cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4513747
title: MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2006 at 1-km

description: Layers include: Land Surface Temperature daytime low (0.05), median (0.50) and high (0.95) temperatures for the year 2006. Derived using the data.table package and quantile function in R. For more info about the MODIS LST product see: https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod11a2_v006. Antarctica is not included. To access and visualize maps use: OpenLandMap.org To download and compute with maps using Cloud-Optimized-GeoTIFF see <strong>this tutorial</strong>. If you discover a bug, artifact or inconsistency in the OpenLandMap maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/-/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, lst = variable: land surface temperature, mod11a2.daytime = determination method: MOD11A2 product, day time values, d = median value / sd = standard deviation / u.95 = aggregation/statistics method: 95% probability upper quantile, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2000..2020 = time reference: from 2000 to 2020, v1.1 = version number: 1.1,
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.5281/zenodo.4513746
title: MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2006 at 1-km

description: Layers include: Land Surface Temperature daytime low (0.05), median (0.50) and high (0.95) temperatures for the year 2006. Derived using the data.table package and quantile function in R. For more info about the MODIS LST product see: https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod11a2_v006. Antarctica is not included. To access and visualize maps use: OpenLandMap.org To download and compute with maps using Cloud-Optimized-GeoTIFF see <strong>this tutorial</strong>. If you discover a bug, artifact or inconsistency in the OpenLandMap maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/-/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, lst = variable: land surface temperature, mod11a2.daytime = determination method: MOD11A2 product, day time values, d = median value / sd = standard deviation / u.95 = aggregation/statistics method: 95% probability upper quantile, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2000..2020 = time reference: from 2000 to 2020, v1.1 = version number: 1.1,
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.6084/m9.figshare.13725970
title: Supplementary Figure – D614 vs N501 ( SARS-COV-2 ) Mutants Data Analysis

description: Bioenergetics data ( DEL2G ) of interaction between D614G mutants vs N501Y mutants are statistically analysed to find out the correlation study .
DOI: 10.6084/m9.figshare.13726018
title: Data set for Muslim study

description: Climatic and social data for 145 countries.<br>
DOI: 10.6084/m9.figshare.13726018.v1
title: Data set for Muslim study

description: Climatic and social data for 145 countries.<br>
DOI: 10.5281/zenodo.4514397
title: RoB 2 details for Cochrane Review '(Ultra-)long-acting insulin analogues for people with type 1 diabetes mellitus'

description: Systematic review and meta-analysis on to compare the effects of long-term treatment with (ultra-)long-acting insulin analogues to NPH insulin (neutral protamine Hagedorn) or another (ultra-)long-acting insulin analogue in people with type 1 diabetes mellitus. Details of the Cochrane risk of bias 2 (RoB 2) tool.
DOI: 10.5281/zenodo.4514396
title: RoB 2 details for Cochrane Review '(Ultra-)long-acting insulin analogues for people with type 1 diabetes mellitus'

description: Systematic review and meta-analysis on to compare the effects of long-term treatment with (ultra-)long-acting insulin analogues to NPH insulin (neutral protamine Hagedorn) or another (ultra-)long-acting insulin analogue in people with type 1 diabetes mellitus. Details of the Cochrane risk of bias 2 (RoB 2) tool.
DOI: 10.34740/kaggle/dsv/1915822
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.4511796
title: Mask Dataset for: Unconstrained Text Detection in Manga: a New Dataset and Baseline

description: This is the dataset used in out paper "Unconstrained Text Detection in Manga: a New Dataset and Baseline". It contains 450 images with the text segmentation of images from Manga109 dataset (need to request access to this dataset in order to view original manga image). Pre-processed version of the images is how they were saved straight out of GIMP. These were later processed before using for training. Post-processed version of the images is after automatically removing small connected components and filling small holes. They are also slightly bigger in width/height in order to be multiples of 8. The text is split in 2 colors: black and pink. Text in black represents text we consider easy to recognize, which is mostly when inside a speech bubble. Text in pink represents text we consider harder to detect, such as text in covers, sound effects or text outside speech bubbles. Further details can be found in our paper.
DOI: 10.5281/zenodo.4511795
title: Mask Dataset for: Unconstrained Text Detection in Manga: a New Dataset and Baseline

description: This is the dataset used in out paper "Unconstrained Text Detection in Manga: a New Dataset and Baseline". It contains 450 images with the text segmentation of images from Manga109 dataset (need to request access to this dataset in order to view original manga image). Pre-processed version of the images is how they were saved straight out of GIMP. These were later processed before using for training. Post-processed version of the images is after automatically removing small connected components and filling small holes. They are also slightly bigger in width/height in order to be multiples of 8. The text is split in 2 colors: black and pink. Text in black represents text we consider easy to recognize, which is mostly when inside a speech bubble. Text in pink represents text we consider harder to detect, such as text in covers, sound effects or text outside speech bubbles. Further details can be found in our paper.
DOI: 10.17632/thshz3pghm.1
title: Data for: Characteristics of drag due to streamwise inhomogeneous roughness

description: RANS simulations of skin friction drag of streamwise inhomogeneous rough surfaces
DOI: 10.6084/m9.figshare.13726120
title: Información adicional al artículo (Seijas y Uskola, 2021).pdf

description: <b>Información adicional al artículo: ¿Qué hipótesis formulan y en qué las basan los estudiantes de grado de Educación Primaria al analizar la formación de un diapiro? <br></b><br><b>Concretamente, se adjunta el ejemplo de análisis de los momentos de hipótesis del grupo A (sesión 5).</b>
DOI: 10.6084/m9.figshare.13726120.v1
title: Información adicional al artículo (Seijas y Uskola, 2021).pdf

description: <b>Información adicional al artículo: ¿Qué hipótesis formulan y en qué las basan los estudiantes de grado de Educación Primaria al analizar la formación de un diapiro? <br></b><br><b>Concretamente, se adjunta el ejemplo de análisis de los momentos de hipótesis del grupo A (sesión 5).</b>
DOI: 10.5519/qd.vkk3mfpu
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (37 records)
DOI: 10.6084/m9.figshare.13625606
title: SARS-CoV-2 viral loads - French Covid19 cohort

description: Dataset from French Covid Cohort 655 patients<br>time_monolix = Time of symptom onset + 14 daysdelay_monolix = Time of hospital admission + 14 days<br>If you use this dataset, please cite as follows :The French COVID cohort was conducted and supported by Inserm in collaboration with the French COVID cohort investigators and study group. <br>This manuscript was prepared using a limited-access data set obtained from Néant et al (https://doi.org/10.1073/pnas.2017962118). <br>The present reanalysis did not involve researchers from INSERM and does not necessarily reflect the opinions or views of the French COVID cohort investigators and study group or INSERM.<br>
DOI: 10.5519/qd.7koe4t4v
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6073/pasta/268a0738c61fc36244e13c77910bfc4e
title: Hohokam canals as multi-use facilities: Pre-historic canal system in the central Arizona-Phoenix metropolitan area

description: This is the digitized version of a map of the Hohokam canal system in what is now the Phoenix metropolitan area. It is based on the thesis research by J. B. Howard (Howard, J. (1990). Paleohydraulics : techniques for modeling the operation and growth of prehistoric canal systems. Thesis (M.A.)--Arizona State University, 1990). The original paper map is based on previous archaeological data, overlayed onto USGS 7.5 minute quadrangle maps to recreate the canal pattern.
DOI: 10.5519/qd.uak12xe0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (19702 records)
DOI: 10.5517/ccdc.csd.cc24s7ry
title: CCDC 1989510: Experimental Crystal Structure Determination

description: Related Article: Paulo R.S. Salbego, Gustavo H. Weimer, Alexandre R. Meyer, Rafael N. Soek, Ellery R. Garbelini, Fábio S. Nunes, Nilo Zanatta, Helio G. Bonacorso, Manfredo Hörner, Marcos A.P. Martins|2021|J.Mol.Struct.|1231|129942|doi:10.1016/j.molstruc.2021.129942
DOI: 10.5517/ccdc.csd.cc2541lz
title: CCDC 1999890: Experimental Crystal Structure Determination

description: Related Article: Dohyun Moon, Sunghwan Jeon, Milan Mazúr, Marián Valko, Jong-Ha Choi|2021|J.Mol.Struct.|1231|129897|doi:10.1016/j.molstruc.2021.129897
DOI: 10.5517/ccdc.csd.cc2541m0
title: CCDC 1999891: Experimental Crystal Structure Determination

description: Related Article: Dohyun Moon, Sunghwan Jeon, Milan Mazúr, Marián Valko, Jong-Ha Choi|2021|J.Mol.Struct.|1231|129897|doi:10.1016/j.molstruc.2021.129897
DOI: 10.5517/ccdc.csd.cc25g5mg
title: CCDC 2009625: Experimental Crystal Structure Determination

description: Related Article: Ting Pan, Yinuo Wang, Feng-Shou Liu, Huancai Lin, Yan Zhou|2021|Polyhedron|197|115033|doi:10.1016/j.poly.2021.115033
DOI: 10.5517/ccdc.csd.cc25g60w
title: CCDC 2009637: Experimental Crystal Structure Determination

description: Related Article: Vahid Amani, Esmail Owla, Darioush Sharafie|2021|J.Mol.Struct.|1230|129877|doi:10.1016/j.molstruc.2021.129877
DOI: 10.5517/ccdc.csd.cc25hvp7
title: CCDC 2011239: Experimental Crystal Structure Determination

description: Related Article: Zhijun Song, Caiyun Yao, Shuo Wang, Bingxiong Yan, Yunqiu Wu, Shanshan Song, Xihui Liu, Lingling Wu, Xiaomei Gong, Lili He, Zhizhou He, Lijun Ruan, Jianhua Miao|2021|Phytochemistry|184|112659|doi:10.1016/j.phytochem.2021.112659
DOI: 10.5517/ccdc.csd.cc25m2qm
title: CCDC 2014340: Experimental Crystal Structure Determination

description: Related Article: Paulo R.S. Salbego, Gustavo H. Weimer, Alexandre R. Meyer, Rafael N. Soek, Ellery R. Garbelini, Fábio S. Nunes, Nilo Zanatta, Helio G. Bonacorso, Manfredo Hörner, Marcos A.P. Martins|2021|J.Mol.Struct.|1231|129942|doi:10.1016/j.molstruc.2021.129942
DOI: 10.5517/ccdc.csd.cc265mmn
title: CCDC 2031201: Experimental Crystal Structure Determination

description: Related Article: Malathy Selvachandran, Satyendra Kumar, Xiaodong Zhang, Joel T. Mague, James P. Donahue|2021|Polyhedron|196|114985|doi:10.1016/j.poly.2020.114985
DOI: 10.5517/ccdc.csd.cc265mnp
title: CCDC 2031202: Experimental Crystal Structure Determination

description: Related Article: Malathy Selvachandran, Satyendra Kumar, Xiaodong Zhang, Joel T. Mague, James P. Donahue|2021|Polyhedron|196|114985|doi:10.1016/j.poly.2020.114985
DOI: 10.5517/ccdc.csd.cc268h88
title: CCDC 2033949: Experimental Crystal Structure Determination

description: Related Article: Malathy Selvachandran, Satyendra Kumar, Xiaodong Zhang, Joel T. Mague, James P. Donahue|2021|Polyhedron|196|114985|doi:10.1016/j.poly.2020.114985
DOI: 10.5517/ccdc.csd.cc265mpq
title: CCDC 2031203: Experimental Crystal Structure Determination

description: Related Article: Malathy Selvachandran, Satyendra Kumar, Xiaodong Zhang, Joel T. Mague, James P. Donahue|2021|Polyhedron|196|114985|doi:10.1016/j.poly.2020.114985
DOI: 10.5517/ccdc.csd.cc26nrbz
title: CCDC 2045731: Experimental Crystal Structure Determination

description: Related Article: Ji-Fa Wang, Ruo-Yu Li, Peng Li, Wen-Kui Dong|2021|Inorg.Chim.Acta|518|120247|doi:10.1016/j.ica.2021.120247
DOI: 10.5517/ccdc.csd.cc26nrc0
title: CCDC 2045732: Experimental Crystal Structure Determination

description: Related Article: Ji-Fa Wang, Ruo-Yu Li, Peng Li, Wen-Kui Dong|2021|Inorg.Chim.Acta|518|120247|doi:10.1016/j.ica.2021.120247
DOI: 10.5517/ccdc.csd.cc26nrd1
title: CCDC 2045733: Experimental Crystal Structure Determination

description: Related Article: Ji-Fa Wang, Ruo-Yu Li, Peng Li, Wen-Kui Dong|2021|Inorg.Chim.Acta|518|120247|doi:10.1016/j.ica.2021.120247
DOI: 10.5517/ccdc.csd.cc26q076
title: CCDC 2046937: Experimental Crystal Structure Determination

description: Related Article: Yoshinori Ikumura, Yusuke Habuka, Akiko Hori|2021|Polyhedron|197|115035|doi:10.1016/j.poly.2021.115035
DOI: 10.6084/m9.figshare.13633997.v1
title: Corpus of mentions in Polish reputational crises peaks .xlsx

description: This is a corpus of mentions (posts, tweets, retweets, articles, comments to public articles, social media posts and comments, forum discussion comments) concerning three reputational crisis peaks in the Polish language. It also contains mention classification with respect to emotions, topics and communicative actions.
DOI: 10.6084/m9.figshare.13633997.v2
title: Corpus of mentions in Polish reputational crises peaks .xlsxA corpus of texts published online in public and social media about specific reputational crises in Poland

description: This is a corpus of mentions (posts, tweets, retweets, articles, comments to public articles, social media posts and comments, forum discussion comments) concerning three reputational crisis peaks in the Polish language. It also contains mention classification with respect to emotions, topics and communicative actions.
DOI: 10.6084/m9.figshare.13633997
title: Corpus of mentions in Polish reputational crises peaks .xlsxA corpus of texts published online in public and social media about specific reputational crises in Poland

description: This is a corpus of mentions (posts, tweets, retweets, articles, comments to public articles, social media posts and comments, forum discussion comments) concerning three reputational crisis peaks in the Polish language. It also contains mention classification with respect to emotions, topics and communicative actions.
DOI: 10.6084/m9.figshare.13633997.v4
title: Corpus of mentions in Polish reputational crises peaks .xlsxA corpus of texts published online in public and social media about specific reputational crises in Poland

description: This is a corpus of mentions (posts, tweets, retweets, articles, comments to public articles, social media posts and comments, forum discussion comments) concerning three reputational crisis peaks in the Polish language. It also contains mention classification with respect to emotions, topics and communicative actions.
DOI: 10.6084/m9.figshare.13633997.v3
title: Corpus of mentions in Polish reputational crises peaks .xlsxA corpus of texts published online in public and social media about specific reputational crises in Poland

description: This is a corpus of mentions (posts, tweets, retweets, articles, comments to public articles, social media posts and comments, forum discussion comments) concerning three reputational crisis peaks in the Polish language. It also contains mention classification with respect to emotions, topics and communicative actions.
DOI: 10.5281/zenodo.4514689
title: Dataset for Centris

description: Dataset for Centris.
DOI: 10.5281/zenodo.4514688
title: Dataset for Centris

description: Dataset for Centris.
DOI: 10.5281/zenodo.4445287
title: ShallowChrome – preprocessed data

description: Preprocessed data to reproduce results in: Frasca F., Matteucci M., Leone M., Morelli M. J. and Masseroli M. "Accurate and highly interpretable prediction of gene expression from histone modifications", 2021 Code repository at: https://github.com/DEIB-GECO/ShallowChrome
DOI: 10.5281/zenodo.4445286
title: ShallowChrome – preprocessed data

description: Preprocessed data to reproduce results in: Frasca F., Matteucci M., Leone M., Morelli M. J. and Masseroli M. "Accurate and highly interpretable prediction of gene expression from histone modifications", 2021 Code repository at: https://github.com/DEIB-GECO/ShallowChrome
DOI: 10.5517/ccdc.csd.cc249g64
title: CCDC 1975295: Experimental Crystal Structure Determination

description: Related Article: Jakub Brześkiewicz,  Barbara Stańska,  Piotr Dąbrowski,  Rafał Loska|2020|Eur.J.Org.Chem.|2021|814|doi:10.1002/ejoc.202001496
DOI: 10.6073/pasta/c5a25192fbcde6990bf6c72a6f942345
title: Database of Geographic Information: Canals in the Phoenix metropolitan area (1996-1998)
DOI: 10.6084/m9.figshare.13726189
title: Data.xlsx

description: data from listed firms in Saudi Arabia
DOI: 10.5281/zenodo.4514257
title: Semantics-aware dataset for the mono-label supervised classification of animals

description: This image dataset has been derived from Wikimedia Commons (https://commons.wikimedia.org), a large-scale free and collaborative media repository currently including over 92 million items including images, videos and recordings. The dataset includes images of several types of animals. The images are assigned to categories according to the Wikimedia Commons Category Graph and its direct links with the considered medias. As an output of the development of this image dataset, we created three ZIP Files that can be used for the evaluation of the effect of semantic features of considered labels on the efficiency of mono-label image classification algorithms : Class1 (The most general one): The labels are "Birds" and "mammals". Each category precisely includes 450 images. Class2: The labels are "Cat", "Cattle", "Columbidae", "Dog", "Phoenicopteridae", and "Psittacidae". Each category precisely includes 150 images. Class3 (The most granular one): The labels here are "Highland cattle", "‎Holstein Friesian cattle", "Charolais cattle‎", "American Pit Bull Terrier", "‎Belgian Shepherd Malinois", "‎Miniature Schnauzer‎", "Persian cats", "‎Chinchilla (cat)", "‎Bengal cats", "‎Phoeniconaias minor‎", "Phoenicopterus roseus‎", "Phoenicoparrus andinus", "‎Anodorhynchus hyacinthinus‎", "Ara ararauna‎", "Ara macao‎", "Ocyphaps lophotes", "Columbina talpacoti", and "Columba palumbus"‎. Each category precisely includes 50 images.
description: This dataset has been developed to support a forthcoming proceedings paper in KDD 2021. Image Credits: Wikimedia Commons, CC-BY-SA 4.0.
DOI: 10.5519/qd.4x4a8poo
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.25919/7rm1-2240
title: Parkes observations for project P1068 semester 2020APRS_38

description: In the fast-moving world of Fast Radio Bursts (FRBs), the key question of what fraction (as high as 100%?) of FRBs emit repeat bursts remains unanswered. Of order 10 repeating FRBs are now known, and their spectro-temporal properties hint at differences with apparently non-repeating bursts - but poor statistics preclude a definitive diagnosis. FRB 180301 is a promising source for further study for multiple reasons: it is the first repeating FRB seen by the FAST telescope, and has the second-highest rotation measure ever seen for a FRB (after the original repeater, FRB121102). We request Parkes observations with the UWL to characterise the broadband emission properties of this FRB, with the following key goals: to constrain the repetition rate, identify any variation of pulse characteristics over time, and provide insight into the emission mechanisms. In its initial detection, FRB 180301 was poorly fit by regular Faraday rotation models, and showed significant circular polarization, which may indicate the progenitor is embedded in an extreme magneto-ionic environment with complex field structure that has not been seen before. These observations will generate a large data volume. We will use the Medusa backend in parallel with the Breakthrough Listen data recorder (BL), and will transfer data to BL immediately after observations.These data will be used by P. Kumar to prototype a FRB pipeline for the UWL, that will be made broadly available for similar studies.
DOI: 10.34740/kaggle/dsv/1916392
title: US counties COVID 19 dataset
DOI: 10.6084/m9.figshare.12840827
title: Supplemental Table S2. Putative DEG targets of miR-7 upregulated by matrix stiffness.

description: <b>Supplemental Table S1.</b> <b>Ranking of miRNAs according to the number of mechanoactivated differentially expressed gene (DEG) targets.</b>
DOI: 10.6084/m9.figshare.12840827.v1
title: Supplemental Table S2. Putative DEG targets of miR-7 upregulated by matrix stiffness.

description: <b>Supplemental Table S1.</b> <b>Ranking of miRNAs according to the number of mechanoactivated differentially expressed gene (DEG) targets.</b>
DOI: 10.6084/m9.figshare.13726222
title: Screening Data 2017 2018.xlsx

description: Health history, gender, age, blood pressure, blood glucose, total cholesterol, height, weight, and Body Mass Index for a rural tribal population
DOI: 10.6084/m9.figshare.13726222.v1
title: Screening Data 2017 2018.xlsx

description: Health history, gender, age, blood pressure, blood glucose, total cholesterol, height, weight, and Body Mass Index for a rural tribal population
DOI: 10.6084/m9.figshare.12839162
title: Supplemental Table S1. Ranking of miRNAs according to the number of mechanoactivated differentially expressed gene (DEG) targets

description: <b>Supplemental Table S1. Ranking of miRNAs according to the number of mechanoactivated differentially expressed gene (DEG) targets</b><br>
DOI: 10.6084/m9.figshare.12839162.v1
title: Supplemental Table S1. Ranking of miRNAs according to the number of mechanoactivated differentially expressed gene (DEG) targets

description: <b>Supplemental Table S1. Ranking of miRNAs according to the number of mechanoactivated differentially expressed gene (DEG) targets</b><br>
DOI: 10.17632/v686ns7rdm.1
title: Data for: Immigration and Institutional Change: Did Mass Immigration Cause Peronism in Argentina?

description: The Pyhton code attached is used to generate the plots in the paper. I'm afraid, however, that the excel file with the data is not properly uploading to the system. I'll be happy to share the data in an alternative form if possible. We can also upload the Python code and dataset to an online repository.
DOI: 10.6084/m9.figshare.3761562.v1767
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.18112/openneuro.ds003507.v1.0.0
title: fMRI: Audiovisual Valence Congruence