cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wnxvz3br5w
title: Design files and data for a lab-scale methane biofiltration system

description: Methane (CH4) is a potent greenhouse gas with a global warming potential 27–30 times greater than CO2. Diffuse sources such as livestock facilities, landfills, and coal mines emit methane at low concentrations (&lt;5% v/v), limiting the applicability of conventional mitigation technologies. Biofiltration, which uses methanotrophic bacteria to oxidize CH4 to CO2, offers a sustainable alternative but lacks standardized hardware, resulting in inconsistent designs and limited reproducibility. We present an open-source, modular lab-scale biofiltration system optimized for continuous operation and experimental replication. The system comprises triplicate packed-bed columns constructed from chemically resistant materials, integrated with mass flow controllers for precise gas delivery, humidifiers to maintain moisture, and standardized fittings for leak-free assembly. Its transparent columns enable visual monitoring, and the bottom-up flow design minimizes media compaction. Validation at an inlet concentration of 0.5% CH4 achieved mean removal efficiencies of 89.0 ± 6.7%. Design files, bill of materials, and assembly instructions are provided under a CERN OHL license to facilitate adoption and customization. This hardware supports methane mitigation research and broader applications in gas-phase bioprocessing, enabling reproducible studies and accelerating development of scalable biofiltration technologies.

This repository includes the design files for the hardware, the bill of materials, and the data obtained during hardware validation for three biofilters ran as replicates. The design files include all CAD files and 3D printing files for the biofilter head/baseplates, as well as frame feet, extrusion mount, and tube clamps to mount the biofilter in its support. Additionally, the files include a metal grate added inside the biofilter for solid media support and a manometer mount.
Headplate/Baseplate: The headplate and baseplate provide the seal for the top and bottom of the biofilter and humidifier columns. Design files, including CAD and shop drawings, are provided for machining. 
Frame Feet: These 3D-printed parts press-fit into the 2020 aluminum frame. Both STL and 3MF files are provided, and the latter include print settings.
Extrusion Mount: The biofilter sits on this 3D-printed part, which bolts to the 2020 aluminum frame. Both STL and 3MF files are provided, and the latter include print settings.
Biofilter Tube Clamp: These two parts, which are mirror images of one another, clamp the outside of the biofilter column to provide a mounting point. CAD and STL files are provided for both the left and right tube clamp. 3MF files include both sides printed together with appropriate print settings.
Metal Grate: These discs are laser cut from stainless steel and support the solid medium inside the biofilter column. DXF files are provided for laser-cutting services.
DOI: 10.17632/wnxvz3br5w.2
title: Design files and data for a lab-scale methane biofiltration system

description: Methane (CH4) is a potent greenhouse gas with a global warming potential 27–30 times greater than CO2. Diffuse sources such as livestock facilities, landfills, and coal mines emit methane at low concentrations (&lt;5% v/v), limiting the applicability of conventional mitigation technologies. Biofiltration, which uses methanotrophic bacteria to oxidize CH4 to CO2, offers a sustainable alternative but lacks standardized hardware, resulting in inconsistent designs and limited reproducibility. We present an open-source, modular lab-scale biofiltration system optimized for continuous operation and experimental replication. The system comprises triplicate packed-bed columns constructed from chemically resistant materials, integrated with mass flow controllers for precise gas delivery, humidifiers to maintain moisture, and standardized fittings for leak-free assembly. Its transparent columns enable visual monitoring, and the bottom-up flow design minimizes media compaction. Validation at an inlet concentration of 0.5% CH4 achieved mean removal efficiencies of 89.0 ± 6.7%. Design files, bill of materials, and assembly instructions are provided under a CERN OHL license to facilitate adoption and customization. This hardware supports methane mitigation research and broader applications in gas-phase bioprocessing, enabling reproducible studies and accelerating development of scalable biofiltration technologies.

This repository includes the design files for the hardware, the bill of materials, and the data obtained during hardware validation for three biofilters ran as replicates. The design files include all CAD files and 3D printing files for the biofilter head/baseplates, as well as frame feet, extrusion mount, and tube clamps to mount the biofilter in its support. Additionally, the files include a metal grate added inside the biofilter for solid media support and a manometer mount.
Headplate/Baseplate: The headplate and baseplate provide the seal for the top and bottom of the biofilter and humidifier columns. Design files, including CAD and shop drawings, are provided for machining. 
Frame Feet: These 3D-printed parts press-fit into the 2020 aluminum frame. Both STL and 3MF files are provided, and the latter include print settings.
Extrusion Mount: The biofilter sits on this 3D-printed part, which bolts to the 2020 aluminum frame. Both STL and 3MF files are provided, and the latter include print settings.
Biofilter Tube Clamp: These two parts, which are mirror images of one another, clamp the outside of the biofilter column to provide a mounting point. CAD and STL files are provided for both the left and right tube clamp. 3MF files include both sides printed together with appropriate print settings.
Metal Grate: These discs are laser cut from stainless steel and support the solid medium inside the biofilter column. DXF files are provided for laser-cutting services.
DOI: 10.6084/m9.figshare.30719321
title: Raw Image Dataset for “An Image-based Global Climate Sentiment Index” (2020–2024)

description: This repository provides the 2020–2024 portion (Part 2 of 2) of the image dataset used in developing “<i>An Image-based Global Climate Sentiment Index</i>”. It contains images retrieved from web searches using climate-related keyword queries during 2020–2024 and subsequently processed through data-cleaning procedures. The corresponding dataset for 2015–2019 (Part 1 of 2) is available at: Raw Image Dataset for “An Image-based Global Climate Sentiment Index” (2015–2019)
DOI: 10.6084/m9.figshare.30719321.v1
title: Raw Image Dataset for “An Image-based Global Climate Sentiment Index” (2020–2024)

description: This repository provides the 2020–2024 portion (Part 2 of 2) of the image dataset used in developing “<i>An Image-based Global Climate Sentiment Index</i>”. It contains images retrieved from web searches using climate-related keyword queries during 2020–2024 and subsequently processed through data-cleaning procedures. The corresponding dataset for 2015–2019 (Part 1 of 2) is available at: Raw Image Dataset for “An Image-based Global Climate Sentiment Index” (2015–2019)
DOI: 10.17632/jzngzjymhj
title: Novel approaches to invasive annual grass management

description: Species percent cover data and soil analyses collected from three semi-arid grasslands in southwestern Montana. Three novel annual grass management approaches (mustard seed meal, NutraFix, and indaziflam) were compared to non-managed controls in combination with a split broadcast restoration seeding treatment over three years. Data were used to assess treatment efficacy of managing cheatgrass as well as impacts to the remaining plant community richness, alpha diversity, and community composition. Both raw data and R analysis are included.
DOI: 10.17632/jzngzjymhj.2
title: Novel approaches to invasive annual grass management

description: Species percent cover data and soil analyses collected from three semi-arid grasslands in southwestern Montana. Three novel annual grass management approaches (mustard seed meal, NutraFix, and indaziflam) were compared to non-managed controls in combination with a split broadcast restoration seeding treatment over three years. Data were used to assess treatment efficacy of managing cheatgrass as well as impacts to the remaining plant community richness, alpha diversity, and community composition. Both raw data and R analysis are included.
DOI: 10.17632/tp96dzwcdk
title: HP1β recruits RING1A to ubiquitinate histone H2A for BRCA1 mediated resection of Double-Stand Breaks

description: These are raw data of the figures described in the mansucript.
DOI: 10.17632/tp96dzwcdk.1
title: HP1β recruits RING1A to ubiquitinate histone H2A for BRCA1 mediated resection of Double-Stand Breaks

description: These are raw data of the figures described in the mansucript.
DOI: 10.17632/kzs3dyjns6
title: Bank competition, monetary policy, and housing prices

description: Does the structure of local banking markets—specifically the degree of bank competition—determine the strength and symmetry of the regional housing price response to monetary policy?
DOI: 10.17632/kzs3dyjns6.2
title: Bank competition, monetary policy, and housing prices

description: Does the structure of local banking markets—specifically the degree of bank competition—determine the strength and symmetry of the regional housing price response to monetary policy?
DOI: 10.17632/tv4kjwczty
title: Supplementary Data for: Scalp Tape-Strip RNA Sequencing Captures Disease and Treatment-Responsive Signatures in Alopecia Areata

description: This dataset accompanies the manuscript “Scalp Tape-Strip RNA Sequencing Captures Disease and Treatment-Responsive Signatures in Alopecia Areata”.
It provides the processed transcriptomic data and analysis scripts used to characterize the molecular landscape of alopecia areata (AA) through a minimally invasive tape-strip approach.

A total of 61 RNA-seq profiles were analyzed, including scalp tape-strip and bulk biopsy samples from healthy controls and patients with AA across the clinical spectrum, before and after treatment with oral baricitinib.
Gene expression was profiled using the Ion AmpliSeq™ Transcriptome Human Gene Expression Panel v2.0, aligned to the human reference genome (hg19_AmpliSeq_Transcriptome_v1.1.04042016.Designed.bed), normalized with voom, and batch-corrected with ComBat (sva package).

The dataset includes:
1) counts_batch_corrected_ComBat_bySymbol.csv — log₂-normalized, batch-corrected expression matrix (genes × samples).
2) metadata_final.csv — clinical and experimental metadata (group, severity, treatment, sample type).
3) custom_gene_sets_AA_tapestrips.gmt — curated gene sets representing key immune (IFN/JAK–STAT, Th1/Th2/Th17/Th22, cytotoxic/NK) and epithelial (follicular, keratinization, fibrosis, proteostasis) pathways.¡
4) /scripts folder — R scripts for GSVA, DEG analysis, and figure generation.

The tape-strip RNA-seq method captured the primary immune and epithelial signatures observed in lesional biopsies—highlighting strong activation of the interferon/JAK–STAT and cytotoxic T/NK pathways, suppression of follicular and keratinization programs, and molecular normalization in post-baricitinib responders.
These data support the translational use of tape-strip transcriptomics as a noninvasive biomarker and disease-monitoring tool in alopecia areata.

All files are ready to reproduce the analyses and figures described in the publication using standard R (v4.3.2) workflows.
DOI: 10.5281/zenodo.7883957
title: Generated Wikidata Subset for geneWiki based on dump: GeneWiki_wikidata-20160613-all

description: Source file: GeneWiki_wikidata-20160613-all.ttl.gz
DOI: 10.5281/zenodo.7883958
title: Generated Wikidata Subset for geneWiki based on dump: GeneWiki_wikidata-20160613-all

description: Source file: GeneWiki_wikidata-20160613-all.ttl.gz
DOI: 10.17632/tv4kjwczty.2
title: Supplementary Data for: Scalp Tape-Strip RNA Sequencing Captures Disease and Treatment-Responsive Signatures in Alopecia Areata

description: This dataset accompanies the manuscript “Scalp Tape-Strip RNA Sequencing Captures Disease and Treatment-Responsive Signatures in Alopecia Areata”.
It provides the processed transcriptomic data and analysis scripts used to characterize the molecular landscape of alopecia areata (AA) through a minimally invasive tape-strip approach.

A total of 61 RNA-seq profiles were analyzed, including scalp tape-strip and bulk biopsy samples from healthy controls and patients with AA across the clinical spectrum, before and after treatment with oral baricitinib.
Gene expression was profiled using the Ion AmpliSeq™ Transcriptome Human Gene Expression Panel v2.0, aligned to the human reference genome (hg19_AmpliSeq_Transcriptome_v1.1.04042016.Designed.bed), normalized with voom, and batch-corrected with ComBat (sva package).

The dataset includes:
1) counts_batch_corrected_ComBat_bySymbol.csv — log₂-normalized, batch-corrected expression matrix (genes × samples).
2) metadata_final.csv — clinical and experimental metadata (group, severity, treatment, sample type).
3) custom_gene_sets_AA_tapestrips.gmt — curated gene sets representing key immune (IFN/JAK–STAT, Th1/Th2/Th17/Th22, cytotoxic/NK) and epithelial (follicular, keratinization, fibrosis, proteostasis) pathways.¡
4) /scripts folder — R scripts for GSVA, DEG analysis, and figure generation.

The tape-strip RNA-seq method captured the primary immune and epithelial signatures observed in lesional biopsies—highlighting strong activation of the interferon/JAK–STAT and cytotoxic T/NK pathways, suppression of follicular and keratinization programs, and molecular normalization in post-baricitinib responders.
These data support the translational use of tape-strip transcriptomics as a noninvasive biomarker and disease-monitoring tool in alopecia areata.

All files are ready to reproduce the analyses and figures described in the publication using standard R (v4.3.2) workflows.
DOI: 10.17632/hsz69vx893
title: Scripts and data for the manuscript "The three-morph problem: male trimorphism and alternative reproductive tactics in a Neotropical arachnid" submitted to Animal Behaviour
DOI: 10.17632/hsz69vx893.1
title: Scripts and data for the manuscript "The three-morph problem: male trimorphism and alternative reproductive tactics in a Neotropical arachnid" submitted to Animal Behaviour
DOI: 10.17632/f9nxr6745y
title: Standardized litchi leaf disease image dataset for deep learning applications

description: Standardized litchi leaf disease image dataset is a curated image dataset of healthy and diseased litchi (Litchi chinensis) leaves designed for computer vision and deep learning research in plant pathology. The dataset contains 11 classes of leaf conditions captured using a high-resolution smartphone camera under natural lighting on a clean white background to reduce visual noise and enhance symptom visibility. Raw images were pre-processed through a standardized pipeline that performs background removal, leaf-centric cropping and aspect ratio preserving resizing to generate three aligned versions of each sample: 512 × 512 pixels with a black background, 512 × 512 pixels with a white background and 224 × 224 pixels with a white background tailored for transfer learning models.

In addition to the original pre-processed images, this repository also includes an augmented dataset where each 224 × 224 sample is expanded using geometric and photometric transformations such as rotation, scaling, flipping, elastic deformation, Gaussian blur, cutout, negative transform and brightness variations. This results in 1–12 images per original sample and provides increased variability for training robust models. All images are RGB and each sample has been reviewed and labeled by agricultural experts to ensure reliable ground truth. The dataset is intended for reuse in tasks such as disease classification, image based plant phenotyping, segmentation of symptomatic regions and severity analysis as well as for benchmarking new computer vision methods on litchi leaf disease data and for teaching in machine learning, deep learning and digital agriculture.
DOI: 10.17632/f9nxr6745y.1
title: Standardized litchi leaf disease image dataset for deep learning applications

description: Standardized litchi leaf disease image dataset is a curated image dataset of healthy and diseased litchi (Litchi chinensis) leaves designed for computer vision and deep learning research in plant pathology. The dataset contains 11 classes of leaf conditions captured using a high-resolution smartphone camera under natural lighting on a clean white background to reduce visual noise and enhance symptom visibility. Raw images were pre-processed through a standardized pipeline that performs background removal, leaf-centric cropping and aspect ratio preserving resizing to generate three aligned versions of each sample: 512 × 512 pixels with a black background, 512 × 512 pixels with a white background and 224 × 224 pixels with a white background tailored for transfer learning models.

In addition to the original pre-processed images, this repository also includes an augmented dataset where each 224 × 224 sample is expanded using geometric and photometric transformations such as rotation, scaling, flipping, elastic deformation, Gaussian blur, cutout, negative transform and brightness variations. This results in 1–12 images per original sample and provides increased variability for training robust models. All images are RGB and each sample has been reviewed and labeled by agricultural experts to ensure reliable ground truth. The dataset is intended for reuse in tasks such as disease classification, image based plant phenotyping, segmentation of symptomatic regions and severity analysis as well as for benchmarking new computer vision methods on litchi leaf disease data and for teaching in machine learning, deep learning and digital agriculture.
DOI: 10.15468/dl.fy2fnh
title: Occurrence Download

description: A dataset containing 5167 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON Z((72.55581 34.27476 0,74.04267 33.22041 0,76.53545 31.62866 0,77.03702 30.74826 0,77.33249 30.48654 0,77.99463 30.18798 0,79.44641 29.23289 0,81.87325 28.05351 0,86.4637 26.70215 0,90.68933 26.76255 0,93.77432 26.99214 0,95.56711 28.21201 0,96.17122 27.9398 0,97.57701 26.72746 0,97.4964 25.70944 0,98.66888 25.41075 0,99.53837 25.39827 0,99.53789 27.77607 0,99.31775 28.62547 0,98.65463 29.01301 0,97.53114 29.80043 0,95.48076 30.23184 0,93.46168 30.4656 0,92.05728 29.26726 0,91.51648 28.57722 0,90.41589 28.48018 0,88.70823 28.52966 0,86.22449 28.68589 0,84.64413 29.40084 0,81.24842 31.44002 0,79.93861 32.28306 0,78.84629 33.52148 0,74.53391 35.3006 0,74.1196 35.42985 0,73.35163 35.61047 0,72.57392 35.51471 0,72.35195 34.72705 0,72.55581 34.27476 0))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Marchantiophyta"
 ]
}

 The dataset includes 5167 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011383-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/9h98-2684
title: Measurement of pH at Tustervatn

description: Measurement of pH at Tustervatn
DOI: 10.48597/9meq-ygh7
title: Measurement of Inorganics in precipitation at Kårvatn

description: Measurement of Inorganics in precipitation at Kårvatn
DOI: 10.48597/9mm6-zz93
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/a5de-2n3y
title: Measurement of pH at Birkenes

description: Measurement of pH at Birkenes
DOI: 10.48597/a6jk-ftk5
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/ak8b-pexq
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/ak9h-3man
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/b54m-e6z6
title: Measurement of Inorganics in precipitation at Birkenes

description: Measurement of Inorganics in precipitation at Birkenes
DOI: 10.48597/b5s9-spma
title: Measurement of Inorganics in precipitation at Kårvatn

description: Measurement of Inorganics in precipitation at Kårvatn
DOI: 10.48597/bcqu-dqvm
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/bk5e-m28z
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/brf7-aw9f
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/bxwb-75em
title: Measurement of Inorganics in precipitation at Birkenes

description: Measurement of Inorganics in precipitation at Birkenes
DOI: 10.48597/cnas-df7f
title: Measurement of Chloride at Birkenes

description: Measurement of Chloride at Birkenes
DOI: 10.48597/csxb-k8ct
title: Measurement of Inorganics in precipitation at Kårvatn

description: Measurement of Inorganics in precipitation at Kårvatn
DOI: 10.48597/e9rx-9ext
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/efmx-hwqr
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/f38y-y4ym
title: Measurement of Inorganics in precipitation at Kårvatn

description: Measurement of Inorganics in precipitation at Kårvatn
DOI: 10.48597/f4k4-tnba
title: Measurement of Inorganics in precipitation at Kårvatn

description: Measurement of Inorganics in precipitation at Kårvatn
DOI: 10.48597/f4yu-g3we
title: Measurement of Inorganics in precipitation at Birkenes

description: Measurement of Inorganics in precipitation at Birkenes
DOI: 10.48597/ffdp-6hey
title: Measurement of Sulphate_total at Birkenes

description: Measurement of Sulphate_total at Birkenes
DOI: 10.48597/fspu-qryg
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/g6hw-9ndd
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/ge7h-pybz
title: Measurement of Inorganics in precipitation at Birkenes

description: Measurement of Inorganics in precipitation at Birkenes
DOI: 10.48597/gfkk-6gbq
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/gxu5-sggu
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/h2et-vx2s
title: Measurement of Inorganics in precipitation at Birkenes

description: Measurement of Inorganics in precipitation at Birkenes
DOI: 10.48597/h64g-q7gx
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/h94t-2w9e
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/hn4j-n8ej
title: Measurement of Magnesium at Tustervatn

description: Measurement of Magnesium at Tustervatn
DOI: 10.48597/hwst-hb5n
title: Measurement of Precipitation_amount at Tustervatn

description: Measurement of Precipitation_amount at Tustervatn
DOI: 10.48597/k5px-6g4s
title: Measurement of pH at Birkenes

description: Measurement of pH at Birkenes
DOI: 10.48597/kgen-nq2t
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn