, 4 consensus biomarkers of A2m, Ca3, Cxcl1, and Cyp8b1 were identified from four large-scale microarray datasets of the one-day single maximum tolerated dose and a large set of chemicals without inconsistent classifications. Machine learning techniques were subsequently applied to develop prediction models for NGHCs. The final bagging decision tree models were constructed with an average AUC performance of 0.803 for an independent test. A set of 16 chemicals with controversial classifications were reclassified according to the consensus biomarkers. The developed prediction models and identified consensus biomarkers are expected to be potential alternative methods for prioritization of NGHCs for further experimental validation. PMID:28117354

Adaptive Landscape Flattening Accelerates Sampling of Alchemical Space in Multisite λ Dynamics.

PubMed

Hayes, Ryan L; Armacost, Kira A; Vilseck, Jonah Z; Brooks, Charles L

2017-04-20

Multisite λ dynamics (MSλD) is a powerful emerging method in free energy calculation that allows prediction of relative free energies for a large set of compounds from very few simulations. Calculating free energy differences between substituents that constitute large volume or flexibility jumps in chemical space is difficult for free energy methods in general, and for MSλD in particular, due to large free energy barriers in alchemical space. This study demonstrates that a simple biasing potential can flatten these barriers and introduces an algorithm that determines system specific biasing potential coefficients. Two sources of error, deep traps at the end points and solvent disruption by hard-core potentials, are identified. Both scale with the size of the perturbed substituent and are removed by sharp biasing potentials and a new soft-core implementation, respectively. MSλD with landscape flattening is demonstrated on two sets of molecules: derivatives of the heat shock protein 90 inhibitor geldanamycin and derivatives of benzoquinone. In the benzoquinone system, landscape flattening leads to 2 orders of magnitude improvement in transition rates between substituents and robust solvation free energies. Landscape flattening opens up new applications for MSλD by enabling larger chemical perturbations to be sampled with improved precision and accuracy.

Selection, application, and validation of a set of molecular descriptors for nuclear receptor ligands.

PubMed

Stewart, Eugene L; Brown, Peter J; Bentley, James A; Willson, Timothy M

2004-08-01

A methodology for the selection and validation of nuclear receptor ligand chemical descriptors is described. After descriptors for a targeted chemical space were selected, a virtual screening methodology utilizing this space was formulated for the identification of potential NR ligands from our corporate collection. Using simple descriptors and our virtual screening method, we are able to quickly identify potential NR ligands from a large collection of compounds. As validation of the virtual screening procedure, an 8, 000-membered NR targeted set and a 24, 000-membered diverse control set of compounds were selected from our in-house general screening collection and screened in parallel across a number of orphan NR FRET assays. For the two assays that provided at least one hit per set by the established minimum pEC(50) for activity, the results showed a 2-fold increase in the hit-rate of the targeted compound set over the diverse set.

Benchmark data sets for structure-based computational target prediction.

PubMed

Schomburg, Karen T; Rarey, Matthias

2014-08-25

Structure-based computational target prediction methods identify potential targets for a bioactive compound. Methods based on protein-ligand docking so far face many challenges, where the greatest probably is the ranking of true targets in a large data set of protein structures. Currently, no standard data sets for evaluation exist, rendering comparison and demonstration of improvements of methods cumbersome. Therefore, we propose two data sets and evaluation strategies for a meaningful evaluation of new target prediction methods, i.e., a small data set consisting of three target classes for detailed proof-of-concept and selectivity studies and a large data set consisting of 7992 protein structures and 72 drug-like ligands allowing statistical evaluation with performance metrics on a drug-like chemical space. Both data sets are built from openly available resources, and any information needed to perform the described experiments is reported. We describe the composition of the data sets, the setup of screening experiments, and the evaluation strategy. Performance metrics capable to measure the early recognition of enrichments like AUC, BEDROC, and NSLR are proposed. We apply a sequence-based target prediction method to the large data set to analyze its content of nontrivial evaluation cases. The proposed data sets are used for method evaluation of our new inverse screening method iRAISE. The small data set reveals the method's capability and limitations to selectively distinguish between rather similar protein structures. The large data set simulates real target identification scenarios. iRAISE achieves in 55% excellent or good enrichment a median AUC of 0.67 and RMSDs below 2.0 Å for 74% and was able to predict the first true target in 59 out of 72 cases in the top 2% of the protein data set of about 8000 structures.

Electrostatic similarity of proteins: Application of three dimensional spherical harmonic decomposition

PubMed Central

Długosz, Maciej; Trylska, Joanna

2008-01-01

We present a method for describing and comparing global electrostatic properties of biomolecules based on the spherical harmonic decomposition of electrostatic potential data. Unlike other approaches our method does not require any prior three dimensional structural alignment. The electrostatic potential, given as a volumetric data set from a numerical solution of the Poisson or Poisson–Boltzmann equation, is represented with descriptors that are rotation invariant. The method can be applied to large and structurally diverse sets of biomolecules enabling to cluster them according to their electrostatic features. PMID:18624502

Can Personal Goal Setting Tap the Potential of the Gifted Underachiever?

ERIC Educational Resources Information Center

Morisano, Dominique; Shore, Bruce M.

2010-01-01

Although underachieving gifted students have been largely ignored in empirical research, there has been a modest surge of interest in describing and "treating" this population in recent years. It is estimated that nearly half of gifted youth achieve significantly below their potential. In the realm of school psychology, gifted children have…

Variation in pollen limitation and floral parasitism across a mating system transition in a Pacific coastal dune plant: evolutionary causes or ecological consequences?

PubMed

Dart, Sara; Eckert, Christopher G

2015-02-01

Evolutionary transitions from outcrossing to self-fertilization are thought to occur because selfing provides reproductive assurance when pollinators or mates are scarce, but they could also occur via selection to reduce floral vulnerability to herbivores. This study investigated geographic covariation between floral morphology, fruit set, pollen limitation and florivory across the geographic range of Camissoniopsis cheiranthifolia, a Pacific coastal dune endemic that varies strikingly in flower size and mating system. Fruit set was quantified in 75 populations, and in 41 of these floral herbivory by larvae of a specialized moth (Mompha sp.) that consumes anthers in developing buds was also quantified. Experimental pollen supplementation was performed to quantify pollen limitation in three large-flowered, outcrossing and two small-flowered, selfing populations. These parameters were also compared between large- and small-flowered phenotypes within three mixed populations. Fruit set was much lower in large-flowered populations, and also much lower among large- than small-flowered plants within populations. Pollen supplementation increased per flower seed production in large-flowered but not small-flowered populations, but fruit set was not pollen limited. Hence inadequate pollination cannot account for the low fruit set of large-flowered plants. Floral herbivory was much more frequent in large-flowered populations and correlated negatively with fruit set. However, florivores did not preferentially attack large-flowered plants in three large-flowered populations or in two of three mixed populations. Selfing alleviated pollen limitation of seeds per fruit, but florivory better explains the marked variation in fruit set. Although florivory was more frequent in large-flowered populations, large-flowered individuals were not generally more vulnerable within populations. Rather than a causative selective factor, reduced florivory in small-flowered, selfing populations is probably an ecological consequence of mating system differentiation, with potentially significant effects on population demography and biotic interactions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Approaching the basis set limit for DFT calculations using an environment-adapted minimal basis with perturbation theory: Formulation, proof of concept, and a pilot implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Yuezhi; Horn, Paul R.; Mardirossian, Narbe

2016-07-28

Recently developed density functionals have good accuracy for both thermochemistry (TC) and non-covalent interactions (NC) if very large atomic orbital basis sets are used. To approach the basis set limit with potentially lower computational cost, a new self-consistent field (SCF) scheme is presented that employs minimal adaptive basis (MAB) functions. The MAB functions are optimized on each atomic site by minimizing a surrogate function. High accuracy is obtained by applying a perturbative correction (PC) to the MAB calculation, similar to dual basis approaches. Compared to exact SCF results, using this MAB-SCF (PC) approach with the same large target basis set producesmore » <0.15 kcal/mol root-mean-square deviations for most of the tested TC datasets, and <0.1 kcal/mol for most of the NC datasets. The performance of density functionals near the basis set limit can be even better reproduced. With further improvement to its implementation, MAB-SCF (PC) is a promising lower-cost substitute for conventional large-basis calculations as a method to approach the basis set limit of modern density functionals.« less

Review of comparative LCAs of food waste management systems - Current status and potential improvements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernstad, A., E-mail: anna.bernstad@chemeng.lth.se; Cour Jansen, J. la

2012-12-15

Highlights: Black-Right-Pointing-Pointer GHG-emissions from different treatment alternatives vary largely in 25 reviewed comparative LCAs of bio-waste management. Black-Right-Pointing-Pointer System-boundary settings often vary largely in reviewed studies. Black-Right-Pointing-Pointer Existing LCA guidelines give varying recommendations in relation to several key issues. - Abstract: Twenty-five comparative cycle assessments (LCAs) addressing food waste treatment were reviewed, including the treatment alternatives landfill, thermal treatment, compost (small and large scale) and anaerobic digestion. The global warming potential related to these treatment alternatives varies largely amongst the studies. Large differences in relation to setting of system boundaries, methodological choices and variations in used input data were seenmore » between the studies. Also, a number of internal contradictions were identified, many times resulting in biased comparisons between alternatives. Thus, noticed differences in global warming potential are not found to be a result of actual differences in the environmental impacts from studied systems, but rather to differences in the performance of the study. A number of key issues with high impact on the overall global warming potential from different treatment alternatives for food waste were identified through the use of one-way sensitivity analyses in relation to a previously performed LCA of food waste management. Assumptions related to characteristics in treated waste, losses and emissions of carbon, nutrients and other compounds during the collection, storage and pretreatment, potential energy recovery through combustion, emissions from composting, emissions from storage and land use of bio-fertilizers and chemical fertilizers and eco-profiles of substituted goods were all identified as highly relevant for the outcomes of this type of comparisons. As the use of LCA in this area is likely to increase in coming years, it is highly relevant to establish more detailed guidelines within this field in order to increase both the general quality in assessments as well as the potentials for cross-study comparisons.« less

Using Collaborative Two-Stage Examinations to Address Test Anxiety in a Large Enrollment Gateway Course

ERIC Educational Resources Information Center

Fournier, Kimberly A.; Couret, Jannelle; Ramsay, Jason B.; Caulkins, Joshua L.

2017-01-01

Large enrollment foundational courses are perceived as "high stakes" because of their potential to act as barriers for progression to the next course or admittance to a program. The nature of gateway courses makes them ideal settings to explore the relationship between anxiety, pedagogical interventions, and student performance. Here,…

A large set of potential past, present and future hydro-meteorological time series for the UK

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Dadson, Simon J.; Coxon, Gemma; Bussi, Gianbattista; Freer, James; Kay, Alison L.; Massey, Neil R.; Sparrow, Sarah N.; Wallom, David C. H.; Allen, Myles R.; Hall, Jim W.

2018-01-01

Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900-2006), (ii) five near-future scenarios (2020-2049) and (iii) five far-future scenarios (2070-2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1-30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK.

Comparing Analysis Frames for Visual Data Sets: Using Pupil Views Templates to Explore Perspectives of Learning

ERIC Educational Resources Information Center

Wall, Kate; Higgins, Steve; Remedios, Richard; Rafferty, Victoria; Tiplady, Lucy

2013-01-01

A key challenge of visual methodology is how to combine large-scale qualitative data sets with epistemologically acceptable and rigorous analysis techniques. The authors argue that a pragmatic approach drawing on ideas from mixed methods is helpful to open up the full potential of visual data. However, before one starts to "mix" the…

Entropic potential field formed for a linear-motor protein near a filament: Statistical-mechanical analyses using simple models.

PubMed

Amano, Ken-Ichi; Yoshidome, Takashi; Iwaki, Mitsuhiro; Suzuki, Makoto; Kinoshita, Masahiro

2010-07-28

We report a new progress in elucidating the mechanism of the unidirectional movement of a linear-motor protein (e.g., myosin) along a filament (e.g., F-actin). The basic concept emphasized here is that a potential field is entropically formed for the protein on the filament immersed in solvent due to the effect of the translational displacement of solvent molecules. The entropic potential field is strongly dependent on geometric features of the protein and the filament, their overall shapes as well as details of the polyatomic structures. The features and the corresponding field are judiciously adjusted by the binding of adenosine triphosphate (ATP) to the protein, hydrolysis of ATP into adenosine diphosphate (ADP)+Pi, and release of Pi and ADP. As the first step, we propose the following physical picture: The potential field formed along the filament for the protein without the binding of ATP or ADP+Pi to it is largely different from that for the protein with the binding, and the directed movement is realized by repeated switches from one of the fields to the other. To illustrate the picture, we analyze the spatial distribution of the entropic potential between a large solute and a large body using the three-dimensional integral equation theory. The solute is modeled as a large hard sphere. Two model filaments are considered as the body: model 1 is a set of one-dimensionally connected large hard spheres and model 2 is a double helical structure formed by two sets of connected large hard spheres. The solute and the filament are immersed in small hard spheres forming the solvent. The major findings are as follows. The solute is strongly confined within a narrow space in contact with the filament. Within the space there are locations with sharply deep local potential minima along the filament, and the distance between two adjacent locations is equal to the diameter of the large spheres constituting the filament. The potential minima form a ringlike domain in model 1 while they form a pointlike one in model 2. We then examine the effects of geometric features of the solute on the amplitudes and asymmetry of the entropic potential field acting on the solute along the filament. A large aspherical solute with a cleft near the solute-filament interface, which mimics the myosin motor domain, is considered in the examination. Thus, the two fields in our physical picture described above are qualitatively reproduced. The factors to be taken into account in further studies are also discussed.

Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

PubMed

Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

2015-12-21

Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKemmish, Laura K., E-mail: laura.mckemmish@gmail.com; Research School of Chemistry, Australian National University, Canberra

Algorithms for the efficient calculation of two-electron integrals in the newly developed mixed ramp-Gaussian basis sets are presented, alongside a Fortran90 implementation of these algorithms, RAMPITUP. These new basis sets have significant potential to (1) give some speed-up (estimated at up to 20% for large molecules in fully optimised code) to general-purpose Hartree-Fock (HF) and density functional theory quantum chemistry calculations, replacing all-Gaussian basis sets, and (2) give very large speed-ups for calculations of core-dependent properties, such as electron density at the nucleus, NMR parameters, relativistic corrections, and total energies, replacing the current use of Slater basis functions or verymore » large specialised all-Gaussian basis sets for these purposes. This initial implementation already demonstrates roughly 10% speed-ups in HF/R-31G calculations compared to HF/6-31G calculations for large linear molecules, demonstrating the promise of this methodology, particularly for the second application. As well as the reduction in the total primitive number in R-31G compared to 6-31G, this timing advantage can be attributed to the significant reduction in the number of mathematically complex intermediate integrals after modelling each ramp-Gaussian basis-function-pair as a sum of ramps on a single atomic centre.« less

Diet and conservation implications of an invasive chameleon, Chamaeleo jacksonii (Squamata: Chamaeleonidae) in Hawaii

USGS Publications Warehouse

Kraus, Fred; Medeiros, Arthur; Preston, David; Jarnevich, Catherine S.; Rodda, Gordon H.

2012-01-01

We summarize information on current distribution of the invasive lizard Chamaeleo jacksonii and predict its potential distribution in the Hawaiian Islands. Potential distribution maps are based on climate models developed from known localities in its native range and its Hawaiian range. We also present results of analysis of stomach contents of a sample of 34 chameleons collected from native, predominantly dryland, forest on Maui. These data are the first summarizing prey range of this non-native species in an invaded native-forest setting. Potential distribution models predict that the species can occur throughout most of Hawaii from sea level to >2,100 m elevation. Important features of this data set are that approximately one-third of the diet of these lizards is native insects, and the lizards are consuming large numbers of arthropods each day. Prey sizes span virtually the entire gamut of native Hawaiian arthropod diversity, thereby placing a large number of native species at risk of predation. Our dietary results contrast with expectations for most iguanian lizards and support suggestions that chameleons comprise a third distinct foraging-mode category among saurians. The combination of expanding distribution, large potential range size, broad diet, high predation rates, and high densities of these chameleons imply that they may well become a serious threat to some of the Hawaiian fauna.

Attract them anyway: benefits of large, showy flowers in a highly autogamous, carnivorous plant species

PubMed Central

Salces-Castellano, A.; Paniw, M.; Casimiro-Soriguer, R.; Ojeda, F.

2016-01-01

Reproductive biology of carnivorous plants has largely been studied on species that rely on insects as pollinators and prey, creating potential conflicts. Autogamous pollination, although present in some carnivorous species, has received less attention. In angiosperms, autogamous self-fertilization is expected to lead to a reduction in flower size, thereby reducing resource allocation to structures that attract pollinators. A notable exception is the carnivorous pyrophyte Drosophyllum lusitanicum (Drosophyllaceae), which has been described as an autogamous selfing species but produces large, yellow flowers. Using a flower removal and a pollination experiment, we assessed, respectively, whether large flowers in this species may serve as an attracting device to prey insects or whether previously reported high selfing rates for this species in peripheral populations may be lower in more central, less isolated populations. We found no differences between flower-removed plants and intact, flowering plants in numbers of prey insects trapped. We also found no indication of reduced potential for autogamous reproduction, in terms of either seed set or seed size. However, our results showed significant increases in seed set of bagged, hand-pollinated flowers and unbagged flowers exposed to insect visitation compared with bagged, non-manipulated flowers that could only self-pollinate autonomously. Considering that the key life-history strategy of this pyrophytic species is to maintain a viable seed bank, any increase in seed set through insect pollinator activity would increase plant fitness. This in turn would explain the maintenance of large, conspicuous flowers in a highly autogamous, carnivorous plant. PMID:26977052

Racking Response of Reinforced Concrete Cut and Cover Tunnel

DOT National Transportation Integrated Search

2016-01-01

Currently, the knowledge base and quantitative data sets concerning cut and cover tunnel seismic response are scarce. In this report, a large-scale experimental program is conducted to assess: i) stiffness, capacity, and potential seismically-induced...

Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

PubMed Central

Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

2000-01-01

We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

Machine-assisted discovery of relationships in astronomy

NASA Astrophysics Data System (ADS)

Graham, Matthew J.; Djorgovski, S. G.; Mahabal, Ashish A.; Donalek, Ciro; Drake, Andrew J.

2013-05-01

High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of parameters is non-trivial. Similar problems in biological and geosciences have led to the development of systems which can explore large parameter spaces and identify potentially interesting sets of associations. In this paper, we describe the application of automated discovery systems of relationships to astronomical data sets, focusing on an evolutionary programming technique and an information-theory technique. We demonstrate their use with classical astronomical relationships - the Hertzsprung-Russell diagram and the Fundamental Plane of elliptical galaxies. We also show how they work with the issue of binary classification which is relevant to the next generation of large synoptic sky surveys, such as the Large Synoptic Survey Telescope (LSST). We find that comparable results to more familiar techniques, such as decision trees, are achievable. Finally, we consider the reality of the relationships discovered and how this can be used for feature selection and extraction.

Assessing Lebanon's wildfire potential in association with current and future climatic conditions

Treesearch

George H. Mitri; Mireille G. Jazi; David McWethy

2015-01-01

The increasing occurrence and extent of large-scale wildfires in the Mediterranean have been linked to extended periods of warm and dry weather. We set out to assess Lebanon's wildfire potential in association with current and future climatic conditions. The Keetch-Byram Drought Index (KBDI) was the primary climate variable used in our evaluation of climate/fire...

A Novel Technique for Endovascular Removal of Large Volume Right Atrial Tumor Thrombus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nickel, Barbara, E-mail: nickel.ba@gmail.com; McClure, Timothy, E-mail: tmcclure@gmail.com; Moriarty, John, E-mail: jmoriarty@mednet.ucla.edu

Venous thromboembolic disease is a significant cause of morbidity and mortality, particularly in the setting of large volume pulmonary embolism. Thrombolytic therapy has been shown to be a successful treatment modality; however, its use somewhat limited due to the risk of hemorrhage and potential for distal embolization in the setting of large mobile thrombi. In patients where either thrombolysis is contraindicated or unsuccessful, and conventional therapies prove inadequate, surgical thrombectomy may be considered. We present a case of percutaneous endovascular extraction of a large mobile mass extending from the inferior vena cava into the right atrium using the Angiovac device,more » a venovenous bypass system designed for high-volume aspiration of undesired endovascular material. Standard endovascular methods for removal of cancer-associated thrombus, such as catheter-directed lysis, maceration, and exclusion, may prove inadequate in the setting of underlying tumor thrombus. Where conventional endovascular methods either fail or are unsuitable, endovascular thrombectomy with the Angiovac device may be a useful and safe minimally invasive alternative to open resection.« less

Research directions in large scale systems and decentralized control

NASA Technical Reports Server (NTRS)

Tenney, R. R.

1980-01-01

Control theory provides a well established framework for dealing with automatic decision problems and a set of techniques for automatic decision making which exploit special structure, but it does not deal well with complexity. The potential exists for combining control theoretic and knowledge based concepts into a unified approach. The elements of control theory are diagrammed, including modern control and large scale systems.

Large Nc equivalence and baryons

NASA Astrophysics Data System (ADS)

Blake, Mike; Cherman, Aleksey

2012-09-01

In the large Nc limit, gauge theories with different gauge groups and matter content sometimes turn out to be “large Nc equivalent,” in the sense of having a set of coincident correlation functions. Large Nc equivalence has mainly been explored in the glueball and meson sectors. However, a recent proposal to dodge the fermion sign problem of QCD with a quark number chemical potential using large Nc equivalence motivates investigating the applicability of large Nc equivalence to correlation functions involving baryon operators. Here we present evidence that large Nc equivalence extends to the baryon sector, under the same type of symmetry realization assumptions as in the meson sector, by adapting the classic Witten analysis of large Nc baryons.

Simulation of fruit-set and trophic competition and optimization of yield advantages in six Capsicum cultivars using functional-structural plant modelling.

PubMed

Ma, Y T; Wubs, A M; Mathieu, A; Heuvelink, E; Zhu, J Y; Hu, B G; Cournède, P H; de Reffye, P

2011-04-01

Many indeterminate plants can have wide fluctuations in the pattern of fruit-set and harvest. Fruit-set in these types of plants depends largely on the balance between source (assimilate supply) and sink strength (assimilate demand) within the plant. This study aims to evaluate the ability of functional-structural plant models to simulate different fruit-set patterns among Capsicum cultivars through source-sink relationships. A greenhouse experiment of six Capsicum cultivars characterized with different fruit weight and fruit-set was conducted. Fruit-set patterns and potential fruit sink strength were determined through measurement. Source and sink strength of other organs were determined via the GREENLAB model, with a description of plant organ weight and dimensions according to plant topological structure established from the measured data as inputs. Parameter optimization was determined using a generalized least squares method for the entire growth cycle. Fruit sink strength differed among cultivars. Vegetative sink strength was generally lower for large-fruited cultivars than for small-fruited ones. The larger the size of the fruit, the larger variation there was in fruit-set and fruit yield. Large-fruited cultivars need a higher source-sink ratio for fruit-set, which means higher demand for assimilates. Temporal heterogeneity of fruit-set affected both number and yield of fruit. The simulation study showed that reducing heterogeneity of fruit-set was obtained by different approaches: for example, increasing source strength; decreasing vegetative sink strength, source-sink ratio for fruit-set and flower appearance rate; and harvesting individual fruits earlier before full ripeness. Simulation results showed that, when we increased source strength or decreased vegetative sink strength, fruit-set and fruit weight increased. However, no significant differences were found between large-fruited and small-fruited groups of cultivars regarding the effects of source and vegetative sink strength on fruit-set and fruit weight. When the source-sink ratio at fruit-set decreased, the number of fruit retained on the plant increased competition for assimilates with vegetative organs. Therefore, total plant and vegetative dry weights decreased, especially for large-fruited cultivars. Optimization study showed that temporal heterogeneity of fruit-set and ripening was predicted to be reduced when fruits were harvested earlier. Furthermore, there was a 20 % increase in the number of extra fruit set.

Fitting a Point Cloud to a 3d Polyhedral Surface

NASA Astrophysics Data System (ADS)

Popov, E. V.; Rotkov, S. I.

2017-05-01

The ability to measure parameters of large-scale objects in a contactless fashion has a tremendous potential in a number of industrial applications. However, this problem is usually associated with an ambiguous task to compare two data sets specified in two different co-ordinate systems. This paper deals with the study of fitting a set of unorganized points to a polyhedral surface. The developed approach uses Principal Component Analysis (PCA) and Stretched grid method (SGM) to substitute a non-linear problem solution with several linear steps. The squared distance (SD) is a general criterion to control the process of convergence of a set of points to a target surface. The described numerical experiment concerns the remote measurement of a large-scale aerial in the form of a frame with a parabolic shape. The experiment shows that the fitting process of a point cloud to a target surface converges in several linear steps. The method is applicable to the geometry remote measurement of large-scale objects in a contactless fashion.

SNAP: Automated Generation of High-Accuracy Interatomic Potentials using Quantum Data

NASA Astrophysics Data System (ADS)

Thompson, Aidan; Wood, Mitchell; Phillpot, Simon

Molecular dynamics simulation is a powerful computational method for bridging between macroscopic continuum models and quantum models treating a few hundred atoms, but it is limited by the accuracy of the interatomic potential. Sound physical and chemical understanding have led to good potentials for certain systems, but it is difficult to extend them to new materials and properties. The solution is obvious but challenging: develop more complex potentials that reproduce large quantum datasets. The growing availability of large data sets has made it possible to use automated machine-learning approaches for interatomic potential development. In the SNAP approach, the interatomic potential depends on a very general set of atomic neighborhood descriptors, based on the bispectrum components of the density projected onto the surface of the unit 3-sphere. Previously, this approach was demonstrated for tantalum, reproducing the screw dislocation Peierls barrier. In this talk, it will be shown that the SNAP method is capable of reproducing a wide range of energy landscapes relevant to diverse material science applications: i) point defects in indium phosphide, ii) stability of tungsten surfaces at high temperatures, and iii) formation of intrinsic defects in uranium. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corp., for the U.S. Dept. of Energys National Nuclear Security Admin. under contract DE-AC04-94AL85000.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

PubMed

Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

2017-06-30

Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

PubMed Central

2017-01-01

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113

Conservation economics. Response to Comment on "Using ecological thresholds to evaluate the costs and benefits of set-asides in a biodiversity hotspot".

PubMed

Banks-Leite, Cristina; Pardini, Renata; Tambosi, Leandro R; Pearse, William D; Bueno, Adriana A; Bruscagin, Roberta T; Condez, Thais H; Dixo, Marianna; Igari, Alexandre T; Martensen, Alexandre C; Metzger, Jean Paul

2015-02-13

Finney claims that we did not include transaction costs while assessing the economic costs of a set-aside program in Brazil and that accounting for them could potentially render large payments for environmental services (PES) projects unfeasible. We agree with the need for a better understanding of transaction costs but provide evidence that they do not alter the feasibility of the set-aside scheme we proposed. Copyright © 2015, American Association for the Advancement of Science.

Low Voltage Electrolytic Capacitor Pulse Forming Inductive Network for Electric Weapons

DTIC Science & Technology

2006-06-01

reliable high- current, high-energy pulses of many megawatts. Pulsed alternators potentially have the same maintenance issues as other motor ...high-energy pulses of many megawatts. Pulsed alternators potentially have the same maintenance issues as other motor -generator sets, so a solid...Rotating Flywheel) Pulse Forming Network Compensated Pulsed Alternators, or Compulsators as they are called, are essentially large motor -generator

Theoretical study on the dissociation energies, ionization potentials and electron affinities of three perfluoroalkyl iodides

NASA Astrophysics Data System (ADS)

Cheng, Li; Shen, Zuochun; Lu, Jianye; Gao, Huide; Lü, Zhiwei

2005-11-01

Dissociation energies, ionization potentials and electron affinities of three perfluoroalkyl iodides, CF 3I, C 2F 5I, and i-C 3F 7I are calculated accurately with B3LYP, MP n ( n = 2-4), QCISD, QCISD(T), CCSD, and CCSD(T) methods. Calculations are performed by using large-core correlation-consistent pseudopotential basis set (SDB-aug-cc-pVTZ) for iodine atom. In all energy calculations, the zero point vibration energy is corrected. And the basis set superposition error is corrected by counterpoise method in the calculation of dissociation energy. Theoretical results are compared with the experimental values.

Big Data in the Industry - Overview of Selected Issues

NASA Astrophysics Data System (ADS)

Gierej, Sylwia

2017-12-01

This article reviews selected issues related to the use of Big Data in the industry. The aim is to define the potential scope and forms of using large data sets in manufacturing companies. By systematically reviewing scientific and professional literature, selected issues related to the use of mass data analytics in production were analyzed. A definition of Big Data was presented, detailing its main attributes. The importance of mass data processing technology in the development of Industry 4.0 concept has been highlighted. Subsequently, attention was paid to issues such as production process optimization, decision making and mass production individualisation, and indicated the potential for large volumes of data. As a result, conclusions were drawn regarding the potential of using Big Data in the industry.

Threshold Theory Tested in an Organizational Setting: The Relation between Perceived Innovativeness and Intelligence in a Large Sample of Leaders

ERIC Educational Resources Information Center

Christensen, Bo T.; Hartmann, Peter V. W.; Rasmussen, Thomas Hedegaard

2017-01-01

A large sample of leaders (N = 4257) was used to test the link between leader innovativeness and intelligence. The threshold theory of the link between creativity and intelligence assumes that below a certain IQ level (approximately IQ 120), there is some correlation between IQ and creative potential, but above this cutoff point, there is no…

A Psychoevolutionary Approach to Identifying Preferred Nature Scenes With Potential to Provide Restoration From Stress.

PubMed

Thake, Carol L; Bambling, Matthew; Edirippulige, Sisira; Marx, Eric

2017-10-01

Research supports therapeutic use of nature scenes in healthcare settings, particularly to reduce stress. However, limited literature is available to provide a cohesive guide for selecting scenes that may provide optimal therapeutic effect. This study produced and tested a replicable process for selecting nature scenes with therapeutic potential. Psychoevolutionary theory informed the construction of the Importance for Survival Scale (IFSS), and its usefulness for identifying scenes that people generally prefer to view and that hold potential to reduce stress was tested. Relationships between Importance for Survival (IFS), preference, and restoration were tested. General community participants ( N = 20 males, 20 females; M age = 48 years) Q-sorted sets of landscape photographs (preranked by the researcher in terms of IFS using the IFSS) from most to least preferred, and then completed the Short-Version Revised Restoration Scale in response to viewing a selection of the scenes. Results showed significant positive relationships between IFS and each of scene preference (large effect), and restoration potential (medium effect), as well as between scene preference and restoration potential across the levels of IFS (medium effect), and for individual participants and scenes (large effect). IFS was supported as a framework for identifying nature scenes that people will generally prefer to view and that hold potential for restoration from emotional distress; however, greater therapeutic potential may be expected when people can choose which of the scenes they would prefer to view. Evidence for the effectiveness of the IFSS was produced.

Problems in merging Earth sensing satellite data sets

NASA Technical Reports Server (NTRS)

Smith, Paul H.; Goldberg, Michael J.

1987-01-01

Satellite remote sensing systems provide a tremendous source of data flow to the Earth science community. These systems provide scientists with data of types and on a scale previously unattainable. Looking forward to the capabilities of Space Station and the Earth Observing System (EOS), the full realization of the potential of satellite remote sensing will be handicapped by inadequate information systems. There is a growing emphasis in Earth science research to ask questions which are multidisciplinary in nature and global in scale. Many of these research projects emphasize the interactions of the land surface, the atmosphere, and the oceans through various physical mechanisms. Conducting this research requires large and complex data sets and teams of multidisciplinary scientists, often working at remote locations. A review of the problems of merging these large volumes of data into spatially referenced and manageable data sets is presented.

Capturing haplotypes in germplasm core collections

USDA-ARS?s Scientific Manuscript database

Genomewide data sets of single nucleotide polymorphisms (SNPs) offer great potential to improve ex situ conservation. Two factors impede their use for producing core collections. First, due to the large number of SNPs, the assembly of collections that maximize diversity may be intractable using ex...

The prevalence of terraced treescapes in analyses of phylogenetic data sets.

PubMed

Dobrin, Barbara H; Zwickl, Derrick J; Sanderson, Michael J

2018-04-04

The pattern of data availability in a phylogenetic data set may lead to the formation of terraces, collections of equally optimal trees. Terraces can arise in tree space if trees are scored with parsimony or with partitioned, edge-unlinked maximum likelihood. Theory predicts that terraces can be large, but their prevalence in contemporary data sets has never been surveyed. We selected 26 data sets and phylogenetic trees reported in recent literature and investigated the terraces to which the trees would belong, under a common set of inference assumptions. We examined terrace size as a function of the sampling properties of the data sets, including taxon coverage density (the proportion of taxon-by-gene positions with any data present) and a measure of gene sampling "sufficiency". We evaluated each data set in relation to the theoretical minimum gene sampling depth needed to reduce terrace size to a single tree, and explored the impact of the terraces found in replicate trees in bootstrap methods. Terraces were identified in nearly all data sets with taxon coverage densities < 0.90. They were not found, however, in high-coverage-density (i.e., ≥ 0.94) transcriptomic and genomic data sets. The terraces could be very large, and size varied inversely with taxon coverage density and with gene sampling sufficiency. Few data sets achieved a theoretical minimum gene sampling depth needed to reduce terrace size to a single tree. Terraces found during bootstrap resampling reduced overall support. If certain inference assumptions apply, trees estimated from empirical data sets often belong to large terraces of equally optimal trees. Terrace size correlates to data set sampling properties. Data sets seldom include enough genes to reduce terrace size to one tree. When bootstrap replicate trees lie on a terrace, statistical support for phylogenetic hypotheses may be reduced. Although some of the published analyses surveyed were conducted with edge-linked inference models (which do not induce terraces), unlinked models have been used and advocated. The present study describes the potential impact of that inference assumption on phylogenetic inference in the context of the kinds of multigene data sets now widely assembled for large-scale tree construction.

Assessing the 5S ribosomal RNA heterogeneity in Arabidopsis thaliana using short RNA next generation sequencing data.

PubMed

Szymanski, Maciej; Karlowski, Wojciech M

2016-01-01

In eukaryotes, ribosomal 5S rRNAs are products of multigene families organized within clusters of tandemly repeated units. Accumulation of genomic data obtained from a variety of organisms demonstrated that the potential 5S rRNA coding sequences show a large number of variants, often incompatible with folding into a correct secondary structure. Here, we present results of an analysis of a large set of short RNA sequences generated by the next generation sequencing techniques, to address the problem of heterogeneity of the 5S rRNA transcripts in Arabidopsis and identification of potentially functional rRNA-derived fragments.

Lithium enrichment in intracontinental rhyolite magmas leads to Li deposits in caldera basins.

PubMed

Benson, Thomas R; Coble, Matthew A; Rytuba, James J; Mahood, Gail A

2017-08-16

The omnipresence of lithium-ion batteries in mobile electronics, and hybrid and electric vehicles necessitates discovery of new lithium resources to meet rising demand and to diversify the global lithium supply chain. Here we demonstrate that lake sediments preserved within intracontinental rhyolitic calderas formed on eruption and weathering of lithium-enriched magmas have the potential to host large lithium clay deposits. We compare lithium concentrations of magmas formed in a variety of tectonic settings using in situ trace-element measurements of quartz-hosted melt inclusions to demonstrate that moderate to extreme lithium enrichment occurs in magmas that incorporate felsic continental crust. Cenozoic calderas in western North America and in other intracontinental settings that generated such magmas are promising new targets for lithium exploration because lithium leached from the eruptive products by meteoric and hydrothermal fluids becomes concentrated in clays within caldera lake sediments to potentially economically extractable levels.Lithium is increasingly being utilized for modern technology in the form of lithium-ion batteries. Here, using in situ measurements of quartz-hosted melt inclusions, the authors demonstrate that preserved lake sediments within rhyolitic calderas have the potential to host large lithium-rich clay deposits.

Brake mechanics, asbestos, and disease risk.

PubMed

Huncharek, M

1990-09-01

Health risks posed by inhalable asbestos fibers are known to exist in a variety of industrial and nonindustrial settings. Although early studies described an increased risk of asbestosis, lung cancer, and mesothelioma in asbestos-industry workers, subsequent research revealed the existence of a potential asbestos-related health hazard in nonasbestos industries such as the textile and railroad industries. Brake mechanics and garage workers constitute a large work force with potential exposures to levels of asbestos capable of producing disease. Unfortunately, the health risk faced by these workers has received little attention. This article briefly discusses currently available information on the asbestos health risks of workers in this setting, and highlights the need for further investigations of this occupational group.

Estimating the Tradeoff Between Risk Protection and Moral Hazard with a Nonlinear Budget Set Model of Health Insurance*

PubMed Central

Kowalski, Amanda E.

2015-01-01

Insurance induces a tradeoff between the welfare gains from risk protection and the welfare losses from moral hazard. Empirical work traditionally estimates each side of the tradeoff separately, potentially yielding mutually inconsistent results. I develop a nonlinear budget set model of health insurance that allows for both simultaneously. Nonlinearities in the budget set arise from deductibles, coinsurance rates, and stoplosses that alter moral hazard as well as risk protection. I illustrate the properties of my model by estimating it using data on employer sponsored health insurance from a large firm. PMID:26664035

Tool for Rapid Analysis of Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.

2011-01-01

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very di cult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The Tool for Rapid Analysis of Monte Carlo simulations (TRAM) has been used in recent design and analysis work for the Orion vehicle, greatly decreasing the time it takes to evaluate performance requirements. A previous version of this tool was developed to automatically identify driving design variables in Monte Carlo data sets. This paper describes a new, parallel version, of TRAM implemented on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

How to derive biological information from the value of the normalization constant in allometric equations.

PubMed

Kaitaniemi, Pekka

2008-04-09

Allometric equations are widely used in many branches of biological science. The potential information content of the normalization constant b in allometric equations of the form Y = bX(a) has, however, remained largely neglected. To demonstrate the potential for utilizing this information, I generated a large number of artificial datasets that resembled those that are frequently encountered in biological studies, i.e., relatively small samples including measurement error or uncontrolled variation. The value of X was allowed to vary randomly within the limits describing different data ranges, and a was set to a fixed theoretical value. The constant b was set to a range of values describing the effect of a continuous environmental variable. In addition, a normally distributed random error was added to the values of both X and Y. Two different approaches were then used to model the data. The traditional approach estimated both a and b using a regression model, whereas an alternative approach set the exponent a at its theoretical value and only estimated the value of b. Both approaches produced virtually the same model fit with less than 0.3% difference in the coefficient of determination. Only the alternative approach was able to precisely reproduce the effect of the environmental variable, which was largely lost among noise variation when using the traditional approach. The results show how the value of b can be used as a source of valuable biological information if an appropriate regression model is selected.

Enzyme/non-enzyme discrimination and prediction of enzyme active site location using charge-based methods.

PubMed

Bate, Paul; Warwicker, Jim

2004-07-02

Calculations of charge interactions complement analysis of a characterised active site, rationalising pH-dependence of activity and transition state stabilisation. Prediction of active site location through large DeltapK(a)s or electrostatic strain is relevant for structural genomics. We report a study of ionisable groups in a set of 20 enzymes, finding that false positives obscure predictive potential. In a larger set of 156 enzymes, peaks in solvent-space electrostatic properties are calculated. Both electric field and potential match well to active site location. The best correlation is found with electrostatic potential calculated from uniform charge density over enzyme volume, rather than from assignment of a standard atom-specific charge set. Studying a shell around each molecule, for 77% of enzymes the potential peak is within that 5% of the shell closest to the active site centre, and 86% within 10%. Active site identification by largest cleft, also with projection onto a shell, gives 58% of enzymes for which the centre of the largest cleft lies within 5% of the active site, and 70% within 10%. Dielectric boundary conditions emphasise clefts in the uniform charge density method, which is suited to recognition of binding pockets embedded within larger clefts. The variation of peak potential with distance from active site, and comparison between enzyme and non-enzyme sets, gives an optimal threshold distinguishing enzyme from non-enzyme. We find that 87% of the enzyme set exceeds the threshold as compared to 29% of the non-enzyme set. Enzyme/non-enzyme homologues, "structural genomics" annotated proteins and catalytic/non-catalytic RNAs are studied in this context.

The U.S. Army in Asia, 2030-2040

DTIC Science & Technology

2014-01-01

in general. However, to be fully effective in a war with China, AirSea Battle would likely require early (if not pre- 5 There is a potential downside...to establish a regional sphere of influence, potentially espousing ideologies that are in conflict with core values of the international system ...China may wish to deploy large-scale ground forces punitively, over a set of limited objectives, or differentiating Between a “ Systemic Continuity

Strongly nonlinear composite dielectrics: A perturbation method for finding the potential field and bulk effective properties

NASA Astrophysics Data System (ADS)

Blumenfeld, Raphael; Bergman, David J.

1991-10-01

A class of strongly nonlinear composite dielectrics is studied. We develop a general method to reduce the scalar-potential-field problem to the solution of a set of linear Poisson-type equations in rescaled coordinates. The method is applicable for a large variety of nonlinear materials. For a power-law relation between the displacement and the electric fields, it is used to solve explicitly for the value of the bulk effective dielectric constant ɛe to second order in the fluctuations of its local value. A simlar procedure for the vector potential, whose curl is the displacement field, yields a quantity analogous to the inverse dielectric constant in linear dielectrics. The bulk effective dielectric constant is given by a set of linear integral expressions in the rescaled coordinates and exact bounds for it are derived.

Preliminary Results from the Flight of the Solar Array Module Plasma Interactions Experiment (SAMPIE)

NASA Technical Reports Server (NTRS)

Ferguson, Dale C.; Hillard, G. Barry

1994-01-01

SAMPIE, the Solar Array Module Plasma Interactions Experiment, flew in the Space Shuttle Columbia payload bay as part of the OAST-2 mission on STS-62, March, 1994. SAMPIE biased samples of solar arrays and space power materials to varying potentials with respect to the surrounding space plasma, and recorded the plasma currents collected and the arcs which occurred, along with a set of plasma diagnostics data. A large set of high quality data was obtained on the behavior of solar arrays and space power materials in the space environment. This paper is the first report on the data SAMPIE telemetered to the ground during the mission. It will be seen that the flight data promise to help determine arcing thresholds, snapover potentials and floating potentials for arrays and spacecraft in LEO.

A distributed parallel storage architecture and its potential application within EOSDIS

NASA Technical Reports Server (NTRS)

Johnston, William E.; Tierney, Brian; Feuquay, Jay; Butzer, Tony

1994-01-01

We describe the architecture, implementation, use of a scalable, high performance, distributed-parallel data storage system developed in the ARPA funded MAGIC gigabit testbed. A collection of wide area distributed disk servers operate in parallel to provide logical block level access to large data sets. Operated primarily as a network-based cache, the architecture supports cooperation among independently owned resources to provide fast, large-scale, on-demand storage to support data handling, simulation, and computation.

Coupled modeling and simulation of electro-elastic materials at large strains

NASA Astrophysics Data System (ADS)

Possart, Gunnar; Steinmann, Paul; Vu, Duc-Khoi

2006-03-01

In the recent years various novel materials have been developed that respond to the application of electrical loading by large strains. An example is the class of so-called electro-active polymers (EAP). Certainly these materials are technologically very interesting, e.g. for the design of actuators in mechatronics or in the area of artificial tissues. This work focuses on the phenomenological modeling of such materials within the setting of continuum-electro-dynamics specialized to the case of electro-hyperelastostatics and the corresponding computational setting. Thereby a highly nonlinear coupled problem for the deformation and the electric potential has to be considered. The finite element method is applied to solve the underlying equations numerically and some exemplary applications are presented.

Soil temperature variability in complex terrain measured using fiber-optic distributed temperature sensing

USDA-ARS?s Scientific Manuscript database

Soil temperature (Ts) exerts critical controls on hydrologic and biogeochemical processes but magnitude and nature of Ts variability in a landscape setting are rarely documented. Fiber optic distributed temperature sensing systems (FO-DTS) potentially measure Ts at high density over a large extent. ...

An Aggregate IRT Procedure for Exploratory Factor Analysis

ERIC Educational Resources Information Center

Camilli, Gregory; Fox, Jean-Paul

2015-01-01

An aggregation strategy is proposed to potentially address practical limitation related to computing resources for two-level multidimensional item response theory (MIRT) models with large data sets. The aggregate model is derived by integration of the normal ogive model, and an adaptation of the stochastic approximation expectation maximization…

Aquatic Ecosystems, Water Quality, and Global Change: Challenges of conducting Multi-Stressor Vulnerability Assessments (External Review Draft)

EPA Science Inventory

This draft report investigates the issues and challenges associated with identifying, calculating, and mapping indicators of the relative vulnerability of water quality and aquatic ecosystems, across the United States, to the potential impacts of global change. Using a large set...

Creating Social Presence in Online Environments

ERIC Educational Resources Information Center

Aragon, Steven R.

2003-01-01

During the last decade, the Internet has significantly changed the way learning is delivered and facilitated in both educational and noneducational settings. Advocates of Internet-based instruction are largely positive and optimistic about its potential. Before it can be fully accepted by the mainstream public and educational community, however,…

Leadership and priority setting: the perspective of hospital CEOs.

PubMed

Reeleder, David; Goel, Vivek; Singer, Peter A; Martin, Douglas K

2006-11-01

The role of leadership in health care priority setting remains largely unexplored. While the management leadership literature has grown rapidly, the growing literature on priority setting in health care has looked in other directions to improve priority setting practices--to health economics and ethical approaches. Consequently, potential for improvement in hospital priority setting practices may be overlooked. A qualitative study involving interviews with 46 Ontario hospital CEOs was done to describe the role of leadership in priority setting through the perspective of hospital leaders. For the first time, we report a framework of leadership domains including vision, alignment, relationships, values and process to facilitate priority setting practices in health services' organizations. We believe this fledgling framework forms the basis for the sharing of good leadership practices for health reform. It also provides a leadership guide for decision makers to improve the quality of their leadership, and in so doing, we believe, the fairness of their priority setting.

Pitfalls of insulin pump clocks: technical glitches that may potentially affect medical care in patients with diabetes.

PubMed

Aldasouqi, Saleh A; Reed, Amy J

2014-11-01

The objective was to raise awareness about the importance of ensuring that insulin pumps internal clocks are set up correctly at all times. This is a very important safety issue because all commercially available insulin pumps are not GPS-enabled (though this is controversial), nor equipped with automatically adjusting internal clocks. Special attention is paid to how basal and bolus dose errors can be introduced by daylight savings time changes, travel across time zones, and am-pm clock errors. Correct setting of insulin pump internal clock is crucial for appropriate insulin delivery. A comprehensive literature review is provided, as are illustrative cases. Incorrect setting can potentially result in incorrect insulin delivery, with potential harmful consequences, if too much or too little insulin is delivered. Daylight saving time changes may not significantly affect basal insulin delivery, given the triviality of the time difference. However, bolus insulin doses can be dramatically affected. Such problems may occur when pump wearers have large variations in their insulin to carb ratio, especially if they forget to change their pump clock in the spring. More worrisome than daylight saving time change is the am-pm clock setting. If this setting is set up incorrectly, both basal rates and bolus doses will be affected. Appropriate insulin delivery through insulin pumps requires correct correlation between dose settings and internal clock time settings. Because insulin pumps are not GPS-enabled or automatically time-adjusting, extra caution should be practiced by patients to ensure correct time settings at all times. Clinicians and diabetes educators should verify the date/time of insulin pumps during patients' visits, and should remind their patients to always verify these settings. © 2014 Diabetes Technology Society.

Heavier alkali-metal monosulfides (KS, RbS, CsS, and FrS) and their cations.

PubMed

Lee, Edmond P F; Wright, Timothy G

2005-10-08

The heavier alkali-metal monosulfides (KS, RbS, CsS, and FrS) have been studied by high-level ab initio calculations. The RCCSD(T) method has been employed, combined with large flexible valence basis sets. All-electron basis sets are used for potassium and sulfur, with effective core potentials being used for the other metals, describing the core electrons. Potential-energy curves are calculated for the lowest two neutral and cationic states: all neutral monosulfide species have a (2)Pi ground state, in contrast with the alkali-metal monoxide species, which undergo a change in the electronic ground state from (2)Pi to (2)Sigma(+) as the group is descended. In the cases of KS, RbS, and CsS, spin-orbit curves are also calculated. We also calculate potential-energy curves for the lowest (3)Sigma(-) and (3)Pi states of the cations. From the potential-energy curves, spectroscopic constants are derived, and for KS the spectroscopic results are compared to experimental spectroscopic values. Ionization energies, dissociation energies, and heats of formation are also calculated; for KS, we explore the effects of relativity and basis set extrapolation on these values.

Addressing Methodological Challenges in Large Communication Datasets: Collecting and Coding Longitudinal Interactions in Home Hospice Cancer Care

PubMed Central

Reblin, Maija; Clayton, Margaret F; John, Kevin K; Ellington, Lee

2015-01-01

In this paper, we present strategies for collecting and coding a large longitudinal communication dataset collected across multiple sites, consisting of over 2000 hours of digital audio recordings from approximately 300 families. We describe our methods within the context of implementing a large-scale study of communication during cancer home hospice nurse visits, but this procedure could be adapted to communication datasets across a wide variety of settings. This research is the first study designed to capture home hospice nurse-caregiver communication, a highly understudied location and type of communication event. We present a detailed example protocol encompassing data collection in the home environment, large-scale, multi-site secure data management, the development of theoretically-based communication coding, and strategies for preventing coder drift and ensuring reliability of analyses. Although each of these challenges have the potential to undermine the utility of the data, reliability between coders is often the only issue consistently reported and addressed in the literature. Overall, our approach demonstrates rigor and provides a “how-to” example for managing large, digitally-recorded data sets from collection through analysis. These strategies can inform other large-scale health communication research. PMID:26580414

Large-scale dynamics of the stratosphere and mesosphere during the MAP/WINE campaign winter 1983 to 1984 in comparison with other winters

NASA Technical Reports Server (NTRS)

Petzoldt, K.

1989-01-01

For the MAP/WINE winter temperature and wind measurements of rockets were combined with SSU radiances (Stratospheric Sounder Unit onboard the NOAA satellites) and stratopause heights from the Solar Mesosphere Explorer (SME) to get a retrieved data set including all available information. By means of this data set a hemispheric geopotential height, temperature and geostrophic wind fields eddy transports for wave mean flow interaction and potential vorticity for the interpretation of nonlinear wave breaking could be computed. Wave reflection at critical lines was investigated with respect of stratospheric warmings. The meridional gradient of the potential vorticity and focusing of wave activity is compared with derived data from satellite observations during other winters.

Aeromagnetic Survey in Afghanistan: A Website for Distribution of Data

USGS Publications Warehouse

Abraham, Jared D.; Anderson, Eric D.; Drenth, Benjamin J.; Finn, Carol A.; Kucks, Robert P.; Lindsay, Charles R.; Phillips, Jeffrey D.; Sweeney, Ronald E.

2007-01-01

Afghanistan's geologic setting indicates significant natural resource potential While important mineral deposits and petroleum resources have been identified, much of the country's potential remains unknown. Airborne geophysical surveys are a well accepted and cost effective method for obtaining information of the geological setting of an area without the need to be physically located on the ground. Due to the security situation and the large areas of the country of Afghanistan that has not been covered with geophysical exploration methods a regional airborne geophysical survey was proposed. Acting upon the request of the Islamic Republic of Afghanistan Ministry of Mines, the U.S. Geological Survey contracted with the Naval Research Laboratory to jointly conduct an airborne geophysical and remote sensing survey of Afghanistan.

Applicability of effective fragment potential version 2 - Molecular dynamics (EFP2-MD) simulations for predicting excess properties of mixed solvents

NASA Astrophysics Data System (ADS)

Kuroki, Nahoko; Mori, Hirotoshi

2018-02-01

Effective fragment potential version 2 - molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations were applied to water-methanol binary mixture. Comparing EFP2s defined with (aug-)cc-pVXZ (X = D,T) basis sets, it was found that large sets are necessary to generate sufficiently accurate EFP2 for predicting mixture properties. It was shown that EFP2-MD could predict the excess molar volume. Since the computational cost of EFP2-MD are far less than ab initio MD, the results presented herein demonstrate that EFP2-MD is promising for predicting physicochemical properties of novel mixed solvents.

Seismology: tectonic strain in plate interiors?

PubMed

Calais, E; Mattioli, G; DeMets, C; Nocquet, J-M; Stein, S; Newman, A; Rydelek, P

2005-12-15

It is not fully understood how or why the inner areas of tectonic plates deform, leading to large, although infrequent, earthquakes. Smalley et al. offer a potential breakthrough by suggesting that surface deformation in the central United States accumulates at rates comparable to those across plate boundaries. However, we find no statistically significant deformation in three independent analyses of the data set used by Smalley et al., and conclude therefore that only the upper bounds of magnitude and repeat time for large earthquakes can be inferred at present.

A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets.

PubMed

Carrig, Madeline M; Manrique-Vallier, Daniel; Ranby, Krista W; Reiter, Jerome P; Hoyle, Rick H

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches.

A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

PubMed Central

Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437

SymDex: increasing the efficiency of chemical fingerprint similarity searches for comparing large chemical libraries by using query set indexing.

PubMed

Tai, David; Fang, Jianwen

2012-08-27

The large sizes of today's chemical databases require efficient algorithms to perform similarity searches. It can be very time consuming to compare two large chemical databases. This paper seeks to build upon existing research efforts by describing a novel strategy for accelerating existing search algorithms for comparing large chemical collections. The quest for efficiency has focused on developing better indexing algorithms by creating heuristics for searching individual chemical against a chemical library by detecting and eliminating needless similarity calculations. For comparing two chemical collections, these algorithms simply execute searches for each chemical in the query set sequentially. The strategy presented in this paper achieves a speedup upon these algorithms by indexing the set of all query chemicals so redundant calculations that arise in the case of sequential searches are eliminated. We implement this novel algorithm by developing a similarity search program called Symmetric inDexing or SymDex. SymDex shows over a 232% maximum speedup compared to the state-of-the-art single query search algorithm over real data for various fingerprint lengths. Considerable speedup is even seen for batch searches where query set sizes are relatively small compared to typical database sizes. To the best of our knowledge, SymDex is the first search algorithm designed specifically for comparing chemical libraries. It can be adapted to most, if not all, existing indexing algorithms and shows potential for accelerating future similarity search algorithms for comparing chemical databases.

Mapping Topographic Structure in White Matter Pathways with Level Set Trees

PubMed Central

Kent, Brian P.; Rinaldo, Alessandro; Yeh, Fang-Cheng; Verstynen, Timothy

2014-01-01

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees–which provide a concise representation of the hierarchical mode structure of probability density functions–offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30), we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber pathways and an efficient segmentation of the pathways that had empirical accuracy comparable to standard nonparametric clustering techniques. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output. PMID:24714673

Joint Analysis of the Full AzTEC Sub-Millimeter Galaxy Data Set

NASA Astrophysics Data System (ADS)

Wilson, Grant; Ade, P.; Aretxaga, I.; Austermann, J.; Bock, J.; Hughes, D.; Kang, Y.; Kim, S.; Lowenthal, J.; Mauskopf, P.; Perera, T.; Scott, K.; Yun, M.

2006-12-01

Using the new AzTEC millimeter-wave camera on the James Clerk Maxwell Telescope (JCMT) in winter 2005/06, we conducted several surveys of the submm galaxy (SMG) population. The AzTEC 1.1 millimeter surveys include both blank-fields (no significant bias or foreground contamination) and regions of known over-densities, and are both large (100-1000 sq. arcmin.) and sensitive ( 1 mJy rms). The unique power of the AzTEC data set lies not only in the size and depth of the individual fields, but in the combined surveyed area that totals over 1 square degree. Hundreds of new sub-millimeter sources have been detected. A joint analysis of all AzTEC surveys will provide important new constraints on many characteristics of the SMG population, including number counts, clustering, and variance. In particular, the large area of the full AzTEC data set provides the first significant measurement of the brightest and most rare of the SMG population. Herein we present the initial combined results and explore the future potential of a complete joint analysis of the full AzTEC SMG data set.

Preliminary results from the flight of the Solar Array Module Plasma Interactions Experiment (SAMPIE)

NASA Technical Reports Server (NTRS)

Ferguson, Dale C.; Hillard, G. Barry

1994-01-01

SAMPIE, the Solar Array Module Plasma Interactions Experiment, flew in the Space Shuttle Columbia payload bay as part of the Office of Aeronautics and Space Technology-2 (OAST-2) mission on STS-62, March, 1994. SAMPIE biased samples of solar arrays and space power materials to varying potentials with respect to the surrounding space plasma, and recorded the plasma currents collected and the arcs which occurred, along with a set of plasma diagnostics data. A large set of high quality data was obtained on the behavior of solar arrays and space power materials in the space environment. This paper is the first report on the data SAMPIE telemetered to the ground during the mission. It will be seen that the flight data promise to help determine arcing thresholds, snapover potentials, and floating potentials for arrays and spacecraft in LEO.

A study of System Interface Sets (SIS) for the host, target and integration environments of the Space Station Program (SSP)

NASA Technical Reports Server (NTRS)

Mckay, Charles; Auty, David; Rogers, Kathy

1987-01-01

System interface sets (SIS) for large, complex, non-stop, distributed systems are examined. The SIS of the Space Station Program (SSP) was selected as the focus of this study because an appropriate virtual interface specification of the SIS is believed to have the most potential to free the project from four life cycle tyrannies which are rooted in a dependance on either a proprietary or particular instance of: operating systems, data management systems, communications systems, and instruction set architectures. The static perspective of the common Ada programming support environment interface set (CAIS) and the portable common execution environment (PCEE) activities are discussed. Also, the dynamic perspective of the PCEE is addressed.

Reported Influence of Evaluation Data on Decision Makers' Actions: An Empirical Examination

ERIC Educational Resources Information Center

Christie, Christina A.

2007-01-01

Using a set of scenarios derived from actual evaluation studies, this simulation study examines the reported influence of evaluation information on decision makers' potential actions. Each scenario described a context where one of three types of evaluation information (large-scale study data, case study data, or anecdotal accounts) is presented…

Early Childhood Education: Pathways to Better Health. Preschool Policy Brief Issue 25

ERIC Educational Resources Information Center

Friedman-Krauss, Allison; Barnett, W. Steven

2013-01-01

The potential health benefits of early childhood education programs are quite large, especially for children living in poverty. In this report, authors Allison Friedman-Krauss and Steve Barnett set out the evidence regarding the short and long term health benefits to children from early childhood education programs, identify the features of…

Abel inversion using fast Fourier transforms.

PubMed

Kalal, M; Nugent, K A

1988-05-15

A fast Fourier transform based Abel inversion technique is proposed. The method is faster than previously used techniques, potentially very accurate (even for a relatively small number of points), and capable of handling large data sets. The technique is discussed in the context of its use with 2-D digital interferogram analysis algorithms. Several examples are given.

The Measurement of Stress among College Students.

ERIC Educational Resources Information Center

Hensley, Wayne E.

This paper reports on a study to develop a scale of stress measurement and its use with undergraduate students (N=269) at a large land grant mid-Atlantic university. Students, within the classroom setting, were given a questionnaire containing 52 potentially stressful hypothetical situations and were asked to indicate the degree of stress they…

Generic cosmic-censorship violation in anti-de Sitter space.

PubMed

Hertog, Thomas; Horowitz, Gary T; Maeda, Kengo

2004-04-02

We consider (four-dimensional) gravity coupled to a scalar field with potential V(phi). The potential satisfies the positive energy theorem for solutions that asymptotically tend to a negative local minimum. We show that for a large class of such potentials, there is an open set of smooth initial data that evolve to naked singularities. Hence cosmic censorship does not hold for certain reasonable matter theories in asymptotically anti-de Sitter spacetimes. The asymptotically flat case is more subtle. We suspect that potentials with a local Minkowski minimum may similarly lead to violations of cosmic censorship in asymptotically flat spacetimes, but we do not have definite results.

Clinical applications of textural analysis in non-small cell lung cancer.

PubMed

Phillips, Iain; Ajaz, Mazhar; Ezhil, Veni; Prakash, Vineet; Alobaidli, Sheaka; McQuaid, Sarah J; South, Christopher; Scuffham, James; Nisbet, Andrew; Evans, Philip

2018-01-01

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed "radiomics" and includes semantic and agnostic approaches. Textural analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue subtypes of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarize the current published data and understand the potential future role of TA in managing lung cancer.

An aqueous electrolyte, sodium ion functional, large format energy storage device for stationary applications

NASA Astrophysics Data System (ADS)

Whitacre, J. F.; Wiley, T.; Shanbhag, S.; Wenzhuo, Y.; Mohamed, A.; Chun, S. E.; Weber, E.; Blackwood, D.; Lynch-Bell, E.; Gulakowski, J.; Smith, C.; Humphreys, D.

2012-09-01

An approach to making large format economical energy storage devices based on a sodium-interactive set of electrodes in a neutral pH aqueous electrolyte is described. The economics of materials and manufacturing are examined, followed by a description of an asymmetric/hybrid device that has λ-MnO2 positive electrode material and low cost activated carbon as the negative electrode material. Data presented include materials characterization of the active materials, cyclic voltammetry, galvanostatic charge/discharge cycling, and application-specific performance of an 80 V, 2.4 kW h pack. The results indicate that this set of electrochemical couples is stable, low cost, requires minimal battery management control electronics, and therefore has potential for use in stationary applications where device energy density is not a concern.

Perl One-Liners: Bridging the Gap Between Large Data Sets and Analysis Tools.

PubMed

Hokamp, Karsten

2015-01-01

Computational analyses of biological data are becoming increasingly powerful, and researchers intending on carrying out their own analyses can often choose from a wide array of tools and resources. However, their application might be obstructed by the wide variety of different data formats that are in use, from standard, commonly used formats to output files from high-throughput analysis platforms. The latter are often too large to be opened, viewed, or edited by standard programs, potentially leading to a bottleneck in the analysis. Perl one-liners provide a simple solution to quickly reformat, filter, and merge data sets in preparation for downstream analyses. This chapter presents example code that can be easily adjusted to meet individual requirements. An online version is available at http://bioinf.gen.tcd.ie/pol.

Missed Opportunities for Improving Nutrition Through Institutional Food: The Case for Food Worker Training

PubMed Central

Deutsch, Jonathan; Patinella, Stefania; Freudenberg, Nicholas

2013-01-01

The institutional food sector—including food served in schools, child care settings, hospitals, and senior centers—is a largely untapped resource for public health that may help to arrest increasing rates of obesity and diet-related health problems. To make this case, we estimated the reach of a diverse institutional food sector in 1 large municipality, New York City, in 2012, and explored the potential for improving institutional food by building the skills and nutritional knowledge of foodservice workers through training. Drawing on the research literature and preliminary data collected in New York City, we discuss the dynamics of nutritional decision-making in these settings. Finally, we identify opportunities and challenges associated with training the institutional food workforce to enhance nutrition and health. PMID:23865653

Tool for Rapid Analysis of Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.

2013-01-01

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very difficult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The first version of this tool was a serial code and the current version is a parallel code, which has greatly increased the analysis capabilities. This paper describes the new implementation of this analysis tool on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Beyond Linear Sequence Comparisons: The use of genome-levelcharacters for phylogenetic reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boore, Jeffrey L.

2004-11-27

Although the phylogenetic relationships of many organisms have been convincingly resolved by the comparisons of nucleotide or amino acid sequences, others have remained equivocal despite great effort. Now that large-scale genome sequencing projects are sampling many lineages, it is becoming feasible to compare large data sets of genome-level features and to develop this as a tool for phylogenetic reconstruction that has advantages over conventional sequence comparisons. Although it is unlikely that these will address a large number of evolutionary branch points across the broad tree of life due to the infeasibility of such sampling, they have great potential for convincinglymore » resolving many critical, contested relationships for which no other data seems promising. However, it is important that we recognize potential pitfalls, establish reasonable standards for acceptance, and employ rigorous methodology to guard against a return to earlier days of scenario-driven evolutionary reconstructions.« less

Caught you: threats to confidentiality due to the public release of large-scale genetic data sets

PubMed Central

2010-01-01

Background Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers. Discussion The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual. Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach. Summary Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public. PMID:21190545

Caught you: threats to confidentiality due to the public release of large-scale genetic data sets.

PubMed

Wjst, Matthias

2010-12-29

Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers. The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual. Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach. Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public.

Use of psi(alpha)-ETOs in the unified treatment of electronic attraction, electric field and electric field gradient multicenter integrals of screened Coulomb potentials over Slater orbitals.

PubMed

Guseinov, Israfil

2004-02-01

In this study, using complete orthonormal sets of Psi(alpha)-ETOs (where alpha=1, 0, -1, -2, ...) introduced by the author, a large number of series expansion formulae for the multicenter electronic attraction (EA), electric field (EF) and electric field gradient (EFG) integrals of the Yukawa-like screened Coulomb potentials (SCPs) is presented through the new central and noncentral potentials and the overlap integrals with the same screening constants. The final results obtained are valid for arbitrary locations of STOs and their parameters.

Big data analytics in healthcare: promise and potential.

PubMed

Raghupathi, Wullianallur; Raghupathi, Viju

2014-01-01

To describe the promise and potential of big data analytics in healthcare. The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Rapid insights from remote sensing in the geosciences

NASA Astrophysics Data System (ADS)

Plaza, Antonio

2015-03-01

The growing availability of capacity computing for atomistic materials modeling has encouraged the use of high-accuracy computationally intensive interatomic potentials, such as SNAP. These potentials also happen to scale well on petascale computing platforms. SNAP has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The computational cost per atom is much greater than that of simpler potentials such as Lennard-Jones or EAM, while the communication cost remains modest. We discuss a variety of strategies for implementing SNAP in the LAMMPS molecular dynamics package. We present scaling results obtained running SNAP on three different classes of machine: a conventional Intel Xeon CPU cluster; the Titan GPU-based system; and the combined Sequoia and Vulcan BlueGene/Q. The growing availability of capacity computing for atomistic materials modeling has encouraged the use of high-accuracy computationally intensive interatomic potentials, such as SNAP. These potentials also happen to scale well on petascale computing platforms. SNAP has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The computational cost per atom is much greater than that of simpler potentials such as Lennard-Jones or EAM, while the communication cost remains modest. We discuss a variety of strategies for implementing SNAP in the LAMMPS molecular dynamics package. We present scaling results obtained running SNAP on three different classes of machine: a conventional Intel Xeon CPU cluster; the Titan GPU-based system; and the combined Sequoia and Vulcan BlueGene/Q. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corp., for the U.S. Dept. of Energy's National Nuclear Security Admin. under Contract DE-AC04-94AL85000.

GreedyMAX-type Algorithms for the Maximum Independent Set Problem

NASA Astrophysics Data System (ADS)

Borowiecki, Piotr; Göring, Frank

A maximum independent set problem for a simple graph G = (V,E) is to find the largest subset of pairwise nonadjacent vertices. The problem is known to be NP-hard and it is also hard to approximate. Within this article we introduce a non-negative integer valued function p defined on the vertex set V(G) and called a potential function of a graph G, while P(G) = max v ∈ V(G) p(v) is called a potential of G. For any graph P(G) ≤ Δ(G), where Δ(G) is the maximum degree of G. Moreover, Δ(G) - P(G) may be arbitrarily large. A potential of a vertex lets us get a closer insight into the properties of its neighborhood which leads to the definition of the family of GreedyMAX-type algorithms having the classical GreedyMAX algorithm as their origin. We establish a lower bound 1/(P + 1) for the performance ratio of GreedyMAX-type algorithms which favorably compares with the bound 1/(Δ + 1) known to hold for GreedyMAX. The cardinality of an independent set generated by any GreedyMAX-type algorithm is at least sum_{vin V(G)} (p(v)+1)^{-1}, which strengthens the bounds of Turán and Caro-Wei stated in terms of vertex degrees.

Exotic decays of the 125 GeV Higgs boson

DOE PAGES

Curtin, David; Essig, Rouven; Gori, Stefania; ...

2014-10-13

We perform an extensive survey of nonstandard Higgs decays that are consistent with the 125 GeV Higgs-like resonance. Our aim is to motivate a large set of new experimental analyses on the existing and forthcoming data from the Large Hadron Collider (LHC). The explicit search for exotic Higgs decays presents a largely untapped discovery opportunity for the LHC collaborations, as such decays may be easily missed by other searches. We emphasize that the Higgs is uniquely sensitive to the potential existence of new weakly coupled particles and provide a unified discussion of a large class of both simplified and completemore » models that give rise to characteristic patterns of exotic Higgs decays. We assess the status of exotic Higgs decays after LHC run I. In many cases we are able to set new nontrivial constraints by reinterpreting existing experimental analyses. We point out that improvements are possible with dedicated analyses and perform some preliminary collider studies. As a result, we prioritize the analyses according to their theoretical motivation and their experimental feasibility.« less

Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

PubMed

Scorcioni, Ruggero; Wright, Susan N; Patrick Card, J; Ascoli, Giorgio A; Barrionuevo, Germán

2008-01-01

The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

Big Data and Health Economics: Strengths, Weaknesses, Opportunities and Threats.

PubMed

Collins, Brendan

2016-02-01

'Big data' is the collective name for the increasing capacity of information systems to collect and store large volumes of data, which are often unstructured and time stamped, and to analyse these data by using regression and other statistical techniques. This is a review of the potential applications of big data and health economics, using a SWOT (strengths, weaknesses, opportunities, threats) approach. In health economics, large pseudonymized databases, such as the planned care.data programme in the UK, have the potential to increase understanding of how drugs work in the real world, taking into account adherence, co-morbidities, interactions and side effects. This 'real-world evidence' has applications in individualized medicine. More routine and larger-scale cost and outcomes data collection will make health economic analyses more disease specific and population specific but may require new skill sets. There is potential for biomonitoring and lifestyle data to inform health economic analyses and public health policy.

The GS (genetic selection) Principle.

PubMed

Abel, David L

2009-01-01

The GS (Genetic Selection) Principle states that biological selection must occur at the nucleotide-sequencing molecular-genetic level of 3'5' phosphodiester bond formation. After-the-fact differential survival and reproduction of already-living phenotypic organisms (ordinary natural selection) does not explain polynucleotide prescription and coding. All life depends upon literal genetic algorithms. Even epigenetic and "genomic" factors such as regulation by DNA methylation, histone proteins and microRNAs are ultimately instructed by prior linear digital programming. Biological control requires selection of particular configurable switch-settings to achieve potential function. This occurs largely at the level of nucleotide selection, prior to the realization of any integrated biofunction. Each selection of a nucleotide corresponds to the setting of two formal binary logic gates. The setting of these switches only later determines folding and binding function through minimum-free-energy sinks. These sinks are determined by the primary structure of both the protein itself and the independently prescribed sequencing of chaperones. The GS Principle distinguishes selection of existing function (natural selection) from selection for potential function (formal selection at decision nodes, logic gates and configurable switch-settings).

Visualizing phylogenetic tree landscapes.

PubMed

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D projections significantly increase the fit between the tree-to-tree distances and can facilitate the interpretation of the relationship among phylogenetic trees. We demonstrate that the choice of dimensionality reduction method can significantly influence the spatial relationship among a large set of competing phylogenetic trees. We highlight the importance of selecting a dimensionality reduction method to visualize large multi-locus phylogenetic landscapes and demonstrate that 3D projections of mitochondrial tree landscapes better capture the relationship among the trees being compared.

Quantum potential induced UV-IR coupling in analogue Hawking radiation: From Bose-Einstein condensates to canonical acoustic black holes

NASA Astrophysics Data System (ADS)

Sarkar, Supratik; Bhattacharyay, A.

2017-09-01

Arising out of a nonlocal nonrelativistic Bose-Einstein condensates (BEC), we present an analogue gravity model up to O (ξ2) accuracy (ξ being the healing length of the condensate) in the presence of the quantum potential term for a canonical acoustic black hole in (3 +1 )D spacetime, where the series solution of the free minimally coupled KG equation for the large-length-scale massive scalar modes is derived. We systematically address the issues of the presence of the quantum potential term being the root cause of a UV-IR coupling between short-wavelength primary modes which are supposedly Hawking-radiated through the sonic horizon and the large-wavelength secondary modes. In the quantum gravity experiments of analogue Hawking radiation within the scope of the laboratory set up, this UV-IR coupling is inevitable, and one cannot get rid of these large-wavelength excitations which would grow over space by gaining energy from the short-wavelength Hawking-radiated modes. We identify the characteristic feature in the growth rate(s) that would distinguish these primary and secondary modes.

Prediction of protein tertiary structure to low resolution: performance for a large and structurally diverse test set.

PubMed

Eyrich, V A; Standley, D M; Friesner, R A

1999-05-14

We report the tertiary structure predictions for 95 proteins ranging in size from 17 to 160 residues starting from known secondary structure. Predictions are obtained from global minimization of an empirical potential function followed by the application of a refined atomic overlap potential. The minimization strategy employed represents a variant of the Monte Carlo plus minimization scheme of Li and Scheraga applied to a reduced model of the protein chain. For all of the cases except beta-proteins larger than 75 residues, a native-like structure, usually 4-6 A root-mean-square deviation from the native, is located. For beta-proteins larger than 75 residues, the energy gap between native-like structures and the lowest energy structures produced in the simulation is large, so that low RMSD structures are not generated starting from an unfolded state. This is attributed to the lack of an explicit hydrogen bond term in the potential function, which we hypothesize is necessary to stabilize large assemblies of beta-strands. Copyright 1999 Academic Press.

Aeromagnetic surveys in Afghanistan: An updated website for distribution of data

USGS Publications Warehouse

Shenwary, Ghulam Sakhi; Kohistany, Abdul Hakim; Hussain, Sardar; Ashan, Said; Mutty, Abdul Salam; Daud, Mohammad Ahmad; Wussow, Michael D.; Sweeney, Ronald E.; Phillips, Jeffrey D.; Lindsay, Charles R.; Kucks, Robert P.; Finn, Carol A.; Drenth, Benjamin J.; Anderson, Eric D.; Abraham, Jared D.; Liang, Robert T.; Jarvis, James L.; Gardner, Joan M.; Childers, Vicki A.; Ball, David C.; Brozena, John M.

2011-01-01

Because of its geologic setting, Afghanistan has the potential to contain substantial natural resources. Although valuable mineral deposits and petroleum resources have been identified, much of the country's potential remains unknown. Airborne geophysical surveys are a well accepted and cost effective method for obtaining information about the geological setting of an area without the need to be physically located on the ground. Owing to the current security situation and the large areas of the country that have not been evaluated by geophysical exploration methods, a regional airborne geophysical survey was proposed. Acting upon the request of the Islamic Republic of Afghanistan Ministry of Mines, the U.S. Geological Survey contracted with the Naval Research Laboratory to jointly conduct an airborne geophysical and remote sensing survey of Afghanistan.

Optimizing technology investments: a broad mission model approach

NASA Technical Reports Server (NTRS)

Shishko, R.

2003-01-01

A long-standing problem in NASA is how to allocate scarce technology development resources across advanced technologies in order to best support a large set of future potential missions. Within NASA, two orthogonal paradigms have received attention in recent years: the real-options approach and the broad mission model approach. This paper focuses on the latter.

How "Boundaryless" Are the Careers of High Potentials, Key Experts and Average Performers?

ERIC Educational Resources Information Center

Dries, Nicky; Van Acker, Frederik; Verbruggen, Marijke

2012-01-01

The talent management literature declares talent management a prime concern for HRM professionals while the careers literature calls talent management archaic. Three sets of assumptions identified through comparative review of both streams of the literature were tested in a large-scale survey (n = 941). We found more support for the assumptions…

Investigating the Sets of Values That Community Members Hold toward Local Nature Centers

ERIC Educational Resources Information Center

Browning, Matthew H. E. M.; Stern, Marc J.; Ardoin, Nicole M.; Heimlich, Joe E.; Petty, Robert; Charles, Cheryl

2017-01-01

While nature center's missions often point to connecting people to nature in various ways, their potential to provide a broader array of services to their communities remains largely unexplored. To better understand the values local community members hold for nature centers, we conducted survey research around 16 centers in the United States.…

Characterization of ToxCast Phase II compounds disruption of spontaneous network activity in cortical networks grown on multi-well microelectrode array (mwMEA) plates.

EPA Science Inventory

The development of multi-well microelectrode array (mwMEA) systems has increased in vitro screening throughput making them an effective method to screen and prioritize large sets of compounds for potential neurotoxicity. In the present experiments, a multiplexed approach was used...

Hospital Selective Contracting without Consumer Choice: What Can We Learn from Medi-Cal?

ERIC Educational Resources Information Center

Bamezai, Anil; Melnick, Glenn A.; Mann, Joyce M.; Zwanziger, Jack

2003-01-01

In the selective contracting era, consumer choice has generally been absent in most state Medicaid programs, including California's (called Medi-Cal). In a setting where beneficiary exit is not a threat, a large payer may have both the incentives and the ability to exercise undue market power, potentially exposing an already vulnerable population…

Understanding Information Anxiety and How Academic Librarians Can Minimize Its Effects

ERIC Educational Resources Information Center

Eklof, Ashley

2013-01-01

Information anxiety is a serious issue that has the potential to hinder the success of a large percentage of the population in both education and professional settings. It has become more prevalent as societies begin to focus more on the value of technology, multitasking, and instant information access. The majority of the population has felt, to…

A Multivariate Analysis of Secondary Students' Experience of Web-Based Language Acquisition

ERIC Educational Resources Information Center

Felix, Uschi

2004-01-01

This paper reports on a large-scale project designed to replicate an earlier investigation of tertiary students (Felix, 2001) in a secondary school environment. The new project was carried out in five settings, again investigating the potential of the Web as a medium of language instruction. Data was collected by questionnaires and observational…

Nutritional composition and cooking characteristics of tepary bean (Phaseolus acutifolius Gray) in comparison with common bean (Phaseolus vulgaris L.)

USDA-ARS?s Scientific Manuscript database

Tepary bean is a highly abiotic stress tolerant orphan crop, however, there has been limited research on its nutritional value and cooking characteristics, key aspects when considering the potential for broader adoption globally. The goal of this study was to evaluate a large set of seed composition...

Applications of artificial intelligence systems in the analysis of epidemiological data.

PubMed

Flouris, Andreas D; Duffy, Jack

2006-01-01

A brief review of the germane literature suggests that the use of artificial intelligence (AI) statistical algorithms in epidemiology has been limited. We discuss the advantages and disadvantages of using AI systems in large-scale sets of epidemiological data to extract inherent, formerly unidentified, and potentially valuable patterns that human-driven deductive models may miss.

Code of Practice for the Use of Ionizing Radiations in Secondary Schools.

ERIC Educational Resources Information Center

National Health and Medical Research Council, Canberra (Australia).

The appreciation of the potential hazard of ionizing radiation led to the setting up of national, and later, international commissions for the defining of standards of protection for the occupationally exposed worker in the use of ionizing radiation. However, in the last twenty years, with the large scale development of nuclear energy, the need…

Action-based Dynamical Modeling for the Milky Way Disk: The Influence of Spiral Arms

NASA Astrophysics Data System (ADS)

Trick, Wilma H.; Bovy, Jo; D'Onghia, Elena; Rix, Hans-Walter

2017-04-01

RoadMapping is a dynamical modeling machinery developed to constrain the Milky Way’s (MW) gravitational potential by simultaneously fitting an axisymmetric parametrized potential and an action-based orbit distribution function (DF) to discrete 6D phase-space measurements of stars in the Galactic disk. In this work, we demonstrate RoadMapping's robustness in the presence of spiral arms by modeling data drawn from an N-body simulation snapshot of a disk-dominated galaxy of MW mass with strong spiral arms (but no bar), exploring survey volumes with radii 500 {pc}≤slant {r}\\max ≤slant 5 {kpc}. The potential constraints are very robust, even though we use a simple action-based DF, the quasi-isothermal DF. The best-fit RoadMapping model always recovers the correct gravitational forces where most of the stars that entered the analysis are located, even for small volumes. For data from large survey volumes, RoadMapping finds axisymmetric models that average well over the spiral arms. Unsurprisingly, the models are slightly biased by the excess of stars in the spiral arms. Gravitational potential models derived from survey volumes with at least {r}\\max =3 {kpc} can be reliably extrapolated to larger volumes. However, a large radial survey extent, {r}\\max ˜ 5 {kpc}, is needed to correctly recover the halo scale length. In general, the recovery and extrapolability of potentials inferred from data sets that were drawn from inter-arm regions appear to be better than those of data sets drawn from spiral arms. Our analysis implies that building axisymmetric models for the Galaxy with upcoming Gaia data will lead to sensible and robust approximations of the MW’s potential.

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

NASA Technical Reports Server (NTRS)

Hill, Matthew L. (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Castelli, Vittorio (Inventor); Bergman, Lawrence David (Inventor)

2008-01-01

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

NASA Technical Reports Server (NTRS)

Hill, Matthew L. (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Castelli, Vittorio (Inventor); Bergman, Lawrence David (Inventor)

2005-01-01

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Cosmic shear as a probe of galaxy formation physics

DOE PAGES

Foreman, Simon; Becker, Matthew R.; Wechsler, Risa H.

2016-09-01

Here, we evaluate the potential for current and future cosmic shear measurements from large galaxy surveys to constrain the impact of baryonic physics on the matter power spectrum. We do so using a model-independent parametrization that describes deviations of the matter power spectrum from the dark-matter-only case as a set of principal components that are localized in wavenumber and redshift. We perform forecasts for a variety of current and future data sets, and find that at least ~90 per cent of the constraining power of these data sets is contained in no more than nine principal components. The constraining powermore » of different surveys can be quantified using a figure of merit defined relative to currently available surveys. With this metric, we find that the final Dark Energy Survey data set (DES Y5) and the Hyper Suprime-Cam Survey will be roughly an order of magnitude more powerful than existing data in constraining baryonic effects. Upcoming Stage IV surveys (Large Synoptic Survey Telescope, Euclid, and Wide Field Infrared Survey Telescope) will improve upon this by a further factor of a few. We show that this conclusion is robust to marginalization over several key systematics. The ultimate power of cosmic shear to constrain galaxy formation is dependent on understanding systematics in the shear measurements at small (sub-arcminute) scales. Lastly, if these systematics can be sufficiently controlled, cosmic shear measurements from DES Y5 and other future surveys have the potential to provide a very clean probe of galaxy formation and to strongly constrain a wide range of predictions from modern hydrodynamical simulations.« less

Neuro-genetic system for optimization of GMI samples sensitivity.

PubMed

Pitta Botelho, A C O; Vellasco, M M B R; Hall Barbosa, C R; Costa Silva, E

2016-03-01

Magnetic sensors are largely used in several engineering areas. Among them, magnetic sensors based on the Giant Magnetoimpedance (GMI) effect are a new family of magnetic sensing devices that have a huge potential for applications involving measurements of ultra-weak magnetic fields. The sensitivity of magnetometers is directly associated with the sensitivity of their sensing elements. The GMI effect is characterized by a large variation of the impedance (magnitude and phase) of a ferromagnetic sample, when subjected to a magnetic field. Recent studies have shown that phase-based GMI magnetometers have the potential to increase the sensitivity by about 100 times. The sensitivity of GMI samples depends on several parameters, such as sample length, external magnetic field, DC level and frequency of the excitation current. However, this dependency is yet to be sufficiently well-modeled in quantitative terms. So, the search for the set of parameters that optimizes the samples sensitivity is usually empirical and very time consuming. This paper deals with this problem by proposing a new neuro-genetic system aimed at maximizing the impedance phase sensitivity of GMI samples. A Multi-Layer Perceptron (MLP) Neural Network is used to model the impedance phase and a Genetic Algorithm uses the information provided by the neural network to determine which set of parameters maximizes the impedance phase sensitivity. The results obtained with a data set composed of four different GMI sample lengths demonstrate that the neuro-genetic system is able to correctly and automatically determine the set of conditioning parameters responsible for maximizing their phase sensitivities. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exploring the parameter space of the coarse-grained UNRES force field by random search: selecting a transferable medium-resolution force field.

PubMed

He, Yi; Xiao, Yi; Liwo, Adam; Scheraga, Harold A

2009-10-01

We explored the energy-parameter space of our coarse-grained UNRES force field for large-scale ab initio simulations of protein folding, to obtain good initial approximations for hierarchical optimization of the force field with new virtual-bond-angle bending and side-chain-rotamer potentials which we recently introduced to replace the statistical potentials. 100 sets of energy-term weights were generated randomly, and good sets were selected by carrying out replica-exchange molecular dynamics simulations of two peptides with a minimal alpha-helical and a minimal beta-hairpin fold, respectively: the tryptophan cage (PDB code: 1L2Y) and tryptophan zipper (PDB code: 1LE1). Eight sets of parameters produced native-like structures of these two peptides. These eight sets were tested on two larger proteins: the engrailed homeodomain (PDB code: 1ENH) and FBP WW domain (PDB code: 1E0L); two sets were found to produce native-like conformations of these proteins. These two sets were tested further on a larger set of nine proteins with alpha or alpha + beta structure and found to locate native-like structures of most of them. These results demonstrate that, in addition to finding reasonable initial starting points for optimization, an extensive search of parameter space is a powerful method to produce a transferable force field. Copyright 2009 Wiley Periodicals, Inc.

The Electrolyte Genome project: A big data approach in battery materials discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qu, Xiaohui; Jain, Anubhav; Rajput, Nav Nidhi

2015-06-01

We present a high-throughput infrastructure for the automated calculation of molecular properties with a focus on battery electrolytes. The infrastructure is largely open-source and handles both practical aspects (input file generation, output file parsing, and information management) as well as more complex problems (structure matching, salt complex generation, and failure recovery). Using this infrastructure, we have computed the ionization potential (IP) and electron affinities (EA) of 4830 molecules relevant to battery electrolytes (encompassing almost 55,000 quantum mechanics calculations) at the B3LYP/6-31+G(*) level. We describe automated workflows for computing redox potential, dissociation constant, and salt-molecule binding complex structure generation. We presentmore » routines for automatic recovery from calculation errors, which brings the failure rate from 9.2% to 0.8% for the QChem DFT code. Automated algorithms to check duplication between two arbitrary molecules and structures are described. We present benchmark data on basis sets and functionals on the G2-97 test set; one finding is that a IP/EA calculation method that combines PBE geometry optimization and B3LYP energy evaluation requires less computational cost and yields nearly identical results as compared to a full B3LYP calculation, and could be suitable for the calculation of large molecules. Our data indicates that among the 8 functionals tested, XYGJ-OS and B3LYP are the two best functionals to predict IP/EA with an RMSE of 0.12 and 0.27 eV, respectively. Application of our automated workflow to a large set of quinoxaline derivative molecules shows that functional group effect and substitution position effect can be separated for IP/EA of quinoxaline derivatives, and the most sensitive position is different for IP and EA. Published by Elsevier B.V« less

New Evidence on Self-Affirmation Effects and Theorized Sources of Heterogeneity from Large-Scale Replications

PubMed Central

Hanselman, Paul; Rozek, Christopher S.; Grigg, Jeffrey; Borman, Geoffrey D.

2016-01-01

Brief, targeted self-affirmation writing exercises have recently been offered as a way to reduce racial achievement gaps, but evidence about their effects in educational settings is mixed, leaving ambiguity about the likely benefits of these strategies if implemented broadly. A key limitation in interpreting these mixed results is that they come from studies conducted by different research teams with different procedures in different settings; it is therefore impossible to isolate whether different effects are the result of theorized heterogeneity, unidentified moderators, or idiosyncratic features of the different studies. We addressed this limitation by conducting a well-powered replication of self-affirmation in a setting where a previous large-scale field experiment demonstrated significant positive impacts, using the same procedures. We found no evidence of effects in this replication study and estimates were precise enough to reject benefits larger than an effect size of 0.10. These null effects were significantly different from persistent benefits in the prior study in the same setting, and extensive testing revealed that currently theorized moderators of self-affirmation effects could not explain the difference. These results highlight the potential fragility of self-affirmation in educational settings when implemented widely and the need for new theory, measures, and evidence about the necessary conditions for self-affirmation success. PMID:28450753

Methods and apparatus of analyzing electrical power grid data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hafen, Ryan P.; Critchlow, Terence J.; Gibson, Tara D.

Apparatus and methods of processing large-scale data regarding an electrical power grid are described. According to one aspect, a method of processing large-scale data regarding an electrical power grid includes accessing a large-scale data set comprising information regarding an electrical power grid; processing data of the large-scale data set to identify a filter which is configured to remove erroneous data from the large-scale data set; using the filter, removing erroneous data from the large-scale data set; and after the removing, processing data of the large-scale data set to identify an event detector which is configured to identify events of interestmore » in the large-scale data set.« less

Nature is the best source of anti-inflammatory drugs: indexing natural products for their anti-inflammatory bioactivity.

PubMed

Aswad, Miran; Rayan, Mahmoud; Abu-Lafi, Saleh; Falah, Mizied; Raiyn, Jamal; Abdallah, Ziyad; Rayan, Anwar

2018-01-01

The aim was to index natural products for less expensive preventive or curative anti-inflammatory therapeutic drugs. A set of 441 anti-inflammatory drugs representing the active domain and 2892 natural products representing the inactive domain was used to construct a predictive model for bioactivity-indexing purposes. The model for indexing the natural products for potential anti-inflammatory activity was constructed using the iterative stochastic elimination algorithm (ISE). ISE is capable of differentiating between active and inactive anti-inflammatory molecules. By applying the prediction model to a mix set of (active/inactive) substances, we managed to capture 38% of the anti-inflammatory drugs in the top 1% of the screened set of chemicals, yielding enrichment factor of 38. Ten natural products that scored highly as potential anti-inflammatory drug candidates are disclosed. Searching the PubMed revealed that only three molecules (Moupinamide, Capsaicin, and Hypaphorine) out of the ten were tested and reported as anti-inflammatory. The other seven phytochemicals await evaluation for their anti-inflammatory activity in wet lab. The proposed anti-inflammatory model can be utilized for the virtual screening of large chemical databases and for indexing natural products for potential anti-inflammatory activity.

Multipole moments in the effective fragment potential method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bertoni, Colleen; Slipchenko, Lyudmila V.; Misquitta, Alston J.

In the effective fragment potential (EFP) method the Coulomb potential is represented using a set of multipole moments generated by the distributed multipole analysis (DMA) method. Misquitta, Stone, and Fazeli recently developed a basis space-iterated stockholder atom (BS-ISA) method to generate multipole moments. This study assesses the accuracy of the EFP interaction energies using sets of multipole moments generated from the BS-ISA method, and from several versions of the DMA method (such as analytic and numeric grid-based), with varying basis sets. Both methods lead to reasonable results, although using certain implementations of the DMA method can result in large errors.more » With respect to the CCSD(T)/CBS interaction energies, the mean unsigned error (MUE) of the EFP method for the S22 data set using BS-ISA–generated multipole moments and DMA-generated multipole moments (using a small basis set and the analytic DMA procedure) is 0.78 and 0.72 kcal/mol, respectively. Here, the MUE accuracy is on the same order as MP2 and SCS-MP2. The MUEs are lower than in a previous study benchmarking the EFP method without the EFP charge transfer term, demonstrating that the charge transfer term increases the accuracy of the EFP method. Regardless of the multipole moment method used, it is likely that much of the error is due to an insufficient short-range electrostatic term (i.e., charge penetration term), as shown by comparisons with symmetry-adapted perturbation theory.« less

Multipole moments in the effective fragment potential method

DOE PAGES

Bertoni, Colleen; Slipchenko, Lyudmila V.; Misquitta, Alston J.; ...

2017-02-17

In the effective fragment potential (EFP) method the Coulomb potential is represented using a set of multipole moments generated by the distributed multipole analysis (DMA) method. Misquitta, Stone, and Fazeli recently developed a basis space-iterated stockholder atom (BS-ISA) method to generate multipole moments. This study assesses the accuracy of the EFP interaction energies using sets of multipole moments generated from the BS-ISA method, and from several versions of the DMA method (such as analytic and numeric grid-based), with varying basis sets. Both methods lead to reasonable results, although using certain implementations of the DMA method can result in large errors.more » With respect to the CCSD(T)/CBS interaction energies, the mean unsigned error (MUE) of the EFP method for the S22 data set using BS-ISA–generated multipole moments and DMA-generated multipole moments (using a small basis set and the analytic DMA procedure) is 0.78 and 0.72 kcal/mol, respectively. Here, the MUE accuracy is on the same order as MP2 and SCS-MP2. The MUEs are lower than in a previous study benchmarking the EFP method without the EFP charge transfer term, demonstrating that the charge transfer term increases the accuracy of the EFP method. Regardless of the multipole moment method used, it is likely that much of the error is due to an insufficient short-range electrostatic term (i.e., charge penetration term), as shown by comparisons with symmetry-adapted perturbation theory.« less

The global problem of childhood diarrhoeal diseases: emerging strategies in prevention and management

PubMed Central

Mokomane, Margaret; Kasvosve, Ishmael; de Melo, Emilia; Pernica, Jeffrey M.; Goldfarb, David M.

2017-01-01

Acute diarrhoeal diseases remain a leading cause of global morbidity and mortality particularly among young children in resource-limited countries. Recent large studies utilizing case–control design, prospective sampling and more sensitive and broad diagnostic techniques have shed light on particular pathogens of importance and highlighted the previously under recognized impact of these infections on post-acute illness mortality and growth. Vaccination, particularly against rotavirus, has emerged as a key effective means of preventing significant morbidity and mortality from childhood diarrhoeal disease. Other candidate vaccines against leading diarrhoeal pathogens, such as enterotoxigenic Escherichia coli and Shigella spp., also hold significant promise in further ameliorating the burden of enteric infections in children. Large studies are also currently underway evaluating novel and potential easy-to-implement water, sanitation and hygiene (WASH) preventive strategies. Given the ongoing global burden of this illness, the paucity of new advances in case management over the last several decades remains a challenge. The increasing recognition of post-acute illness mortality and growth impairment has highlighted the need for interventions that go beyond management of dehydration and electrolyte disturbances. The few trials of novel promising interventions such as probiotics have mainly been conducted in high-income settings. Trials of antimicrobials have also been primarily conducted in high-income settings or in travellers from high-income settings. Bloody diarrhoea has been shown to be a poor marker of potentially treatable bacterial enteritis, and rising antimicrobial resistance has also made empiric antimicrobial therapy more challenging in many settings. Novel effective and sustainable interventions and diagnostic strategies are clearly needed to help improve case management. Diarrhoeal disease and other enteric infections remain an unmet challenge in global child health. Most promising recent developments have been focused around preventive measures, in particular vaccination. Further advances in prevention and case management including the possible use of targeted antimicrobial treatment are also required to fully address this critical burden on child health and human potential. PMID:29344358

Estimating the intrinsic limit of the Feller-Peterson-Dixon composite approach when applied to adiabatic ionization potentials in atoms and small molecules

NASA Astrophysics Data System (ADS)

Feller, David

2017-07-01

Benchmark adiabatic ionization potentials were obtained with the Feller-Peterson-Dixon (FPD) theoretical method for a collection of 48 atoms and small molecules. In previous studies, the FPD method demonstrated an ability to predict atomization energies (heats of formation) and electron affinities well within a 95% confidence level of ±1 kcal/mol. Large 1-particle expansions involving correlation consistent basis sets (up to aug-cc-pV8Z in many cases and aug-cc-pV9Z for some atoms) were chosen for the valence CCSD(T) starting point calculations. Despite their cost, these large basis sets were chosen in order to help minimize the residual basis set truncation error and reduce dependence on approximate basis set limit extrapolation formulas. The complementary n-particle expansion included higher order CCSDT, CCSDTQ, or CCSDTQ5 (coupled cluster theory with iterative triple, quadruple, and quintuple excitations) corrections. For all of the chemical systems examined here, it was also possible to either perform explicit full configuration interaction (CI) calculations or to otherwise estimate the full CI limit. Additionally, corrections associated with core/valence correlation, scalar relativity, anharmonic zero point vibrational energies, non-adiabatic effects, and other minor factors were considered. The root mean square deviation with respect to experiment for the ionization potentials was 0.21 kcal/mol (0.009 eV). The corresponding level of agreement for molecular enthalpies of formation was 0.37 kcal/mol and for electron affinities 0.20 kcal/mol. Similar good agreement with experiment was found in the case of molecular structures and harmonic frequencies. Overall, the combination of energetic, structural, and vibrational data (655 comparisons) reflects the consistent ability of the FPD method to achieve close agreement with experiment for small molecules using the level of theory applied in this study.

Visualization of diversity in large multivariate data sets.

PubMed

Pham, Tuan; Hess, Rob; Ju, Crystal; Zhang, Eugene; Metoyer, Ronald

2010-01-01

Understanding the diversity of a set of multivariate objects is an important problem in many domains, including ecology, college admissions, investing, machine learning, and others. However, to date, very little work has been done to help users achieve this kind of understanding. Visual representation is especially appealing for this task because it offers the potential to allow users to efficiently observe the objects of interest in a direct and holistic way. Thus, in this paper, we attempt to formalize the problem of visualizing the diversity of a large (more than 1000 objects), multivariate (more than 5 attributes) data set as one worth deeper investigation by the information visualization community. In doing so, we contribute a precise definition of diversity, a set of requirements for diversity visualizations based on this definition, and a formal user study design intended to evaluate the capacity of a visual representation for communicating diversity information. Our primary contribution, however, is a visual representation, called the Diversity Map, for visualizing diversity. An evaluation of the Diversity Map using our study design shows that users can judge elements of diversity consistently and as or more accurately than when using the only other representation specifically designed to visualize diversity.

Measuring CAMD technique performance. 2. How "druglike" are drugs? Implications of Random test set selection exemplified using druglikeness classification models.

PubMed

Good, Andrew C; Hermsmeier, Mark A

2007-01-01

Research into the advancement of computer-aided molecular design (CAMD) has a tendency to focus on the discipline of algorithm development. Such efforts are often wrought to the detriment of the data set selection and analysis used in said algorithm validation. Here we highlight the potential problems this can cause in the context of druglikeness classification. More rigorous efforts are applied to the selection of decoy (nondruglike) molecules from the ACD. Comparisons are made between model performance using the standard technique of random test set creation with test sets derived from explicit ontological separation by drug class. The dangers of viewing druglike space as sufficiently coherent to permit simple classification are highlighted. In addition the issues inherent in applying unfiltered data and random test set selection to (Q)SAR models utilizing large and supposedly heterogeneous databases are discussed.

Potentially ineffective care: time for earnest reexamination.

PubMed

Jackson, William L; Sales, Joseph F

2014-01-01

The rising costs and suboptimal quality throughout the American health care system continue to invite critical inquiry, and practice in the intensive care unit setting is no exception. Due to their relatively large impact, outcomes and costs in critical care are of significant interest to policymakers and health care administrators. Measurement of potentially ineffective care has been proposed as an outcome measure to evaluate critical care delivery, and the Patient Protection and Affordable Care Act affords the opportunity to reshape the care of the critically ill. Given the impetus of the PPACA, systematic formal measurement of potentially ineffective care and its clinical, economic, and societal impact merits timely reconsideration.

Intelligent System Development Using a Rough Sets Methodology

NASA Technical Reports Server (NTRS)

Anderson, Gray T.; Shelton, Robert O.

1997-01-01

The purpose of this research was to examine the potential of the rough sets technique for developing intelligent models of complex systems from limited information. Rough sets a simple but promising technology to extract easily understood rules from data. The rough set methodology has been shown to perform well when used with a large set of exemplars, but its performance with sparse data sets is less certain. The difficulty is that rules will be developed based on just a few examples, each of which might have a large amount of noise associated with them. The question then becomes, what is the probability of a useful rule being developed from such limited information? One nice feature of rough sets is that in unusual situations, the technique can give an answer of 'I don't know'. That is, if a case arises that is different from the cases the rough set rules were developed on, the methodology can recognize this and alert human operators of it. It can also be trained to do this when the desired action is unknown because conflicting examples apply to the same set of inputs. This summer's project was to look at combining rough set theory with statistical theory to develop confidence limits in rules developed by rough sets. Often it is important not to make a certain type of mistake (e.g., false positives or false negatives), so the rules must be biased toward preventing a catastrophic error, rather than giving the most likely course of action. A method to determine the best course of action in the light of such constraints was examined. The resulting technique was tested with files containing electrical power line 'signatures' from the space shuttle and with decompression sickness data.

Resource-poor settings: infrastructure and capacity building: care of the critically ill and injured during pandemics and disasters: CHEST consensus statement.

PubMed

Geiling, James; Burkle, Frederick M; Amundson, Dennis; Dominguez-Cherit, Guillermo; Gomersall, Charles D; Lim, Matthew L; Luyckx, Valerie; Sarani, Babak; Uyeki, Timothy M; West, T Eoin; Christian, Michael D; Devereaux, Asha V; Dichter, Jeffrey R; Kissoon, Niranjan

2014-10-01

Planning for mass critical care (MCC) in resource-poor or constrained settings has been largely ignored, despite their large populations that are prone to suffer disproportionately from natural disasters. Addressing MCC in these settings has the potential to help vast numbers of people and also to inform planning for better-resourced areas. The Resource-Poor Settings panel developed five key question domains; defining the term resource poor and using the traditional phases of disaster (mitigation/preparedness/response/recovery), literature searches were conducted to identify evidence on which to answer the key questions in these areas. Given a lack of data upon which to develop evidence-based recommendations, expert-opinion suggestions were developed, and consensus was achieved using a modified Delphi process. The five key questions were then separated as follows: definition, infrastructure and capacity building, resources, response, and reconstitution/recovery of host nation critical care capabilities and research. Addressing these questions led the panel to offer 33 suggestions. Because of the large number of suggestions, the results have been separated into two sections: part 1, Infrastructure/Capacity in this article, and part 2, Response/Recovery/Research in the accompanying article. Lack of, or presence of, rudimentary ICU resources and limited capacity to enhance services further challenge resource-poor and constrained settings. Hence, capacity building entails preventative strategies and strengthening of primary health services. Assistance from other countries and organizations is needed to mount a surge response. Moreover, planning should include when to disengage and how the host nation can provide capacity beyond the mass casualty care event.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

PubMed

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.

A new potential energy surface for vibration-vibration coupling in HF-HF collisions. Formulation and quantal scattering calculations

NASA Astrophysics Data System (ADS)

Schwenke, David W.; Truhlar, Donald G.

1988-04-01

We present new ab initio calculations of the HF-HF interaction potential for the case where both molecules are simultaneously displaced from their equilibrium internuclear distance. These and previous ab initio calculations are then fit to a new analytic representation which is designed to be efficient to evaluate and to provide an especially faithful account of the forces along the vibrational coordinates. We use the new potential for two sets of quantal scattering calculations for collisions in three dimensions with total angular momentum zero. First we test that the angular harmonic representation of the anisotropy is adequate by comparing quantal rigid rotator calculations to those carried out for potentials involving higher angular harmonics and for which the expansion in angular harmonics is systematically increased to convergence. Then we carry out large-scale quantal calculations of vibration-vibration energy transfer including the coupling of both sets of vibrational and rotational coordinates. These calculations indicate that significant rotational energy transfer accompanies the vibration-to-vibration energy transfer process.

Theoretical studies of potential energy surface and rotational spectra of Xe -H2O van der Waals complex

NASA Astrophysics Data System (ADS)

Wang, Lin; Yang, Minghui

2008-11-01

In this work we report an ab initio intermolecular potential energy surface and theoretical spectroscopic studies for Xe -H2O complex. The ab initio energies are calculated with CCSD(T) method and large basis sets (aug-cc-pVQZ for H and O and aug-cc-pVQZ-PP for Xe) augmented by a {3s3p2d2f1g} set of bond functions. This potential energy surface has a global minimum corresponding to a planar and nearly linear hydrogen bonded configuration with a well depth of 192.5cm-1 at intermolecular distance of 4.0Å, which is consistent with the previous determined potential by Wen and Jäger [J. Phys. Chem. A 110, 7560 (2006)]. The bound state calculations have been performed for the complex by approximating the water molecule as a rigid rotor. The theoretical rotational transition frequencies, isotopic shifts, nuclear quadrupole coupling constants, and structure parameters are in good agreement with the experimental observed values. The wavefunctions are analyzed to understand the dynamics of the ground and the first excited states.

Internet Versus Virtual Reality Settings for Genomics Information Provision.

PubMed

Persky, Susan; Kistler, William D; Klein, William M P; Ferrer, Rebecca A

2018-06-22

Current models of genomic information provision will be unable to handle large-scale clinical integration of genomic information, as may occur in primary care settings. Therefore, adoption of digital tools for genetic and genomic information provision is anticipated, primarily using Internet-based, distributed approaches. The emerging consumer communication platform of virtual reality (VR) is another potential intermediate approach between face-to-face and distributed Internet platforms to engage in genomics education and information provision. This exploratory study assessed whether provision of genomics information about body weight in a simulated, VR-based consultation (relative to a distributed, Internet platform) would be associated with differences in health behavior-related attitudes and beliefs, and interpersonal reactions to the avatar-physician. We also assessed whether outcomes differed depending upon whether genomic versus lifestyle-oriented information was conveyed. There were significant differences between communication platforms for all health behavior-oriented outcomes. Following communication in the VR setting, participants reported greater self-efficacy, dietary behavioral intentions, and exercise behavioral intentions than in the Internet-based setting. There were no differences in trust of the physician by setting, and no interaction between setting effects and the content of the information. This study was a first attempt to examine the potential capabilities of a VR-based communication setting for conveying genomic content in the context of weight management. There may be benefits to use of VR settings for communication about genomics, as well as more traditional health information, when it comes to influencing the attitudes and beliefs that underlie healthy lifestyle behaviors.

Theoretical studies of the potential surface for the F - H2 greater than HF + H reaction

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Walch, Stephen, P.; Langhoff, Stephen R.; Taylor, Peter R.; Jaffe, Richard L.

1987-01-01

The F + H2 yields HF + H potential energy hypersurface was studied in the saddle point and entrance channel regions. Using a large (5s 5p 3d 2f 1g/4s 3p 2d) atomic natural orbital basis set, a classical barrier height of 1.86 kcal/mole was obtained at the CASSCF/multireference CI level (MRCI) after correcting for basis set superposition error and including a Davidson correction (+Q) for higher excitations. Based upon an analysis of the computed results, the true classical barrier is estimated to be about 1.4 kcal/mole. The location of the bottleneck on the lowest vibrationally adiabatic potential curve was also computed and the translational energy threshold determined from a one-dimensional tunneling calculation. Using the difference between the calculated and experimental threshold to adjust the classical barrier height on the computed surface yields a classical barrier in the range of 1.0 to 1.5 kcal/mole. Combining the results of the direct estimates of the classical barrier height with the empirical values obtained from the approximation calculations of the dynamical threshold, it is predicted that the true classical barrier height is 1.4 + or - 0.4 kcal/mole. Arguments are presented in favor of including the relatively large +Q correction obtained when nine electrons are correlated at the CASSCF/MRCI level.

FURTHER STUDY OF SOMA, DENDRITE, AND AXON EXCITATION IN SINGLE NEURONS

PubMed Central

Eyzaguirre, Carlos; Kuffler, Stephen W.

1955-01-01

The present investigation continues a previous study in which the soma-dendrite system of sensory neurons was excited by stretch deformation of the peripheral dendrite portions. Recording was done with intracellular leads which were inserted into the cell soma while the neuron was activated orthodromically or antidromically. The analysis was also extended to axon conduction. Crayfish, Procambarus alleni (Faxon) and Orconectes virilis (Hagen), were used. 1. The size and time course of action potentials recorded from the soma-dendrite complex vary greatly with the level of the cell's membrane potential. The latter can be changed over a wide range by stretch deformation which sets up a "generator potential" in the distal portions of the dendrites. If a cell is at its resting unstretched equilibrium potential, antidromic stimulation through the axon causes an impulse which normally overshoots the resting potential and decays into an afternegativity of 15 to 20 msec. duration. The postspike negativity is not followed by an appreciable hyperpolarization (positive) phase. If the membrane potential is reduced to a new steady level a postspike positivity appears and increases linearly over a depolarization range of 12 to 20 mv. in various cells. At those levels the firing threshold of the cell for orthodromic discharges is generally reached. 2. The safety factor for conduction between axon and cell soma is reduced under three unrelated conditions, (a) During the recovery period (2 to 3 msec.) immediately following an impulse which has conducted fully over the cell soma, a second impulse may be delayed, may invade the soma partially, or may be blocked completely. (b) If progressive depolarization is produced by stretch, it leads to a reduction of impulse height and eventually to complete block of antidromic soma invasion, resembling cathodal block, (c) In some cells, when the normal membrane potential is within several millivolts of the relaxed resting state, an antidromic impulse may be blocked and may set up within the soma a local potential only. The local potential can sum with a second one or it may sum with potential changes set up in the dendrites, leading to complete invasion of the soma. Such antidromic invasion block can always be relieved by appropriate stretch which shifts the membrane potential out of the "blocking range" nearer to the soma firing level. During the afterpositivity of an impulse in a stretched cell the membrane potential may fall below or near the blocking range. During that period another impulse may be delayed or blocked. 3. Information regarding activity and conduction in dendrites has been obtained indirectly, mainly by analyzing the generator action under various conditions of stretch. The following conclusions have been reached: The large dendrite branches have similar properties to the cell body from which they arise and carry the same kind of impulses. In the finer distal filaments of even lightly depolarized dendrites, however, no axon type all-or-none conduction occurs since the generator potential persists to a varying degree during antidromic invasion of the cell. With the membrane potential at its resting level the dendrite terminals contribute to the prolonged impulse afternegativity of the soma. 4. Action potentials in impaled axons and in cell bodies have been compared. It is thought that normally the over-all duration of axon impulses is shorter. Local activity during reduction of the safety margin for conduction was studied. 5. An analysis was made of high frequency grouped discharges which occasionally arise in cells. They differ in many essential aspects from the regular discharges set up by the generator action. It is proposed that grouped discharges occur only when invasion of dendrites is not synchronous, due to a delay in excitation spread between soma and dendrites. Each impulse in a group is assumed to be caused by an impulse in at least one of the large dendrite branches. Depolarization of dendrites abolishes the grouped activity by facilitating invasion of the large dendrite branches. PMID:13252238

A large-scale video codec comparison of x264, x265 and libvpx for practical VOD applications

NASA Astrophysics Data System (ADS)

De Cock, Jan; Mavlankar, Aditya; Moorthy, Anush; Aaron, Anne

2016-09-01

Over the last years, we have seen exciting improvements in video compression technology, due to the introduction of HEVC and royalty-free coding specifications such as VP9. The potential compression gains of HEVC over H.264/AVC have been demonstrated in different studies, and are usually based on the HM reference software. For VP9, substantial gains over H.264/AVC have been reported in some publications, whereas others reported less optimistic results. Differences in configurations between these publications make it more difficult to assess the true potential of VP9. Practical open-source encoder implementations such as x265 and libvpx (VP9) have matured, and are now showing high compression gains over x264. In this paper, we demonstrate the potential of these encoder imple- mentations, with settings optimized for non-real-time random access, as used in a video-on-demand encoding pipeline. We report results from a large-scale video codec comparison test, which includes x264, x265 and libvpx. A test set consisting of a variety of titles with varying spatio-temporal characteristics from our catalog is used, resulting in tens of millions of encoded frames, hence larger than test sets previously used in the literature. Re- sults are reported in terms of PSNR, SSIM, MS-SSIM, VIF and the recently introduced VMAF quality metric. BD-rate calculations show that using x265 and libvpx vs. x264 can lead to significant bitrate savings for the same quality. x265 outperforms libvpx in most cases, but the performance gap narrows (or even reverses) at the higher resolutions.

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging.

PubMed

Eloyan, Ani; Muschelli, John; Nebel, Mary Beth; Liu, Han; Han, Fang; Zhao, Tuo; Barber, Anita D; Joel, Suresh; Pekar, James J; Mostofsky, Stewart H; Caffo, Brian

2012-01-01

Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions (SVDs), CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry, and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD.

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

PubMed Central

Eloyan, Ani; Muschelli, John; Nebel, Mary Beth; Liu, Han; Han, Fang; Zhao, Tuo; Barber, Anita D.; Joel, Suresh; Pekar, James J.; Mostofsky, Stewart H.; Caffo, Brian

2012-01-01

Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions (SVDs), CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry, and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD. PMID:22969709

Predicting climate-induced range shifts: model differences and model reliability.

Treesearch

Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein

2006-01-01

Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common data set, we investigated the potential implications of alternative modeling approaches for...

Development of a large set of microsatellite markers in Zapote Maney (Pouteria sapota (Jacq.) (H.E. Moore & Stearn) and their potential use in the study of the species

USDA-ARS?s Scientific Manuscript database

The tropical plant Pouteria sapota (Jacq.) is known for its edible fruits that contain unique carotenoids, and for the chemicals extracted from its bark, leaves and roots having fungitoxic, insecticidal, anti-inflamatory, anti-oxidant and tyrosinase inhibitory activities. Currently, there is no gen...

Listening to Music: Helping Children Regulate Their Emotions and Improve Learning in the Classroom

ERIC Educational Resources Information Center

Foran, Lucille M.

2009-01-01

Early education teachers are familiar with using music and rhythm as tools for learning language and building memory. However, the potential of music to help across all special education settings is largely unexplored. Work with music has been widely judged helpful in cases of psychological trauma, yet people do not know why it is helpful. The…

Managing protected health information in distributed research network environments: automated review to facilitate collaboration.

PubMed

Bredfeldt, Christine E; Butani, Amy; Padmanabhan, Sandhyasree; Hitz, Paul; Pardee, Roy

2013-03-22

Multi-site health sciences research is becoming more common, as it enables investigation of rare outcomes and diseases and new healthcare innovations. Multi-site research usually involves the transfer of large amounts of research data between collaborators, which increases the potential for accidental disclosures of protected health information (PHI). Standard protocols for preventing release of PHI are extremely vulnerable to human error, particularly when the shared data sets are large. To address this problem, we developed an automated program (SAS macro) to identify possible PHI in research data before it is transferred between research sites. The macro reviews all data in a designated directory to identify suspicious variable names and data patterns. The macro looks for variables that may contain personal identifiers such as medical record numbers and social security numbers. In addition, the macro identifies dates and numbers that may identify people who belong to small groups, who may be identifiable even in the absences of traditional identifiers. Evaluation of the macro on 100 sample research data sets indicated a recall of 0.98 and precision of 0.81. When implemented consistently, the macro has the potential to streamline the PHI review process and significantly reduce accidental PHI disclosures.

Reducing Information Overload in Large Seismic Data Sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

HAMPTON,JEFFERY W.; YOUNG,CHRISTOPHER J.; MERCHANT,BION J.

2000-08-02

Event catalogs for seismic data can become very large. Furthermore, as researchers collect multiple catalogs and reconcile them into a single catalog that is stored in a relational database, the reconciled set becomes even larger. The sheer number of these events makes searching for relevant events to compare with events of interest problematic. Information overload in this form can lead to the data sets being under-utilized and/or used incorrectly or inconsistently. Thus, efforts have been initiated to research techniques and strategies for helping researchers to make better use of large data sets. In this paper, the authors present their effortsmore » to do so in two ways: (1) the Event Search Engine, which is a waveform correlation tool and (2) some content analysis tools, which area combination of custom-built and commercial off-the-shelf tools for accessing, managing, and querying seismic data stored in a relational database. The current Event Search Engine is based on a hierarchical clustering tool known as the dendrogram tool, which is written as a MatSeis graphical user interface. The dendrogram tool allows the user to build dendrogram diagrams for a set of waveforms by controlling phase windowing, down-sampling, filtering, enveloping, and the clustering method (e.g. single linkage, complete linkage, flexible method). It also allows the clustering to be based on two or more stations simultaneously, which is important to bridge gaps in the sparsely recorded event sets anticipated in such a large reconciled event set. Current efforts are focusing on tools to help the researcher winnow the clusters defined using the dendrogram tool down to the minimum optimal identification set. This will become critical as the number of reference events in the reconciled event set continually grows. The dendrogram tool is part of the MatSeis analysis package, which is available on the Nuclear Explosion Monitoring Research and Engineering Program Web Site. As part of the research into how to winnow the reference events in these large reconciled event sets, additional database query approaches have been developed to provide windows into these datasets. These custom built content analysis tools help identify dataset characteristics that can potentially aid in providing a basis for comparing similar reference events in these large reconciled event sets. Once these characteristics can be identified, algorithms can be developed to create and add to the reduced set of events used by the Event Search Engine. These content analysis tools have already been useful in providing information on station coverage of the referenced events and basic statistical, information on events in the research datasets. The tools can also provide researchers with a quick way to find interesting and useful events within the research datasets. The tools could also be used as a means to review reference event datasets as part of a dataset delivery verification process. There has also been an effort to explore the usefulness of commercially available web-based software to help with this problem. The advantages of using off-the-shelf software applications, such as Oracle's WebDB, to manipulate, customize and manage research data are being investigated. These types of applications are being examined to provide access to large integrated data sets for regional seismic research in Asia. All of these software tools would provide the researcher with unprecedented power without having to learn the intricacies and complexities of relational database systems.« less

Analysis of classifiers performance for classification of potential microcalcification

NASA Astrophysics Data System (ADS)

M. N., Arun K.; Sheshadri, H. S.

2013-07-01

Breast cancer is a significant public health problem in the world. According to the literature early detection improve breast cancer prognosis. Mammography is a screening tool used for early detection of breast cancer. About 10-30% cases are missed during the routine check as it is difficult for the radiologists to make accurate analysis due to large amount of data. The Microcalcifications (MCs) are considered to be important signs of breast cancer. It has been reported in literature that 30% - 50% of breast cancer detected radio graphically show MCs on mammograms. Histologic examinations report 62% to 79% of breast carcinomas reveals MCs. MC are tiny, vary in size, shape, and distribution, and MC may be closely connected to surrounding tissues. There is a major challenge using the traditional classifiers in the classification of individual potential MCs as the processing of mammograms in appropriate stage generates data sets with an unequal amount of information for both classes (i.e., MC, and Not-MC). Most of the existing state-of-the-art classification approaches are well developed by assuming the underlying training set is evenly distributed. However, they are faced with a severe bias problem when the training set is highly imbalanced in distribution. This paper addresses this issue by using classifiers which handle the imbalanced data sets. In this paper, we also compare the performance of classifiers which are used in the classification of potential MC.

Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

PubMed Central

Vajda, Szilárd; Rangoni, Yves; Cecotti, Hubert

2015-01-01

For training supervised classifiers to recognize different patterns, large data collections with accurate labels are necessary. In this paper, we propose a generic, semi-automatic labeling technique for large handwritten character collections. In order to speed up the creation of a large scale ground truth, the method combines unsupervised clustering and minimal expert knowledge. To exploit the potential discriminant complementarities across features, each character is projected into five different feature spaces. After clustering the images in each feature space, the human expert labels the cluster centers. Each data point inherits the label of its cluster’s center. A majority (or unanimity) vote decides the label of each character image. The amount of human involvement (labeling) is strictly controlled by the number of clusters – produced by the chosen clustering approach. To test the efficiency of the proposed approach, we have compared, and evaluated three state-of-the art clustering methods (k-means, self-organizing maps, and growing neural gas) on the MNIST digit data set, and a Lampung Indonesian character data set, respectively. Considering a k-nn classifier, we show that labeling manually only 1.3% (MNIST), and 3.2% (Lampung) of the training data, provides the same range of performance than a completely labeled data set would. PMID:25870463

Feature Selection Methods for Zero-Shot Learning of Neural Activity.

PubMed

Caceres, Carlos A; Roos, Matthew J; Rupp, Kyle M; Milsap, Griffin; Crone, Nathan E; Wolmetz, Michael E; Ratto, Christopher R

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

Accurate force field for molybdenum by machine learning large materials data

NASA Astrophysics Data System (ADS)

Chen, Chi; Deng, Zhi; Tran, Richard; Tang, Hanmei; Chu, Iek-Heng; Ong, Shyue Ping

2017-09-01

In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning techniques on large materials data sets. Despite Mo's importance as a structural metal, existing force fields for Mo based on the embedded atom and modified embedded atom methods do not provide satisfactory accuracy on many properties. We will show that by fitting to the energies, forces, and stress tensors of a large density functional theory (DFT)-computed dataset on a diverse set of Mo structures, a Mo SNAP model can be developed that achieves close to DFT accuracy in the prediction of a broad range of properties, including elastic constants, melting point, phonon spectra, surface energies, grain boundary energies, etc. We will outline a systematic model development process, which includes a rigorous approach to structural selection based on principal component analysis, as well as a differential evolution algorithm for optimizing the hyperparameters in the model fitting so that both the model error and the property prediction error can be simultaneously lowered. We expect that this newly developed Mo SNAP model will find broad applications in large and long-time scale simulations.

Constructing Flexible, Configurable, ETL Pipelines for the Analysis of "Big Data" with Apache OODT

NASA Astrophysics Data System (ADS)

Hart, A. F.; Mattmann, C. A.; Ramirez, P.; Verma, R.; Zimdars, P. A.; Park, S.; Estrada, A.; Sumarlidason, A.; Gil, Y.; Ratnakar, V.; Krum, D.; Phan, T.; Meena, A.

2013-12-01

A plethora of open source technologies for manipulating, transforming, querying, and visualizing 'big data' have blossomed and matured in the last few years, driven in large part by recognition of the tremendous value that can be derived by leveraging data mining and visualization techniques on large data sets. One facet of many of these tools is that input data must often be prepared into a particular format (e.g.: JSON, CSV), or loaded into a particular storage technology (e.g.: HDFS) before analysis can take place. This process, commonly known as Extract-Transform-Load, or ETL, often involves multiple well-defined steps that must be executed in a particular order, and the approach taken for a particular data set is generally sensitive to the quantity and quality of the input data, as well as the structure and complexity of the desired output. When working with very large, heterogeneous, unstructured or semi-structured data sets, automating the ETL process and monitoring its progress becomes increasingly important. Apache Object Oriented Data Technology (OODT) provides a suite of complementary data management components called the Process Control System (PCS) that can be connected together to form flexible ETL pipelines as well as browser-based user interfaces for monitoring and control of ongoing operations. The lightweight, metadata driven middleware layer can be wrapped around custom ETL workflow steps, which themselves can be implemented in any language. Once configured, it facilitates communication between workflow steps and supports execution of ETL pipelines across a distributed cluster of compute resources. As participants in a DARPA-funded effort to develop open source tools for large-scale data analysis, we utilized Apache OODT to rapidly construct custom ETL pipelines for a variety of very large data sets to prepare them for analysis and visualization applications. We feel that OODT, which is free and open source software available through the Apache Software Foundation, is particularly well suited to developing and managing arbitrary large-scale ETL processes both for the simplicity and flexibility of its wrapper framework, as well as the detailed provenance information it exposes throughout the process. Our experience using OODT to manage processing of large-scale data sets in domains as diverse as radio astronomy, life sciences, and social network analysis demonstrates the flexibility of the framework, and the range of potential applications to a broad array of big data ETL challenges.

The impact of galactic disc environment on star-forming clouds

NASA Astrophysics Data System (ADS)

Nguyen, Ngan K.; Pettitt, Alex R.; Tasker, Elizabeth J.; Okamoto, Takashi

2018-03-01

We explore the effect of different galactic disc environments on the properties of star-forming clouds through variations in the background potential in a set of isolated galaxy simulations. Rising, falling, and flat rotation curves expected in halo-dominated, disc-dominated, and Milky Way-like galaxies were considered, with and without an additional two-arm spiral potential. The evolution of each disc displayed notable variations that are attributed to different regimes of stability, determined by shear and gravitational collapse. The properties of a typical cloud were largely unaffected by the changes in rotation curve, but the production of small and large cloud associations was strongly dependent on this environment. This suggests that while differing rotation curves can influence where clouds are initially formed, the average bulk properties are effectively independent of the global environment. The addition of a spiral perturbation made the greatest difference to cloud properties, successfully sweeping the gas into larger, seemingly unbound, extended structures and creating large arm-interarm contrasts.

Shearing black holes and scans of the quark matter phase diagram

NASA Astrophysics Data System (ADS)

McInnes, Brett

2014-01-01

Future facilities such as FAIR and NICA are expected to produce collisions of heavy ions generating quark-gluon plasmas (QGPs) with large values of the quark chemical potential; peripheral collisions in such experiments will also lead to large values of the angular momentum density, associated with the internal shearing motion of the plasma. It is well known that shearing motions in fluids can lead to instabilities which cause a transition from laminar to turbulent flow, and such instabilities in the QGP have recently attracted some attention. We set up a holographic model of this situation by constructing a gravitational dual system exhibiting an instability which is indeed triggered by shearing angular momentum in the bulk. We show that holography indicates that the transition to an unstable fluid happens more quickly as one scans across the quark matter phase diagram towards large values of the chemical potential. This may have negative consequences for the observability of quark polarization effects.

[siRNAs with high specificity to the target: a systematic design by CRM algorithm].

PubMed

Alsheddi, T; Vasin, L; Meduri, R; Randhawa, M; Glazko, G; Baranova, A

2008-01-01

'Off-target' silencing effect hinders the development of siRNA-based therapeutic and research applications. Common solution to this problem is an employment of the BLAST that may miss significant alignments or an exhaustive Smith-Waterman algorithm that is very time-consuming. We have developed a Comprehensive Redundancy Minimizer (CRM) approach for mapping all unique sequences ("targets") 9-to-15 nt in size within large sets of sequences (e.g. transcriptomes). CRM outputs a list of potential siRNA candidates for every transcript of the particular species. These candidates could be further analyzed by traditional "set-of-rules" types of siRNA designing tools. For human, 91% of transcripts are covered by candidate siRNAs with kernel targets of N = 15. We tested our approach on the collection of previously described experimentally assessed siRNAs and found that the correlation between efficacy and presence in CRM-approved set is significant (r = 0.215, p-value = 0.0001). An interactive database that contains a precompiled set of all human siRNA candidates with minimized redundancy is available at http://129.174.194.243. Application of the CRM-based filtering minimizes potential "off-target" silencing effects and could improve routine siRNA applications.

Promoting safe motherhood through the private sector in low- and middle-income countries.

PubMed Central

Brugha, Ruair; Pritze-Aliassime, Susanne

2003-01-01

The formal private sector could play a significant role in determining whether success or failure is achieved in working towards goals for safe motherhood in many low- and middle-income settings. Established private providers, especially nurses/midwives, have the potential to contribute to safe motherhood practices if they are involved in the care continuum. However, they have largely been overlooked by policy-makers in low-income settings. The private sector (mainly doctors) contributes to overprovision and high Caesarean section rates in settings where it provides care to wealthier segments of the population; such care is often funded through third-party payment schemes. In poorer settings, especially rural areas, private nurses/midwives and the women who choose to use them are likely to experience similar constraints to those encountered in the public sector - for example, poor or unaffordable access to higher level facilities for the management of obstetrical emergencies. Policy-makers at the country-level need to map the health system and understand the nature and distribution of the private sector, and what influences it. This potential resource could then be mobilized to work towards the achievement of safe motherhood goals. PMID:14576894

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Initial Validation of Robotic Operations for In-Space Assembly of a Large Solar Electric Propulsion Transport Vehicle

NASA Technical Reports Server (NTRS)

Komendera, Erik E.; Dorsey, John T.

2017-01-01

Developing a capability for the assembly of large space structures has the potential to increase the capabilities and performance of future space missions and spacecraft while reducing their cost. One such application is a megawatt-class solar electric propulsion (SEP) tug, representing a critical transportation ability for the NASA lunar, Mars, and solar system exploration missions. A series of robotic assembly experiments were recently completed at Langley Research Center (LaRC) that demonstrate most of the assembly steps for the SEP tug concept. The assembly experiments used a core set of robotic capabilities: long-reach manipulation and dexterous manipulation. This paper describes cross-cutting capabilities and technologies for in-space assembly (ISA), applies the ISA approach to a SEP tug, describes the design and development of two assembly demonstration concepts, and summarizes results of two sets of assembly experiments that validate the SEP tug assembly steps.

Confronting Practical Problems for Initiation of On-line Hemodiafiltration Therapy.

PubMed

Kim, Yang Wook; Park, Sihyung

2016-06-01

Conventional hemodialysis, which is based on the diffusive transport of solutes, is the most widely used renal replacement therapy. It effectively removes small solutes such as urea and corrects fluid, electrolyte and acid-base imbalance. However, solute diffusion coefficients decreased rapidly as molecular size increased. Because of this, middle and large molecules are not removed effectively and clinical problem such as dialysis amyloidosis might occur. Online hemodiafiltration which is combined by diffusive and convective therapies can overcome such problems by removing effectively middle and large solutes. Online hemodiafiltration is safe, very effective, economically affordable, improving session tolerance and may improve the mortality superior to high flux hemodialysis. However, there might be some potential limitations for setting up online hemodiafiltaration. In this article, we review the uremic toxins associated with dialysis, definition of hemodiafiltration, indication and prescription of hemodiafiltration and the limitations of setting up hemodiafiltration.

Distribution of subtidal sedimentary bedforms in a macrotidal setting: The Bay of Fundy, Atlantic Canada

NASA Astrophysics Data System (ADS)

Todd, Brian J.; Shaw, John; Li, Michael Z.; Kostylev, Vladimir E.; Wu, Yongsheng

2014-07-01

The Bay of Fundy, Canada, a large macrotidal embayment with the World's highest recorded tides, was mapped using multibeam sonar systems. High-resolution imagery of seafloor terrain and backscatter strength, combined with geophysical and sampling data, reveal for the first time the morphology, architecture, and spatial relationships of a spectrum of bedforms: (1) flow-transverse bedforms occur as both discrete large two-dimensional dunes and as three-dimensional dunes in sand sheets; (2) flow-parallel bedforms are numerous straight ridges described by others as horse mussel bioherms; (3) sets of banner banks that flank prominent headlands and major shoals. The suite of bedforms developed during the Holocene, as tidal energy increased due to the bay approaching resonance. We consider the evolution of these bedforms, their migration potential and how they may place limitations on future in-stream tidal power development in the Bay of Fundy.

Reuse of clinical data.

PubMed

Safran, C

2014-08-15

To provide an overview of the benefits of clinical data collected as a by-product of the care process, the potential problems with large aggregations of these data, the policy frameworks that have been formulated, and the major challenges in the coming years. This report summarizes some of the major observations from AMIA and IMIA conferences held on this admittedly broad topic from 2006 through 2013. This report also includes many unsupported opinions of the author. The benefits of aggregating larger and larger sets of routinely collected clinical data are well documented and of great societal benefit. These large data sets will probably never answer all possible clinical questions for methodological reasons. Non-traditional sources of health data that are patient-sources will pose new data science challenges. If we ever hope to have tools that can rapidly provide evidence for daily practice of medicine we need a science of health data perhaps modeled after the science of astronomy.

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

An improved interatomic potential for xenon in UO2: a combined density functional theory/genetic algorithm approach.

PubMed

Thompson, Alexander E; Meredig, Bryce; Wolverton, C

2014-03-12

We have created an improved xenon interatomic potential for use with existing UO2 potentials. This potential was fit to density functional theory calculations with the Hubbard U correction (DFT + U) using a genetic algorithm approach called iterative potential refinement (IPR). We examine the defect energetics of the IPR-fitted xenon interatomic potential as well as other, previously published xenon potentials. We compare these potentials to DFT + U derived energetics for a series of xenon defects in a variety of incorporation sites (large, intermediate, and small vacant sites). We find the existing xenon potentials overestimate the energy needed to add a xenon atom to a wide set of defect sites representing a range of incorporation sites, including failing to correctly rank the energetics of the small incorporation site defects (xenon in an interstitial and xenon in a uranium site neighboring uranium in an interstitial). These failures are due to problematic descriptions of Xe-O and/or Xe-U interactions of the previous xenon potentials. These failures are corrected by our newly created xenon potential: our IPR-generated potential gives good agreement with DFT + U calculations to which it was not fitted, such as xenon in an interstitial (small incorporation site) and xenon in a double Schottky defect cluster (large incorporation site). Finally, we note that IPR is very flexible and can be applied to a wide variety of potential forms and materials systems, including metals and EAM potentials.

Heavy quarkonium hybrids: Spectrum, decay, and mixing

NASA Astrophysics Data System (ADS)

Oncala, Ruben; Soto, Joan

2017-07-01

We present a largely model-independent analysis of the lighter heavy quarkonium hybrids based on the strong coupling regime of potential nonrelativistic QCD. We calculate the spectrum at leading order, including the mixing of static hybrid states. We use potentials that fulfill the required short and long distance theoretical constraints and fit well the available lattice data. We argue that the decay width to the lower lying heavy quarkonia can be reliably estimated in some cases and provide results for a selected set of decays. We also consider the mixing with heavy quarkonium states. We establish the form of the mixing potential at O (1 /mQ) , mQ being the mass of the heavy quarks, and work out its short and long distance constraints. The weak coupling regime of potential nonrelativistic QCD and the effective string theory of QCD are used for that goal. We show that the mixing effects may indeed be important and produce large spin symmetry violations. Most of the isospin zero XYZ states fit well in our spectrum, either as a hybrid or standard quarkonium candidate.

Slide Set: Reproducible image analysis and batch processing with ImageJ.

PubMed

Nanes, Benjamin A

2015-11-01

Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.

A combining rule calculation of the ground-state van der Waals potentials of the magnesium rare-gas complexes

NASA Astrophysics Data System (ADS)

Saidi, Samah; Alharzali, Nissrin; Berriche, Hamid

2017-04-01

The potential energy curves and spectroscopic constants of the ground-state of the Mg-Rg (Rg = He, Ne, Ar, Kr, and Xe) van der Waals complexes are generated by the Tang-Toennies potential model and a set of derived combining rules. The parameters of the model are calculated from the potentials of the homonuclear magnesium and rare-gas dimers. The predicted spectroscopic constants are comparable to other available theoretical and experimental results, except in the case of Mg-He, we note that there are large differences between various determinations. Moreover, in order to reveal relative differences between species more obviously we calculated the reduced potential of these five systems. The curves are clumped closely together, but at intermediate range the Mg-He reduced potential is clearly very different from the others.

Routine health insurance data for scientific research: potential and limitations of the Agis Health Database.

PubMed

Smeets, Hugo M; de Wit, Niek J; Hoes, Arno W

2011-04-01

Observational studies performed within routine health care databases have the advantage of their large size and, when the aim is to assess the effect of interventions, can offer a completion to randomized controlled trials with usually small samples from experimental situations. Institutional Health Insurance Databases (HIDs) are attractive for research because of their large size, their longitudinal perspective, and their practice-based information. As they are based on financial reimbursement, the information is generally reliable. The database of one of the major insurance companies in the Netherlands, the Agis Health Database (AHD), is described in detail. Whether the AHD data sets meet the specific requirements to conduct several types of clinical studies is discussed according to the classification of the four different types of clinical research; that is, diagnostic, etiologic, prognostic, and intervention research. The potential of the AHD for these various types of research is illustrated using examples of studies recently conducted in the AHD. HIDs such as the AHD offer large potential for several types of clinical research, in particular etiologic and intervention studies, but at present the lack of detailed clinical information is an important limitation. Copyright © 2011 Elsevier Inc. All rights reserved.

Investigation of the Large Scale Evolution and Topology of Coronal Mass Ejections in the Solar Wind

NASA Technical Reports Server (NTRS)

Riley, Peter

1999-01-01

This investigation is concerned with the large-scale evolution and topology of Coronal Mass Ejections (CMEs) in the solar wind. During this reporting period we have analyzed a series of low density intervals in the ACE (Advanced Composition Explorer) plasma data set that bear many similarities to CMEs. We have begun a series of 3D, MHD (Magnetohydrodynamics) coronal models to probe potential causes of these events. We also edited two manuscripts concerning the properties of CMEs in the solar wind. One was re-submitted to the Journal of Geophysical Research.

Large-Scale Analysis of Network Bistability for Human Cancers

PubMed Central

Shiraishi, Tetsuya; Matsuyama, Shinako; Kitano, Hiroaki

2010-01-01

Protein–protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers. PMID:20628618

Equation of motion coupled cluster methods for electron attachment and ionization potential in polyacenes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhaskaran-Nair, Kiran; Kowalski, Karol; Jarrell, Mark

2015-11-05

Polyacenes have attracted considerable attention due to their use in organic based optoelectronic materials. Polyacenes are polycyclic aromatic hydrocarbons composed of fused benzene rings. Key to understanding and design of new functional materials is an understanding of their excited state properties starting with their electron affinity (EA) and ionization potential (IP). We have developed a highly accurate and com- putationally e*fficient EA/IP equation of motion coupled cluster singles and doubles (EA/IP-EOMCCSD) method that is capable of treating large systems and large basis set. In this study we employ the EA/IP-EOMCCSD method to calculate the electron affinity and ionization potential ofmore » naphthalene, anthracene, tetracene, pentacene, hex- acene and heptacene. We have compared our results with other previous theoretical studies and experimental data. Our EA/IP results are in very good agreement with experiment and when compared with the other theoretical investigations our results represent the most accurate calculations as compared to experiment.« less

Decolonization of patients and health care workers to control nosocomial spread of methicillin-resistant Staphylococcus aureus: a simulation study.

PubMed

Gurieva, Tatiana V; Bootsma, Martin C J; Bonten, Marc J M

2012-11-14

Control of methicillin-resistant Staphylococcus aureus (MRSA) transmission has been unsuccessful in many hospitals. Recommended control measures include isolation of colonized patients, rather than decolonization of carriage among patients and/or health care workers. Yet, the potential effects of such measures are poorly understood. We use a stochastic simulation model in which health care workers can transmit MRSA through short-lived hand contamination, or through persistent colonization. Hand hygiene interrupts the first mode, decolonization strategies the latter. We quantified the effectiveness of decolonization of patients and health care workers, relative to patient isolation in settings where MRSA carriage is endemic (rather than sporadic outbreaks in non-endemic settings caused by health care workers). Patient decolonization is the most effective intervention and outperforms patient isolation, even with low decolonization efficacy and when decolonization is not achieved immediately. The potential role of persistently colonized health care workers in MRSA transmission depends on the proportion of persistently colonized health care workers and the likelihood per colonized health care worker to transmit. As stand-alone intervention, universal screening and decolonization of persistently colonized health care workers is generally the least effective intervention, especially in high endemicity settings. When added to patient isolation, such a strategy would have maximum benefits if few health care workers cause a large proportion of the acquisitions. In high-endemicity settings regular screening of health care workers followed by decolonization of MRSA-carriers is unlikely to reduce nosocomial spread of MRSA unless there are few persistently colonized health care workers who are responsible for a large fraction of the MRSA acquisitions by patients. In contrast, decolonization of patients can be very effective.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Palaeogeography of late Cambrian to early Ordovician sediments in the Amadeus Basin, central Australia

NASA Astrophysics Data System (ADS)

Gorter, John D.

The depositional history of 6 sequences encompassing 18 parasequence of the Late Cambrian to Early Ordovician age in the Amadeus Basin is presented in a seried of generalized paleogeographic maps. As some of the parasequence sets are known to host large deposits of oil and gas, a thorough understanding of the potential reservoir-source rock combinations in the Amadeus Basin is essential for the discovery of further oil and gas reserves in this vast, under-explored basin. The best reservoir rocks in the Pacoota Sandstone are concentrated above the major sequence boundary between the Wallaby and Tempe Vale sequences on the Central Ridge. Poorer reservoirs occur within other sequences (e.g., parasequence set 3 and 13). Parasequence set 3 reservoirs, localized on the Central Ridge, are generally poor but owe their reservoir character to weathering at the pre-Tempe Vale sequence unconformity. Parasequence set 13 reservoirs are also concenterated along the Central Ridge, where small-scale shoaling clastic cycles are better developed. Basal Stairway Sandstone reservoirs in the Mereenie area on the Central Ridge are generally very poor, due to the cementation of the clean sandstone, but should improve to the southwest due to lesser burial-induced silicification. The source potential of the major Arenig organic-rich sediments is concentrated in the transitional zone between parasequence sets 15 and 16. East of West Waterhouse 1 well, these parasequence sets have been eroded and there is no remaining source potential. The transitional source-rich zone is better developed on the Central Ridge than in the Missionary Plain Trough. The Central Ridge is therefore of prime importance in the localization of both reservoir and source rocks in the Late Cambrian and Early Ordovician section of the Amadeus Basin.

Solar Energy Economics Revisited: The Promise and Challenge of Orbiting Reflectors for World Energy Supply

NASA Technical Reports Server (NTRS)

Billman, Kenneth W.; Gilbreath, William P.; Bowen, Stuart W.

1978-01-01

A system of orbiting, large-area, low mass density reflector satellites which provide nearly continuous solar energy to a world-distributed set of conversion sites is examined under the criteria for any potential new energy system: technical feasibility, significant and renewable energy impact, economic feasibility and social/political acceptability. Although many technical issues need further study, reasonable advances in space technology appear sufficient to implement the system. The enhanced insolation is shown to greatly improve the economic competitiveness of solar-electric generation to circa 1995 fossil/nuclear alternatives. The system is shown to have the potential for supplying a significant fraction of future domestic and world energy needs. Finally, the environmental and social issues, including a means for financing such a large shift to a world solar energy dependence, is addressed.

The Effectiveness of Instructor Personalized and Formative Feedback Provided by Instructor in an Online Setting: Some Unresolved Issues

ERIC Educational Resources Information Center

Planar, Dolors; Moya, Soledad

2016-01-01

Formative feedback has great potential for teaching and learning in online undergraduate programmes. There is a large number of courses where the main source of feedback is provided by the instructor. This is particularly seen in subjects where assessments are designed based on specific activities which are the same for all students, and where the…

Rates and determinants of uptake and use of an internet physical activity and weight management program in office and manufacturing work sites in England: Cohort Study

USDA-ARS?s Scientific Manuscript database

Internet-based physical activity (PA) and weight management programs have the potential to improve employees' health in large occupational health settings. To be successful, the program must engage a wide range of employees, especially those at risk of weight gain or ill health. The aim of the study...

Effects of Peer-Assessed Feedback, Goal Setting and a Group Contingency on Performance and Learning by 10-12-Year-Old Academy Soccer Players

ERIC Educational Resources Information Center

Holt, Josh E.; Kinchin, Gary; Clarke, Gill

2012-01-01

Background: Coaches developing young talent in team sports must maximise practice and learning of essential game skills and accurately and continuously assess the performance and potential of each player. Relative age effects highlight an erroneous process of initial and on-going player assessment, based largely on subjective opinions of game…

Dielectric capacitors with three-dimensional nanoscale interdigital electrodes for energy storage.

PubMed

Han, Fangming; Meng, Guowen; Zhou, Fei; Song, Li; Li, Xinhua; Hu, Xiaoye; Zhu, Xiaoguang; Wu, Bing; Wei, Bingqing

2015-10-01

Dielectric capacitors are promising candidates for high-performance energy storage systems due to their high power density and increasing energy density. However, the traditional approach strategies to enhance the performance of dielectric capacitors cannot simultaneously achieve large capacitance and high breakdown voltage. We demonstrate that such limitations can be overcome by using a completely new three-dimensional (3D) nanoarchitectural electrode design. First, we fabricate a unique nanoporous anodic aluminum oxide (AAO) membrane with two sets of interdigitated and isolated straight nanopores opening toward opposite planar surfaces. By depositing carbon nanotubes in both sets of pores inside the AAO membrane, the new dielectric capacitor with 3D nanoscale interdigital electrodes is simply realized. In our new capacitors, the large specific surface area of AAO can provide large capacitance, whereas uniform pore walls and hemispheric barrier layers can enhance breakdown voltage. As a result, a high energy density of 2 Wh/kg, which is close to the value of a supercapacitor, can be achieved, showing promising potential in high-density electrical energy storage for various applications.

Dielectric capacitors with three-dimensional nanoscale interdigital electrodes for energy storage

PubMed Central

Han, Fangming; Meng, Guowen; Zhou, Fei; Song, Li; Li, Xinhua; Hu, Xiaoye; Zhu, Xiaoguang; Wu, Bing; Wei, Bingqing

2015-01-01

Dielectric capacitors are promising candidates for high-performance energy storage systems due to their high power density and increasing energy density. However, the traditional approach strategies to enhance the performance of dielectric capacitors cannot simultaneously achieve large capacitance and high breakdown voltage. We demonstrate that such limitations can be overcome by using a completely new three-dimensional (3D) nanoarchitectural electrode design. First, we fabricate a unique nanoporous anodic aluminum oxide (AAO) membrane with two sets of interdigitated and isolated straight nanopores opening toward opposite planar surfaces. By depositing carbon nanotubes in both sets of pores inside the AAO membrane, the new dielectric capacitor with 3D nanoscale interdigital electrodes is simply realized. In our new capacitors, the large specific surface area of AAO can provide large capacitance, whereas uniform pore walls and hemispheric barrier layers can enhance breakdown voltage. As a result, a high energy density of 2 Wh/kg, which is close to the value of a supercapacitor, can be achieved, showing promising potential in high-density electrical energy storage for various applications. PMID:26601294

Disparate Tectonic Settings of Devastating Earthquakes in Mexico, September 2017

NASA Astrophysics Data System (ADS)

Li, J.; Chen, W. P.; Ning, J.

2017-12-01

Large earthquakes associated with thrust faulting along the plate interface typically pose the highest seismic risk along subduction zones. However, both damaging earthquakes in Mexico of September 2017 are notable exceptions. The Tehuantepec event on the 8th (Mw 8.1) occurred just landward of the trench but is associated with normal faulting, akin to the large (Ms 8) historical event of 1931 that occurred about 200 km to the northwest along this subduction zone. The Puebla earthquake (on the 19th, Mw 7.1) occurred almost 300 km away from the trench where seismic imaging had indicated that the flat-lying slab steepens abruptly and plunges aseismically into the deep mantle. Here we show that both types of tectonic settings are in fact common along a large portion of the Mexican subduction zone, thus identifying source zones of potentially damaging earthquakes away from the plate interface. Additionally, modeling of broadband waveforms made clear that another significant event (Mw 6.1) on the 23rd, is associated with shallow normal faulting in the upper crust, not directly related to the two damaging earthquakes.

Disentangling multidimensional spatio-temporal data into their common and aberrant responses

DOE PAGES

Chang, Young Hwan; Korkola, James; Amin, Dhara N.; ...

2015-04-22

With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures andmore » how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data.« less

Priority setting in guideline development: article 2 in Integrating and coordinating efforts in COPD guideline development. An official ATS/ERS workshop report.

PubMed

Atkins, David; Perez-Padilla, Rogelio; Macnee, William; Buist, A Sonia; Cruz, Alvaro A

2012-12-01

Professional societies, like many other organizations around the world, have recognized the need to use more rigorous processes to ensure that health care recommendations are informed by the best available research evidence. Priority setting is an essential component of developing clinical practice guidelines informed by the best available research evidence. It ensures that resources and attention are devoted to those areas in which clinical recommendations will provide the greatest benefit to patients, clinicians, and policy makers. This is the second of a series of 14 articles that methodologists and researchers from around the world prepared to advise guideline developers in respiratory and other diseases. This review focuses on priority setting, addressing five key questions. In this review, we addressed the following questions. (1) At which steps of guideline development should priorities be considered? (2) How do we create an initial list of potential topics within the guideline? (3) What criteria should be used to establish priorities? (4) What parties should be involved and what processes should be used to set priorities? (5)What are the potential challenges of setting priorities? We updated an existing review on priority setting, and searched PubMed and other databases of methodological studies for existing systematic reviews and relevant methodological research. We did not conduct systematic reviews ourselves. Our conclusions are based on available evidence, our own experience working with guideline developers, and workshop discussions. Existing literature on priority setting largely applies to identifying priorities for which guidelines to develop rather than setting priorities for recommendations within a guideline. Nonetheless, there is substantial consensus about the general factors that should be considered in setting priorities. These include the burdens and costs of illness, potential impact of a recommendation, identified deficits or weak points in practice, variation or uncertainty in practice, and availability of evidence. The input of a variety of stakeholders is useful in setting priorities, although informal consultation is used more often than formal methods. Processes for setting priorities remains poorly described in most guidelines.

Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments.

PubMed

Ionescu, Catalin; Papava, Dragos; Olaru, Vlad; Sminchisescu, Cristian

2014-07-01

We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.

Pitfalls of Insulin Pump Clocks

PubMed Central

Reed, Amy J.

2014-01-01

The objective was to raise awareness about the importance of ensuring that insulin pumps internal clocks are set up correctly at all times. This is a very important safety issue because all commercially available insulin pumps are not GPS-enabled (though this is controversial), nor equipped with automatically adjusting internal clocks. Special attention is paid to how basal and bolus dose errors can be introduced by daylight savings time changes, travel across time zones, and am-pm clock errors. Correct setting of insulin pump internal clock is crucial for appropriate insulin delivery. A comprehensive literature review is provided, as are illustrative cases. Incorrect setting can potentially result in incorrect insulin delivery, with potential harmful consequences, if too much or too little insulin is delivered. Daylight saving time changes may not significantly affect basal insulin delivery, given the triviality of the time difference. However, bolus insulin doses can be dramatically affected. Such problems may occur when pump wearers have large variations in their insulin to carb ratio, especially if they forget to change their pump clock in the spring. More worrisome than daylight saving time change is the am-pm clock setting. If this setting is set up incorrectly, both basal rates and bolus doses will be affected. Appropriate insulin delivery through insulin pumps requires correct correlation between dose settings and internal clock time settings. Because insulin pumps are not GPS-enabled or automatically time-adjusting, extra caution should be practiced by patients to ensure correct time settings at all times. Clinicians and diabetes educators should verify the date/time of insulin pumps during patients’ visits, and should remind their patients to always verify these settings. PMID:25355713

Performance of a lateral flow immunochromatography test for the rapid diagnosis of active tuberculosis in a large multicentre study in areas with different clinical settings and tuberculosis exposure levels.

PubMed

Manga, Selene; Perales, Rocio; Reaño, Maria; D'Ambrosio, Lia; Migliori, Giovanni Battista; Amicosante, Massimo

2016-11-01

Tuberculosis (TB) continues to cause an outsized burden of morbidity and mortality worldwide, still missing efficient and largely accessible diagnostic tools determining an appropriate control of the disease. Serological tests have the potentially to impact TB diagnosis, in particular in extreme clinical settings. The diagnostic performances of the TB-XT HEMA EXPRESS (HEMA-EXPRESS) immunochromatographic rapid test for active TB diagnosis, based on use of multiple Mycobacterium tuberculosis (MTB) specific antigens, have been evaluated in a large study multicentre TB case-finding study, in populations with different exposure level to TB. A total of 1,386 subjects were enrolled in the six participating centres in Peru: 290 active-TB and 1,096 unaffected subjects. The TB prevalence (overall 20.5%) varied between 4.0% and 41.1% in the different study groups. Overall, the HEMA-EXPRESS test had 30.6% sensitivity (range 3.9-77.9%) and 84.6% specificity (range 51.6-97.3%). A significant inverse correlation between test accuracy (overall 73.5%, range 40.4-96.4%) and TB prevalence in the various study populations was observed (Pearson's r=-0.7985; P=0.05). HEMA-EXPRESS, is rapid and relatively inexpensive test suitable for routine use in TB diagnosis. In low TB prevalence conditions, test performance appears in line with WHO Target Product Profile for TB diagnostics. Performances appear suboptimal in high TB prevalence settings. Appropriate set-up in operative clinical settings has to be considered for novel serological tests for TB diagnosis, particularly for formats suitable for point-of-care use.

Photoisomerization-induced manipulation of single-electron tunneling for novel Si-based optical memory.

PubMed

Hayakawa, Ryoma; Higashiguchi, Kenji; Matsuda, Kenji; Chikyow, Toyohiro; Wakayama, Yutaka

2013-11-13

We demonstrated optical manipulation of single-electron tunneling (SET) by photoisomerization of diarylethene molecules in a metal-insulator-semiconductor (MIS) structure. Stress is placed on the fact that device operation is realized in the practical device configuration of MIS structure and that it is not achieved in structures based on nanogap electrodes and scanning probe techniques. Namely, this is a basic memory device configuration that has the potential for large-scale integration. In our device, the threshold voltage of SET was clearly modulated as a reversible change in the molecular orbital induced by photoisomerization, indicating that diarylethene molecules worked as optically controllable quantum dots. These findings will allow the integration of photonic functionality into current Si-based memory devices, which is a unique feature of organic molecules that is unobtainable with inorganic materials. Our proposed device therefore has enormous potential for providing a breakthrough in Si technology.

Molecular dynamics simulation of premelting and melting phase transitions in stoichiometric uranium dioxide

NASA Astrophysics Data System (ADS)

Yakub, Eugene; Ronchi, Claudio; Staicu, Dragos

2007-09-01

Results of molecular dynamics (MD) simulation of UO2 in a wide temperature range are presented and discussed. A new approach to the calibration of a partly ionic Busing-Ida-type model is proposed. A potential parameter set is obtained reproducing the experimental density of solid UO2 in a wide range of temperatures. A conventional simulation of the high-temperature stoichiometric UO2 on large MD cells, based on a novel fast method of computation of Coulomb forces, reveals characteristic features of a premelting λ transition at a temperature near to that experimentally observed (Tλ=2670K ). A strong deviation from the Arrhenius behavior of the oxygen self-diffusion coefficient was found in the vicinity of the transition point. Predictions for liquid UO2, based on the same potential parameter set, are in good agreement with existing experimental data and theoretical calculations.

Ab initio structural and spectroscopic study of HPS{sup x} and HSP{sup x} (x = 0,+1,−1) in the gas phase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yaghlane, Saida Ben; Cotton, C. Eric; Francisco, Joseph S., E-mail: francisc@purdue.edu, E-mail: hochlaf@univ-mlv.fr

2013-11-07

Accurate ab initio computations of structural and spectroscopic parameters for the HPS/HSP molecules and corresponding cations and anions have been performed. For the electronic structure computations, standard and explicitly correlated coupled cluster techniques in conjunction with large basis sets have been adopted. In particular, we present equilibrium geometries, rotational constants, harmonic vibrational frequencies, adiabatic ionization energies, electron affinities, and, for the neutral species, singlet-triplet relative energies. Besides, the full-dimensional potential energy surfaces (PESs) for HPS{sup x} and HSP{sup x} (x = −1,0,1) systems have been generated at the standard coupled cluster level with a basis set of augmented quintuple-zeta quality.more » By applying perturbation theory to the calculated PESs, an extended set of spectroscopic constants, including τ, first-order centrifugal distortion and anharmonic vibrational constants has been obtained. In addition, the potentials have been used in a variational approach to deduce the whole pattern of vibrational levels up to 4000 cm{sup −1} above the minima of the corresponding PESs.« less

Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids.

PubMed

Cao, Lingdi; Zhu, Peng; Zhao, Yongsheng; Zhao, Jihong

2018-06-15

Large-scale application of ionic liquids (ILs) hinges on the advancement of designable and eco-friendly nature. Research of the potential toxicity of ILs towards different organisms and trophic levels is insufficient. Quantitative structure-activity relationships (QSAR) model is applied to evaluate the toxicity of ILs towards the leukemia rat cell line (ICP-81). The structures of 57 cations and 21 anions were optimized by quantum chemistry. The electrostatic potential surface area (S EP ) and charge distribution area (S σ-profile ) descriptors are calculated and used to predict the toxicity of ILs. The performance and predictive aptitude of extreme learning machine (ELM) model are analyzed and compared with those of multiple linear regression (MLR) and support vector machine (SVM) models. The highest R 2 and the lowest AARD% and RMSE of the training set, test set and total set for the ELM are observed, which validates the superior performance of the ELM than that of obtained by the MLR and SVM. The applicability domain of the model is assessed by the Williams plot. Copyright © 2018 Elsevier B.V. All rights reserved.

An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.

PubMed

Fitzpatrick, J M; Roberts, D W; Patlewicz, G

2018-06-01

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.

Projection of participant recruitment to primary care research: a qualitative study.

PubMed

White, David; Hind, Daniel

2015-10-20

Recruitment to clinical trials remains a challenge, particularly in primary care settings. Initial projections of participant recruitment need to be as accurate as possible in order to avoid the financial, clinical and ethical costs of trial extensions or failures. However, estimation of recruitment rates is challenging and often poorly executed, if attempted at all. We used qualitative methods to explore the experiences and views of researchers on the planning of recruitment in this setting. Participants had registered accrual to a UK-based primary care research study between April 2009 and March 2012. We conducted nine interviews with chief investigators or study managers, using a semi-structured topic guide. Analysis was conducted using the framework approach. Three themes are presented: 1) the factors affecting recruitment rates, 2) the use of planning techniques, and 3) influences on poor estimation. 1) A large number of factors affecting recruitment rates were discussed, including those relating to the study protocol, the clinical setting and the research setting. Use of targeted mail-outs to invite apparently eligible individuals to participate was preferred in order to eliminate some of the uncertainty in the recruitment rate associated with opportunistic clinician referrals. 2) The importance of pilot work was stressed. We identified significant uncertainty as to how best to schedule trial timelines to maximise efficiency. 3) Several potential sources of bias involved in the estimation of recruitment rates were explored and framed as technological, psychological or political factors. We found a large number of factors that interviewees felt impact recruitment rates to primary care research and highlighted the complexity of realistic estimation. Suitable early planning of the recruitment process is essential, and there may be potential to improve the projection of trial timelines by reducing biases involved in the process. Further research is needed to develop formal approaches that would be suitable for use in this setting.

Action-Based Dynamical Modelling For The Milky Way Disk

NASA Astrophysics Data System (ADS)

Trick, Wilma; Rix, Hans-Walter; Bovy, Jo

2016-09-01

We present Road Mapping, a full-likelihood dynamical modelling machinery, that aims to recover the Milky Way's (MW) gravitational potential from large samples of stars in the Galactic disk. Road Mapping models the observed positions and velocities of stars with a parameterized, action-based distribution function (DF) in a parameterized axisymmetric gravitational potential (Binney & McMillan 2011, Binney 2012, Bovy & Rix 2013).In anticipation of the Gaia data release in autumn, we have fully tested Road Mapping and demonstrated its robustness against the breakdown of its assumptions.Using large suites of mock data, we investigated in isolated test cases how the modelling would be affected if the data's true potential or DF was not included in the families of potentials and DFs assumed by Road Mapping, or if we misjudged measurement errors or the spatial selection function (SF) (Trick et al., submitted to ApJ). We found that the potential can be robustly recovered — given the limitations of the assumed potential model—, even for minor misjudgments in DF or SF, or for proper motion errors or distances known to within 10%.We were also able to demonstrate that Road Mapping is still successful if the strong assumption of axisymmetric breaks down (Trick et al., in preparation). Data drawn from a highresolution simulation (D'Onghia et al. 2013) of a MW-like galaxy with pronounced spiral arms does neither follow the assumed simple DF, nor does it come from an axisymmetric potential. We found that as long as the survey volume is large enough, Road Mapping gives good average constraints on the galaxy's potential.We are planning to apply Road Mapping to a real data set — the Tycho-2 catalogue (Hog et al. 2000) —very soon, and might be able to present some preliminary results already at the conference.

Carbonate Precipitation through Microbial Activities in Natural Environment, and Their Potential in Biotechnology: A Review

PubMed Central

Zhu, Tingting; Dittrich, Maria

2016-01-01

Calcium carbonate represents a large portion of carbon reservoir and is used commercially for a variety of applications. Microbial carbonate precipitation, a by-product of microbial activities, plays an important metal coprecipitation and cementation role in natural systems. This natural process occurring in various geological settings can be mimicked and used for a number of biotechnologies, such as metal remediation, carbon sequestration, enhanced oil recovery, and construction restoration. In this study, different metabolic activities leading to calcium carbonate precipitation, their native environment, and potential applications and challenges are reviewed. PMID:26835451

Evaluation of linear classifiers on articles containing pharmacokinetic evidence of drug-drug interactions.

PubMed

Kolchinsky, A; Lourenço, A; Li, L; Rocha, L M

2013-01-01

Drug-drug interaction (DDI) is a major cause of morbidity and mortality. DDI research includes the study of different aspects of drug interactions, from in vitro pharmacology, which deals with drug interaction mechanisms, to pharmaco-epidemiology, which investigates the effects of DDI on drug efficacy and adverse drug reactions. Biomedical literature mining can aid both kinds of approaches by extracting relevant DDI signals from either the published literature or large clinical databases. However, though drug interaction is an ideal area for translational research, the inclusion of literature mining methodologies in DDI workflows is still very preliminary. One area that can benefit from literature mining is the automatic identification of a large number of potential DDIs, whose pharmacological mechanisms and clinical significance can then be studied via in vitro pharmacology and in populo pharmaco-epidemiology. We implemented a set of classifiers for identifying published articles relevant to experimental pharmacokinetic DDI evidence. These documents are important for identifying causal mechanisms behind putative drug-drug interactions, an important step in the extraction of large numbers of potential DDIs. We evaluate performance of several linear classifiers on PubMed abstracts, under different feature transformation and dimensionality reduction methods. In addition, we investigate the performance benefits of including various publicly-available named entity recognition features, as well as a set of internally-developed pharmacokinetic dictionaries. We found that several classifiers performed well in distinguishing relevant and irrelevant abstracts. We found that the combination of unigram and bigram textual features gave better performance than unigram features alone, and also that normalization transforms that adjusted for feature frequency and document length improved classification. For some classifiers, such as linear discriminant analysis (LDA), proper dimensionality reduction had a large impact on performance. Finally, the inclusion of NER features and dictionaries was found not to help classification.

Integrated Design of Downwind Land-Based Wind Turbines using Analytic Gradients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ning, Andrew; Petch, Derek

2016-12-01

Wind turbines are complex systems where component-level changes can have significant system-level effects. Effective wind turbine optimization generally requires an integrated analysis approach with a large number of design variables. Optimizing across large variable sets is orders of magnitude more efficient with gradient-based methods as compared with gradient-free method, particularly when using exact gradients. We have developed a wind turbine analysis set of over 100 components where 90% of the models provide numerically exact gradients through symbolic differentiation, automatic differentiation, and adjoint methods. This framework is applied to a specific design study focused on downwind land-based wind turbines. Downwind machinesmore » are of potential interest for large wind turbines where the blades are often constrained by the stiffness required to prevent a tower strike. The mass of these rotor blades may be reduced by utilizing a downwind configuration where the constraints on tower strike are less restrictive. The large turbines of this study range in power rating from 5-7MW and in diameter from 105m to 175m. The changes in blade mass and power production have important effects on the rest of the system, and thus the nacelle and tower systems are also optimized. For high-speed wind sites, downwind configurations do not appear advantageous. The decrease in blade mass (10%) is offset by increases in tower mass caused by the bending moment from the rotor-nacelle-assembly. For low-wind speed sites, the decrease in blade mass is more significant (25-30%) and shows potential for modest decreases in overall cost of energy (around 1-2%).« less

Clinical Supervision of Mental Health Professionals Serving Youth: Format and Microskills.

PubMed

Bailin, Abby; Bearman, Sarah Kate; Sale, Rafaella

2018-03-21

Clinical supervision is an element of quality assurance in routine mental health care settings serving children; however, there is limited scientific evaluation of its components. This study examines the format and microskills of routine supervision. Supervisors (n = 13) and supervisees (n = 20) reported on 100 supervision sessions, and trained coders completed observational coding on a subset of recorded sessions (n = 57). Results indicate that microskills shown to enhance supervisee competency in effectiveness trials and experiments were largely absent from routine supervision, highlighting potential missed opportunities to impart knowledge to therapists. Findings suggest areas for quality improvement within routine care settings.

Fierz-complete NJL model study. II. Toward the fixed-point and phase structure of hot and dense two-flavor QCD

NASA Astrophysics Data System (ADS)

Braun, Jens; Leonhardt, Marc; Pospiech, Martin

2018-04-01

Nambu-Jona-Lasinio-type models are often employed as low-energy models for the theory of the strong interaction to analyze its phase structure at finite temperature and quark chemical potential. In particular, at low temperature and large chemical potential, where the application of fully first-principles approaches is currently difficult at best, this class of models still plays a prominent role in guiding our understanding of the dynamics of dense strong-interaction matter. In this work, we consider a Fierz-complete version of the Nambu-Jona-Lasinio model with two massless quark flavors and study its renormalization group flow and fixed-point structure at leading order of the derivative expansion of the effective action. Sum rules for the various four-quark couplings then allow us to monitor the strength of the breaking of the axial UA(1 ) symmetry close to and above the phase boundary. We find that the dynamics in the ten-dimensional Fierz-complete space of four-quark couplings can only be reduced to a one-dimensional space associated with the scalar-pseudoscalar coupling in the strict large-Nc limit. Still, the interacting fixed point associated with this one-dimensional subspace appears to govern the dynamics at small quark chemical potential even beyond the large-Nc limit. At large chemical potential, corrections beyond the large-Nc limit become important, and the dynamics is dominated by diquarks, favoring the formation of a chirally symmetric diquark condensate. In this regime, our study suggests that the phase boundary is shifted to higher temperatures when a Fierz-complete set of four-quark interactions is considered.

The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

PubMed

Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

2017-01-01

Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

The leukemia-associated Rho guanine nucleotide exchange factor LARG is required for efficient replication stress signaling

PubMed Central

Beveridge, Ryan D; Staples, Christopher J; Patil, Abhijit A; Myers, Katie N; Maslen, Sarah; Skehel, J Mark; Boulton, Simon J; Collis, Spencer J

2014-01-01

We previously identified and characterized TELO2 as a human protein that facilitates efficient DNA damage response (DDR) signaling. A subsequent yeast 2-hybrid screen identified LARG; Leukemia-Associated Rho Guanine Nucleotide Exchange Factor (also known as Arhgef12), as a potential novel TELO2 interactor. LARG was previously shown to interact with Pericentrin (PCNT), which, like TELO2, is required for efficient replication stress signaling. Here we confirm interactions between LARG, TELO2 and PCNT and show that a sub-set of LARG co-localizes with PCNT at the centrosome. LARG-deficient cells exhibit replication stress signaling defects as evidenced by; supernumerary centrosomes, reduced replication stress-induced γH2AX and RPA nuclear foci formation, and reduced activation of the replication stress signaling effector kinase Chk1 in response to hydroxyurea. As such, LARG-deficient cells are sensitive to replication stress-inducing agents such as hydroxyurea and mitomycin C. Conversely we also show that depletion of TELO2 and the replication stress signaling kinase ATR leads to RhoA signaling defects. These data therefore reveal a level of crosstalk between the RhoA and DDR signaling pathways. Given that mutations in both ATR and PCNT can give rise to the related primordial dwarfism disorders of Seckel Syndrome and Microcephalic osteodysplastic primordial dwarfism type II (MOPDII) respectively, which both exhibit defects in ATR-dependent checkpoint signaling, these data also raise the possibility that mutations in LARG or disruption to RhoA signaling may be contributory factors to the etiology of a sub-set of primordial dwarfism disorders. PMID:25485589

The Potential Wind Power Resource in Australia: A New Perspective

PubMed Central

Hallgren, Willow; Gunturu, Udaya Bhaskar; Schlosser, Adam

2014-01-01

Australia’s wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia’s electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia’s energy mix, this study sets out to analyze and interpret the nature of Australia’s wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast’s electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it’s intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale. PMID:24988222

The potential wind power resource in Australia: a new perspective.

PubMed

Hallgren, Willow; Gunturu, Udaya Bhaskar; Schlosser, Adam

2014-01-01

Australia's wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia's electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia's energy mix, this study sets out to analyze and interpret the nature of Australia's wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast's electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it's intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale.

A web-based laboratory information system to improve quality of care of tuberculosis patients in Peru: functional requirements, implementation and usage statistics.

PubMed

Blaya, Joaquin A; Shin, Sonya S; Yagui, Martin J A; Yale, Gloria; Suarez, Carmen Z; Asencios, Luis L; Cegielski, J Peter; Fraser, Hamish S F

2007-10-28

Multi-drug resistant tuberculosis patients in resource-poor settings experience large delays in starting appropriate treatment and may not be monitored appropriately due to an overburdened laboratory system, delays in communication of results, and missing or error-prone laboratory data. The objective of this paper is to describe an electronic laboratory information system implemented to alleviate these problems and its expanding use by the Peruvian public sector, as well as examine the broader issues of implementing such systems in resource-poor settings. A web-based laboratory information system "e-Chasqui" has been designed and implemented in Peru to improve the timeliness and quality of laboratory data. It was deployed in the national TB laboratory, two regional laboratories and twelve pilot health centres. Using needs assessment and workflow analysis tools, e-Chasqui was designed to provide for improved patient care, increased quality control, and more efficient laboratory monitoring and reporting. Since its full implementation in March 2006, 29,944 smear microscopy, 31,797 culture and 7,675 drug susceptibility test results have been entered. Over 99% of these results have been viewed online by the health centres. High user satisfaction and heavy use have led to the expansion of e-Chasqui to additional institutions. In total, e-Chasqui will serve a network of institutions providing medical care for over 3.1 million people. The cost to maintain this system is approximately US$0.53 per sample or 1% of the National Peruvian TB program's 2006 budget. Electronic laboratory information systems have a large potential to improve patient care and public health monitoring in resource-poor settings. Some of the challenges faced in these settings, such as lack of trained personnel, limited transportation, and large coverage areas, are obstacles that a well-designed system can overcome. e-Chasqui has the potential to provide a national TB laboratory network in Peru. Furthermore, the core functionality of e-Chasqui as been implemented in the open source medical record system OpenMRS http://www.openmrs.org for other countries to use.

A web-based laboratory information system to improve quality of care of tuberculosis patients in Peru: functional requirements, implementation and usage statistics

PubMed Central

Blaya, Joaquin A; Shin, Sonya S; Yagui, Martin JA; Yale, Gloria; Suarez, Carmen Z; Asencios, Luis L; Cegielski, J Peter; Fraser, Hamish SF

2007-01-01

Background Multi-drug resistant tuberculosis patients in resource-poor settings experience large delays in starting appropriate treatment and may not be monitored appropriately due to an overburdened laboratory system, delays in communication of results, and missing or error-prone laboratory data. The objective of this paper is to describe an electronic laboratory information system implemented to alleviate these problems and its expanding use by the Peruvian public sector, as well as examine the broader issues of implementing such systems in resource-poor settings. Methods A web-based laboratory information system "e-Chasqui" has been designed and implemented in Peru to improve the timeliness and quality of laboratory data. It was deployed in the national TB laboratory, two regional laboratories and twelve pilot health centres. Using needs assessment and workflow analysis tools, e-Chasqui was designed to provide for improved patient care, increased quality control, and more efficient laboratory monitoring and reporting. Results Since its full implementation in March 2006, 29,944 smear microscopy, 31,797 culture and 7,675 drug susceptibility test results have been entered. Over 99% of these results have been viewed online by the health centres. High user satisfaction and heavy use have led to the expansion of e-Chasqui to additional institutions. In total, e-Chasqui will serve a network of institutions providing medical care for over 3.1 million people. The cost to maintain this system is approximately US$0.53 per sample or 1% of the National Peruvian TB program's 2006 budget. Conclusion Electronic laboratory information systems have a large potential to improve patient care and public health monitoring in resource-poor settings. Some of the challenges faced in these settings, such as lack of trained personnel, limited transportation, and large coverage areas, are obstacles that a well-designed system can overcome. e-Chasqui has the potential to provide a national TB laboratory network in Peru. Furthermore, the core functionality of e-Chasqui as been implemented in the open source medical record system OpenMRS for other countries to use. PMID:17963522

Methods for the computation of detailed geoids and their accuracy

NASA Technical Reports Server (NTRS)

Rapp, R. H.; Rummel, R.

1975-01-01

Two methods for the computation of geoid undulations using potential coefficients and 1 deg x 1 deg terrestrial anomaly data are examined. It was found that both methods give the same final result but that one method allows a more simplified error analysis. Specific equations were considered for the effect of the mass of the atmosphere and a cap dependent zero-order undulation term was derived. Although a correction to a gravity anomaly for the effect of the atmosphere is only about -0.87 mgal, this correction causes a fairly large undulation correction that was not considered previously. The accuracy of a geoid undulation computed by these techniques was estimated considering anomaly data errors, potential coefficient errors, and truncation (only a finite set of potential coefficients being used) errors. It was found that an optimum cap size of 20 deg should be used. The geoid and its accuracy were computed in the Geos 3 calibration area using the GEM 6 potential coefficients and 1 deg x 1 deg terrestrial anomaly data. The accuracy of the computed geoid is on the order of plus or minus 2 m with respect to an unknown set of best earth parameter constants.

Effects of hippocampal lesions on the monkey's ability to learn large sets of object-place associations.

PubMed

Belcher, Annabelle M; Harrington, Rebecca A; Malkova, Ludise; Mishkin, Mortimer

2006-01-01

Earlier studies found that recognition memory for object-place associations was impaired in patients with relatively selective hippocampal damage (Vargha-Khadem et al., Science 1997; 277:376-380), but was unaffected after selective hippocampal lesions in monkeys (Malkova and Mishkin, J Neurosci 2003; 23:1956-1965). A potentially important methodological difference between the two studies is that the patients were required to remember a set of 20 object-place associations for several minutes, whereas the monkeys had to remember only two such associations at a time, and only for a few seconds. To approximate more closely the task given to the patients, we trained monkeys on several successive sets of 10 object-place pairs each, with each set requiring learning across days. Despite the increased associative memory demands, monkeys given hippocampal lesions were unimpaired relative to their unoperated controls, suggesting that differences other than set size and memory duration underlie the different outcomes in the human and animal studies. (c) 2005 Wiley-Liss, Inc.

Can a pairwise contact potential stabilize native protein folds against decoys obtained by threading?

PubMed

Vendruscolo, M; Najmanovich, R; Domany, E

2000-02-01

We present a method to derive contact energy parameters from large sets of proteins. The basic requirement on which our method is based is that for each protein in the database the native contact map has lower energy than all its decoy conformations that are obtained by threading. Only when this condition is satisfied one can use the proposed energy function for fold identification. Such a set of parameters can be found (by perceptron learning) if Mp, the number of proteins in the database, is not too large. Other aspects that influence the existence of such a solution are the exact definition of contact and the value of the critical distance Rc, below which two residues are considered to be in contact. Another important novel feature of our approach is its ability to determine whether an energy function of some suitable proposed form can or cannot be parameterized in a way that satisfies our basic requirement. As a demonstration of this, we determine the region in the (Rc, Mp) plane in which the problem is solvable, i.e., we can find a set of contact parameters that stabilize simultaneously all the native conformations. We show that for large enough databases the contact approximation to the energy cannot stabilize all the native folds even against the decoys obtained by gapless threading.

Simulation Tools for Digital LSI (Large Scale Integration) Design.

DTIC Science & Technology

1983-09-01

potential paths e:,,t from a t.,sde to t alnd (,A I isl gc’, , that It iioht he coton ilci, ilt d I:eriniiie d f ’ Ti.. ’he o diti ns for %0l’h , i p th...the flag is set during an execution of the code, another iteration is performed; otherwise, the subroutine is finished . The following is an extended

Hydrologic Effects of Global Climate Change on a Large Drained Pine Forest

Treesearch

Devendra M. Amatya; Ge Sun; R. W. Skaggs; G. M Chescheir; J. E. Nettles

2006-01-01

A simulation study using a watershed scale forest hydrology model (DRAINWAT) was conducted to evaluate potential effects of climate change on the hydrology of a 3,000 ha managed pine forest in coastal North Carolina. The model was first validated with a five-year (1996-2000) data set fro111 the study site and then run with 50-years (1951-00) of historic weather data...

Managing protected health information in distributed research network environments: automated review to facilitate collaboration

PubMed Central

2013-01-01

Background Multi-site health sciences research is becoming more common, as it enables investigation of rare outcomes and diseases and new healthcare innovations. Multi-site research usually involves the transfer of large amounts of research data between collaborators, which increases the potential for accidental disclosures of protected health information (PHI). Standard protocols for preventing release of PHI are extremely vulnerable to human error, particularly when the shared data sets are large. Methods To address this problem, we developed an automated program (SAS macro) to identify possible PHI in research data before it is transferred between research sites. The macro reviews all data in a designated directory to identify suspicious variable names and data patterns. The macro looks for variables that may contain personal identifiers such as medical record numbers and social security numbers. In addition, the macro identifies dates and numbers that may identify people who belong to small groups, who may be identifiable even in the absences of traditional identifiers. Results Evaluation of the macro on 100 sample research data sets indicated a recall of 0.98 and precision of 0.81. Conclusions When implemented consistently, the macro has the potential to streamline the PHI review process and significantly reduce accidental PHI disclosures. PMID:23521861

Using Landsat Surface Reflectance Data as a Reference Target for Multiswath Hyperspectral Data Collected Over Mixed Agricultural Rangeland Areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra

Low-cost flight-based hyperspectral imaging systems have the potential to provide important information for ecosystem and environmental studies as well as aide in land management. To realize this potential, methods must be developed to provide large-area surface reflectance data allowing for temporal data sets at the mesoscale. This paper describes a bootstrap method of producing a large-area, radiometrically referenced hyperspectral data set using the Landsat surface reflectance (LaSRC) data product as a reference target. The bootstrap method uses standard hyperspectral processing techniques that are extended to remove uneven illumination conditions between flight passes, allowing for radiometrically self-consistent data after mosaicking. Throughmore » selective spectral and spatial resampling, LaSRC data are used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from two hyperspectral flights over the same managed agricultural and unmanaged range land covering approximately 5.8 km 2 acquired on June 21, 2014 and June 24, 2015 are presented. As a result, data from a flight over agricultural land collected on June 6, 2016 are compared with concurrently collected ground-based reflectance spectra as a means of validation.« less

Using Landsat Surface Reflectance Data as a Reference Target for Multiswath Hyperspectral Data Collected Over Mixed Agricultural Rangeland Areas

DOE PAGES

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra; ...

2017-07-25

Low-cost flight-based hyperspectral imaging systems have the potential to provide important information for ecosystem and environmental studies as well as aide in land management. To realize this potential, methods must be developed to provide large-area surface reflectance data allowing for temporal data sets at the mesoscale. This paper describes a bootstrap method of producing a large-area, radiometrically referenced hyperspectral data set using the Landsat surface reflectance (LaSRC) data product as a reference target. The bootstrap method uses standard hyperspectral processing techniques that are extended to remove uneven illumination conditions between flight passes, allowing for radiometrically self-consistent data after mosaicking. Throughmore » selective spectral and spatial resampling, LaSRC data are used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from two hyperspectral flights over the same managed agricultural and unmanaged range land covering approximately 5.8 km 2 acquired on June 21, 2014 and June 24, 2015 are presented. As a result, data from a flight over agricultural land collected on June 6, 2016 are compared with concurrently collected ground-based reflectance spectra as a means of validation.« less

MicroRNA signatures in B-cell lymphomas

PubMed Central

Di Lisio, L; Sánchez-Beato, M; Gómez-López, G; Rodríguez, M E; Montes-Moreno, S; Mollejo, M; Menárguez, J; Martínez, M A; Alves, F J; Pisano, D G; Piris, M A; Martínez, N

2012-01-01

Accurate lymphoma diagnosis, prognosis and therapy still require additional markers. We explore the potential relevance of microRNA (miRNA) expression in a large series that included all major B-cell non-Hodgkin lymphoma (NHL) types. The data generated were also used to identify miRNAs differentially expressed in Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) samples. A series of 147 NHL samples and 15 controls were hybridized on a human miRNA one-color platform containing probes for 470 human miRNAs. Each lymphoma type was compared against the entire set of NHLs. BL was also directly compared with DLBCL, and 43 preselected miRNAs were analyzed in a new series of routinely processed samples of 28 BLs and 43 DLBCLs using quantitative reverse transcription-polymerase chain reaction. A signature of 128 miRNAs enabled the characterization of lymphoma neoplasms, reflecting the lymphoma type, cell of origin and/or discrete oncogene alterations. Comparative analysis of BL and DLBCL yielded 19 differentially expressed miRNAs, which were confirmed in a second confirmation series of 71 paraffin-embedded samples. The set of differentially expressed miRNAs found here expands the range of potential diagnostic markers for lymphoma diagnosis, especially when differential diagnosis of BL and DLBCL is required. PMID:22829247

Feature Selection Methods for Zero-Shot Learning of Neural Activity

PubMed Central

Caceres, Carlos A.; Roos, Matthew J.; Rupp, Kyle M.; Milsap, Griffin; Crone, Nathan E.; Wolmetz, Michael E.; Ratto, Christopher R.

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy. PMID:28690513

sw-SVM: sensor weighting support vector machines for EEG-based brain-computer interfaces.

PubMed

Jrad, N; Congedo, M; Phlypo, R; Rousseau, S; Flamary, R; Yger, F; Rakotomamonjy, A

2011-10-01

In many machine learning applications, like brain-computer interfaces (BCI), high-dimensional sensor array data are available. Sensor measurements are often highly correlated and signal-to-noise ratio is not homogeneously spread across sensors. Thus, collected data are highly variable and discrimination tasks are challenging. In this work, we focus on sensor weighting as an efficient tool to improve the classification procedure. We present an approach integrating sensor weighting in the classification framework. Sensor weights are considered as hyper-parameters to be learned by a support vector machine (SVM). The resulting sensor weighting SVM (sw-SVM) is designed to satisfy a margin criterion, that is, the generalization error. Experimental studies on two data sets are presented, a P300 data set and an error-related potential (ErrP) data set. For the P300 data set (BCI competition III), for which a large number of trials is available, the sw-SVM proves to perform equivalently with respect to the ensemble SVM strategy that won the competition. For the ErrP data set, for which a small number of trials are available, the sw-SVM shows superior performances as compared to three state-of-the art approaches. Results suggest that the sw-SVM promises to be useful in event-related potentials classification, even with a small number of training trials.

Interactions of C+(2PJ) with rare gas atoms: incipient chemical interactions, potentials and transport coefficients

NASA Astrophysics Data System (ADS)

Tuttle, William D.; Thorington, Rebecca L.; Viehland, Larry A.; Breckenridge, W. H.; Wright, Timothy G.

2018-03-01

Accurate interatomic potentials were calculated for the interaction of a singly charged carbon cation, C+, with a single rare gas atom, RG (RG = Ne-Xe). The RCCSD(T) method and basis sets of quadruple-ζ and quintuple-ζ quality were employed; each interaction energy was counterpoise corrected and extrapolated to the basis set limit. The lowest C+(2P) electronic term of the carbon cation was considered, and the interatomic potentials calculated for the diatomic terms that arise from these: 2Π and 2Σ+. Additionally, the interatomic potentials for the respective spin-orbit levels were calculated, and the effect on the spectroscopic parameters was examined. In doing this, anomalously large spin-orbit splittings for RG = Ar-Xe were found, and this was investigated using multi-reference configuration interaction calculations. The latter indicated a small amount of RG → C+ electron transfer and this was used to rationalize the observations. This is taken as evidence of an incipient chemical interaction, which was also examined via contour plots, Birge-Sponer plots and various population analyses across the C+-RG series (RG = He-Xe), with the latter showing unexpected results. Trends in several spectroscopic parameters were examined as a function of the increasing atomic number of the RG atom. Finally, each set of RCCSD(T) potentials was employed, including spin-orbit coupling to calculate the transport coefficients for C+ in RG, and the results were compared with the limited available data. This article is part of the theme issue `Modern theoretical chemistry'.

Source localization in electromyography using the inverse potential problem

NASA Astrophysics Data System (ADS)

van den Doel, Kees; Ascher, Uri M.; Pai, Dinesh K.

2011-02-01

We describe an efficient method for reconstructing the activity in human muscles from an array of voltage sensors on the skin surface. MRI is used to obtain morphometric data which are segmented into muscle tissue, fat, bone and skin, from which a finite element model for volume conduction is constructed. The inverse problem of finding the current sources in the muscles is solved using a careful regularization technique which adds a priori information, yielding physically reasonable solutions from among those that satisfy the basic potential problem. Several regularization functionals are considered and numerical experiments on a 2D test model are performed to determine which performs best. The resulting scheme leads to numerical difficulties when applied to large-scale 3D problems. We clarify the nature of these difficulties and provide a method to overcome them, which is shown to perform well in the large-scale problem setting.

Estimation of Radiative Efficiency of Chemicals with Potentially Significant Global Warming Potential.

PubMed

Betowski, Don; Bevington, Charles; Allison, Thomas C

2016-01-19

Halogenated chemical substances are used in a broad array of applications, and new chemical substances are continually being developed and introduced into commerce. While recent research has considerably increased our understanding of the global warming potentials (GWPs) of multiple individual chemical substances, this research inevitably lags behind the development of new chemical substances. There are currently over 200 substances known to have high GWP. Evaluation of schemes to estimate radiative efficiency (RE) based on computational chemistry are useful where no measured IR spectrum is available. This study assesses the reliability of values of RE calculated using computational chemistry techniques for 235 chemical substances against the best available values. Computed vibrational frequency data is used to estimate RE values using several Pinnock-type models, and reasonable agreement with reported values is found. Significant improvement is obtained through scaling of both vibrational frequencies and intensities. The effect of varying the computational method and basis set used to calculate the frequency data is discussed. It is found that the vibrational intensities have a strong dependence on basis set and are largely responsible for differences in computed RE values.

PepLine: a software pipeline for high-throughput direct mapping of tandem mass spectrometry data on genomic sequences.

PubMed

Ferro, Myriam; Tardif, Marianne; Reguer, Erwan; Cahuzac, Romain; Bruley, Christophe; Vermat, Thierry; Nugues, Estelle; Vigouroux, Marielle; Vandenbrouck, Yves; Garin, Jérôme; Viari, Alain

2008-05-01

PepLine is a fully automated software which maps MS/MS fragmentation spectra of trypsic peptides to genomic DNA sequences. The approach is based on Peptide Sequence Tags (PSTs) obtained from partial interpretation of QTOF MS/MS spectra (first module). PSTs are then mapped on the six-frame translations of genomic sequences (second module) giving hits. Hits are then clustered to detect potential coding regions (third module). Our work aimed at optimizing the algorithms of each component to allow the whole pipeline to proceed in a fully automated manner using raw nucleic acid sequences (i.e., genomes that have not been "reduced" to a database of ORFs or putative exons sequences). The whole pipeline was tested on controlled MS/MS spectra sets from standard proteins and from Arabidopsis thaliana envelope chloroplast samples. Our results demonstrate that PepLine competed with protein database searching softwares and was fast enough to potentially tackle large data sets and/or high size genomes. We also illustrate the potential of this approach for the detection of the intron/exon structure of genes.

Multiresolution persistent homology for excessively large biomolecular datasets

NASA Astrophysics Data System (ADS)

Xia, Kelin; Zhao, Zhixiong; Wei, Guo-Wei

2015-10-01

Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

PubMed

Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well.

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

PubMed Central

Wang, Jun Yi; Ngo, Michael M.; Hessl, David; Hagerman, Randi J.; Rivera, Susan M.

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer’s segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well. PMID:27213683

A Composite Network Approach for Assessing Multi-Species Connectivity: An Application to Road Defragmentation Prioritisation

PubMed Central

Saura, Santiago; Rondinini, Carlo

2016-01-01

One of the biggest challenges in large-scale conservation is quantifying connectivity at broad geographic scales and for a large set of species. Because connectivity analyses can be computationally intensive, and the planning process quite complex when multiple taxa are involved, assessing connectivity at large spatial extents for many species turns to be often intractable. Such limitation results in that conducted assessments are often partial by focusing on a few key species only, or are generic by considering a range of dispersal distances and a fixed set of areas to connect that are not directly linked to the actual spatial distribution or mobility of particular species. By using a graph theory framework, here we propose an approach to reduce computational effort and effectively consider large assemblages of species in obtaining multi-species connectivity priorities. We demonstrate the potential of the approach by identifying defragmentation priorities in the Italian road network focusing on medium and large terrestrial mammals. We show that by combining probabilistic species graphs prior to conducting the network analysis (i) it is possible to analyse connectivity once for all species simultaneously, obtaining conservation or restoration priorities that apply for the entire species assemblage; and that (ii) those priorities are well aligned with the ones that would be obtained by aggregating the results of separate connectivity analysis for each of the individual species. This approach offers great opportunities to extend connectivity assessments to large assemblages of species and broad geographic scales. PMID:27768718

Mapping the integrated Sachs-Wolfe effect

NASA Astrophysics Data System (ADS)

Manzotti, A.; Dodelson, S.

2014-12-01

On large scales, the anisotropies in the cosmic microwave background (CMB) reflect not only the primordial density field but also the energy gain when photons traverse decaying gravitational potentials of large scale structure, what is called the integrated Sachs-Wolfe (ISW) effect. Decomposing the anisotropy signal into a primordial piece and an ISW component, the main secondary effect on large scales, is more urgent than ever as cosmologists strive to understand the Universe on those scales. We present a likelihood technique for extracting the ISW signal combining measurements of the CMB, the distribution of galaxies, and maps of gravitational lensing. We test this technique with simulated data showing that we can successfully reconstruct the ISW map using all the data sets together. Then we present the ISW map obtained from a combination of real data: the NRAO VLA sky survey (NVSS) galaxy survey, temperature anisotropies, and lensing maps made by the Planck satellite. This map shows that, with the data sets used and assuming linear physics, there is no evidence, from the reconstructed ISW signal in the Cold Spot region, for an entirely ISW origin of this large scale anomaly in the CMB. However a large scale structure origin from low redshift voids outside the NVSS redshift range is still possible. Finally we show that future surveys, thanks to a better large scale lensing reconstruction will be able to improve the reconstruction signal to noise which is now mainly coming from galaxy surveys.

Chemically derived graphene oxide: towards large-area thin-film electronics and optoelectronics.

PubMed

Eda, Goki; Chhowalla, Manish

2010-06-11

Chemically derived graphene oxide (GO) possesses a unique set of properties arising from oxygen functional groups that are introduced during chemical exfoliation of graphite. Large-area thin-film deposition of GO, enabled by its solubility in a variety of solvents, offers a route towards GO-based thin-film electronics and optoelectronics. The electrical and optical properties of GO are strongly dependent on its chemical and atomic structure and are tunable over a wide range via chemical engineering. In this Review, the fundamental structure and properties of GO-based thin films are discussed in relation to their potential applications in electronics and optoelectronics.

Analysis of suspicious powders following the post 9/11 anthrax scare.

PubMed

Wills, Brandon; Leikin, Jerrold; Rhee, James; Saeedi, Bijan

2008-06-01

Following the 9/11 terrorist attacks, SET Environmental, Inc., a Chicago-based environmental and hazardous materials management company received a large number of suspicious powders for analysis. Samples of powders were submitted to SET for anthrax screening and/or unknown identification (UI). Anthrax screening was performed on-site using a ruggedized analytical pathogen identification device (R.A.P.I.D.) (Idaho Technologies, Salt Lake City, UT). UI was performed at SET headquarters (Wheeling, IL) utilizing a combination of wet chemistry techniques, infrared spectroscopy, and gas chromatography/mass spectroscopy. Turnaround time was approximately 2-3 hours for either anthrax or UI. Between October 10, 2001 and October 11, 2002, 161 samples were analyzed. Of these, 57 were for anthrax screening only, 78 were for anthrax and UI, and 26 were for UI only. Sources of suspicious powders included industries (66%), U.S. Postal Service (19%), law enforcement (9%), and municipalities (7%). There were 0/135 anthrax screens that were positive. There were no positive anthrax screens performed by SET in the Chicago area following the post-9/11 anthrax scare. The only potential biological or chemical warfare agent identified (cyanide) was provided by law enforcement. Rapid anthrax screening and identification of unknown substances at the scene are useful to prevent costly interruption of services and potential referral for medical evaluation.

The ecological future of the North American bison: Conceiving long-term, large-scale conservation of a species

USGS Publications Warehouse

Sanderson, E.W.; Redford, Kent; Weber, Bill; Aune, K.; Baldes, Dick; Berger, J.; Carter, Dave; Curtin, C.; Derr, James N.; Dobrott, S.J.; Fearn, Eva; Fleener, Craig; Forrest, Steven C.; Gerlach, Craig; Gates, C. Cormack; Gross, J.E.; Gogan, P.; Grassel, Shaun M.; Hilty, Jodi A.; Jensen, Marv; Kunkel, Kyran; Lammers, Duane; List, R.; Minkowski, Karen; Olson, Tom; Pague, Chris; Robertson, Paul B.; Stephenson, Bob

2008-01-01

Many wide-ranging mammal species have experienced significant declines over the last 200 years; restoring these species will require long-term, large-scale recovery efforts. We highlight 5 attributes of a recent range-wide vision-setting exercise for ecological recovery of the North American bison (Bison bison) that are broadly applicable to other species and restoration targets. The result of the exercise, the “Vermejo Statement” on bison restoration, is explicitly (1) large scale, (2) long term, (3) inclusive, (4) fulfilling of different values, and (5) ambitious. It reads, in part, “Over the next century, the ecological recovery of the North American bison will occur when multiple large herds move freely across extensive landscapes within all major habitats of their historic range, interacting in ecologically significant ways with the fullest possible set of other native species, and inspiring, sustaining and connecting human cultures.” We refined the vision into a scorecard that illustrates how individual bison herds can contribute to the vision. We also developed a set of maps and analyzed the current and potential future distributions of bison on the basis of expert assessment. Although more than 500,000 bison exist in North America today, we estimated they occupy <1% of their historical range and in no place express the full range of ecological and social values of previous times. By formulating an inclusive, affirmative, and specific vision through consultation with a wide range of stakeholders, we hope to provide a foundation for conservation of bison, and other wide-ranging species, over the next 100 years.

Telluric currents: A meeting of theory and observation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boteler, D.H.; Seager, W.H.

Pipe-to-soil (P/S) potential variations resulting from telluric currents have been observed on pipelines in many locations. However, it has never teen clear which parts of a pipeline will experience the worst effects. Two studies were conducted to answer this question. Distributed-source transmission line (DSTL) theory was applied to the problem of modeling geomagnetic induction in pipelines. This theory predicted that the largest P/S potential variations would occur at the ends of the pipeline. The theory also predicted that large P/S potential variations, of opposite sign, should occur on either side of an insulating flange. Independently, an observation program was conductedmore » to determine the change in telluric current P/S potential variations and to design counteractive measures along a pipeline in northern Canada. Observations showed that the amplitude of P/S potential fluctuations had maxima at the northern and southern ends of the pipeline. A further set of recordings around an insulating flange showed large P/S potential variations, of opposite sign, on either side of the flange. Agreement between the observations and theoretical predictions was remarkable. While the observations confirmed the theory, the theory explains how P/S potential variations are produced by telluric currents and provides the basis for design of cathodic protection systems for pipelines that can counteract any adverse telluric effects.« less

Energy Efficiency Potential in the U.S. Single-Family Housing Stock

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, Eric J.; Christensen, Craig B.; Horowitz, Scott G.

Typical approaches for assessing energy efficiency potential in buildings use a limited number of prototypes, and therefore suffer from inadequate resolution when pass-fail cost-effectiveness tests are applied, which can significantly underestimate or overestimate the economic potential of energy efficiency technologies. This analysis applies a new approach to large-scale residential energy analysis, combining the use of large public and private data sources, statistical sampling, detailed building simulations, and high-performance computing to achieve unprecedented granularity - and therefore accuracy - in modeling the diversity of the single-family housing stock. The result is a comprehensive set of maps, tables, and figures showing themore » technical and economic potential of 50 plus residential energy efficiency upgrades and packages for each state. Policymakers, program designers, and manufacturers can use these results to identify upgrades with the highest potential for cost-effective savings in a particular state or region, as well as help identify customer segments for targeted marketing and deployment. The primary finding of this analysis is that there is significant technical and economic potential to save electricity and on-site fuel use in the single-family housing stock. However, the economic potential is very sensitive to the cost-effectiveness criteria used for analysis. Additionally, the savings of particular energy efficiency upgrades is situation-specific within the housing stock (depending on climate, building vintage, heating fuel type, building physical characteristics, etc.).« less

Injury surveillance in low-resource settings using Geospatial and Social Web technologies

PubMed Central

2010-01-01

Background Extensive public health gains have benefited high-income countries in recent decades, however, citizens of low and middle-income countries (LMIC) have largely not enjoyed the same advancements. This is in part due to the fact that public health data - the foundation for public health advances - are rarely collected in many LMIC. Injury data are particularly scarce in many low-resource settings, despite the huge associated burden of morbidity and mortality. Advances in freely-accessible and easy-to-use information and communication (ICT) technology may provide the impetus for increased public health data collection in settings with limited financial and personnel resources. Methods and Results A pilot study was conducted at a hospital in Cape Town, South Africa to assess the utility and feasibility of using free (non-licensed), and easy-to-use Social Web and GeoWeb tools for injury surveillance in low-resource settings. Data entry, geocoding, data exploration, and data visualization were successfully conducted using these technologies, including Google Spreadsheet, Mapalist, BatchGeocode, and Google Earth. Conclusion This study examined the potential for Social Web and GeoWeb technologies to contribute to public health data collection and analysis in low-resource settings through an injury surveillance pilot study conducted in Cape Town, South Africa. The success of this study illustrates the great potential for these technologies to be leveraged for public health surveillance in resource-constrained environments, given their ease-of-use and low-cost, and the sharing and collaboration capabilities they afford. The possibilities and potential limitations of these technologies are discussed in relation to the study, and to the field of public health in general. PMID:20497570

Baryon interactions from lattice QCD with physical masses — strangeness S = -1 sector —

NASA Astrophysics Data System (ADS)

Nemura, Hidekatsu; Aoki, Sinya; Doi, Takumi; Gongyo, Shinya; Hatsuda, Tetsuo; Ikeda, Yoichi; Inoue, Takashi; Iritani, Takumi; Ishii, Noriyoshi; Miyamoto, Takaya; Sasaki, Kenji

2018-03-01

We present our recent results of baryon interactions with strangeness S = -1 based on Nambu-Bethe-Salpeter (NBS) correlation functions calculated fromlattice QCD with almost physical quark masses corresponding to (mk,mk) ≈ (146, 525) MeV and large volume (La)4 ≈ (96a)4 ≈ (8.1 fm)4. In order to perform a comprehensive study of baryon interactions, a large number of NBS correlation functions from NN to ΞΞ are calculated simultaneously by using large scale computer resources. In this contribution, we focus on the strangeness S = -1 channels of the hyperon interactions by means of HAL QCD method. Four sets of three potentials (the 3S1 - 3 D1 central, 3S1 - 3 D1 tensor, and the 1S0 central potentials) are presented for the ∑N - ∑N (the isospin I = 3/2) diagonal, the ∧N - ∧N diagonal, the ∧N → ∑N transition, and the ∑N - ∑N (I = 1/2) diagonal interactions. Scattering phase shifts for ∑N (I = 3/2) system are presented.

Visual Word Recognition Across the Adult Lifespan

PubMed Central

Cohen-Shikora, Emily R.; Balota, David A.

2016-01-01

The current study examines visual word recognition in a large sample (N = 148) across the adult lifespan and across a large set of stimuli (N = 1187) in three different lexical processing tasks (pronunciation, lexical decision, and animacy judgments). Although the focus of the present study is on the influence of word frequency, a diverse set of other variables are examined as the system ages and acquires more experience with language. Computational models and conceptual theories of visual word recognition and aging make differing predictions for age-related changes in the system. However, these have been difficult to assess because prior studies have produced inconsistent results, possibly due to sample differences, analytic procedures, and/or task-specific processes. The current study confronts these potential differences by using three different tasks, treating age and word variables as continuous, and exploring the influence of individual differences such as vocabulary, vision, and working memory. The primary finding is remarkable stability in the influence of a diverse set of variables on visual word recognition across the adult age spectrum. This pattern is discussed in reference to previous inconsistent findings in the literature and implications for current models of visual word recognition. PMID:27336629

Possible explanation of the atmospheric kinetic and potential energy spectra.

PubMed

Vallgren, Andreas; Deusebio, Enrico; Lindborg, Erik

2011-12-23

We hypothesize that the observed wave number spectra of kinetic and potential energy in the atmosphere can be explained by assuming that there are two related cascade processes emanating from the same large-scale energy source, a downscale cascade of potential enstrophy, giving rise to the k(-3) spectrum at synoptic scales and a downscale energy cascade giving rise to the k(-5/3) spectrum at mesoscales. The amount of energy which is going into the downscale energy cascade is determined by the rate of system rotation, with negligible energy going downscale in the limit of very fast rotation. We present a set of simulations of a system with strong rotation and stratification, supporting these hypotheses and showing good agreement with observations.

Single embryo transfer and IVF/ICSI outcome: a balanced appraisal.

PubMed

Gerris, Jan M R

2005-01-01

This review considers the value of single embryo transfer (SET) to prevent multiple pregnancies (MP) after IVF/ICSI. The incidence of MP (twins and higher order pregnancies) after IVF/ICSI is much higher (approximately 30%) than after natural conception (approximately 1%). Approximately half of all the neonates are multiples. The obstetric, neonatal and long-term consequences for the health of these children are enormous and costs incurred extremely high. Judicious SET is the only method to decrease this epidemic of iatrogenic multiple gestations. Clinical trials have shown that programmes with >50% of SET maintain high overall ongoing pregnancy rates ( approximately 30% per started cycle) while reducing the MP rate to <10%. Experience with SET remains largely European although the need to reduce MP is accepted worldwide. An important issue is how to select patients suitable for SET and embryos with a high putative implantation potential. The typical patient suitable for SET is young (aged <36 years) and in her first or second IVF/ICSI trial. Embryo selection is performed using one or a combination of embryo characteristics. Available evidence suggests that, for the overall population, day 3 and day 5 selection yield similar results but better than zygote selection results. Prospective studies correlating embryo characteristics with documented implantation potential, utilizing databases of individual embryos, are needed. The application of SET should be supported by other measures: reimbursement of IVF/ICSI (earned back by reducing costs), optimized cryopreservation to augment cumulative pregnancy rates per oocyte harvest and a standardized format for reporting results. To make SET the standard of care in the appropriate target group, there is a need for more clinical studies, for intensive counselling of patients, and for an increased sense of responsibility in patients, health care providers and health insurers.

Query-based biclustering of gene expression data using Probabilistic Relational Models.

PubMed

Zhao, Hui; Cloots, Lore; Van den Bulcke, Tim; Wu, Yan; De Smet, Riet; Storms, Valerie; Meysman, Pieter; Engelen, Kristof; Marchal, Kathleen

2011-02-15

With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set of genes of interest (i.e., a query or seed set) for a subset of conditions. To that end, a query-based strategy is needed that maximally exploits the coexpression behaviour of the seed genes to guide the biclustering, but that at the same time is robust against the presence of noisy genes in the seed set as seed genes are often assumed, but not guaranteed to be coexpressed in the queried compendium. Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within the seed set. We applied ProBic on a large scale Escherichia coli compendium to extend partially described regulons with potentially novel members. We compared ProBic's performance with previously published query-based biclustering algorithms, namely ISA and QDB, from the perspective of bicluster expression quality, robustness of the outcome against noisy seed sets and biological relevance.This comparison learns that ProBic is able to retrieve biologically relevant, high quality biclusters that retain their seed genes and that it is particularly strong in handling noisy seeds. ProBic is a query-based biclustering algorithm developed in a flexible framework, designed to detect biologically relevant, high quality biclusters that retain relevant seed genes even in the presence of noise or when dealing with low quality seed sets.

Automatic Earthquake Detection by Active Learning

NASA Astrophysics Data System (ADS)

Bergen, K.; Beroza, G. C.

2017-12-01

In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Balaji, R.

2017-12-01

In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

Extending the accuracy of the SNAP interatomic potential form

NASA Astrophysics Data System (ADS)

Wood, Mitchell A.; Thompson, Aidan P.

2018-06-01

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functions in EAM. The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similar to artificial neural network potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting. The quality of this new potential form is measured through a robust cross-validation analysis.

Evaluating data mining algorithms using molecular dynamics trajectories.

PubMed

Tatsis, Vasileios A; Tjortjis, Christos; Tzirakis, Panagiotis

2013-01-01

Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.

Identity and privacy. Unique in the shopping mall: on the reidentifiability of credit card metadata.

PubMed

de Montjoye, Yves-Alexandre; Radaelli, Laura; Singh, Vivek Kumar; Pentland, Alex Sandy

2015-01-30

Large-scale data sets of human behavior have the potential to fundamentally transform the way we fight diseases, design cities, or perform research. Metadata, however, contain sensitive information. Understanding the privacy of these data sets is key to their broad use and, ultimately, their impact. We study 3 months of credit card records for 1.1 million people and show that four spatiotemporal points are enough to uniquely reidentify 90% of individuals. We show that knowing the price of a transaction increases the risk of reidentification by 22%, on average. Finally, we show that even data sets that provide coarse information at any or all of the dimensions provide little anonymity and that women are more reidentifiable than men in credit card metadata. Copyright © 2015, American Association for the Advancement of Science.

Spatiotemporal property and predictability of large-scale human mobility

NASA Astrophysics Data System (ADS)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

Methanol production from Eucalyptus wood chips. Working Document 2. Vegetative propagation of Eucalypts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fishkind, H.H.

1982-04-01

The feasibility of large-scale plantation establishment by various methods was examined, and the following conclusions were reached: seedling plantations are limited in potential yield due to genetic variation among the planting stock and often inadequate supplies of appropriate seed; vegetative propagation by rooted cuttings can provide good genetic uniformity of select hybrid planting stock; however, large-scale production requires establishment and maintenance of extensive cutting orchards. The collection of shoots and preparation of cuttings, although successfully implemented in the Congo and Brazil, would not be economically feasible in Florida for large-scale plantations; tissue culture propagation of select hybrid eucalypts offers themore » only opportunity to produce the very large number of trees required to establish the energy plantation. The cost of tissue culture propagation, although higher than seedling production, is more than off-set by the increased productivity of vegetative plantations established from select hybrid Eucalyptus.« less

Challenges in evaluating cancer as a clinical outcome in postapproval studies of drug safety

PubMed Central

Pinheiro, Simone P.; Rivera, Donna R.; Graham, David J.; Freedman, Andrew N.; Major, Jacqueline M.; Penberthy, Lynne; Levenson, Mark; Bradley, Marie C.; Wong, Hui-Lee; Ouellet-Hellstrom, Rita

2017-01-01

Pharmaceuticals approved in the United States are largely not known human carcinogens. However, cancer signals associated with pharmaceuticals may be hypothesized or arise after product approval. There are many study designs that can be used to evaluate cancer as an outcome in the postapproval setting. Because prospective systematic collection of cancer outcomes from a large number of individuals may be lengthy, expensive, and challenging, leveraging data from large existing databases are an integral approach. Such studies have the capability to evaluate the clinical experience of a large number of individuals, yet there are unique methodological challenges involved in their use to evaluate cancer outcomes. To discuss methodological challenges and potential solutions, the Food and Drug Administration and the National Cancer Institute convened a two-day public meeting in 2014. This commentary summarizes the most salient issues discussed at the meeting. PMID:27663208

Size does matter - span of control in hospitals.

PubMed

Holm-Petersen, Christina; Østergaard, Sussanne; Andersen, Per Bo Noergaard

2017-04-10

Purpose Centralization, mergers and cost reductions have generally led to increasing levels of span of control (SOC), and thus potentially to lower leadership capacity. The purpose of this paper is to explore how a large SOC impacts hospital staff and their leaders. Design/methodology/approach The study is based on a qualitative explorative case study of three large inpatient wards. Findings The study finds that the nursing staff and their frontline leaders experience challenges in regard to visibility and role of the leader, e.g., in creating overview, coordination, setting-up clear goals, following up and being in touch. However, large wards also provide flexibility and development possibilities. Practical implications The authors discuss the implications of these findings for decision makers in deciding future SOC and for future SOC research. Originality/value Only few studies have qualitatively explored the consequences of large SOC in hospitals.

Challenges in evaluating cancer as a clinical outcome in postapproval studies of drug safety.

PubMed

Pinheiro, Simone P; Rivera, Donna R; Graham, David J; Freedman, Andrew N; Major, Jacqueline M; Penberthy, Lynne; Levenson, Mark; Bradley, Marie C; Wong, Hui-Lee; Ouellet-Hellstrom, Rita

2016-11-01

Pharmaceuticals approved in the United States are largely not known human carcinogens. However, cancer signals associated with pharmaceuticals may be hypothesized or arise after product approval. There are many study designs that can be used to evaluate cancer as an outcome in the postapproval setting. Because prospective systematic collection of cancer outcomes from a large number of individuals may be lengthy, expensive, and challenging, leveraging data from large existing databases are an integral approach. Such studies have the capability to evaluate the clinical experience of a large number of individuals, yet there are unique methodological challenges involved in their use to evaluate cancer outcomes. To discuss methodological challenges and potential solutions, the Food and Drug Administration and the National Cancer Institute convened a two-day public meeting in 2014. This commentary summarizes the most salient issues discussed at the meeting. Published by Elsevier Inc.

Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets

PubMed Central

Kotera, Masaaki; Tabei, Yasuo; Yamanishi, Yoshihiro; Tokimatsu, Toshiaki; Goto, Susumu

2013-01-01

Motivation: The metabolic pathway is an important biochemical reaction network involving enzymatic reactions among chemical compounds. However, it is assumed that a large number of metabolic pathways remain unknown, and many reactions are still missing even in known pathways. Therefore, the most important challenge in metabolomics is the automated de novo reconstruction of metabolic pathways, which includes the elucidation of previously unknown reactions to bridge the metabolic gaps. Results: In this article, we develop a novel method to reconstruct metabolic pathways from a large compound set in the reaction-filling framework. We define feature vectors representing the chemical transformation patterns of compound–compound pairs in enzymatic reactions using chemical fingerprints. We apply a sparsity-induced classifier to learn what we refer to as ‘enzymatic-reaction likeness’, i.e. whether compound pairs are possibly converted to each other by enzymatic reactions. The originality of our method lies in the search for potential reactions among many compounds at a time, in the extraction of reaction-related chemical transformation patterns and in the large-scale applicability owing to the computational efficiency. In the results, we demonstrate the usefulness of our proposed method on the de novo reconstruction of 134 metabolic pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG). Our comprehensively predicted reaction networks of 15 698 compounds enable us to suggest many potential pathways and to increase research productivity in metabolomics. Availability: Softwares are available on request. Supplementary material are available at http://web.kuicr.kyoto-u.ac.jp/supp/kot/ismb2013/. Contact: goto@kuicr.kyoto-u.ac.jp PMID:23812977

Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism.

PubMed

Meyer, Ashley N D; Murphy, Daniel R; Al-Mutairi, Aymer; Sittig, Dean F; Wei, Li; Russo, Elise; Singh, Hardeep

2017-07-01

Delays in following up abnormal test results are a common problem in outpatient settings. Surveillance systems that use trigger tools to identify delayed follow-up can help reduce missed opportunities in care. To develop and test an electronic health record (EHR)-based trigger algorithm to identify instances of delayed follow-up of abnormal thyroid-stimulating hormone (TSH) results in patients being treated for hypothyroidism. We developed an algorithm using structured EHR data to identify patients with hypothyroidism who had delayed follow-up (>60 days) after an abnormal TSH. We then retrospectively applied the algorithm to a large EHR data warehouse within the Department of Veterans Affairs (VA), on patient records from two large VA networks for the period from January 1, 2011, to December 31, 2011. Identified records were reviewed to confirm the presence of delays in follow-up. During the study period, 645,555 patients were seen in the outpatient setting within the two networks. Of 293,554 patients with at least one TSH test result, the trigger identified 1250 patients on treatment for hypothyroidism with elevated TSH. Of these patients, 271 were flagged as potentially having delayed follow-up of their test result. Chart reviews confirmed delays in 163 of the 271 flagged patients (PPV = 60.1%). An automated trigger algorithm applied to records in a large EHR data warehouse identified patients with hypothyroidism with potential delays in thyroid function test results follow-up. Future prospective application of the TSH trigger algorithm can be used by clinical teams as a surveillance and quality improvement technique to monitor and improve follow-up.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodrigues, Davi C.; Piattella, Oliver F.; Chauvineau, Bertrand, E-mail: davi.rodrigues@cosmo-ufes.org, E-mail: Bertrand.Chauvineau@oca.eu, E-mail: oliver.piattella@pq.cnpq.br

We show that Renormalization Group extensions of the Einstein-Hilbert action for large scale physics are not, in general, a particular case of standard Scalar-Tensor (ST) gravity. We present a new class of ST actions, in which the potential is not necessarily fixed at the action level, and show that this extended ST theory formally contains the Renormalization Group case. We also propose here a Renormalization Group scale setting identification that is explicitly covariant and valid for arbitrary relativistic fluids.

Understanding the potential dispersal of HPAI H5N1 virus by migratory wildfowl

USGS Publications Warehouse

Gaidet, Nicolas; Cappelle, Julien; Takekawa, John Y.; Prosser, Diann J.; Iverson, Samuel A.; Douglas, David C.; Perry, William M.; Mundkur, Taej; Newman, Scott H.

2010-01-01

We analysed wildfowl movements between 2006-2009, including 228 birds from 19 species, part of a larger international programme (see Figure 1) coordinated by the Food and Agricultural Organisation (FAO) of the United Nations aimed at understanding if there are temporal or spatial relationships between HPAI H5N1 outbreaks and movements of migratory wildfowl, the first large scale data set available for such an analysis.

Integrating Fire, Climate, and Societal Factors into Decision Support for Strategic Planning in Wildland Fire Management

Treesearch

Barbara J. Morehouse; Gregg Garfin; Timothy Brown; Thomas W. Swetnam

2006-01-01

An El Niño winter in 1998-99, followed by a strong La Niña winter in 1999- 2000, set the stage for potentially large wildfires in the southwestern, southeastern, and northwestern forests of the United States. Researchers at the University of Arizona organized a three-day workshop to discuss the relationship between synoptic scale climate conditions and wildland fire...

Transmission of Human Respiratory Syncytial Virus in the Immunocompromised Ferret Model

PubMed Central

de Waal, Leon; Smits, Saskia L.; Veldhuis Kroeze, Edwin J. B.; van Amerongen, Geert; Pohl, Marie O.; Osterhaus, Albert D. M. E.; Stittelaar, Koert J.

2018-01-01

Human respiratory syncytial virus (HRSV) causes substantial morbidity and mortality in vulnerable patients, such as the very young, the elderly, and immunocompromised individuals of any age. Nosocomial transmission of HRSV remains a serious challenge in hospital settings, with intervention strategies largely limited to infection control measures, including isolation of cases, high standards of hand hygiene, cohort nursing, and use of personal protective equipment. No vaccines against HRSV are currently available, and treatment options are largely supportive care and expensive monoclonal antibody or antiviral therapy. The limitations of current animal models for HRSV infection impede the development of new preventive and therapeutic agents, and the assessment of their potential for limiting HRSV transmission, in particular in nosocomial settings. Here, we demonstrate the efficient transmission of HRSV from immunocompromised ferrets to both immunocompromised and immunocompetent contact ferrets, with pathological findings reproducing HRSV pathology in humans. The immunocompromised ferret-HRSV model represents a novel tool for the evaluation of intervention strategies against nosocomial transmission of HRSV. PMID:29301313

Dynamic permeability in fault damage zones induced by repeated coseismic fracturing events

NASA Astrophysics Data System (ADS)

Aben, F. M.; Doan, M. L.; Mitchell, T. M.

2017-12-01

Off-fault fracture damage in upper crustal fault zones change the fault zone properties and affect various co- and interseismic processes. One of these properties is the permeability of the fault damage zone rocks, which is generally higher than the surrounding host rock. This allows large-scale fluid flow through the fault zone that affects fault healing and promotes mineral transformation processes. Moreover, it might play an important role in thermal fluid pressurization during an earthquake rupture. The damage zone permeability is dynamic due to coseismic damaging. It is crucial for earthquake mechanics and for longer-term processes to understand how the dynamic permeability structure of a fault looks like and how it evolves with repeated earthquakes. To better detail coseismically induced permeability, we have performed uniaxial split Hopkinson pressure bar experiments on quartz-monzonite rock samples. Two sample sets were created and analyzed: single-loaded samples subjected to varying loading intensities - with damage varying from apparently intact to pulverized - and samples loaded at a constant intensity but with a varying number of repeated loadings. The first set resembles a dynamic permeability structure created by a single large earthquake. The second set resembles a permeability structure created by several earthquakes. After, the permeability and acoustic velocities were measured as a function of confining pressure. The permeability in both datasets shows a large and non-linear increase over several orders of magnitude (from 10-20 up to 10-14 m2) with an increasing amount of fracture damage. This, combined with microstructural analyses of the varying degrees of damage, suggests a percolation threshold. The percolation threshold does not coincide with the pulverization threshold. With increasing confining pressure, the permeability might drop up to two orders of magnitude, which supports the possibility of large coseismic fluid pulses over relatively large distances along a fault. Also, a relatively small threshold could potentially increase permeability in a large volume of rock, given that previous earthquakes already damaged these rocks.

CPM Is a Useful Cell Surface Marker to Isolate Expandable Bi-Potential Liver Progenitor Cells Derived from Human iPS Cells.

PubMed

Kido, Taketomo; Koui, Yuta; Suzuki, Kaori; Kobayashi, Ayaka; Miura, Yasushi; Chern, Edward Y; Tanaka, Minoru; Miyajima, Atsushi

2015-10-13

To develop a culture system for large-scale production of mature hepatocytes, liver progenitor cells (LPCs) with a high proliferation potential would be advantageous. We have found that carboxypeptidase M (CPM) is highly expressed in embryonic LPCs, hepatoblasts, while its expression is decreased along with hepatic maturation. Consistently, CPM expression was transiently induced during hepatic specification from human-induced pluripotent stem cells (hiPSCs). CPM(+) cells isolated from differentiated hiPSCs at the immature hepatocyte stage proliferated extensively in vitro and expressed a set of genes that were typical of hepatoblasts. Moreover, the CPM(+) cells exhibited a mature hepatocyte phenotype after induction of hepatic maturation and also underwent cholangiocytic differentiation in a three-dimensional culture system. These results indicated that hiPSC-derived CPM(+) cells share the characteristics of LPCs, with the potential to proliferate and differentiate bi-directionally. Thus, CPM is a useful marker for isolating hiPSC-derived LPCs, which allows development of a large-scale culture system for producing hepatocytes and cholangiocytes. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

CPM Is a Useful Cell Surface Marker to Isolate Expandable Bi-Potential Liver Progenitor Cells Derived from Human iPS Cells

PubMed Central

Kido, Taketomo; Koui, Yuta; Suzuki, Kaori; Kobayashi, Ayaka; Miura, Yasushi; Chern, Edward Y.; Tanaka, Minoru; Miyajima, Atsushi

2015-01-01

Summary To develop a culture system for large-scale production of mature hepatocytes, liver progenitor cells (LPCs) with a high proliferation potential would be advantageous. We have found that carboxypeptidase M (CPM) is highly expressed in embryonic LPCs, hepatoblasts, while its expression is decreased along with hepatic maturation. Consistently, CPM expression was transiently induced during hepatic specification from human-induced pluripotent stem cells (hiPSCs). CPM+ cells isolated from differentiated hiPSCs at the immature hepatocyte stage proliferated extensively in vitro and expressed a set of genes that were typical of hepatoblasts. Moreover, the CPM+ cells exhibited a mature hepatocyte phenotype after induction of hepatic maturation and also underwent cholangiocytic differentiation in a three-dimensional culture system. These results indicated that hiPSC-derived CPM+ cells share the characteristics of LPCs, with the potential to proliferate and differentiate bi-directionally. Thus, CPM is a useful marker for isolating hiPSC-derived LPCs, which allows development of a large-scale culture system for producing hepatocytes and cholangiocytes. PMID:26365514

Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

PubMed Central

Bockholt, Henry J.; Scully, Mark; Courtney, William; Rachakonda, Srinivas; Scott, Adam; Caprihan, Arvind; Fries, Jill; Kalyanam, Ravi; Segall, Judith M.; de la Garza, Raul; Lane, Susan; Calhoun, Vince D.

2009-01-01

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining. PMID:20461147

Response of Coastal Fishes to the Gulf of Mexico Oil Disaster

PubMed Central

Fodrie, F. Joel; Heck, Kenneth L.

2011-01-01

The ecosystem-level impacts of the Deepwater Horizon disaster have been largely unpredictable due to the unique setting and magnitude of this spill. We used a five-year (2006–2010) data set within the oil-affected region to explore acute consequences for early-stage survival of fish species inhabiting seagrass nursery habitat. Although many of these species spawned during spring-summer, and produced larvae vulnerable to oil-polluted water, overall and species-by-species catch rates were high in 2010 after the spill (1,989±220 fishes km-towed−1 [μ ± 1SE]) relative to the previous four years (1,080±43 fishes km-towed−1). Also, several exploited species were characterized by notably higher juvenile catch rates during 2010 following large-scale fisheries closures in the northern Gulf, although overall statistical results for the effects of fishery closures on assemblage-wide CPUE data were ambiguous. We conclude that immediate, catastrophic losses of 2010 cohorts were largely avoided, and that no shifts in species composition occurred following the spill. The potential long-term impacts facing fishes as a result of chronic exposure and delayed, indirect effects now require attention. PMID:21754992

Argentine Population Genetic Structure: Large Variance in Amerindian Contribution

PubMed Central

Seldin, Michael F.; Tian, Chao; Shigeta, Russell; Scherbarth, Hugo R.; Silva, Gabriel; Belmont, John W.; Kittles, Rick; Gamron, Susana; Allevi, Alberto; Palatnik, Simon A.; Alvarellos, Alejandro; Paira, Sergio; Caprarulo, Cesar; Guillerón, Carolina; Catoggio, Luis J.; Prigione, Cristina; Berbotto, Guillermo A.; García, Mercedes A.; Perandones, Carlos E.; Pons-Estel, Bernardo A.; Alarcon-Riquelme, Marta E.

2011-01-01

Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies. PMID:17177183

Eucalyptus plantations for energy production in Hawaii. 1980 annual report, January 1980-December 1980

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitesell, C. D.

1980-01-01

In 1980 200 acres of eucalyptus trees were planted for a research and development biomass energy plantation bringing the total area under cultivation to 300 acres. Of this total acreage, 90 acres or 30% was planted in experimental plots. The remaining 70% of the cultivated area was closely monitored to determine the economic cost/benefit ratio of large scale biomass energy production. In the large scale plantings, standard field practices were set up for all phases of production: nursery, clearing, planting, weed control and fertilization. These practices were constantly evaluated for potential improvements in efficiency and reduced cost. Promising experimental treatmentsmore » were implemented on a large scale to test their effectiveness under field production conditions. In the experimental areas all scheduled data collection in 1980 has been completed and most measurements have been keypunched and analyzed. Soil samples and leaf samples have been analyzed for nutrient concentrations. Crop logging procedures have been set up to monitor tree growth through plant tissue analysis. An intensive computer search on biomass, nursery practices, harvesting equipment and herbicide applications has been completed through the services of the US Forest Service.« less

Studies of Tidal and Planetary Wave Variability in the Middle Atmosphere using UARS and Correlative MF Radar Data

NASA Technical Reports Server (NTRS)

Fritts, David C.

1996-01-01

The goals of this research effort have been to use MF radar and UARS/HRDI wind measurements for correlative studies of large-scale atmospheric dynamics, focusing specifically on the tidal and various planetary wave structures occurring in the middle atmosphere. We believed that the two data sets together would provide the potential for much more comprehensive studies than either by itself, since they jointly would allow the removal of ambiguities in wave structure that are difficult to resolve with either data set alone. The joint data were to be used for studies of wave structure, variability, and the coupling of these motions to mean and higher-frequency motions.

Propylene Glycol Poisoning From Excess Whiskey Ingestion: A Case of High Osmolal Gap Metabolic Acidosis.

PubMed

Cunningham, Courtney A; Ku, Kevin; Sue, Gloria R

2015-01-01

In this report, we describe a case of high anion gap metabolic acidosis with a significant osmolal gap attributed to the ingestion of liquor containing propylene glycol. Recently, several reports have characterized severe lactic acidosis occurring in the setting of iatrogenic unintentional overdosing of medications that use propylene glycol as a diluent, including lorazepam and diazepam. To date, no studies have explored potential effects of excess propylene glycol in the setting of alcohol intoxication. Our patient endorsed drinking large volumes of cinnamon flavored whiskey, which was likely Fireball Cinnamon Whisky. To our knowledge, this is the first case of propylene glycol toxicity from an intentional ingestion of liquor containing propylene glycol.

Propylene Glycol Poisoning From Excess Whiskey Ingestion

PubMed Central

Ku, Kevin; Sue, Gloria R.

2015-01-01

In this report, we describe a case of high anion gap metabolic acidosis with a significant osmolal gap attributed to the ingestion of liquor containing propylene glycol. Recently, several reports have characterized severe lactic acidosis occurring in the setting of iatrogenic unintentional overdosing of medications that use propylene glycol as a diluent, including lorazepam and diazepam. To date, no studies have explored potential effects of excess propylene glycol in the setting of alcohol intoxication. Our patient endorsed drinking large volumes of cinnamon flavored whiskey, which was likely Fireball Cinnamon Whisky. To our knowledge, this is the first case of propylene glycol toxicity from an intentional ingestion of liquor containing propylene glycol. PMID:26904700

Statistical learning and selective inference.

PubMed

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

A Mine of Information: Can Sports Analytics Provide Wisdom From Your Data?

PubMed

Passfield, Louis; Hopker, James G

2017-08-01

This paper explores the notion that the availability and analysis of large data sets have the capacity to improve practice and change the nature of science in the sport and exercise setting. The increasing use of data and information technology in sport is giving rise to this change. Web sites hold large data repositories, and the development of wearable technology, mobile phone applications, and related instruments for monitoring physical activity, training, and competition provide large data sets of extensive and detailed measurements. Innovative approaches conceived to more fully exploit these large data sets could provide a basis for more objective evaluation of coaching strategies and new approaches to how science is conducted. An emerging discipline, sports analytics, could help overcome some of the challenges involved in obtaining knowledge and wisdom from these large data sets. Examples of where large data sets have been analyzed, to evaluate the career development of elite cyclists and to characterize and optimize the training load of well-trained runners, are discussed. Careful verification of large data sets is time consuming and imperative before useful conclusions can be drawn. Consequently, it is recommended that prospective studies be preferred over retrospective analyses of data. It is concluded that rigorous analysis of large data sets could enhance our knowledge in the sport and exercise sciences, inform competitive strategies, and allow innovative new research and findings.

Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements.

PubMed

Lan, Hui; Carson, Rachel; Provart, Nicholas J; Bonner, Anthony J

2007-09-21

Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these genes is currently unknown. The purpose of this study is to infer gene function in Arabidopsis using machine-learning algorithms applied to large-scale gene expression data sets, with the goal of identifying genes that are potentially involved in plant response to abiotic stress. Using in house and publicly available data, we assembled a large set of gene expression measurements for A. thaliana. Using those genes of known function, we first evaluated and compared the ability of basic machine-learning algorithms to predict which genes respond to stress. Predictive accuracy was measured using ROC50 and precision curves derived through cross validation. To improve accuracy, we developed a method for combining these classifiers using a weighted-voting scheme. The combined classifier was then trained on genes of known function and applied to genes of unknown function, identifying genes that potentially respond to stress. Visual evidence corroborating the predictions was obtained using electronic Northern analysis. Three of the predicted genes were chosen for biological validation. Gene knockout experiments confirmed that all three are involved in a variety of stress responses. The biological analysis of one of these genes (At1g16850) is presented here, where it is shown to be necessary for the normal response to temperature and NaCl. Supervised learning methods applied to large-scale gene expression measurements can be used to predict gene function. However, the ability of basic learning methods to predict stress response varies widely and depends heavily on how much dimensionality reduction is used. Our method of combining classifiers can improve the accuracy of such predictions - in this case, predictions of genes involved in stress response in plants - and it effectively chooses the appropriate amount of dimensionality reduction automatically. The method provides a useful means of identifying genes in A. thaliana that potentially respond to stress, and we expect it would be useful in other organisms and for other gene functions.

Photodissociation of phenol via nonadiabatic tunneling: Comparison of two ab initio based potential energy surfaces

NASA Astrophysics Data System (ADS)

Xie, Changjian; Guo, Hua

2017-09-01

The nonadiabatic tunneling-facilitated photodissociation of phenol is investigated using a reduced-dimensional quantum model on two ab initio-based coupled potential energy surfaces (PESs). Although dynamics occurs largely on the lower adiabat, the proximity to a conical intersection between the S1 and S2 states requires the inclusion of both the geometric phase (GP) and diagonal Born-Oppenheimer correction (DBOC). The lifetime of the lowest-lying vibronic state is computed using the diabatic and various adiabatic models. The GP and DBOC terms are found to be essential on one set of PESs, but have a small impact on the other.

Estimation of Radiative Efficiency of Chemicals with Potentially Significant Global Warming Potential

EPA Pesticide Factsheets

The set of commercially available chemical substances in commerce that may have significant global warming potential (GWP) is not well defined. Although there are currently over 200 chemicals with high GWP reported by the Intergovernmental Panel on Climate Change, World Meteorological Organization, or Environmental Protection Agency, there may be hundreds of additional chemicals that may also have significant GWP. Evaluation of various approaches to estimate radiative efficiency (RE) and atmospheric lifetime will help to refine GWP estimates for compounds where no measured IR spectrum is available. This study compares values of RE calculated using computational chemistry techniques for 235 chemical compounds against the best available values. It is important to assess the reliability of the underlying computational methods for computing RE to understand the sources of deviations from the best available values. Computed vibrational frequency data is used to estimate RE values using several Pinnock-type models. The values derived using these models are found to be in reasonable agreement with reported RE values (though significant improvement is obtained through scaling). The effect of varying the computational method and basis set used to calculate the frequency data is also discussed. It is found that the vibrational intensities have a strong dependence on basis set and are largely responsible for differences in computed values of RE in this study. Deviations of

The prediction of airborne and structure-borne noise potential for a tire

NASA Astrophysics Data System (ADS)

Sakamoto, Nicholas Y.

Tire/pavement interaction noise is a major component of both exterior pass-by noise and vehicle interior noise. The current testing methods for ranking tires from loud to quiet require expensive equipment, multiple tires, and/or long experimental set-up and run times. If a laboratory based off-vehicle test could be used to identify the airborne and structure-borne potential of a tire from its dynamic characteristics, a relative ranking of a large group of tires could be performed at relatively modest expense. This would provide a smaller sample set of tires for follow-up testing and thus save expense for automobile OEMs. The focus of this research was identifying key noise features from a tire/pavement experiment. These results were compared against a stationary tire test in which the natural response of the tire to a forced input was measured. Since speed was identified as having some effect on the noise, an input function was also developed to allow the tires to be ranked at an appropriate speed. A relative noise model was used on a second sample set of tires to verify if the ranking could be used against interior vehicle measurements. While overall level analysis of the specified spectrum had mixed success, important noise generating features were identified, and the methods used could be improved to develop a standard off-vehicle test to predict a tire's noise potential.

Effects of Baseline Levels of Flexibility and Vertical Jump Ability on Performance Following Different Volumes of Static Stretching and Potentiating Exercises in Elite Gymnasts

PubMed Central

Donti, Olyvia; Tsolakis, Charilaos; Bogdanis, Gregory C.

2014-01-01

This study examined the effects of baseline flexibility and vertical jump ability on straight leg raise range of motion (ROM) and counter-movement jump performance (CMJ) following different volumes of stretching and potentiating exercises. ROM and CMJ were measured after two different warm-up protocols involving static stretching and potentiating exercises. Three groups of elite athletes (10 male, 14 female artistic gymnasts and 10 female rhythmic gymnasts) varying greatly in ROM and CMJ, performed two warm-up routines. One warm-up included short (15 s) static stretching followed by 5 tuck jumps, while the other included long static stretching (30 s) followed by 3x5 tuck jumps. ROM and CMJ were measured before, during and for 12 min after the two warm-up routines. Three-way ANOVA showed large differences between the three groups in baseline ROM and CMJ performance. A type of warm-up x time interaction was found for both ROM (p = 0.031) and CMJ (p = 0.016). However, all athletes, irrespective of group, responded in a similar fashion to the different warm-up protocols for both ROM and CMJ, as indicated from the lack of significant interactions for group (condition x group, time x group or condition x time x group). In the short warm-up protocol, ROM was not affected by stretching, while in the long warm-up protocol ROM increased by 5.9% ± 0.7% (p = 0.001) after stretching. Similarly, CMJ remained unchanged after the short warm-up protocol, but increased by 4.6 ± 0.9% (p = 0.012) 4 min after the long warm- up protocol, despite the increased ROM. It is concluded that the initial levels of flexibility and CMJ performance do not alter the responses of elite gymnasts to warm-up protocols differing in stretching and potentiating exercise volumes. Furthermore, 3 sets of 5 tuck jumps result in a relatively large increase in CMJ performance despite an increase in flexibility in these highly-trained athletes. Key Points The initial levels of flexibility and vertical jump ability have no effect on straight leg raise range of motion (ROM) and counter-movement jump performance (CMJ) of elite gymnasts following warm-up protocols differing in stretching and potentiating exercise volumes Stretching of the main leg muscle groups for only 15 s has no effect on ROM of elite gymnasts In these highly-trained athletes, one set of 5 tuck jumps during warm-up is not adequate to increase CMJ performance, while 3 sets of 5 tuck jumps result in a relatively large increase in CMJ performance (by 4.6% above baseline), despite a 5.9% increase in flexibility due to the 30 s stretching exercises PMID:24570613

Optimizing for Large Planar Fractures in Multistage Horizontal Wells in Enhanced Geothermal Systems Using a Coupled Fluid and Geomechanics Simulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Xiexiaomen; Tutuncu, Azra; Eustes, Alfred

Enhanced Geothermal Systems (EGS) could potentially use technological advancements in coupled implementation of horizontal drilling and multistage hydraulic fracturing techniques in tight oil and shale gas reservoirs along with improvements in reservoir simulation techniques to design and create EGS reservoirs. In this study, a commercial hydraulic fracture simulation package, Mangrove by Schlumberger, was used in an EGS model with largely distributed pre-existing natural fractures to model fracture propagation during the creation of a complex fracture network. The main goal of this study is to investigate optimum treatment parameters in creating multiple large, planar fractures to hydraulically connect a horizontal injectionmore » well and a horizontal production well that are 10,000 ft. deep and spaced 500 ft. apart from each other. A matrix of simulations for this study was carried out to determine the influence of reservoir and treatment parameters on preventing (or aiding) the creation of large planar fractures. The reservoir parameters investigated during the matrix simulations include the in-situ stress state and properties of the natural fracture set such as the primary and secondary fracture orientation, average fracture length, and average fracture spacing. The treatment parameters investigated during the simulations were fluid viscosity, proppant concentration, pump rate, and pump volume. A final simulation with optimized design parameters was performed. The optimized design simulation indicated that high fluid viscosity, high proppant concentration, large pump volume and pump rate tend to minimize the complexity of the created fracture network. Additionally, a reservoir with 'friendly' formation characteristics such as large stress anisotropy, natural fractures set parallel to the maximum horizontal principal stress (SHmax), and large natural fracture spacing also promote the creation of large planar fractures while minimizing fracture complexity.« less

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork.

PubMed

Druka, Arnis; Druka, Ilze; Centeno, Arthur G; Li, Hongqiang; Sun, Zhaohui; Thomas, William T B; Bonar, Nicola; Steffenson, Brian J; Ullrich, Steven E; Kleinhofs, Andris; Wise, Roger P; Close, Timothy J; Potokina, Elena; Luo, Zewei; Wagner, Carola; Schweizer, Günther F; Marshall, David F; Kearsey, Michael J; Williams, Robert W; Waugh, Robbie

2008-11-18

A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.

Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

PubMed

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

PubMed Central

Purcell, Shaun ; Neale, Benjamin ; Todd-Brown, Kathe ; Thomas, Lori ; Ferreira, Manuel A. R. ; Bender, David ; Maller, Julian ; Sklar, Pamela ; de Bakker, Paul I. W. ; Daly, Mark J. ; Sham, Pak C. 

2007-01-01

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis. PMID:17701901

Habitat suitability of the Atlantic bluefin tuna by size class: An ecological niche approach

NASA Astrophysics Data System (ADS)

Druon, Jean-Noël; Fromentin, Jean-Marc; Hanke, Alex R.; Arrizabalaga, Haritz; Damalas, Dimitrios; Tičina, Vjekoslav; Quílez-Badia, Gemma; Ramirez, Karina; Arregui, Igor; Tserpes, George; Reglero, Patricia; Deflorio, Michele; Oray, Isik; Saadet Karakulak, F.; Megalofonou, Persefoni; Ceyhan, Tevfik; Grubišić, Leon; MacKenzie, Brian R.; Lamkin, John; Afonso, Pedro; Addis, Piero

2016-03-01

An ecological niche modelling (ENM) approach was used to predict the potential feeding and spawning habitats of small (5-25 kg, only feeding) and large (>25 kg) Atlantic bluefin tuna (ABFT), Thunnus thynnus, in the Mediterranean Sea, the North Atlantic and the Gulf of Mexico. The ENM was built bridging knowledge on ecological traits of ABFT (e.g. temperature tolerance, mobility, feeding and spawning strategy) with patterns of selected environmental variables (chlorophyll-a fronts and concentration, sea surface current and temperature, sea surface height anomaly) that were identified using an extensive set of precisely geo-located presence data. The results highlight a wider temperature tolerance for larger fish allowing them to feed in the northern - high chlorophyll levels - latitudes up to the Norwegian Sea in the eastern Atlantic and to the Gulf of Saint Lawrence in the western basin. Permanent suitable feeding habitat for small ABFT was predicted to be mostly located in temperate latitudes in the North Atlantic and in the Mediterranean Sea, as well as in subtropical waters off north-west Africa, while summer potential habitat in the Gulf of Mexico was found to be unsuitable for both small and large ABFTs. Potential spawning grounds were found to occur in the Gulf of Mexico from March-April in the south-east to April-May in the north, while favourable conditions evolve in the Mediterranean Sea from mid-May in the eastern to mid-July in the western basin. Other secondary potential spawning grounds not supported by observations were predicted in the Azores area and off Morocco to Senegal during July and August when extrapolating the model settings from the Gulf of Mexico into the North Atlantic. The presence of large ABFT off Florida and the Bahamas in spring was not explained by the model as is, however the environmental variables other than the sea surface height anomaly appeared to be favourable for spawning in part of this area. Defining key spatial and temporal habitats should further help in building spatially-explicit stock assessment models, thus improving the spatial management of bluefin tuna fisheries.

How Many Separable Sources? Model Selection In Independent Components Analysis

PubMed Central

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Fast, Safe, Propellant-Efficient Spacecraft Motion Planning Under Clohessy-Wiltshire-Hill Dynamics

NASA Technical Reports Server (NTRS)

Starek, Joseph A.; Schmerling, Edward; Maher, Gabriel D.; Barbee, Brent W.; Pavone, Marco

2016-01-01

This paper presents a sampling-based motion planning algorithm for real-time and propellant-optimized autonomous spacecraft trajectory generation in near-circular orbits. Specifically, this paper leverages recent algorithmic advances in the field of robot motion planning to the problem of impulsively actuated, propellant- optimized rendezvous and proximity operations under the Clohessy-Wiltshire-Hill dynamics model. The approach calls upon a modified version of the FMT* algorithm to grow a set of feasible trajectories over a deterministic, low-dispersion set of sample points covering the free state space. To enforce safety, the tree is only grown over the subset of actively safe samples, from which there exists a feasible one-burn collision-avoidance maneuver that can safely circularize the spacecraft orbit along its coasting arc under a given set of potential thruster failures. Key features of the proposed algorithm include 1) theoretical guarantees in terms of trajectory safety and performance, 2) amenability to real-time implementation, and 3) generality, in the sense that a large class of constraints can be handled directly. As a result, the proposed algorithm offers the potential for widespread application, ranging from on-orbit satellite servicing to orbital debris removal and autonomous inspection missions.

The ESO Diffuse Interstellar Band Large Exploration Survey (EDIBLES)

NASA Astrophysics Data System (ADS)

Cami, J.; Cox, N. L.; Farhang, A.; Smoker, J.; Elyajouri, M.; Lallement, R.; Bacalla, X.; Bhatt, N. H.; Bron, E.; Cordiner, M. A.; de Koter, A..; Ehrenfreund, P.; Evans, C.; Foing, B. H.; Javadi, A.; Joblin, C.; Kaper, L.; Khosroshahi, H. G.; Laverick, M.; Le Petit, F..; Linnartz, H.; Marshall, C. C.; Monreal-Ibero, A.; Mulas, G.; Roueff, E.; Royer, P.; Salama, F.; Sarre, P. J.; Smith, K. T.; Spaans, M.; van Loon, J. T..; Wade, G.

2018-03-01

The ESO Diffuse Interstellar Band Large Exploration Survey (EDIBLES) is a Large Programme that is collecting high-signal-to-noise (S/N) spectra with UVES of a large sample of O and B-type stars covering a large spectral range. The goal of the programme is to extract a unique sample of high-quality interstellar spectra from these data, representing different physical and chemical environments, and to characterise these environments in great detail. An important component of interstellar spectra is the diffuse interstellar bands (DIBs), a set of hundreds of unidentified interstellar absorption lines. With the detailed line-of-sight information and the high-quality spectra, EDIBLES will derive strong constraints on the potential DIB carrier molecules. EDIBLES will thus guide the laboratory experiments necessary to identify these interstellar “mystery molecules”, and turn DIBs into powerful diagnostics of their environments in our Milky Way Galaxy and beyond. We present some preliminary results showing the unique capabilities of the EDIBLES programme.

Accounting for baryonic effects in cosmic shear tomography: Determining a minimal set of nuisance parameters using PCA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eifler, Tim; Krause, Elisabeth; Dodelson, Scott

2014-05-28

Systematic uncertainties that have been subdominant in past large-scale structure (LSS) surveys are likely to exceed statistical uncertainties of current and future LSS data sets, potentially limiting the extraction of cosmological information. Here we present a general framework (PCA marginalization) to consistently incorporate systematic effects into a likelihood analysis. This technique naturally accounts for degeneracies between nuisance parameters and can substantially reduce the dimension of the parameter space that needs to be sampled. As a practical application, we apply PCA marginalization to account for baryonic physics as an uncertainty in cosmic shear tomography. Specifically, we use CosmoLike to run simulatedmore » likelihood analyses on three independent sets of numerical simulations, each covering a wide range of baryonic scenarios differing in cooling, star formation, and feedback mechanisms. We simulate a Stage III (Dark Energy Survey) and Stage IV (Large Synoptic Survey Telescope/Euclid) survey and find a substantial bias in cosmological constraints if baryonic physics is not accounted for. We then show that PCA marginalization (employing at most 3 to 4 nuisance parameters) removes this bias. Our study demonstrates that it is possible to obtain robust, precise constraints on the dark energy equation of state even in the presence of large levels of systematic uncertainty in astrophysical processes. We conclude that the PCA marginalization technique is a powerful, general tool for addressing many of the challenges facing the precision cosmology program.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Hypotheses generation as supervised link discovery with automated class labeling on large-scale biomedical concept networks

PubMed Central

2012-01-01

Computational approaches to generate hypotheses from biomedical literature have been studied intensively in recent years. Nevertheless, it still remains a challenge to automatically discover novel, cross-silo biomedical hypotheses from large-scale literature repositories. In order to address this challenge, we first model a biomedical literature repository as a comprehensive network of biomedical concepts and formulate hypotheses generation as a process of link discovery on the concept network. We extract the relevant information from the biomedical literature corpus and generate a concept network and concept-author map on a cluster using Map-Reduce frame-work. We extract a set of heterogeneous features such as random walk based features, neighborhood features and common author features. The potential number of links to consider for the possibility of link discovery is large in our concept network and to address the scalability problem, the features from a concept network are extracted using a cluster with Map-Reduce framework. We further model link discovery as a classification problem carried out on a training data set automatically extracted from two network snapshots taken in two consecutive time duration. A set of heterogeneous features, which cover both topological and semantic features derived from the concept network, have been studied with respect to their impacts on the accuracy of the proposed supervised link discovery process. A case study of hypotheses generation based on the proposed method has been presented in the paper. PMID:22759614

EEGVIS: A MATLAB Toolbox for Browsing, Exploring, and Viewing Large Datasets.

PubMed

Robbins, Kay A

2012-01-01

Recent advances in data monitoring and sensor technology have accelerated the acquisition of very large data sets. Streaming data sets from instrumentation such as multi-channel EEG recording usually must undergo substantial pre-processing and artifact removal. Even when using automated procedures, most scientists engage in laborious manual examination and processing to assure high quality data and to indentify interesting or problematic data segments. Researchers also do not have a convenient method of method of visually assessing the effects of applying any stage in a processing pipeline. EEGVIS is a MATLAB toolbox that allows users to quickly explore multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. Customizable summary views reveal potentially interesting sections of data, which users can explore further by clicking to examine using detailed viewing components. The viewer and a companion browser are built on our MoBBED framework, which has a library of modular viewing components that can be mixed and matched to best reveal structure. Users can easily create new viewers for their specific data without any programming during the exploration process. These viewers automatically support pan, zoom, resizing of individual components, and cursor exploration. The toolbox can be used directly in MATLAB at any stage in a processing pipeline, as a plug-in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license at http://visual.cs.utsa.edu/eegvis.

Large-scale quarantine following biological terrorism in the United States: scientific examination, logistic and legal limits, and possible consequences.

PubMed

Barbera, J; Macintyre, A; Gostin, L; Inglesby, T; O'Toole, T; DeAtley, C; Tonat, K; Layton, M

2001-12-05

Concern for potential bioterrorist attacks causing mass casualties has increased recently. Particular attention has been paid to scenarios in which a biological agent capable of person-to-person transmission, such as smallpox, is intentionally released among civilians. Multiple public health interventions are possible to effect disease containment in this context. One disease control measure that has been regularly proposed in various settings is the imposition of large-scale or geographic quarantine on the potentially exposed population. Although large-scale quarantine has not been implemented in recent US history, it has been used on a small scale in biological hoaxes, and it has been invoked in federally sponsored bioterrorism exercises. This article reviews the scientific principles that are relevant to the likely effectiveness of quarantine, the logistic barriers to its implementation, legal issues that a large-scale quarantine raises, and possible adverse consequences that might result from quarantine action. Imposition of large-scale quarantine-compulsory sequestration of groups of possibly exposed persons or human confinement within certain geographic areas to prevent spread of contagious disease-should not be considered a primary public health strategy in most imaginable circumstances. In the majority of contexts, other less extreme public health actions are likely to be more effective and create fewer unintended adverse consequences than quarantine. Actions and areas for future research, policy development, and response planning efforts are provided.

Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

PubMed Central

Tabchy, Adel; Eltonsy, Nevine; Housman, David E.; Mills, Gordon B.

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. PMID:23577104

Systematic identification of combinatorial drivers and targets in cancer cell lines.

PubMed

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

Implications from the Use of Non-timber Forest Products on the Consumption of Wood as a Fuel Source in Human-Dominated Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Cavalcanti, Maria Clara B. T.; Ramos, Marcelo Alves; Araújo, Elcida L.; Albuquerque, Ulysses P.

2015-08-01

Little is known about what possible effects on wood resources might be caused by non-timber forest products (NTFPs). Here, we assessed the patterns of fuelwood consumption related to an NTFP ( Caryocar coriaceum) oil extraction and how this non-domestic activity can indirectly increase the use pressure on fuelwood species in a protected area, semiarid of Brazil. We conducted semi-structured interviews, in situ inventories, phytosociological surveys, and analyses of wood quality to identify the set of woody plants used in oil production. Householders use large volumes of dry wood and a set of woody species, which are highly exploited. Additionally, many preferred species have low fuel potential and suffer much use pressure. The best fuelwood species are underused, what requires management strategies to improve their potential as a source of energy. As a result, we suggest some conservation and management actions of fuelwood resources related to the use of NTFPs.

Reply & Supply: Efficient crowdsourcing when workers do more than answer questions

PubMed Central

McAndrew, Thomas C.; Guseva, Elizaveta A.

2017-01-01

Crowdsourcing works by distributing many small tasks to large numbers of workers, yet the true potential of crowdsourcing lies in workers doing more than performing simple tasks—they can apply their experience and creativity to provide new and unexpected information to the crowdsourcer. One such case is when workers not only answer a crowdsourcer’s questions but also contribute new questions for subsequent crowd analysis, leading to a growing set of questions. This growth creates an inherent bias for early questions since a question introduced earlier by a worker can be answered by more subsequent workers than a question introduced later. Here we study how to perform efficient crowdsourcing with such growing question sets. By modeling question sets as networks of interrelated questions, we introduce algorithms to help curtail the growth bias by efficiently distributing workers between exploring new questions and addressing current questions. Experiments and simulations demonstrate that these algorithms can efficiently explore an unbounded set of questions without losing confidence in crowd answers. PMID:28806413

Electronic and spectroscopic characterizations of SNP isomers

NASA Astrophysics Data System (ADS)

Trabelsi, Tarek; Al Mogren, Muneerah Mogren; Hochlaf, Majdi; Francisco, Joseph S.

2018-02-01

High-level ab initio electronic structure calculations were performed to characterize SNP isomers. In addition to the known linear SNP, cyc-PSN, and linear SPN isomers, we identified a fourth isomer, linear PSN, which is located ˜2.4 eV above the linear SNP isomer. The low-lying singlet and triplet electronic states of the linear SNP and SPN isomers were investigated using a multi-reference configuration interaction method and large basis set. Several bound electronic states were identified. However, their upper rovibrational levels were predicted to pre-dissociate, leading to S + PN, P + NS products, and multi-step pathways were discovered. For the ground states, a set of spectroscopic parameters were derived using standard and explicitly correlated coupled-cluster methods in conjunction with augmented correlation-consistent basis sets extrapolated to the complete basis set limit. We also considered scalar and core-valence effects. For linear isomers, the rovibrational spectra were deduced after generation of their 3D-potential energy surfaces along the stretching and bending coordinates and variational treatments of the nuclear motions.

wACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials

NASA Astrophysics Data System (ADS)

Gastegger, M.; Schwiedrzik, L.; Bittermann, M.; Berzsenyi, F.; Marquetand, P.

2018-06-01

We introduce weighted atom-centered symmetry functions (wACSFs) as descriptors of a chemical system's geometry for use in the prediction of chemical properties such as enthalpies or potential energies via machine learning. The wACSFs are based on conventional atom-centered symmetry functions (ACSFs) but overcome the undesirable scaling of the latter with an increasing number of different elements in a chemical system. The performance of these two descriptors is compared using them as inputs in high-dimensional neural network potentials (HDNNPs), employing the molecular structures and associated enthalpies of the 133 855 molecules containing up to five different elements reported in the QM9 database as reference data. A substantially smaller number of wACSFs than ACSFs is needed to obtain a comparable spatial resolution of the molecular structures. At the same time, this smaller set of wACSFs leads to a significantly better generalization performance in the machine learning potential than the large set of conventional ACSFs. Furthermore, we show that the intrinsic parameters of the descriptors can in principle be optimized with a genetic algorithm in a highly automated manner. For the wACSFs employed here, we find however that using a simple empirical parametrization scheme is sufficient in order to obtain HDNNPs with high accuracy.

Ab initio study of the diatomic fluorides FeF, CoF, NiF, and CuF.

PubMed

Koukounas, Constantine; Mavridis, Aristides

2008-11-06

The late-3d transition-metal diatomic fluorides MF = FeF, CoF, NiF, and CuF have been studied using variational multireference (MRCI) and coupled-cluster [RCCSD(T)] methods, combined with large to very large basis sets. We examined a total of 35 (2S+1)|Lambda| states, constructing as well 29 full potential energy curves through the MRCI method. All examined states are ionic, diabatically correlating to M(+)+F(-)((1)S). Notwithstanding the "eccentric" character of the 3d transition metals and the difficulties to accurately be described with all-electron ab initio methods, our results are, in general, in very good agreement with available experimental numbers.

Sculpting Computational-Level Models.

PubMed

Blokpoel, Mark

2017-06-27

In this commentary, I advocate for strict relations between Marr's levels of analysis. Under a strict relationship, each level is exactly implemented by the subordinate level. This yields two benefits. First, it brings consistency for multilevel explanations. Second, similar to how a sculptor chisels away superfluous marble, a modeler can chisel a computational-level model by applying constraints. By sculpting the model, one restricts the (potentially infinitely large) set of possible algorithmic- and implementational-level theories. Copyright © 2017 Cognitive Science Society, Inc.

Interface Engineering with MoS2 -Pd Nanoparticles Hybrid Structure for a Low Voltage Resistive Switching Memory.

PubMed

Wang, Xue-Feng; Tian, He; Zhao, Hai-Ming; Zhang, Tian-Yu; Mao, Wei-Quan; Qiao, Yan-Cong; Pang, Yu; Li, Yu-Xing; Yang, Yi; Ren, Tian-Ling

2018-01-01

Metal oxide-based resistive random access memory (RRAM) has attracted a lot of attention for its scalability, temperature robustness, and potential to achieve machine learning. However, a thick oxide layer results in relatively high program voltage while a thin one causes large leakage current and a small window. Owing to these fundamental limitations, by optimizing the oxide layer itself a novel interface engineering idea is proposed to reduce the programming voltage, increase the uniformity and on/off ratio. According to this idea, a molybdenum disulfide (MoS 2 )-palladium nanoparticles hybrid structure is used to engineer the oxide/electrode interface of hafnium oxide (HfO x )-based RRAM. Through its interface engineering, the set voltage can be greatly lowered (from -3.5 to -0.8 V) with better uniformity under a relatively thick HfO x layer (≈15 nm), and a 30 times improvement of the memory window can be obtained. Moreover, due to the atomic thickness of MoS 2 film and high transmittance of ITO, the proposed RRAM exhibits high transparency in visible light. As the proposed interface-engineering RRAM exhibits good transparency, low SET voltage, and a large resistive switching window, it has huge potential in data storage in transparent circuits and wearable electronics with relatively low supply voltage. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Limits to reproductive success of Sarracenia purpurea (Sarraceniaceae).

PubMed

Ne'eman, Gidi; Ne'eman, Rina; Ellison, Aaron M

2006-11-01

Plant biologists have an enduring interest in assessing components of plant fitness and determining limits to seed set. Consequently, the relative contributions of resource and pollinator availability have been documented for a large number of plant species. We experimentally examined the roles of resource and pollen availability on seed set by the northern pitcher plant Sarracenia purpurea. We were able to distinguish the relative contributions of carbon (photosynthate) and mineral nutrients (nitrogen) to reproductive success. We also determined potential pollinators of this species. The bees Bombus affinis and Augochlorella aurata and the fly Fletcherimyia fletcheri were the only floral visitors to S. purpurea that collected pollen. Supplemental pollination increased seed set by <10%, a much lower percentage than would be expected, given data from noncarnivorous, animal-pollinated taxa. Seed set was reduced by 14% in plants that could not capture prey and by another 23% in plants whose pitcher-shaped leaves were also prevented from photosynthesizing. We conclude that resources are more important than pollen availability in determining seed set by this pitcher plant and that reproductive output may be another "cost" of the carnivorous habit.

Characterization of a Methanogenic Community within an Algal Fed Anaerobic Digester

PubMed Central

Ellis, Joshua T.; Tramp, Cody; Sims, Ronald C.; Miller, Charles D.

2012-01-01

The microbial diversity and metabolic potential of a methanogenic consortium residing in a 3785-liter anaerobic digester, fed with wastewater algae, was analyzed using 454 pyrosequencing technology. DNA was extracted from anaerobic sludge material and used in metagenomic analysis through PCR amplification of the methyl-coenzyme M reductase α subunit (mcrA) gene using primer sets ML, MCR, and ME. The majority of annotated mcrA sequences were assigned taxonomically to the genera Methanosaeta in the order Methanosarcinales. Methanogens from the genus Methanosaeta are obligate acetotrophs, suggesting this genus plays a dominant role in methane production from the analyzed fermentation sample. Numerous analyzed sequences within the algae fed anaerobic digester were unclassified and could not be assigned taxonomically. Relative amplicon frequencies were determined for each primer set to determine the utility of each in pyrosequencing. Primer sets ML and MCR performed better quantitatively (representing the large majority of analyzed sequences) than primer set ME. However, each of these primer sets was shown to provide a quantitatively unique community structure, and thus they are of equal importance in mcrA metagenomic analysis. PMID:23724331

A theoretical study of the adiabatic and vertical ionization potentials of water.

PubMed

Feller, David; Davidson, Ernest R

2018-06-21

Theoretical predictions of the three lowest adiabatic and vertical ionization potentials of water were obtained from the Feller-Peterson-Dixon approach. This approach combines multiple levels of coupled cluster theory with basis sets as large as aug-cc-pV8Z in some cases and various corrections up to and including full configuration interaction theory. While agreement with experiment for the adiabatic ionization potential of the lowest energy 2 B 1 state was excellent, differences for other states were much larger, sometimes exceeding 10 kcal/mol (0.43 eV). Errors of this magnitude are inconsistent with previous benchmark work on 52 adiabatic ionization potentials, where a root mean square of 0.20 kcal/mol (0.009 eV) was found. Difficulties in direct comparisons between theory and experiment for vertical ionization potentials are discussed. With regard to the differences found for the 2 A 1 / 2 Π u and 2 B 2 adiabatic ionization potentials, a reinterpretation of the experimental spectrum appears justified.

Segtor: Rapid Annotation of Genomic Coordinates and Single Nucleotide Variations Using Segment Trees

PubMed Central

Renaud, Gabriel; Neves, Pedro; Folador, Edson Luiz; Ferreira, Carlos Gil; Passetti, Fabio

2011-01-01

Various research projects often involve determining the relative position of genomic coordinates, intervals, single nucleotide variations (SNVs), insertions, deletions and translocations with respect to genes and their potential impact on protein translation. Due to the tremendous increase in throughput brought by the use of next-generation sequencing, investigators are routinely faced with the need to annotate very large datasets. We present Segtor, a tool to annotate large sets of genomic coordinates, intervals, SNVs, indels and translocations. Our tool uses segment trees built using the start and end coordinates of the genomic features the user wishes to use instead of storing them in a database management system. The software also produces annotation statistics to allow users to visualize how many coordinates were found within various portions of genes. Our system currently can be made to work with any species available on the UCSC Genome Browser. Segtor is a suitable tool for groups, especially those with limited access to programmers or with interest to analyze large amounts of individual genomes, who wish to determine the relative position of very large sets of mapped reads and subsequently annotate observed mutations between the reads and the reference. Segtor (http://lbbc.inca.gov.br/segtor/) is an open-source tool that can be freely downloaded for non-profit use. We also provide a web interface for testing purposes. PMID:22069465

Complex extreme learning machine applications in terahertz pulsed signals feature sets.

PubMed

Yin, X-X; Hadjiloucas, S; Zhang, Y

2014-11-01

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis

PubMed Central

Finak, Greg; Frelinger, Jacob; Jiang, Wenxin; Newell, Evan W.; Ramey, John; Davis, Mark M.; Kalams, Spyros A.; De Rosa, Stephen C.; Gottardo, Raphael

2014-01-01

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment. PMID:25167361

OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.

PubMed

Finak, Greg; Frelinger, Jacob; Jiang, Wenxin; Newell, Evan W; Ramey, John; Davis, Mark M; Kalams, Spyros A; De Rosa, Stephen C; Gottardo, Raphael

2014-08-01

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment.

A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

PubMed

Pinto, Nicolas; Doukhan, David; DiCarlo, James J; Cox, David D

2009-11-01

While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

PubMed

Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

High-Throughput Tabular Data Processor – Platform independent graphical tool for processing large data sets

PubMed Central

Bałut, Magdalena; Buckley, Patrick G.; Ochocka, J. Renata; Bartoszewski, Rafał; Crossman, David K.; Messiaen, Ludwine M.; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp). PMID:29432475

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

PubMed Central

Pinto, Nicolas; Doukhan, David; DiCarlo, James J.; Cox, David D.

2009-01-01

While many models of biological object recognition share a common set of “broad-stroke” properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model—e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct “parts” have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision. PMID:19956750

Picking Cell Lines for High-Throughput Transcriptomic Toxicity ...

EPA Pesticide Factsheets

High throughput, whole genome transcriptomic profiling is a promising approach to comprehensively evaluate chemicals for potential biological effects. To be useful for in vitro toxicity screening, gene expression must be quantified in a set of representative cell types that captures the diversity of potential responses across chemicals. The ideal dataset to select these cell types would consist of hundreds of cell types treated with thousands of chemicals, but does not yet exist. However, basal gene expression data may be useful as a surrogate for representing the relevant biological space necessary for cell type selection. The goal of this study was to identify a small (< 20) number of cell types that capture a large, quantifiable fraction of basal gene expression diversity. Three publicly available collections of Affymetrix U133+2.0 cellular gene expression data were used: 1) 59 cell lines from the NCI60 set; 2) 303 primary cell types from the Mabbott et al (2013) expression atlas; and 3) 1036 cell lines from the Cancer Cell Line Encyclopedia. The data were RMA normalized, log-transformed, and the probe sets mapped to HUGO gene identifiers. The results showed that <20 cell lines capture only a small fraction of the total diversity in basal gene expression when evaluated using either the entire set of 20960 HUGO genes or a subset of druggable genes likely to be chemical targets. The fraction of the total gene expression variation explained was consistent when

Towards a Full-sky, High-resolution Dust Extinction Map with WISE and Planck

NASA Astrophysics Data System (ADS)

Meisner, Aaron M.; Finkbeiner, D. P.

2014-01-01

We have recently completed a custom processing of the entire WISE 12 micron All-sky imaging data set. The result is a full-sky map of diffuse, mid-infrared Galactic dust emission with angular resolution of 15 arcseconds, and with contaminating artifacts such as compact sources removed. At the same time, the 2013 Planck HFI maps represent a complementary data set in the far-infrared, with zero-point relatively immune to zodiacal contamination and angular resolution superior to previous full-sky data sets at similar frequencies. Taken together, these WISE and Planck data products present an opportunity to improve upon the SFD (1998) dust extinction map, by virtue of enhanced angular resolution and potentially better-controlled systematics on large scales. We describe our continuing efforts to construct and test high-resolution dust extinction and temperature maps based on our custom WISE processing and Planck HFI data.

Efficient bulk-loading of gridfiles

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Nicol, David M.

1994-01-01

This paper considers the problem of bulk-loading large data sets for the gridfile multiattribute indexing technique. We propose a rectilinear partitioning algorithm that heuristically seeks to minimize the size of the gridfile needed to ensure no bucket overflows. Empirical studies on both synthetic data sets and on data sets drawn from computational fluid dynamics applications demonstrate that our algorithm is very efficient, and is able to handle large data sets. In addition, we present an algorithm for bulk-loading data sets too large to fit in main memory. Utilizing a sort of the entire data set it creates a gridfile without incurring any overflows.

Lightcurve Studies of Trans-Neptunian Objects from the Outer Solar System Origins Survey using the Hyper Suprime-Camera

NASA Astrophysics Data System (ADS)

Alexandersen, Mike; Benecchi, Susan D.; Chen, Ying-Tung; Schwamb, Megan Elizabeth; Wang, Shiang-Yu; Lehner, Matthew; Gladman, Brett; Kavelaars, JJ; Petit, Jean-Marc; Bannister, Michele T.; Gwyn, Stephen; Volk, Kathryn

2016-10-01

Lightcurves can reveal information about the gravitational processes that have acted on small bodies since their formation and/or their gravitational history.At the extremes, lightcurves can provide constraints on the material properties and interior structure of individual objects.In large sets, lightcurves can possibly shed light on the source of small body populations that did not form in place (such as the dynamically excited trans-Neptunian Objects (TNOs)).We have used the sparsely sampled photometry from the well characterized Outer Solar System Origins Survey (OSSOS) discovery and recovery observations to identify TNOs with potentially large amplitude lightcurves.Large lightcurve amplitudes would indicate that the objects are likely elongated or in potentially interesting spin states; however, this would need to be confirmed with further follow-up observations.We here present the results of a 6-hour pilot study of a subset of 17 OSSOS objects using Hyper Suprime-Cam (HSC) on the Subaru Telescope.Subaru's large aperture and HSC's large field of view allows us to obtain measurements on multiple objects with a range of magnitudes in each telescope pointing.Photometry was carefully measusured using an elongated aperture method to account for the motion of the objects, producing the short but precise lightcurves that we present here.The OSSOS objects span a large range of sizes, from as large as several hundred kilometres to as small as a few tens of kilometres in diameter.We are thus investigating smaller objects than previous light-curve projects have typically studied.

Bringing modeling to the masses: A web based system to predict potential species distributions

USGS Publications Warehouse

Graham, Jim; Newman, Greg; Kumar, Sunil; Jarnevich, Catherine S.; Young, Nick; Crall, Alycia W.; Stohlgren, Thomas J.; Evangelista, Paul

2010-01-01

Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.

A two-step hierarchical hypothesis set testing framework, with applications to gene expression data on ordered categories

PubMed Central

2014-01-01

Background In complex large-scale experiments, in addition to simultaneously considering a large number of features, multiple hypotheses are often being tested for each feature. This leads to a problem of multi-dimensional multiple testing. For example, in gene expression studies over ordered categories (such as time-course or dose-response experiments), interest is often in testing differential expression across several categories for each gene. In this paper, we consider a framework for testing multiple sets of hypothesis, which can be applied to a wide range of problems. Results We adopt the concept of the overall false discovery rate (OFDR) for controlling false discoveries on the hypothesis set level. Based on an existing procedure for identifying differentially expressed gene sets, we discuss a general two-step hierarchical hypothesis set testing procedure, which controls the overall false discovery rate under independence across hypothesis sets. In addition, we discuss the concept of the mixed-directional false discovery rate (mdFDR), and extend the general procedure to enable directional decisions for two-sided alternatives. We applied the framework to the case of microarray time-course/dose-response experiments, and proposed three procedures for testing differential expression and making multiple directional decisions for each gene. Simulation studies confirm the control of the OFDR and mdFDR by the proposed procedures under independence and positive correlations across genes. Simulation results also show that two of our new procedures achieve higher power than previous methods. Finally, the proposed methodology is applied to a microarray dose-response study, to identify 17 β-estradiol sensitive genes in breast cancer cells that are induced at low concentrations. Conclusions The framework we discuss provides a platform for multiple testing procedures covering situations involving two (or potentially more) sources of multiplicity. The framework is easy to use and adaptable to various practical settings that frequently occur in large-scale experiments. Procedures generated from the framework are shown to maintain control of the OFDR and mdFDR, quantities that are especially relevant in the case of multiple hypothesis set testing. The procedures work well in both simulations and real datasets, and are shown to have better power than existing methods. PMID:24731138

Graphical Methods for Reducing, Visualizing and Analyzing Large Data Sets Using Hierarchical Terminologies

PubMed Central

Jing, Xia; Cimino, James J.

2011-01-01

Objective: To explore new graphical methods for reducing and analyzing large data sets in which the data are coded with a hierarchical terminology. Methods: We use a hierarchical terminology to organize a data set and display it in a graph. We reduce the size and complexity of the data set by considering the terminological structure and the data set itself (using a variety of thresholds) as well as contributions of child level nodes to parent level nodes. Results: We found that our methods can reduce large data sets to manageable size and highlight the differences among graphs. The thresholds used as filters to reduce the data set can be used alone or in combination. We applied our methods to two data sets containing information about how nurses and physicians query online knowledge resources. The reduced graphs make the differences between the two groups readily apparent. Conclusions: This is a new approach to reduce size and complexity of large data sets and to simplify visualization. This approach can be applied to any data sets that are coded with hierarchical terminologies. PMID:22195119

Scada Malware, a Proof of Concept

NASA Astrophysics Data System (ADS)

Carcano, Andrea; Fovino, Igor Nai; Masera, Marcelo; Trombetta, Alberto

Critical Infrastructures are nowadays exposed to new kind of threats. The cause of such threats is related to the large number of new vulnerabilities and architectural weaknesses introduced by the extensive use of ICT and Network technologies into such complex critical systems. Of particular interest are the set of vulnerabilities related to the class of communication protocols normally known as “SCADA” protocols, under which fall all the communication protocols used to remotely control the RTU devices of an industrial system. In this paper we present a proof of concept of the potential effects of a set of computer malware specifically designed and created in order to impact, by taking advantage of some vulnerabilities of the ModBUS protocol, on a typical Supervisory Control and Data Acquisition system.

Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guarnieri, Michael T.; Nag, Ambarish; Yang, Shihui

2013-11-01

Oleaginous microalgae are capable of producing large quantities of fatty acids and triacylglycerides. As such, they are promising feedstocks for the production of biofuels and bioproducts. Genetic strain-engineering strategies offer a means to accelerate the commercialization of algal biofuels by improving the rate and total accumulation of microalgal lipids. However, the industrial potential of these organisms remains to be met, largely due to the incomplete knowledgebase surrounding the mechanisms governing the induction of algal lipid biosynthesis. Such strategies require further elucidation of genes and gene products controlling algal lipid accumulation. In this study, we have set out to examine thesemore » mechanisms and identify novel strain-engineering targets in the oleaginous microalga, Chlorella vulgaris. Comparative shotgun proteomic analyses have identified a number of novel targets, including previously unidentified transcription factors and proteins involved in cell signaling and cell cycle regulation. These results lay the foundation for strain-improvement strategies and demonstrate the power of translational proteomic analysis.« less

Quantitative Profiling of Peptides from RNAs classified as non-coding

PubMed Central

Prabakaran, Sudhakaran; Hemberg, Martin; Chauhan, Ruchi; Winter, Dominic; Tweedie-Cullen, Ry Y.; Dittrich, Christian; Hong, Elizabeth; Gunawardena, Jeremy; Steen, Hanno; Kreiman, Gabriel; Steen, Judith A.

2014-01-01

Only a small fraction of the mammalian genome codes for messenger RNAs destined to be translated into proteins, and it is generally assumed that a large portion of transcribed sequences - including introns and several classes of non-coding RNAs (ncRNAs) do not give rise to peptide products. A systematic examination of translation and physiological regulation of ncRNAs has not been conducted. Here, we use computational methods to identify the products of non-canonical translation in mouse neurons by analyzing unannotated transcripts in combination with proteomic data. This study supports the existence of non-canonical translation products from both intragenic and extragenic genomic regions, including peptides derived from anti-sense transcripts and introns. Moreover, the studied novel translation products exhibit temporal regulation similar to that of proteins known to be involved in neuronal activity processes. These observations highlight a potentially large and complex set of biologically regulated translational events from transcripts formerly thought to lack coding potential. PMID:25403355

Structural Feasibility Analysis of a Robotically Assembled Very Large Aperture Optical Space Telescope

NASA Technical Reports Server (NTRS)

Wilkie, William Keats; Williams, R. Brett; Agnes, Gregory S.; Wilcox, Brian H.

2007-01-01

This paper presents a feasibility study of robotically constructing a very large aperture optical space telescope on-orbit. Since the largest engineering challenges are likely to reside in the design and assembly of the 150-m diameter primary reflector, this preliminary study focuses on this component. The same technology developed for construction of the primary would then be readily used for the smaller optical structures (secondary, tertiary, etc.). A reasonable set of ground and on-orbit loading scenarios are compiled from the literature and used to define the structural performance requirements and size the primary reflector. A surface precision analysis shows that active adjustment of the primary structure is required in order to meet stringent optical surface requirements. Two potential actuation strategies are discussed along with potential actuation devices at the current state of the art. The finding of this research effort indicate that successful technology development combined with further analysis will likely enable such a telescope to be built in the future.

The use of Benford's law for evaluation of quality of occupational hygiene data.

PubMed

De Vocht, Frank; Kromhout, Hans

2013-04-01

Benford's law is the contra-intuitive empirical observation that the digits 1-9 are not equally likely to appear as the initial digit in numbers resulting from the same phenomenon. Manipulated, unrelated, or created numbers usually do not follow Benford's law, and as such this law has been used in the investigation of fraudulent data in, for example, accounting and to identify errors in data sets due to, for example, data transfer. We describe the use of Benford's law to screen occupational hygiene measurement data sets using exposure data from the European rubber manufacturing industry as an illustration. Two rubber process dust measurement data sets added to the European Union ExAsRub project but initially collected by the UK Health and Safety Executive (HSE) and British Rubber Manufacturers' Association (BRMA) and one pre- and one post-treatment n-nitrosamines data set collated in the German MEGA database and also added to the ExAsRub database were compared with the expected first-digit (1BL) and second-digit (2BL) Benford distributions. Evaluation indicated only small deviations from the expected 1BL and 2BL distributions for the data sets collated by the UK HSE and industry (BRMA), respectively, while for the MEGA data larger deviations were observed. To a large extent the latter could be attributed to imputation and replacement by a constant of n-nitrosamine measurements below the limit of detection, but further evaluation of these data to determine why other deviations from 1BL and 2BL expected distributions exist may be beneficial. Benford's law is a straightforward and easy-to-implement analytical tool to evaluate the quality of occupational hygiene data sets, and as such can be used to detect potential problems in large data sets that may be caused by malcontent a priori or a posteriori manipulation of data sets and by issues like treatment of observations below the limit of detection, rounding and transfer of data.

Carbon dioxide efficiency of terrestrial enhanced weathering.

PubMed

Moosdorf, Nils; Renforth, Phil; Hartmann, Jens

2014-05-06

Terrestrial enhanced weathering, the spreading of ultramafic silicate rock flour to enhance natural weathering rates, has been suggested as part of a strategy to reduce global atmospheric CO2 levels. We budget potential CO2 sequestration against associated CO2 emissions to assess the net CO2 removal of terrestrial enhanced weathering. We combine global spatial data sets of potential source rocks, transport networks, and application areas with associated CO2 emissions in optimistic and pessimistic scenarios. The results show that the choice of source rocks and material comminution technique dominate the CO2 efficiency of enhanced weathering. CO2 emissions from transport amount to on average 0.5-3% of potentially sequestered CO2. The emissions of material mining and application are negligible. After accounting for all emissions, 0.5-1.0 t CO2 can be sequestered on average per tonne of rock, translating into a unit cost from 1.6 to 9.9 GJ per tonne CO2 sequestered by enhanced weathering. However, to control or reduce atmospheric CO2 concentrations substantially with enhanced weathering would require very large amounts of rock. Before enhanced weathering could be applied on large scales, more research is needed to assess weathering rates, potential side effects, social acceptability, and mechanisms of governance.

The Implicitome: A Resource for Rationalizing Gene-Disease Associations

PubMed Central

van der Horst, Eelke; Kaliyaperumal, Rajaram; Mina, Eleni; Tatum, Zuotian; Laros, Jeroen F. J.; van Mulligen, Erik M.; Schuemie, Martijn; Aten, Emmelien; Li, Tong Shu; Bruskiewich, Richard; Good, Benjamin M.; Su, Andrew I.; Kors, Jan A.; den Dunnen, Johan; van Ommen, Gert-Jan B.; Roos, Marco; ‘t Hoen, Peter A.C.; Mons, Barend; Schultes, Erik A.

2016-01-01

High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations. PMID:26919047

Feasible Application Area Study for Linear Laser Cutting in Paper Making Processes

NASA Astrophysics Data System (ADS)

Happonen, A.; Stepanov, A.; Piili, H.

Traditional industry sectors, like paper making industry, tend to stay within well-known technology rather than going forward towards promising, but still quite new technical solutions and applications. This study analyses the feasibility of the laser cutting in large-scale industrial paper making processes. Aim was to reveal development and process related challenges and improvement potential in paper making processes by utilizing laser technology. This study has been carried out, because there still seems to be only few large-scale industrial laser processing applications in paper converting processes worldwide, even in the beginning of 2010's. Because of this, the small-scale use of lasers in paper material manufacturing industry is related to a shortage of well-known and widely available published research articles and published measurement data (e.g. actual achieved cut speeds with high quality cut edges, set-up times and so on). It was concluded that laser cutting has strong potential in industrial applications for paper making industries. This potential includes quality improvements and a competitive advantage for paper machine manufacturers and industry. The innovations have also added potential, when developing new paper products. An example of these kinds of products are ones with printed intelligence, which could be a new business opportunity for the paper industries all around the world.

Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

PubMed

Beltz, Adriene M; Molenaar, Peter C M

2016-01-01

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

Simple Food Group Diversity Indicators Predict Micronutrient Adequacy of Women’s Diets in 5 Diverse, Resource-Poor Settings1234567

PubMed Central

Arimond, Mary; Wiesmann, Doris; Becquey, Elodie; Carriquiry, Alicia; Daniels, Melissa C.; Deitchler, Megan; Fanou-Fogny, Nadia; Joseph, Maria L.; Kennedy, Gina; Martin-Prevel, Yves; Torheim, Liv Elin

2010-01-01

Women of reproductive age living in resource-poor settings are at high risk of inadequate micronutrient intakes when diets lack diversity and are dominated by staple foods. Yet comparative information on diet quality is scarce and quantitative data on nutrient intakes is expensive and difficult to gather. We assessed the potential of simple indicators of dietary diversity, such as could be generated from large household surveys, to serve as proxy indicators of micronutrient adequacy for population-level assessment. We used 5 existing data sets (from Burkina Faso, Mali, Mozambique, Bangladesh, and the Philippines) with repeat 24-h recalls to construct 8 candidate food group diversity indicators (FGI) and to calculate the mean probability of adequacy (MPA) for 11 micronutrients. FGI varied in food group disaggregation and in minimum consumption required for a food group to count. There were large gaps between intakes and requirements across a range of micronutrients in each site. All 8 FGI were correlated with MPA in all sites; regression analysis confirmed that associations remained when controlling for energy intake. Assessment of dichotomous indicators through receiver-operating characteristic analysis showed moderate predictive strength for the best choice indicators, which varied by site. Simple FGI hold promise as proxy indicators of micronutrient adequacy. PMID:20881077

ESR paper on the proper use of mobile devices in radiology.

PubMed

2018-04-01

Mobile devices (smartphones, tablets, etc.) have become key methods of communication, data access and data sharing for the population in the past decade. The technological capabilities of these devices have expanded very rapidly; for example, their in-built cameras have largely replaced conventional cameras. Their processing power is often sufficient to handle the large data sets of radiology studies and to manipulate images and studies directly on hand-held devices. Thus, they can be used to transmit and view radiology studies, often in locations remote from the source of the imaging data. They are not recommended for primary interpretation of radiology studies, but they facilitate sharing of studies for second opinions, viewing of studies and reports by clinicians at the bedside, etc. Other potential applications include remote participation in educational activity (e.g. webinars) and consultation of online educational content, e-books, journals and reference sources. Social-networking applications can be used for exchanging professional information and teaching. Users of mobile device must be aware of the vulnerabilities and dangers of their use, in particular regarding the potential for inappropriate sharing of confidential patient information, and must take appropriate steps to protect confidential data. • Mobile devices have revolutionized communication in the past decade, and are now ubiquitous. • Mobile devices have sufficient processing power to manipulate and display large data sets of radiological images. • Mobile devices allow transmission & sharing of radiologic studies for purposes of second opinions, bedside review of images, teaching, etc. • Mobile devices are currently not recommended as tools for primary interpretation of radiologic studies. • The use of mobile devices for image and data transmission carries risks, especially regarding confidentiality, which must be considered.

Modeling Hurricane Katrina's merchantable timber and wood damage in south Mississippi using remotely sensed and field-measured data

NASA Astrophysics Data System (ADS)

Collins, Curtis Andrew

Ordinary and weighted least squares multiple linear regression techniques were used to derive 720 models predicting Katrina-induced storm damage in cubic foot volume (outside bark) and green weight tons (outside bark). The large number of models was dictated by the use of three damage classes, three product types, and four forest type model strata. These 36 models were then fit and reported across 10 variable sets and variable set combinations for volume and ton units. Along with large model counts, potential independent variables were created using power transforms and interactions. The basis of these variables was field measured plot data, satellite (Landsat TM and ETM+) imagery, and NOAA HWIND wind data variable types. As part of the modeling process, lone variable types as well as two-type and three-type combinations were examined. By deriving models with these varying inputs, model utility is flexible as all independent variable data are not needed in future applications. The large number of potential variables led to the use of forward, sequential, and exhaustive independent variable selection techniques. After variable selection, weighted least squares techniques were often employed using weights of one over the square root of the pre-storm volume or weight of interest. This was generally successful in improving residual variance homogeneity. Finished model fits, as represented by coefficient of determination (R2), surpassed 0.5 in numerous models with values over 0.6 noted in a few cases. Given these models, an analyst is provided with a toolset to aid in risk assessment and disaster recovery should Katrina-like weather events reoccur.

Optical spectroscopy for quantitative sensing in human pancreatic tissues

NASA Astrophysics Data System (ADS)

Wilson, Robert H.; Chandra, Malavika; Lloyd, William; Chen, Leng-Chun; Scheiman, James; Simeone, Diane; McKenna, Barbara; Mycek, Mary-Ann

2011-07-01

Pancreatic adenocarcinoma has a five-year survival rate of only 6%, largely because current diagnostic methods cannot reliably detect the disease in its early stages. Reflectance and fluorescence spectroscopies have the potential to provide quantitative, minimally-invasive means of distinguishing pancreatic adenocarcinoma from normal pancreatic tissue and chronic pancreatitis. The first collection of wavelength-resolved reflectance and fluorescence spectra and time-resolved fluorescence decay curves from human pancreatic tissues was acquired with clinically-compatible instrumentation. Mathematical models of reflectance and fluorescence extracted parameters related to tissue morphology and biochemistry that were statistically significant for distinguishing between pancreatic tissue types. These results suggest that optical spectroscopy has the potential to detect pancreatic disease in a clinical setting.

Colour coding scrubs as a means of improving perioperative communication.

PubMed

Litak, Dominika

2011-05-01

Effective communication within the operating department is essential for achieving patient safety. A large part of the perioperative communication is non-verbal. One type of non-verbal communication is 'object communication', the most common form of which is clothing. The colour coding of clothing such as scrubs has the potential to optimise perioperative communication with the patients and between the staff. A colour contains a coded message, and is a visual cue for an immediate identification of personnel. This is of key importance in the perioperative environment. The idea of colour coded scrubs in the perioperative setting has not been much explored to date and, given the potential contributiontowards improvement of patient outcomes, deserves consideration.

Making the most of MBSE: pragmatic model-based engineering for the SKA Telescope Manager

NASA Astrophysics Data System (ADS)

Le Roux, Gerhard; Bridger, Alan; MacIntosh, Mike; Nicol, Mark; Schnetler, Hermine; Williams, Stewart

2016-08-01

Many large projects including major astronomy projects are adopting a Model Based Systems Engineering approach. How far is it possible to get value for the effort involved in developing a model that accurately represents a significant project such as SKA? Is it possible for such a large project to ensure that high-level requirements are traceable through the various system-engineering artifacts? Is it possible to utilize the tools available to produce meaningful measures for the impact of change? This paper shares one aspect of the experience gained on the SKA project. It explores some of the recommended and pragmatic approaches developed, to get the maximum value from the modeling activity while designing the Telescope Manager for the SKA. While it is too early to provide specific measures of success, certain areas are proving to be the most helpful and offering significant potential over the lifetime of the project. The experience described here has been on the 'Cameo Systems Modeler' tool-set, supporting a SysML based System Engineering approach; however the concepts and ideas covered would potentially be of value to any large project considering a Model based approach to their Systems Engineering.

Simulation of coherent nonlinear neutrino flavor transformation in the supernova environment: Correlated neutrino trajectories

NASA Astrophysics Data System (ADS)

Duan, Huaiyu; Fuller, George M.; Carlson, J.; Qian, Yong-Zhong

2006-11-01

We present results of large-scale numerical simulations of the evolution of neutrino and antineutrino flavors in the region above the late-time post-supernova-explosion proto-neutron star. Our calculations are the first to allow explicit flavor evolution histories on different neutrino trajectories and to self-consistently couple flavor development on these trajectories through forward scattering-induced quantum coupling. Employing the atmospheric-scale neutrino mass-squared difference (|δm2|≃3×10-3eV2) and values of θ13 allowed by current bounds, we find transformation of neutrino and antineutrino flavors over broad ranges of energy and luminosity in roughly the “bi-polar” collective mode. We find that this large-scale flavor conversion, largely driven by the flavor off-diagonal neutrino-neutrino forward scattering potential, sets in much closer to the proto-neutron star than simple estimates based on flavor-diagonal potentials and Mikheyev-Smirnov-Wolfenstein evolution would indicate. In turn, this suggests that models of r-process nucleosynthesis sited in the neutrino-driven wind could be affected substantially by active-active neutrino flavor mixing, even with the small measured neutrino mass-squared differences.

Examining the construct and known-group validity of a composite endpoint for The Older Persons and Informal Caregivers Survey Minimum Data Set (TOPICS-MDS); A large-scale data sharing initiative

PubMed Central

Hofman, Cynthia S.; Lutomski, Jennifer E.; Boter, Han; Buurman, Bianca M.; Donders, Rogier; Olde Rikkert, Marcel G. M.; Makai, Peter; Melis, René J. F.

2017-01-01

Background Preference-weighted multi-faceted endpoints have the potential to facilitate comparative effectiveness research that incorporates patient preferences. The Older Persons and Informal Caregivers Survey—Composite endpoint (TOPICS-CEP) is potentially a valuable outcome measure for evaluating interventions in geriatric care as it combines multiple outcomes relevant to older persons in a single metric. The objective of this study was to validate TOPICS-CEP across different study settings (general population, primary care and hospital). Methods Data were extracted from TOPICS Minimum Dataset (MDS), a pooled public-access national database with information on older persons throughout the Netherlands. Data of 17,603 older persons were used. Meta-correlations were performed between TOPICS-CEP indexed scores, EuroQol5-D utility scores and Cantril’s ladder life satisfaction scores. Mixed linear regression analyses were performed to compare TOPICS-CEP indexed scores between known groups, e.g. persons with versus without depression. Results In the complete sample and when stratified by study setting TOPICS-CEP and Cantril’s ladder were moderately correlated, whereas TOPICS-CEP and EQ-5D were highly correlated. Higher mean TOPICS-CEP scores were found in persons who were: married, lived independently and had an education at university level. Moreover, higher mean TOPICS-CEP scores were found in persons without dementia, depression, and dizziness with falls, respectively. Similar results were found when stratified by subgroup. Conclusion This study supports that TOPICS-CEP is a robust measure which can potentially be used in broad settings to identify the effect of intervention or of prevention in elderly care. PMID:28296910

Ocean Simulation Model. Version 2. First Order Frontal Simulation

DTIC Science & Technology

1991-05-01

REAL DEP(NXVS),TEMP(MXVS),SAL(MXVS),SIG(MXVS), DVF (MXVS), * DEP2(MXVS),TEMP2(MXVS),SAL2(MXVS),SIG2CMXVS),BVF2(MXVS), * DEPO(MXVS), TEMPO(MX)VS),SALO...processing parameters to desired values. Generating the Front Position Directive FRNT uses the current clock time as initial seed to call the intrinsic...potentially be very time consuming if the parameter ITER is set to a large number. Directive RES was designed to allow the user to resume the HELM

Hamilton's Equations with Euler Parameters for Rigid Body Dynamics Modeling. Chapter 3

NASA Technical Reports Server (NTRS)

Shivarama, Ravishankar; Fahrenthold, Eric P.

2004-01-01

A combination of Euler parameter kinematics and Hamiltonian mechanics provides a rigid body dynamics model well suited for use in strongly nonlinear problems involving arbitrarily large rotations. The model is unconstrained, free of singularities, includes a general potential energy function and a minimum set of momentum variables, and takes an explicit state space form convenient for numerical implementation. The general formulation may be specialized to address particular applications, as illustrated in several three dimensional example problems.

An Impaled Potential Unexploded Device in the Civilian Training Trauma Setting: A Case Report and Review of the Literature

DTIC Science & Technology

2017-12-11

responsibility.(!) 62 Additionally, eme rgency physicians need to know how to manage a patient with 63 an impaled unexploded device. Improper...his leg during the explosion. He was evaluated by EMS in 76 the field where his limb was noted to be grossly unstable with a large anterior soft 77...including roadside 127 explosives, explosive formed projectile devices and suicide bombs .(S) 128 In the United States military medical literature

Teaching in the Age of Electrons

NASA Astrophysics Data System (ADS)

Impey, C. D.

2002-12-01

Technology opens up a bewildering array of opportunities and options for faculty teaching courses to large groups of non-science majors. The trick is in understanding which modes of instruction increase the engagement and learning of students. Among the tools that show good potential for advancing learning in introductory astronomy classes are virtual worlds, exercises that use real astronomy data sets, expert systems, and content accessible by phone. Some of the capabilities of a new web site to assist astronomy instructors, www.astronomica.org, will be demonstrated.

Controller certification: The generalized stability margin inference for a large number of MIMO controllers

NASA Astrophysics Data System (ADS)

Park, Jisang

In this dissertation, we investigate MIMO stability margin inference of a large number of controllers using pre-established stability margins of a small number of nu-gap-wise adjacent controllers. The generalized stability margin and the nu-gap metric are inherently able to handle MIMO system analysis without the necessity of repeating multiple channel-by-channel SISO analyses. This research consists of three parts: (i) development of a decision support tool for inference of the stability margin, (ii) computational considerations for yielding the maximal stability margin with the minimal nu-gap metric in a less conservative manner, and (iii) experiment design for estimating the generalized stability margin with an assured error bound. A modern problem from aerospace control involves the certification of a large set of potential controllers with either a single plant or a fleet of potential plant systems, with both plants and controllers being MIMO and, for the moment, linear. Experiments on a limited number of controller/plant pairs should establish the stability and a certain level of margin of the complete set. We consider this certification problem for a set of controllers and provide algorithms for selecting an efficient subset for testing. This is done for a finite set of candidate controllers and, at least for SISO plants, for an infinite set. In doing this, the nu-gap metric will be the main tool. We provide a theorem restricting a radius of a ball in the parameter space so that the controller can guarantee a prescribed level of stability and performance if parameters of the controllers are contained in the ball. Computational examples are given, including one of certification of an aircraft engine controller. The overarching aim is to introduce truly MIMO margin calculations and to understand their efficacy in certifying stability over a set of controllers and in replacing legacy single-loop gain and phase margin calculations. We consider methods for the computation of; maximal MIMO stability margins bP̂,C, minimal nu-gap metrics deltanu , and the maximal difference between these two values, through the use of scaling and weighting functions. We propose simultaneous scaling selections that attempt to maximize the generalized stability margin and minimize the nu-gap. The minimization of the nu-gap by scaling involves a non-convex optimization. We modify the XY-centering algorithm to handle this non-convexity. This is done for applications in controller certification. Estimating the generalized stability margin with an accurate error bound has significant impact on controller certification. We analyze an error bound of the generalized stability margin as the infinity norm of the MIMO empirical transfer function estimate (ETFE). Input signal design to reduce the error on the estimate is also studied. We suggest running the system for a certain amount of time prior to recording of each output data set. The assured upper bound of estimation error can be tuned by the amount of the pre-experiment.

MiniWall Tool for Analyzing CFD and Wind Tunnel Large Data Sets

NASA Technical Reports Server (NTRS)

Schuh, Michael J.; Melton, John E.; Stremel, Paul M.

2017-01-01

It is challenging to review and assimilate large data sets created by Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. Over the past 10 years, NASA Ames Research Center has developed and refined a software tool dubbed the MiniWall to increase productivity in reviewing and understanding large CFD-generated data sets. Under the recent NASA ERA project, the application of the tool expanded to enable rapid comparison of experimental and computational data. The MiniWall software is browser based so that it runs on any computer or device that can display a web page. It can also be used remotely and securely by using web server software such as the Apache HTTP server. The MiniWall software has recently been rewritten and enhanced to make it even easier for analysts to review large data sets and extract knowledge and understanding from these data sets. This paper describes the MiniWall software and demonstrates how the different features are used to review and assimilate large data sets.

MiniWall Tool for Analyzing CFD and Wind Tunnel Large Data Sets

NASA Technical Reports Server (NTRS)

Schuh, Michael J.; Melton, John E.; Stremel, Paul M.

2017-01-01

It is challenging to review and assimilate large data sets created by Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. Over the past 10 years, NASA Ames Research Center has developed and refined a software tool dubbed the "MiniWall" to increase productivity in reviewing and understanding large CFD-generated data sets. Under the recent NASA ERA project, the application of the tool expanded to enable rapid comparison of experimental and computational data. The MiniWall software is browser based so that it runs on any computer or device that can display a web page. It can also be used remotely and securely by using web server software such as the Apache HTTP Server. The MiniWall software has recently been rewritten and enhanced to make it even easier for analysts to review large data sets and extract knowledge and understanding from these data sets. This paper describes the MiniWall software and demonstrates how the different features are used to review and assimilate large data sets.

Influence of geologic setting on ground-water availability in the Lawrenceville area, Gwinnett County, Georgia

USGS Publications Warehouse

Williams, Lester J.; Kath, Randy L.; Crawford, Thomas J.; Chapman, Melinda J.

2005-01-01

Obtaining large quantities of ground water needed for municipal and industrial supply in the Piedmont and Blue Ridge physiographic provinces can be challenging because of the complex geology and the typically low primary permeability of igneous and metamorphic rocks. Areas of enhanced secondary permeability in the bedrock do occur, however, and 'high-yield' wells are not uncommon, particularly where careful site-selection techniques are used prior to test drilling. The U.S. Geological Survey - in cooperation with the City of Lawrenceville, Georgia - conducted this study from 2000 to 2002 to learn more about how different geologic settings influence the availability of ground water in igneous and metamorphic bedrock with the expectation that this knowledge could be used to help identify additional water resources in the area. In compositionally layered-rock settings, wells derive water almost exclusively from lithologically and structurally controlled water-bearing zones formed parallel to foliation and compositional layering. These high-permeability, water-bearing zones - termed foliation-parallel parting systems -combined with high-angle joint systems, are the primary control for the high-yield wells drilled in the Lawrenceville area; yields range from 100 to several hundred gallons per minute (gal/min). Near Lawrenceville, areas with high ground-water yield are present in sequences of amphibolite, biotite gneiss, and button schist where the structural attitude of the rocks is gently dipping, in areas characterized by abundant jointing, and in topographic settings with a continuous source of recharge along these structures. In massive-rock settings, wells derive water mostly from joint systems, although foliation-parallel parting systems also may be important. Wells deriving water primarily from steeply-dipping joint systems typically have low yields ranging from 1 to 5 gal/min. Joint systems in massive-rock settings can be identified and characterized by using many of the methods described in this report. Geologic mapping was the primary method used to determine the distribution, variability, and relative concentrations (intensity) of joint systems. In the subsurface, joints were characterized by taking orientation measurements in the open boreholes of wells using acoustic and/or optical televiewers. In this investigation, the only practical approach found for locating areas of high ground-water potential was first through detailed geologic mapping followed by test drilling, borehole geophysical logging, and aquifer testing. Geologic methods help characterize both large- and small-scale structures and other lithologic and stratigraphic features that influence development of increased secondary permeability in the bedrock. The rock types, discontinuities, depth of weathering, topographic position, and recharge potential - which were the principal factors assessed through detailed geologic mapping - must be evaluated carefully, in relation to one another, to assess the ground-water potential in a given area.

Factors influencing antibiotic-prescribing decisions among inpatient physicians: a qualitative investigation

PubMed Central

Livorsi, D; Comer, AR; Matthias, MS; Perencevich, EN; Bair, MJ

2016-01-01

Objective To understand the professional and psychosocial factors that influence physicians' antibiotic-prescribing habits in the inpatient setting. Design We conducted semi-structured interviews with 30 inpatient physicians. Interviews consisted of open-ended questions and flexible probes based on participants' responses. Interviews were audio recorded, transcribed, de-identified, and reviewed for accuracy and completeness. Data were analyzed using emergent thematic analysis. Setting Two teaching hospitals in Indianapolis, IN Participants Thirty inpatient physicians (10 physicians-in-training, 20 supervising staff) Results Participants recognized that antibiotics are over-used, and many admitted to prescribing antibiotics even when the clinical evidence of infection was uncertain. Over-prescription was largely driven by anxiety about missing an infection while potential adverse effects of antibiotics did not strongly influence decision-making. Participants did not routinely disclose potential adverse effects of antibiotics to inpatients. Physicians-in-training were strongly influenced by the antibiotic prescribing behavior of their supervising staff physicians. Participants sometimes questioned their colleagues' antibiotic-prescribing decisions but frequently avoided providing direct feedback or critique, citing obstacles of hierarchy, infrequent face-to-face encounters, and the awkwardness of these conversations. Conclusion There is a physician-based culture of prescribing antibiotics, which involves over-using antibiotics and not challenging colleagues' decisions. The potential adverse effects of antibiotics do not strongly influence decision-making in this sample. A better understanding of these factors could be leveraged in future efforts to improve antibiotic-prescribing in the inpatient setting. PMID:26078017

Accurate potential energy, dipole moment curves, and lifetimes of vibrational states of heteronuclear alkali dimers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fedorov, Dmitry A.; Varganov, Sergey A., E-mail: svarganov@unr.edu; Derevianko, Andrei

2014-05-14

We calculate the potential energy curves, the permanent dipole moment curves, and the lifetimes of the ground and excited vibrational states of the heteronuclear alkali dimers XY (X, Y = Li, Na, K, Rb, Cs) in the X{sup 1}Σ{sup +} electronic state using the coupled cluster with singles doubles and triples method. All-electron quadruple-ζ basis sets with additional core functions are used for Li and Na, and small-core relativistic effective core potentials with quadruple-ζ quality basis sets are used for K, Rb, and Cs. The inclusion of the coupled cluster non-perturbative triple excitations is shown to be crucial for obtainingmore » the accurate potential energy curves. A large one-electron basis set with additional core functions is needed for the accurate prediction of permanent dipole moments. The dissociation energies are overestimated by only 14 cm{sup −1} for LiNa and by no more than 114 cm{sup −1} for the other molecules. The discrepancies between the experimental and calculated harmonic vibrational frequencies are less than 1.7 cm{sup −1}, and the discrepancies for the anharmonic correction are less than 0.1 cm{sup −1}. We show that correlation between atomic electronegativity differences and permanent dipole moment of heteronuclear alkali dimers is not perfect. To obtain the vibrational energies and wave functions the vibrational Schrödinger equation is solved with the B-spline basis set method. The transition dipole moments between all vibrational states, the Einstein coefficients, and the lifetimes of the vibrational states are calculated. We analyze the decay rates of the vibrational states in terms of spontaneous emission, and stimulated emission and absorption induced by black body radiation. In all studied heteronuclear alkali dimers the ground vibrational states have much longer lifetimes than any excited states.« less

Twelve- to 14-Month-Old Infants Can Predict Single-Event Probability with Large Set Sizes

ERIC Educational Resources Information Center

Denison, Stephanie; Xu, Fei

2010-01-01

Previous research has revealed that infants can reason correctly about single-event probabilities with small but not large set sizes (Bonatti, 2008; Teglas "et al.", 2007). The current study asks whether infants can make predictions regarding single-event probability with large set sizes using a novel procedure. Infants completed two trials: A…

Search for pair production of gluinos decaying via stop and sbottom in events with b -jets and large missing transverse momentum in p p collisions at s = 13 TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2016-08-09

A search for supersymmetry involving the pair production of gluinos decaying via third-generation squarks to the lightest neutralino (χ˜ 0 1) is reported. It uses an LHC proton-proton data set at a center-of-mass energy √s = 13 TeV with an integrated luminosity of 3.2 fb –1 collected with the ATLAS detector in 2015. The signal is searched for in events containing several energetic jets, of which at least three must be identified as b jets, large missing transverse momentum, and, potentially, isolated electrons or muons. Large-radius jets with a high mass are also used to identify highly boosted top quarks.more » No excess is found above the predicted background. For χ˜ 0 1 masses below approximately 700 GeV, gluino masses of less than 1.78 TeV and 1.76 TeV are excluded at the 95% C.L. in simplified models of the pair production of gluinos decaying via sbottom and stop, respectively. Furthermore, these results significantly extend the exclusion limits obtained with the √s = 8 TeV data set.« less

Continental-scale patterns of canopy tree composition and function across Amazonia.

PubMed

ter Steege, Hans; Pitman, Nigel C A; Phillips, Oliver L; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-28

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Revealing the global map of protein folding space by large-scale simulations

NASA Astrophysics Data System (ADS)

Sinner, Claude; Lutz, Benjamin; Verma, Abhinav; Schug, Alexander

2015-12-01

The full characterization of protein folding is a remarkable long-standing challenge both for experiment and simulation. Working towards a complete understanding of this process, one needs to cover the full diversity of existing folds and identify the general principles driving the process. Here, we want to understand and quantify the diversity in folding routes for a large and representative set of protein topologies covering the full range from all alpha helical topologies towards beta barrels guided by the key question: Does the majority of the observed routes contribute to the folding process or only a particular route? We identified a set of two-state folders among non-homologous proteins with a sequence length of 40-120 residues. For each of these proteins, we ran native-structure based simulations both with homogeneous and heterogeneous contact potentials. For each protein, we simulated dozens of folding transitions in continuous uninterrupted simulations and constructed a large database of kinetic parameters. We investigate folding routes by tracking the formation of tertiary structure interfaces and discuss whether a single specific route exists for a topology or if all routes are equiprobable. These results permit us to characterize the complete folding space for small proteins in terms of folding barrier ΔG‡, number of routes, and the route specificity RT.

Continental-scale patterns of canopy tree composition and function across Amazonia

NASA Astrophysics Data System (ADS)

Ter Steege, Hans; Pitman, Nigel C. A.; Phillips, Oliver L.; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-01

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Osmotic generation of 'anomalous' fluid pressures in geological environments

USGS Publications Warehouse

Neuzii, C.E.

2000-01-01

Osmotic pressures are generated by differences in chemical potential of a solution across a membrane. But whether osmosis can have a significant effect on the pressure of fluids in geological environments has been controversial, because the membrane properties of geological media are poorly understood. 'Anomalous' pressures - large departures from hydrostatic pressure that are not explicable in terms of topographic or fluid-density effects are widely found in geological settings, and are commonly considered to result from processes that alter the pore or fluid volume, which in turn implies crustal changes happening at a rate too slow to observe directly. Yet if osmosis can explain some anomalies, there is no need to invoke such dynamic geological processes in those cases. Here I report results of a nine- year in situ measurement of fluid pressures and solute concentrations in shale that are consistent with the generation of large (up to 20 MPa) osmotic-pressure anomalies which could persist for tens of millions of years. Osmotic pressures of this magnitude and duration can explain many of the pressure anomalies observed in geological settings. The require, however, small shale porosity and large contrasts in the amount of dissolved solids in the pore waters - criteria that may help to distinguish between osmotic and crystal-dynamic origins of anomalous pressures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Kelin; Zhao, Zhixiong; Wei, Guo-Wei, E-mail: wei@math.msu.edu

Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topologicalmore » analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.« less

The Gap in Big Data: Getting to Wellbeing, Strengths, and a Whole-person Perspective

PubMed Central

Peters, Judith; Schlesner, Sara; Vanderboom, Catherine E.; Holland, Diane E.

2015-01-01

Background: Electronic health records (EHRs) provide a clinical view of patient health. EHR data are becoming available in large data sets and enabling research that will transform the landscape of healthcare research. Methods are needed to incorporate wellbeing dimensions and strengths in large data sets. The purpose of this study was to examine the potential alignment of the Wellbeing Model with a clinical interface terminology standard, the Omaha System, for documenting wellbeing assessments. Objective: To map the Omaha System and Wellbeing Model for use in a clinical EHR wellbeing assessment and to evaluate the feasibility of describing strengths and needs of seniors generated through this assessment. Methods: The Wellbeing Model and Omaha System were mapped using concept mapping techniques. Based on this mapping, a wellbeing assessment was developed and implemented within a clinical EHR. Strengths indicators and signs/symptoms data for 5 seniors living in a residential community were abstracted from wellbeing assessments and analyzed using standard descriptive statistics and pattern visualization techniques. Results: Initial mapping agreement was 93.5%, with differences resolved by consensus. Wellbeing data analysis showed seniors had an average of 34.8 (range=22-49) strengths indicators for 22.8 concepts. They had an average of 6.4 (range=4-8) signs/symptoms for an average of 3.2 (range=2-5) concepts. The ratio of strengths indicators to signs/symptoms was 6:1 (range 2.8-9.6). Problem concepts with more signs/symptoms had fewer strengths. Conclusion: Together, the Wellbeing Model and the Omaha System have potential to enable a whole-person perspective and enhance the potential for a wellbeing perspective in big data research in healthcare. PMID:25984416

The Gap in Big Data: Getting to Wellbeing, Strengths, and a Whole-person Perspective.

PubMed

Monsen, Karen A; Peters, Judith; Schlesner, Sara; Vanderboom, Catherine E; Holland, Diane E

2015-05-01

Electronic health records (EHRs) provide a clinical view of patient health. EHR data are becoming available in large data sets and enabling research that will transform the landscape of healthcare research. Methods are needed to incorporate wellbeing dimensions and strengths in large data sets. The purpose of this study was to examine the potential alignment of the Wellbeing Model with a clinical interface terminology standard, the Omaha System, for documenting wellbeing assessments. To map the Omaha System and Wellbeing Model for use in a clinical EHR wellbeing assessment and to evaluate the feasibility of describing strengths and needs of seniors generated through this assessment. The Wellbeing Model and Omaha System were mapped using concept mapping techniques. Based on this mapping, a wellbeing assessment was developed and implemented within a clinical EHR. Strengths indicators and signs/symptoms data for 5 seniors living in a residential community were abstracted from wellbeing assessments and analyzed using standard descriptive statistics and pattern visualization techniques. Initial mapping agreement was 93.5%, with differences resolved by consensus. Wellbeing data analysis showed seniors had an average of 34.8 (range=22-49) strengths indicators for 22.8 concepts. They had an average of 6.4 (range=4-8) signs/symptoms for an average of 3.2 (range=2-5) concepts. The ratio of strengths indicators to signs/symptoms was 6:1 (range 2.8-9.6). Problem concepts with more signs/symptoms had fewer strengths. Together, the Wellbeing Model and the Omaha System have potential to enable a whole-person perspective and enhance the potential for a wellbeing perspective in big data research in healthcare.

An automated approach towards detecting complex behaviours in deep brain oscillations.

PubMed

Mace, Michael; Yousif, Nada; Naushahi, Mohammad; Abdullah-Al-Mamun, Khondaker; Wang, Shouyan; Nandi, Dipankar; Vaidyanathan, Ravi

2014-03-15

Extracting event-related potentials (ERPs) from neurological rhythms is of fundamental importance in neuroscience research. Standard ERP techniques typically require the associated ERP waveform to have low variance, be shape and latency invariant and require many repeated trials. Additionally, the non-ERP part of the signal needs to be sampled from an uncorrelated Gaussian process. This limits methods of analysis to quantifying simple behaviours and movements only when multi-trial data-sets are available. We introduce a method for automatically detecting events associated with complex or large-scale behaviours, where the ERP need not conform to the aforementioned requirements. The algorithm is based on the calculation of a detection contour and adaptive threshold. These are combined using logical operations to produce a binary signal indicating the presence (or absence) of an event with the associated detection parameters tuned using a multi-objective genetic algorithm. To validate the proposed methodology, deep brain signals were recorded from implanted electrodes in patients with Parkinson's disease as they participated in a large movement-based behavioural paradigm. The experiment involved bilateral recordings of local field potentials from the sub-thalamic nucleus (STN) and pedunculopontine nucleus (PPN) during an orientation task. After tuning, the algorithm is able to extract events achieving training set sensitivities and specificities of [87.5 ± 6.5, 76.7 ± 12.8, 90.0 ± 4.1] and [92.6 ± 6.3, 86.0 ± 9.0, 29.8 ± 12.3] (mean ± 1 std) for the three subjects, averaged across the four neural sites. Furthermore, the methodology has the potential for utility in real-time applications as only a single-trial ERP is required. Copyright © 2013 Elsevier B.V. All rights reserved.

Fast and Scalable Gaussian Process Modeling with Applications to Astronomical Time Series

NASA Astrophysics Data System (ADS)

Foreman-Mackey, Daniel; Agol, Eric; Ambikasaran, Sivaram; Angus, Ruth

2017-12-01

The growing field of large-scale time domain astronomy requires methods for probabilistic data analysis that are computationally tractable, even with large data sets. Gaussian processes (GPs) are a popular class of models used for this purpose, but since the computational cost scales, in general, as the cube of the number of data points, their application has been limited to small data sets. In this paper, we present a novel method for GPs modeling in one dimension where the computational requirements scale linearly with the size of the data set. We demonstrate the method by applying it to simulated and real astronomical time series data sets. These demonstrations are examples of probabilistic inference of stellar rotation periods, asteroseismic oscillation spectra, and transiting planet parameters. The method exploits structure in the problem when the covariance function is expressed as a mixture of complex exponentials, without requiring evenly spaced observations or uniform noise. This form of covariance arises naturally when the process is a mixture of stochastically driven damped harmonic oscillators—providing a physical motivation for and interpretation of this choice—but we also demonstrate that it can be a useful effective model in some other cases. We present a mathematical description of the method and compare it to existing scalable GP methods. The method is fast and interpretable, with a range of potential applications within astronomical data analysis and beyond. We provide well-tested and documented open-source implementations of this method in C++, Python, and Julia.

Clustering social cues to determine social signals: developing learning algorithms using the "n-most likely states" approach

NASA Astrophysics Data System (ADS)

Best, Andrew; Kapalo, Katelynn A.; Warta, Samantha F.; Fiore, Stephen M.

2016-05-01

Human-robot teaming largely relies on the ability of machines to respond and relate to human social signals. Prior work in Social Signal Processing has drawn a distinction between social cues (discrete, observable features) and social signals (underlying meaning). For machines to attribute meaning to behavior, they must first understand some probabilistic relationship between the cues presented and the signal conveyed. Using data derived from a study in which participants identified a set of salient social signals in a simulated scenario and indicated the cues related to the perceived signals, we detail a learning algorithm, which clusters social cue observations and defines an "N-Most Likely States" set for each cluster. Since multiple signals may be co-present in a given simulation and a set of social cues often maps to multiple social signals, the "N-Most Likely States" approach provides a dramatic improvement over typical linear classifiers. We find that the target social signal appears in a "3 most-likely signals" set with up to 85% probability. This results in increased speed and accuracy on large amounts of data, which is critical for modeling social cognition mechanisms in robots to facilitate more natural human-robot interaction. These results also demonstrate the utility of such an approach in deployed scenarios where robots need to communicate with human teammates quickly and efficiently. In this paper, we detail our algorithm, comparative results, and offer potential applications for robot social signal detection and machine-aided human social signal detection.

Characterization of a biosurfactant produced by Pseudomonas cepacia CCT6659 in the presence of industrial wastes and its application in the biodegradation of hydrophobic compounds in soil.

PubMed

Silva, Elias J; Rocha e Silva, Nathália Maria P; Rufino, Raquel D; Luna, Juliana M; Silva, Ricardo O; Sarubbo, Leonie A

2014-05-01

The bacterium Pseudomonas cepacia CCT6659 cultivated with 2% soybean waste frying oil and 2% corn steep liquor as substrates produced a biosurfactant with potential application in the bioremediation of soils. The biosurfactant was classified as an anionic biomolecule composed of 75% lipids and 25% carbohydrates. Characterization by proton nuclear magnetic resonance ((1)H and (13)C NMR) revealed the presence of carbonyl, olefinic and aliphatic groups, with typical spectra of lipids. Four sets of biodegradation experiments were carried out with soil contaminated by hydrophobic organic compounds amended with molasses in the presence of an indigenous consortium, as follows: Set 1-soil+bacterial cells; Set 2-soil+biosurfactant; Set 3-soil+bacterial cells+biosurfactant; and Set 4-soil without bacterial cells or biosurfactant (control). Significant oil biodegradation activity (83%) occurred in the first 10 days of the experiments when the biosurfactant and bacterial cells were used together (Set 3), while maximum degradation of the organic compounds (above 95%) was found in Sets 1-3 between 35 and 60 days. It is evident from the results that the biosurfactant alone and its producer species are both capable of promoting biodegradation to a large extent. Copyright © 2014 Elsevier B.V. All rights reserved.

Mineral resources and land use in Stanislaus County, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higgins, C.T.; Dupras, D.L.; Chapman, R.H.

1993-04-01

Stanislaus County covers portions of 3 geologic provinces: Coast Ranges, Great Valley, and Sierra Nevada. Each has been exploited for a distinct set of mineral resources, which include sand and gravel, ball and fire clay, placer gold, manganese, chromite, magnesite, mercury, diatomite, building stone, and mineral pigment. Of these, sand and gravel, clay, and diatomite have been the most important commodities produced recently. Sand and gravel, particularly that along the Tuolumne River, is and will continue to be the county's main mineral product; other potentially important areas include alluvial fans along the west side of the Great Valley. Clay andmore » diatomite could resume importance in the future. There is also potential for quartz-rich specialty sands. Although the county is largely rural, it is undergoing one of the highest growth rates in California. Several new residential communities are being proposed in the county, which would have two major effects on mineral resources: (1) large sources of aggregate will be required for construction, and (2) development of residential areas may preclude mining of resources in those areas. Maps of mineral resources produced by this study, will assist decisions on such potential conflicts in land use.« less

Study of the Hyperon-Nucleon Interaction in Exclusive Λ Photoproduction off the Deuteron

NASA Astrophysics Data System (ADS)

Zachariou, Nicholas; CLAS Collaboration

2014-09-01

Understanding the nature of the nuclear force in terms of the fundamental degrees of freedom of the theory of strong interaction, Quantum Chromodynamics (QCD), is one of the primary goals of modern nuclear physics. While the nucleon-nucleon (NN) interaction has been studied for decades, a systematic description of the NN potential has been achieved only recently with the development of low-energy Effective Field Theories (EFT). To obtain a comprehensive understanding of the strong interaction, dynamics involving strange baryons must be studied. Currently, little is known about the properties of the hyperon-nucleon (YN) and the hyperon-hyperon (YY) interactions. In this talk I will describe our current research of the Λn interaction using the E06-103 experiment performed with the CLAS detector in Hall B at Jefferson Lab. The large kinematic coverage of the CLAS combined with the exceptionally high quality of the experimental data allows to identify and select final-state interaction events in the reaction γd -->K+ Λn and to establish their kinematical dependencies. The large set of observables we aim to obtain will provide tight constraints on modern YN potentials. I will present the current status of the project and will discuss future incentives. Understanding the nature of the nuclear force in terms of the fundamental degrees of freedom of the theory of strong interaction, Quantum Chromodynamics (QCD), is one of the primary goals of modern nuclear physics. While the nucleon-nucleon (NN) interaction has been studied for decades, a systematic description of the NN potential has been achieved only recently with the development of low-energy Effective Field Theories (EFT). To obtain a comprehensive understanding of the strong interaction, dynamics involving strange baryons must be studied. Currently, little is known about the properties of the hyperon-nucleon (YN) and the hyperon-hyperon (YY) interactions. In this talk I will describe our current research of the Λn interaction using the E06-103 experiment performed with the CLAS detector in Hall B at Jefferson Lab. The large kinematic coverage of the CLAS combined with the exceptionally high quality of the experimental data allows to identify and select final-state interaction events in the reaction γd -->K+ Λn and to establish their kinematical dependencies. The large set of observables we aim to obtain will provide tight constraints on modern YN potentials. I will present the current status of the project and will discuss future incentives. for the CLAS Collaboration.

Improved moving window cross-spectral analysis for resolving large temporal seismic velocity changes in permafrost

DOE PAGES

James, S. R.; Knox, H. A.; Abbott, R. E.; ...

2017-04-13

Cross correlations of seismic noise can potentially record large changes in subsurface velocity due to permafrost dynamics and be valuable for long-term Arctic monitoring. We applied seismic interferometry, using moving window cross-spectral analysis (MWCS), to 2 years of ambient noise data recorded in central Alaska to investigate whether seismic noise could be used to quantify relative velocity changes due to seasonal active-layer dynamics. The large velocity changes (>75%) between frozen and thawed soil caused prevalent cycle-skipping which made the method unusable in this setting. We developed an improved MWCS procedure which uses a moving reference to measure daily velocity variationsmore » that are then accumulated to recover the full seasonal change. This approach reduced cycle-skipping and recovered a seasonal trend that corresponded well with the timing of active-layer freeze and thaw. Lastly, this improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise.« less

Proposed solution methodology for the dynamically coupled nonlinear geared rotor mechanics equations

NASA Technical Reports Server (NTRS)

Mitchell, L. D.; David, J. W.

1983-01-01

The equations which describe the three-dimensional motion of an unbalanced rigid disk in a shaft system are nonlinear and contain dynamic-coupling terms. Traditionally, investigators have used an order analysis to justify ignoring the nonlinear terms in the equations of motion, producing a set of linear equations. This paper will show that, when gears are included in such a rotor system, the nonlinear dynamic-coupling terms are potentially as large as the linear terms. Because of this, one must attempt to solve the nonlinear rotor mechanics equations. A solution methodology is investigated to obtain approximate steady-state solutions to these equations. As an example of the use of the technique, a simpler set of equations is solved and the results compared to numerical simulations. These equations represent the forced, steady-state response of a spring-supported pendulum. These equations were chosen because they contain the type of nonlinear terms found in the dynamically-coupled nonlinear rotor equations. The numerical simulations indicate this method is reasonably accurate even when the nonlinearities are large.

Vibration and buckling of rotating, pretwisted, preconed beams including Coriolis effects

NASA Technical Reports Server (NTRS)

Subrahmanyam, K. B.; Kaza, K. R. V.

1985-01-01

The effects of pretwist, precone, setting angle and Coriolis forces on the vibration and buckling behavior of rotating, torsionally rigid, cantilevered beams were studied. The beam is considered to be clamped on the axis of rotation in one case, and off the axis of rotation in the other. Two methods are employed for the solution of the vibration problem: (1) one based upon a finite-difference approach using second order central differences for solution of the equations of motion, and (2) based upon the minimum of the total potential energy functional with a Ritz type of solution procedure making use of complex forms of shape functions for the dependent variables. The individual and collective effects of pretwist, precone, setting angle, thickness ratio and Coriolis forces on the natural frequencies and the buckling boundaries are presented. It is shown that the inclusion of Coriolis effects is necessary for blades of moderate to large thickness ratios while these effects are not so important for small thickness ratio blades. The possibility of buckling due to centrifugal softening terms for large values of precone and rotation is shown.

Vibration and buckling of rotating, pretwisted, preconed beams including Cooriolis effects

NASA Technical Reports Server (NTRS)

Subrahmanyam, K. B.; Kaza, K. R. V.

1985-01-01

The effects of pretwist, precone, setting angle and Coriolis forces on the vibration and buckling behavior of rotating, torsionally rigid, cantilevered beams were studied. The beam is considered to be clamped on the axis of rotation in one case, and off the axis of rotation in the other. Two methods are employed for the solution of the vibration problem: (1) one based upon a finite-difference approach using second order central differences for solution of the equations of motion, and (2) based upon the minimum of the total potential energy functional with a Ritz type of solution procedure making use of complex forms of shape functions for the dependent variables. The individual and collective effects of pretwist, precone, setting angle, thickness ratio and Coriolis forces on the natural frequencies and the buckling boundaries are presented. It is shown that the inclusion of Coriolis effects is necessary for blades of moderate to large thickness ratios while these effects are not so important for small thickness ratio blades. The possibility of buckling due to centrifugal softening terms for large values of precone and rotation is shown.

Kullback Leibler divergence in complete bacterial and phage genomes

PubMed Central

Akhter, Sajia; Kashef, Mona T.; Ibrahim, Eslam S.; Bailey, Barbara

2017-01-01

The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback–Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses. PMID:29204318

Kullback Leibler divergence in complete bacterial and phage genomes.

PubMed

Akhter, Sajia; Aziz, Ramy K; Kashef, Mona T; Ibrahim, Eslam S; Bailey, Barbara; Edwards, Robert A

2017-01-01

The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback-Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.; Abbott, B.; Abdallah, J.

A search for supersymmetry involving the pair production of gluinos decaying via third-generation squarks to the lightest neutralino (χ˜ 0 1) is reported. It uses an LHC proton-proton data set at a center-of-mass energy √s = 13 TeV with an integrated luminosity of 3.2 fb –1 collected with the ATLAS detector in 2015. The signal is searched for in events containing several energetic jets, of which at least three must be identified as b jets, large missing transverse momentum, and, potentially, isolated electrons or muons. Large-radius jets with a high mass are also used to identify highly boosted top quarks.more » No excess is found above the predicted background. For χ˜ 0 1 masses below approximately 700 GeV, gluino masses of less than 1.78 TeV and 1.76 TeV are excluded at the 95% C.L. in simplified models of the pair production of gluinos decaying via sbottom and stop, respectively. Furthermore, these results significantly extend the exclusion limits obtained with the √s = 8 TeV data set.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.; Abbott, B.; Abdallah, J.

A search for supersymmetry involving the pair production of gluinos decaying via third-generation squarks to the lightest neutralino ( χmore » $$~0\\atop{1}$$ ) is reported. It uses an LHC proton-proton data set at a center-of-mass energy √ s = 13 TeV with an integrated luminosity of 3.2 fb -1 collected with the ATLAS detector in 2015. The signal is searched for in events containing several energetic jets, of which at least three must be identified as b jets, large missing transverse momentum, and, potentially, isolated electrons or muons. Large-radius jets with a high mass are also used to identify highly boosted top quarks. No excess is found above the predicted background. For χ$$~0\\atop{1}$$ masses below approximately 700 GeV, gluino masses of less than 1.78 TeV and 1.76 TeV are excluded at the 95% C.L. in simplified models of the pair production of gluinos decaying via sbottom and stop, respectively. These results significantly extend the exclusion limits obtained with the √ s = 8 TeV data set.« less

Breaking the bottleneck: Use of molecular tailoring approach for the estimation of binding energies at MP2/CBS limit for large water clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Gurmeet; Nandi, Apurba; Gadre, Shridhar R., E-mail: gadre@iitk.ac.in

2016-03-14

A pragmatic method based on the molecular tailoring approach (MTA) for estimating the complete basis set (CBS) limit at Møller-Plesset second order perturbation (MP2) theory accurately for large molecular clusters with limited computational resources is developed. It is applied to water clusters, (H{sub 2}O){sub n} (n = 7, 8, 10, 16, 17, and 25) optimized employing aug-cc-pVDZ (aVDZ) basis-set. Binding energies (BEs) of these clusters are estimated at the MP2/aug-cc-pVNZ (aVNZ) [N = T, Q, and 5 (whenever possible)] levels of theory employing grafted MTA (GMTA) methodology and are found to lie within 0.2 kcal/mol of the corresponding full calculationmore » MP2 BE, wherever available. The results are extrapolated to CBS limit using a three point formula. The GMTA-MP2 calculations are feasible on off-the-shelf hardware and show around 50%–65% saving of computational time. The methodology has a potential for application to molecular clusters containing ∼100 atoms.« less

Remote sensing techniques in cultural resource management archaeology

NASA Astrophysics Data System (ADS)

Johnson, Jay K.; Haley, Bryan S.

2003-04-01

Cultural resource management archaeology in the United States concerns compliance with legislation set in place to protect archaeological resources from the impact of modern activities. Traditionally, surface collection, shovel testing, test excavation, and mechanical stripping are used in these projects. These methods are expensive, time consuming, and may poorly represent the features within archaeological sites. The use of remote sensing techniques in cultural resource management archaeology may provide an answer to these problems. Near-surface geophysical techniques, including magnetometry, resistivity, electromagnetics, and ground penetrating radar, have proven to be particularly successful at efficiently locating archaeological features. Research has also indicated airborne and satellite remote sensing may hold some promise in the future for large-scale archaeological survey, although this is difficult in many areas of the world where ground cover reflect archaeological features in an indirect manner. A cost simulation of a hypothetical data recovery project on a large complex site in Mississippi is presented to illustrate the potential advantages of remote sensing in a cultural resource management setting. The results indicate these techniques can save a substantial amount of time and money for these projects.

A potential energy surface for the process H2 + H2O yielding H + H + H2O - Ab initio calculations and analytical representation

NASA Technical Reports Server (NTRS)

Schwenke, David W.; Walch, Stephen P.; Taylor, Peter R.

1991-01-01

Extensive ab initio calculations on the ground state potential energy surface of H2 + H2O were performed using a large contracted Gaussian basis set and a high level of correlation treatment. An analytical representation of the potential energy surface was then obtained which reproduces the calculated energies with an overall root-mean-square error of only 0.64 mEh. The analytic representation explicitly includes all nine internal degrees of freedom and is also well behaved as the H2 dissociates; it thus can be used to study collision-induced dissociation or recombination of H2. The strategy used to minimize the number of energy calculations is discussed, as well as other advantages of the present method for determining the analytical representation.

A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables

NASA Astrophysics Data System (ADS)

Madonna, Erica; Ginsbourger, David; Martius, Olivia

2018-05-01

In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.

Antagonistic and synergistic interactions among predators.

PubMed

Huxel, Gary R

2007-08-01

The structure and dynamics of food webs are largely dependent upon interactions among consumers and their resources. However, interspecific interactions such as intraguild predation and interference competition can also play a significant role in the stability of communities. The role of antagonistic/synergistic interactions among predators has been largely ignored in food web theory. These mechanisms influence predation rates, which is one of the key factors regulating food web structure and dynamics, thus ignoring them can potentially limit understanding of food webs. Using nonlinear models, it is shown that critical aspects of multiple predator food web dynamics are antagonistic/synergistic interactions among predators. The influence of antagonistic/synergistic interactions on coexistence of predators depended largely upon the parameter set used and the degree of feeding niche differentiation. In all cases when there was no effect of antagonism or synergism (a ( ij )=1.00), the predators coexisted. Using the stable parameter set, coexistence occurred across the range of antagonism/synergism used. However, using the chaotic parameter strong antagonism resulted in the extinction of one or both species, while strong synergism tended to coexistence. Whereas using the limit cycle parameter set, coexistence was strongly dependent on the degree of feeding niche overlap. Additionally increasing the degree of feeding specialization of the predators on the two prey species increased the amount of parameter space in which coexistence of the two predators occurred. Bifurcation analyses supported the general pattern of increased stability when the predator interaction was synergistic and decreased stability when it was antagonistic. Thus, synergistic interactions should be more common than antagonistic interactions in ecological systems.

ReOpt[trademark] V2.0 user guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, M K; Bryant, J L

1992-10-01

Cleaning up the large number of contaminated waste sites at Department of Energy (DOE) facilities in the US presents a large and complex problem. Each waste site poses a singular set of circumstances (different contaminants, environmental concerns, and regulations) that affect selection of an appropriate response. Pacific Northwest Laboratory (PNL) developed ReOpt to provide information about the remedial action technologies that are currently available. It is an easy-to-use personal computer program and database that contains data about these remedial technologies and auxiliary data about contaminants and regulations. ReOpt will enable engineers and planners involved in environmental restoration efforts to quicklymore » identify potentially applicable environmental restoration technologies and access corresponding information required to select cleanup activities for DOE sites.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

James, S. R.; Knox, H. A.; Abbott, R. E.

Cross correlations of seismic noise can potentially record large changes in subsurface velocity due to permafrost dynamics and be valuable for long-term Arctic monitoring. We applied seismic interferometry, using moving window cross-spectral analysis (MWCS), to 2 years of ambient noise data recorded in central Alaska to investigate whether seismic noise could be used to quantify relative velocity changes due to seasonal active-layer dynamics. The large velocity changes (>75%) between frozen and thawed soil caused prevalent cycle-skipping which made the method unusable in this setting. We developed an improved MWCS procedure which uses a moving reference to measure daily velocity variationsmore » that are then accumulated to recover the full seasonal change. This approach reduced cycle-skipping and recovered a seasonal trend that corresponded well with the timing of active-layer freeze and thaw. Lastly, this improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise.« less

GARN: Sampling RNA 3D Structure Space with Game Theory and Knowledge-Based Scoring Strategies.

PubMed

Boudard, Mélanie; Bernauer, Julie; Barth, Dominique; Cohen, Johanne; Denise, Alain

2015-01-01

Cellular processes involve large numbers of RNA molecules. The functions of these RNA molecules and their binding to molecular machines are highly dependent on their 3D structures. One of the key challenges in RNA structure prediction and modeling is predicting the spatial arrangement of the various structural elements of RNA. As RNA folding is generally hierarchical, methods involving coarse-grained models hold great promise for this purpose. We present here a novel coarse-grained method for sampling, based on game theory and knowledge-based potentials. This strategy, GARN (Game Algorithm for RNa sampling), is often much faster than previously described techniques and generates large sets of solutions closely resembling the native structure. GARN is thus a suitable starting point for the molecular modeling of large RNAs, particularly those with experimental constraints. GARN is available from: http://garn.lri.fr/.

Profiling of potential driver mutations in sarcomas by targeted next generation sequencing.

PubMed

Andersson, Carola; Fagman, Henrik; Hansson, Magnus; Enlund, Fredrik

2016-04-01

Comprehensive genetic profiling by massively parallel sequencing, commonly known as next generation sequencing (NGS), is becoming the foundation of personalized oncology. For sarcomas very few targeted treatments are currently in routine use. In clinical practice the preoperative diagnostic workup of soft tissue tumours largely relies on core needle biopsies. Although mostly sufficient for histopathological diagnosis, only very limited amounts of formalin fixated paraffin embedded tissue are often available for predictive mutation analysis. Targeted NGS may thus open up new possibilities for comprehensive characterization of scarce biopsies. We therefore set out to search for driver mutations by NGS in a cohort of 55 clinically and morphologically well characterized sarcomas using low input of DNA from formalin fixated paraffin embedded tissues. The aim was to investigate if there are any recurrent or targetable aberrations in cancer driver genes in addition to known chromosome translocations in different types of sarcomas. We employed a panel covering 207 mutation hotspots in 50 cancer-associated genes to analyse DNA from nine gastrointestinal stromal tumours, 14 synovial sarcomas, seven myxoid liposarcomas, 22 Ewing sarcomas and three Ewing-like small round cell tumours at a large sequencing depth to detect also mutations that are subclonal or occur at low allele frequencies. We found nine mutations in eight different potential driver genes, some of which are potentially actionable by currently existing targeted therapies. Even though no recurrent mutations in driver genes were found in the different sarcoma groups, we show that targeted NGS-based sequencing is clearly feasible in a diagnostic setting with very limited amounts of paraffin embedded tissue and may provide novel insights into mesenchymal cell signalling and potentially druggable targets. Interestingly, we also identify five non-synonymous sequence variants in 4 established cancer driver genes in DNA from normal tissue from sarcoma patients that may possibly predispose or contribute to neoplastic development. Copyright © 2016 Elsevier Inc. All rights reserved.

Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob; Gonder, Jeffrey D

The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption modelsmore » are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.« less

Large Artery Atherosclerotic Occlusive Disease.

PubMed

Cole, John W

2017-02-01

Extracranial or intracranial large artery atherosclerosis is often identified as a potential etiologic cause for ischemic stroke and transient ischemic attack. Given the high prevalence of large artery atherosclerosis in the general population, determining whether an identified atherosclerotic lesion is truly the cause of a patient's symptomatology can be difficult. In all cases, optimally treating each patient to minimize future stroke risk is paramount. Extracranial or intracranial large artery atherosclerosis can be broadly compartmentalized into four distinct clinical scenarios based upon the individual patient's history, examination, and anatomic imaging findings: asymptomatic and symptomatic extracranial carotid stenosis, intracranial atherosclerosis, and extracranial vertebral artery atherosclerotic disease. This review provides a framework for clinicians evaluating and treating such patients. Intensive medical therapy achieves low rates of stroke and death in asymptomatic carotid stenosis. Evidence indicates that patients with severe symptomatic carotid stenosis should undergo carotid revascularization sooner rather than later and that the risk of stroke or death is lower using carotid endarterectomy than with carotid stenting. Specific to stenting, the risk of stroke or death is greatest among older patients and women. Continuous vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy is the mainstay for stroke prevention in the setting of intracranial and vertebral artery origin atherosclerosis. Lifelong vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy are the key elements to reduce future stroke risk in the setting of large artery atherosclerosis. When considering a revascularization procedure for carotid stenosis, patient demographics, comorbidities, and the periprocedural risks of stroke and death should be carefully considered.

Large Artery Atherosclerotic Occlusive Disease

PubMed Central

Cole, John W.

2017-01-01

ABSTRACT Purpose of Review: Extracranial or intracranial large artery atherosclerosis is often identified as a potential etiologic cause for ischemic stroke and transient ischemic attack. Given the high prevalence of large artery atherosclerosis in the general population, determining whether an identified atherosclerotic lesion is truly the cause of a patient’s symptomatology can be difficult. In all cases, optimally treating each patient to minimize future stroke risk is paramount. Extracranial or intracranial large artery atherosclerosis can be broadly compartmentalized into four distinct clinical scenarios based upon the individual patient’s history, examination, and anatomic imaging findings: asymptomatic and symptomatic extracranial carotid stenosis, intracranial atherosclerosis, and extracranial vertebral artery atherosclerotic disease. This review provides a framework for clinicians evaluating and treating such patients. Recent Findings: Intensive medical therapy achieves low rates of stroke and death in asymptomatic carotid stenosis. Evidence indicates that patients with severe symptomatic carotid stenosis should undergo carotid revascularization sooner rather than later and that the risk of stroke or death is lower using carotid endarterectomy than with carotid stenting. Specific to stenting, the risk of stroke or death is greatest among older patients and women. Continuous vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy is the mainstay for stroke prevention in the setting of intracranial and vertebral artery origin atherosclerosis. Summary: Lifelong vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy are the key elements to reduce future stroke risk in the setting of large artery atherosclerosis. When considering a revascularization procedure for carotid stenosis, patient demographics, comorbidities, and the periprocedural risks of stroke and death should be carefully considered. PMID:28157748

CERAPP: Collaborative Estrogen Receptor Activity Prediction ...

EPA Pesticide Factsheets

Humans potentially are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Many of these chemicals never have been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for assessment in costly in vivo tests, for instance, within the EPA Endocrine Disruptor Screening Program. Here, we describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating the efficacy of using predictive computational models on high-throughput screening data to screen thousands of chemicals against the ER. CERAPP combined multiple models developed in collaboration among 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1677 compounds provided by EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were tested using an evaluation set of 7522 chemicals collected from the literature. To overcome the limitations of single models, a consensus was built weighting models using a scoring function (0 to 1) based on their accuracies. Individual model scores ranged from 0.69 to 0.85, showing

BACHSCORE. A tool for evaluating efficiently and reliably the quality of large sets of protein structures

NASA Astrophysics Data System (ADS)

Sarti, E.; Zamuner, S.; Cossio, P.; Laio, A.; Seno, F.; Trovato, A.

2013-12-01

In protein structure prediction it is of crucial importance, especially at the refinement stage, to score efficiently large sets of models by selecting the ones that are closest to the native state. We here present a new computational tool, BACHSCORE, that allows its users to rank different structural models of the same protein according to their quality, evaluated by using the BACH++ (Bayesian Analysis Conformation Hunt) scoring function. The original BACH statistical potential was already shown to discriminate with very good reliability the protein native state in large sets of misfolded models of the same protein. BACH++ features a novel upgrade in the solvation potential of the scoring function, now computed by adapting the LCPO (Linear Combination of Pairwise Orbitals) algorithm. This change further enhances the already good performance of the scoring function. BACHSCORE can be accessed directly through the web server: bachserver.pd.infn.it. Catalogue identifier: AEQD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQD_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 130159 No. of bytes in distributed program, including test data, etc.: 24 687 455 Distribution format: tar.gz Programming language: C++. Computer: Any computer capable of running an executable produced by a g++ compiler (4.6.3 version). Operating system: Linux, Unix OS-es. RAM: 1 073 741 824 bytes Classification: 3. Nature of problem: Evaluate the quality of a protein structural model, taking into account the possible “a priori” knowledge of a reference primary sequence that may be different from the amino-acid sequence of the model; the native protein structure should be recognized as the best model. Solution method: The contact potential scores the occurrence of any given type of residue pair in 5 possible contact classes (α-helical contact, parallel β-sheet contact, anti-parallel β-sheet contact, side-chain contact, no contact). The solvation potential scores the occurrence of any residue type in 2 possible environments: buried and solvent exposed. Residue environment is assigned by adapting the LCPO algorithm. Residues present in the reference primary sequence and not present in the model structure contribute to the model score as solvent exposed and as non contacting all other residues. Restrictions: Input format file according to the Protein Data Bank standard Additional comments: Parameter values used in the scoring function can be found in the file /folder-to-bachscore/BACH/examples/bach_std.par. Running time: Roughly one minute to score one hundred structures on a desktop PC, depending on their size.

Response Grids: Practical Ways to Display Large Data Sets with High Visual Impact

ERIC Educational Resources Information Center

Gates, Simon

2013-01-01

Spreadsheets are useful for large data sets but they may be too wide or too long to print as conventional tables. Response grids offer solutions to the challenges posed by any large data set. They have wide application throughout science and for every subject and context where visual data displays are designed, within education and elsewhere.…

Orientation-dependent potential of mean force for protein folding

NASA Astrophysics Data System (ADS)

Mukherjee, Arnab; Bhimalapuram, Prabhakar; Bagchi, Biman

2005-07-01

We present a solvent-implicit minimalistic model potential among the amino acid residues of proteins, obtained by using the known native structures [deposited in the Protein Data Bank (PDB)]. In this model, the amino acid side chains are represented by a single ellipsoidal site, defined by the group of atoms about the center of mass of the side chain. These ellipsoidal sites interact with other sites through an orientation-dependent interaction potential which we construct in the following fashion. First, the site-site potential of mean force (PMF) between heavy atoms is calculated [following F. Melo and E. Feytsman, J. Mol. Biol. 267, 207 (1997)] from statistics of their distance separation obtained from crystal structures. These site-site potentials are then used to calculate the distance and the orientation-dependent potential between side chains of all the amino acid residues (AAR). The distance and orientation dependencies show several interesting results. For example, we find that the PMF between two hydrophobic AARs, such as phenylalanine, is strongly attractive at short distances (after the obvious repulsive region at very short separation) and is characterized by a deep minimum, for specific orientations. For the interaction between two hydrophilic AARs, such a deep minimum is absent and in addition, the potential interestingly reveals the combined effect of polar (charge) and hydrophobic interactions among some of these AARs. The effectiveness of our potential has been tested by calculating the Z-scores for a large set of proteins. The calculated Z-scores show high negative values for most of them, signifying the success of the potential to identify the native structure from among a large number of its decoy states.

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork

PubMed Central

Druka, Arnis; Druka, Ilze; Centeno, Arthur G; Li, Hongqiang; Sun, Zhaohui; Thomas, William TB; Bonar, Nicola; Steffenson, Brian J; Ullrich, Steven E; Kleinhofs, Andris; Wise, Roger P; Close, Timothy J; Potokina, Elena; Luo, Zewei; Wagner, Carola; Schweizer, Günther F; Marshall, David F; Kearsey, Michael J; Williams, Robert W; Waugh, Robbie

2008-01-01

Background A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Description Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork . GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. Conclusion By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets. PMID:19017390

Semiconductor of spinons: from Ising band insulator to orthogonal band insulator.

PubMed

Farajollahpour, T; Jafari, S A

2018-01-10

We use the ionic Hubbard model to study the effects of strong correlations on a two-dimensional semiconductor. The spectral gap in the limit where on-site interactions are zero is set by the staggered ionic potential, while in the strong interaction limit it is set by the Hubbard U. Combining mean field solutions of the slave spin and slave rotor methods, we propose two interesting gapped phases in between: (i) the insulating phase before the Mott phase can be viewed as gapping a non-Fermi liquid state of spinons by the staggered ionic potential. The quasi-particles of underlying spinons are orthogonal to physical electrons, giving rise to the 'ARPES-dark' state where the ARPES gap will be larger than the optical and thermal gap. (ii) The Ising insulator corresponding to ordered phase of the Ising variable is characterized by single-particle excitations whose dispersion is controlled by Ising-like temperature and field dependences. The temperature can be conveniently employed to drive a phase transition between these two insulating phases where Ising exponents become measurable by ARPES and cyclotron resonance. The rare earth monochalcogenide semiconductors where the magneto-resistance is anomalously large can be a candidate system for the Ising band insulator. We argue that the Ising and orthogonal insulating phases require strong enough ionic potential to survive the downward renormalization of the ionic potential caused by Hubbard U.

Semiconductor of spinons: from Ising band insulator to orthogonal band insulator

NASA Astrophysics Data System (ADS)

Farajollahpour, T.; Jafari, S. A.

2018-01-01

We use the ionic Hubbard model to study the effects of strong correlations on a two-dimensional semiconductor. The spectral gap in the limit where on-site interactions are zero is set by the staggered ionic potential, while in the strong interaction limit it is set by the Hubbard U. Combining mean field solutions of the slave spin and slave rotor methods, we propose two interesting gapped phases in between: (i) the insulating phase before the Mott phase can be viewed as gapping a non-Fermi liquid state of spinons by the staggered ionic potential. The quasi-particles of underlying spinons are orthogonal to physical electrons, giving rise to the ‘ARPES-dark’ state where the ARPES gap will be larger than the optical and thermal gap. (ii) The Ising insulator corresponding to ordered phase of the Ising variable is characterized by single-particle excitations whose dispersion is controlled by Ising-like temperature and field dependences. The temperature can be conveniently employed to drive a phase transition between these two insulating phases where Ising exponents become measurable by ARPES and cyclotron resonance. The rare earth monochalcogenide semiconductors where the magneto-resistance is anomalously large can be a candidate system for the Ising band insulator. We argue that the Ising and orthogonal insulating phases require strong enough ionic potential to survive the downward renormalization of the ionic potential caused by Hubbard U.

Assessing modelled spatial distributions of ice water path using satellite data

NASA Astrophysics Data System (ADS)

Eliasson, S.; Buehler, S. A.; Milz, M.; Eriksson, P.; John, V. O.

2010-05-01

The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations.

Consistent structures and interactions by density functional theory with small atomic orbital basis sets.

PubMed

Grimme, Stefan; Brandenburg, Jan Gerit; Bannwarth, Christoph; Hansen, Andreas

2015-08-07

A density functional theory (DFT) based composite electronic structure approach is proposed to efficiently compute structures and interaction energies in large chemical systems. It is based on the well-known and numerically robust Perdew-Burke-Ernzerhoff (PBE) generalized-gradient-approximation in a modified global hybrid functional with a relatively large amount of non-local Fock-exchange. The orbitals are expanded in Ahlrichs-type valence-double zeta atomic orbital (AO) Gaussian basis sets, which are available for many elements. In order to correct for the basis set superposition error (BSSE) and to account for the important long-range London dispersion effects, our well-established atom-pairwise potentials are used. In the design of the new method, particular attention has been paid to an accurate description of structural parameters in various covalent and non-covalent bonding situations as well as in periodic systems. Together with the recently proposed three-fold corrected (3c) Hartree-Fock method, the new composite scheme (termed PBEh-3c) represents the next member in a hierarchy of "low-cost" electronic structure approaches. They are mainly free of BSSE and account for most interactions in a physically sound and asymptotically correct manner. PBEh-3c yields good results for thermochemical properties in the huge GMTKN30 energy database. Furthermore, the method shows excellent performance for non-covalent interaction energies in small and large complexes. For evaluating its performance on equilibrium structures, a new compilation of standard test sets is suggested. These consist of small (light) molecules, partially flexible, medium-sized organic molecules, molecules comprising heavy main group elements, larger systems with long bonds, 3d-transition metal systems, non-covalently bound complexes (S22 and S66×8 sets), and peptide conformations. For these sets, overall deviations from accurate reference data are smaller than for various other tested DFT methods and reach that of triple-zeta AO basis set second-order perturbation theory (MP2/TZ) level at a tiny fraction of computational effort. Periodic calculations conducted for molecular crystals to test structures (including cell volumes) and sublimation enthalpies indicate very good accuracy competitive to computationally more involved plane-wave based calculations. PBEh-3c can be applied routinely to several hundreds of atoms on a single processor and it is suggested as a robust "high-speed" computational tool in theoretical chemistry and physics.

Large Renal Corpuscle: Clinical Significance of Evaluation of the Largest Renal Corpuscle in Kidney Biopsy Specimens.

PubMed

Kataoka, Hiroshi; Mochizuki, Toshio; Nitta, Kosaku

2018-01-01

Renal prognostic factors of chronic kidney disease are important concerns for patients. Kidney biopsy can be used to evaluate not only the activity of the original disease but also various risk factors related to the lifestyle of patients. Considering that lifestyle-related factors, including obesity and metabolic syndrome, are crucial prognostic risk factors of kidney disease progression and all-cause mortality, evaluation of lifestyle-related prognostic factors in kidney biopsy of all kidney diseases is important. Renal corpuscle size (glomerular size) is an easily measured parameter and potentially acts as a predictor of long-term renal function. Large renal corpuscle found on kidney biopsy is a classic and simple indicator, and has merit owing to its quantitative nature, but it has yet to be used to its full potential in clinical settings. Large renal corpuscle is an index that includes not only the activity of the original disease but also the damage of various metabolic risk states as represented by obesity, diabetes, and metabolic syndrome. Large renal corpuscles could be used to guide therapy. In this review, after identifying the pitfalls regarding the assessment of mean values in medical research, we propose that measurement of the maximum renal corpuscle profile (glomerular profile) in renal biopsies would provide valuable insights into the diagnosis, prognosis, and management of kidney diseases. © 2018 S. Karger AG, Basel.

Regular Benzodiazepine and Z-Substance Use and Risk of Dementia: An Analysis of German Claims Data.

PubMed

Gomm, Willy; von Holt, Klaus; Thomé, Friederike; Broich, Karl; Maier, Wolfgang; Weckbecker, Klaus; Fink, Anne; Doblhammer, Gabriele; Haenisch, Britta

2016-09-06

While acute detrimental effects of benzodiazepine (BDZ), and BDZ and related z-substance (BDZR) use on cognition and memory are known, the association of BDZR use and risk of dementia in the elderly is controversially discussed. Previous studies on cohort or claims data mostly show an increased risk for dementia with the use of BDZs or BDZRs. For Germany, analyses on large population-based data sets are missing. To evaluate the association between regular BDZR use and incident any dementia in a large German claims data set. Using longitudinal German public health insurance data from 2004 to 2011 we analyzed the association between regular BDZR use (versus no BDZR use) and incident dementia in a case-control design. We examined patient samples aged≥60 years that were free of dementia at baseline. To address potential protopathic bias we introduced a lag time between BDZR prescription and dementia diagnosis. Odds ratios were calculated applying conditional logistic regression, adjusted for potential confounding factors such as comorbidities and polypharmacy. The regular use of BDZRs was associated with a significant increased risk of incident dementia for patients aged≥60 years (adjusted odds ratio [OR] 1.21, 95% confidence interval [CI] 1.13-1.29). The association was slightly stronger for long-acting substances than for short-acting ones. A trend for increased risk for dementia with higher exposure was observed. The restricted use of BDZRs may contribute to dementia prevention in the elderly.

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

PubMed

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A framework for improving access and customer service times in health care: application and analysis at the UCLA Medical Center.

PubMed

Duda, Catherine; Rajaram, Kumar; Barz, Christiane; Rosenthal, J Thomas

2013-01-01

There has been an increasing emphasis on health care efficiency and costs and on improving quality in health care settings such as hospitals or clinics. However, there has not been sufficient work on methods of improving access and customer service times in health care settings. The study develops a framework for improving access and customer service time for health care settings. In the framework, the operational concept of the bottleneck is synthesized with queuing theory to improve access and reduce customer service times without reduction in clinical quality. The framework is applied at the Ronald Reagan UCLA Medical Center to determine the drivers for access and customer service times and then provides guidelines on how to improve these drivers. Validation using simulation techniques shows significant potential for reducing customer service times and increasing access at this institution. Finally, the study provides several practice implications that could be used to improve access and customer service times without reduction in clinical quality across a range of health care settings from large hospitals to small community clinics.

Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

PubMed

Winkler, David A; Le, Tu C

2017-01-01

Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Revealing the secret life of pre-implantation embryos by time-lapse monitoring: A review

PubMed Central

Faramarzi, Azita; Khalili, Mohammad Ali; Micara, Giulietta; Agha-Rahimi, Azam

2017-01-01

High implantation success following in vitro fertilization cycles are achieved via the transfer of embryos with the highest developmental competence. Multiple pregnancies as a result of the transfer of several embryos per cycle accompany with various complication. Thus, single-embryo transfer (SET) is the preferred practice in assisted reproductive technique (ART) treatment. In order to improve the pregnancy rate for SET, embryologists need reliable biomarkers to aid their selection of embryos with the highest developmental potential. Time-lapse technology is a noninvasive alternative conventional microscopic assessment. It provides uninterrupted and continues the survey of embryo development to transfer day. Today, there are four time-lapse systems that are commercially available for ART centers. In world and Iran, the first time lapse babies were born in 2010 and 2015, respectively, conceived by SET. Here, we review the use of time-lapse monitoring in the observation of embryogenesis as well as its role in SET. Although, the findings from our review support common use of time-lapse monitoring in ART centers; but, future large studies assessing this system in well-designed trials are necessary. PMID:28744520

Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark.

PubMed

Grinter, Sam Z; Yan, Chengfei; Huang, Sheng-You; Jiang, Lin; Zou, Xiaoqin

2013-08-26

In this study, we use the recently released 2012 Community Structure-Activity Resource (CSAR) data set to evaluate two knowledge-based scoring functions, ITScore and STScore, and a simple force-field-based potential (VDWScore). The CSAR data set contains 757 compounds, most with known affinities, and 57 crystal structures. With the help of the script files for docking preparation, we use the full CSAR data set to evaluate the performances of the scoring functions on binding affinity prediction and active/inactive compound discrimination. The CSAR subset that includes crystal structures is used as well, to evaluate the performances of the scoring functions on binding mode and affinity predictions. Within this structure subset, we investigate the importance of accurate ligand and protein conformational sampling and find that the binding affinity predictions are less sensitive to non-native ligand and protein conformations than the binding mode predictions. We also find the full CSAR data set to be more challenging in making binding mode predictions than the subset with structures. The script files used for preparing the CSAR data set for docking, including scripts for canonicalization of the ligand atoms, are offered freely to the academic community.

The use of surveillance data and market research to promote physical activity.

PubMed

Fridinger, Fred; Macera, Carol; Cordell, H Ken

2002-08-01

Using various types of data sources for assessing and monitoring physical activity behaviors on a population level adds to our ability to explain the relationships between individuals and their surrounding social and physical environments. This article presents the findings from part of a panel presentation on available data sets at the 2001 Cooper Conference on Innovative Approaches to Understanding and Influencing Physical Activity. First, an overview of large national epidemiologic and surveillance data sets is offered, followed by a discussion on the use of market segmentation data to complement more traditional sources of data by adding new dimensions to our understanding of target groups and potential intervention strategies. The relative advantages and disadvantages of using each type of data are also given, as well as recommendations for further use.

Synthetic aperture tomographic phase microscopy for 3D imaging of live cells in translational motion

PubMed Central

Lue, Niyom; Choi, Wonshik; Popescu, Gabriel; Badizadegan, Kamran; Dasari, Ramachandra R.; Feld, Michael S.

2009-01-01

We present a technique for 3D imaging of live cells in translational motion without need of axial scanning of objective lens. A set of transmitted electric field images of cells at successive points of transverse translation is taken with a focused beam illumination. Based on Hyugens’ principle, angular plane waves are synthesized from E-field images of a focused beam. For a set of synthesized angular plane waves, we apply a filtered back-projection algorithm and obtain 3D maps of refractive index of live cells. This technique, which we refer to as synthetic aperture tomographic phase microscopy, can potentially be combined with flow cytometry or microfluidic devices, and will enable high throughput acquisition of quantitative refractive index data from large numbers of cells. PMID:18825263

Balancing efficiency, equity and feasibility of HIV treatment in South Africa – development of programmatic guidance

PubMed Central

2013-01-01

South Africa, the country with the largest HIV epidemic worldwide, has been scaling up treatment since 2003 and is rapidly expanding its eligibility criteria. The HIV treatment programme has achieved significant results, and had 1.8 million people on treatment per 2011. Despite these achievements, it is now facing major concerns regarding (i) efficiency: alternative treatment policies may save more lives for the same budget; (ii) equity: there are large inequalities in who receives treatment; (iii) feasibility: still only 52% of the eligible population receives treatment. Hence, decisions on the design of the present HIV treatment programme in South Africa can be considered suboptimal. We argue there are two fundamental reasons to this. First, while there is a rapidly growing evidence-base to guide priority setting decisions on HIV treatment, its included studies typically consider only one criterion at a time and thus fail to capture the broad range of values that stakeholders have. Second, priority setting on HIV treatment is a highly political process but it seems no adequate participatory processes are in place to incorporate stakeholders’ views and evidences of all sorts. We propose an alternative approach that provides a better evidence base and outlines a fair policy process to improve priority setting in HIV treatment. The approach integrates two increasingly important frameworks on health care priority setting: accountability for reasonableness (A4R) to foster procedural fairness, and multi-criteria decision analysis (MCDA) to construct an evidence-base on the feasibility, efficiency, and equity of programme options including trade-offs. The approach provides programmatic guidance on the choice of treatment strategies at various decisions levels based on a sound conceptual framework, and holds large potential to improve HIV priority setting in South Africa. PMID:24107435

Periodic boundary conditions for QM/MM calculations: Ewald summation for extended Gaussian basis sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holden, Zachary C.; Richard, Ryan M.; Herbert, John M., E-mail: herbert@chemistry.ohio-state.edu

2013-12-28

An implementation of Ewald summation for use in mixed quantum mechanics/molecular mechanics (QM/MM) calculations is presented, which builds upon previous work by others that was limited to semi-empirical electronic structure for the QM region. Unlike previous work, our implementation describes the wave function's periodic images using “ChElPG” atomic charges, which are determined by fitting to the QM electrostatic potential evaluated on a real-space grid. This implementation is stable even for large Gaussian basis sets with diffuse exponents, and is thus appropriate when the QM region is described by a correlated wave function. Derivatives of the ChElPG charges with respect tomore » the QM density matrix are a potentially serious bottleneck in this approach, so we introduce a ChElPG algorithm based on atom-centered Lebedev grids. The ChElPG charges thus obtained exhibit good rotational invariance even for sparse grids, enabling significant cost savings. Detailed analysis of the optimal choice of user-selected Ewald parameters, as well as timing breakdowns, is presented.« less

Comparison of main-shock and aftershock fragility curves developed for New Zealand and US buildings

USGS Publications Warehouse

Uma, S.R.; Ryu, H.; Luco, N.; Liel, A.B.; Raghunandan, M.

2011-01-01

Seismic risk assessment involves the development of fragility functions to express the relationship between ground motion intensity and damage potential. In evaluating the risk associated with the building inventory in a region, it is essential to capture 'actual' characteristics of the buildings and group them so that 'generic building types' can be generated for further analysis of their damage potential. Variations in building characteristics across regions/countries largely influence the resulting fragility functions, such that building models are unsuitable to be adopted for risk assessment in any other region where a different set of building is present. In this paper, for a given building type (represented in terms of height and structural system), typical New Zealand and US building models are considered to illustrate the differences in structural model parameters and their effects on resulting fragility functions for a set of main-shocks and aftershocks. From this study, the general conclusion is that the methodology and assumptions used to derive basic capacity curve parameters have a considerable influence on fragility curves.

Understanding the Origin of Species with Genome-Scale Data: the Role of Gene Flow

PubMed Central

Sousa, Vitor; Hey, Jody

2017-01-01

As it becomes easier to sequence multiple genomes from closely related species, evolutionary biologists working on speciation are struggling to get the most out of very large population-genomic data sets. Such data hold the potential to resolve evolutionary biology’s long-standing questions about the role of gene exchange in species formation. In principle the new population genomic data can be used to disentangle the conflicting roles of natural selection and gene flow during the divergence process. However there are great challenges in taking full advantage of such data, especially with regard to including recombination in genetic models of the divergence process. Current data, models, methods and the potential pitfalls in using them will be considered here. PMID:23657479

A refined quartic potential energy surface and large scale vibrational calculations for S0 thiophosgene.

PubMed

Rashev, Svetoslav; Moule, David C

2015-04-05

In this work we present a full 6D quartic potential energy surface (PES) for S0 thiophosgene in curvilinear symmetrized bond-angle coordinates. The PES was refined starting from an ab initio field derived from acc-pVTZ basis set with CCSD(T) corrections for electron correlation. In the present calculations we used our variational method that was recently tested on formaldehyde and some of its isotopomers, along with additional improvements. The lower experimentally known vibrational levels for 35Cl2CS were reproduced quite well in the calculations, which can be regarded as a test for the feasibility of the obtained quartic PES. Copyright © 2015 Elsevier B.V. All rights reserved.

Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

NASA Technical Reports Server (NTRS)

Frei, Allan; Nolin, Anne W.; Serreze, Mark C.; Armstrong, Richard L.; McGinnis, David L.; Robinson, David A.

2004-01-01

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.

NV PFA Regional Data

DOE Data Explorer

James Faulds

2015-10-28

This project focused on defining geothermal play fairways and development of a detailed geothermal potential map of a large transect across the Great Basin region (96,000 km2), with the primary objective of facilitating discovery of commercial-grade, blind geothermal fields (i.e. systems with no surface hot springs or fumaroles) and thereby accelerating geothermal development in this promising region. Data included in this submission consists of: structural settings (target areas, recency of faulting, slip and dilation potential, slip rates, quality), regional-scale strain rates, earthquake density and magnitude, gravity data, temperature at 3 km depth, permeability models, favorability models, degree of exploration and exploration opportunities, data from springs and wells, transmission lines and wilderness areas, and published maps and theses for the Nevada Play Fairway area.

Crowdsourcing contest dilemma

PubMed Central

Naroditskiy, Victor; Jennings, Nicholas R.; Van Hentenryck, Pascal; Cebrian, Manuel

2014-01-01

Crowdsourcing offers unprecedented potential for solving tasks efficiently by tapping into the skills of large groups of people. A salient feature of crowdsourcing—its openness of entry—makes it vulnerable to malicious behaviour. Such behaviour took place in a number of recent popular crowdsourcing competitions. We provide game-theoretic analysis of a fundamental trade-off between the potential for increased productivity and the possibility of being set back by malicious behaviour. Our results show that in crowdsourcing competitions malicious behaviour is the norm, not the anomaly—a result contrary to the conventional wisdom in the area. Counterintuitively, making the attacks more costly does not deter them but leads to a less desirable outcome. These findings have cautionary implications for the design of crowdsourcing competitions. PMID:25142518

Perspective: Machine learning potentials for atomistic simulations

NASA Astrophysics Data System (ADS)

Behler, Jörg

2016-11-01

Nowadays, computer simulations have become a standard tool in essentially all fields of chemistry, condensed matter physics, and materials science. In order to keep up with state-of-the-art experiments and the ever growing complexity of the investigated problems, there is a constantly increasing need for simulations of more realistic, i.e., larger, model systems with improved accuracy. In many cases, the availability of sufficiently efficient interatomic potentials providing reliable energies and forces has become a serious bottleneck for performing these simulations. To address this problem, currently a paradigm change is taking place in the development of interatomic potentials. Since the early days of computer simulations simplified potentials have been derived using physical approximations whenever the direct application of electronic structure methods has been too demanding. Recent advances in machine learning (ML) now offer an alternative approach for the representation of potential-energy surfaces by fitting large data sets from electronic structure calculations. In this perspective, the central ideas underlying these ML potentials, solved problems and remaining challenges are reviewed along with a discussion of their current applicability and limitations.

The effect of dose reduction on the detection of anatomical structures on panoramic radiographs.

PubMed

Kaeppler, G; Dietz, K; Reinert, S

2006-07-01

The aim was to evaluate the effect of dose reduction on diagnostic accuracy using different screen-film combinations and digital techniques for panoramic radiography. Five observers assessed 201 pairs of panoramic radiographs (a total of 402 panoramic radiographs) taken with the Orthophos Plus (Sirona, Bensheim, Germany), for visualization of 11 anatomical structures on each side, using a 3-point scale -1, 0 and 1. Two radiographs of each patient were taken at two different times (conventional setting and setting with decreased dose, done by increasing tube potential settings or halving tube current). To compare the dose at different tube potential settings dose-length product was measured at the secondary collimator. Films with medium and regular intensifying screens (high and low tube potential settings) and storage phosphor plates (low tube potential setting, tube current setting equivalent to regular intensifying screen and halved) were compared. The five observers made 27 610 assessments. Intrarater agreement was expressed by Cohen's kappa coefficient. The results demonstrated an equivalence of regular screens (low tube potential setting) and medium screens (high and low tube potential settings). A significant difference existed between medium screens (low tube potential setting, mean score 0.92) and the group of regular film-screen combinations at high tube potential settings (mean score 0.89) and between all film-screen combinations and the digital system irrespective of exposure (mean score below 0.82). There were no significant differences between medium and regular screens (mean score 0.88 to 0.92) for assessment of the periodontal ligament space, but there was a significant difference compared with the digital system (mean score below 0.76). The kappa coefficient for intrarater agreement was moderate (0.55). New regular intensifying screens can replace medium screens at low tube potential settings. Digital panoramic radiographs should be taken at low tube potential levels with an exposure equivalent at least to a regular intensifying screen.

Empirical relations between large wood transport and catchment characteristics

NASA Astrophysics Data System (ADS)

Steeb, Nicolas; Rickenmann, Dieter; Rickli, Christian; Badoux, Alexandre

2017-04-01

The transport of vast amounts of large wood (LW) in water courses can considerably aggravate hazardous situations during flood events, and often strongly affects resulting flood damage. Large wood recruitment and transport are controlled by various factors which are difficult to assess and the prediction of transported LW volumes is difficult. Such information are, however, important for engineers and river managers to adequately dimension retention structures or to identify critical stream cross-sections. In this context, empirical formulas have been developed to estimate the volume of transported LW during a flood event (Rickenmann, 1997; Steeb et al., 2017). The data base of existing empirical wood load equations is, however, limited. The objective of the present study is to test and refine existing empirical equations, and to derive new relationships to reveal trends in wood loading. Data have been collected for flood events with LW occurrence in Swiss catchments of various sizes. This extended data set allows us to derive statistically more significant results. LW volumes were found to be related to catchment and transport characteristics, such as catchment size, forested area, forested stream length, water discharge, sediment load, or Melton ratio. Both the potential wood load and the fraction that is effectively mobilized during a flood event (effective wood load) are estimated. The difference of potential and effective wood load allows us to derive typical reduction coefficients that can be used to refine spatially explicit GIS models for potential LW recruitment.

Phonological Iconicity Electrifies: An ERP Study on Affective Sound-to-Meaning Correspondences in German

PubMed Central

Ullrich, Susann; Kotz, Sonja A.; Schmidtke, David S.; Aryani, Arash; Conrad, Markus

2016-01-01

While linguistic theory posits an arbitrary relation between signifiers and the signified (de Saussure, 1916), our analysis of a large-scale German database containing affective ratings of words revealed that certain phoneme clusters occur more often in words denoting concepts with negative and arousing meaning. Here, we investigate how such phoneme clusters that potentially serve as sublexical markers of affect can influence language processing. We registered the EEG signal during a lexical decision task with a novel manipulation of the words' putative sublexical affective potential: the means of valence and arousal values for single phoneme clusters, each computed as a function of respective values of words from the database these phoneme clusters occur in. Our experimental manipulations also investigate potential contributions of formal salience to the sublexical affective potential: Typically, negative high-arousing phonological segments—based on our calculations—tend to be less frequent and more structurally complex than neutral ones. We thus constructed two experimental sets, one involving this natural confound, while controlling for it in the other. A negative high-arousing sublexical affective potential in the strictly controlled stimulus set yielded an early posterior negativity (EPN), in similar ways as an independent manipulation of lexical affective content did. When other potentially salient formal features at the sublexical level were not controlled for, the effect of the sublexical affective potential was strengthened and prolonged (250–650 ms), presumably because formal salience helps making specific phoneme clusters efficient sublexical markers of negative high-arousing affective meaning. These neurophysiological data support the assumption that the organization of a language's vocabulary involves systematic sound-to-meaning correspondences at the phonemic level that influence the way we process language. PMID:27588008

MOLSIM: A modular molecular simulation software

PubMed Central

Jurij, Reščič

2015-01-01

The modular software MOLSIM for all‐atom molecular and coarse‐grained simulations is presented with focus on the underlying concepts used. The software possesses four unique features: (1) it is an integrated software for molecular dynamic, Monte Carlo, and Brownian dynamics simulations; (2) simulated objects are constructed in a hierarchical fashion representing atoms, rigid molecules and colloids, flexible chains, hierarchical polymers, and cross‐linked networks; (3) long‐range interactions involving charges, dipoles and/or anisotropic dipole polarizabilities are handled either with the standard Ewald sum, the smooth particle mesh Ewald sum, or the reaction‐field technique; (4) statistical uncertainties are provided for all calculated observables. In addition, MOLSIM supports various statistical ensembles, and several types of simulation cells and boundary conditions are available. Intermolecular interactions comprise tabulated pairwise potentials for speed and uniformity and many‐body interactions involve anisotropic polarizabilities. Intramolecular interactions include bond, angle, and crosslink potentials. A very large set of analyses of static and dynamic properties is provided. The capability of MOLSIM can be extended by user‐providing routines controlling, for example, start conditions, intermolecular potentials, and analyses. An extensive set of case studies in the field of soft matter is presented covering colloids, polymers, and crosslinked networks. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:25994597

Defaunation affects carbon storage in tropical forests

PubMed Central

Bello, Carolina; Galetti, Mauro; Pizo, Marco A.; Magnago, Luiz Fernando S.; Rocha, Mariana F.; Lima, Renato A. F.; Peres, Carlos A.; Ovaskainen, Otso; Jordano, Pedro

2015-01-01

Carbon storage is widely acknowledged as one of the most valuable forest ecosystem services. Deforestation, logging, fragmentation, fire, and climate change have significant effects on tropical carbon stocks; however, an elusive and yet undetected decrease in carbon storage may be due to defaunation of large seed dispersers. Many large tropical trees with sizeable contributions to carbon stock rely on large vertebrates for seed dispersal and regeneration, however many of these frugivores are threatened by hunting, illegal trade, and habitat loss. We used a large data set on tree species composition and abundance, seed, fruit, and carbon-related traits, and plant-animal interactions to estimate the loss of carbon storage capacity of tropical forests in defaunated scenarios. By simulating the local extinction of trees that depend on large frugivores in 31 Atlantic Forest communities, we found that defaunation has the potential to significantly erode carbon storage even when only a small proportion of large-seeded trees are extirpated. Although intergovernmental policies to reduce carbon emissions and reforestation programs have been mostly focused on deforestation, our results demonstrate that defaunation, and the loss of key ecological interactions, also poses a serious risk for the maintenance of tropical forest carbon storage. PMID:26824067

Efficient preparation of large-block-code ancilla states for fault-tolerant quantum computation

NASA Astrophysics Data System (ADS)

Zheng, Yi-Cong; Lai, Ching-Yi; Brun, Todd A.

2018-03-01

Fault-tolerant quantum computation (FTQC) schemes that use multiqubit large block codes can potentially reduce the resource overhead to a great extent. A major obstacle is the requirement for a large number of clean ancilla states of different types without correlated errors inside each block. These ancilla states are usually logical stabilizer states of the data-code blocks, which are generally difficult to prepare if the code size is large. Previously, we have proposed an ancilla distillation protocol for Calderbank-Shor-Steane (CSS) codes by classical error-correcting codes. It was assumed that the quantum gates in the distillation circuit were perfect; however, in reality, noisy quantum gates may introduce correlated errors that are not treatable by the protocol. In this paper, we show that additional postselection by another classical error-detecting code can be applied to remove almost all correlated errors. Consequently, the revised protocol is fully fault tolerant and capable of preparing a large set of stabilizer states sufficient for FTQC using large block codes. At the same time, the yield rate can be boosted from O (t-2) to O (1 ) in practice for an [[n ,k ,d =2 t +1

Data Mining of Extremely Large Ad Hoc Data Sets to Produce Inverted Indices

DTIC Science & Technology

2016-06-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited DATA MINING OF...COVERED Master’s Thesis 4. TITLE AND SUBTITLE DATA MINING OF EXTREMELY LARGE AD HOC DATA SETS TO PRODUCE INVERTED INDICES 5. FUNDING NUMBERS 6...INTENTIONALLY LEFT BLANK iii Approved for public release; distribution is unlimited DATA MINING OF EXTREMELY LARGE AD HOC DATA SETS TO PRODUCE

Theory of self-resonance after inflation. I. Adiabatic and isocurvature Goldstone modes

NASA Astrophysics Data System (ADS)

Hertzberg, Mark P.; Karouby, Johanna; Spitzer, William G.; Becerra, Juana C.; Li, Lanqing

2014-12-01

We develop a theory of self-resonance after inflation. We study a large class of models involving multiple scalar fields with an internal symmetry. For illustration, we often specialize to dimension-four potentials, but we derive results for general potentials. This is the first part of a two part series of papers. Here in Part 1 we especially focus on the behavior of long-wavelength modes, which are found to govern most of the important physics. Since the inflaton background spontaneously breaks the time-translation symmetry and the internal symmetry, we obtain Goldstone modes; these are the adiabatic and isocurvature modes. We find general conditions on the potential for when a large instability band exists for these modes at long wavelengths. For the adiabatic mode, this is determined by a sound speed derived from the time-averaged potential, while for the isocurvature mode, this is determined by a speed derived from a time-averaged auxiliary potential. Interestingly, we find that this instability band usually exists for one of these classes of modes, rather than both simultaneously. We focus on backgrounds that evolve radially in field space, as set up by inflation, and also mention circular orbits, as relevant to Q -balls. In Part 2 [M. P. Hertzberg et al., Phys. Rev. D 90, 123529 (2014)] we derive the central behavior from the underlying description of many-particle quantum mechanics, and introduce a weak breaking of the symmetry to study corrections to particle-antiparticle production from preheating.

The Project Data Sphere Initiative: Accelerating Cancer Research by Sharing Data

PubMed Central

Reeder-Hayes, Katherine E.; Corty, Robert W.; Basch, Ethan; Milowsky, Mathew I.; Dusetzina, Stacie B.; Bennett, Antonia V.; Wood, William A.

2015-01-01

Background. In this paper, we provide background and context regarding the potential for a new data-sharing platform, the Project Data Sphere (PDS) initiative, funded by financial and in-kind contributions from the CEO Roundtable on Cancer, to transform cancer research and improve patient outcomes. Given the relatively modest decline in cancer death rates over the past several years, a new research paradigm is needed to accelerate therapeutic approaches for oncologic diseases. Phase III clinical trials generate large volumes of potentially usable information, often on hundreds of patients, including patients treated with standard of care therapies (i.e., controls). Both nationally and internationally, a variety of stakeholders have pursued data-sharing efforts to make individual patient-level clinical trial data available to the scientific research community. Potential Benefits and Risks of Data Sharing. For researchers, shared data have the potential to foster a more collaborative environment, to answer research questions in a shorter time frame than traditional randomized control trials, to reduce duplication of effort, and to improve efficiency. For industry participants, use of trial data to answer additional clinical questions could increase research and development efficiency and guide future projects through validation of surrogate end points, development of prognostic or predictive models, selection of patients for phase II trials, stratification in phase III studies, and identification of patient subgroups for development of novel therapies. Data transparency also helps promote a public image of collaboration and altruism among industry participants. For patient participants, data sharing maximizes their contribution to public health and increases access to information that may be used to develop better treatments. Concerns about data-sharing efforts include protection of patient privacy and confidentiality. To alleviate these concerns, data sets are deidentified to maintain anonymity. To address industry concerns about protection of intellectual property and competitiveness, we illustrate several models for data sharing with varying levels of access to the data and varying relationships between trial sponsors and data access sponsors. The Project Data Sphere Initiative. PDS is an independent initiative of the CEO Roundtable on Cancer Life Sciences Consortium, built to voluntarily share, integrate, and analyze comparator arms of historical cancer clinical trial data sets to advance future cancer research. The aim is to provide a neutral, broad-access platform for industry and academia to share raw, deidentified data from late-phase oncology clinical trials using comparator-arm data sets. These data are likely to be hypothesis generating or hypothesis confirming but, notably, do not take the place of performing a well-designed trial to address a specific hypothesis. Prospective providers of data to PDS complete and sign a data sharing agreement that includes a description of the data they propose to upload, and then they follow easy instructions on the website for uploading their deidentified data. The SAS Institute has also collaborated with the initiative to provide intrinsic analytic tools accessible within the website itself. As of October 2014, the PDS website has available data from 14 cancer clinical trials covering 9,000 subjects, with hopes to further expand the database to include more than 25,000 subject accruals within the next year. PDS differentiates itself from other data-sharing initiatives by its degree of openness, requiring submission of only a brief application with background information of the individual requesting access and agreement to terms of use. Data from several different sponsors may be pooled to develop a comprehensive cohort for analysis. In order to protect patient privacy, data providers in the U.S. are responsible for deidentifying data according to standards set forth by the Privacy Rule of the U.S. Health Insurance Portability and Accountability Act of 1996. Using Data Sharing to Improve Outcomes in Cancer: The “Prostate Cancer Challenge.” Control-arm data of several studies among patients with metastatic castration-resistant prostate cancer (mCRPC) are currently available through PDS. These data sets have multiple potential uses. The “Prostate Cancer Challenge” will ask the cancer research community to use clinical trial data deposited in the PDS website to address key research questions regarding mCRPC. General themes that could be explored by the cancer community are described in this article: prognostic models evaluating the influence of pretreatment factors on survival and patient-reported outcomes; comparative effectiveness research evaluating the efficacy of standard of care therapies, as illustrated in our companion article comparing mitoxantrone plus prednisone with prednisone alone; effects of practice variation in dose, frequency, and duration of therapy; level of patient adherence to elements of trial protocols to inform the design of future clinical trials; and age of subjects, regional differences in health care, and other confounding factors that might affect outcomes. Potential Limitations and Methodological Challenges. The number of data sets available and the lack of experimental-arm data limit the potential scope of research using the current PDS. The number of trials is expected to grow exponentially over the next year and may include multiple cancer settings, such as breast, colorectal, lung, hematologic malignancy, and bone marrow transplantation. Other potential limitations include the retrospective nature of the data analyses performed using PDS and its generalizability, given that clinical trials are often conducted among younger, healthier, and less racially diverse patient populations. Methodological challenges exist when combining individual patient data from multiple clinical trials; however, advancements in statistical methods for secondary database analysis offer many tools for reanalyzing data arising from disparate trials, such as propensity score matching. Despite these concerns, few if any comparable data sets include this level of detail across multiple clinical trials and populations. Conclusion. Access to large, late-phase, cancer-trial data sets has the potential to transform cancer research by optimizing research efficiency and accelerating progress toward meaningful improvements in cancer care. This type of platform provides opportunities for unique research projects that can examine relatively neglected areas and that can construct models necessitating large amounts of detailed data. The full potential of PDS will be realized only when multiple tumor types and larger numbers of data sets are available through the website. PMID:25876994

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

PubMed Central

Beaulieu, J; Doerksen, T; Clément, S; MacKay, J; Bousquet, J

2014-01-01

Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach. PMID:24781808

Height and Cognition at Work: Labor market productivity in a low income setting

PubMed Central

LaFave, Daniel; Thomas, Duncan

2016-01-01

Taller workers earn more, particularly in lower income settings. It has been argued that adult height is a marker of strength which is rewarded in the labor market; a proxy for cognitive performance or other dimensions of human capital such as school quality; a proxy for health status; and a proxy for family background and genetic characteristics. As a result, the argument goes, height is rewarded in the labor market because it is an informative signal of worker quality to an employer. It has also been argued that the height premium is driven by occupational and sectoral choice. This paper evaluates the relative importance of these potential mechanisms underlying the link between adult stature and labor market productivity in a specific low income setting, rural Central Java, Indonesia. Drawing on twelve waves of longitudinal survey data, we establish that height predicts hourly earnings after controlling education, multiple indicators of cognitive performance and physical health status, measures of family background, sectoral and occupational choice, as well as local area market characteristics. The height premium is large and significant in both the wage and self-employed sectors indicating height is not only a signal of worker quality to employers. Since adult stature is largely determined in the first few years of life, we conclude that exposures during this critical period have an enduring impact on labor market productivity. PMID:27843117

Privacy-preserving heterogeneous health data sharing.

PubMed

Mohammed, Noman; Jiang, Xiaoqian; Chen, Rui; Fung, Benjamin C M; Ohno-Machado, Lucila

2013-05-01

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among existing privacy models, ε-differential privacy provides one of the strongest privacy guarantees and makes no assumptions about an adversary's background knowledge. All existing solutions that ensure ε-differential privacy handle the problem of disclosing relational and set-valued data in a privacy-preserving manner separately. In this paper, we propose an algorithm that considers both relational and set-valued data in differentially private disclosure of healthcare data. The proposed approach makes a simple yet fundamental switch in differentially private algorithm design: instead of listing all possible records (ie, a contingency table) for noise addition, records are generalized before noise addition. The algorithm first generalizes the raw data in a probabilistic way, and then adds noise to guarantee ε-differential privacy. We showed that the disclosed data could be used effectively to build a decision tree induction classifier. Experimental results demonstrated that the proposed algorithm is scalable and performs better than existing solutions for classification analysis. The resulting utility may degrade when the output domain size is very large, making it potentially inappropriate to generate synthetic data for large health databases. Unlike existing techniques, the proposed algorithm allows the disclosure of health data containing both relational and set-valued data in a differentially private manner, and can retain essential information for discriminative analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosch, R.; Trosseille, C.; Caillaud, T.

The Laser Megajoule (LMJ) facility located at CEA/CESTA started to operate in the early 2014 with two quadruplets (20 kJ at 351 nm) focused on target for the first experimental campaign. We present here the first set of gated x-ray imaging (GXI) diagnostics implemented on LMJ since mid-2014. This set consists of two imaging diagnostics with spatial, temporal, and broadband spectral resolution. These diagnostics will give basic measurements, during the entire life of the facility, such as position, structure, and balance of beams, but they will also be used to characterize gas filled target implosion symmetry and timing, to studymore » x-ray radiography and hydrodynamic instabilities. The design requires a vulnerability approach, because components will operate in a harsh environment induced by neutron fluxes, gamma rays, debris, and shrapnel. Grazing incidence x-ray microscopes are fielded as far as possible away from the target to minimize potential damage and signal noise due to these sources. These imaging diagnostics incorporate microscopes with large source-to-optic distance and large size gated microchannel plate detectors. Microscopes include optics with grazing incidence mirrors, pinholes, and refractive lenses. Spatial, temporal, and spectral performances have been measured on x-ray tubes and UV lasers at CEA-DIF and at Physikalisch-Technische Bundesanstalt BESSY II synchrotron prior to be set on LMJ. GXI-1 and GXI-2 designs, metrology, and first experiments on LMJ are presented here.« less

Privacy-preserving heterogeneous health data sharing

PubMed Central

Mohammed, Noman; Jiang, Xiaoqian; Chen, Rui; Fung, Benjamin C M; Ohno-Machado, Lucila

2013-01-01

Objective Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among existing privacy models, ε-differential privacy provides one of the strongest privacy guarantees and makes no assumptions about an adversary's background knowledge. All existing solutions that ensure ε-differential privacy handle the problem of disclosing relational and set-valued data in a privacy-preserving manner separately. In this paper, we propose an algorithm that considers both relational and set-valued data in differentially private disclosure of healthcare data. Methods The proposed approach makes a simple yet fundamental switch in differentially private algorithm design: instead of listing all possible records (ie, a contingency table) for noise addition, records are generalized before noise addition. The algorithm first generalizes the raw data in a probabilistic way, and then adds noise to guarantee ε-differential privacy. Results We showed that the disclosed data could be used effectively to build a decision tree induction classifier. Experimental results demonstrated that the proposed algorithm is scalable and performs better than existing solutions for classification analysis. Limitation The resulting utility may degrade when the output domain size is very large, making it potentially inappropriate to generate synthetic data for large health databases. Conclusions Unlike existing techniques, the proposed algorithm allows the disclosure of health data containing both relational and set-valued data in a differentially private manner, and can retain essential information for discriminative analysis. PMID:23242630

Utilization of Expert Knowledge in a Multi-Objective Hydrologic Model Automatic Calibration Process

NASA Astrophysics Data System (ADS)

Quebbeman, J.; Park, G. H.; Carney, S.; Day, G. N.; Micheletty, P. D.

2016-12-01

Spatially distributed continuous simulation hydrologic models have a large number of parameters for potential adjustment during the calibration process. Traditional manual calibration approaches of such a modeling system is extremely laborious, which has historically motivated the use of automatic calibration procedures. With a large selection of model parameters, achieving high degrees of objective space fitness - measured with typical metrics such as Nash-Sutcliffe, Kling-Gupta, RMSE, etc. - can easily be achieved using a range of evolutionary algorithms. A concern with this approach is the high degree of compensatory calibration, with many similarly performing solutions, and yet grossly varying parameter set solutions. To help alleviate this concern, and mimic manual calibration processes, expert knowledge is proposed for inclusion within the multi-objective functions, which evaluates the parameter decision space. As a result, Pareto solutions are identified with high degrees of fitness, but also create parameter sets that maintain and utilize available expert knowledge resulting in more realistic and consistent solutions. This process was tested using the joint SNOW-17 and Sacramento Soil Moisture Accounting method (SAC-SMA) within the Animas River basin in Colorado. Three different elevation zones, each with a range of parameters, resulted in over 35 model parameters simultaneously calibrated. As a result, high degrees of fitness were achieved, in addition to the development of more realistic and consistent parameter sets such as those typically achieved during manual calibration procedures.

A comprehensive data set of lake surface water temperature over the Tibetan Plateau derived from MODIS LST products 2001–2015

PubMed Central

Wan, Wei; Li, Huan; Xie, Hongjie; Hong, Yang; Long, Di; Zhao, Limin; Han, Zhongying; Cui, Yaokui; Liu, Baojian; Wang, Cunguang; Yang, Wenting

2017-01-01

Lake surface water temperature (LSWT) is sensitive to long-term changes in thermal structure of lakes and regional air temperature. In the context of global climate change, recent studies showed a significant warming trend of LSWT based on investigating 291 lakes (71% are large lakes, ≥50 km2 each) globally. However, further efforts are needed to examine variation in LSWT at finer regional spatial and temporal scales. The Tibetan Plateau (TP), known as ‘the Roof of the World’ and ‘Asia’s water towers’, exerts large influences on and is sensitive to regional and even global climates. Aiming to examine detailed changing patterns and potential driven mechanisms for temperature variations of lakes across the TP region, this paper presents the first comprehensive data set of 15-year (2001–2015) nighttime and daytime LSWT for 374 lakes (≥10 km2 each), using MODIS (Moderate Resolution Imaging Spectroradiometer) Land Surface Temperature (LST) products as well as four lake boundary shapefiles (i.e., 2002, 2005, 2009, and 2014) derived from Landsat/CBERS/GaoFen-1 satellite images. The data set itself reveals significant information on LSWT and its changes over the TP and is an indispensable variable for numerous applications related to climate change, water budget analysis (particularly lake evaporation), water storage changes, glacier melting and permafrost degradation, etc. PMID:28742066

A comprehensive data set of lake surface water temperature over the Tibetan Plateau derived from MODIS LST products 2001-2015.

PubMed

Wan, Wei; Li, Huan; Xie, Hongjie; Hong, Yang; Long, Di; Zhao, Limin; Han, Zhongying; Cui, Yaokui; Liu, Baojian; Wang, Cunguang; Yang, Wenting

2017-07-25

Lake surface water temperature (LSWT) is sensitive to long-term changes in thermal structure of lakes and regional air temperature. In the context of global climate change, recent studies showed a significant warming trend of LSWT based on investigating 291 lakes (71% are large lakes, ≥50 km 2 each) globally. However, further efforts are needed to examine variation in LSWT at finer regional spatial and temporal scales. The Tibetan Plateau (TP), known as 'the Roof of the World' and 'Asia's water towers', exerts large influences on and is sensitive to regional and even global climates. Aiming to examine detailed changing patterns and potential driven mechanisms for temperature variations of lakes across the TP region, this paper presents the first comprehensive data set of 15-year (2001-2015) nighttime and daytime LSWT for 374 lakes (≥10 km 2 each), using MODIS (Moderate Resolution Imaging Spectroradiometer) Land Surface Temperature (LST) products as well as four lake boundary shapefiles (i.e., 2002, 2005, 2009, and 2014) derived from Landsat/CBERS/GaoFen-1 satellite images. The data set itself reveals significant information on LSWT and its changes over the TP and is an indispensable variable for numerous applications related to climate change, water budget analysis (particularly lake evaporation), water storage changes, glacier melting and permafrost degradation, etc.

Evaluating a campaign GNSS velocity field derived from an online precise point positioning service

NASA Astrophysics Data System (ADS)

Holden, L.; Silcock, D.; Choy, S.; Cas, R.; Ailleres, L.; Fournier, N.

2017-01-01

Traditional processing of Global Navigation Satellite System (GNSS) data using dedicated scientific software has provided the highest levels of positional accuracy, and has been used extensively in geophysical deformation studies. To achieve these accuracies a significant level of understanding and training is required, limiting their availability to the general scientific community. Various online GNSS processing services, now freely available, address some of these difficulties and allow users to easily process their own GNSS data and potentially obtain high quality results. Previous research into these services has focused on Continually Operating Reference Station (CORS) GNSS data. Less research exists on the results achievable with these services using large campaign GNSS data sets, which are inherently noisier than CORS data. Even less research exists on the quality of velocity fields derived from campaign GNSS data processed through online precise point positioning services. Particularly, whether they are suitable for geodynamic and deformation studies where precise and reliable velocities are needed. In this research, we process a very large campaign GPS data set (spanning 10 yr) with the online Jet Propulsion Laboratory Automated Precise Positioning Service. This data set is taken from a GNSS network specifically designed and surveyed to measure deformation through the central North Island of New Zealand. This includes regional CORS stations. We then use these coordinates to derive a horizontal and vertical velocity field. This is the first time that a large campaign GPS data set has been processed solely using an online service and the solutions used to determine a horizontal and vertical velocity field. We compared this velocity field to that of another well utilized GNSS scientific software package. The results show a good agreement between the CORS positions and campaign station velocities obtained from the two approaches. We discuss the implications of these results for how future GNSS campaign field surveys might be conducted and how their data might be processed.

Food choice in the laboratory pigeon.

PubMed

Biedermann, Traci; Garlick, Dennis; Blaisdell, Aaron P

2012-09-01

Although food reward plays a large role in learning and behavioral experiments, there have been few studies examining the most motivating food reward for pigeons. Brown (1969) found that pigeons had a tendency to prefer peas, while Killeen et al. (1993) found pigeons to prefer peas and popcorn in Experiment 1A. We looked to further explore these options as well as expand upon the types of foods examined beyond mainly grains and seeds. Pigeons were presented with six novel foods (granulated peanuts, popping corn, freeze-dried mealworms, bread crumbs, split peas, and sunflower hearts) allocated into two sets of three food items. Once the most consumed food from each food set was determined, they were pooled together with sorghum seeds (a familiar food) to form a third set. Sunflower hearts were the most consumed of all the food items, followed by corn and granulated peanuts. We discuss the potential factors mediating consumption choice, including nutritional profile and food particle size. Copyright © 2012 Elsevier B.V. All rights reserved.

Food choice in the laboratory pigeon

PubMed Central

Biedermann, Traci; Garlick, Dennis; Blaisdell, Aaron P.

2012-01-01

Although food reward plays a large role in learning and behavioral experiments, there have been few studies examining the most motivating food reward for pigeons. Brown (1969) found that pigeons had a tendency to prefer peas, while Killeen, Cate, and Tran (1993) found pigeons to prefer peas and popcorn in Experiment 1A. We looked to further explore these options as well as expand upon the types of foods examined beyond mainly grains and seeds. Pigeons were presented with six novel foods (granulated peanuts, popping corn, freeze-dried mealworms, bread crumbs, split peas, and sunflower hearts) allocated into two sets of three food items. Once the most consumed food from each food set was determined, they were pooled together with sorghum seeds (a familiar food) to form a third set. Sunflower hearts were the most consumed of all the food items, followed by corn and granulated peanuts. We discuss the potential factors mediating consumption choice, including nutritional profile and food particle size. PMID:22750307

Setting action levels for drinking water: are we protecting our health or our economy (or our backs!)?

PubMed

Reimann, Clemens; Banks, David

2004-10-01

Clean and healthy drinking water is important for life. Drinking water can be drawn from streams, lakes and rivers, directly collected (and stored) from rain, acquired by desalination of ocean water and melting of ice or it can be extracted from groundwater resources. Groundwater may reach the earth's surface in the form of springs or can be extracted via dug or drilled wells; it also contributes significantly to river baseflow. Different water quality issues have to be faced when utilising these different water resources. Some of these are at present largely neglected in water quality regulations. This paper focuses on the inorganic chemical quality of natural groundwater. Possible health effects, the problems of setting meaningful action levels or maximum admissible concentrations (MAC-values) for drinking water, and potential shortcomings in current legislation are discussed. An approach to setting action levels based on transparency, toxicological risk assessment, completeness, and identifiable responsibility is suggested.

Using the Periscope Live Video-Streaming Application for Global Pathology Education: A Brief Introduction.

PubMed

Fuller, Maren Y; Mukhopadhyay, Sanjay; Gardner, Jerad M

2016-07-21

Periscope is a live video-streaming smartphone application (app) that allows any individual with a smartphone to broadcast live video simultaneously to multiple smartphone users around the world. The aim of this review is to describe the potential of this emerging technology for global pathology education. To our knowledge, since the launch of the Periscope app (2015), only a handful of educational presentations by pathologists have been streamed as live video via Periscope. This review includes links to these initial attempts, a step-by-step guide for those interested in using the app for pathology education, and a summary of the pros and cons, including ethical/legal issues. We hope that pathologists will appreciate the potential of Periscope for sharing their knowledge, expertise, and research with a live (and potentially large) audience without the barriers associated with traditional video equipment and standard classroom/conference settings.

A global ab initio potential for HCN/HNC, exact vibrational energies, and comparison to experiment

NASA Technical Reports Server (NTRS)

Bentley, Joseph A.; Bowman, Joel M.; Gazdy, Bela; Lee, Timothy J.; Dateo, Christopher E.

1992-01-01

An ab initio (i.e., from first principles) calculation of vibrational energies of HCN and HNC is reported. The vibrational calculations were done with a new potential derived from a fit to 1124 ab initio electronic energies which were calculated using the highly accurate CCSD(T) coupled-cluster method in conjunction with a large atomic natural orbital basis set. The properties of this potential are presented, and the vibrational calculations are compared to experiment for 54 vibrational transitions, 39 of which are for zero total angular momentum, J = 0, and 15 of which are for J = 1. The level of agreement with experiment is unprecedented for a triatomic with two nonhydrogen atoms, and demonstrates the capability of the latest computational methods to give reliable predictions on a strongly bound triatomic molecule at very high levels of vibrational excitation.

Angle-dependent strong-field molecular ionization rates with tuned range-separated time-dependent density functional theory.

PubMed

Sissay, Adonay; Abanador, Paul; Mauger, François; Gaarde, Mette; Schafer, Kenneth J; Lopata, Kenneth

2016-09-07

Strong-field ionization and the resulting electronic dynamics are important for a range of processes such as high harmonic generation, photodamage, charge resonance enhanced ionization, and ionization-triggered charge migration. Modeling ionization dynamics in molecular systems from first-principles can be challenging due to the large spatial extent of the wavefunction which stresses the accuracy of basis sets, and the intense fields which require non-perturbative time-dependent electronic structure methods. In this paper, we develop a time-dependent density functional theory approach which uses a Gaussian-type orbital (GTO) basis set to capture strong-field ionization rates and dynamics in atoms and small molecules. This involves propagating the electronic density matrix in time with a time-dependent laser potential and a spatial non-Hermitian complex absorbing potential which is projected onto an atom-centered basis set to remove ionized charge from the simulation. For the density functional theory (DFT) functional we use a tuned range-separated functional LC-PBE*, which has the correct asymptotic 1/r form of the potential and a reduced delocalization error compared to traditional DFT functionals. Ionization rates are computed for hydrogen, molecular nitrogen, and iodoacetylene under various field frequencies, intensities, and polarizations (angle-dependent ionization), and the results are shown to quantitatively agree with time-dependent Schrödinger equation and strong-field approximation calculations. This tuned DFT with GTO method opens the door to predictive all-electron time-dependent density functional theory simulations of ionization and ionization-triggered dynamics in molecular systems using tuned range-separated hybrid functionals.

Angle-dependent strong-field molecular ionization rates with tuned range-separated time-dependent density functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sissay, Adonay; Abanador, Paul; Mauger, François

2016-09-07

Strong-field ionization and the resulting electronic dynamics are important for a range of processes such as high harmonic generation, photodamage, charge resonance enhanced ionization, and ionization-triggered charge migration. Modeling ionization dynamics in molecular systems from first-principles can be challenging due to the large spatial extent of the wavefunction which stresses the accuracy of basis sets, and the intense fields which require non-perturbative time-dependent electronic structure methods. In this paper, we develop a time-dependent density functional theory approach which uses a Gaussian-type orbital (GTO) basis set to capture strong-field ionization rates and dynamics in atoms and small molecules. This involves propagatingmore » the electronic density matrix in time with a time-dependent laser potential and a spatial non-Hermitian complex absorbing potential which is projected onto an atom-centered basis set to remove ionized charge from the simulation. For the density functional theory (DFT) functional we use a tuned range-separated functional LC-PBE*, which has the correct asymptotic 1/r form of the potential and a reduced delocalization error compared to traditional DFT functionals. Ionization rates are computed for hydrogen, molecular nitrogen, and iodoacetylene under various field frequencies, intensities, and polarizations (angle-dependent ionization), and the results are shown to quantitatively agree with time-dependent Schrödinger equation and strong-field approximation calculations. This tuned DFT with GTO method opens the door to predictive all-electron time-dependent density functional theory simulations of ionization and ionization-triggered dynamics in molecular systems using tuned range-separated hybrid functionals.« less

Assessment of the potential of urban organic carbon dynamics to off-set urban anthropogenic emissions

NASA Astrophysics Data System (ADS)

Gottschalk, P.; Churkina, G.; Wattenbach, M.; Cubasch, U.

2010-12-01

The impact of urban systems on current and future global carbon emissions has been a focus of several studies. Many mitigation options in terms of increasing energy efficiency are discussed. However, apart from technical mitigation potential urban systems also have a considerable biogenic potential to mitigate carbon through an optimized management of organic carbon pools of vegetation and soil. Berlin city area comprises almost 50% of areas covered with vegetation or largely covered with vegetation. This potentially offers various areas for carbon mitigation actions. To assess the mitigation potentials our first objective is to estimate how large current vegetation and soil carbon stocks of Berlin are. We use publicly available forest and soil inventories to calculate soil organic carbon of non-pervious areas and forest standing biomass carbon. This research highlights data-gaps and assigns uncertainty ranges to estimated carbon resources. The second objective is to assess the carbon mitigation potential of Berlin’s vegetation and soils using a biogeochemical simulation model. BIOME-BGC simulates carbon-, nitrogen- and water-fluxes of ecosystems mechanistically. First, its applicability for Berlin forests is tested at selected sites. A spatial application gives an estimate of current net carbon fluxes. The application of such a model allows determining the sensitivity of key ecosystem processes (e.g. carbon gains through photosynthesis, carbon losses through decomposition) towards external drivers. This information can then be used to optimise forest management in terms of carbon mitigation. Initial results of Berlin’s current carbon stocks and its spatial distribution and preliminary simulations results will be presented.

A geometrical correction for the inter- and intra-molecular basis set superposition error in Hartree-Fock and density functional theory calculations for large systems

NASA Astrophysics Data System (ADS)

Kruse, Holger; Grimme, Stefan

2012-04-01

A semi-empirical counterpoise-type correction for basis set superposition error (BSSE) in molecular systems is presented. An atom pair-wise potential corrects for the inter- and intra-molecular BSSE in supermolecular Hartree-Fock (HF) or density functional theory (DFT) calculations. This geometrical counterpoise (gCP) denoted scheme depends only on the molecular geometry, i.e., no input from the electronic wave-function is required and hence is applicable to molecules with ten thousands of atoms. The four necessary parameters have been determined by a fit to standard Boys and Bernadi counterpoise corrections for Hobza's S66×8 set of non-covalently bound complexes (528 data points). The method's target are small basis sets (e.g., minimal, split-valence, 6-31G*), but reliable results are also obtained for larger triple-ζ sets. The intermolecular BSSE is calculated by gCP within a typical error of 10%-30% that proves sufficient in many practical applications. The approach is suggested as a quantitative correction in production work and can also be routinely applied to estimate the magnitude of the BSSE beforehand. The applicability for biomolecules as the primary target is tested for the crambin protein, where gCP removes intramolecular BSSE effectively and yields conformational energies comparable to def2-TZVP basis results. Good mutual agreement is also found with Jensen's ACP(4) scheme, estimating the intramolecular BSSE in the phenylalanine-glycine-phenylalanine tripeptide, for which also a relaxed rotational energy profile is presented. A variety of minimal and double-ζ basis sets combined with gCP and the dispersion corrections DFT-D3 and DFT-NL are successfully benchmarked on the S22 and S66 sets of non-covalent interactions. Outstanding performance with a mean absolute deviation (MAD) of 0.51 kcal/mol (0.38 kcal/mol after D3-refit) is obtained at the gCP-corrected HF-D3/(minimal basis) level for the S66 benchmark. The gCP-corrected B3LYP-D3/6-31G* model chemistry yields MAD=0.68 kcal/mol, which represents a huge improvement over plain B3LYP/6-31G* (MAD=2.3 kcal/mol). Application of gCP-corrected B97-D3 and HF-D3 on a set of large protein-ligand complexes prove the robustness of the method. Analytical gCP gradients make optimizations of large systems feasible with small basis sets, as demonstrated for the inter-ring distances of 9-helicene and most of the complexes in Hobza's S22 test set. The method is implemented in a freely available FORTRAN program obtainable from the author's website.

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

PubMed

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J; Inzé, Dirk; Van de Peer, Yves

2013-03-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

Information science team

NASA Technical Reports Server (NTRS)

Billingsley, F.

1982-01-01

Concerns are expressed about the data handling aspects of system design and about enabling technology for data handling and data analysis. The status, contributing factors, critical issues, and recommendations for investigations are listed for data handling, rectification and registration, and information extraction. Potential supports to individual P.I., research tasks, systematic data system design, and to system operation. The need for an airborne spectrometer class instrument for fundamental research in high spectral and spatial resolution is indicated. Geographic information system formatting and labelling techniques, very large scale integration, and methods for providing multitype data sets must also be developed.

OSHA safety requirements for hazardous chemicals in the workplace.

PubMed

Dohms, J

1992-01-01

This article outlines the Occupational Safety and Health Administration (OSHA) requirements set forth by the Hazard Communication Standard, which has been in effect for the healthcare industry since 1987. Administrators who have not taken concrete steps to address employee health and safety issues relating to hazardous chemicals are encouraged to do so to avoid the potential of large fines for cited violations. While some states administer their own occupational safety and health programs, they must adopt standards and enforce requirements that are at least as effective as federal requirements.

Acquisition and Processing of Information During States of Rapid Eye Movement (REM) Sleep and Slow-Wave Sleep

DTIC Science & Technology

1990-07-01

sleep to favor one set of material in preference to others. This could apply to skill learning as well as declarative memory with considerable potential...not be advantageous for an organism to store a large number of specific memories , specific records of the many experiences of each day of its lifetime...be stored in real time in a sequential representation, as on a serial computer tape. Access to this "episodic" memory would be by serial order, by time

Observation of alpha particle loss from JET plasmas during ion cyclotron resonance frequency heating using a thin foil Faraday cup detector array.

PubMed

Darrow, D S; Cecil, F E; Kiptily, V; Fullard, K; Horton, A; Murari, A

2010-10-01

The loss of MeV alpha particles from JET plasmas has been measured with a set of thin foil Faraday cup detectors during third harmonic heating of helium neutral beam ions. Tail temperatures of ∼ 2 MeV have been observed, with radial scrape off lengths of a few centimeters. Operational experience from this system indicates that such detectors are potentially feasible for future large tokamaks, but careful attention to screening rf and MHD induced noise is essential.

Extending the accuracy of the SNAP interatomic potential form

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Mitchell A.; Thompson, Aidan P.

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functionsmore » in EAM. It is also argued that the quadratic SNAP form is a special case of an artificial neural network (ANN). The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similarly to ANN potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting, as measured by cross-validation analysis.« less

Extending the accuracy of the SNAP interatomic potential form

DOE PAGES

Wood, Mitchell A.; Thompson, Aidan P.

2018-03-28

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functionsmore » in EAM. It is also argued that the quadratic SNAP form is a special case of an artificial neural network (ANN). The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similarly to ANN potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting, as measured by cross-validation analysis.« less

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

PubMed

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

A Comprehensive Precipitation Data Set for Global Land Areas (TR-051)

DOE Data Explorer

Eischeid, J. K. [Univ. of Colorado, Boulder, CO (United States) Cooperative Inst. for Research in Environmental Sciences (CIRES); NOAA; Diaz, H. F. [Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); NOAA; Bradley, R. S. [University of Massachusetts, Amherst, MA (USA); Jones, P. D. [University of East Anglia, Norwich, United Kingdom

1994-01-01

An expanded and updated compilation of long-term station precipitation data, together with a new set of gridded monthly mean fields for global land areas, are described. The present data set contains 5328 station records of monthly total precipitation, covering the period from the mid-1800s to the late 1980s. The station data were individually tested and visually inspected for the presence of spurious trends, jumps, and other measurement biases. The quality control procedure which was used to check the station records for nonclimatic discontinuities and other biases is detailed. We also discuss some of the problems which typically contribute to potential inhomogeneities in precipitation records. The station data were interpolated onto a 4° latitude by 5° longitude uniform grid. Comparisons of these data with two other global-scale precipitation climatologies are presented. We find good agreement among the three global-scale climatologies over the common areas in each set. Three different indices of long-term precipitation variations over the global land areas all indicate a general increase of annual precipitation since the 1940s, although a decline is evident over the last decade. There is some indication that the last few decades of the 19th century may have been as wet as the recent ones. An interesting feature of this study is the presence of relatively large differences in seasonal trends, with March-May and September-November becoming wetter in the last few decades. The December-February and June-August seasons exhibit smaller overall trends, although the northern winter season does exhibit large decadal-scale fluctuations.

Ab Initio and Analytic Intermolecular Potentials for Ar-CF₄

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vayner, Grigoriy; Alexeev, Yuri; Wang, Jiangping

2006-03-09

Ab initio calculations at the CCSD(T) level of theory are performed to characterize the Ar + CF ₄ intermolecular potential. Extensive calculations, with and without a correction for basis set superposition error (BSSE), are performed with the cc-pVTZ basis set. Additional calculations are performed with other correlation consistent (cc) basis sets to extrapolate the Ar---CF₄potential energy minimum to the complete basis set (CBS) limit. Both the size of the basis set and BSSE have substantial effects on the Ar + CF₄ potential. Calculations with the cc-pVTZ basis set and without a BSSE correction, appear to give a good representation ofmore » the potential at the CBS limit and with a BSSE correction. In addition, MP2 theory is found to give potential energies in very good agreement with those determined by the much higher level CCSD(T) theory. Two analytic potential energy functions were determined for Ar + CF₄by fitting the cc-pVTZ calculations both with and without a BSSE correction. These analytic functions were written as a sum of two body potentials and excellent fits to the ab initio potentials were obtained by representing each two body interaction as a Buckingham potential.« less

Combination of large and small basis sets in electronic structure calculations on large systems

NASA Astrophysics Data System (ADS)

Røeggen, Inge; Gao, Bin

2018-04-01

Two basis sets—a large and a small one—are associated with each nucleus of the system. Each atom has its own separate one-electron basis comprising the large basis set of the atom in question and the small basis sets for the partner atoms in the complex. The perturbed atoms in molecules and solids model is at core of the approach since it allows for the definition of perturbed atoms in a system. It is argued that this basis set approach should be particularly useful for periodic systems. Test calculations are performed on one-dimensional arrays of H and Li atoms. The ground-state energy per atom in the linear H array is determined versus bond length.

Identifying Attributes of CO2 Leakage Zones in Shallow Aquifers Using a Parametric Level Set Method

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Islam, A.; Wheeler, M.

2016-12-01

Leakage through abandoned wells and geologic faults poses the greatest risk to CO2 storage permanence. For shallow aquifers, secondary CO2 plumes emanating from the leak zones may go undetected for a sustained period of time and has the greatest potential to cause large-scale and long-term environmental impacts. Identification of the attributes of leak zones, including their shape, location, and strength, is required for proper environmental risk assessment. This study applies a parametric level set (PaLS) method to characterize the leakage zone. Level set methods are appealing for tracking topological changes and recovering unknown shapes of objects. However, level set evolution using the conventional level set methods is challenging. In PaLS, the level set function is approximated using a weighted sum of basis functions and the level set evolution problem is replaced by an optimization problem. The efficacy of PaLS is demonstrated through recovering the source zone created by CO2 leakage into a carbonate aquifer. Our results show that PaLS is a robust source identification method that can recover the approximate source locations in the presence of measurement errors, model parameter uncertainty, and inaccurate initial guesses of source flux strengths. The PaLS inversion framework introduced in this work is generic and can be adapted for any reactive transport model by switching the pre- and post-processing routines.

Analyzing Real-World Light Duty Vehicle Efficiency Benefits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonder, Jeffrey; Wood, Eric; Chaney, Larry

Off-cycle technologies represent an important pathway to achieve real-world fuel savings, through which OEMs can potentially receive credit toward CAFE compliance. DOE national labs such as NREL are well positioned to provide objective input on these technologies using large, national data sets in conjunction with OEM- and technology-specific testing. This project demonstrates an approach that combines vehicle testing (dynamometer and on-road) with powertrain modeling and simulation over large, representative datasets to quantify real-world fuel economy. The approach can be applied to specific off-cycle technologies (engine encapsulation, start/stop, connected vehicle, etc.) in A/B comparisons to support calculation of realistic real-world impacts.more » Future work will focus on testing-based A/B technology comparisons that demonstrate the significance of this approach.« less

Spherical collapse in chameleon models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brax, Ph.; Rosenfeld, R.; Steer, D.A., E-mail: brax@spht.saclay.cea.fr, E-mail: rosenfel@ift.unesp.br, E-mail: daniele.steer@apc.univ-paris7.fr

2010-08-01

We study the gravitational collapse of an overdensity of nonrelativistic matter under the action of gravity and a chameleon scalar field. We show that the spherical collapse model is modified by the presence of a chameleon field. In particular, we find that even though the chameleon effects can be potentially large at small scales, for a large enough initial size of the inhomogeneity the collapsing region possesses a thin shell that shields the modification of gravity induced by the chameleon field, recovering the standard gravity results. We analyse the behaviour of a collapsing shell in a cosmological setting in themore » presence of a thin shell and find that, in contrast to the usual case, the critical density for collapse in principle depends on the initial comoving size of the inhomogeneity.« less

Examining Spillovers between Long and Short Repeated Prisoner's Dilemma Games Played in the Laboratory.

PubMed

Arechar, Antonio A; Kouchaki, Maryam; Rand, David G

2018-03-01

We had participants play two sets of repeated Prisoner's Dilemma (RPD) games, one with a large continuation probability and the other with a small continuation probability, as well as Dictator Games (DGs) before and after the RPDs. We find that, regardless of which is RPD set is played first, participants typically cooperate when the continuation probability is large and defect when the continuation probability is small. However, there is an asymmetry in behavior when transitioning from one continuation probability to the other. When switching from large to small, transient higher levels of cooperation are observed in the early games of the small continuation set. Conversely, when switching from small to large, cooperation is immediately high in the first game of the large continuation set. We also observe that response times increase when transitioning between sets of RPDs, except for altruistic participants transitioning into the set of RPDs with long continuation probabilities. These asymmetries suggest a bias in favor of cooperation. Finally, we examine the link between altruism and RPD play. We find that small continuation probability RPD play is correlated with giving in DGs played before and after the RPDs, whereas high continuation probability RPD play is not.

Statistical study of conductance properties in one-dimensional quantum wires focusing on the 0.7 anomaly

NASA Astrophysics Data System (ADS)

Smith, L. W.; Al-Taie, H.; Sfigakis, F.; See, P.; Lesage, A. A. J.; Xu, B.; Griffiths, J. P.; Beere, H. E.; Jones, G. A. C.; Ritchie, D. A.; Kelly, M. J.; Smith, C. G.

2014-07-01

The properties of conductance in one-dimensional (1D) quantum wires are statistically investigated using an array of 256 lithographically identical split gates, fabricated on a GaAs/AlGaAs heterostructure. All the split gates are measured during a single cooldown under the same conditions. Electron many-body effects give rise to an anomalous feature in the conductance of a one-dimensional quantum wire, known as the "0.7 structure" (or "0.7 anomaly"). To handle the large data set, a method of automatically estimating the conductance value of the 0.7 structure is developed. Large differences are observed in the strength and value of the 0.7 structure [from 0.63 to 0.84×(2e2/h)], despite the constant temperature and identical device design. Variations in the 1D potential profile are quantified by estimating the curvature of the barrier in the direction of electron transport, following a saddle-point model. The 0.7 structure appears to be highly sensitive to the specific confining potential within individual devices.

Bifurcation and stability of single and multiple vortex rings in three-dimensional Bose-Einstein condensates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bisset, R. N.; Wang, Wenlong; Ticknor, C.

Here, we investigate how single- and multi-vortex-ring states can emerge from a planar dark soliton in three-dimensional (3D) Bose-Einstein condensates (confined in isotropic or anisotropic traps) through bifurcations. We characterize such bifurcations quantitatively using a Galerkin-type approach and find good qualitative and quantitative agreement with our Bogoliubov–de Gennes (BdG) analysis. We also systematically characterize the BdG spectrum of the dark solitons, using perturbation theory, and obtain a quantitative match with our 3D BdG numerical calculations. We then turn our attention to the emergence of single- and multi-vortex-ring states. We systematically capture these as stationary states of the system and quantifymore » their BdG spectra numerically. We found that although the vortex ring may be unstable when bifurcating, its instabilities weaken and may even eventually disappear for sufficiently large chemical potentials and suitable trap settings. For instance, we demonstrate the stability of the vortex ring for an isotropic trap in the large-chemical-potential regime.« less

The watershed-scale optimized and rearranged landscape design (WORLD) model and local biomass processing depots for sustainable biofuel production: Integrated life cycle assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eranki, Pragnya L.; Manowitz, David H.; Bals, Bryan D.

An array of feedstock is being evaluated as potential raw material for cellulosic biofuel production. Thorough assessments are required in regional landscape settings before these feedstocks can be cultivated and sustainable management practices can be implemented. On the processing side, a potential solution to the logistical challenges of large biorefi neries is provided by a network of distributed processing facilities called local biomass processing depots. A large-scale cellulosic ethanol industry is likely to emerge soon in the United States. We have the opportunity to influence the sustainability of this emerging industry. The watershed-scale optimized and rearranged landscape design (WORLD) modelmore » estimates land allocations for different cellulosic feedstocks at biorefinery scale without displacing current animal nutrition requirements. This model also incorporates a network of the aforementioned depots. An integrated life cycle assessment is then conducted over the unified system of optimized feedstock production, processing, and associated transport operations to evaluate net energy yields (NEYs) and environmental impacts.« less

Knowledge Support and Automation for Performance Analysis with PerfExplorer 2.0

DOE PAGES

Huck, Kevin A.; Malony, Allen D.; Shende, Sameer; ...

2008-01-01

The integration of scalable performance analysis in parallel development tools is difficult. The potential size of data sets and the need to compare results from multiple experiments presents a challenge to manage and process the information. Simply to characterize the performance of parallel applications running on potentially hundreds of thousands of processor cores requires new scalable analysis techniques. Furthermore, many exploratory analysis processes are repeatable and could be automated, but are now implemented as manual procedures. In this paper, we will discuss the current version of PerfExplorer, a performance analysis framework which provides dimension reduction, clustering and correlation analysis ofmore » individual trails of large dimensions, and can perform relative performance analysis between multiple application executions. PerfExplorer analysis processes can be captured in the form of Python scripts, automating what would otherwise be time-consuming tasks. We will give examples of large-scale analysis results, and discuss the future development of the framework, including the encoding and processing of expert performance rules, and the increasing use of performance metadata.« less

Potential value of systematic reviews of qualitative evidence in informing user-centered health and social care: findings from a descriptive overview.

PubMed

Dalton, Jane; Booth, Andrew; Noyes, Jane; Sowden, Amanda J

2017-08-01

Systematic reviews of quantitative evidence are well established in health and social care. Systematic reviews of qualitative evidence are increasingly available, but volume, topics covered, methods used, and reporting quality are largely unknown. We provide a descriptive overview of systematic reviews of qualitative evidence assessing health and social care interventions included on the Database of Abstracts of Reviews of Effects (DARE). We searched DARE for reviews published between January 1, 2009, and December 31, 2014. We extracted data on review content and methods, summarized narratively, and explored patterns over time. We identified 145 systematic reviews conducted worldwide (64 in the UK). Interventions varied but largely covered treatment or service delivery in community and hospital settings. There were no discernible patterns over time. Critical appraisal of primary studies was conducted routinely. Most reviews were poorly reported. Potential exists to use systematic reviews of qualitative evidence when driving forward user-centered health and social care. We identify where more research is needed and propose ways to improve review methodology and reporting. Copyright © 2017 Elsevier Inc. All rights reserved.

Bifurcation and stability of single and multiple vortex rings in three-dimensional Bose-Einstein condensates

DOE PAGES

Bisset, R. N.; Wang, Wenlong; Ticknor, C.; ...

2015-10-01

Here, we investigate how single- and multi-vortex-ring states can emerge from a planar dark soliton in three-dimensional (3D) Bose-Einstein condensates (confined in isotropic or anisotropic traps) through bifurcations. We characterize such bifurcations quantitatively using a Galerkin-type approach and find good qualitative and quantitative agreement with our Bogoliubov–de Gennes (BdG) analysis. We also systematically characterize the BdG spectrum of the dark solitons, using perturbation theory, and obtain a quantitative match with our 3D BdG numerical calculations. We then turn our attention to the emergence of single- and multi-vortex-ring states. We systematically capture these as stationary states of the system and quantifymore » their BdG spectra numerically. We found that although the vortex ring may be unstable when bifurcating, its instabilities weaken and may even eventually disappear for sufficiently large chemical potentials and suitable trap settings. For instance, we demonstrate the stability of the vortex ring for an isotropic trap in the large-chemical-potential regime.« less

An automated procedure to identify biomedical articles that contain cancer-associated gene variants.

PubMed

McDonald, Ryan; Scott Winters, R; Ankuda, Claire K; Murphy, Joan A; Rogers, Amy E; Pereira, Fernando; Greenblatt, Marc S; White, Peter S

2006-09-01

The proliferation of biomedical literature makes it increasingly difficult for researchers to find and manage relevant information. However, identifying research articles containing mutation data, a requisite first step in integrating large and complex mutation data sets, is currently tedious, time-consuming and imprecise. More effective mechanisms for identifying articles containing mutation information would be beneficial both for the curation of mutation databases and for individual researchers. We developed an automated method that uses information extraction, classifier, and relevance ranking techniques to determine the likelihood of MEDLINE abstracts containing information regarding genomic variation data suitable for inclusion in mutation databases. We targeted the CDKN2A (p16) gene and the procedure for document identification currently used by CDKN2A Database curators as a measure of feasibility. A set of abstracts was manually identified from a MEDLINE search as potentially containing specific CDKN2A mutation events. A subset of these abstracts was used as a training set for a maximum entropy classifier to identify text features distinguishing "relevant" from "not relevant" abstracts. Each document was represented as a set of indicative word, word pair, and entity tagger-derived genomic variation features. When applied to a test set of 200 candidate abstracts, the classifier predicted 88 articles as being relevant; of these, 29 of 32 manuscripts in which manual curation found CDKN2A sequence variants were positively predicted. Thus, the set of potentially useful articles that a manual curator would have to review was reduced by 56%, maintaining 91% recall (sensitivity) and more than doubling precision (positive predictive value). Subsequent expansion of the training set to 494 articles yielded similar precision and recall rates, and comparison of the original and expanded trials demonstrated that the average precision improved with the larger data set. Our results show that automated systems can effectively identify article subsets relevant to a given task and may prove to be powerful tools for the broader research community. This procedure can be readily adapted to any or all genes, organisms, or sets of documents. Published 2006 Wiley-Liss, Inc.

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

PubMed

Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

2015-01-01

Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

High-Throughput Screening Using iPSC-Derived Neuronal Progenitors to Identify Compounds Counteracting Epigenetic Gene Silencing in Fragile X Syndrome.

PubMed

Kaufmann, Markus; Schuffenhauer, Ansgar; Fruh, Isabelle; Klein, Jessica; Thiemeyer, Anke; Rigo, Pierre; Gomez-Mancilla, Baltazar; Heidinger-Millot, Valerie; Bouwmeester, Tewis; Schopfer, Ulrich; Mueller, Matthias; Fodor, Barna D; Cobos-Correa, Amanda

2015-10-01

Fragile X syndrome (FXS) is the most common form of inherited mental retardation, and it is caused in most of cases by epigenetic silencing of the Fmr1 gene. Today, no specific therapy exists for FXS, and current treatments are only directed to improve behavioral symptoms. Neuronal progenitors derived from FXS patient induced pluripotent stem cells (iPSCs) represent a unique model to study the disease and develop assays for large-scale drug discovery screens since they conserve the Fmr1 gene silenced within the disease context. We have established a high-content imaging assay to run a large-scale phenotypic screen aimed to identify compounds that reactivate the silenced Fmr1 gene. A set of 50,000 compounds was tested, including modulators of several epigenetic targets. We describe an integrated drug discovery model comprising iPSC generation, culture scale-up, and quality control and screening with a very sensitive high-content imaging assay assisted by single-cell image analysis and multiparametric data analysis based on machine learning algorithms. The screening identified several compounds that induced a weak expression of fragile X mental retardation protein (FMRP) and thus sets the basis for further large-scale screens to find candidate drugs or targets tackling the underlying mechanism of FXS with potential for therapeutic intervention. © 2015 Society for Laboratory Automation and Screening.

Dynamics of large submarine landslide from analyzing the basal section of mass-transport deposits sampled by IODP Nankai Trough Submarine Landslide History (NanTroSLIDE)

NASA Astrophysics Data System (ADS)

Strasser, M.; Dugan, B.; Henry, P.; Jurado, M. J.; Kanagawa, K.; Kanamatsu, T.; Moore, G. F.; Panieri, G.; Pini, G. A.

2014-12-01

Mulitbeam swath bathymetry and reflection seismic data image large submarine landslide complexes along ocean margins worldwide. However, slope failure initiation, acceleration of motion and mass-transport dynamics of submarine landslides, which are all key to assess their tsunamigenic potential or impact on offshore infrastructure, cannot be conclusively deduced from geometric expression and acoustic characteristics of geophysical data sets alone, but cores and in situ data from the subsurface are needed to complement our understanding of submarine landslide dynamics. Here we present data and results from drilling, logging and coring thick mass-transport deposits (MTDs) in the Nankai Trough accretionary prism during Integrated Ocean Drilling Program (IODP) Expeditions 333 and 338. We integrate analysis on 3D seismic and Logging While Drilling (LWD) data sets, with data from laboratory analysis on core samples (geotechnical shear experiments, X-ray Computed Tomography (X-CT), Scanning Electron Microscopy (SEM) of deformation indicators, and magnetic fabric analysis) to study nature and mode of deformation and dynamics of mass transport in this active tectonic setting. In particular, we show that Fe-S filaments commonly observed on X-ray CT data of marine sediments, likely resulting from early diagenesis of worm burrows, are folded in large MTDs and display preferential orientation at their base. The observed lineation has low dip and is interpreted as the consequence of shear along the basal surface, revealing a new proxy for strain in soft sediments that can be applied to cores that reach through the entire depth of MTDs. Shear deformation in the lower part of thick MTDs is also revealed from AMS data, which - in combination with other paleo-magnetic data - is used to reconstruct strain and transport direction of the landslides.

Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

NASA Astrophysics Data System (ADS)

Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

2010-12-01

Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

Revisiting the immune microenvironment of diffuse large B-cell lymphoma using a tissue microarray and immunohistochemistry: robust semi-automated analysis reveals CD3 and FoxP3 as potential predictors of response to R-CHOP

PubMed Central

Coutinho, Rita; Clear, Andrew J.; Mazzola, Emanuele; Owen, Andrew; Greaves, Paul; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Neuberg, Donna; Calaminici, Maria; Gribben, John G.

2015-01-01

Gene expression studies have identified the microenvironment as a prognostic player in diffuse large B-cell lymphoma. However, there is a lack of simple immune biomarkers that can be applied in the clinical setting and could be helpful in stratifying patients. Immunohistochemistry has been used for this purpose but the results are inconsistent. We decided to reinvestigate the immune microenvironment and its impact using immunohistochemistry, with two systems of image analysis, in a large set of patients with diffuse large B-cell lymphoma. Diagnostic tissue from 309 patients was arrayed onto tissue microarrays. Results from 161 chemoimmunotherapy-treated patients were used for outcome prediction. Positive cells, percentage stained area and numbers of pixels/area were quantified and results were compared with the purpose of inferring consistency between the two semi-automated systems. Measurement cutpoints were assessed using a recursive partitioning algorithm classifying results according to survival. Kaplan-Meier estimators and Fisher exact tests were evaluated to check for significant differences between measurement classes, and for dependence between pairs of measurements, respectively. Results were validated by multivariate analysis incorporating the International Prognostic Index. The concordance between the two systems of image analysis was surprisingly high, supporting their applicability for immunohistochemistry studies. Patients with a high density of CD3 and FoxP3 by both methods had a better outcome. Automated analysis should be the preferred method for immunohistochemistry studies. Following the use of two methods of semi-automated analysis we suggest that CD3 and FoxP3 play a role in predicting response to chemoimmunotherapy in diffuse large B-cell lymphoma. PMID:25425693

Revisiting the immune microenvironment of diffuse large B-cell lymphoma using a tissue microarray and immunohistochemistry: robust semi-automated analysis reveals CD3 and FoxP3 as potential predictors of response to R-CHOP.

PubMed

Coutinho, Rita; Clear, Andrew J; Mazzola, Emanuele; Owen, Andrew; Greaves, Paul; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Neuberg, Donna; Calaminici, Maria; Gribben, John G

2015-03-01

Gene expression studies have identified the microenvironment as a prognostic player in diffuse large B-cell lymphoma. However, there is a lack of simple immune biomarkers that can be applied in the clinical setting and could be helpful in stratifying patients. Immunohistochemistry has been used for this purpose but the results are inconsistent. We decided to reinvestigate the immune microenvironment and its impact using immunohistochemistry, with two systems of image analysis, in a large set of patients with diffuse large B-cell lymphoma. Diagnostic tissue from 309 patients was arrayed onto tissue microarrays. Results from 161 chemoimmunotherapy-treated patients were used for outcome prediction. Positive cells, percentage stained area and numbers of pixels/area were quantified and results were compared with the purpose of inferring consistency between the two semi-automated systems. Measurement cutpoints were assessed using a recursive partitioning algorithm classifying results according to survival. Kaplan-Meier estimators and Fisher exact tests were evaluated to check for significant differences between measurement classes, and for dependence between pairs of measurements, respectively. Results were validated by multivariate analysis incorporating the International Prognostic Index. The concordance between the two systems of image analysis was surprisingly high, supporting their applicability for immunohistochemistry studies. Patients with a high density of CD3 and FoxP3 by both methods had a better outcome. Automated analysis should be the preferred method for immunohistochemistry studies. Following the use of two methods of semi-automated analysis we suggest that CD3 and FoxP3 play a role in predicting response to chemoimmunotherapy in diffuse large B-cell lymphoma. Copyright© Ferrata Storti Foundation.

Exploring the large-scale structure of Taylor–Couette turbulence through Large-Eddy Simulations

NASA Astrophysics Data System (ADS)

Ostilla-Mónico, Rodolfo; Zhu, Xiaojue; Verzicco, Roberto

2018-04-01

Large eddy simulations (LES) of Taylor-Couette (TC) flow, the flow between two co-axial and independently rotating cylinders are performed in an attempt to explore the large-scale axially-pinned structures seen in experiments and simulations. Both static and dynamic LES models are used. The Reynolds number is kept fixed at Re = 3.4 · 104, and the radius ratio η = ri /ro is set to η = 0.909, limiting the effects of curvature and resulting in frictional Reynolds numbers of around Re τ ≈ 500. Four rotation ratios from Rot = ‑0.0909 to Rot = 0.3 are simulated. First, the LES of TC is benchmarked for different rotation ratios. Both the Smagorinsky model with a constant of cs = 0.1 and the dynamic model are found to produce reasonable results for no mean rotation and cyclonic rotation, but deviations increase for increasing rotation. This is attributed to the increasing anisotropic character of the fluctuations. Second, “over-damped” LES, i.e. LES with a large Smagorinsky constant is performed and is shown to reproduce some features of the large-scale structures, even when the near-wall region is not adequately modeled. This shows the potential for using over-damped LES for fast explorations of the parameter space where large-scale structures are found.

Accurately Assessing the Risk of Schizophrenia Conferred by Rare Copy-Number Variation Affecting Genes with Brain Function

PubMed Central

Raychaudhuri, Soumya; Korn, Joshua M.; McCarroll, Steven A.; Altshuler, David; Sklar, Pamela; Purcell, Shaun; Daly, Mark J.

2010-01-01

Investigators have linked rare copy number variation (CNVs) to neuropsychiatric diseases, such as schizophrenia. One hypothesis is that CNV events cause disease by affecting genes with specific brain functions. Under these circumstances, we expect that CNV events in cases should impact brain-function genes more frequently than those events in controls. Previous publications have applied “pathway” analyses to genes within neuropsychiatric case CNVs to show enrichment for brain-functions. While such analyses have been suggestive, they often have not rigorously compared the rates of CNVs impacting genes with brain function in cases to controls, and therefore do not address important confounders such as the large size of brain genes and overall differences in rates and sizes of CNVs. To demonstrate the potential impact of confounders, we genotyped rare CNV events in 2,415 unaffected controls with Affymetrix 6.0; we then applied standard pathway analyses using four sets of brain-function genes and observed an apparently highly significant enrichment for each set. The enrichment is simply driven by the large size of brain-function genes. Instead, we propose a case-control statistical test, cnv-enrichment-test, to compare the rate of CNVs impacting specific gene sets in cases versus controls. With simulations, we demonstrate that cnv-enrichment-test is robust to case-control differences in CNV size, CNV rate, and systematic differences in gene size. Finally, we apply cnv-enrichment-test to rare CNV events published by the International Schizophrenia Consortium (ISC). This approach reveals nominal evidence of case-association in neuronal-activity and the learning gene sets, but not the other two examined gene sets. The neuronal-activity genes have been associated in a separate set of schizophrenia cases and controls; however, testing in independent samples is necessary to definitively confirm this association. Our method is implemented in the PLINK software package. PMID:20838587

Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study.

PubMed

Chowell, Gerardo; Abdirizak, Fatima; Lee, Sunmi; Lee, Jonggul; Jung, Eunok; Nishiura, Hiroshi; Viboud, Cécile

2015-09-03

The Middle East respiratory syndrome (MERS) coronavirus has caused recurrent outbreaks in the Arabian Peninsula since 2012. Although MERS has low overall human-to-human transmission potential, there is occasional amplification in the healthcare setting, a pattern reminiscent of the dynamics of the severe acute respiratory syndrome (SARS) outbreaks in 2003. Here we provide a head-to-head comparison of exposure patterns and transmission dynamics of large hospital clusters of MERS and SARS, including the most recent South Korean outbreak of MERS in 2015. To assess the unexpected nature of the recent South Korean nosocomial outbreak of MERS and estimate the probability of future large hospital clusters, we compared exposure and transmission patterns for previously reported hospital clusters of MERS and SARS, based on individual-level data and transmission tree information. We carried out simulations of nosocomial outbreaks of MERS and SARS using branching process models rooted in transmission tree data, and inferred the probability and characteristics of large outbreaks. A significant fraction of MERS cases were linked to the healthcare setting, ranging from 43.5 % for the nosocomial outbreak in Jeddah, Saudi Arabia, in 2014 to 100 % for both the outbreak in Al-Hasa, Saudi Arabia, in 2013 and the outbreak in South Korea in 2015. Both MERS and SARS nosocomial outbreaks are characterized by early nosocomial super-spreading events, with the reproduction number dropping below 1 within three to five disease generations. There was a systematic difference in the exposure patterns of MERS and SARS: a majority of MERS cases occurred among patients who sought care in the same facilities as the index case, whereas there was a greater concentration of SARS cases among healthcare workers throughout the outbreak. Exposure patterns differed slightly by disease generation, however, especially for SARS. Moreover, the distributions of secondary cases per single primary case varied highly across individual hospital outbreaks (Kruskal-Wallis test; P < 0.0001), with significantly higher transmission heterogeneity in the distribution of secondary cases for MERS than SARS. Simulations indicate a 2-fold higher probability of occurrence of large outbreaks (>100 cases) for SARS than MERS (2 % versus 1 %); however, owing to higher transmission heterogeneity, the largest outbreaks of MERS are characterized by sharper incidence peaks. The probability of occurrence of MERS outbreaks larger than the South Korean cluster (n = 186) is of the order of 1 %. Our study suggests that the South Korean outbreak followed a similar progression to previously described hospital clusters involving coronaviruses, with early super-spreading events generating a disproportionately large number of secondary infections, and the transmission potential diminishing greatly in subsequent generations. Differences in relative exposure patterns and transmission heterogeneity of MERS and SARS could point to changes in hospital practices since 2003 or differences in transmission mechanisms of these coronaviruses.

Limitations and potentials of current motif discovery algorithms

PubMed Central

Hu, Jianjun; Li, Bin; Kihara, Daisuke

2005-01-01

Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithms, their strengths and weaknesses are not sufficiently understood. Here, we designed a comprehensive set of performance measures and benchmarked five modern sequence-based motif discovery algorithms using large datasets generated from Escherichia coli RegulonDB. Factors that affect the prediction accuracy, scalability and reliability are characterized. It is revealed that the nucleotide and the binding site level accuracy are very low, while the motif level accuracy is relatively high, which indicates that the algorithms can usually capture at least one correct motif in an input sequence. To exploit diverse predictions from multiple runs of one or more algorithms, a consensus ensemble algorithm has been developed, which achieved 6–45% improvement over the base algorithms by increasing both the sensitivity and specificity. Our study illustrates limitations and potentials of existing sequence-based motif discovery algorithms. Taking advantage of the revealed potentials, several promising directions for further improvements are discussed. Since the sequence-based algorithms are the baseline of most of the modern motif discovery algorithms, this paper suggests substantial improvements would be possible for them. PMID:16284194

Low energy peripheral scaling in nucleon-nucleon scattering and uncertainty quantification

NASA Astrophysics Data System (ADS)

Ruiz Simo, I.; Amaro, J. E.; Ruiz Arriola, E.; Navarro Pérez, R.

2018-03-01

We analyze the peripheral structure of the nucleon-nucleon interaction for LAB energies below 350 MeV. To this end we transform the scattering matrix into the impact parameter representation by analyzing the scaled phase shifts (L + 1/2) δ JLS (p) and the scaled mixing parameters (L + 1/2)ɛ JLS (p) in terms of the impact parameter b = (L + 1/2)/p. According to the eikonal approximation, at large angular momentum L these functions should become an universal function of b, independent on L. This allows to discuss in a rather transparent way the role of statistical and systematic uncertainties in the different long range components of the two-body potential. Implications for peripheral waves obtained in chiral perturbation theory interactions to fifth order (N5LO) or from the large body of NN data considered in the SAID partial wave analysis are also drawn from comparing them with other phenomenological high-quality interactions, constructed to fit scattering data as well. We find that both N5LO and SAID peripheral waves disagree more than 5σ with the Granada-2013 statistical analysis, more than 2σ with the 6 statistically equivalent potentials fitting the Granada-2013 database and about 1σ with the historical set of 13 high-quality potentials developed since the 1993 Nijmegen analysis.

Fast wave experiments in LAPD: RF sheaths, convective cells and density modifications

NASA Astrophysics Data System (ADS)

Carter, T. A.; van Compernolle, B.; Martin, M.; Gekelman, W.; Pribyl, P.; van Eester, D.; Crombe, K.; Perkins, R.; Lau, C.; Martin, E.; Caughman, J.; Tripathi, S. K. P.; Vincena, S.

2017-10-01

An overview is presented of recent work on ICRF physics at the Large Plasma Device (LAPD) at UCLA. The LAPD has typical plasma parameters ne 1012 -1013 cm-3, Te 1 - 10 eV and B 1000 G. A new high-power ( 150 kW) RF system and fast wave antenna have been developed for LAPD. The source runs at a frequency of 2.4 MHz, corresponding to 1 - 7fci , depending on plasma parameters. Evidence of rectified RF sheaths is seen in large increases ( 10Te) in the plasma potential on field lines connected to the antenna. The rectified potential scales linearly with antenna current. The rectified RF sheaths set up convective cells of local E × B flows, measured indirectly by potential measurements, and measured directly with Mach probes. At high antenna powers substantial modifications of the density profile were observed. The plasma density profile initially exhibits transient low frequency oscillations (10 kHz). The amplitude of the fast wave fields in the core plasma is modulated at the same low frequency, suggesting fast wave coupling is affected by the density rearrangement. Work performed at the Basic Plasma Science Facility, supported jointly by the National Science Foundation and the Department of Energy.

Multidisciplinary population monitoring when demographic data are sparse: a case study of remote trout populations

PubMed Central

Fraser, Dylan J; Calvert, Anna M; Bernatchez, Louis; Coon, Andrew

2013-01-01

The potential of genetic, genomic, and phenotypic metrics for monitoring population trends may be especially high in isolated regions, where traditional demographic monitoring is logistically difficult and only sporadic sampling is possible. This potential, however, is relatively underexplored empirically. Over eleven years, we assessed several such metrics along with traditional ecological knowledge and catch data in a socioeconomically important trout species occupying a large, remote lake. The data revealed largely stable characteristics in two populations over 2–3 generations, but possible contemporary changes in a third population. These potential shifts were suggested by reduced catch rates, reduced body size, and changes in selection implied at one gene-associated single nucleotide polymorphism. A demographic decline in this population, however, was ambiguously supported, based on the apparent lack of temporal change in effective population size, and corresponding traditional knowledge suggesting little change in catch. We illustrate how the pluralistic approach employed has practicality for setting future monitoring efforts of these populations, by guiding monitoring priorities according to the relative merits of different metrics and availability of resources. Our study also considers some advantages and disadvantages to adopting a pluralistic approach to population monitoring where demographic data are not easily obtained. PMID:24455128

New type of hill-top inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barvinsky, A.O.; Department of Physics, Tomsk State University,Lenin Ave. 36, Tomsk 634050; Department of Physics and Astronomy, Pacific Institue for Theoretical Physics,University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1

2016-01-20

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on themore » background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ϵ and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.« less

New type of hill-top inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barvinsky, A.O.; Nesterov, D.V.; Kamenshchik, A.Yu., E-mail: barvin@td.lpi.ru, E-mail: Alexander.Kamenshchik@bo.infn.it, E-mail: nesterov@td.lpi.ru

2016-01-01

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on themore » background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ε and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winkler, Mirko S., E-mail: mirko.winkler@unibas.c; NewFields, LLC, Pretoria 0062; Divall, Mark J., E-mail: mdivall@newfields.co

In the developing world, large-scale projects in the extractive industry and natural resources sectors are often controversial and associated with long-term adverse health consequences to local communities. In many industrialised countries, health impact assessment (HIA) has been institutionalized for the mitigation of anticipated negative health effects while enhancing the benefits of projects, programmes and policies. However, in developing country settings, relatively few HIAs have been performed. Hence, more HIAs with a focus on low- and middle-income countries are needed to advance and refine tools and methods for impact assessment and subsequent mitigation measures. We present a promising HIA approach, developedmore » within the frame of a large gold-mining project in the Democratic Republic of the Congo. The articulation of environmental health areas, the spatial delineation of potentially affected communities and the use of a diversity of sources to obtain quality baseline health data are utilized for risk profiling. We demonstrate how these tools and data are fed into a risk analysis matrix, which facilitates ranking of potential health impacts for subsequent prioritization of mitigation strategies. The outcomes encapsulate a multitude of environmental and health determinants in a systematic manner, and will assist decision-makers in the development of mitigation measures that minimize potential adverse health effects and enhance positive ones.« less

Hydrology and relation of selected water-quality constituents to selected physical factors in Dakota County, Minnesota, 1990-91

USGS Publications Warehouse

Almendinger, J.E.; Mitton, G.B.

1995-01-01

Selected water-quality constituents were determined in water from 5 surface-water sites and 29 wells in Dakota County, Minnesota, to search for possible relations to selected physical factors, including waste-water discharge, agricultural land, Quaternary deposits, bedrock, soil-leaching potential, and water-table depth. All surface-water samples were from the Vermillion River Basin, whose hydrologic setting was studied to determine its relation to the ground-water flow in the surrounding surficial sand aquifer. Each site was sampled from 1 to 12 times during 1990- 91. A total of 198 samples were collected; selected samples were analyzed for major inorganic ions, nutrients, and triazine content. Physical factors within the area of land assumed to be contributing water to each sampling site were determined from existing mapped or digitized sources. Nitrate concentrations in ground water were related to agricultural land and soil-leaching potential. Nitrate concentrations were large (median 13.2 milligrams per liter as nitrogen) where the percentage of agricultural land in the contributing area was large (equal to or greater than 75 percent) and where the soils had a large soil-leaching potential. Nitrate concentrations were small (median 3.2 milligrams per liter as nitrogen) where the soils had a small soil-leaching potential, despite a large percentage of agricultural land. The statistical relation was not particularly strong, however: the null hypothesis that sites with different soil-leaching potentials had the same nitrate concentrations in ground water was rejected by the Kruskal-Wallis test at only the probability P = 0.15 level. Water-table depth was not an important factor in the relation between nitrate concentrations in ground water and agricultural land. Discharge from a waste-water treatment plant provided most of the downstream loading of nitrate into the Vermillion River mainstem. Triazines were found in small concentrations (less than 2 micrograms per liter) in the Vermillion River and its tributaries. No relation was apparent between selected water-quality constituents and either Quaternary deposits or bedrock.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Common complementary and alternative therapies with potential use in dermatologic surgery: risks and benefits.

PubMed

Reddy, Kavitha K; Grossman, Lauri; Rogers, Gary S

2013-04-01

Ambulatory surgery patients often use complementary and alternative medicine (CAM) therapies. CAM therapies may create beneficial and detrimental perioperative conditions. We sought to improve knowledge of CAM effects in dermatologic surgery, allowing dermatologists to potentially capitalize on therapeutic actions and to mitigate complications. PubMed literature search of CAM therapies in dermatologic and surgical settings was performed. Common CAM therapies with possible effects on dermatologic surgery were selected. Beneficial and detri-mental effects were reviewed. A myriad of products may be used perioperatively by the patient. Therapies appearing to have some evidence for potential benefit include bromelain, honey, propolis, arnica, vitamin C and bioflavonoids, chamomile, aloe vera gel, grape seed extract, zinc, turmeric, calendula, chlorella, lavender oil, and gotu kola. Potential complications vary according to product and include platelet inhibition, contact dermatitis and, in rare cases, systemic toxicity. This review focuses on CAM having significant published studies evaluating efficacy for wound healing, anti-inflammatory, antipurpuric, or perioperative-related use. Most published studies have been small and often have design flaws. The scope of CAM is large and not all therapies are discussed. Selected CAM therapies have been reported to promote wound healing, reduce edema or purpura, and provide anti-inflammatory effects. Because of high rates of CAM use, surgeons should familiarize themselves with common uses, potential benefits, and complications. Further study of effects in the dermatologic surgery setting may improve the patient-doctor relationship and enhance outcomes. Copyright © 2011 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Thermophysical properties of krypton-helium gas mixtures from ab initio pair potentials

PubMed Central

2017-01-01

A new potential energy curve for the krypton-helium atom pair was developed using supermolecular ab initio computations for 34 interatomic distances. Values for the interaction energies at the complete basis set limit were obtained from calculations with the coupled-cluster method with single, double, and perturbative triple excitations and correlation consistent basis sets up to sextuple-zeta quality augmented with mid-bond functions. Higher-order coupled-cluster excitations up to the full quadruple level were accounted for in a scheme of successive correction terms. Core-core and core-valence correlation effects were included. Relativistic corrections were considered not only at the scalar relativistic level but also using full four-component Dirac–Coulomb and Dirac–Coulomb–Gaunt calculations. The fitted analytical pair potential function is characterized by a well depth of 31.42 K with an estimated standard uncertainty of 0.08 K. Statistical thermodynamics was applied to compute the krypton-helium cross second virial coefficients. The results show a very good agreement with the best experimental data. Kinetic theory calculations based on classical and quantum-mechanical approaches for the underlying collision dynamics were utilized to compute the transport properties of krypton-helium mixtures in the dilute-gas limit for a large temperature range. The results were analyzed with respect to the orders of approximation of kinetic theory and compared with experimental data. Especially the data for the binary diffusion coefficient confirm the predictive quality of the new potential. Furthermore, inconsistencies between two empirical pair potential functions for the krypton-helium system from the literature could be resolved. PMID:28595411

Paediatric in-patient prescribing errors in Malaysia: a cross-sectional multicentre study.

PubMed

Khoo, Teik Beng; Tan, Jing Wen; Ng, Hoong Phak; Choo, Chong Ming; Bt Abdul Shukor, Intan Nor Chahaya; Teh, Siao Hean

2017-06-01

Background There is a lack of large comprehensive studies in developing countries on paediatric in-patient prescribing errors in different settings. Objectives To determine the characteristics of in-patient prescribing errors among paediatric patients. Setting General paediatric wards, neonatal intensive care units and paediatric intensive care units in government hospitals in Malaysia. Methods This is a cross-sectional multicentre study involving 17 participating hospitals. Drug charts were reviewed in each ward to identify the prescribing errors. All prescribing errors identified were further assessed for their potential clinical consequences, likely causes and contributing factors. Main outcome measures Incidence, types, potential clinical consequences, causes and contributing factors of the prescribing errors. Results The overall prescribing error rate was 9.2% out of 17,889 prescribed medications. There was no significant difference in the prescribing error rates between different types of hospitals or wards. The use of electronic prescribing had a higher prescribing error rate than manual prescribing (16.9 vs 8.2%, p < 0.05). Twenty eight (1.7%) prescribing errors were deemed to have serious potential clinical consequences and 2 (0.1%) were judged to be potentially fatal. Most of the errors were attributed to human factors, i.e. performance or knowledge deficit. The most common contributing factors were due to lack of supervision or of knowledge. Conclusions Although electronic prescribing may potentially improve safety, it may conversely cause prescribing errors due to suboptimal interfaces and cumbersome work processes. Junior doctors need specific training in paediatric prescribing and close supervision to reduce prescribing errors in paediatric in-patients.

Thermophysical properties of krypton-helium gas mixtures from ab initio pair potentials

NASA Astrophysics Data System (ADS)

Jäger, Benjamin; Bich, Eckard

2017-06-01

A new potential energy curve for the krypton-helium atom pair was developed using supermolecular ab initio computations for 34 interatomic distances. Values for the interaction energies at the complete basis set limit were obtained from calculations with the coupled-cluster method with single, double, and perturbative triple excitations and correlation consistent basis sets up to sextuple-zeta quality augmented with mid-bond functions. Higher-order coupled-cluster excitations up to the full quadruple level were accounted for in a scheme of successive correction terms. Core-core and core-valence correlation effects were included. Relativistic corrections were considered not only at the scalar relativistic level but also using full four-component Dirac-Coulomb and Dirac-Coulomb-Gaunt calculations. The fitted analytical pair potential function is characterized by a well depth of 31.42 K with an estimated standard uncertainty of 0.08 K. Statistical thermodynamics was applied to compute the krypton-helium cross second virial coefficients. The results show a very good agreement with the best experimental data. Kinetic theory calculations based on classical and quantum-mechanical approaches for the underlying collision dynamics were utilized to compute the transport properties of krypton-helium mixtures in the dilute-gas limit for a large temperature range. The results were analyzed with respect to the orders of approximation of kinetic theory and compared with experimental data. Especially the data for the binary diffusion coefficient confirm the predictive quality of the new potential. Furthermore, inconsistencies between two empirical pair potential functions for the krypton-helium system from the literature could be resolved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grimme, Stefan, E-mail: grimme@thch.uni-bonn.de; Brandenburg, Jan Gerit; Bannwarth, Christoph

A density functional theory (DFT) based composite electronic structure approach is proposed to efficiently compute structures and interaction energies in large chemical systems. It is based on the well-known and numerically robust Perdew-Burke-Ernzerhoff (PBE) generalized-gradient-approximation in a modified global hybrid functional with a relatively large amount of non-local Fock-exchange. The orbitals are expanded in Ahlrichs-type valence-double zeta atomic orbital (AO) Gaussian basis sets, which are available for many elements. In order to correct for the basis set superposition error (BSSE) and to account for the important long-range London dispersion effects, our well-established atom-pairwise potentials are used. In the design ofmore » the new method, particular attention has been paid to an accurate description of structural parameters in various covalent and non-covalent bonding situations as well as in periodic systems. Together with the recently proposed three-fold corrected (3c) Hartree-Fock method, the new composite scheme (termed PBEh-3c) represents the next member in a hierarchy of “low-cost” electronic structure approaches. They are mainly free of BSSE and account for most interactions in a physically sound and asymptotically correct manner. PBEh-3c yields good results for thermochemical properties in the huge GMTKN30 energy database. Furthermore, the method shows excellent performance for non-covalent interaction energies in small and large complexes. For evaluating its performance on equilibrium structures, a new compilation of standard test sets is suggested. These consist of small (light) molecules, partially flexible, medium-sized organic molecules, molecules comprising heavy main group elements, larger systems with long bonds, 3d-transition metal systems, non-covalently bound complexes (S22 and S66×8 sets), and peptide conformations. For these sets, overall deviations from accurate reference data are smaller than for various other tested DFT methods and reach that of triple-zeta AO basis set second-order perturbation theory (MP2/TZ) level at a tiny fraction of computational effort. Periodic calculations conducted for molecular crystals to test structures (including cell volumes) and sublimation enthalpies indicate very good accuracy competitive to computationally more involved plane-wave based calculations. PBEh-3c can be applied routinely to several hundreds of atoms on a single processor and it is suggested as a robust “high-speed” computational tool in theoretical chemistry and physics.« less

Sizing and Discovery of Nanosized Polyoxometalate Clusters by Mass Spectrometry

PubMed Central

2016-01-01

Ion mobility-mass spectrometry (IM-MS) is a powerful technique for structural characterization, e.g., sizing and conformation, particularly when combined with quantitative modeling and comparison to theoretical values. Traveling wave IM-MS (TW-IM-MS) has recently become commercially available to nonspecialist groups and has been exploited in the structural study of large biomolecules, however reliable calibrants for large anions have not been available. Polyoxometalate (POM) species—nanoscale inorganic anions—share many of the facets of large biomolecules, however, the full potential of IM-MS in their study has yet to be realized due to a lack of suitable calibration data or validated theoretical models. Herein we address these limitations by reporting DT-IM (drift tube) data for a set of POM clusters {M12} Keggin 1, {M18} Dawson 2, and two {M7} Anderson derivatives 3 and 4 which demonstrate their use as a TW-IM-MS calibrant set to facilitate characterization of very large (ca. 1–4 nm) anionic species. The data was also used to assess the validity of standard techniques to model the collision cross sections of large inorganic anions using the nanoscale family of compounds based upon the {Se2W29} unit including the trimer, {Se8W86O299} A, tetramer, {Se8W116O408} B, and hexamer {Se12W174O612} C, including their relative sizing in solution. Furthermore, using this data set, we demonstrated how IM-MS can be used to conveniently characterize and identify the synthesis of two new, i.e., previously unreported POM species, {P8W116}, unknown D, and {Te8W116}, unknown E, which are not amenable to analysis by other means with the approximate formulation of [H34W118X8M2O416]44–, where X = P and M = Co for D and X = Te and M = Mn for E. This work establishes a new type of inorganic calibrant for IM-MS allowing sizing, structural analysis, and discovery of molecular nanostructures directly from solution. PMID:26906879

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

NASA Technical Reports Server (NTRS)

Rutherford, Brian

2000-01-01

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Exploration of Mechanisms behind Changes after Participation in a Parenting Intervention: A Qualitative Study in a Low-Resource Setting.

PubMed

Mejia, Anilena; Ulph, Fiona; Calam, Rachel

2016-03-01

Parenting interventions are effective for preventing psychological difficulties in children. However, their active ingredients have not been comprehensively explored. How do they work? What are the mechanisms operating behind changes? In 2012, a randomized controlled trial of a parenting intervention was conducted in low-resource communities of Panama. Effects on child behavioral difficulties, parental stress, and parenting practices were large in the short and long term. This was an ideal opportunity to explore potential mechanisms operating behind effects found in this low-resource setting. Twenty-five parents were interviewed. Data were analyzed through an inductive semantic thematic analysis. Three themes emerged from the data: (a) psychological mechanisms behind changes, (b) behavioral changes in parent, and (c) changes in the children. Parents described that the intervention triggered changes in emotion regulation, self-efficacy, and problem solving. Parents also reported behavioral changes such as praising their children more often, who in turn seemed more responsible and better at following instructions. The study offers participant-driven insight into potential pathways of change after participation in this parenting intervention, pathways that are often overlooked in quantitative studies. Future studies should further explore these pathways, through mediator and moderator analyses, and determine how much is shared across interventions and across different cultural settings. © Society for Community Research and Action 2016.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

2017-12-01

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Development of glue type potentials for the Al-Pb system: computer simulation of Pb/Al interfaces and phase diagram calculation

NASA Astrophysics Data System (ADS)

Landa, Alex; Wynblatt, Paul; Siegel, Donald; Adams, Jim; Johnson, Erik; Dahmen, Uli

2000-03-01

Empirical many-body potentials have been constructed for the Al-Pb system using the ``force matching" method. The potentials have been fitted to a set of the ground state physical quantities calculated within ab initio approach and a massive quantum mechanical forces database for samples of bulk Al-Pb liquid alloys generated using ab initio molecular dynamics program VASP. Monte Carlo simulations using these potentials have been employed to compute an Al-Pb phase diagram, which is in fair agreement with experimental data, and to model the structure of (111) and (100) Pb/Al interfaces. The calculated free energy ratios for the Pb/Al 100 and 111 interfaces are in good agreement with recent high-resolution transmission electron microscopy measurements. The constructed glue potentials correctly reflects the large change in anisotropy which is observed experimentally between isolated Pb crystals and Pb crystals embedded in Al. Support by the DOE under grants DE-FG02-99ER45773 and DE-AC03-76SF00098, the NSF under grant DMR9619353 and the Danish Natural Sciences Research Council.

Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron

NASA Astrophysics Data System (ADS)

Dragoni, Daniele; Daff, Thomas D.; Csányi, Gábor; Marzari, Nicola

2018-01-01

We show that the Gaussian Approximation Potential (GAP) machine-learning framework can describe complex magnetic potential energy surfaces, taking ferromagnetic iron as a paradigmatic challenging case. The training database includes total energies, forces, and stresses obtained from density-functional theory in the generalized-gradient approximation, and comprises approximately 150,000 local atomic environments, ranging from pristine and defected bulk configurations to surfaces and generalized stacking faults with different crystallographic orientations. We find the structural, vibrational, and thermodynamic properties of the GAP model to be in excellent agreement with those obtained directly from first-principles electronic-structure calculations. There is good transferability to quantities, such as Peierls energy barriers, which are determined to a large extent by atomic configurations that were not part of the training set. We observe the benefit and the need of using highly converged electronic-structure calculations to sample a target potential energy surface. The end result is a systematically improvable potential that can achieve the same accuracy of density-functional theory calculations, but at a fraction of the computational cost.

Research-IQ: Development and Evaluation of an Ontology-anchored Integrative Query Tool

PubMed Central

Borlawsky, Tara B.; Lele, Omkar; Payne, Philip R. O.

2011-01-01

Investigators in the translational research and systems medicine domains require highly usable, efficient and integrative tools and methods that allow for the navigation of and reasoning over emerging large-scale data sets. Such resources must cover a spectrum of granularity from bio-molecules to population phenotypes. Given such information needs, we report upon the initial design and evaluation of an ontology-anchored integrative query tool, Research-IQ, which employs a combination of conceptual knowledge engineering and information retrieval techniques to enable the intuitive and rapid construction of queries, in terms of semi-structured textual propositions, that can subsequently be applied to integrative data sets. Our initial results, based upon both quantitative and qualitative evaluations of the efficacy and usability of Research-IQ, demonstrate its potential to increase clinical and translational research throughput. PMID:21821150

Revisiting the Rossby Haurwitz wave test case with contour advection

NASA Astrophysics Data System (ADS)

Smith, Robert K.; Dritschel, David G.

2006-09-01

This paper re-examines a basic test case used for spherical shallow-water numerical models, and underscores the need for accurate, high resolution models of atmospheric and ocean dynamics. The Rossby-Haurwitz test case, first proposed by Williamson et al. [D.L. Williamson, J.B. Drake, J.J. Hack, R. Jakob, P.N. Swarztrauber, A standard test set for numerical approximations to the shallow-water equations on the sphere, J. Comput. Phys. (1992) 221-224], has been examined using a wide variety of shallow-water models in previous papers. Here, two contour-advective semi-Lagrangian (CASL) models are considered, and results are compared with previous test results. We go further by modifying this test case in a simple way to initiate a rapid breakdown of the basic wave state. This breakdown is accompanied by the formation of sharp potential vorticity gradients (fronts), placing far greater demands on the numerics than the original test case does. We also go further by examining other dynamical fields besides the height and potential vorticity, to assess how well the models deal with gravity waves. Such waves are sensitive to the presence or not of sharp potential vorticity gradients, as well as to numerical parameter settings. In particular, large time steps (convenient for semi-Lagrangian schemes) can seriously affect gravity waves but can also have an adverse impact on the primary fields of height and velocity. These problems are exacerbated by a poor resolution of potential vorticity gradients.

YBYRÁ facilitates comparison of large phylogenetic trees.

PubMed

Machado, Denis Jacob

2015-07-01

The number and size of tree topologies that are being compared by phylogenetic systematists is increasing due to technological advancements in high-throughput DNA sequencing. However, we still lack tools to facilitate comparison among phylogenetic trees with a large number of terminals. The "YBYRÁ" project integrates software solutions for data analysis in phylogenetics. It comprises tools for (1) topological distance calculation based on the number of shared splits or clades, (2) sensitivity analysis and automatic generation of sensitivity plots and (3) clade diagnoses based on different categories of synapomorphies. YBYRÁ also provides (4) an original framework to facilitate the search for potential rogue taxa based on how much they affect average matching split distances (using MSdist). YBYRÁ facilitates comparison of large phylogenetic trees and outperforms competing software in terms of usability and time efficiency, specially for large data sets. The programs that comprises this toolkit are written in Python, hence they do not require installation and have minimum dependencies. The entire project is available under an open-source licence at http://www.ib.usp.br/grant/anfibios/researchSoftware.html .

Uniform Temperature Dependency in the Phenology of a Keystone Herbivore in Lakes of the Northern Hemisphere

PubMed Central

Straile, Dietmar; Adrian, Rita; Schindler, Daniel E.

2012-01-01

Spring phenologies are advancing in many ecosystems associated with climate warming causing unpredictable changes in ecosystem functioning. Here we establish a phenological model for Daphnia, an aquatic keystone herbivore based on decadal data on water temperatures and the timing of Daphnia population maxima from Lake Constance, a large European lake. We tested this model with long-term time-series data from two lakes (Müggelsee, Germany; Lake Washington, USA), and with observations from a diverse set of 49 lakes/sites distributed widely across the Northern Hemisphere (NH). The model successfully captured the observed temporal variation of Daphnia phenology in the two case study sites (r2 = 0.25 and 0.39 for Müggelsee and Lake Washington, respectively) and large-scale spatial variation in the NH (R2 = 0.57). These results suggest that Daphnia phenology follows a uniform temperature dependency in NH lakes. Our approach – based on temperature phenologies – has large potential to study and predict phenologies of animal and plant populations across large latitudinal gradients in other ecosystems. PMID:23071520

Static Analysis of Large-Scale Multibody System Using Joint Coordinates and Spatial Algebra Operator

PubMed Central

Omar, Mohamed A.

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations. PMID:25045732

Exploring astrobiology using in silico molecular structure generation.

PubMed

Meringer, Markus; Cleaves, H James

2017-12-28

The origin of life is typically understood as a transition from inanimate or disorganized matter to self-organized, 'animate' matter. This transition probably took place largely in the context of organic compounds, and most approaches, to date, have focused on using the organic chemical composition of modern organisms as the main guide for understanding this process. However, it has gradually come to be appreciated that biochemistry, as we know it, occupies a minute volume of the possible organic 'chemical space'. As the majority of abiotic syntheses appear to make a large set of compounds not found in biochemistry, as well as an incomplete subset of those that are, it is possible that life began with a significantly different set of components. Chemical graph-based structure generation methods allow for exhaustive in silico enumeration of different compound types and different types of 'chemical spaces' beyond those used by biochemistry, which can be explored to help understand the types of compounds biology uses, as well as to understand the nature of abiotic synthesis, and potentially design novel types of living systems.This article is part of the themed issue 'Reconceptualizing the origins of life'. © 2017 The Authors.

Exploring astrobiology using in silico molecular structure generation

NASA Astrophysics Data System (ADS)

Meringer, Markus; Cleaves, H. James

2017-11-01

The origin of life is typically understood as a transition from inanimate or disorganized matter to self-organized, `animate' matter. This transition probably took place largely in the context of organic compounds, and most approaches, to date, have focused on using the organic chemical composition of modern organisms as the main guide for understanding this process. However, it has gradually come to be appreciated that biochemistry, as we know it, occupies a minute volume of the possible organic `chemical space'. As the majority of abiotic syntheses appear to make a large set of compounds not found in biochemistry, as well as an incomplete subset of those that are, it is possible that life began with a significantly different set of components. Chemical graph-based structure generation methods allow for exhaustive in silico enumeration of different compound types and different types of `chemical spaces' beyond those used by biochemistry, which can be explored to help understand the types of compounds biology uses, as well as to understand the nature of abiotic synthesis, and potentially design novel types of living systems. This article is part of the themed issue 'Reconceptualizing the origins of life'.