cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25387/g3.9786281
title: Supplemental Maetrial for Anderson et al., 2019

description: Figure S1: Breakdown of expressed TE families by family size. The proportion and count of TE families with (light blue) or without (dark blue) transcripts for helitrons (DH), TIRs (DT), and LTRs (RL). Families are categorized as small when they have 2-30 members, medium with 31-500 members, and large with &gt; 500 members. <br>Figure S2: TEs contribute to transcriptome dynamics across development in B73. A-B. Principal component analysis was used to plot libraries based on similarity of gene (A) or TE (B) transcript abundance. C. The tissue-specificity of expression was estimated with the tau metric, where low values indicate constitutive expression and high values indicate tissue-specific expression. Tau densities were plotted for helitron (DH), TIR (DT) and LTR (RL) TEs based on family size. Families are categorized as small when they have 2-30 members, medium with 31-500 members, and large with &gt; 500 members. <br><br>Figure S3: Dynamic transcript abundance patterns for expressed TE families in B73. A. Heat map showing the transcript abundance of all TE families detected in the tissue subset. Transcript abundance is normalized by row. B. Rank order plot of the proportion of reads per multi-member family (N = 1176) that are unique mapping. Proportions plotted are the average across all tissues with expression &gt; 1 RPM, and the x-axis is ordered by TE order and proportion unique. C-E. Examples of unique per-element expression patterns for three TE families expressed in the development subset. Libraries are ordered along the x-axis as in A.<br><br>Figure S4: TE transcripts across tissues are dynamic across genotypes. A. The number of TE families expressed (RPM &gt;= 1) is similar in B73 and the other NAM founder lines. B. TE families expressed in B73 also tend to be expressed in a large number of lines, while families not detected in B73 tend to be expressed in few lines. C. Breakdown of TEs detected in any genotype, with rare families detected in &lt; 5 genotypes and common families detected in at least 20 genotypes. <br><br>Figure S5: TE transcript dynamics across Recombinant inbred lines. A. Differentially expressed TE families were plotted, showing little relationship between the difference of members per family in the two parents and the expression difference observed. B. For multi-member TE families expressed specifically in B73 (N = ), the percent of RILs with detectable transcripts (RPM &gt; = 1) is shown. The peak at 50% suggests segregation of a single expressed locus among lines. C. The proportion of TEs in each group that segregate as a unimodal distribution among RILs. <br><br>Table of RNA-seq libraries and accession numbers used in this study.<br>
DOI: 10.25405/data.ncl.9755045.v1
title: Data for "Characterizing the Randot Preschool Stereotest" Read et al 2019

description: This folder contains R markdown files, e.g. AnalyseValidityData6.Rmd, containing analysis code, and associated .RData files containing the data.<br>You will need R, Rstudio and associated libraries (available from rstudio.com, www.r-project.org). <br>To generate the statistical analysis and figures shown in the paper, open up each .Rmd file and hit "knit" to run the code and generate a Word or PDF file.<br><br>
DOI: 10.6084/m9.figshare.8868308.v2
title: Soil GHG Fluxes.xlsx

description: In Sub-Saharan Africa, agricultural production has been on the declined mainly due to low soil fertility exacerbated by climate variability as a result of rise in global atmospheric greenhouse gas (GHG) emissions. Several soil fertility amendments have been developed, experimented, adopted and found to improve both yields and general soil health. However, very few studies has been conducted to quantify the contribution of each the soil fertility amendment towards national GHG budget. This creates a huge data gap which may result to uncertainties in the national GHG inventories and may result to poor targeting of mitigation and adaptation measures thus the need to fill it. Also, Kenya as a developing country has been reporting to the UNFCCC on its current status of GHG emissions using default IPCC Tier I emission factors which tend to over-estimate the national greenhouse status in developing world. It is on these premises that we established this empirical study which was laid down in a randomized complete block design with four treatments replicated thrice. The aim of the study was to determine the soil amendment technology that produces the highest maize yields while simultaneous producing the lowest GHG emissions from a maize field in the arid and semiarid zones of central highlands of Kenya. The three fertiliser treatments investigated were i) animal manure, ii) Inorganic fertiliser, iii) a combination of animal manure and inorganic fertilisers applied at 120 kg N ha<sup>-1 </sup>yr<sup>-1 </sup>and iv) a control (No fertiliser application). The GHG data was collected for a whole year (Feb 2017 –Feb 2018) using static GHG chambers and gas chromatography. Also collected alongside, were the auxiliary data including rainfall, soil water content, soil temperature, LAI, inorganic nitrogen and other soil properties.
DOI: 10.26180/5d78fcbcaf44f
title: Shadow of Mill

description: <sub>This is a music composition for cello and subtone in three movements, composed between 2017 and 2018.</sub><sub><br></sub><sub>It is dedicated to Tristen Parr.</sub><sub><br></sub><sub>The score should be read in the Decibel ScorePlayer application on an iPad. There are three movements, bundled together in a single score file available here. You will also need to print a copy of the White Australia Policy to use in performance, also available here.<br></sub><sub><br></sub><em>Shadow of Mill</em> presents audiences with an open-ended reflection on the issue of settlement and racism in Australia." Eduardo Cossio, Cool Perth Nights. <b><sub><br></sub></b><sub><b>PROGRAM NOTE</b><br>This work is a reflection on the white Australia policy enacted in 1901. The title is taken from Phil Griffith’s paper “Towards White Australia: The Shadow of Mill and the spectre of slavery in the 1802 debates on Chinese Immigration” published in 2002. The peice explores the idea of this Policy, printed on paper of today, interacting with the cello: sensuously rubbed and grated against the body and strings of the instrument as a representative of the European Culture imported into Australia. But this instrument is not played as originally intended. It is detuned, struck and played with two bows, all the time underpinned by subtle 'undertones'.<br>The second movement was commissioned by Gabriella Smart for the APRA|AMC Art Awards in Sydney, 2017. The first and third movements were written for the Summers Night Project in 2018. </sub><sub><br></sub><sub>A digital PDF and hard copy of the score is available from Material Press.</sub><sub><br></sub><sub><br></sub><sub>PERFORMANCES<br><em>2nd movement premiered APRA AMC Art Music Awards, 2017, by Tristen Parr.<br>Full three movements premiered as part of Summers Nights, Perth, Adelaide and Melbourne, July 2018 by Tristen Parr.</em></sub><br>
DOI: 10.25386/genetics.9745103
title: Supplemental Material for Mukiza et al., 2019

description: <b>Supplemental Material</b> file contains:<b>Figure S1</b>, Hotspot-specific chromatin remodeling; <b>Table S1</b>, Fission yeast strain genotypes; <b>Table S2</b>, DNA sequences and locations of <i>ade6</i> alleles; <b>Table S3</b>, DNA sequences and locations of PCR primers; <b>Table S4</b>, Primary data on recombination for Figure 1; <b>Table S5</b>, Primary data on recombination for Figure 5; <b>Table S6</b>, primary data on chromatin structure for Figures 3, 4 and S1.
DOI: 10.25386/genetics.9745103.v1
title: Supplemental Material for Mukiza et al., 2019

description: <b>Supplemental Material</b> file contains:<b>Figure S1</b>, Hotspot-specific chromatin remodeling; <b>Table S1</b>, Fission yeast strain genotypes; <b>Table S2</b>, DNA sequences and locations of <i>ade6</i> alleles; <b>Table S3</b>, DNA sequences and locations of PCR primers; <b>Table S4</b>, Primary data on recombination for Figure 1; <b>Table S5</b>, Primary data on recombination for Figure 5; <b>Table S6</b>, primary data on chromatin structure for Figures 3, 4 and S1.
DOI: 10.6084/m9.figshare.9804470.v1
title: ASCAT segmentation data for array data

description: This is a tab-separated values file containing the ASCAT-derived segmentation data for the array data. This was used as an input to the script provided by Marquard et al 2015 to calculate the HRD score and HRD score components.
DOI: 10.6084/m9.figshare.9786212.v3
title: Water Quality for Kanahwa River WV

description: Data collection for three months (Jan-Mar, 2018) at three locations along the Kanawha River, WV
DOI: 10.25387/g3.7998425.v1
title: Supplemental Material for Li et al., 2019

description: Supplementary figures and tables
DOI: 10.25387/g3.9696170
title: Supplemental Material for Chen, Guo, and Warner, 2019

description: Dataset includes one excel file containing phenotypic data, one excel file containing genotypic data, and one pdf file containing supplementary table and figures.
DOI: 10.25387/g3.9696170.v1
title: Supplemental Material for Chen, Guo, and Warner, 2019

description: Dataset includes one excel file containing phenotypic data, one excel file containing genotypic data, and one pdf file containing supplementary table and figures.
DOI: 10.25387/g3.9820661
title: Supplemental Material for Ochoa et al., 2019

description: Supplemental Material, File S1, and additional input/output data <br>
DOI: 10.25387/g3.9820682
title: Supplemental Material for Mohapatra and Menuz et al., 2019

description: This supporting online material contains a dataset File S1 final, Figure S1, and Supporting Information Captions.<br>
DOI: 10.25387/g3.9820682.v1
title: Supplemental Material for Mohapatra and Menuz et al., 2019

description: This supporting online material contains a dataset File S1 final, Figure S1, and Supporting Information Captions.<br>
DOI: 10.25387/g3.9820661.v1
title: Supplemental Material for Ochoa et al., 2019

description: Supplemental Material, File S1, and additional input/output data <br>
DOI: 10.25387/g3.7998425
title: Supplemental Material for Li et al., 2019

description: Supplementary figures and tables
DOI: 10.6084/m9.figshare.3761562.v1231
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25405/data.ncl.9849803
title: Tracking the evolution of a single composite particle during redox cycling for application in H2 production

description: Composite materials consisting of metal and metal oxide phases are being researched intensively for application in various energy conversion and storage technologies. In these applications, composites are often expected to operate under redox conditions at elevated temperature. The understanding of the dynamics of composite phase and morphology evolution during redox cycling is still very limited, yet critical to maximising performance and increasing durability. Here we track the microstructural evolution of a single composite particle over 200 redox cycles for hydrogen production by chemical looping, using multi-length scale X-ray computed tomography. We show that redox cycling triggers a centrifugal redispersion of the metal phase and a centripetal clustering of porosity, both seemingly driven by the asymmetric nature of oxygen exchange in composites. We show that initially the particle develops a large amount of internal porosity which boosts activity, but on the long term this facilitates structural and compositional reorganisation and eventually degradation. We also correlate the microstructural data with phase and activity analysis to identify structure-property correlations which not only provide valuable insight into the evolution of composite materials under redox conditions but also for the design of new composite materials with enhanced durability.
DOI: 10.25386/genetics.9733838
title: Supplemental Material for Rowan et al., 2019

description: Supplementary Material contains:<br>Tables S1 - S5Figures S1 - S15Files S1 - S5Supplemental Legends<br>
DOI: 10.25386/genetics.9733838.v1
title: Supplemental Material for Rowan et al., 2019

description: Supplementary Material contains:<br>Tables S1 - S5Figures S1 - S15Files S1 - S5Supplemental Legends<br>
DOI: 10.6084/m9.figshare.9786212.v4
title: Water Quality for Kanawha River WV

description: Data collection for three months (Jan-Mar, 2018) at three locations along the Kanawha River, WV
DOI: 10.25387/g3.8796686
title: Supplemental Material for Bellido et al., 2019

description: Excel Table with the raw results for characterization of FOAR segregants<br>
DOI: 10.25387/g3.8796686.v1
title: Supplemental Material for Bellido et al., 2019

description: Excel Table with the raw results for characterization of FOAR segregants<br>
DOI: 10.25573/data.9856769
title: Dataset: Modeling organic carbon accumulation rates and residence times in coastal vegetated ecosystems

description: Coastal vegetated 'blue carbon' ecosystems can store large quantities of organic carbon (OC) within their soils; however, the importance of these sinks for climate change mitigation depends on the OC accumulation rate (CAR) and residence time. Here we evaluate how two modeling approaches, a Bayesian age-depth model alone or in combination with a two-pool OC model, aid in our understanding of the timelines of OC within seagrass soils. Fitting these models to data from Posidonia oceanica soil cores, we show that age-depth models provided reasonable CAR estimates but resulted in a 22% higher estimation of OC burial rates when ephemeral rhizosphere OC was not subtracted. This illustrates the need to standardize CAR estimation to match the research target and time frames under consideration. Using a two-pool model in tandem with an age-depth model also yielded reasonable, albeit lower, CAR estimates with lower estimate uncertainty, which increased our ability to detect among-site differences and seascape-level trends. Moreover, the two-pool model provided several other useful soil OC diagnostics, including OC inputs, decay rates, and transit times. At our sites, soil OC decayed quite slowly both within fast-cycling (0.028 +/- 0.014 yr<sup>-1</sup>) and slow-cycling (0.0007 +/- 0.0003 yr<sup>-1</sup>) soil pools, resulting in OC taking between 146 and 825 yrs to transit the soil system. Further, an estimated 85% to 93% of OC inputs enter slow-cycling soil pools, with transit times ranging from 891 to 3115 yrs, substantiating the importance of P. oceanica soils as natural, long-term OC sinks.<br>
DOI: 10.25387/g3.7811978
title: Supplemental Material for Lee et al., 2019

description: <b>Suppl. File S1.</b> Information of genetic map with marker names, genotypes, map positions, and tag sequences and phenotypes for sex of all individuals<b>Suppl. File S2.</b> Re-scaffolding process and results by Chromonomer.<b>Suppl. File S3.</b> Gene list annotated in the sex-determining region<b> </b><b>Suppl. Data</b><b>Suppl. Table S1. </b>Summary of RACA scaffold realignment after anchoring.<b>Suppl. Table S2. </b>Statistics of anchoring the RACA scaffolds to the genetic map using Chromonomer.<b>Suppl. Table S3. </b>Number of genes annotated in LG-based scaffolds after anchoring process<b>Suppl. Table S4</b>. LOD scores of two additional sex markers<b>Suppl. Table S5</b>. Information of sex linked markers<b>Suppl. Fig. S1. </b>Annotation pipeline of LG-based scaffolds<b>Suppl. Fig. S2. </b>Relationship between the genetic map and the LG-based genome assembly in <i>Oryzias melastigma</i>.<b>Suppl. Fig. S3. </b>Comparison of sequences similarity between the LG-based scaffold in <i>Oryzias melastigma</i> and chromosomes in <i>Oryzias latipes</i><i></i>
DOI: 10.25387/g3.7811978.v1
title: Supplemental Material for Lee et al., 2019

description: <b>File S1 contains:</b><b>Suppl. Table 1. </b>Relationship between the reference-assisted chromosome assembly (RACA) and the integrated assembly in <i>Oryzias melastigma</i><br><b>Suppl. Table 2. </b>Number of genes annotated by linkage groups<b>Suppl. Table S3. </b>Sex-associated markers in the linkage groups based on the Kruskal-Wallis analysis (K*).<b></b><b>Suppl. Fig. 1. </b>Annotation pipeline of <i>Oryzias melastigma</i> genome<b>Suppl. Fig. 2. </b>Genetic map (cM) and the integrated genome assembly (Mp) in <i>Oryzias melastigma</i>. Bold markers represent anchors<b>Suppl. Fig. 3. </b>Comparison of homology between the integrated scaffold of <i>Oryzias melastigma</i> and chromosomes of <i>Oryzias latipes</i><i><br></i><b>File S2 contains:</b>Info tab-genotype, map positions, tag sequences of RAD-tagPhenotype tab- sex phenotype for individuals<br><i></i>
DOI: 10.6084/m9.figshare.9092045.v4
title: MicroArray_Deep_3layer_AE_512.h5

description: Three hidden layer trained autoencoder with 512 nodes on the micro-array transcriptomics data. <br>
DOI: 10.6084/m9.figshare.9092045.v5
title: deep_learning_transcriptomics

description: Three hidden layer trained autoencoder with 512 nodes on the micro-array transcriptomics data. <br>
DOI: 10.6084/m9.figshare.9092045.v6
title: Three layer deep autoencoder trained on the micro-array data with 512 nodes

description: Three hidden layer trained autoencoder with 512 nodes on the micro-array transcriptomics data. <br>
DOI: 10.6084/m9.figshare.9092045.v7
title: Three layer deep autoencoder

description: The file TrainedModelLRFCrp5512.h5 and RNAseq_3L512deepAE.h5 are three hidden layer trained autoencoder with 512 nodes on the micro-array and RNA seq transcriptomics data respectively. <br>
DOI: 10.6084/m9.figshare.9777947
title: Marsh Crick 030919.ppt

description: kevin Marsh Keynote<br>
DOI: 10.6084/m9.figshare.9777947.v1
title: Marsh Crick 030919.ppt

description: kevin Marsh Keynote<br>
DOI: 10.25387/g3.9785951.v1
title: Supplemental Material for Kasimatis et al., 2019

description: Mathematica notebook includes derivation of the model, analyses of equilibria, and analyses of stability.R code includes the recursion equation and simple simulation.SLiM code includes the full simulations.Output from the simulations are in Files S4 and S5
DOI: 10.25387/g3.9785951
title: Supplemental Material for Kasimatis et al., 2019

description: Mathematica notebook includes derivation of the model, analyses of equilibria, and analyses of stability.R code includes the recursion equation and simple simulation.SLiM code includes the full simulations.Output from the simulations are in Files S4 and S5
DOI: 10.6084/m9.figshare.3761562.v1234
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25387/g3.7998425.v2
title: Supplemental Material for Li et al., 2019

description: Supplementary figures and tables
DOI: 10.6084/m9.figshare.9876581.v1
title: Test

description: test test test
DOI: 10.6084/m9.figshare.3761562.v1235
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25387/g3.9835208.v1
title: Supplemental Material for Hamlin et al., 2019

description: Data associated with Hamlin et al. Raw PacBio reads for the three Candida strains are available at the NCBI short-read archive (SRA) under BioProject PRJNA533645. The phased diploid assemblies for the three oak strains are associated with the overall BioProject PRJNA543321. Individual GenBank accession numbers for primary contigs and haplotigs, respectively, for each strain are as follows: NCYC 4144: GCA_005890765.1 and GCA_005890695.1; NCYC 4145: GCA_005890775.1 and GCA_005890685.1; NCYC 4146: GCA_005890745.1 and GCA_005890705.1. Coordinates of haplotigs relative to their respective primary assembly are available in Files S10, S11, and S12. Annotations of positions of centromeres, telomeric repeats, confirmed LOH regions, assembly gaps, uncertain regions with unexpectedly low heterozygosity, and regions that were not polished by FALCON-Unzip are available for primary assemblies in Files S1, S2, and S3. Annotations of unpolished regions for alternative haplotig assemblies are provided in Files S4, S5 and S6. A full description of software version numbers for phased assembly is provided in File S7 and the configuration files used to run FALCON and FALCON-Unzip are provided in Files S8 and S9.<br><br>
DOI: 10.25387/g3.9835208
title: Supplemental Material for Hamlin et al., 2019

description: Data associated with Hamlin et al. Raw PacBio reads for the three Candida strains are available at the NCBI short-read archive (SRA) under BioProject PRJNA533645. The phased diploid assemblies for the three oak strains are associated with the overall BioProject PRJNA543321. Individual GenBank accession numbers for primary contigs and haplotigs, respectively, for each strain are as follows: NCYC 4144: GCA_005890765.1 and GCA_005890695.1; NCYC 4145: GCA_005890775.1 and GCA_005890685.1; NCYC 4146: GCA_005890745.1 and GCA_005890705.1. Coordinates of haplotigs relative to their respective primary assembly are available in Files S10, S11, and S12. Annotations of positions of centromeres, telomeric repeats, confirmed LOH regions, assembly gaps, uncertain regions with unexpectedly low heterozygosity, and regions that were not polished by FALCON-Unzip are available for primary assemblies in Files S1, S2, and S3. Annotations of unpolished regions for alternative haplotig assemblies are provided in Files S4, S5 and S6. A full description of software version numbers for phased assembly is provided in File S7 and the configuration files used to run FALCON and FALCON-Unzip are provided in Files S8 and S9.<br><br>
DOI: 10.6084/m9.figshare.3761562.v1236
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1237
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.9890825.v1
title: ThirdFileTest

description: Testing dat publish
DOI: 10.6084/m9.figshare.3761562.v1238
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.9890825
title: ThirdFileTest

description: Testing dat publish
DOI: 10.6084/m9.figshare.9890837
title: TheDarnTitle

description: Testing DIME publishing
DOI: 10.6084/m9.figshare.9890837.v1
title: TheDarnTitle

description: Testing DIME publishing
DOI: 10.6084/m9.figshare.9890840
title: TheDarnTitle

description: Testing DIME publishing
DOI: 10.6084/m9.figshare.9890840.v1
title: TheDarnTitle

description: Testing DIME publishing