cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19445771.v1
title: Additional file 5 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 5: Table S5. BarWare HTO category assignment counts. Well: Pooled sample well. Total Barcodes: Number of cell barcodes identified for each well. Singlet: Number of cell barcodes assigned to the singlet category. Doublets: Number of cell barcodes assigned to the doublet category. Multiplets: Number of cell barcodes assigned to the multiplet category. No Hash: Number of cell barcodes assigned to the no hash detected category.
DOI: 10.6084/m9.figshare.19445768.v1
title: Additional file 4 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 4: Table S4. Benchmarking statistics for HTO counting methods. Tool: Software tool used for benchmarking. Well: Pooled sample well. Elapsed Time (h:mm:ss): Elapsed (clock) time passed to analyze each well. User Time (s): User Time elapsed to analyze each well. % CPU: Maximum CPU load during well analysis. Max Resident Set Size (KB): Maximum resident memory set size during well analysis. Output Size (bytes): Output file size after analysis.
DOI: 10.6084/m9.figshare.19446050.v1
title: Additional file 1 of Implementation strategies for the patient safety reporting system using Consolidated Framework for Implementation Research: a retrospective mixed-method analysis

description: Additional file 1. Strategies identified for patient safety reporting system using the consolidated framework for implementation research
DOI: 10.6084/m9.figshare.19445765.v1
title: Additional file 3 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 3: Table S3. Sequenced read count statistics. Library ID: Pooled library ID. # Cells: Number of cells loaded. Reads: Number of sequenced read trios for each library (I1, R1, and R2). Reads per cell: Mean number of sequenced reads per cell barcode.
DOI: 10.6084/m9.figshare.19446056.v1
title: Additional file 2 of Microbial and molecular differences according to the location of head and neck cancers

description: Additional file 2: Table S1. The GO analysis results, hub genes, and tumour locations of included patients.
DOI: 10.6084/m9.figshare.19446061.v1
title: Additional file 2 of Microbiome network traits in the rumen predict average daily gain in beef cattle under different backgrounding systems

description: Additional file 2. Indicator ASVs characterizing calves under each backgrounding system at day 55 of backgrounding.
DOI: 10.6084/m9.figshare.19445762.v1
title: Additional file 2 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 2: Table S2. Barcode category assignment discrepancies. Counts and count-derived metrics obtained for each of the top two hashes are shown for each cell barcode assigned to the singlet category BarCounter results. but considered a doublet based on CITE-Seq-Count results. Well: Pooled sample well. Barcode: Cell barcode. BarCounter_1st: Counts for the highest-scoring hash based on BarCounter. BarCoutner_2nd: Counts for the second highest-scoring hash based on BarCounter. CITE_1st: Counts for the highest-scoring hash based on CITE-seq-Count. CITE_2nd: Counts for the second highest-scoring hash based on CITE-seq-Count. Change_1st: Difference in counts for the highest-scoring hash (BarCounter_1st—CITE_1st). Change_2nd: Difference in counts for the second highest-scoring hash (BarCounter_2nd—CITE-seq-Count_2nd). Prop_Change_1st: Difference in counts for the highest-scoring hash as a proportion of BarCounter counts (BarCounter_1st—CITE_1st) / BarCounter_1st. Prop_Change_2nd: Difference in counts for the second highest-scoring hash as a proportion of BarCounter counts (BarCounter_2nd—CITE_2nd) / BarCounter_2nd. Ratio_1st:2nd: Ratio of the highest-scoring BarCounter counts to the second high-scoring BarCounter counts (BarCounter_1st / BarCounter_2nd).
DOI: 10.6084/m9.figshare.19445948.v1
title: watch the batman 2022 full movie

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DOI: 10.6084/m9.figshare.19445759.v1
title: Additional file 1 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 1: Table S1. HTO category agreement across wells. Fraction of agreement of cell barcode assignment to each HTO category for each pooled sample well based on BarCounter and CITE-seq-Count processing. Well: Pooled sample well. Frac_singlet: Fraction of singlet calls that agree using BarCounter and CITE-seq-Count. Frac_doublet: Fraction of doublet calls that agree using BarCounter and CITE-seq-Count. Frac_multiplet: Fraction of multiplet calls that agree using BarCounter and CITE-seq-Count. Frac_no-hash: Fraction of no hash detected calls that agree using BarCounter and CITE-seq-Count.
DOI: 10.6084/m9.figshare.19106429
title: Morphometric analysis toward mapping relative tectonic activity of Lebanon

description: The data contains the following:- RATM raster- Watersheds shapefile
DOI: 10.6084/m9.figshare.19106429.v2
title: Morphometric analysis of hillslope evolution of Kadisha river basin.zip

description: The data includes the following:- Sub watershed polygon- Ridge polyline- Stream polyline- Eroded volume rasters
DOI: 10.6084/m9.figshare.19445825
title: Long, regular return of 4 large earthquakes on Qilian Shan’s Minle-Damaying frontal thrust (NE Tibet): Partial Clustering with great events on the Leng Long Ling fault?

description: DEM data.
DOI: 10.6084/m9.figshare.19434545
title: Muti-omics reveals that the gut microbiome and its metabolite promotes milk fat synthesis in Zhongdian Yak cows

description: Metagenomics of the gut microbiome of Yak cows
DOI: 10.6084/m9.figshare.19445707.v1
title: Additional file 4 of An 8-gene machine learning model improves clinical prediction of severe dengue progression

description: Additional file 4: Table S2. Clinical data, expression of genes in 8- and 20-gene signatures, and 8-gene XGBoost model predicted probabilities for patients in the Colombia cohort.
DOI: 10.6084/m9.figshare.19445677.v1
title: Additional file 1 of Nationwide comprehensive epidemiological study of rare diseases in Japan using a health insurance claims database

description: Additional file 1. The tabular datasets derived from the National Database of Health Insurance Claims and Specific Health Checkups of Japan.
DOI: 10.6084/m9.figshare.19445639.v1
title: Additional file 5 of Use of novel lab assays to examine the effect of pyrethroid-treated bed nets on blood-feeding success and longevity of highly insecticide-resistant Anopheles gambiae s.l. mosquitoes

description: Additional file 5: Table B. Statistical analysis summaries.
DOI: 10.6084/m9.figshare.19445612.v1
title: Additional file 1 of Findings from precision oncology in the clinic: rare, novel variants are a significant contributor to scaling molecular diagnostics

description: Additional file 1. Table S1: Excel worksheet of panel attributes.
DOI: 10.34740/kaggle/dsv/3369702
title: US Road Construction and Closures (2016 - 2021)
DOI: 10.5281/zenodo.6392446
title: Dr.

description: Data for manuscript "Invasive Eupatorium adenophora can maintain its ecological advantages over time through releasing its autotoxicity"
DOI: 10.5281/zenodo.6392445
title: Dr.

description: Data for manuscript "Invasive Eupatorium adenophora can maintain its ecological advantages over time through releasing its autotoxicity"
DOI: 10.5281/zenodo.6392409
title: Seismogenic process of fluid injection revealed by in situ dynamic CT scanning

description: In the process of unconventional energy exploitation, large volumes of fluid are injected into low permeability reservoirs for hydraulic transformation to generate a fracture network conducive to fluid migration. Unfortunately, extensive fluid injection can induce earthquakes, endangering human lives and causing serious economic losses. Understanding the seismogenic process of fluid injection within a reservoir helps to minimize the induced earthquakes. To better monitor the deformation changes in reservoirs, we conducted in situ dynamic X-ray computed tomography (CT) during a series of experiments lasting 3 minutes for real-time identification of the location and geometry of hydraulic fractures and found that the seismogenic process of fluid injection with a wide range of frequencies is triggered by water–rock interactions. The data we uploaded can be divided into two main parts. The first part is the confining, axial and water injection pressures recorded during the hydraulic fracturing experiment. The second part is the CT scans of the rock sample during the hydraulic fracturing experiment.
DOI: 10.5281/zenodo.6392408
title: Seismogenic process of fluid injection revealed by in situ dynamic CT scanning

description: In the process of unconventional energy exploitation, large volumes of fluid are injected into low permeability reservoirs for hydraulic transformation to generate a fracture network conducive to fluid migration. Unfortunately, extensive fluid injection can induce earthquakes, endangering human lives and causing serious economic losses. Understanding the seismogenic process of fluid injection within a reservoir helps to minimize the induced earthquakes. To better monitor the deformation changes in reservoirs, we conducted in situ dynamic X-ray computed tomography (CT) during a series of experiments lasting 3 minutes for real-time identification of the location and geometry of hydraulic fractures and found that the seismogenic process of fluid injection with a wide range of frequencies is triggered by water–rock interactions. The data we uploaded can be divided into two main parts. The first part is the confining, axial and water injection pressures recorded during the hydraulic fracturing experiment. The second part is the CT scans of the rock sample during the hydraulic fracturing experiment.
DOI: 10.6084/m9.figshare.17111606
title: Supplementary Information: Online Social Support via Avatar Communication BuffersHarmful Effects of Offline Bullying Victimization

description: Supplementary Information: Online Social Support via Avatar Communication BuffersHarmful Effects of Offline Bullying Victimization<br>This data would publish in the following paper: Masanori Takano and Kenji Yokotani, "Online Social Support via Avatar Communication Buffers Harmful Effects of Offline Bullying Victimization", Proceedings of the Sixteenth International Conference on Web and Social Media (ICWSM-2022), Vol. 16, No. 1, 2022.
DOI: 10.6084/m9.figshare.19445497.v1
title: Additional file 4 of Locus specific reduction of L1 expression in the cortices of individuals with amyotrophic lateral sclerosis

description: Additional file 4: Table S4. Coordinates and insertion allele frequencies of polymorphic intact and non-intact L1s identified in the Target ALS cohort.
DOI: 10.6084/m9.figshare.19445491.v1
title: Additional file 2 of Locus specific reduction of L1 expression in the cortices of individuals with amyotrophic lateral sclerosis

description: Additional file 2: Table S2. Coordinates of intact and non-intact expressed L1 loci.
DOI: 10.6084/m9.figshare.19445488.v1
title: Additional file 1 of Locus specific reduction of L1 expression in the cortices of individuals with amyotrophic lateral sclerosis

description: Additional file 1: Table S1. Covariates used in the statistical analysis comparing total intact and non-intact L1 expression for each tissue.
DOI: 10.6084/m9.figshare.19445479.v1
title: Additional file 2 of Whole-genome sequencing as an investigational device for return of hereditary disease risk and pharmacogenomic results as part of the All of Us Research Program

description: Additional file 2. Reportable region in bed format.
DOI: 10.6084/m9.figshare.19445461.v1
title: Additional file 2 of Composition and short-term stability of gut microbiota in lean and spontaneously overweight healthy Labrador retriever dogs

description: Additional file 2. Raw data of all dogs: BCS, OTU, IndVal, Similarity index, Diversity, Phyla, Families and Genera.
DOI: 10.6084/m9.figshare.19445314.v1
title: Additional file 2 of Usability evaluation of the Computer-Based Health Evaluation System (CHES) eDiary for patients with faecal incontinence: a pilot study

description: Additional file 2: Appendix 3. Anonymized dataset used in the publication.
DOI: 10.6084/m9.figshare.19445288.v1
title: Additional file 3 of Novel biallelic USH2A variants in a patient with usher syndrome type IIA- a case report

description: Additional file 3.
DOI: 10.6084/m9.figshare.19445285.v1
title: Additional file 2 of Novel biallelic USH2A variants in a patient with usher syndrome type IIA- a case report

description: Additional file 2.
DOI: 10.6084/m9.figshare.19445282.v1
title: Additional file 1 of Novel biallelic USH2A variants in a patient with usher syndrome type IIA- a case report

description: Additional file 1.
DOI: 10.6084/m9.figshare.19445275.v1
title: Additional file 3 of Risk factors for progression of Urolith Associated with Obstructive Urosepsis to severe sepsis or septic shock

description: Additional file 3. Original data.
DOI: 10.6084/m9.figshare.19445272.v1
title: Additional file 2 of Risk factors for progression of Urolith Associated with Obstructive Urosepsis to severe sepsis or septic shock

description: Additional file 2. Table legend.
DOI: 10.15121/1856793
title: Hawaii Play Fairway Analysis: Noble Gas Raw Data for Hawaii, Maui, Oahu, Kauai, and Lanai islands

description: Noble gas raw data for the Hawaiian islands of Big Island, Maui, Oahu, Lanai, and Kauai. Based on results from prior phases of the Hawaii Play Fairway Analysis, this project targeted 66 wells on the islands of Hawaii, Maui, Lanai, Oahu, and Kauai for sampling of dissolved noble gases, trace metals, common ions, and the stable isotopes 2H and 18O. Ultimately, 23 of the 66 well targets were sampled. Noble gas data from this study is supplemented with data shared by the United States Geologic Survey for the summit of Kilauea, and by the geothermal energy company Ormat Technologies Inc. for their geothermal power plant Puna Geothermal Venture on the Lower East Rift of Kilauea, and for their exploration of Kona and Hualalai on Hawaii, as well as the Southwest Rift of Haleakala on Maui. The noble gas helium is used as an indicator of geothermal heat when excess 3He and/or 4He is present when compared to the atmospheric ratio of those isotopes (R/Ra). R/Ra is minimally affected by dilution and transport, allowing even those wells not perfectly situated over a geothermal system to indicate a geothermal anomaly. R/Ra anomalies are present on every island in this study. There is a strong correlation between R/Ra anomalies and proximity to rift zones and calderas. The Hawaii Play Fairway project was funded by the U.S. Department of Energy Geothermal Technologies Office (award DE-EE0006729). For more information, see Colin Ferguson's Master of Science thesis "Exploration for Blind Geothermal Resources in the State of Hawaii Utilizing Dissolved Noble Gasses in Well Waters."
DOI: 10.3886/e112833v1-113580
title: Replication data for: Importers, Exporters, and Exchange Rate Disconnect

description: Large exporters are simultaneously large importers. We show that this pattern is key to understanding low aggregate exchange rate pass-through as well as the variation in pass-through across exporters. We develop a theoretical framework with variable markups and imported inputs, which predicts that firms with high import shares and high market shares have low exchange rate pass-through. We test and quantify the theoretical mechanism using Belgian firm-product-level data on imports and exports. Small nonimporting firms have nearly complete pass-through, while large import-intensive exporters have pass-through around 50 percent, with the marginal cost and markup channels contributing roughly equally.
DOI: 10.6084/m9.figshare.19446061
title: Additional file 2 of Microbiome network traits in the rumen predict average daily gain in beef cattle under different backgrounding systems

description: Additional file 2. Indicator ASVs characterizing calves under each backgrounding system at day 55 of backgrounding.
DOI: 10.6084/m9.figshare.19446056
title: Additional file 2 of Microbial and molecular differences according to the location of head and neck cancers

description: Additional file 2: Table S1. The GO analysis results, hub genes, and tumour locations of included patients.
DOI: 10.6084/m9.figshare.19446050
title: Additional file 1 of Implementation strategies for the patient safety reporting system using Consolidated Framework for Implementation Research: a retrospective mixed-method analysis

description: Additional file 1. Strategies identified for patient safety reporting system using the consolidated framework for implementation research
DOI: 10.6084/m9.figshare.19446023
title: Additional file 9 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 9.
DOI: 10.6084/m9.figshare.19446017
title: Additional file 8 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 8.
DOI: 10.6084/m9.figshare.19446011
title: Additional file 7 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 7.
DOI: 10.6084/m9.figshare.19446005
title: Additional file 6 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 6.
DOI: 10.6084/m9.figshare.19445999
title: Additional file 5 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 5.
DOI: 10.6084/m9.figshare.19445996
title: Additional file 4 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 4.
DOI: 10.6084/m9.figshare.19445993
title: Additional file 3 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 3.
DOI: 10.6084/m9.figshare.19445990
title: Additional file 2 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 2.
DOI: 10.6084/m9.figshare.19445984
title: Additional file 11 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 11.
DOI: 10.6084/m9.figshare.19445981
title: Additional file 10 of Genomic architecture of 5S rDNA cluster and its variations within and between species

description: Additional file 10.
DOI: 10.6084/m9.figshare.19445980
title: Additional file 1 of Retrospective analysis of radiographic signs in feline pleural effusions to predict disease aetiology

description: Additional file 1.
DOI: 10.6084/m9.figshare.19445948
title: watch the batman 2022 full movie

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DOI: 10.6084/m9.figshare.19445935
title: Additional file 1 of Widely used, short 16S rRNA mitochondrial gene fragments yield poor and erratic results in phylogenetic estimation and species delimitation of amphibians

description: Additional file 1: Table S1. List of sequences used in this study and their associated GenBank accession numbers.
DOI: 10.6084/m9.figshare.19445881
title: Additional file 5 of Risk factors for long-term survival in patients with ypN+ M0 rectal cancer after radical anterior resection

description: Additional file 5. Dataset.
DOI: 10.6084/m9.figshare.19445842
title: Additional file 2 of Species and genotypes belonging to Echinococcus granulosus sensu lato complex causing human cystic echinococcosis in Europe (2000–2021): a systematic review

description: Additional file 2: Table S2. Summary of data extracted from publications reviewed in this study.
DOI: 10.6084/m9.figshare.19445792
title: Additional file 1 of Transgenesis in parasitic helminths: a brief history and prospects for the future

description: Additional file 1: Table S1. Extended details in the historical advances in the transgenesis of parasitic helminths.
DOI: 10.6084/m9.figshare.19445774
title: Additional file 6 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 6: Table S6. Antibodies used for Cell Hashing and FACS. Manufacturer: Reagent manufacturer. Catalog No.: Manufacturer catalog number. Conjugate: Moiety (fluorophore or oligonucleotides) conjugated to each antibody. Target: Antibody binding target(s). Clone: Antibody clone. Vol per M cells (µL): Volume of antibody added per million cells for staining.
DOI: 10.6084/m9.figshare.19445771
title: Additional file 5 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 5: Table S5. BarWare HTO category assignment counts. Well: Pooled sample well. Total Barcodes: Number of cell barcodes identified for each well. Singlet: Number of cell barcodes assigned to the singlet category. Doublets: Number of cell barcodes assigned to the doublet category. Multiplets: Number of cell barcodes assigned to the multiplet category. No Hash: Number of cell barcodes assigned to the no hash detected category.
DOI: 10.6084/m9.figshare.19445768
title: Additional file 4 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 4: Table S4. Benchmarking statistics for HTO counting methods. Tool: Software tool used for benchmarking. Well: Pooled sample well. Elapsed Time (h:mm:ss): Elapsed (clock) time passed to analyze each well. User Time (s): User Time elapsed to analyze each well. % CPU: Maximum CPU load during well analysis. Max Resident Set Size (KB): Maximum resident memory set size during well analysis. Output Size (bytes): Output file size after analysis.
DOI: 10.6084/m9.figshare.19445765
title: Additional file 3 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 3: Table S3. Sequenced read count statistics. Library ID: Pooled library ID. # Cells: Number of cells loaded. Reads: Number of sequenced read trios for each library (I1, R1, and R2). Reads per cell: Mean number of sequenced reads per cell barcode.
DOI: 10.6084/m9.figshare.19445762
title: Additional file 2 of BarWare: efficient software tools for barcoded single-cell genomics

description: Additional file 2: Table S2. Barcode category assignment discrepancies. Counts and count-derived metrics obtained for each of the top two hashes are shown for each cell barcode assigned to the singlet category BarCounter results. but considered a doublet based on CITE-Seq-Count results. Well: Pooled sample well. Barcode: Cell barcode. BarCounter_1st: Counts for the highest-scoring hash based on BarCounter. BarCoutner_2nd: Counts for the second highest-scoring hash based on BarCounter. CITE_1st: Counts for the highest-scoring hash based on CITE-seq-Count. CITE_2nd: Counts for the second highest-scoring hash based on CITE-seq-Count. Change_1st: Difference in counts for the highest-scoring hash (BarCounter_1st—CITE_1st). Change_2nd: Difference in counts for the second highest-scoring hash (BarCounter_2nd—CITE-seq-Count_2nd). Prop_Change_1st: Difference in counts for the highest-scoring hash as a proportion of BarCounter counts (BarCounter_1st—CITE_1st) / BarCounter_1st. Prop_Change_2nd: Difference in counts for the second highest-scoring hash as a proportion of BarCounter counts (BarCounter_2nd—CITE_2nd) / BarCounter_2nd. Ratio_1st:2nd: Ratio of the highest-scoring BarCounter counts to the second high-scoring BarCounter counts (BarCounter_1st / BarCounter_2nd).