cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7299483
title: FD-DeepLoc datasets: demo2 dataset

description: Experimental large-FOV astigmatism NPC dataset.
DOI: 10.6084/m9.figshare.21507060
title: The role of grain boundaries in low-temperature plasticity of olivine revealed by nanoindentation

description: Nanoindentation, HR-EBSD and TEM data published in the manuscript titled <em>The role of grain boundaries in low-temperature plasticity of olivine revealed by nanoindentation. </em>The pre-print version of the manuscript can be found at: https://doi.org/10.1002/essoar.10512783.1
DOI: 10.6084/m9.figshare.21507060.v1
title: The role of grain boundaries in low-temperature plasticity of olivine revealed by nanoindentation

description: Nanoindentation, HR-EBSD and TEM data published in the manuscript titled <em>The role of grain boundaries in low-temperature plasticity of olivine revealed by nanoindentation</em>
DOI: 10.5281/zenodo.7299762
title: Dataset related to the article "GRN- /- IPSC-DERIVED CORTICAL NEURONS RECAPITULATE THE PATHOLOGICAL FINDINGS OF BOTH FRONTOTEMPORAL LOBAR DEGENERATION AND NEURONAL CEROIDOLIPOFUSCINOSIS"

description: THE DATASET CONTAINS .XLSX FILES REPORTING BIOCHEMICAL DATA (DENSITOMETRIC ANALYSIS) AND IMMUNOHISTOCHEMICAL DATA (MORPHOMETRIC ANALYSIS AND COUNTING)
description: Study Founded by Italian Ministry of Health (Ricerca Corrente and RF-2013-02355764, C9GenALSPhen)
DOI: 10.5281/zenodo.7299761
title: Dataset related to the article "GRN- /- IPSC-DERIVED CORTICAL NEURONS RECAPITULATE THE PATHOLOGICAL FINDINGS OF BOTH FRONTOTEMPORAL LOBAR DEGENERATION AND NEURONAL CEROIDOLIPOFUSCINOSIS"

description: THE DATASET CONTAINS .XLSX FILES REPORTING BIOCHEMICAL DATA (DENSITOMETRIC ANALYSIS) AND IMMUNOHISTOCHEMICAL DATA (MORPHOMETRIC ANALYSIS AND COUNTING)
description: Study Founded by Italian Ministry of Health (Ricerca Corrente and RF-2013-02355764, C9GenALSPhen)
DOI: 10.5517/ccdc.csd.cc28qwmj
title: CCDC 2107368: Experimental Crystal Structure Determination

description: Related Article: Michael Bolte, R. Tang, M. Skoulatos, A. Tsirlin, M. Kleinhans, R. Georgii, Natalija van Well|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29g97b
title: CCDC 2128901: Experimental Crystal Structure Determination

description: Related Article: Lujun Zhang, Wenfang Xiong, Biao Yao, Haitao Liu, Meng Li, Yu Qin, Yujian Yu, Xu Li, Meng Chen, Wanqing Wu, Jianxiao Li, Jinliang Wang, Huanfeng Jiang|2022|RSC Advances|12|30248|doi:10.1039/D2RA06097C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2clnsf
title: CCDC 2192685: Experimental Crystal Structure Determination

description: Related Article: Atrayee Banaspati, Vanitha Ramu, Md Kausar Raza, Tridib K. Goswami|2022|RSC Advances|12|30722|doi:10.1039/D2RA04813B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2clntg
title: CCDC 2192686: Experimental Crystal Structure Determination

description: Related Article: Atrayee Banaspati, Vanitha Ramu, Md Kausar Raza, Tridib K. Goswami|2022|RSC Advances|12|30722|doi:10.1039/D2RA04813B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21511005.v2
title: heatwaves in South Asia

description: codes and data for the manuscript
DOI: 10.5519/qd.ob75z5e9
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (319 records)
DOI: 10.3886/e175582v1-130442
title: Data and Code for: Social Media and Mental Health

description: The diffusion of social media coincided with a worsening of mental health conditions among adolescents and young adults in the United States, giving rise to speculation that social media might be detrimental to mental health. In this paper, we provide quasi-experimental estimates of the impact of social media on mental health by leveraging a unique natural experiment: the staggered introduction of Facebook across U.S. colleges. Our analysis couples data on student mental health around the years of Facebook's expansion with a generalized difference-in-differences empirical strategy. We find that the roll-out of Facebook at a college increased symptoms of poor mental health, especially depression. We also find that, among students predicted to be most susceptible to mental illness, the introduction of Facebook led to increased utilization of mental healthcare services. Lastly, we find that, after the introduction of Facebook, students were more likely to report experiencing impairments to academic performance resulting from poor mental health. Additional evidence on mechanisms suggests that the results are due to Facebook fostering unfavorable social comparisons.
DOI: 10.6084/m9.figshare.20696866
title: CTMD.xlsx

description: Relevant data of cable temperature mapping model
DOI: 10.6084/m9.figshare.21155419.v3
title: Dataset of freshwater macroinvertebrate occurrences from Cuba

description: Dataset of georeferenced occurrence records of freshwater flatworms (Platyhelminthes: Tricladida), insects (Ephemeroptera, Odonata, Hemiptera, Trichoptera, Coleoptera, Diptera), crabs and shrimps (Crustacea: Decapoda), and mollusks (Mollusca) of Cuba. The information was collated from scientific literature, unpublished field records, museum collections and online databases. The dataset is organized in 31 fields that contains information about the taxonomic classification of each recorded species; sex, and life stage of individuals; location, author and date of the record and a reference to the original data source.
DOI: 10.25574/21122
title: Chandra X-ray Observatory ObsId 21122

description: A possible off-axis GRB in a nearby galaxy
DOI: 10.34740/kaggle/dsv/4464787
title: Mahanagar Yatayat Dataset
DOI: 10.17632/wgmnbmmm7w.1
title: Data-school type-PSAT & CTAT analysis

description:  Before, any teaching was done, form-two students were given a pretest on Critical thinking ability and on problem solving ability. This was done to check their  level of knowledge. Pretest covered  simple machines- a chapter in Physics and was done under similar conditions for four government and four private lower secondary schools.  Problem based learning method was used as an instruction for only schools under treatment group and those under control group used methods like talk and chalk , dictating notes and others. At the end of the a chapter, a post-test was administered.   Critical thinking ability  test (CTAT) scores and problem solving ability test (PSAT) scores were compiled in excel and analyzed using SPSS . PSA post-test showed a very high statistically significant effect between treatment and control group in favor of treatment group. Also high statistically significant difference between Government and Private schools in favor of Private schools. Students in treatment group from private schools have statistically performed well compared to their counterparts from government schools.
 Critical thinking abilities increased significantly after learning. There was a very high statistically significant difference in pre-and post-test. The same significant difference was found between teaching intervention in favor of Problem based learning (PBL).
DOI: 10.17632/wgmnbmmm7w.2
title: Data-school type-PSAT & CTAT analysis

description:  Before, any teaching was done, form-two students were given a pretest on Critical thinking ability and on problem solving ability. This was done to check their  level of knowledge. Pretest covered  simple machines- a chapter in Physics and was done under similar conditions for four government and four private lower secondary schools.  Problem based learning method was used as an instruction for only schools under treatment group and those under control group used methods like talk and chalk , dictating notes and others. At the end of the a chapter, a post-test was administered.   Critical thinking ability  test (CTAT) scores and problem solving ability test (PSAT) scores were compiled in excel and analyzed using SPSS . PSA post-test showed a very high statistically significant effect between treatment and control group in favor of treatment group. Also high statistically significant difference between Government and Private schools in favor of Private schools. Students in treatment group from private schools have statistically performed well compared to their counterparts from government schools.
 Critical thinking abilities increased significantly after learning. There was a very high statistically significant difference in pre-and post-test. The same significant difference was found between teaching intervention in favor of Problem based learning (PBL).
DOI: 10.17632/k33xvnxhdb.1
title: Code & Data for "Viral infection switches the balance between bacterial and eukaryotic recyclers of organic matter during coccolithophore blooms"

description: Code & Data for "Viral infection switches the balance between bacterial and eukaryotic recyclers of organic matter during coccolithophore blooms"
Data also available on Dryad: (https://doi.org/10.5061/dryad.q573n5tfr)
Sequences are deposited on NCBI: Bioproject PRJNA694552: 16S data is available under Biosample SAMN17576248 and 18S data is available under Biosample SAMN20295136
Flow cam data is deposited on Ecotaxa: "Flowcam Composite Aquacosm_2018_VIMS-Ehux"
DOI: 10.17632/4s57j4zc7g.1
title: FILTER_BUBBLE_AND_LEARNING_IN_THE_DIGITAL_AGE_rawData

description: These data refers to the paper entitled "FILTER BUBBLE AND LEARNING IN THE DIGITAL AGE: a study between Brazilian children and adolescents". Data were analyzed by Jamovi software.
DOI: 10.17632/4s57j4zc7g.2
title: FILTER_BUBBLE_AND_LEARNING_IN_THE_DIGITAL_AGE_rawData

description: These data refers to the paper entitled "Social Networking Sites information versus school information: A high school students' perception". Data were analyzed by Jamovi software.
DOI: 10.17632/4s57j4zc7g.3
title: Social_Networking_Sites_information_versus_school_information_rawData

description: These data refers to the paper entitled "Social Networking Sites information versus school information: A high school students' perception". Data were analyzed by Jamovi software.
DOI: 10.5519/qd.uxkbcj2w
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (39 records)
DOI: 10.17632/v362rp78dc.1
title: Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes

description: There are eight separate directories for each category of news. Each directory contains CSV files that have five columns, including the news article, category, heading, publication date, and source of the news (newspaper). The data is kept in raw format as is; no cleaning, stemming or any type of preprocessing is applied after scraping. There are about 665K articles and 12.5M sentences with 185.5M words in the dataset. We add a folder called balanced_dataset that contains a balanced dataset where each category has 40K articles, and the total number of articles is 320K.
DOI: 10.17632/v362rp78dc.2
title: Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes

description: Knowledge is central to human and scientific developments. Natural Language Processing (NLP) allows automated analysis and creation of knowledge. Data is a crucial NLP and machine learning ingredient. The scarcity of open datasets is a well-known problem in the machine and deep learning research. This is very much the case for textual NLP datasets in English and other major world languages. For the Bangla language, the situation is even more challenging and the number of large datasets for NLP research is practically nil. We hereby present Potrika, a large single-label Bangla news article textual dataset curated for NLP research from six popular online news portals in Bangladesh (Jugantor, Jaijaidin, Ittefaq, Kaler Kontho, Inqilab, and Somoyer Alo) for the period 2014-2020. The articles are classified into eight distinct categories (National, Sports, International, Entertainment, Economy, Education, Politics, and Science & Technology) providing five attributes (News Article, Category, Headline, Publication Date, and Newspaper Source). The raw dataset contains 185.51 million words and 12.57 million sentences contained in 664,880 news articles. Moreover, using NLP augmentation techniques, we create from the raw (unbalanced) dataset another (balanced) dataset comprising 320,000 news articles with 40,000 articles in each of the eight news categories. Potrika contains both datasets (raw and balanced) to suit a wide range of NLP research. By far, to the best of our knowledge, Potrika is the largest and the most extensive dataset for news classification.
DOI: 10.17632/v362rp78dc.3
title: Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes

description: Knowledge is central to human and scientific developments. Natural Language Processing (NLP) allows automated analysis and creation of knowledge. Data is a crucial NLP and machine learning ingredient. The scarcity of open datasets is a well-known problem in the machine and deep learning research. This is very much the case for textual NLP datasets in English and other major world languages. For the Bangla language, the situation is even more challenging and the number of large datasets for NLP research is practically nil. We hereby present Potrika, a large single-label Bangla news article textual dataset curated for NLP research from six popular online news portals in Bangladesh (Jugantor, Jaijaidin, Ittefaq, Kaler Kontho, Inqilab, and Somoyer Alo) for the period 2014-2020. The articles are classified into eight distinct categories (National, Sports, International, Entertainment, Economy, Education, Politics, and Science & Technology) providing five attributes (News Article, Category, Headline, Publication Date, and Newspaper Source). The raw dataset contains 185.51 million words and 12.57 million sentences contained in 664,880 news articles. Moreover, using NLP augmentation techniques, we create from the raw (unbalanced) dataset another (balanced) dataset comprising 320,000 news articles with 40,000 articles in each of the eight news categories. Potrika contains both datasets (raw and balanced) to suit a wide range of NLP research. By far, to the best of our knowledge, Potrika is the largest and the most extensive dataset for news classification.

Further details of the dataset, its collection, and usage for deep journalism including detection of the multi-perspective parameters for transportation can be found in our article here: https://doi.org/10.3390/su14095711.
DOI: 10.17632/v362rp78dc.4
title: Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes

description: Knowledge is central to human and scientific developments. Natural Language Processing (NLP) allows automated analysis and creation of knowledge. Data is a crucial NLP and machine learning ingredient. The scarcity of open datasets is a well-known problem in the machine and deep learning research. This is very much the case for textual NLP datasets in English and other major world languages. For the Bangla language, the situation is even more challenging and the number of large datasets for NLP research is practically nil. We hereby present Potrika, a large single-label Bangla news article textual dataset curated for NLP research from six popular online news portals in Bangladesh (Jugantor, Jaijaidin, Ittefaq, Kaler Kontho, Inqilab, and Somoyer Alo) for the period 2014-2020. The articles are classified into eight distinct categories (National, Sports, International, Entertainment, Economy, Education, Politics, and Science & Technology) providing five attributes (News Article, Category, Headline, Publication Date, and Newspaper Source). The raw dataset contains 185.51 million words and 12.57 million sentences contained in 664,880 news articles. Moreover, using NLP augmentation techniques, we create from the raw (unbalanced) dataset another (balanced) dataset comprising 320,000 news articles with 40,000 articles in each of the eight news categories. Potrika contains both datasets (raw and balanced) to suit a wide range of NLP research. By far, to the best of our knowledge, Potrika is the largest and the most extensive dataset for news classification.

Further details of the dataset, its collection, and usage can be found in our article here: https://doi.org/10.48550/arXiv.2210.09389.
DOI: 10.17632/pxmh4jsb54.1
title: POLQ seals post-replicative ssDNA gaps to maintain genome stability in BRCA-deficient cancer cells, Belan et al

description: A file containing all the original images shown in the manuscript with cropped areas marked for the manuscript entitled 'POLQ seals post-replicative ssDNA gaps to maintain genome stability in BRCA-deficient cancer cells' by Belan et al.
DOI: 10.23645/epacomptox.21502758.v2
title: High Throughput Transcriptomics (HTTr)

description: Science Inventory, CCTE products: https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25 <br>
DOI: 10.6084/m9.figshare.20468700
title: Annual total emission (NetCDF)

description: Annual total emission of VOCs, NOx, PM2.5, SO2, CO, and NH3 in NetCDF format. The unit is ton/km2/yr
DOI: 10.6084/m9.figshare.20468700.v1
title: Annual total emission (NetCDF)

description: Annual total emission of VOCs, NOx, PM2.5, SO2, CO, and NH3 in NetCDF format. The unit is ton/km2/yr
DOI: 10.6084/m9.figshare.20468745
title: Annual total emission (Shapefile)

description: Annual total emission of VOCs, NOx, PM2.5, SO2, CO, and NH3 in Shapefile format. The unit is ton/km2/yr
DOI: 10.6084/m9.figshare.20468748
title: Monthly mean emission from rail sector (NetCDF)

description: Monthly mean emission from railroads sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468748.v1
title: Monthly mean emission from rail sector (NetCDF)

description: Monthly mean emission from railroads sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468751
title: Monthly mean emission from nonroad sector (NetCDF, Part I)

description: Monthly mean emission from on-land mobile sources not on roads or railroads in NetCDF format (Part I), providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468751.v1
title: Monthly mean emission from nonroad sector (NetCDF, Part I)

description: Monthly mean emission from on-land mobile sources not on roads or railroads in NetCDF format (Part I), providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468754
title: Monthly mean emission from rwc sector (NetCDF)

description: Monthly mean emission from residential wood combustion sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468754.v1
title: Monthly mean emission from rwc sector (NetCDF)

description: Monthly mean emission from residential wood combustion sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468760
title: Monthly mean emission from np_oilgas sector (NetCDF)

description: Monthly mean emission from nonpoint oil and gas-production-related sources sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468760.v1
title: Monthly mean emission from np_oilgas sector (NetCDF)

description: Monthly mean emission from nonpoint oil and gas-production-related sources sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468763
title: Monthly mean emission from nonroad sector (NetCDF, Part II)

description: Monthly mean emission from on-land mobile sources not on roads or railroads in NetCDF format (Part II), providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468763.v1
title: Monthly mean emission from nonroad sector (NetCDF, Part II)

description: Monthly mean emission from on-land mobile sources not on roads or railroads in NetCDF format (Part II), providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468982
title: Monthly mean emission from afdust sector (NetCDF)

description: Monthly mean emission from fugitive dusts in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20468982.v1
title: Monthly mean emission from afdust sector (NetCDF)

description: Monthly mean emission from fugitive dusts in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20469069
title: Monthly mean emission from ag sector (NetCDF)

description: Monthly mean emission from agricultural sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20469069.v1
title: Monthly mean emission from ag sector (NetCDF)

description: Monthly mean emission from agricultural sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20474004.v1
title: Monthly mean emission from onroad sector (NetCDF)

description: Monthly mean emission from on-land mobile sources that drive on roads in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20474232
title: Monthly mean emission from airport sector (NetCDF)

description: Monthly mean emission from airport sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20474004
title: Monthly mean emission from onroad sector (NetCDF)

description: Monthly mean emission from on-land mobile sources that drive on roads in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20474079
title: Monthly mean emission from nonpt sector (NetCDF)

description: Monthly mean emission from other non-point sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20474079.v1
title: Monthly mean emission from nonpt sector (NetCDF)

description: Monthly mean emission from other non-point sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.
DOI: 10.6084/m9.figshare.20474232.v1
title: Monthly mean emission from airport sector (NetCDF)

description: Monthly mean emission from airport sources in NetCDF format, providing the model species for CB6 mechanism. The unit is moles/s.