cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1487715.v1
title: Hybomitra arpadi (Diptera: Tabanidae) dataset

description: 18 July 2015 This data archive relates to the following paper: Smith, S.M., Turnbull, D.A. and Taylor, P.D. 1994. Assembly, mating, and energetics of Hybomitra arpadi (Diptera: Tabanidae) at Churchill, Manitoba. Journal of Insect Behavior, 7: 355–383. The archive contains analytical notes, raw data, SYSTAT command files, field notes, correspondence relating to the manuscript and some black-and-white and color photographs of the study site.
DOI: 10.6084/m9.figshare.1487712
title: new fileset

description: Graphical Abstract
DOI: 10.6084/m9.figshare.1487714
title: Mineral Composition and Soil-Plant Relationships for Common Guava (<i>Psidium guajava</i> L.) and Yellow Strawberry Guava (<i>Psidium cattleianum</i> var. lucidum) Tree Parts and Fruits

description: The mineral compositions of the fruit and tree parts of common guava, <i>Psidium guajava</i> L., and strawberry guava, <i>Psidium cattleianum</i> var. lucidum, were determined. The study occurred during three seasons at six locations in Hawaii to assess guava as feed for livestock. Guava bark contained the greatest concentrations of calcium (Ca) and ash; leaves the greatest concentrations of magnesium (Mg), sulfur (S), sodium (Na), boron (B), and manganese (Mn); and the shoots had the greatest concentrations of nitrogen (N), phosphorus (P), and potassium (K). The leaves and the shoots had the greatest concentrations of copper (Cu) and iron (Fe). Between guava and waiwi, guava had greater concentrations of most minerals except for Na in all plant parts, and Mg and ash in the leaves. Guava leaves and shoots meet the macromineral requirements for various phases of sheep, goat, and beef cattle life cycles with the exception of P and Na. Guava shoots do not meet Mn requirements for lactating cows.
DOI: 10.6084/m9.figshare.1487696
title: Metabolite BridgeDb ID Mapping Database (20150717)

description: BridgeDb ID mapping database for metabolites, using HMDB 3.6, ChEBI 125, and Wikidata (15 April) as data sources. Affiliation: Dept. of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, The Netherlands
DOI: 10.6084/m9.figshare.1487712.v1
title: new fileset

description: Graphical Abstract
DOI: 10.6084/m9.figshare.1486478
title: LIDDI - Provenance-Centered Dataset of Drug-Drug Interactions

description: Over the years several studies have demonstrated the ability to identify potential drug-drug interactions via data mining from the literature (MEDLINE), electronic health records, public databases (Drugbank), etc. While each one of these approaches is properly statistically validated, they do not take into consideration the overlap between them as one of their decision making variables. In this paper we present LInked Drug-Drug Interactions (LIDDI), a public nanopublication-based RDF dataset with trusty URIs that encompasses some of the most cited prediction methods and sources to provide researchers a resource for leveraging the work of others into their prediction methods. As one of the main issues to overcome the usage of external resources is their mappings between drug names and identifiers used, we also provide the set of mappings we curated to be able to compare the multiple sources we aggregate in our dataset.
DOI: 10.6084/m9.figshare.1486484
title: Old Growth AMF Kootenays

description: We collected soil from adjacent old growth and clear cut redcedar forests in SC BC. Sequences represent 18S SSU rDNA for Glomeromycota (AML1/AML2)
DOI: 10.6084/m9.figshare.1486484.v1
title: Old Growth AMF Kootenays

description: We collected soil from adjacent old growth and clear cut redcedar forests in SC BC. Sequences represent 18S SSU rDNA for Glomeromycota (AML1/AML2)
DOI: 10.6084/m9.figshare.1486475
title: IQ vs. green flags

description: Data from Raven-online (https://raven-online.com/en/page/average-iq-by-country) of 183 countries ranked by average IQ. I have added a boolean for whether the flag of the countries have any green in them. Blog post here: http://pleiotropy.fieldofscience.com/2015/07/having-green-in-your-flag-is-bad-for.html
DOI: 10.6084/m9.figshare.1487696.v1
title: Metabolite BridgeDb ID Mapping Database

description: BridgeDb ID mapping database for metabolites, using HMDB 3.6, ChEBI 125, and Wikidata (15 April) as data sources.
DOI: 10.6084/m9.figshare.1487714.v1
title: Mineral Composition and Soil-Plant Relationships for Common Guava (Psidium guajava L.) and Yellow, Strawberry Guava (Psidium cattleianum var. lucidum) Tree Parts and Fruits

description: The mineral composition of common guava, Psidium guajava L., and strawberry guava, Psidium cattleianum var. lucidum fruit and tree parts was determined. The study occurred during three seasons at six locations in Hawaii to assess guava as feed for livestock. Guava bark contained the greatest concentrations of calcium (Ca) and ash; guava leaves the greatest concentrations of magnesium (Mg), sulfur (S), sodium (Na), boron (B), and manganese (Mn), while the shoots had the greatest concentrations of nitrogen (N), phosphorus (P), and potassium (K). The leaves and the shoots had the greatest concentrations of copper (Cu) and iron (Fe). Between guava and waiwi, guava had greater concentrations of most minerals except for Na in all plant parts, and Mg and ash in the leaves. Guava leaves and shoots meet the macro-mineral requirements for various phases of sheep, goat, and beef cattle life cycles with the exception of P and Na. Guava shoots do not meet Mn requirements for lactating cows.
DOI: 10.6084/m9.figshare.1486472
title: Wave Gradiometry and Helmholtz equatio solutions applied to USArray

description: Gradiometry paramters for 700 events
DOI: 10.6084/m9.figshare.1486475.v1
title: IQ vs. green flags

description: Data from Raven-online (https://raven-online.com/en/page/average-iq-by-country) of 183 countries ranked by average IQ. I have added a boolean for whether the flag of the countries have any green in them. Blog post here: http://pleiotropy.fieldofscience.com/2015/07/having-green-in-your-flag-is-bad-for.html
DOI: 10.6084/m9.figshare.1486472.v1
title: Wave Gradiometry and Helmholtz equatio solutions applied to USArray

description: Gradiometry paramters for 700 events
DOI: 10.6084/m9.figshare.1487714.v3
title: Mineral Composition and Soil-Plant Relationships for Common Guava (<i>Psidium guajava</i> L.) and Yellow Strawberry Guava (<i>Psidium cattleianum</i> var. lucidum) Tree Parts and Fruits

description: The mineral compositions of the fruit and tree parts of common guava, <i>Psidium guajava</i> L., and strawberry guava, <i>Psidium cattleianum</i> var. lucidum, were determined. The study occurred during three seasons at six locations in Hawaii to assess guava as feed for livestock. Guava bark contained the greatest concentrations of calcium (Ca) and ash; leaves the greatest concentrations of magnesium (Mg), sulfur (S), sodium (Na), boron (B), and manganese (Mn); and the shoots had the greatest concentrations of nitrogen (N), phosphorus (P), and potassium (K). The leaves and the shoots had the greatest concentrations of copper (Cu) and iron (Fe). Between guava and waiwi, guava had greater concentrations of most minerals except for Na in all plant parts, and Mg and ash in the leaves. Guava leaves and shoots meet the macromineral requirements for various phases of sheep, goat, and beef cattle life cycles with the exception of P and Na. Guava shoots do not meet Mn requirements for lactating cows.
DOI: 10.6084/m9.figshare.1486471
title: 20070108172150

description: results for 20070108172150 event
DOI: 10.6084/m9.figshare.1487714.v2
title: Mineral Composition and Soil-Plant Relationships for Common Guava (<i>Psidium guajava</i> L.) and Yellow Strawberry Guava (<i>Psidium cattleianum</i> var. lucidum) Tree Parts and Fruits

description: The mineral compositions of the fruit and tree parts of common guava, <i>Psidium guajava</i> L., and strawberry guava, <i>Psidium cattleianum</i> var. lucidum, were determined. The study occurred during three seasons at six locations in Hawaii to assess guava as feed for livestock. Guava bark contained the greatest concentrations of calcium (Ca) and ash; leaves the greatest concentrations of magnesium (Mg), sulfur (S), sodium (Na), boron (B), and manganese (Mn); and the shoots had the greatest concentrations of nitrogen (N), phosphorus (P), and potassium (K). The leaves and the shoots had the greatest concentrations of copper (Cu) and iron (Fe). Between guava and waiwi, guava had greater concentrations of most minerals except for Na in all plant parts, and Mg and ash in the leaves. Guava leaves and shoots meet the macromineral requirements for various phases of sheep, goat, and beef cattle life cycles with the exception of P and Na. Guava shoots do not meet Mn requirements for lactating cows.
DOI: 10.6084/m9.figshare.1486471.v1
title: 20070108172150

description: results for 20070108172150 event
DOI: 10.6084/m9.figshare.1486461
title: Parallel Resampling in the Particle Filter

description: Modern parallel computing devices, such as the graphics processing unit (GPU), have gained significant traction in scientific and statistical computing. They are particularly well-suited to data-parallel algorithms such as the particle filter, or more generally sequential Monte Carlo (SMC), which are increasingly used in statistical inference. SMC methods carry a set of weighted <i>particles</i> through repeated propagation, weighting, and resampling steps. The propagation and weighting steps are straightforward to parallelize, as they require only independent operations on each particle. The resampling step is more difficult, as standard schemes require a collective operation, such as a sum, across particle weights. Focusing on this resampling step, we analyze two alternative schemes that do not involve a collective operation (Metropolis and rejection resamplers), and compare them to standard schemes (multinomial, stratified, and systematic resamplers). We find that, in certain circumstances, the alternative resamplers can perform significantly faster on a GPU, and to a lesser extent on a CPU, than the standard approaches. Moreover, in single precision, the standard approaches are numerically biased for upward of hundreds of thousands of particles, while the alternatives are not. This is particularly important given greater single- than double-precision throughput on modern devices, and the consequent temptation to use single precision with a greater number of particles. Finally, we provide auxiliary functions useful for implementation, such as for the permutation of ancestry vectors to enable in-place propagation. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.1486460
title: Zero Expectile Processes and Bayesian Spatial Regression

description: We introduce new classes of stationary spatial processes with asymmetric, sub-Gaussian marginal distributions using the idea of expectiles. We derive theoretical properties of the proposed processes. Moreover, we use the proposed spatial processes to formulate a spatial regression model for point-referenced data where the spatially correlated errors have skewed marginal distribution. We introduce a Bayesian computational procedure for model fitting and inference for this class of spatial regression models. We compare the performance of the proposed method with the traditional Gaussian process-based spatial regression through simulation studies and by applying it to a dataset on air pollution in California.
DOI: 10.6084/m9.figshare.1486461.v2
title: Parallel Resampling in the Particle Filter

description: Modern parallel computing devices, such as the graphics processing unit (GPU), have gained significant traction in scientific and statistical computing. They are particularly well-suited to data-parallel algorithms such as the particle filter, or more generally sequential Monte Carlo (SMC), which are increasingly used in statistical inference. SMC methods carry a set of weighted <i>particles</i> through repeated propagation, weighting, and resampling steps. The propagation and weighting steps are straightforward to parallelize, as they require only independent operations on each particle. The resampling step is more difficult, as standard schemes require a collective operation, such as a sum, across particle weights. Focusing on this resampling step, we analyze two alternative schemes that do not involve a collective operation (Metropolis and rejection resamplers), and compare them to standard schemes (multinomial, stratified, and systematic resamplers). We find that, in certain circumstances, the alternative resamplers can perform significantly faster on a GPU, and to a lesser extent on a CPU, than the standard approaches. Moreover, in single precision, the standard approaches are numerically biased for upward of hundreds of thousands of particles, while the alternatives are not. This is particularly important given greater single- than double-precision throughput on modern devices, and the consequent temptation to use single precision with a greater number of particles. Finally, we provide auxiliary functions useful for implementation, such as for the permutation of ancestry vectors to enable in-place propagation. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.1486460.v1
title: Zero Expectile Processes and Bayesian Spatial Regression

description: We introduce new classes of stationary spatial processes with asymmetric, sub-Gaussian marginal distributions using the idea of expectiles. We derive theoretical properties of the proposed processes. Moreover, we use the proposed spatial processes to formulate a spatial regression model for point-referenced data where the spatially correlated errors have skewed marginal distribution. We introduce a Bayesian computational procedure for model fitting and inference for this class of spatial regression models. We compare the performance of the proposed method with the traditional Gaussian process-based spatial regression through simulation studies and by applying it to a dataset on air pollution in California.
DOI: 10.6084/m9.figshare.1486461.v1
title: Parallel resampling in the particle filter

description: Modern parallel computing devices, such as the graphics processing unit (GPU), have gained significant traction in scientific and statistical computing. They are particularly well-suited to data-parallel algorithms such as the particle filter, or more generally Sequential Monte Carlo (SMC), which are increasingly used in statistical inference. SMC methods carry a set of weighted <i>particles</i> through repeated propagation, weighting and resampling steps. The propagation and weighting steps are straightforward to parallelise, as they require only independent operations on each particle. The resampling step is more difficult, as standard schemes require a collective operation, such as a sum, across particle weights. Focusing on this resampling step, we analyse two alternative schemes that do not involve a collective operation (Metropolis and rejection resamplers), and compare them to standard schemes (multinomial, stratified and systematic resamplers). We find that, in certain circumstances, the alternative resamplers can perform significantly faster on a GPU, and to a lesser extent on a CPU, than the standard approaches. Moreover, in single precision, the standard approaches are numerically biased for upwards of hundreds of thousands of particles, while the alternatives are not. This is particularly important given greater single- than double-precision throughput on modern devices, and the consequent temptation to use single precision with a greater number of particles. Finally, we provide auxiliary functions useful for implementation, such as for the permutation of ancestry vectors to enable in-place propagation. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.1486456
title: 20070108124841

description: results for 20070108124841 event
DOI: 10.6084/m9.figshare.1486454
title: Babble Model Parameter Variations Sounds

description: These sounds were produced by a computational spiking neural network model of learning to produce syllabic vocalizations (i.e. canonical babbling) in infancy. The vocalizations produced by each simulation from each parameter combination were sampled at regular intervals. For each simulation, these samples were concatenated into a single sound file that can provide an auditory sense of how the simulation's vocalizations changed over time. The best parameter combination is 200 neurons (200n) and 2 muscle scaling (2n).
DOI: 10.6084/m9.figshare.1486456.v1
title: 20070108124841

description: results for 20070108124841 event
DOI: 10.6084/m9.figshare.1486393
title: new fileset

description: spatial discrimiantion data
DOI: 10.6084/m9.figshare.1486454.v1
title: BabbleModelParameterVariationsSounds

description: These sounds were produced by a computational spiking neural network model of learning to produce syllabic vocalizations (i.e. canonical babbling) in infancy. The vocalizations produced by each simulation from each parameter combination were sampled at regular intervals. For each simulation, these samples were concatenated into a single sound file that can provide an auditory sense of how the simulation's vocalizations changed over time. The best parameter combination is 200 neurons (200n) and 2 muscle scaling (2n).
DOI: 10.6084/m9.figshare.1486393.v1
title: new fileset

description: spatial discrimiantion data
DOI: 10.6084/m9.figshare.1486454.v3
title: Babble Model Parameter Variations Sounds

description: These sounds were produced by a computational spiking neural network model of learning to produce syllabic vocalizations (i.e. canonical babbling) in infancy. The vocalizations produced by each simulation from each parameter combination were sampled at regular intervals. For each simulation, these samples were concatenated into a single sound file that can provide an auditory sense of how the simulation's vocalizations changed over time. The best parameter combination is 200 neurons (200n) and 2 muscle scaling (2n).
DOI: 10.6084/m9.figshare.1486377
title: Publication bias in OB/GYN systematic reviews

description: Data from Chong et al study
DOI: 10.6084/m9.figshare.1486454.v5
title: Babble Model Parameter Variations Sounds

description: These sounds were produced by a computational spiking neural network model of learning to produce syllabic vocalizations (i.e. canonical babbling) in infancy. The vocalizations produced by each simulation from each parameter combination were sampled at regular intervals. For each simulation, these samples were concatenated into a single sound file that can provide an auditory sense of how the simulation's vocalizations changed over time. The best parameter combination is 200 neurons (200n) and 2 muscle scaling (2n).
DOI: 10.6084/m9.figshare.1486377.v1
title: Publication bias in OB/GYN systematic reviews

description: Data from Chong et al study
DOI: 10.6084/m9.figshare.1486454.v4
title: Babble Model Parameter Variations Sounds

description: These sounds were produced by a computational spiking neural network model of learning to produce syllabic vocalizations (i.e. canonical babbling) in infancy. The vocalizations produced by each simulation from each parameter combination were sampled at regular intervals. For each simulation, these samples were concatenated into a single sound file that can provide an auditory sense of how the simulation's vocalizations changed over time. The best parameter combination is 200 neurons (200n) and 2 muscle scaling (2n).
DOI: 10.6084/m9.figshare.1486374
title: Green chemistry in chemical reactions: informatics by design

description: Chemical informatics technology can be of assistance to chemists for describing reactions in numerous ways, including calculating green chemistry metrics such as process mass intensity, E-factor and atom economy. To facilitate this, chemical reactions have to be described in more precise detail than is the norm for most chemists. There are also numerous practical ways to add more green chemistry functionality to lab notebooks, such as enumerating searchable reaction transforms for environmentally favourable reactions, automatically looking up toxicity and hazard information, and others which are mentioned in the slides. This presentation was given at the Green Chemistry & Engineering conference in 2015 (Americal Chemical Society Green Chemistry Insititute).
DOI: 10.6084/m9.figshare.1486372
title: Data from: Steep Decline and Cessation in Seed Dispersal by Myrmica rubra Ants

description: Datas from the article "Steep Decline and Cessation in Seed Dispersal by Myrmica rubra Ants" SeedSource: number of seeds left at the foraging platform PreySource: number of prey leyft at the foraging platform
DOI: 10.6084/m9.figshare.1486374.v1
title: Green chemistry in chemical reactions: informatics by design

description: Chemical informatics technology can be of assistance to chemists for describing reactions in numerous ways, including calculating green chemistry metrics such as process mass intensity, E-factor and atom economy. To facilitate this, chemical reactions have to be described in more precise detail than is the norm for most chemists. There are also numerous practical ways to add more green chemistry functionality to lab notebooks, such as enumerating searchable reaction transforms for environmentally favourable reactions, automatically looking up toxicity and hazard information, and others which are mentioned in the slides. This presentation was given at the Green Chemistry & Engineering conference in 2015 (Americal Chemical Society Green Chemistry Insititute).
DOI: 10.6084/m9.figshare.1486364
title: Talk Queen Mary Quantum Graphity

description: given on 17th July 2015
DOI: 10.6084/m9.figshare.1486365
title: Evolving Networks with Memory

description: Package for simulating graphs with memory - Running instructions. Simply unzip into a folder, and run "gui" from a Matlab terminal.
DOI: 10.6084/m9.figshare.1486372.v1
title: Data from: Steep Decline and Cessation in Seed Dispersal by Myrmica rubra Ants

description: Datas from the article "Steep Decline and Cessation in Seed Dispersal by Myrmica rubra Ants" SeedSource: number of seeds left at the foraging platform PreySource: number of prey leyft at the foraging platform
DOI: 10.6084/m9.figshare.1486364.v1
title: Talk Queen Mary Quantum Graphity

description: given on 17th July 2015
DOI: 10.6084/m9.figshare.1485719
title: A Pharmacokinetics-Neural Mass Model (PK-NMM) For the Simulation of EEG Activity during Propofol Anesthesia

description: This file includes the <strong>dataset</strong> and MATLAB programs underlying the findings in the artilcle "A Pharmacokinetics-Neural Mass Model for the Simulation of EEG activity during Propofol Anesthesia" submitted to PLoS ONE.
DOI: 10.6084/m9.figshare.1486354
title: Data from "Warming reduces the cover and diversity of biocrust-forming mosses and lichens, and increases the physiological stress of soil microbial communities in a semi-arid Pinus halepensis plantation"

description: Data from "F. T. Maestre, Escolar, C., R. Bardgett, J. A. D. Dungait, B. Gozalo & V. Ochoa. Warming reduces the cover and diversity of biocrust-forming mosses and lichens, and increases the physiological stress of soil microbial communities in a semi-arid Pinus halepensis plantation. Frontiers in Microbiology 6:865. doi: 10.3389/fmicb.2015.00865" There are three spreadsheets with data. The spreadsheet "PLFA_data" contains the raw PLFA data at the different sampling times. The spreadsheet "Cover_data" contains the cover data for mosses, lichens and the sum of both at the different sampling times. The third spreadshet contains the associated metadata, where a description of all the variables and units can be found.