cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5064/f6g2petf/aso06l
title: Moore-et-al_MD_0121_Governor Larry Hogan - Official Website for the Governor of Maryland_05.pdf
DOI: 10.5064/f6g2petf/tdlnuw
title: Moore-et-al_ME_0421_COVID Vaccines_ME DHHS_Core Set_04-16-2021 .pdf
DOI: 10.5064/f6g2petf/4glpsz
title: Moore-et-al_ME_0521_Quarantine-After-Vaccination.pdf
DOI: 10.5064/f6g2petf/e5slm9
title: Moore-et-al_MD_0221_Maryland Department of Health Maryland Department of Health brings mobile sound truck to Prince George’s County .pdf
DOI: 10.5064/f6g2petf/9ue2fl
title: Moore-et-al_MD_0221_Governor Larry Hogan - Official Website for the Governor of Maryland_11.pdf
DOI: 10.5064/f6g2petf/y9ffwq
title: Moore-et-al_ME_0221_COVID-19 Vaccination Dashboard _ Covid-19.pdf
DOI: 10.5064/f6g2petf/04oye4
title: Moore-et-al_MD_0121_Governor Larry Hogan - Official Website for the Governor of Maryland_03.pdf
DOI: 10.5064/f6g2petf/sdnczp
title: Moore-et-al_MD_0721_MDPCP_Vaccine_Outreach_Guide.pdf
DOI: 10.5064/f6g2petf/f2knvr
title: Moore-et-al_ME_1220_covid19-vaccine-planning-work-group12172020.pdf
DOI: 10.5064/f6g2petf/mjp9tf
title: Moore-et-al_ME_0121_2021PHADV001COVIDUpdatesQuarantineTe.pdf
DOI: 10.5064/f6g2petf/okuvpf
title: Moore-et-al_MD_0421_Maryland Department of Health GoVAX Mobile COVID-19 vaccine clinics serve Harford County residents.pdf
DOI: 10.5064/f6g2petf/yc6lhv
title: Moore-et-al_MD_1220_Governor Larry Hogan - Official Website for the Governor of Maryland_09.pdf
DOI: 10.57783/7ntg-mv65
title: LibreChat
DOI: 10.24355/dbbs.084-202105030818-0
title: Capillary, film, and vapor flow in bare soil evaporation: Identifiability analysis

description: Evaporation experiments are frequently used to identify the hydraulic properties of soils by inverse simulations with the Richards equation or simplified calculation methods. Laboratory evaporation experiments were simulated with a coupled water, vapor and heat flow model which solves the surface energy balance. The simulated data were used in inverse simulations with the Richards equation to analyze the identifiability of soil hydraulic properties. The dataset contains the results of the forward simulations with the coupled water-vapor-heat model for different soil hydraulic properties and the results of inverse simulations which illustrate the applicability of the Richards equation.
DOI: 10.18150/1vxzjg
title: How far can you stretch 'ionic liquid' before it snaps? Exploring the fine line between exact science and speculative science

description: The dataset contains the results of a bibliometric analysis based on the Scopus database, focusing on scientific publications related to ionic liquids. The data were collected in April 2025 to assess the popularity of selected search phrases and their geographical and temporal distribution.The set includes two separate files in .xlsx format:Country_analysis_ionic_liquids.xlsx – provides numerical data showing the number of publications for selected keyword combinations (e.g., “Ionic liquids AND synthesis”, “AND thermal stability”) by country. This file allows for the evaluation of research activity in this thematic area at the national level.Yearly_trends_ionic_liquids.xlsx – contains similar data broken down by year (2020–2024), enabling the analysis of temporal trends in research on ionic liquids.
DOI: 10.5281/zenodo.15431784
title: mTopic - Supplementary RDS data

description: Uploaded files are raw (*_raw.rds) and filtered (*_filtered.rds) RDS objects used for R tutorials of mTopic.

Single-cell data processed here are publicly available from the Gene Expression Omnibus (GEO) and 10x Genomics:

Human PBMC dataset (Human_PBMC_ATAC_RNA_Protein) [1]GSE166188– GSM5065524 for ATAC– GSM5065525 for RNA– GSM5065526 for protein

Human tonsil dataset (Human_Tonsil_RNA_Protein)Available from 10x Genomics here.References[1] Mimitou EP, Lareau CA, Chen KY, Zorzetto-Fernandes AL et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat Biotechnol 2021 Oct;39(10):1246-1258. PMID: 34083792
DOI: 10.5281/zenodo.15431783
title: mTopic - Supplementary RDS data

description: Uploaded files are raw (*_raw.rds) and filtered (*_filtered.rds) RDS objects used for R tutorials of mTopic.

Single-cell data processed here are publicly available from the Gene Expression Omnibus (GEO) and 10x Genomics:

P22 mouse brain dataset (P22_Mouse_Brain_ATAC_RNA) [1]

– GSE218593 (GSM6753043) for RNA– GSE205055 (GSM6758285) for ATAC

Human tonsil dataset (Human_Tonsil_RNA_Protein)Available from 10x Genomics here.

Human PBMC dataset (Human_PBMC_ATAC_RNA_Protein) [2]GSE166188– GSM5065524 for ATAC– GSM5065525 for RNA– GSM5065526 for protein

References[1] Zhang D, Deng Y, Kukanja P, Agirre E et al. Spatial epigenome-transcriptome co-profiling of mammalian tissues. Nature 2023 Apr;616(7955):113-122. PMID: 36922587[2] Mimitou EP, Lareau CA, Chen KY, Zorzetto-Fernandes AL et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat Biotechnol 2021 Oct;39(10):1246-1258. PMID: 34083792
DOI: 10.5281/zenodo.15472980
title: mTopic - Supplementary RDS data

description: Uploaded files are raw (*_raw.rds) and filtered (*_filtered.rds) RDS objects used for R tutorials of mTopic.

Single-cell data processed here are publicly available from the Gene Expression Omnibus (GEO) and 10x Genomics:

P22 mouse brain dataset (P22_Mouse_Brain_ATAC_RNA) [1]

– GSE218593 (GSM6753043) for RNA– GSE205055 (GSM6758285) for ATAC

Human tonsil dataset (Human_Tonsil_RNA_Protein)Available from 10x Genomics here.

Human PBMC dataset (Human_PBMC_ATAC_RNA_Protein) [2]GSE166188– GSM5065524 for ATAC– GSM5065525 for RNA– GSM5065526 for protein

References[1] Zhang D, Deng Y, Kukanja P, Agirre E et al. Spatial epigenome-transcriptome co-profiling of mammalian tissues. Nature 2023 Apr;616(7955):113-122. PMID: 36922587[2] Mimitou EP, Lareau CA, Chen KY, Zorzetto-Fernandes AL et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat Biotechnol 2021 Oct;39(10):1246-1258. PMID: 34083792
DOI: 10.5281/zenodo.18337745
title: Ignitia Dataset : A Multimodal Machine Learning and Simulation Framework for Spatiotemporal Risk Assessment

description: Wildfires in mountainous regions such as Uttarakhand, India, are driven by complex interactions among topographic, climatic, vegetation, and anthropogenic factors, necessitating high-resolution, region-specific prediction datasets. This work presents the Ignitia Wildfire Susceptibility Prediction Dataset, a curated, analysis-ready geospatial dataset designed to support machine-learning–based wildfire ignition modeling in complex Himalayan terrain.

The dataset was constructed using multisource remote-sensing and environmental variables processed within a cloud-based geospatial framework and harmonized at 30 m spatial resolution. It comprises topographic features (elevation, slope, aspect), meteorological variables (humidity, wind), vegetation and land-surface indicators (NDVI, land-cover class, land surface temperature), and spatio-temporal attributes (latitude, longitude, date, and month), along with a binary wildfire occurrence label. All features are provided in cleaned and scaled form to facilitate direct use in supervised learning workflows.

This dataset underpins the Ignitia wildfire susceptibility modeling pipeline, where multiple supervised machine-learning models are benchmarked under k-fold cross-validation to quantify feature influence, improve interpretability, and identify key ignition drivers in mountainous ecosystems. Although the broader Ignitia framework integrates probabilistic cellular automata–based fire-spread simulation and interactive web deployment, the present release focuses exclusively on the prediction-ready dataset, enabling reproducible experimentation and comparative evaluation by the research community.

The primary contribution of this dataset lies in providing a localized, high-resolution, multimodal feature space for wildfire ignition prediction in mountainous regions, supporting future advances in data-driven fire-risk assessment, explainable modeling, and region-specific wildfire early-warning systems.
DOI: 10.25824/redu/ol8chj
title: Detection of microservices anti patterns using dynamic analysis runtime in Spinnaker

description: This attachment contains documents on strategies for detecting antipatterns using dynamic analysis, based on logs extracted from sidecars in a Kubernetes environment hosting the Spinnaker (https://spinnaker.io/) application. These antipatterns were selected through a systematic literature review to identify the most critical antipatterns and evaluate their detection strategies. The emphasis was on antipatterns that either lacked effective detection by current methods or were not well addressed by static analysis techniques (e.g., source code, repositories, or process artifacts). All processes related to the detection and triggering of Spinnaker tools, which aim to generate concise logs of Istio usage within a Kubernetes cluster, were included to facilitate understanding of the main idea behind the detections. In addition, we have gathered information on how to execute, manage, and access the log data produced by Istio sidecars deployed with the Spinnaker application. This includes configuring the sidecars to properly capture logs, adjusting log levels, and ensuring that telemetry collection is working as intended. More details are available in the text documents in the files. The file "spinnaker-artifacts-20250524T182034Z-1-001.zip" contains information on detections, strategies, decisions, and results based on antipatterns, derived from Spinnaker logs. On the other hand, the file "runtime-detection-notebook-artifacts-20250524T182033Z-1-001.zip" displays instructions for executing, collecting, and orchestrating Spinnaker, as well as for gathering and processing its logs. Additionally, there is a dataset of logs available for three types of executions: - Initial (toy example), - Intermediate (with a small "hello world" flow inside Spinnaker), and - Complete (focused on achieving more functionalities). References: - [1] L. H. de Braz, B. B. N. de França, and B. B. P. Cafeo, “Dynamic Analysis for Detecting Microservices Antipatterns,” Anais do XIX Simpósio Brasileiro de Componentes, Arquiteturas e Reutilização de Software (SBCARS 2025). Sociedade Brasileira de Computação, pp. 67–78, Sep. 22, 2025. doi: 10.5753/sbcars.2025.14576. - [2] L. H. de Braz, "Microservice Antipatterns: an approach for detection using dynamic analysis", Computer Science Dissertation. Dec. 04, 2025.
DOI: 10.57841/casdc.0006994
title: 有机微晶阵列在超低磁场下产生巨磁光致发光用于片上光学磁强计论文数据集
DOI: 10.15468/dl.c82kjw
title: Occurrence Download

description: A dataset listing the 2398882 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Europe, North America, Asia)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 2398882 records were derived from 59702 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004755-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15547954
title: AIS_BaTh_v1

description: This file is the data availability for the basal thermal state of the Antarctic ice sheet as seen in Seiner et al. (2025). This netcdf file includes the x and y coordinate vectors (in km), binary results from the ISMIP6 modeling of the basal thermal temperature, results from the basal slip method, outputs from the subglacial hydrologic routing including all subglacial lakes and only active subglacial lakes, as well as the agreement map generated from the ISMIP6 modeling and the basal slip method.
DOI: 10.5281/zenodo.15547955
title: AIS_BaTh_v1

description: This file is the data availability for the basal thermal state of the Antarctic ice sheet as seen in Seiner et al. (2025). This netcdf file includes the x and y coordinate vectors (in km), binary results from the ISMIP6 modeling of the basal thermal temperature, results from the basal slip method, outputs from the subglacial hydrologic routing including all subglacial lakes and only active subglacial lakes, as well as the agreement map generated from the ISMIP6 modeling and the basal slip method.
DOI: 10.5281/zenodo.15556691
title: AIS_BaTh_v1

description: This file is the data availability for the basal thermal state of the Antarctic ice sheet as seen in Seiner et al. (2025). This netcdf file includes the x and y coordinate vectors (in km), binary results from the ISMIP6 modeling of the basal thermal temperature, results from the basal slip method, outputs from the subglacial hydrologic routing including all subglacial lakes and only active subglacial lakes, as well as the agreement map generated from the ISMIP6 modeling and the basal slip method.
DOI: 10.15468/dl.ua3wnt
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thunnus albacares",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1930",
 "Year is less than or equal to 1939"
 ]
}

 The dataset includes 4 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006751-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qyab4j
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Begonia confinis"
 ]
}

 The dataset includes 9 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006752-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ntxbmk
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Begonia embera"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006754-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.km32xn
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thunnus albacares",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1940",
 "Year is less than or equal to 1949"
 ]
}

 The dataset includes 10 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006755-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bfthwu
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thunnus albacares",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1950",
 "Year is less than or equal to 1959"
 ]
}

 The dataset includes 36 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006757-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15472028
title: BHDSM Code and Data

description: Code and datasets used in the manuscript "Use of a Bayesian hierarchical density surface model to estimate seasonal distributions of large whales off the East Coast of the United States with an application to a wind energy area"
DOI: 10.5281/zenodo.15472029
title: BHDSM Code and Data

description: Code and datasets used in the manuscript "Use of a Bayesian hierarchical density surface model to estimate seasonal distributions of large whales off the East Coast of the United States with an application to a wind energy area"
DOI: 10.15468/dl.wv2ac2
title: Occurrence Download

description: A dataset containing 12383 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Cynodon dactylon (L.) Pers.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 12383 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015853-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yd6h6v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Eleutherodactylus coqui Thomas, 1966)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015854-250525065834625/datasets/export for details.
DOI: 10.15468/dl.sshp8a
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Falcataria moluccana",
 "Country is Palau",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024670-250811113504898/datasets/export for details.
DOI: 10.15468/dl.dwbpce
title: Occurrence Download

description: A dataset containing 297000 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Castor fiber"
 ]
}

 The dataset includes 297000 records from 513 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004249-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8052664
title: S17 | KEMIMARKET | KEMI Market List

description: List of chemicals on the market from the Swedish Chemicals Agency (KEMI). Provided by Stellan Fischer, KEMI including Hazard and Exposure scores, documented here. Curated by Reza Aalizadeh, University of Athens and Emma Schymanski, UniLu. Dataset DOI: 10.5281/zenodo.2628786.

Nov 14 2019 update: added CSV of latest file. Nov 21 Update: fixed 3 truncated InChIKeys in CSV and InChIKey file. Feb 6, 2020: fixed SMILES issues in CSV for PubChem import. Jul 24, 2020: fixed two synonyms based on feedback from PubChem for GFMHHNOUDDHEOO-UHFFFAOYSA-N and LAUVMIDRJMQUQL-UHFFFAOYSA-N. 17 July 2022: fixed several SMILES errors in CSV, updated IK file for PubChem deposition. 18 July 2022: fixed truncated SMILES that failed PubChem standardization (LCTORFDMHNKUSG-GJHKVECASA-N). 18 Jun 2023: fixed two SMILES that failed PubChem deposition for ILENATNBFPBMHG-UHFFFAOYSA-N and NOESYZHRGYRDHS-ZYCCASTOSA-N, plus one that failed standardization (JBEHRBTVEGZLAF-UHFFFAOYSA-N).
DOI: 10.5281/zenodo.2628786
title: S17 | KEMIMARKET | KEMI Market List

description: List of chemicals on the market from the Swedish Chemicals Agency (KEMI). Provided by Stellan Fischer, KEMI including Hazard and Exposure scores, documented here. Curated by Reza Aalizadeh, University of Athens and Emma Schymanski, UniLu. Dataset DOI: 10.5281/zenodo.2628786.

Nov 14 2019 update: added CSV of latest file. Nov 21 Update: fixed 3 truncated InChIKeys in CSV and InChIKey file. Feb 6, 2020: fixed SMILES issues in CSV for PubChem import. Jul 24, 2020: fixed two synonyms based on feedback from PubChem for GFMHHNOUDDHEOO-UHFFFAOYSA-N and LAUVMIDRJMQUQL-UHFFFAOYSA-N. 17 July 2022: fixed several SMILES errors in CSV, updated IK file for PubChem deposition. 18 July 2022: fixed truncated SMILES that failed PubChem standardization (LCTORFDMHNKUSG-GJHKVECASA-N). 18 Jun 2023: fixed two SMILES that failed PubChem deposition for ILENATNBFPBMHG-UHFFFAOYSA-N and NOESYZHRGYRDHS-ZYCCASTOSA-N, plus one that failed standardization (JBEHRBTVEGZLAF-UHFFFAOYSA-N).
DOI: 10.15468/dl.ymjssg
title: Occurrence Download

description: A dataset containing 10545 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-83.38876 2.98020,-63.52189 2.98020,-63.52189 10.93515,-83.38876 10.93515,-83.38876 2.98020))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Milvago chimachima",
 "Year 2003-2025"
 ]
}

 The dataset includes 10545 records from 403 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004263-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.et37th
title: Occurrence Download

description: A dataset containing 101619 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Saudi Arabia, Oman, Iraq, Qatar, United Arab Emirates, Lebanon, Syrian Arab Republic, Jordan, Palestine, State of, Israel, Yemen)",
 "OccurrenceStatus is Present",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 101619 records from 175 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004248-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15758239
title: S18 | TSCASURF | TSCA Surfactants

description: Surfactant information compiled from TSCA by James Little while at Eastman Chemical. More information at https://littlemsandsailing.wordpress.com/2011/05/01/identification-of-surfactants-in-commercial-products-by-mass-spectrometry/. Dataset DOI: 10.5281/zenodo.2628791.

Nov 14 update: added CSVs from major sheets of interest. 27 Jun. 2025 update: added merged CSV.
DOI: 10.5281/zenodo.2628791
title: S18 | TSCASURF | TSCA Surfactants

description: Surfactant information compiled from TSCA by James Little while at Eastman Chemical. More information at https://littlemsandsailing.wordpress.com/2011/05/01/identification-of-surfactants-in-commercial-products-by-mass-spectrometry/. Dataset DOI: 10.5281/zenodo.2628791.

Nov 14 update: added CSVs from major sheets of interest. 27 Jun. 2025 update: added merged CSV.