cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/v61izz
title: Global Register of Introduced and Invasive Species - Lesotho

description: The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified national checklists of introduced (alien) and invasive alien species at the country, territory, and associated island level. Checklists are living entities, especially for biological invasions given the growing nature of the problem. GRIIS checklists are based on a published methodology and supported by the Integrated Publishing Tool that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 aimed to achieve global coverage including non-party countries and all overseas territories of countries, e.g. those of the Netherlands, France, and the United Kingdom. All kingdoms of organisms occurring in all environments and systems are covered. Checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records, as well as those under review, are presented on the online GRIIS website (www.griis.org) in addition to being published through the GBIF Integrated Publishing Tool.
DOI: 10.6084/m9.figshare.13049138
title: Proteome database of Carnobacterium sp CP1

description: <i>Carnobacterium</i> spp are Gram-positive rod-shaped lactic acid bacteria. Able to produce lactic acid from glucose during fermentative growth, <i>Carnobacterium</i> spp have been found in many environments around the world. This work reports the proteome database of <i>Carnobacterium</i> sp. CP1. Parsed from the UniProt proteome file, the proteome database comprises protein name, amino acid sequence, and number of residues. In addition, the in-house MATLAB proteome analysis software also calculates molecular weight of each protein and its nucleotide sequence for inclusion into the database. Overall, the presented proteome database of <i>Carnobacterium</i> sp. CP1 should find use in a variety of biotechnology applications where understanding of the proteome complement of the species and manipulations of genes and genetic repertoire is important.
DOI: 10.6084/m9.figshare.13049138.v1
title: Proteome database of Carnobacterium sp CP1

description: <i>Carnobacterium</i> spp are Gram-positive rod-shaped lactic acid bacteria. Able to produce lactic acid from glucose during fermentative growth, <i>Carnobacterium</i> spp have been found in many environments around the world. This work reports the proteome database of <i>Carnobacterium</i> sp. CP1. Parsed from the UniProt proteome file, the proteome database comprises protein name, amino acid sequence, and number of residues. In addition, the in-house MATLAB proteome analysis software also calculates molecular weight of each protein and its nucleotide sequence for inclusion into the database. Overall, the presented proteome database of <i>Carnobacterium</i> sp. CP1 should find use in a variety of biotechnology applications where understanding of the proteome complement of the species and manipulations of genes and genetic repertoire is important.
DOI: 10.5517/ccdc.csd.cc2610jt
title: CCDC 2026765: Experimental Crystal Structure Determination

description: Related Article: Chihiro Maeda, Shoki Toyama, Naoki Okada, Kazuto Takaishi, Seongsoo Kang, Dongho Kim, Tadashi Ema|2020|J.Am.Chem.Soc.|142|15661|doi:10.1021/jacs.0c07707
DOI: 10.5517/ccdc.csd.cc25kql2
title: CCDC 2013034: Experimental Crystal Structure Determination

description: Related Article: T.E. Shaw, P. LeMagueres, A.P. Sattelberger, T. Jurca|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|947|doi:10.1107/S2053229620011626
DOI: 10.5517/ccdc.csd.cc265clc
title: CCDC 2030952: Experimental Crystal Structure Determination

description: Related Article: A.M. Grześkiewicz, T. Stefański, Z. Dutkiewicz, D. Buśko, M. Kubicki|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|958|doi:10.1107/S205322962001236X
DOI: 10.5517/ccdc.csd.cc265cmd
title: CCDC 2030953: Experimental Crystal Structure Determination

description: Related Article: A.M. Grześkiewicz, T. Stefański, Z. Dutkiewicz, D. Buśko, M. Kubicki|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|958|doi:10.1107/S205322962001236X
DOI: 10.5517/ccdc.csd.cc241wy1
title: CCDC 1968033: Experimental Crystal Structure Determination

description: Related Article: A. Wood, P.V. Bernhardt, I. van Altena, M.I. Simone|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1653|doi:10.1107/S2056989020012438
DOI: 10.5517/ccdc.csd.cc265tjr
title: CCDC 2031384: Experimental Crystal Structure Determination

description: Related Article: H.H. Mallard, N.D. Kennedy, N.A. Rudman, A.M. Greenwood, J. Nicoleau, C.E. Angle, N.A. Torquato, M.R. Gau, P.J. Carroll, M.R. Anstey|2020|IUCrData|5|x201248|doi:10.1107/S2414314620012481
DOI: 10.5517/ccdc.csd.cc14ljmw
title: CCDC 1060498: Experimental Crystal Structure Determination

description: Related Article: H. Li, B. Yan, H. Ma, X. Ma, Z. Sun, Y. Ma|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|965|doi:10.1107/S2053229620012516
DOI: 10.5517/ccdc.csd.cc2666tg
title: CCDC 2031765: Experimental Crystal Structure Determination

description: Related Article: M. Yano, Y. Kashiwagi, Y. Inada, Y. Hayashi, K. Mitsudo, K. Kubono|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1649|doi:10.1107/S2056989020012529
DOI: 10.5517/ccdc.csd.cc266m8b
title: CCDC 2032151: Experimental Crystal Structure Determination

description: Related Article: S.V. Shishkina, L.A. Petrushova, K.O. Burian, A.I. Fedosov, I.V. Ukrainets|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1657|doi:10.1107/S2056989020012566
DOI: 10.5517/ccdc.csd.cc266rt0
title: CCDC 2032292: Experimental Crystal Structure Determination

description: Related Article: K. Znovjyak, M. Seredyuk, S.O. Malinkin, S. Shova, L. Soliev|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1661|doi:10.1107/S2056989020012608
DOI: 10.5517/ccdc.csd.cc266sqy
title: CCDC 2032320: Experimental Crystal Structure Determination

description: Related Article: J. Fábry, E. Samolová|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1669|doi:10.1107/S2056989020012591
DOI: 10.15468/f0llqo
title: Global Register of Introduced and Invasive Species - Liberia

description: The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified national checklists of introduced (alien) and invasive alien species at the country, territory, and associated island level. Checklists are living entities, especially for biological invasions given the growing nature of the problem. GRIIS checklists are based on a published methodology and supported by the Integrated Publishing Tool that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 aimed to achieve global coverage including non-party countries and all overseas territories of countries, e.g. those of the Netherlands, France, and the United Kingdom. All kingdoms of organisms occurring in all environments and systems are covered. Checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records, as well as those under review, are presented on the online GRIIS website (www.griis.org) in addition to being published through the GBIF Integrated Publishing Tool.
DOI: 10.15468/p4jxvy
title: Global Register of Introduced and Invasive Species - Libya

description: The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified national checklists of introduced (alien) and invasive alien species at the country, territory, and associated island level. Checklists are living entities, especially for biological invasions given the growing nature of the problem. GRIIS checklists are based on a published methodology and supported by the Integrated Publishing Tool that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 aimed to achieve global coverage including non-party countries and all overseas territories of countries, e.g. those of the Netherlands, France, and the United Kingdom. All kingdoms of organisms occurring in all environments and systems are covered. Checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records, as well as those under review, are presented on the online GRIIS website (www.griis.org) in addition to being published through the GBIF Integrated Publishing Tool.
DOI: 10.6084/m9.figshare.13049147.v1
title: Additional file 1 of Non-target screening for detecting the occurrence of plant metabolites in river waters

description: Additional file 1: Table S1: Information on sampling site for river water and plant species. Table S2. Analytical standards used. Table S3. Internal standards used for the chemical analysis (ESIpos).
DOI: 10.15468/u1s0kr
title: Global Register of Introduced and Invasive Species - Liechtenstein

description: The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified national checklists of introduced (alien) and invasive alien species at the country, territory, and associated island level. Checklists are living entities, especially for biological invasions given the growing nature of the problem. GRIIS checklists are based on a published methodology and supported by the Integrated Publishing Tool that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 aimed to achieve global coverage including non-party countries and all overseas territories of countries, e.g. those of the Netherlands, France, and the United Kingdom. All kingdoms of organisms occurring in all environments and systems are covered. Checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records, as well as those under review, are presented on the online GRIIS website (www.griis.org) in addition to being published through the GBIF Integrated Publishing Tool.
DOI: 10.6084/m9.figshare.13049240.v1
title: Additional file 1 of Etiology of community-acquired pneumonia in adults: a systematic review

description: Additional file 1.
DOI: 10.6084/m9.figshare.13049240
title: Additional file 1 of Etiology of community-acquired pneumonia in adults: a systematic review

description: Additional file 1.
DOI: 10.6084/m9.figshare.13049141.v1
title: A multiple land surface models based China evapotranspiration dataset

description: I developed an evpotranspiration (ET) dataset over China during 1979-2012, by using three land surface models including the CLM4.0, DLM, and VIC. The ET data was validated against flux towers at site scale and surface water budget-based ET at regional scale. It was also compared to the MODIS and machine learning based upscaling ET.
DOI: 10.6084/m9.figshare.13049141
title: A multiple land surface models based China evapotranspiration dataset

description: I developed an evpotranspiration (ET) dataset over China during 1979-2012, by using three land surface models including the CLM4.0, DLM, and VIC. The ET data was validated against flux towers at site scale and surface water budget-based ET at regional scale. It was also compared to the MODIS and machine learning based upscaling ET.
DOI: 10.15468/tvi3gf
title: Global Register of Introduced and Invasive Species GRIIS - Luxembourg

description: The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified national checklists of introduced (alien) and invasive alien species at the country, territory, and associated island level. Checklists are living entities, especially for biological invasions given the growing nature of the problem. GRIIS checklists are based on a published methodology and supported by the Integrated Publishing Tool that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 aimed to achieve global coverage including non-party countries and all overseas territories of countries, e.g. those of the Netherlands, France, and the United Kingdom. All kingdoms of organisms occurring in all environments and systems are covered. Checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records, as well as those under review, are presented on the online GRIIS website (www.griis.org) in addition to being published through the GBIF Integrated Publishing Tool.
DOI: 10.6084/m9.figshare.13049243
title: Terrestrial ecosystem model based China gross primary productivity data

description: Forcing an improved process-based model with observation-based China meteorological data, I simulated the gross primary productivity (GPP) over China during 1979-2012. The GPP data was validated against observations from flux towers and satellite remote sensing, and machine learning based upscaling GPP.
DOI: 10.6084/m9.figshare.13049243.v1
title: Terrestrial ecosystem model based China gross primary productivity data

description: Forcing an improved process-based model with observation-based China meteorological data, I simulated the gross primary productivity (GPP) over China during 1979-2012. The GPP data was validated against observations from flux towers and satellite remote sensing, and machine learning based upscaling GPP.
DOI: 10.6084/m9.figshare.13049147
title: Additional file 1 of Non-target screening for detecting the occurrence of plant metabolites in river waters

description: Additional file 1: Table S1: Information on sampling site for river water and plant species. Table S2. Analytical standards used. Table S3. Internal standards used for the chemical analysis (ESIpos).
DOI: 10.6084/m9.figshare.13049279
title: Terrestrial ecosystem models based China ecosystem water use efficiency

description: Using the gross primary productivity (GPP) and evapotranspiration (ET) which I have simulated using process-based models, I also generated a ecosystem water use efficiency (eWUE) data over China during 1979-2012. The data was validated against observations from 16 flux towers.
DOI: 10.6084/m9.figshare.13049279.v1
title: Terrestrial ecosystem models based China ecosystem water use efficiency

description: Using the gross primary productivity (GPP) and evapotranspiration (ET) which I have simulated using process-based models, I also generated a ecosystem water use efficiency (eWUE) data over China during 1979-2012. The data was validated against observations from 16 flux towers.
DOI: 10.6084/m9.figshare.13049299
title: Figures Licenses from Probing plasmonic excitation mechanisms and far-field radiation of single-crystalline gold tapers with electrons

description: Conical metallic tapers represent an intriguing of metallic nanostructures, as their plasmonic properties show interesting characteristics in strong correlation to their geometrical properties. This is important for possible applications such as in the field of scanning optical microscopy, as favourable plasmonic resonance behaviour can be tailored by optimizing structural parameters like surface roughness or opening angle. Here, we review our recent studies, where single-crystalline gold tapers were investigated experimentally by means of electron energy-loss and cathodoluminescence spectroscopy techniques inside electron microscopes, supported by theoretical finite-difference time-domain calculations. Through the study of tapers with various opening angles, the underlying resonance mechanisms are discussed.This article is part of the theme issue ‘Dynamic in-situ microscopy relating structure and function’.
DOI: 10.6084/m9.figshare.13049299.v1
title: Figures Licenses from Probing plasmonic excitation mechanisms and far-field radiation of single-crystalline gold tapers with electrons

description: Conical metallic tapers represent an intriguing of metallic nanostructures, as their plasmonic properties show interesting characteristics in strong correlation to their geometrical properties. This is important for possible applications such as in the field of scanning optical microscopy, as favourable plasmonic resonance behaviour can be tailored by optimizing structural parameters like surface roughness or opening angle. Here, we review our recent studies, where single-crystalline gold tapers were investigated experimentally by means of electron energy-loss and cathodoluminescence spectroscopy techniques inside electron microscopes, supported by theoretical finite-difference time-domain calculations. Through the study of tapers with various opening angles, the underlying resonance mechanisms are discussed.This article is part of the theme issue ‘Dynamic in-situ microscopy relating structure and function’.
DOI: 10.5517/ccdc.csd.cc206mjd
title: CCDC 1853413: Experimental Crystal Structure Determination

description: Related Article: Gang Xiong, Dan Qi, Yongke He, Lixin You, Baoyi Ren, Yaguang Sun|2018|Inorg.Chim.Acta|483|299|doi:10.1016/j.ica.2018.08.044
DOI: 10.21227/xn7q-aw61
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.-------------------------------------Recently added: Coronavirus (COVID-19) Global Sentiment Trend-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 237,051 tweets— Coverage : Global— Language : English (EN)— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Usage policy : As per Twitter's Developer Policy— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time of each CSV file present in this dataset.
DOI: 10.21227/pg8e-yv92
title: Coronavirus (COVID-19) Tweets Sentiment Trend (Global)

description: This dataset gives a cursory glimpse at the overall sentiment trend of the public discourse regarding the COVID-19 pandemic on Twitter. The live scatter plot of this dataset is available as The Overall Trend block at https://live.rlamsal.com.np. The trend graph reveals multiple peaks and drops that need further analysis. The n-grams during those peaks and drops can prove beneficial for better understanding the discourse.The dataset will be updated weekly and will continue until the development of the Coronavirus (COVID-19) Tweets Dataset is ongoing.A quick overview of the datasetThe sentiment scores are defined in the range [-1,0), 0, and (0,+1] for negative sentiment, neutral sentiment, and positive sentiment. Since the number of negative sentiment tweets is always less than the combined number of neutral and positive sentiment tweets, the majority of the time, the average sentiment falls pretty close to +0.05. So if we consider +0.05 as the neutral point for average sentiment score, then any score greater than +0.1 (peaks) and smaller than 0 (drops) can be regarded as a point of interest for further scrutinizing. Following are the dates when the Twitter stream (based on the tweets present in the Coronavirus (COVID-19) Tweets Dataset) experienced those peaks and drops:Positive peaks: In 2020 (April 30, May 3, May 23, May 24, May 25, May 26, June 2, June 22, June 28, July 3, July 12, July 26, August 15, August 16, August 18, August 21, August 24, August 31, September 1, September 2, September 4, September 5, September 9, September 21, September 23)Negative Peaks: In 2020 (May 28, May 30, May 31, June 1, June 2, June 7, June 8, June 12, June 13, June 14, June 15, June 21, June 24, june 25, July 6, July 7, July 10, August 26, September 1, September 3, September 13, September 17, September 25, September 26, September 28)What's inside the dataset files?Tweets collected every 10 minutes are sampled together, and an average sentiment score is computed. This dataset contains TXT files, each with two columns: (i) date/time (in UTC) and (ii) average sentiment. The first column is date/time and is by default in Unix timestamp (in ms). You can use this formula =cell/1000/60/60/24 + DATE(1970,1,1) in Spreadsheets, or this pd.to_datetime(dataframe_name[column],unit='ms') if you're comfortable with Python, to convert the Unix timestamp to human-readable format. There are 44 instances where the average sentiment score is NULL because of networking issues with the cloud service.
DOI: 10.21227/3c4f-h516
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.-------------------------------------Recently added: Coronavirus (COVID-19) Tweets Sentiment Trend (Global)-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 237,051 tweets— Coverage : Global— Language : English (EN)— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Usage policy : As per Twitter's Developer Policy— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time of each CSV file present in this dataset.
DOI: 10.6084/m9.figshare.13049315
title: WGD

description: Whole genome duplication
DOI: 10.6084/m9.figshare.13049315.v1
title: WGD

description: Whole genome duplication