cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/vf6jmvz83b.1
title: Pre-trained Flair and BERT weights (Spanish biomedical literature, SciELO) and corpus

description: This zipped folder includes pre-trained weights of BERT and Flair models. Both of these models were trained from scratch on Spanish biomedical literature texts obtained from SciELO website. The corpus on which the models were trained is also included. It consists of over 86B tokens. More details on the corpus and training process could be found in our paper "Testing Contextualized Word Embeddings to Improve NER in Spanish Clinical Case Narratives", doi: 10.21203/rs.2.22697/v2
DOI: 10.17632/5yvjwnpggg.2
title: Spatiotemporal Content of Saccade Transients

description: This repository contains data associated with the paper "Spatiotemporal Content of Saccade Transients" by Naghmeh Mostofi, Zhetuo Zhao, Janis Intoy, Marco Boi, Jonathan D. Victor, and Michele Rucci
DOI: 10.17632/v4knrwgj9y.1
title: Thermal imagery from composite material academic samples

description: The infrared camera recorded the thermal evolution on the surface of the inspected CFRP/GFRP sample for several seconds (approximately 16 to 17 s) at 120 and 145 frames/s sampling rate, from before applying a heat pulse, during the heat pulse and during cooling. The experiment was performed from the two faces of the specimen (providing shallow defect depths form the front face and deeper depths from the back face), and each sequence was labeled and saved into an independent file. Every .zip file contains a folder and files inside. Both are labeled as CFRP-samplename_facq-frequencyvalue_s-sideofinspection_Img-frames. This tagging scheme describes the sample name tested, the acquisition frequency used, the sample side of inspection taken, as well as the number of each frame (for .CSV files) within the sequence, and the whole number of frames from the image sequence (for the folders), respectively.
DOI: 10.17632/gnp7ybm24n.1
title: Data for: 3659607
DOI: 10.17632/3vf7m4gtzb.1
title: Data for: 3659611

description: This dataset includes every reference to the 1787 United States Constitutional Convention in Supreme Court opinions through the 2019 term. Other variables such as citing justice, case name, year, and portion of the opinion quoting the Convention are included among many other variables.
DOI: 10.17632/jwdskk8rtx.3
title: covid-19 oxygen blender 1

description: the attached file is a complete design for our new covid-19 oxygen blender for home isolation patients,to solve hospital availability for respiratory patients
DOI: 10.13011/m3-geke-ey79
title: dataset test
DOI: 10.5517/ccdc.csd.cc241md7
title: CCDC 1967768: Experimental Crystal Structure Determination

description: Related Article: Sanjit Konar, Arpan Mondal, Subhadip Roy|2020|Chem.-Eur.J.|26|8774|doi:10.1002/chem.202000438
DOI: 10.5517/ccdc.csd.cc24yvb9
title: CCDC 1994891: Experimental Crystal Structure Determination

description: Related Article: Daniel Kim, Chi Chen, Brandon Q. Mercado, Daniel J. Weix, Patrick L. Holland|2020|Organometallics|39|2415|doi:10.1021/acs.organomet.0c00241
DOI: 10.17632/8f556g8mxc.5
title: Data for: Effect of Azamethiphos on enzymatic activity and metabolic fingerprints of marine microbial communities from the water column

description: The general objective of this study was to determine the effect of different concentrations of the pesticide Azamethiphos on the metabolism of microbial plankton communities (&lt;100 µm) in two contrasting zones, one without salmon farming and the other with a high level of aquaculture activity. Several methodological approaches were used, including the enzymatic activity of β-glucosidase and malate dehydrogenase (MDH), fingerprinting techniques (EcoPlates for bacteria and FF microplate for marine fungi) and the estimation of microbial aerobic respiration. The data set contains the results from the experiments conducted. Variables; ATP [nM] MDH µmol min-1 L-1 β- glucosidase [nmol h-1mL-1] NO2 [µmol/L] PO4 [µmol/L] SILICATE [µmol/L] NO3 [µmol/L] Chlorophyll-a [mg Cl-a m-3] Pheopigments [mg feop m-3]
DOI: 10.17632/8f556g8mxc.6
title: Data for: Effect of Azamethiphos on enzymatic activity and metabolic fingerprints of marine microbial communities from the water column

description: The general objective of this study was to determine the effect of different concentrations of the pesticide Azamethiphos on the metabolism of microbial plankton communities (&lt;100 µm) in two contrasting zones, one without salmon farming and the other with a high level of aquaculture activity. Several methodological approaches were used, including the enzymatic activity of β-glucosidase and malate dehydrogenase (MDH), fingerprinting techniques (EcoPlates for bacteria and FF microplate for marine fungi) and the estimation of microbial aerobic respiration. The data set contains the results from the experiments conducted. Variables; ATP [nM] MDH µmol min-1 L-1 β- glucosidase [nmol h-1mL-1] NO2 [µmol/L] PO4 [µmol/L] SILICATE [µmol/L] NO3 [µmol/L] Chlorophyll-a [mg Cl-a m-3] Pheopigments [mg feop m-3]
DOI: 10.5281/zenodo.3950379
title: SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)

description: The task involves three subtasks corresponding to the hierarchical taxonomy of the OLID schema (Zampieri et al., 2019) from OffensEval 2019. The task featured five languages and this upload is for the English language. In addition, English also featured Subtasks B and C. OffensEval 2020 was one of the most popular tasks at SemEval-2020 attracting a large number of participants across all subtasks and also across all languages. A total of 528 teams signed up to participate in the task, 145 teams submitted systems during the evaluation period, and 70 submitted system description papers. This upload includes a test set used in the paper describing the dataset used in the shared task as well as the official test set used in the shared task. The evaluation phase for English is available on Codalab: https://competitions.codalab.org/competitions/23285 The Website for the shared task is https://sites.google.com/site/offensevalsharedtask/home
description: {"references": ["Rosenthal, Sara, et al. \"A large-scale semi-supervised dataset for offensive language identification.\" arXiv preprint arXiv:2004.14454 (2020).", "Zampieri, Marcos, et al. \"SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020).\" arXiv preprint arXiv:2006.07235 (2020)."]}
DOI: 10.5281/zenodo.3950378
title: SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)

description: The task involves three subtasks corresponding to the hierarchical taxonomy of the OLID schema (Zampieri et al., 2019) from OffensEval 2019. The task featured five languages and this upload is for the English language. In addition, English also featured Subtasks B and C. OffensEval 2020 was one of the most popular tasks at SemEval-2020 attracting a large number of participants across all subtasks and also across all languages. A total of 528 teams signed up to participate in the task, 145 teams submitted systems during the evaluation period, and 70 submitted system description papers. This upload includes a test set used in the paper describing the dataset used in the shared task as well as the official test set used in the shared task. The evaluation phase for English is available on Codalab: https://competitions.codalab.org/competitions/23285 The Website for the shared task is https://sites.google.com/site/offensevalsharedtask/home
description: {"references": ["Rosenthal, Sara, et al. \"A large-scale semi-supervised dataset for offensive language identification.\" arXiv preprint arXiv:2004.14454 (2020).", "Zampieri, Marcos, et al. \"SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020).\" arXiv preprint arXiv:2006.07235 (2020)."]}
DOI: 10.5281/zenodo.3958257
title: SC20 HPC Workload Analysis Dataset

description: This repository contains the job trace dataset for an analysis publication submitted to SC20.
DOI: 10.7910/dvn/5rs7wx/yxaqax
title: app_paper_fig_3.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/9f4hxw
title: paper_fig_3.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/eshq11
title: paper_fig_6c.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/u5dibz
title: header.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/9a72pq
title: app_paper_fig_8.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/msr2rr
title: README.txt

description: :unav
DOI: 10.7910/dvn/5rs7wx/th1lsp
title: app_paper_fig_1.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/z8cq4m
title: appx_paper_fig_9.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/bezunk
title: appx_paper_fig_1.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/iuxf0v
title: paper_fig_3c.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/tfiwnk
title: paper_fig_3a.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/jvosf7
title: appx_paper_fig_4.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/djiiz1
title: paper_fig_4.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/g1anu6
title: appx_paper_fig_2acd.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/5orc4k
title: paper_fig_1a.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/yg6wku
title: paper_tab_4.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/6infbs
title: appx_paper_fig_3a.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/96xetc
title: paper_fig_6a.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/1shfvq
title: mrc_table15.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/egza32
title: paper_fig_2.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/u5uf8j
title: paper_fig_5.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/zruuph
title: app_paper_fig_9.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/a5flft
title: app_paper_fig_5.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/iatvpc
title: appx_paper_fig_2b.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/zzqdt1
title: paper_fig_2.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/na3nko
title: paper_tab_2.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/hqqcyh
title: tables_from_microdata.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/wbkdbv
title: appx_paper_fig_8.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/8atka5
title: app_paper_fig_2.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/0e6lbf
title: appx_paper_fig_3b.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/2zu2k5
title: paper_fig_3b.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/f0aqua
title: paper_tab_1.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/igslhn
title: paper_fig_5b.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/zbhff4
title: paper_fig_5a.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/htcfic
title: appx_paper_fig_7.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/u7esr0
title: appx_paper_fig_6.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/7acz2g
title: app_paper_fig_10.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/jsaa9o
title: app_paper_fig_6.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/qq0uwm
title: paper_tab_5.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/kahvpk
title: paper_fig_6.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/r3pklj
title: paper_fig_1.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/6o1ndz
title: paper_fig_6b.tab

description: :unav
DOI: 10.7910/dvn/5rs7wx/d8aren
title: app_paper_fig_7.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/qc0aqr
title: draw_paper_figs_tabs.do

description: :unav
DOI: 10.7910/dvn/5rs7wx/ku1fnb
title: app_paper_fig_4.do

description: :unav
DOI: 10.17632/8f556g8mxc.7
title: Data for: Effect of Azamethiphos on enzymatic activity and metabolic fingerprints of marine microbial communities from the water column

description: The general objective of this study was to determine the effect of different concentrations of the pesticide Azamethiphos on the metabolism of microbial plankton communities (&lt;100 µm) in two contrasting zones, one without salmon farming and the other with a high level of aquaculture activity. Several methodological approaches were used, including the enzymatic activity of β-glucosidase and malate dehydrogenase (MDH), fingerprinting techniques (EcoPlates for bacteria and FF microplate for marine fungi) and the estimation of microbial aerobic respiration. The data set contains the results from the experiments conducted. Variables; ATP [nM] MDH µmol min-1 L-1 β- glucosidase [nmol h-1mL-1] NO2 [µmol/L] PO4 [µmol/L] SILICATE [µmol/L] NO3 [µmol/L] Chlorophyll-a [mg Cl-a m-3] Pheopigments [mg feop m-3]
DOI: 10.5281/zenodo.3958266
title: The scalogram of the Radio Frequency Interference (RFI) signals

description: This dataset includes the scalogram of RFI signals for RFI classification and Modulation recognition application. In this dataset, SoI is a video stream transmitted based on DVB-S2 standards in a real-time Satellite to Ground communication. CWI refers to a combination of SoI with Continous Wave Interference (CWI) MCWI is also a combination of SoI with Multi-CWI and CI indicates the combination of SoI with Chirp Interference. Moreover, SoI has been transmitted in four different modulation types namely QPSK, 8APSK, 16APSK and 32APSK.
DOI: 10.5281/zenodo.3958265
title: The scalogram of the Radio Frequency Interference (RFI) signals

description: This dataset includes the scalogram of RFI signals for RFI classification and Modulation recognition application. In this dataset, SoI is a video stream transmitted based on DVB-S2 standards in a real-time Satellite to Ground communication. CWI refers to a combination of SoI with Continous Wave Interference (CWI) MCWI is also a combination of SoI with Multi-CWI and CI indicates the combination of SoI with Chirp Interference. Moreover, SoI has been transmitted in four different modulation types namely QPSK, 8APSK, 16APSK and 32APSK.
DOI: 10.25345/c5t17z
title: MassIVE MSV000085822 - Identification of the global histone posttranslational modification landscape in kidney of euryhaline tilapia
title: Experiments were performed by Elizabeth Mojica in the laboratory of Dietmar K&uumlltz at UC Davis. Sample preparation was based on histone acid extraction combined with a modification of a previously published protocol (https://doi.org/10.1074/mcp.M113.029827). Partial trypsin digestion was performed for 6h at a ratio of 1:50. Biological mass spectrometry (Bottom-up proteomics) was performed in the K&uumlltz laboratory. Samples represent a single biological replicate processed using an identical procedure.
DOI: 10.17632/8f556g8mxc.8
title: Data for: Effect of Azamethiphos on enzymatic activity and metabolic fingerprints of marine microbial communities from the water column

description: The general objective of this study was to determine the effect of different concentrations of the pesticide Azamethiphos on the metabolism of microbial plankton communities (&lt;100 µm) in two contrasting zones, one without salmon farming and the other with a high level of aquaculture activity. Several methodological approaches were used, including the enzymatic activity of β-glucosidase and malate dehydrogenase (MDH), fingerprinting techniques (EcoPlates for bacteria and FF microplate for marine fungi) and the estimation of microbial aerobic respiration. The data set contains the results from the experiments conducted. Variables; ATP [nM] MDH µmol min-1 L-1 β- glucosidase [nmol h-1mL-1] NO2 [µmol/L] PO4 [µmol/L] SILICATE [µmol/L] NO3 [µmol/L] Chlorophyll-a [mg Cl-a m-3] Pheopigments [mg feop m-3]
DOI: 10.5281/zenodo.3749292
title: Experimental Data for Emergent Helical Texture of Electric Dipoles

description: BiCu0.1Mn6.9O12_NPD.zip contains TOF neutron powder diffraction patterns collected in the temperature range of 100K-600K BiCu0.1Mn6.9O12_XRPD_T300K.txt is room temperature X-ray synchrotron powder diffraction pattern BiCu0.05Mn6.95O12-105.51mg-exp-Dec-06-2016-DSC.prn contains differential scanning calorimetry data BiCu0.1Mn6.9O12-109.89mg-exp-Nov-08-2016-DSC.prn contains differential scanning calorimetry data BiCu0.1Mn6.9O12_PE_loop_data_T77K.dat is P-E loop data
description: R.D.J. acknowledges support from a Royal Society University Research Fellowship and A.A.B. acknowledges partial support from grant JPJ004596 (ATLA, Japan).
DOI: 10.5281/zenodo.3749291
title: Experimental Data for Emergent Helical Texture of Electric Dipoles

description: BiCu0.1Mn6.9O12_NPD.zip contains TOF neutron powder diffraction patterns collected in the temperature range of 100K-600K BiCu0.1Mn6.9O12_XRPD_T300K.txt is room temperature X-ray synchrotron powder diffraction pattern BiCu0.05Mn6.95O12-105.51mg-exp-Dec-06-2016-DSC.prn contains differential scanning calorimetry data BiCu0.1Mn6.9O12-109.89mg-exp-Nov-08-2016-DSC.prn contains differential scanning calorimetry data BiCu0.1Mn6.9O12_PE_loop_data_T77K.dat is P-E loop data
description: R.D.J. acknowledges support from a Royal Society University Research Fellowship and A.A.B. acknowledges partial support from grant JPJ004596 (ATLA, Japan).
DOI: 10.26300/bp2g-4295
title: Model results for "CO2 fertilization expands where plants can grow"
DOI: 10.3886/e119549v3
title: Data and Code for Money Mining and Price Dynamics

description: The deposit contains the data and computer code for the paper "Money mining and price dynamics" written by Michael Choi and Guillaume Rocheteau.
DOI: 10.3886/e110905
title: Data and Code for: Market Panics, Frenzies, and Informational Efficiency

description: In a market rush, the fear of future adverse price movements causes traders to trade before they become well-informed, reducing the informational efficiency of the market. I derive theoretical conditions under which market rushes are equilibrium behavior and study how well these conditions organize trading behavior in a laboratory implementation of the model. Market rushes, including both panics and frenzies, occur more frequently when predicted by theory. However, subjects use commonly-discussed, momentum-like strategies that lead to informational losses not predicted by theory, suggesting that these strategies may exacerbate both the occurrence and consequences of panics and frenzies.
DOI: 10.3886/e110905v1
title: Data and Code for: Market Panics, Frenzies, and Informational Efficiency

description: In a market rush, the fear of future adverse price movements causes traders to trade before they become well-informed, reducing the informational efficiency of the market. I derive theoretical conditions under which market rushes are equilibrium behavior and study how well these conditions organize trading behavior in a laboratory implementation of the model. Market rushes, including both panics and frenzies, occur more frequently when predicted by theory. However, subjects use commonly-discussed, momentum-like strategies that lead to informational losses not predicted by theory, suggesting that these strategies may exacerbate both the occurrence and consequences of panics and frenzies.
DOI: 10.3886/e117842v1
title: Replication Code for: "A Behavioral New Keynesian Model"

description: This paper analyzes how bounded rationality affects monetary and fiscal policy via an empirically-relevant enrichment of the New Keynesian model. It models agents' partial myopia towards distant atypical events using a new microfounded cognitive discounting parameter. Compared to the rational model: (i) there is no forward guidance puzzle; (ii) the Taylor principle changes — with passive monetary policy but enough myopia equilibria are determinate and economies stable; (iii) the zero lower bound is much less costly; (iv) price-level targeting is not optimal; (v) fiscal stimulus is effective; (vi) the model is neo-Fisherian in the long run, Keynesian in the short run.
DOI: 10.3886/e117662v1
title: Data and Code for: Multidimensional Skills, Sorting, and Human Capital Accumulation

description: We construct a structural model of on-the-job search in which workersdiffer in skills along several dimensions and sort themselves intojobs with heterogeneous skill requirements along those same dimensions.Skills are accumulated when used, and depreciate when not used. Weestimate the model combining data from O{*}NET with the NLSY79. Weuse the model to shed light on the origins and costs of mismatch alongheterogeneous skill dimensions. We highlight the deficiencies of relyingon a unidimensional model of skill when decomposing the sources ofvariation in the value of lifetime output between initial conditionsand career shocks.
DOI: 10.3886/e117047
title: Replication material for "Financial Crises, Dollarization and Lending of Last Resort in Open Economies"

description: This repository collects the files to replicate the paper "Financial Crises, Dollarization, and Lending of Last Resort in Open Economies", by Luigi Bocola ad Guido Lorenzoni
DOI: 10.3886/e117047v1
title: Replication material for "Financial Crises, Dollarization and Lending of Last Resort in Open Economies"

description: This repository collects the files to replicate the paper "Financial Crises, Dollarization, and Lending of Last Resort in Open Economies", by Luigi Bocola ad Guido Lorenzoni
DOI: 10.5281/zenodo.3932442
title: SemEval-2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals

description: <strong>SemEval-2020 Task 5</strong> <strong>Subtask-1:</strong> Recognizing Counterfactual Statements (RCS) -- Determine whether a given sentence is counterfactual or not. <strong>Subtask-2: </strong>Detecting Antecedent and Consequent (DAC) -- Extract the antecedent and consequent part in a given counterfactual sentence. The released dataset consists of train/test data of both subtask-1 and subtask-2. In our competition, participants could only use the corresponding dataset in each subtask. <strong>Task 5 Codalab Website:</strong> https://competitions.codalab.org/competitions/21691
DOI: 10.5281/zenodo.3932440
title: SemEval-2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals

description: <strong>SemEval-2020 Task 5</strong> <strong>Subtask-1:</strong> Recognizing Counterfactual Statements (RCS) -- Determine whether a given sentence is counterfactual or not. <strong>Subtask-2: </strong>Detecting Antecedent and Consequent (DAC) -- Extract the antecedent and consequent part in a given counterfactual sentence. The released dataset consists of train/test data of both subtask-1 and subtask-2. In our competition, participants could only use the corresponding dataset in each subtask. <strong>Task 5 Codalab Website:</strong> https://competitions.codalab.org/competitions/21691
DOI: 10.5281/zenodo.3958290
title: Gradients1-KOK1606-FluorometricChlorophyll_2020-03-03_V1.3

description: Fluorometric Chlorophyll were collected from rosette niskin bottles at specific depths and filtered at low vacuum through a glass fiber filter. Samples were then flash frozen in liquid nitrogen and stored in a histoprep capsule at -80°C until analysis. Post cruise, the filters were extracted using 90% acetone for a total of 48 hours in a -20°C freezer, covered to prevent the photodegradation of pigments. Upon extraction samples were centrifuged to settle filter particulates and gently poured into a glass cuvette. Samples were then run on a Turner 10-AU Fluorometer. Data were corrected for average glass fiber filter blank values and are reported as the average of duplicate samples.
DOI: 10.5281/zenodo.3697217
title: Gradients1-KOK1606-FluorometricChlorophyll_2020-03-03_V1.3

description: Fluorometric Chlorophyll were collected from rosette niskin bottles at specific depths and filtered at low vacuum through a glass fiber filter. Samples were then flash frozen in liquid nitrogen and stored in a histoprep capsule at -80°C until analysis. Post cruise, the filters were extracted using 90% acetone for a total of 48 hours in a -20°C freezer, covered to prevent the photodegradation of pigments. Upon extraction samples were centrifuged to settle filter particulates and gently poured into a glass cuvette. Samples were then run on a Turner 10-AU Fluorometer. Data were corrected for average glass fiber filter blank values and are reported as the average of duplicate samples.