cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/21564756.v1
title: Supplementary Dataset 1 from the paper "Highly differentiated genomic properties underpin the different cell walls of Poaceae and eudicots"

description: Cell wall synteny network of 169 angiosperm genomes <br> The dataset reports the network depicting the syntenic relationships between all cell wall genes from 149 different gene families, across 169 genomes representing the evolutionary diversity of angiosperms. The dataset has six total columns: the first two columns report the direct syntenic relationships between pairs of cell wall genes, while the remaining columns report the broad biological process and specific function of each gene from the first two columns, in the context of cell wall biology/biosynthesis. The network was created following the methodology described in the paper "Highly differentiated genomic properties underpin the different cell walls of Poaceae and eudicots", by Pancaldi et al. (which is currently under peer review; once the review process is finishes, the resource title and DOI will be added).
DOI: 10.4121/21896757
title: Supplementary Dataset 1 from the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species"

description: This dataset reports all the genetic polymorphisms (SNPs/INDELs) that were detected in all the genes included in the syntenic quantitative trait loci (SQTLs) for which intra-specific genomic diversity was studied by SQTLs alignment across genomes representing different plant accessions in the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species" (currently under peer review; resource title and DOI will be added once the paper is published). <br> The methodology followed for polymorphisms identification is detailly reported in the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species". In brief, SQTL nucleotide sequences were aligned by NUCmer against diverse genomic assemblies from different accessions of six plant species (reported in the dataset). NUCmer outputs report SNPs and INDELs positions along SQTLs, whose data were used to infer changes in translated protein sequences in SQTL genes. <br> Overall, the dataset contains 19 columns: - 1: SQTL ID - 2: The target chromosome over which SQTL produced alignment with NUCmer - 3: Gene ID for which SNPs/INDELs were reported (each row represents one gene from a SQTL) - 4-5: Process and function of a gene in the context of cell wall biosynthesis/biology (in the case a gene is a cell wall gene) - 6-7: The protein sequence and its length as coded by the gene sequence of the reference SQTLs - 8-9: The protein sequence and its length as coded by the gene sequence of the target chromosome against which SQTL produced alignment - 10-11: The number of SNPs and INDELs detected in the alignment of each gene - 12-15: Position and sequence effect of SNPs and INDELs in terms of stop codons (columns 12-13) and point/short amino acid changes (columns 14-15); - 16-19: General information on the assembly, species, and protein's first amino acid for each gene in alignment. <br> <br>
DOI: 10.4121/21896757.v1
title: Supplementary Dataset 1 from the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species"

description: This dataset reports all the genetic polymorphisms (SNPs/INDELs) that were detected in all the genes included in the syntenic quantitative trait loci (SQTLs) for which intra-specific genomic diversity was studied by SQTLs alignment across genomes representing different plant accessions in the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species" (currently under peer review; resource title and DOI will be added once the paper is published). <br> The methodology followed for polymorphisms identification is detailly reported in the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species". In brief, SQTL nucleotide sequences were aligned by NUCmer against diverse genomic assemblies from different accessions of six plant species (reported in the dataset). NUCmer outputs report SNPs and INDELs positions along SQTLs, whose data were used to infer changes in translated protein sequences in SQTL genes. <br> Overall, the dataset contains 19 columns: - 1: SQTL ID - 2: The target chromosome over which SQTL produced alignment with NUCmer - 3: Gene ID for which SNPs/INDELs were reported (each row represents one gene from a SQTL) - 4-5: Process and function of a gene in the context of cell wall biosynthesis/biology (in the case a gene is a cell wall gene) - 6-7: The protein sequence and its length as coded by the gene sequence of the reference SQTLs - 8-9: The protein sequence and its length as coded by the gene sequence of the target chromosome against which SQTL produced alignment - 10-11: The number of SNPs and INDELs detected in the alignment of each gene - 12-15: Position and sequence effect of SNPs and INDELs in terms of stop codons (columns 12-13) and point/short amino acid changes (columns 14-15); - 16-19: General information on the assembly, species, and protein's first amino acid for each gene in alignment. <br> <br>
DOI: 10.4121/22068593.v1
title: Supplementary Dataset 2 from the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species"

description: This dataset contains 100 sets of 91 random QTL regions from the genome of Miscanthus sinensis that mirror the basepair size distribution of 91 QTLs that were found in Miscanthus sinensis through genome-wide association analysis (GWAS) for multiple traits related to biomass (cell wall) quality. The 100 sets of random QTL regions were used in the publication attached to this dataset to perform a permutation analysis to test for co-localization between a set of syntenic QTLs for cell wall quality previously mapped in Miscanthus and the QTLs detected by GWAS (see above). The 100 sets of random QTL regions have been produced in R, by applying the size distribution of GWAS QTLs as constraint for determining the size of random QTLs. Random QTLs could be picked across the whole miscanthus genome, to ensure complete randomness.
DOI: 10.4121/22068593
title: Supplementary Dataset 2 from the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species"

description: This dataset contains 100 sets of 91 random QTL regions from the genome of Miscanthus sinensis that mirror the basepair size distribution of 91 QTLs that were found in Miscanthus sinensis through genome-wide association analysis (GWAS) for multiple traits related to biomass (cell wall) quality. The 100 sets of random QTL regions were used in the publication attached to this dataset to perform a permutation analysis to test for co-localization between a set of syntenic QTLs for cell wall quality previously mapped in Miscanthus and the QTLs detected by GWAS (see above). The 100 sets of random QTL regions have been produced in R, by applying the size distribution of GWAS QTLs as constraint for determining the size of random QTLs. Random QTLs could be picked across the whole miscanthus genome, to ensure complete randomness.
DOI: 10.4121/22009211
title: Previously unpublished water adsorption isotherm data related to the publication: Confined water cluster formation in water harvesting by metal organic frameworks: CAU-10-H versus CAU-10-CH₃

description: Previously unpublished water adsorption isotherm related to the publication: “Confined water cluster formation in water harvesting by metal organic frameworks: CAU-10-H versus CAU-10-CH₃” by van der Veen et al. in Advanced Materials 2023, https://doi.org/10.1002/adma.202210050 . The numbering of the samples (e.g. 1. BioMOF(Ba)) refers to the position of the sample in Table S7 in the supporting information of the publication. All the samples were activated before the sorption measurement. Details of the measurement follow here. The .csv files related to each measurements contain three colums: Relative Pressure (p/pø); Absolute Pressure (mmHg);Quantity Adsorbed (mmol/g). pø refers to the saturation pressure of water at the temperature of the measurement.
DOI: 10.4121/22068791.v1
title: Supplementary Dataset 2 from the paper "Highly differentiated genomic properties underpin the different cell walls of Poaceae and eudicots"

description: This dataset reports the annotation of tandem gene clusters for the cell wall genes belonging to 150 different gene families, across 169 angiosperm genomes covering basal angiosperms, non-commelinid monocots, Poaceae, and eudicots. The dataset was created by analysing the relative genomic position of each cell wall gene to other cell wall genes belonging to each function analysed, in the genome of each species. Data structure and other information can be viewed in the README file.
DOI: 10.4121/21985172
title: Data underlying the publication: Advanced ceramics in radical filtration: TiO2 layer thickness effect on the photocatalytic membrane performance

description: Membranes with advanced oxidation processes (AOPs) are a promising combination to separate and degrade organic pollutants in a single system. In this work, we describe the fabrication and characteristics of nine membranes with different TiO2 top layer thicknesses (from 0.26 to 21.9 μm), giving attention to the critical catalyst thickness and the formation of defects. We also report the optimum photocatalyst thickness for our single-layer membranes (∼2.74 μm), after which more titanium dioxide does not improve the degradation. However, an increase in degradation for membranes with multiple TiO2 layers was still possible. These results and the comparisons with the literature suggested that the optimal catalyst thickness is closely related to the material morphology. We obtained a maximum degradation at the lower filtration rate (1.6 L m−2 h−1) of 72% with a single layer membrane of 3.4 μm and 82% with a membrane with six layers of 21.9 μm. Furthermore, a 1D mass transport and reaction model that describes the coating thickness effect was developed and fitted with the experimental data. Other parameters are also discussed, such as light penetration limitations, surface area, and surface reaction rate constant. These results and analysis provide a better understanding of the fabrication and optimization of photocatalytic membranes.
DOI: 10.4121/21985172.v1
title: Data underlying the publication: Advanced ceramics in radical filtration: TiO2 layer thickness effect on the photocatalytic membrane performance

description: Membranes with advanced oxidation processes (AOPs) are a promising combination to separate and degrade organic pollutants in a single system. In this work, we describe the fabrication and characteristics of nine membranes with different TiO2 top layer thicknesses (from 0.26 to 21.9 μm), giving attention to the critical catalyst thickness and the formation of defects. We also report the optimum photocatalyst thickness for our single-layer membranes (∼2.74 μm), after which more titanium dioxide does not improve the degradation. However, an increase in degradation for membranes with multiple TiO2 layers was still possible. These results and the comparisons with the literature suggested that the optimal catalyst thickness is closely related to the material morphology. We obtained a maximum degradation at the lower filtration rate (1.6 L m−2 h−1) of 72% with a single layer membrane of 3.4 μm and 82% with a membrane with six layers of 21.9 μm. Furthermore, a 1D mass transport and reaction model that describes the coating thickness effect was developed and fitted with the experimental data. Other parameters are also discussed, such as light penetration limitations, surface area, and surface reaction rate constant. These results and analysis provide a better understanding of the fabrication and optimization of photocatalytic membranes.
DOI: 10.4121/21750611
title: Additional data for the paper: Free-Space Diffused Light Collimation and Concentration

description: We are providing raw data and calculation files for the paper: <strong>Free-Space Diffused Light Collimation and Concentration.</strong> The files contain additional simulation results and explanations thereof. Furthermore, spectro-angular emission raw data as well as UV-spectroscopy data is included. Finally, calculation files are also included.
DOI: 10.6084/m9.figshare.22010849
title: ECOPICS_Mx Monolith aggregate stability

description: Aggregate stability by mechanical breakdown by shaking after pre-wetting. Aggregate stability was determined on soil samples taken at 0.15 m depth without mulch. Five grams of aggregates (3.35 - 5 mm; of diameter) were gently immersed in 50 mL of ethanol for 10 minutes; ethanol was then removed gently with a pipette and the soil material was transferred gently to an 250mL Erlenmeyer flask with 50 mL deionized water and made up to 200mL, they were subjected to 20 cycles of 1 turn / second of movements, emulating the yoder apparatus; the soil material was allowed settle for 30 minutes; water was then extracted with a pipette and the soil material was rewet with 70% ethanol immersing the aggregates in a 50 micron sieve. The 50 micron sieve was gently moved five times to separate fragments &lt; 50 µm; the &gt;50 µm fraction was collected, allowed to aerate at room temperature and constant humidity (25 ° C ± 5 ° C; 25% ± 5%) for 24 hours then gently sieved by hand in a 6-size column (2000, 1000, 500, 200, 100 and 50 µm. The mass percentage of each size fraction was calculated, and the aggregate stability was expressed by computation of mean weight diameter (MWD) calculated as follows: MWD= ∑d * , where d is the mean diameter between to sieves (mm) and m the mass fraction (%) remaining in the sieve. The tests were performed on each soil sample per target species -<em>Pinus hartwegii Lupinus montanus Oxylobus arbutifolius-</em> (subdivided in three methodological replicates).
DOI: 10.6084/m9.figshare.22010849.v3
title: ECOPICS_Mx Monolith aggregate stability

description: Aggregate stability by mechanical breakdown by shaking after pre-wetting. Aggregate stability was determined on soil samples taken at 0.15 m depth without mulch. Five grams of aggregates (3.35 - 5 mm; of diameter) were gently immersed in 50 mL of ethanol for 10 minutes; ethanol was then removed gently with a pipette and the soil material was transferred gently to an 250mL Erlenmeyer flask with 50 mL deionized water and made up to 200mL, they were subjected to 20 cycles of 1 turn / second of movements, emulating the yoder apparatus; the soil material was allowed settle for 30 minutes; water was then extracted with a pipette and the soil material was rewet with 70% ethanol immersing the aggregates in a 50 micron sieve. The 50 micron sieve was gently moved five times to separate fragments &lt; 50 µm; the &gt;50 µm fraction was collected, allowed to aerate at room temperature and constant humidity (25 ° C ± 5 ° C; 25% ± 5%) for 24 hours then gently sieved by hand in a 6-size column (2000, 1000, 500, 200, 100 and 50 µm. The mass percentage of each size fraction was calculated, and the aggregate stability was expressed by computation of mean weight diameter (MWD) calculated as follows: MWD= ∑d * , where d is the mean diameter between to sieves (mm) and m the mass fraction (%) remaining in the sieve. The tests were performed on each soil sample per target species -<em>Pinus hartwegii Lupinus montanus Oxylobus arbutifolius-</em> (subdivided in three methodological replicates).
DOI: 10.6084/m9.figshare.22010849.v2
title: ECOPICS_Mx Monolith aggregate stability

description: Aggregate stability by mechanical breakdown by shaking after pre-wetting. Aggregate stability was determined on soil samples taken at 0.15 m depth without mulch. Five grams of aggregates (3.35 - 5 mm; of diameter) were gently immersed in 50 mL of ethanol for 10 minutes; ethanol was then removed gently with a pipette and the soil material was transferred gently to an 250mL Erlenmeyer flask with 50 mL deionized water and made up to 200mL, they were subjected to 20 cycles of 1 turn / second of movements, emulating the yoder apparatus; the soil material was allowed settle for 30 minutes; water was then extracted with a pipette and the soil material was rewet with 70% ethanol immersing the aggregates in a 50 micron sieve. The 50 micron sieve was gently moved five times to separate fragments &lt; 50 µm; the &gt;50 µm fraction was collected, allowed to aerate at room temperature and constant humidity (25 ° C ± 5 ° C; 25% ± 5%) for 24 hours then gently sieved by hand in a 6-size column (2000, 1000, 500, 200, 100 and 50 µm. The mass percentage of each size fraction was calculated, and the aggregate stability was expressed by computation of mean weight diameter (MWD) calculated as follows: MWD= ∑d * , where d is the mean diameter between to sieves (mm) and m the mass fraction (%) remaining in the sieve. The tests were performed on each soil sample per target species -<em>Pinus hartwegii Lupinus montanus Oxylobus arbutifolius-</em> (subdivided in three methodological replicates).
DOI: 10.18746/bmth.data.00000298
title: Kearn, O., Welham, K., Pitman, D., Brisbane, M. and Clews, S., 2023. The research data for the PhD Project Building Roman Britons: The Use of Novel Construction Materials in the Development of Roman Bath.
DOI: 10.6084/m9.figshare.22057160
title: ECOPICS_Mx Monolith earthworms

description: ECOPICS Project : Earthworm Survey 0.25 x 0.25 x 0.15m soil monolith. Field campaign October-November 2017 Last modification : May 2021 by Isabelle Barois Each soil monolith was hand sorted in the field to collect earthworms. Earthworm survey was done by Isabelle Barois and José Carlos Pimentel. Each monolith has a unique name made of : <strong>Altitudinal</strong> <strong>level</strong> : from 3400 to 4400 (every 200 m) <strong>Plot</strong> <strong>Number</strong> : from 1 to 30 <strong>Species</strong> <strong>names</strong>: Tree, <em>Pinus hartwegii</em>; Shrub,<em>Oxylobus arbutifolius/Chianolaena</em> <em>lavandulifolia</em> and; herb, <em>Lupinus monticola/Senecio roseus</em>. Morphological identification (Species level) by Carlos Fragoso, 2018 in Red de Ecología Funcional, INECOL, A.C., Xalapa. --------------------------------------------------------------------------------------------------------------------------------------------------- <em>0.25 x 0.25x 0.15m Earthworm survey sheet</em> : Contains the raw data : <strong>Earthworm density</strong> : number of individuals of each species in each monolith (ind/monolith) <strong>Earthworm biomass </strong>: mass of each species in each monolith (g/monolith) fixed in alcohol
DOI: 10.6084/m9.figshare.22057160.v1
title: ECOPICS_Mx Monolith earthworms

description: ECOPICS Project : Earthworm Survey 0.25 x 0.25 x 0.15m soil monolith. Field campaign October-November 2017 Last modification : May 2021 by Isabelle Barois Each soil monolith was hand sorted in the field to collect earthworms. Earthworm survey was done by Isabelle Barois and José Carlos Pimentel. Each monolith has a unique name made of : <strong>Altitudinal</strong> <strong>level</strong> : from 3400 to 4400 (every 200 m) <strong>Plot</strong> <strong>Number</strong> : from 1 to 30 <strong>Species</strong> <strong>names</strong>: Tree, <em>Pinus hartwegii</em>; Shrub,<em>Oxylobus arbutifolius/Chianolaena</em> <em>lavandulifolia</em> and; herb, <em>Lupinus monticola/Senecio roseus</em>. Morphological identification (Species level) by Carlos Fragoso, 2018 in Red de Ecología Funcional, INECOL, A.C., Xalapa. --------------------------------------------------------------------------------------------------------------------------------------------------- <em>0.25 x 0.25x 0.15m Earthworm survey sheet</em> : Contains the raw data : <strong>Earthworm density</strong> : number of individuals of each species in each monolith (ind/monolith) <strong>Earthworm biomass </strong>: mass of each species in each monolith (g/monolith) fixed in alcohol
DOI: 10.57906/rc8j-mh33
title: COVID-19 COG-UK Viral Genome - England
DOI: 10.17632/f7m6495v55.1
title: CNIR_DMD-optofMRI

description: Original codes and sample data from Kim et al. 2023, Neuron, "Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics" (In press). The procedure described here is for generating subject-specific optogenetic stimulus pattern based on Allen mouse brain atlas  (https://atlas.brain-map.org/), by coregistration between the Atlas, brain structural MR image and optical fluorescence image from a mouse. The generated patterns are transferred to a digital micromirror device (DMD) and then projected onto a thinned-skull-prepared mouse brain.
DOI: 10.17632/djyp3d9mkc.1
title: Data for: Collective asset sharing mechanisms for PV and BESS in renewable energy communities

description: Data set to model the renewable energy community with collective asset sharing.

1. Input data of asset characteristics. Includes all the needed characteristics related to PV and battery energy storage systems.
2. Input data of prices and tariffs.
3. Input data of collective PV systems generation. Includes data for several scenarios for a year.
4. Input data of agents' load profile. Includes the power consumer and the PV generation for a year.
DOI: 10.17632/djyp3d9mkc.2
title: Data for: Collective asset sharing mechanisms for PV and BESS in renewable energy communities

description: Data set to model the renewable energy community with collective asset sharing.

1. Input data of asset characteristics. Includes all the needed characteristics related to PV and battery energy storage systems.
2. Input data of prices and tariffs.
3. Input data of collective PV systems generation. Includes data for several scenarios for a year.
4. Input data of agents' load profile. Includes the power demand and the PV generation for a year.
DOI: 10.17632/gnk7v936xh.1
title: Racial and Ethnic Differences in Women with Melanoma: A Comparison of Demographics, Tumor Characteristics, and Survival

description: Supplementary Material
DOI: 10.17632/gnk7v936xh.2
title: Racial and Ethnic Differences in Tumor Characteristics and Overall Survival of Women with Melanoma: A National Cancer Database Retrospective Cohort Study

description: Supplementary Material
DOI: 10.17632/gnk7v936xh.3
title: Racial and Ethnic Differences in Tumor Characteristics and Overall Survival of Women with Melanoma: A National Cancer Database Retrospective Cohort Study

description: Supplementary Material
DOI: 10.17632/zg5cwgf3b7.1
title: imited Commercialization of Artificial Intelligence Technology in the Diagnosis of Pigmented Lesions Despite Explosive Growth in Published Programs

description: PRISMA diagram for literature review.
DOI: 10.17632/t5p2v7h3vg.1
title: CMU-SynTraffic-2023-ImageDataset

description: This dataset contains tabular network traffic data from the CMU-Syntraffic-2022 dataset that has been transformed into images using the following tabular-to-image techniques: Binary Image Encoding, IGTD, DeepInsight, and feature wrapping (normalized and non-normalized). The data selected from CMU-Syntraffic-2022 contains real network traffic data from the CIC-Darknet2020 dataset along with synthetic data generated using SMOTE. This dataset is not intended to be used in its entirety as it contains different representations of identical samples. The intended use for this dataset is for research on CNN based anonymous network traffic classification and testing the viability of tabular-to-image algorithms.