cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11982540
title: The effects of phosphate on physiological responses and carbohydrate production in Ulva fasciata (Chlorophyta) from two populations

description: Bioproducts derived from <i>Ulva</i> species have received increasing attention in several biotechnological fields due to their economic potential and cosmopolitan distribution. This study assessed the influence of different phosphate concentrations (0, 2 and 4 µM PO<sub>4</sub><sup>3-</sup>) commonly found in eutrophic environments on carbohydrate production, growth rate, tissue phosphorus, phosphate uptake and photosynthetic response in <i>U. fasciata</i> from two distinct sites (Arraial do Cabo, an upwelling site, with cold and nutrient rich water, and Niterói / Rio de Janeiro – Brazil, a non-upwelling site). After fifteen days of the experiment, the carbohydrate content increased in both populations and in all treatments (<i>p</i> &lt; 0.05) at approximately 136 and 264 % for Arraial do Cabo and Niterói, respectively. In Arraial do Cabo individuals, the carbohydrate content was high in all treatments (71 % DW), while Niterói individuals cultivated in the highest phosphate concentration presented the lowest carbohydrate content (46 % DW). Individuals cultivated in the absence of phosphate (control) presented the lowest tissue P and a progressive decline in the maximum quantum yield (Fv/Fm) over the experimental period (<i>p</i> &lt; 0.05). Altogether, the results indicate that phosphate concentrations in the culture medium influenced the carbohydrate content of <i>U. fasciata</i> and that populations from sites with broad environmental variations can present higher productivity.
DOI: 10.6084/m9.figshare.11982522
title: S3: Granite with three-point (air – Cu – W) calibration

description: 3D Mineral texture quantification method<br>
DOI: 10.6084/m9.figshare.11982540.v2
title: The effects of phosphate on physiological responses and carbohydrate production in Ulva fasciata (Chlorophyta) from two populations

description: Bioproducts derived from <i>Ulva</i> species have received increasing attention in several biotechnological fields due to their economic potential and cosmopolitan distribution. This study assessed the influence of different phosphate concentrations (0, 2 and 4 µM PO<sub>4</sub><sup>3-</sup>) commonly found in eutrophic environments on carbohydrate production, growth rate, tissue phosphorus, phosphate uptake and photosynthetic response in <i>U. fasciata</i> from two distinct sites (Arraial do Cabo, an upwelling site, with cold and nutrient rich water, and Niterói / Rio de Janeiro – Brazil, a non-upwelling site). After fifteen days of the experiment, the carbohydrate content increased in both populations and in all treatments (<i>p</i> &lt; 0.05) at approximately 136 and 264 % for Arraial do Cabo and Niterói, respectively. In Arraial do Cabo individuals, the carbohydrate content was high in all treatments (71 % DW), while Niterói individuals cultivated in the highest phosphate concentration presented the lowest carbohydrate content (46 % DW). Individuals cultivated in the absence of phosphate (control) presented the lowest tissue P and a progressive decline in the maximum quantum yield (Fv/Fm) over the experimental period (<i>p</i> &lt; 0.05). Altogether, the results indicate that phosphate concentrations in the culture medium influenced the carbohydrate content of <i>U. fasciata</i> and that populations from sites with broad environmental variations can present higher productivity.
DOI: 10.6084/m9.figshare.11982522.v1
title: S3: Granite with three-point (air – Cu – W) calibration

description: 3D Mineral texture quantification method<br>
DOI: 10.6084/m9.figshare.11982540.v1
title: The effects of phosphate on physiological responses and carbohydrate production in Ulva fasciata (Chlorophyta) from two populations

description: Bioproducts derived from <i>Ulva</i> species have received increasing attention in several biotechnological fields due to their economic potential and cosmopolitan distribution. This study assessed the influence of different phosphate concentrations (0, 2 and 4 µM PO<sub>4</sub><sup>3-</sup>) commonly found in eutrophic environments on carbohydrate production, growth rate, tissue phosphorus, phosphate uptake and photosynthetic response in <i>U. fasciata</i> from two distinct sites (Arraial do Cabo, an upwelling site, with cold and nutrient rich water, and Niterói / Rio de Janeiro – Brazil, a non-upwelling site). After fifteen days of the experiment, the carbohydrate content increased in both populations and in all treatments (<i>p</i> &lt; 0.05) at approximately 136 and 264 % for Arraial do Cabo and Niterói, respectively. In Arraial do Cabo individuals, the carbohydrate content was high in all treatments (71 % DW), while Niterói individuals cultivated in the highest phosphate concentration presented the lowest carbohydrate content (46 % DW). Individuals cultivated in the absence of phosphate (control) presented the lowest tissue P and a progressive decline in the maximum quantum yield (Fv/Fm) over the experimental period (<i>p</i> &lt; 0.05). Altogether, the results indicate that phosphate concentrations in the culture medium influenced the carbohydrate content of <i>U. fasciata</i> and that populations from sites with broad environmental variations can present higher productivity.
DOI: 10.6084/m9.figshare.11982474
title: Data Set for "The Political Economy of Solar Initiatives in the Sunshine state"

description: Data set for: <br><br>Khurana, Ritika, Levan Elbakidze, and Joshua Hall. "The political economy of solar initiatives in the Sunshine state." <i>Applied Economics Letters</i> (2020): 1-4.<br>DOI: https://doi.org/10.1080/13504851.2020.1771269<br>
DOI: 10.6084/m9.figshare.11982471
title: How do social status and tree architecture influence radial growth, wood density and drought response in spontaneously established oak forests?

description: The dataset comprises raw data used in the paper: Alfaro-Sánchez et al. 2020. How do social status and tree architecture influence radial growth, wood density and drought response in spontaneously established oak forests?It includes the coordinates and tree density of the stands and the number of stems, diameter, total height, wood density, raw growth and basal area increments of the sample trees.<br>
DOI: 10.6084/m9.figshare.11982396
title: Table S5 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Table showing the results from the LEfSe analysis including Linear discriminant analysis (LDA) scores, P-values adjusted for multiple testing, and False Discovery Rate (FDR) values. Normalized read abundance values (the input for the analysis) for each host species are also given.
DOI: 10.6084/m9.figshare.11982474.v2
title: Data Set for "The Political Economy of Solar Initiatives in the Sunshine state"

description: Data set for: <br><br>Khurana, Ritika, Levan Elbakidze, and Joshua Hall. "The political economy of solar initiatives in the Sunshine state." <i>Applied Economics Letters</i> (2020): 1-4.<br>DOI: https://doi.org/10.1080/13504851.2020.1771269<br>
DOI: 10.6084/m9.figshare.11982393
title: Table S3 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Table summarizing metadata for each host species and sample (sample_ID) used in this study. Includes various details about the host (e.g., weight, length, gut length, etc.) and the associated microbiome (e.g., number of reads, diversity stats, etc). Rows correspond to sample ID and columns correspond to various traits for each sample.
DOI: 10.6084/m9.figshare.11982396.v1
title: Table S5 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Table showing the results from the LEfSe analysis including Linear discriminant analysis (LDA) scores, P-values adjusted for multiple testing, and False Discovery Rate (FDR) values. Normalized read abundance values (the input for the analysis) for each host species are also given.
DOI: 10.6084/m9.figshare.11982474.v1
title: SolarVote.xlsx

description: Data set for paper "The Political Economy of Solar Initiatives in the Sunshine State"
DOI: 10.6084/m9.figshare.11982387
title: Table S2 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Summary data from observations of individual bites by five species of herbivorous fishes in the Florida Keys. Data include the mean sediment depth and turf height of algal assemblages fed on by each species at each of three sites, as well as the proportion of bites that resulted in a grazing scar on the substrate where reef calcium carbonate had been removed (Prop. grazing scar). The table summarizes the proportion of bites on vertical (&gt; 45 degrees), concave, and convex substrates as well as the relative proportion of bites targeting each of the 10 food types most commonly bitten during the observations. Most macroalgae were aggregated to genus while other food types are summarized by functional group.
DOI: 10.6084/m9.figshare.11982390
title: Table S4 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Table showing Class-level taxonomic diversity of the total microbiome dataset. Data shows the total number of reads and total number of ASVs for each Class plus the relative percent of each in the dataset.
DOI: 10.6084/m9.figshare.11982393.v1
title: Table S3 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Table summarizing metadata for each host species and sample (sample_ID) used in this study. Includes various details about the host (e.g., weight, length, gut length, etc.) and the associated microbiome (e.g., number of reads, diversity stats, etc). Rows correspond to sample ID and columns correspond to various traits for each sample.
DOI: 10.6084/m9.figshare.11982384
title: Table S6 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Full summary table of BLAST analysis for each of the 59 differentially abundant (DA) ASV. The table includes some details about each ASV (e.g., total reads), details of top BLAST hit(s), and alignment results. The table also includes results from queries to the IMNGS database.
DOI: 10.6084/m9.figshare.11982384.v1
title: Table S6 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Full summary table of BLAST analysis for each of the 59 differentially abundant (DA) ASV. The table includes some details about each ASV (e.g., total reads), details of top BLAST hit(s), and alignment results. The table also includes results from queries to the IMNGS database.
DOI: 10.6084/m9.figshare.11982387.v1
title: Table S2 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Summary data from observations of individual bites by five species of herbivorous fishes in the Florida Keys. Data include the mean sediment depth and turf height of algal assemblages fed on by each species at each of three sites, as well as the proportion of bites that resulted in a grazing scar on the substrate where reef calcium carbonate had been removed (Prop. grazing scar). The table summarizes the proportion of bites on vertical (&gt; 45 degrees), concave, and convex substrates as well as the relative proportion of bites targeting each of the 10 food types most commonly bitten during the observations. Most macroalgae were aggregated to genus while other food types are summarized by functional group.
DOI: 10.6084/m9.figshare.11982390.v1
title: Table S4 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: Table showing Class-level taxonomic diversity of the total microbiome dataset. Data shows the total number of reads and total number of ASVs for each Class plus the relative percent of each in the dataset.
DOI: 10.6084/m9.figshare.11982378
title: Table S7 from Intestinal microbes: an axis of functional diversity among large marine consumers

description: This table provides lookup details for all neighbor sequences from BLAST and SILVA-ACT comparisons used in the tree from Figure 3 (main paper). In the tree, sequences are named after the isolation source (e.g., <i>Naso unicornis</i>) plus a unique abbreviated code. This table gives the full accession numbers for each leaf.
DOI: 10.6084/m9.figshare.11982207
title: Snow_Algae_shapefile.zip

description: Polygons outlining green snow algae blooms across the Antarctic Peninsula. Average and standard deviation of biomass within the polygon area given for each bloom in attribute table. Blooms identified and algal biomass estimated derived from Sentinel 2 imagery.
DOI: 10.6084/m9.figshare.11982225
title: IB4

description: C1: IB4 (scaled area integral of Band 4 relative to the continuum reflectance between Bands 3 and 5) taken from Sentinel 2-convolved hyperspectral HDRF of green snow algae. C2: Cell density of corresponding FOV on snow in cells per mL.
DOI: 10.6084/m9.figshare.11982156
title: Additional file 1 of Individualized coracoid osteotomy and 3D congruent arc reconstruction of glenoid for the treatment of recurrent anterior shoulder dislocation

description: Supplementary material video (from preoperative virtual design to postoperative real images, 3D dynamic display of congruent arc glenoid reconstruction. (VOB 146 mb)
DOI: 10.6084/m9.figshare.11982156.v1
title: Additional file 1 of Individualized coracoid osteotomy and 3D congruent arc reconstruction of glenoid for the treatment of recurrent anterior shoulder dislocation

description: Supplementary material video (from preoperative virtual design to postoperative real images, 3D dynamic display of congruent arc glenoid reconstruction. (VOB 146 mb)
DOI: 10.6084/m9.figshare.11982123
title: Additional file 7 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 7. S7a Time tree methods and caption to additional file (Time tree).S7b. Figure demonstrating the time tree, with estimated dates of divergence indicated.
DOI: 10.6084/m9.figshare.11982129
title: Additional file 9 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 9. Python script to compare variants between different isolates or groups of isolates, developed by Dr. R.G. van der Merwe.
DOI: 10.6084/m9.figshare.11982123.v1
title: Additional file 7 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 7. S7a Time tree methods and caption to additional file (Time tree).S7b. Figure demonstrating the time tree, with estimated dates of divergence indicated.
DOI: 10.6084/m9.figshare.11982129.v1
title: Additional file 9 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 9. Python script to compare variants between different isolates or groups of isolates, developed by Dr. R.G. van der Merwe.
DOI: 10.6084/m9.figshare.11982114
title: Additional file 4 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 4. AA1SA defining variants. Each variant listed occurs in all investigated AA1SA isolates, but not in any other strain investigated in this study.
DOI: 10.6084/m9.figshare.11982120
title: Additional file 6 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 6. Number of isolates with underlying (read frequency
DOI: 10.6084/m9.figshare.11982114.v1
title: Additional file 4 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 4. AA1SA defining variants. Each variant listed occurs in all investigated AA1SA isolates, but not in any other strain investigated in this study.
DOI: 10.6084/m9.figshare.11982120.v1
title: Additional file 6 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 6. Number of isolates with underlying (read frequency
DOI: 10.6084/m9.figshare.11982108
title: Additional file 2 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 2. Detailed record of sequencing metrics as well as sampling date, origin and genotypic classification for each isolate.
DOI: 10.6084/m9.figshare.11982111
title: Additional file 3 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 3. SNP distance matrix. Each cell represents the number of single nucleotide differences between two isolates, as indicated in the column header and leading column.
DOI: 10.6084/m9.figshare.11982105
title: Additional file 1 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 1. Genes observed in this study to carry drug resistance conferring mutations.
DOI: 10.6084/m9.figshare.11982111.v1
title: Additional file 3 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 3. SNP distance matrix. Each cell represents the number of single nucleotide differences between two isolates, as indicated in the column header and leading column.
DOI: 10.6084/m9.figshare.11982105.v1
title: Additional file 1 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 1. Genes observed in this study to carry drug resistance conferring mutations.
DOI: 10.6084/m9.figshare.11982108.v1
title: Additional file 2 of A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

description: Additional file 2. Detailed record of sequencing metrics as well as sampling date, origin and genotypic classification for each isolate.
DOI: 10.6084/m9.figshare.11981889
title: Additional file 6 of Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015

description: Sensitivity Analysis of Limits of Detection (LOD) for Imidacloprid. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.11981889.v1
title: Additional file 6 of Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015

description: Sensitivity Analysis of Limits of Detection (LOD) for Imidacloprid. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.11981880
title: Additional file 3 of Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015

description: Summary of Neonicotinoid Concentrations by CommodHybrid Groups, 1999 - 2015 (XLSX 45 kb)
DOI: 10.6084/m9.figshare.11981877
title: Additional file 2 of Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015

description: LODs by Major Commodity, 1999–2015 (XLSX 134 kb)
DOI: 10.6084/m9.figshare.11981880.v1
title: Additional file 3 of Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015

description: Summary of Neonicotinoid Concentrations by CommodHybrid Groups, 1999 - 2015 (XLSX 45 kb)
DOI: 10.6084/m9.figshare.11981877.v1
title: Additional file 2 of Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015

description: LODs by Major Commodity, 1999–2015 (XLSX 134 kb)
DOI: 10.6084/m9.figshare.11981736
title: Additional file 9 of Some data quality issues at ClinicalTrials.gov

description: Records with a primary completion date and registered with an authority in the USA. The data (5101 records from Additional file 7: Table S5) were sorted into a “USA_PriComplDate” sheet for trials registered with at least one authority in the US, and a “USA_PriComplDate_leftovers” sheet with the remaining records. The data are presented in the following six Recruitment Type categories: (1) Active, not recruiting (1085 selected records with 135 leftovers), (2) Completed (1100; 940), (3) Enrolling by invitation (19; 23), (4) Recruiting (773; 609), (5) Suspended (59; 32), and (6) Terminated (252; 74). The sheets for these categories are numbered 1–6, respectively. (XLS 493 kb)
DOI: 10.6084/m9.figshare.11981730
title: Additional file 7 of Some data quality issues at ClinicalTrials.gov

description: Records with a primary completion date. The data (58,685 records from Additional file 6: Table S4) were sorted into a “PriComplDate” sheet for trials with primary completion dates, with the remaining records in a “PriComplDate_leftovers” sheet. The data are presented in the following six Recruitment Type categories: (1) Active, not recruiting (1220 selected records with 51 leftovers), (2) Completed (2040; 414), (3) Enrolling by invitation (42; 3), (4) Recruiting (1382; 164), (5) Suspended (91; 15), and (6) Terminated (326; 63). The sheets for these categories are numbered 1–6, respectively. (XLS 7227 kb)
DOI: 10.6084/m9.figshare.11981733
title: Additional file 8 of Some data quality issues at ClinicalTrials.gov

description: Records with a completion date and registered with an authority in the USA. The data (58,685 records from Additional file 6: Table S4) were sorted into a “USA_ComplDate” sheet for trials registered with at least one authority in the US, and a “USA_ComplDate_leftovers” sheet with the remaining records. The data are presented in the following six Recruitment Type categories: (1) Active, not recruiting (3350 selected records with 2121 leftovers), (2) Completed (21,030; 17,967), (3) Enrolling by invitation (166; 175), (4) Recruiting (3167; 4666), (5) Suspended (134; 99), and (6) Terminated (3986; 1824). The sheets for these categories are numbered 1–6, respectively. (XLS 6129 kb)
DOI: 10.6084/m9.figshare.11981736.v1
title: Additional file 9 of Some data quality issues at ClinicalTrials.gov

description: Records with a primary completion date and registered with an authority in the USA. The data (5101 records from Additional file 7: Table S5) were sorted into a “USA_PriComplDate” sheet for trials registered with at least one authority in the US, and a “USA_PriComplDate_leftovers” sheet with the remaining records. The data are presented in the following six Recruitment Type categories: (1) Active, not recruiting (1085 selected records with 135 leftovers), (2) Completed (1100; 940), (3) Enrolling by invitation (19; 23), (4) Recruiting (773; 609), (5) Suspended (59; 32), and (6) Terminated (252; 74). The sheets for these categories are numbered 1–6, respectively. (XLS 493 kb)
DOI: 10.6084/m9.figshare.11981727
title: Additional file 6 of Some data quality issues at ClinicalTrials.gov

description: Records with a completion date. The data (64,496 records from Additional file 5: Table S3) were sorted into a “ComplDate” sheet for trials with completion dates, with the remaining records in a “ComplDate_leftovers” sheet. The data are presented in the following six Recruitment Type categories: (1) Active, not recruiting (5471 selected records with 1271 leftovers), (2) Completed (38,997; 2454), (3) Enrolling by invitation (341; 45), (4) Recruiting (7833; 1546), (5) Suspended (233; 106), and (6) Terminated (5810; 389). The sheets for these categories are numbered 1–6, respectively. The file is available at https://osf.io/jcb92 . (ODS 2300 kb)
DOI: 10.6084/m9.figshare.11981730.v1
title: Additional file 7 of Some data quality issues at ClinicalTrials.gov

description: Records with a primary completion date. The data (58,685 records from Additional file 6: Table S4) were sorted into a “PriComplDate” sheet for trials with primary completion dates, with the remaining records in a “PriComplDate_leftovers” sheet. The data are presented in the following six Recruitment Type categories: (1) Active, not recruiting (1220 selected records with 51 leftovers), (2) Completed (2040; 414), (3) Enrolling by invitation (42; 3), (4) Recruiting (1382; 164), (5) Suspended (91; 15), and (6) Terminated (326; 63). The sheets for these categories are numbered 1–6, respectively. (XLS 7227 kb)