cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc260grg
title: CCDC 2026245: Experimental Crystal Structure Determination

description: Related Article: Michael P. Luciano,  Adewole O. Atoyebi,  Weston Tardie,  Matthias Zeller,  Christian Brückner|2020|J.Org.Chem.|85|15273|doi:10.1021/acs.joc.0c02108
DOI: 10.5517/ccdc.csd.cc2680dx
title: CCDC 2033488: Experimental Crystal Structure Determination

description: Related Article: Cheng Xu, Guangyu Li, Michel Etienne, Xuebing Leng, Yaofeng Chen|2020|Inorg.Chem.Front.|7|4822|doi:10.1039/D0QI01163K
DOI: 10.6084/m9.figshare.13507281
title: Supplemental Data - Sexual Dysfunction: a neglected and overlooked issue in Adult Growth Hormone Deficiency (AGHD). Results from the Management of AGHD (MAGHD) Study

description: Supplemental Tables about further analysis on AGHD male and female patients.
DOI: 10.6084/m9.figshare.13507281.v2
title: Supplemental Data - Sexual Dysfunction: a neglected and overlooked issue in Adult Growth Hormone Deficiency (AGHD). Results from the Management of AGHD (MAGHD) Study

description: Supplemental Tables about further analysis on AGHD male and female patients.
DOI: 10.6084/m9.figshare.13507281.v1
title: Supplemental Data - Sexual Dysfunction: a neglected and overlooked issue in Adult Growth Hormone Deficiency (AGHD). Results from the Management of AGHD (MAGHD) Study

description: Supplemental Tables about further analysis on AGHD male and female patients.
DOI: 10.5281/zenodo.4405045
title: Nanomechanical topological insulators with an auxiliary orbital degree of freedom - source data

description: This data set contains the source data and the matlab scripts applied to obtain the results published in "Nanomechanical topological insulators with an auxiliary orbital degree of freedom". For details of the experimental procedure please refer to the main text of the article, as well as the supplementary information.
DOI: 10.5281/zenodo.4247232
title: Production line dataset for task scheduling and energy optimization - Demand Response Participation

description: Using the previous dataset at &lt;https://zenodo.org/record/4106746&gt; it was simulated an announcement of a demand response program at period 757, describing a demand response event from period 937 (Friday at 21:00h) to 960 (Friday at 23:00h) , where each period represents five minutes. The demand response program imposed a limit consumption, during its event, of 2.5 kWh. The announcement of the demand response allowed the use of the proposed solution to limit the energy consumption. For that, the algorithm described in section 3.3 was executed at period 769 (Friday at 7:00h). The API can be found at &lt;http://www.gecad.isep.ipp.pt/api/spear/&gt; File Description: Input_JSON_Demand_Response_Optimization - JSON input data for the demand response participation Output_JSON_Demand_Response_Optimization - JSON output data for the demand response participation Output_Statistics_Demand_Response_Optimization - Excel output demand response participation statistics Comparison_Output_Statistics_Demand_Response - Excel output statistics comparing the before and after the demand response participation
description: The present work has received funding from National Funds through FCT under the project UIDB/00760/2020
DOI: 10.5281/zenodo.4247231
title: Production line dataset for task scheduling and energy optimization - Demand Response Participation

description: Using the previous dataset at &lt;https://zenodo.org/record/4106746&gt; it was simulated an announcement of a demand response program at period 757, describing a demand response event from period 937 (Friday at 21:00h) to 960 (Friday at 23:00h) , where each period represents five minutes. The demand response program imposed a limit consumption, during its event, of 2.5 kWh. The announcement of the demand response allowed the use of the proposed solution to limit the energy consumption. For that, the algorithm described in section 3.3 was executed at period 769 (Friday at 7:00h). The API can be found at &lt;http://www.gecad.isep.ipp.pt/api/spear/&gt; File Description: Input_JSON_Demand_Response_Optimization - JSON input data for the demand response participation Output_JSON_Demand_Response_Optimization - JSON output data for the demand response participation Output_Statistics_Demand_Response_Optimization - Excel output demand response participation statistics Comparison_Output_Statistics_Demand_Response - Excel output statistics comparing the before and after the demand response participation
description: The present work has received funding from National Funds through FCT under the project UIDB/00760/2020
DOI: 10.5281/zenodo.4106745
title: Production line dataset for task scheduling and energy optimization - Schedule Optimization

description: The case study of this dataset uses real production data, provided by a textile company that manufactures hang tags. Their working schedule is from 7h00 of Monday to 23h00 of Saturday. This dataset uses a period of 5 minutes for all task durations and energy data. The case study considers a six-day period from 7h00 of Monday to 23h00 of Saturday. The scheduling algorithm was used for three machines that share the same cell.<br> <br> The API can be found at &lt;http://www.gecad.isep.ipp.pt/api/spear/&gt;<br> <br> File Description: Input_JSON_Schedule_Optimization - JSON input data for the schedule optimization Output_JSON_Schedule_Optimization - JSON output data for the schedule optimization Output_Statistics_Schedule_Optimization - Excel output schedule optimization statistics
description: The present work has received funding from National Funds through FCT under the project UIDB/00760/2020
DOI: 10.6084/m9.figshare.13142768.v1
title: Metadata record for the manuscript: Co-producing urban knowledge in Angola and Mozambique: towards meeting SDG 11

description: <b>Summary</b>This metadata record provides details of the data supporting the claims of the related manuscript: “Co-producing urban knowledge in Angola and Mozambique: towards meeting SDG 11”.The related study presents findings from a research project conducted in the cities of Luanda, Angola and Maputo, Mozambique which used citizen science to generate data on the indicators of standalone urban goal 11 adopted as part of the 17 UN Sustainable Development Goals (SDGs) and used these data to inform more inclusive, sustainable and participatory urban planning and policymaking. SDG 11 is encapsulated as the need to make cities in Africa ‘more inclusive, safe, resilient and sustainable’.<br><b>Data access</b>Data sets generated during and/or analyzed during the current study are available (in Portuguese) via DataFirst, the only African open access research data service and repository: https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/central/about. Prospective users must register with DataFirst and agree to terms and conditions of use prior to being provided access to the data. The questionnaires, technical documents and reports that describe the survey process and the key results for ‘Angola - Sustainable Cities Survey 2018, Luanda’ are available at https://doi.org/10.25828/ed1q-2q89, and for ‘Mozambique - Sustainable Cities Survey 2019, Maputo’ at https://doi.org/10.25828/acd7-7q30.<br>The SDG indicator classification by tiers which underlie Box 1 in the related manuscript are publicly available at https://unstats.un.org/sdgs/indicators/indicators-list/ and https://unstats.un.org/sdgs/iaeg-sdgs/tier-classification/. The SDG 11 Targets, indicators and current tier classification that underlie Table 1 in the related manuscript are publicly available at https://unstats.un.org/sdgs/iaeg-sdgs/tier-classification/. Access to the original sources of the SDG 11 indicator data availability, which underlie Table 2 in the related manuscript, for Angola are publicly available at https://www.ine.gov.ao/images/Populacao_Sociedade/Relatorio_ODS_FINAL.pdf and for Mozambique can be requested from the corresponding author, Sylvia Croese (sylviacroese@gmail.com).
DOI: 10.6084/m9.figshare.13337333
title: PAP SMEAR

description: Pap smear screening test research<br>
DOI: 10.6084/m9.figshare.13337333.v1
title: Untitled Item

description: Pap smear screening test research<br>
DOI: 10.6084/m9.figshare.13032740
title: Data and R codes for: Novel trophic interactions under climate change promote alpine plant coexistence

description: ============================================================<br>============================================================<br>============================================================<br><b><br></b><b>When using these datasets, please cite the following references:</b><br>Descombes, P., et al. (2020). Novel trophic interactions under climate change promote alpine plant coexistence. <i>Science</i>, 370(6523), 1469-1473.<br>P. Descombes et al., Data and R codes for: Novel trophic<br>interactions under climate change promote alpine plant<br>coexistence, FigShare (2020); https://doi.org/10.6084/<br>m9.figshare.13032740<br>============================================================<br>============================================================<br>============================================================<br><b><br></b><b>Datasets descriptions:<br></b><b><br></b>Details on the data sampling are fully described in the aforementioned references. The content of each datasets (rows and columns) are described in each datasets "readme" files. <br><br>
DOI: 10.5281/zenodo.4405277
title: Dataset of the WP2 Cranfield

description: C-scan dataset of impact damages on composite coupons and laminates. This dataset contains<br> ultrasonic full-waveform Phased Array (PA) data that were acquired during the experimental<br> assessment of impact damages on composite coupons and laminate conducted by Cranfield in the<br> context of project CompInnova: An Advanced Methodology for the Inspection and Quantification of<br> Damage on Aerospace Composites and Metals using an Innovative Approach (H2020 FET OPEN, Grant<br> Agreement No. 665238). The C-scan data on composite coupons is acquired by using 5MHz wheel probe2 Phased Array (PA)<br> the transducer is in raw CSV format and processed C-scan in PNG image format. The 10MHz PA transducer and novel elastomer wedge which is a part of PA module developed at Cranfield and novel mist couplant delivery are used for scanning both coupons and laminates and raw data is in CSV format and processed data in TIFF image format. Also, a document on information about material and layup of coupons and laminate is also included. The data were used in the deliverable D2.3, D2.4 and D7.1 and D7.2.
DOI: 10.5281/zenodo.4405276
title: Dataset of the WP2 Cranfield

description: C-scan dataset of impact damages on composite coupons and laminates. This dataset contains<br> ultrasonic full-waveform Phased Array (PA) data that were acquired during the experimental<br> assessment of impact damages on composite coupons and laminate conducted by Cranfield in the<br> context of project CompInnova: An Advanced Methodology for the Inspection and Quantification of<br> Damage on Aerospace Composites and Metals using an Innovative Approach (H2020 FET OPEN, Grant<br> Agreement No. 665238). The C-scan data on composite coupons is acquired by using 5MHz wheel probe2 Phased Array (PA)<br> the transducer is in raw CSV format and processed C-scan in PNG image format. The 10MHz PA transducer and novel elastomer wedge which is a part of PA module developed at Cranfield and novel mist couplant delivery are used for scanning both coupons and laminates and raw data is in CSV format and processed data in TIFF image format. Also, a document on information about material and layup of coupons and laminate is also included. The data were used in the deliverable D2.3, D2.4 and D7.1 and D7.2.
DOI: 10.5517/ccdc.csd.cc13pq5p
title: CCDC 1033762: Experimental Crystal Structure Determination

description: Related Article: Yuewei Zhang, Qingqing Bao, Ning Zhang, Shuohang Wang, Xue Yu|2020|RSC Advances|10|41802|doi:10.1039/D0RA08758K
DOI: 10.5517/ccdc.csd.cc2680fy
title: CCDC 2033489: Experimental Crystal Structure Determination

description: Related Article: Cheng Xu, Guangyu Li, Michel Etienne, Xuebing Leng, Yaofeng Chen|2020|Inorg.Chem.Front.|7|4822|doi:10.1039/D0QI01163K
DOI: 10.5517/ccdc.csd.cc2680n5
title: CCDC 2033496: Experimental Crystal Structure Determination

description: Related Article: Cheng Xu, Guangyu Li, Michel Etienne, Xuebing Leng, Yaofeng Chen|2020|Inorg.Chem.Front.|7|4822|doi:10.1039/D0QI01163K
DOI: 10.5517/ccdc.csd.cc26bv6m
title: CCDC 2036210: Experimental Crystal Structure Determination

description: Related Article: Yongxing Tang, Zhaoyang Yin, Ajay Kumar Chinnam, Richard J. Staples, Jean’ne M. Shreeve|2020|Inorg.Chem.|59|17766|doi:10.1021/acs.inorgchem.0c03014
DOI: 10.5517/ccdc.csd.cc26bv7n
title: CCDC 2036211: Experimental Crystal Structure Determination

description: Related Article: Yongxing Tang, Zhaoyang Yin, Ajay Kumar Chinnam, Richard J. Staples, Jean’ne M. Shreeve|2020|Inorg.Chem.|59|17766|doi:10.1021/acs.inorgchem.0c03014
DOI: 10.5517/ccdc.csd.cc26bv8p
title: CCDC 2036212: Experimental Crystal Structure Determination

description: Related Article: Yongxing Tang, Zhaoyang Yin, Ajay Kumar Chinnam, Richard J. Staples, Jean’ne M. Shreeve|2020|Inorg.Chem.|59|17766|doi:10.1021/acs.inorgchem.0c03014
DOI: 10.5517/ccdc.csd.cc26bv9q
title: CCDC 2036213: Experimental Crystal Structure Determination

description: Related Article: Yongxing Tang, Zhaoyang Yin, Ajay Kumar Chinnam, Richard J. Staples, Jean’ne M. Shreeve|2020|Inorg.Chem.|59|17766|doi:10.1021/acs.inorgchem.0c03014
DOI: 10.15468/kkmhjh
title: The westernmost known population of Paracobitis (Teleostei, Nemacheilidae), with the description of a new species from the Euphrates River in southern Anatolia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kaya, C?neyt, Turan, Davut, Kalayci, G?khan, Bay?elebi, Esra, Freyhof, J?rg (2020): The westernmost known population of Paracobitis (Teleostei, Nemacheilidae), with the description of a new species from the Euphrates River in southern Anatolia. Zootaxa 4838 (4): 525-534, DOI: https://doi.org/10.11646/zootaxa.4838.4.6
DOI: 10.25646/7799
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.17632/nzyjn2ft8y.1
title: Data for: Adjuvant Effect of Type I Interferon Induced by Many but Not All Commercial Influenza Vaccines

description: Dataset use to write this paper
DOI: 10.21227/1jvy-1356
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location.The paper associated with this dataset is available here: Design and analysis of a large-scale COVID-19 tweets dataset-------------------------------------Related datasets: (a) Coronavirus (COVID-19) Tweets Sentiment Trend (Global)(b) Tweets Originating from India During COVID-19 Lockdowns-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 289,751 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Developer Policy and (iii) cite the following paper:Lamsal, R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence (2020). https://doi.org/10.1007/s10489-020-02029-z— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time (and other notes) of each CSV file present in this dataset.
DOI: 10.6084/m9.figshare.13507473
title: Application and evaluation of a novel multidisciplinary one health approach for drug, water, and food safety.

description: MOST project
DOI: 10.6084/m9.figshare.13507473.v1
title: Application and evaluation of a novel multidisciplinary one health approach for drug, water, and food safety.

description: MOST project
DOI: 10.5517/ccdc.csd.cc20qwh4
title: CCDC 1869036: Experimental Crystal Structure Determination

description: Related Article: Joshua P. Green, Daniel Morales Salazar, Arvind Kumar Gupta, and Andreas Orthaber|2020|J.Org.Chem.|85|14619|doi:10.1021/acs.joc.0c01336
DOI: 10.5517/ccdc.csd.cc24yl7y
title: CCDC 1994640: Experimental Crystal Structure Determination

description: Related Article: Joshua P. Green, Daniel Morales Salazar, Arvind Kumar Gupta, and Andreas Orthaber|2020|J.Org.Chem.|85|14619|doi:10.1021/acs.joc.0c01336
DOI: 10.5517/ccdc.csd.cc20qwf2
title: CCDC 1869034: Experimental Crystal Structure Determination

description: Related Article: Joshua P. Green, Daniel Morales Salazar, Arvind Kumar Gupta, and Andreas Orthaber|2020|J.Org.Chem.|85|14619|doi:10.1021/acs.joc.0c01336
DOI: 10.5517/ccdc.csd.cc24yl8z
title: CCDC 1994641: Experimental Crystal Structure Determination

description: Related Article: Joshua P. Green, Daniel Morales Salazar, Arvind Kumar Gupta, and Andreas Orthaber|2020|J.Org.Chem.|85|14619|doi:10.1021/acs.joc.0c01336
DOI: 10.5517/ccdc.csd.cc23qj7m
title: CCDC 1958060: Experimental Crystal Structure Determination

description: Related Article: Shintaro Ishida, Shohei Sugawara, Shunya Honda, Takeaki Iwamoto|2020|Chem.Commun.|56|15072|doi:10.1039/D0CC06603F
DOI: 10.5517/ccdc.csd.cc23qj8n
title: CCDC 1958061: Experimental Crystal Structure Determination

description: Related Article: Shintaro Ishida, Shohei Sugawara, Shunya Honda, Takeaki Iwamoto|2020|Chem.Commun.|56|15072|doi:10.1039/D0CC06603F
DOI: 10.5281/zenodo.4405783
title: French Emotional Speech Database - Oréau

description: This document presents the French emotional speech database - Oréau, recorded in a quiet environment. The database is designed for general study of emotional speech and analysis of emotion characteristics for speech synthesis purposes. It contains 79 utterances which could be used in everyday life in the classroom. Between 10 and 13 utterances were written for each of the 7 emotions in French language by 32 non-professional speakers. 2 versions are available, the first one contains 502 sentences. A perception test was performed to evaluate the recognition of emotions and their naturalness. 90% of utterances (434 utterances) were correctly identified and retained after the test and various analyses, which constitutes the second version of database.
DOI: 10.5281/zenodo.4405782
title: French Emotional Speech Database - Oréau

description: This document presents the French emotional speech database - Oréau, recorded in a quiet environment. The database is designed for general study of emotional speech and analysis of emotion characteristics for speech synthesis purposes. It contains 79 utterances which could be used in everyday life in the classroom. Between 10 and 13 utterances were written for each of the 7 emotions in French language by 32 non-professional speakers. 2 versions are available, the first one contains 502 sentences. A perception test was performed to evaluate the recognition of emotions and their naturalness. 90% of utterances (434 utterances) were correctly identified and retained after the test and various analyses, which constitutes the second version of database.
DOI: 10.15468/32mrr3
title: Two new species of the genus Xiphidiopsis Redtenbacher, 1891 (Tettigoniidae Meconematinae: Meconematini) from Yunnan, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Cui, Peng, Liu, Qing, Chang, Yanlin (2020): Two new species of the genus Xiphidiopsis Redtenbacher, 1891 (Tettigoniidae Meconematinae: Meconematini) from Yunnan, China. Zootaxa 4845 (1): 127-132, DOI: https://doi.org/10.11646/zootaxa.4845.1.10
DOI: 10.23729/45d0ade6-1b7b-4008-8938-e2a2b7d2aa23
title: FIRE-heijastusluotaushanke, luotauslinja 1
title: FIRE (The Finnish Reflection Experiment) profile 1

description: Heijastusluotaushankkeen FIRE (The Finnish Reflection Experiment) aineisto koostuu seismisestä heijastusluotausdatasta, joka kattaa neljä linjaa Suomessa. Luotauslinjojen kokonaispituus on 2104 km. Ne leikkaavat useita geologisesti ja taloudellisesti tärkeitä Fennoskandian kilven alueita kuten arkeeisen ja proterotsooisen kuoren rajan sekä Outokummun malmialueen. Alkuperäinen FIRE-hanke toteutettiin vuosina 2001-2015 Geologian tutkimuskeskuksen (GTK), Helsingin yliopiston Seismologian instituutin ja Oulun yliopiston Seismologian instituutin sekä Sodankylän geofysiikan observatorion yhteistyönä. Seismisistä luotauksista vastasivat Specgeofizika S.E. ja Machinoexport S.E. Tämä aineisto kattaa FIRE-hankkeen luotauslinjan 1. FIRE-hanke on kuvattu kattavasti Geologian tutkimuskeskuksen julkaisussa: Kukkonen, I.T., ja Lahtinen, R. (toim.), 2006. Finnish Reflection Experiment FIRE 2001-2005. Geological Survey of Finland, Special Paper 43, 247 s.
description: The Finnish Reflection Experiment (FIRE) dataset consists of seismic reflection data from 2,104 km of common mid-point (CMP) lines. The four FIRE transects cross-cut several geologically and economically important features of Fennoscandian Shield such as the Archaean–Proterozoic boundary and Outokumpu ore district. The original FIRE project took place between 2001 and 2005. It was conducted in co-operation between the Geological Survey of Finland (GTK), the Institute of Seismology at the University of Helsinki and the Institute of Geosciences and the Sodankylä Geophysical Observatory of the University of Oulu. The seismic contractor in the FIRE project was Specgeofizika S.E. together with Machinoexport S.E. The original report of the FIRE project can be found in the Special Paper 43 of the Geological Survey of Finland: Kukkonen, I.T., and Lahtinen, R. (Eds.), 2006. Finnish Reflection Experiment FIRE 2001-2005. Geological Survey of Finland, Special Paper 43, 247 pages. This dataset covers the FIRE profile 1. Data consist of pole co­ordin­ate files, common mid-point coordinate files, original field recordings, shot gathers, field statics, normal move-out and dip move-out stacks, migrated and depth-converted stacks, envelope sections and variable-area plots.
DOI: 10.6084/m9.figshare.13507590
title: Bilingual_Translation_Interlocutor-context.csv

description: This dataset contains reaction time, and accuracy data of a study conducted on thirty nine participants in the University of Hyderabad, India. The aim of the study was to investigate the role of interlocutor-context on cross-linguistic lexical activation and translation in bilinguals. The participants were Hindi-English bilinguals. Their first language was Hindi, and second language was English.