cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16622402.v2
title: Prioritizing health, safety and environmental hazards by integrating risk assessment and analytic hierarchy process techniques in solid waste management facilities

description: The aim of this research was to assess and prioritize risk levels of health, safety, and environmental (HSE) hazards in solid waste management facilities of Tehran, Iran. The risk of HSE hazards was assessed using Fine-Kinney and environmental failure mode and effects analysis (EFMEA) methods and then the high-risk hazards were prioritized for implementing corrective actions by analytic hierarchy process (AHP) considering six criteria of (1) probability of occurrence, (2) severity of consequences, (3) simultaneous HSE effects, and (4-6) feasibility, effectiveness, and cost of corrective actions. A total number of 485 HSE hazards were identified, of which 78% were health and safety hazards and 22% were environmental hazards. The proportions of the transfer and transport, material recovery and composting facilities and landfill sites in the identified hazards were 21%, 38%, and 41%, respectively. Based on the AHP method, the leading hazards in the transfer and transport, material recovery and composting facilities, and landfill sites were exposure to bioaerosol in carwash facilities, exposure to bioaerosols and odor/volatile organic compounds (VOCs) in manual waste separation, and leachate spills in the former landfill site, respectively. This study showed that the hybrid method was an appropriate and reliable tool to prioritize HSE hazards.
DOI: 10.6084/m9.figshare.16622402.v1
title: Prioritizing health, safety and environmental hazards by integrating risk assessment and analytic hierarchy process techniques in solid waste management facilities

description: The aim of this research was to assess and prioritize risk levels of health, safety, and environmental (HSE) hazards in solid waste management facilities of Tehran, Iran. The risk of HSE hazards was assessed using Fine-Kinney and environmental failure mode and effects analysis (EFMEA) methods and then the high-risk hazards were prioritized for implementing corrective actions by analytic hierarchy process (AHP) considering six criteria of (1) probability of occurrence, (2) severity of consequences, (3) simultaneous HSE effects, and (4-6) feasibility, effectiveness, and cost of corrective actions. A total number of 485 HSE hazards were identified, of which 78% were health and safety hazards and 22% were environmental hazards. The proportions of the transfer and transport, material recovery and composting facilities and landfill sites in the identified hazards were 21%, 38%, and 41%, respectively. Based on the AHP method, the leading hazards in the transfer and transport, material recovery and composting facilities, and landfill sites were exposure to bioaerosol in carwash facilities, exposure to bioaerosols and odor/volatile organic compounds (VOCs) in manual waste separation, and leachate spills in the former landfill site, respectively. This study showed that the hybrid method was an appropriate and reliable tool to prioritize HSE hazards.
DOI: 10.5281/zenodo.6671419
title: Aegypius monachus decontaminated gx

description: .
DOI: 10.5281/zenodo.6671418
title: Aegypius monachus decontaminated gx

description: .
DOI: 10.25500/edata.bham.00000850
title: Research data supporting the publication “High-Q 100 GHz Photonic Crystal Resonator Fabricated from a Cyclic Olefin Copolymer”
DOI: 10.34740/kaggle/dsv/3836483
title: Mahanagar Yatayat Dataset
DOI: 10.5281/zenodo.6671472
title: Galeichthys feliceps RB0510 GRAHAM decontaminated gx

description: .
DOI: 10.5281/zenodo.6671471
title: Galeichthys feliceps RB0510 GRAHAM decontaminated gx

description: .
DOI: 10.5281/zenodo.6671496
title: Sylvicola fuscatus decontaminated gx

description: .
DOI: 10.5281/zenodo.6671495
title: Sylvicola fuscatus decontaminated gx

description: .
DOI: 10.5281/zenodo.6671508
title: Enchelyopus cimbrius decontaminated gx

description: .
DOI: 10.5281/zenodo.6671507
title: Enchelyopus cimbrius decontaminated gx

description: .
DOI: 10.5519/qd.p7n7xws1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (8 records)
DOI: 10.5281/zenodo.6671540
title: Heteractis magnifica decontaminated gx

description: .
DOI: 10.5281/zenodo.6671539
title: Heteractis magnifica decontaminated gx

description: .
DOI: 10.6084/m9.figshare.18515420.v1
title: Dev and furrow

description: Raw data for cuticle phenotypes and gene expression in furrow collagen mutants<br>
DOI: 10.21227/59nx-6g46
title: Olfactory EEG data set induced by odors with different  types and concentrations

description: Thirteen odors were used as the stimulating materials, five of which (smelling like rose (A), caramel (B), rotten (C), canned peach (D), and excrement (E)) were selected from the T&T olfactometer (from the Daiichi Yakuhin Sangyo Co., Ltd., Japan) and the remaining eight from essential oils (i.e., mint (F), tea tree (G), coffee (H), rosemary (I), jasmine (J), lemon (K), vanilla (L) and lavender (M)).
DOI: 10.5281/zenodo.6671487
title: Table S1, A Hill Equation for Solid Specific Heat Capacity Calculation

description: Equations for the prediction of Heat Capacity across 53 inorganic solids, technical alloys and refractory ceramics.
DOI: 10.5281/zenodo.6671554
title: Metadata for Reed Warbler Age Diet Paper

description: This dataset comprises metadata which corresponds to a paper prepared for submission entitled "Use of metabarcoding to examine season and ontological variation in prey choice and diet of a generalist songbird, the Eurasian reed warbler". Sample identifiers are given for faecal samples collected from songbirds at Chew Valley Lake in Somerset. Information such as location, date/time of collection, and other environmental data are supplied. Dietary data to be supplied after publication.
DOI: 10.5281/zenodo.5803127
title: Metadata for Reed Warbler Age Diet Paper

description: This dataset comprises metadata which corresponds to a paper prepared for submission entitled "Use of metabarcoding to examine season and ontological variation in prey choice and diet of a generalist songbird, the Eurasian reed warbler". Sample identifiers are given for faecal samples collected from songbirds at Chew Valley Lake in Somerset. Information such as location, date/time of collection, and other environmental data are supplied. Dietary data to be supplied after publication.
DOI: 10.5281/zenodo.6671582
title: Replication Data for: Geometric Transformers for Protein Interface Contact Prediction

description: This dataset contains replication data for the paper titled "Geometric Transformers for Protein Interface Contact Prediction". The dataset consists of pickled Python dictionaries containing pairs of DGLGraphs that can be used to train and validate protein interface contact prediction models. It also contains our best model checkpoints saved as PyTorch LightningModules. Our GitHub repository, DeepInteract, linked in the "Additional notes" metadata section below provides more details on how we use these files as examples for cross-validation.
description: This dataset can be used for training and cross-validation of protein interface contact prediction models via our GitHub repository for DeepInteract (https://github.com/BioinfoMachineLearning/DeepInteract).
DOI: 10.5281/zenodo.5546774
title: Replication Data for: Geometric Transformers for Protein Interface Contact Prediction

description: This dataset contains replication data for the paper titled "Geometric Transformers for Protein Interface Contact Prediction". The dataset consists of pickled Python dictionaries containing pairs of DGLGraphs that can be used to train and validate protein interface contact prediction models. It also contains our best model checkpoints saved as PyTorch LightningModules. Our GitHub repository, DeepInteract, linked in the "Additional notes" metadata section below provides more details on how we use these files as examples for cross-validation.
description: This dataset can be used for training and cross-validation of protein interface contact prediction models via our GitHub repository for DeepInteract (https://github.com/BioinfoMachineLearning/DeepInteract).
DOI: 10.6084/m9.figshare.20102690.v1
title: Supplementary_table_3.xlsx

description: Supplementary table 3. Table reporting the Spearman correlation coefficients between expression levels of DE miRNAs and CRC-relevant genes located in 8q24 in A) Adjacent mucosa and B) Tumor tissue.
DOI: 10.6084/m9.figshare.20102690
title: Supplementary_table_3.xlsx

description: Supplementary table 3. Table reporting the Spearman correlation coefficients between expression levels of DE miRNAs and CRC-relevant genes located in 8q24 in A) Adjacent mucosa and B) Tumor tissue.
DOI: 10.6084/m9.figshare.20102714
title: Supplementary_table_1.xlsx

description: Supplementary table 1. miRNAs in the 8q24 region detected in the tumor tissue and adjacent mucosa of colorectal patients: A) comparison in the whole group; B) tumor tissue stratified by stage vs adjacent mucosa; C) tumor tissue stratified by grade vs adjacent mucosa; D)tumor tissue stratified by tumor localization (colon or rectum) vs adjacent mucosa.
DOI: 10.6084/m9.figshare.20102714.v1
title: Supplementary_table_1.xlsx

description: Supplementary table 1. miRNAs in the 8q24 region detected in the tumor tissue and adjacent mucosa of colorectal patients: A) comparison in the whole group; B) tumor tissue stratified by stage vs adjacent mucosa; C) tumor tissue stratified by grade vs adjacent mucosa; D)tumor tissue stratified by tumor localization (colon or rectum) vs adjacent mucosa.
DOI: 10.5281/zenodo.6670391
title: bulk-tumour-api: a programmatically accessible dataset of pre-processed bulk tumour sequencing data

description: <strong>This repository, including the API, are currently under development.</strong> <strong>bulk-tumour-api</strong>: A programmatically accessible dataset of pre-processed bulk tumour sequencing data. The python API can be found at https://github.com/tomouellette/bulk-tumour-api. All data stored in this repository have been collected from open access online sources. Original references and sources are provided in database.tsv (for empirical patient data) and synthetic.tsv (for simulated data). <strong>A note on datasets: </strong> All <em>empirical patient sequencing </em>samples have been processed into pseudo-VCF files which at minimum contain the following columns: sample identifier (sample), patient identifier (patient), chromosome (chr), position (pos), variant allele frequency (VAF), alternate read counts (t_alt_count), depth (DP), and total copy number (total_cn). However, if more data is required, unprocessed data including copy number segments or gene-level calls, clinical, and/or biopsy level information can be found in the /raw/. All <em>synthetic datasets </em>have also been processed in pseudo-VCF files. In some cases, all ground truth information (e.g. subclone frequency) is contained within the pseudo-VCF. In other cases, additional meta/ground-truth information are in separate files; any simulated sample with a column marked has_meta = True will have multiple files that will be downloaded together.
DOI: 10.5281/zenodo.6670390
title: bulk-tumour-api: a programmatically accessible dataset of pre-processed bulk tumour sequencing data

description: <strong>This repository, including the API, are currently under development.</strong> <strong>bulk-tumour-api</strong>: A programmatically accessible dataset of pre-processed bulk tumour sequencing data. The python API can be found at https://github.com/tomouellette/bulk-tumour-api. All data stored in this repository have been collected from open access online sources. Original references and sources are provided in database.tsv (for empirical patient data) and synthetic.tsv (for simulated data). <strong>A note on datasets: </strong> All <em>empirical patient sequencing </em>samples have been processed into pseudo-VCF files which at minimum contain the following columns: sample identifier (sample), patient identifier (patient), chromosome (chr), position (pos), variant allele frequency (VAF), alternate read counts (t_alt_count), depth (DP), and total copy number (total_cn). However, if more data is required, unprocessed data including copy number segments or gene-level calls, clinical, and/or biopsy level information can be found in the /raw/. All <em>synthetic datasets </em>have also been processed in pseudo-VCF files. In some cases, all ground truth information (e.g. subclone frequency) is contained within the pseudo-VCF. In other cases, additional meta/ground-truth information are in separate files; any simulated sample with a column marked has_meta = True will have multiple files that will be downloaded together.
DOI: 10.5281/zenodo.6670234
title: Exploratory Topic Modelling in Python Dataset - EHRI-3

description: In the EHRI-3 project, we are investigating tools and methods that historical researchers and scholars can use to better understand, visualise, and interpret the material held by our partner archives. This dataset accompanies a tutorial exploring a technique called topic modelling in the context of a Holocaust-related historical collection. We were on the lookout for datasets that would be easily accessible and, for convenience, predominantly in English. One such dataset was the United States Holocaust Memorial Museum’s (USHMM) extensive collection of oral history testimonies, for which there are a considerable number of textual transcripts. The museum’s total collection consists of over 80,703 testimonies, 41,695 of which are available in English, with 2,894 of them listing a transcript. Since there is not yet a ready-to-download dataset that includes these transcripts, we had to construct our own. Using a web scraping tool, we managed to create a list of the links pointing to the metadata (including transcripts) of the testimonies that were of interest to us. After obtaining the transcript and other metadata of each of these testimonies, we were able to create our dataset and curate it to remove any unwanted entries. For example, we made sure to remove entries with restrictions on access or use. We also removed entries with transcripts that consisted only of some automatically generated headers and entries which turned out to be in languages other than English. The remaining 1,873 transcripts form the corpus of this tutorial — a small, but still decently sized dataset. The process that we followed to put together this dataset is detailed in the Jupyter Notebook accompanying this post, which can be found in this Github repository. In this Zenodo upload, the user can find two files, each of them containing a pickled pandas DataFrame that was obtained at a different stage of the tutorial: "unrestricted_df.pkl" contains 1,946 entries of Oral Testimony transcripts and has five fields (RG_number, text, display_date, conditions_access, conditions_use)<br> "unrestricted_lemmatized_df.pkl" contains 1,873 entries of Oral Testimony transcripts and has six fields (RG_number, text, display_date, conditions_access, conditions_use, lemmas) Instructions on their intended use can be found in the accompanying Jupyter Notebook. Credits: The transcripts that form the corpus in this tutorial were obtained through the United States Holocaust Memorial Museum (USHMM).
description: Credits: The transcripts that form the corpus in this tutorial were obtained through the United States Holocaust Memorial Museum (USHMM).
DOI: 10.5281/zenodo.6670103
title: Exploratory Topic Modelling in Python Dataset - EHRI-3

description: In the EHRI-3 project, we are investigating tools and methods that historical researchers and scholars can use to better understand, visualise, and interpret the material held by our partner archives. This dataset accompanies a tutorial exploring a technique called topic modelling in the context of a Holocaust-related historical collection. We were on the lookout for datasets that would be easily accessible and, for convenience, predominantly in English. One such dataset was the United States Holocaust Memorial Museum’s (USHMM) extensive collection of oral history testimonies, for which there are a considerable number of textual transcripts. The museum’s total collection consists of over 80,703 testimonies, 41,695 of which are available in English, with 2,894 of them listing a transcript. Since there is not yet a ready-to-download dataset that includes these transcripts, we had to construct our own. Using a web scraping tool, we managed to create a list of the links pointing to the metadata (including transcripts) of the testimonies that were of interest to us. After obtaining the transcript and other metadata of each of these testimonies, we were able to create our dataset and curate it to remove any unwanted entries. For example, we made sure to remove entries with restrictions on access or use. We also removed entries with transcripts that consisted only of some automatically generated headers and entries which turned out to be in languages other than English. The remaining 1,873 transcripts form the corpus of this tutorial — a small, but still decently sized dataset. The process that we followed to put together this dataset is detailed in the Jupyter Notebook accompanying this post, which can be found in this Github repository. In this Zenodo upload, the user can find two files, each of them containing a pickled pandas DataFrame that was obtained at a different stage of the tutorial: "unrestricted_df.pkl" contains 1,946 entries of Oral Testimony transcripts and has five fields (RG_number, text, display_date, conditions_access, conditions_use)<br> "unrestricted_lemmatized_df.pkl" contains 1,873 entries of Oral Testimony transcripts and has six fields (RG_number, text, display_date, conditions_access, conditions_use, lemmas) Instructions on their intended use can be found in the accompanying Jupyter Notebook. Credits: The transcripts that form the corpus in this tutorial were obtained through the United States Holocaust Memorial Museum (USHMM).
description: Credits: The transcripts that form the corpus in this tutorial were obtained through the United States Holocaust Memorial Museum (USHMM).
DOI: 10.5255/ukda-sn-855705
title: Chinese Communities: Family Ethnography Data, 2017-2020

description: 10 families of different types (SES) and structures (e.g. nuclear, extended, single-parent) were observed. The data provide insight into family members’ ideological positions that can be congruent or conflictual and which may cause conflicting views about how to raise bilingual children. Interactional data capture the actual language practices in families across the communities. The data also allow us to observe the silent cultural conversations among family members, and to identify the critical moments of policy enactment.
DOI: 10.5255/ukda-sn-855704
title: Family Language Policy: National Survey, 2017-2019

description: This large-scale survey of Family Language Policy (FLP) looks into what types of FLP exist in private domains in the current UK society and how mobility and on-going changes in sociocultural contexts impact on the linguistic configurations of transnational families and language practice patterns in transnational and non-transnational families. A total of 385 participants from various ethnic backgrounds, and different cities and regions filled in questionnaire.
DOI: 10.34740/kaggle/dsv/3835347
title: Automotive Service Data
DOI: 10.6073/pasta/b04f2cbdc48930015722bd5d5c7fe010
title: A Global database of methane concentrations and atmospheric fluxes for streams and rivers

description: This dataset, referred to as MethDB, is a collation of publicly available values of methane (CH4) concentrations and atmospheric fluxes for world streams and rivers, along with supporting information on location, geographic, physical, and chemical conditions of the study sites. The data set is composed of four linked tables, corresponding to the data sources (Papers_MethDB), the study sites (Sites_MethDB), concentrations (Concentrations_MethDB), and influx/efflux rates (Fluxes_MethDB). Information was extracted from journal articles, government reports, book chapters, and similar sources that were acquired before 15 September 2015. Concentrations and fluxes were converted to a standard unit (micromoles per liter for concentration and millimoles per square meter per day for flux) and both the author-reported and converted data are included in the database. MethDB was assembled as part of a larger synthesis effort on stream and river CH4 dynamics, and assembled data were used to identify large-scale patterns and potential drivers of fluvial CH4 and to generate an updated global-scale estimate of CH4 emissions from world rivers.
DOI: 10.21227/dwex-hm52
title: A purely spaceborne open source approach for regional bathymetry mapping: Bahamas Median DEM

description: Timely and up-to-date bathymetry maps over large geographical areas have been difficult to create, due to the cost and difficulty of collecting in situ calibration and validation data. Recently, combinations of spaceborne ICESat-2 lidar data and Landsat/Sentinel-2 data have reduced these obstacles. However, to date there have been no means of automatically extracting bathymetry photons from ICESat-2 tracks for model calibration/validation and no well established open source workflows for generating regional scale bathymetric models. Here we provide an open source approach for generating bathymetry maps for the shallow water region around the island of Andros, Bahamas. We demonstrate an efficient means of processing 224 ICESat-2 tracks and 221 Landsat-8 scenes, using the C-SHELPh algorithm and Extra Trees Regression to provide 30 m pixel estimates of per-pixel depth and standard error. We map bathymetry with an RMSE of 0.32 m and RMSE% of 6.7 \%. Our workflow and results demonstrate a means of achieving accurate regional--scale bathymetry maps from purely spaceborne data.
DOI: 10.3886/e123541v1-121180
title: National Neighborhood Data Archive (NaNDA): Liquor, Tobacco, and Convenience Stores by Census Tract, United States, 2003-2017

description: This dataset contains measures of the number and density of liquor, tobacco, and convenience stores per United States census tract from 2003 through 2017.
description: Liquor, tobacco, and convenience stores in all census tracts in the United States, including Puerto Rico and the US Virgin Islands. Smallest Geographic Unit: census tract
DOI: 10.6084/m9.figshare.20102816
title: SM2_PanOrtho.xlsx

description: Supplemental Material 2
DOI: 10.6084/m9.figshare.20102816.v2
title: SM2_PanOrtho.xlsx

description: Supplemental Material 2
DOI: 10.6084/m9.figshare.20102816.v1
title: SM2_PanOrtho.xlsx

description: Supplemental Material 2
DOI: 10.25573/data.20102891
title: BCI Evaporation method comparison

description: In order to evaluate the evaporation estimates using Bellini plate atmometer, a comparison study was carried out from 1997 to 2001, we operated a side-by-side set of continuous measurements, in the lab clearing, comparing the Bellini plate atmometers and a 1.2-meter diameter, insulated, type-A evaporation pans of the type used by the Panama Canal Authority. Up to three Bellani-plate gages were located next to a Pan and observed for more than 5 years.
DOI: 10.25573/data.20102891.v1
title: BCI Evaporation method comparison

description: In order to evaluate the evaporation estimates using Bellini plate atmometer, a comparison study was carried out from 1997 to 2001, we operated a side-by-side set of continuous measurements, in the lab clearing, comparing the Bellini plate atmometers and a 1.2-meter diameter, insulated, type-A evaporation pans of the type used by the Panama Canal Authority. Up to three Bellani-plate gages were located next to a Pan and observed for more than 5 years.