cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3841050
title: Results "Anti-obesity effects of individual or combination treatment with Spirulina platensis and green coffee bean aqueous extracts in high-fat diet-induced obese rats"

description: <strong>Background</strong>: Obesity, a chronic disease, is associated with serious health risks, including premature mortality. This study aimed to investigate the anti-obesity effects of individual or combination treatment with <em>Spirulina platensis</em> and green coffee bean aqueous extracts in high-fat diet-induced (HFD) obese rats. <strong>Methods</strong>: Rats were fed on HFD to induce obesity. Corn oil in the HFD accounted for 50.98 % of the calories. Fifty rats were divided into the following five groups (10 rats/group): control, HFD, HFD-<em>Spirulina</em>, HFD-coffee, HFD-<em>Spirulina</em> and coffee co-treatment groups. The serum levels of lipid, leptin, and insulin, as well as the hepatic mRNA levels of fatty acid synthase (FAS), peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α), and peroxisome proliferator-activated alpha receptor (PPARα) were estimated. <strong>Results</strong>: The <em>Spirulina</em> and/or green coffee bean aqueous extracts decreased the final bodyweight and liver weight, and the serum levels of alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase. Additionally, the extracts decreased the serum levels of total cholesterol, triacylglycerol, low-density lipoprotein-cholesterol, leptin, and glucose, and enhanced the serum insulin level. Furthermore, the extracts enhanced the PGC-1α and PPARα mRNA levels and decreased the FAS mRNA levels. <strong>Conclusion</strong>: The individual or combination treatment with <em>Spirulina</em> and green coffee bean extracts decreased obesity-induced hyperlipidemia. Thus, <em>Spirulina platensis</em> and green coffee can be potentially used to treat obesity.
DOI: 10.15468/38wmsk
title: Revision of the costata-group of Alona s. lato (Cladocera: Anomopoda: Chydoridae) confirms its generic status

description: This dataset contains the digitized treatments in Plazi based on the original journal article Sinev, Artem Y., Dumont, Henri J. (2016): Revision of the costata-group of Alona s. lato (Cladocera: Anomopoda: Chydoridae) confirms its generic status. European Journal of Taxonomy 223: 1-38, DOI: http://dx.doi.org/10.5852/ejt.2016.223
DOI: 10.25919/5ec9d87e6f2bf
title: Parkes observations for project P1038 semester 2020APRS_04

description: PSR~J1759-2402 is one of a small handful of pulsars which are in orbit about high mass stars. Its orbital period is 8.2 years and the orbit is highly eccentric with periastron expected in 2021 January. Although discovered at Parkes, the Lovell telescope has been monitoring the pulsar over many years. However, it's restricted bandwidth and lack of polarization capability make it unsuitable to follow the pulsar as it enters and leaves the eclipse by the companion. In contrast, the UWL on Parkes with its wide-band and excellent polarization characteristics means that we can determine scattering, polarization, dispersion measure and rotation measure changes as the pulsar enters its companion wind. We request weekly observations of the pulsar to track its progress around the orbit.
DOI: 10.15468/dacjnw
title: A new species of Lynceus Müller, 1776 from New Caledonia (Crustacea: Branchiopoda: Laevicaudata) from dolines, with remarks on zoogeography

description: This dataset contains the digitized treatments in Plazi based on the original journal article Olesen, Jørgen, Pöllabauer, Christine, Sigvardt, Zandra M. S., Rogers, D. Christopher (2016): A new species of Lynceus Müller, 1776 from New Caledonia (Crustacea: Branchiopoda: Laevicaudata) from dolines, with remarks on zoogeography. European Journal of Taxonomy 224: 1-18, DOI: http://dx.doi.org/10.5852/ejt.2016.224
DOI: 10.25919/5ec9da584cc80
title: Parkes observations for project P1059 semester 2020APRS_05

description: We propose to observe a sample of 22 pulsars at high Galactic latitudes with the Parkes Ultra-Wideband Low (UWL) receiver. This sample of pulsars does not have flux densities nor polarisation measured before. The goal is to characterise their wideband properties in polarisation, spectrum and interstellar scintillation. Such properties will help us develop imaging pulsar search techniques for future radio continuum surveys, such as with the Australian SKA Pathfinder (ASKAP). Wideband spectrum, polarisation and scintillation of pulsars will also be useful for studies of pulsar radiation mechanism and interstellar medium at high Galactic latitudes.
DOI: 10.15468/a6q9r3
title: Cave-dwelling Coecobrya from southern China with a survey of clypeal chaetae in Entomobryoidea (Collembola)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zhang, Feng, Bedos, Anne, Deharveng, Louis (2016): Cave-dwelling Coecobrya from southern China with a survey of clypeal chaetae in Entomobryoidea (Collembola). European Journal of Taxonomy 226: 1-21, DOI: http://dx.doi.org/10.5852/ejt.2016.226
DOI: 10.15468/grrxad
title: Two new species of Anamastigona from Cyprus and an updated key to species of the genus (Diplopoda: Chordeumatida: Anthroleucosomatidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Vagalinski, Boyan, Golovatch, Sergei I. (2016): Two new species of Anamastigona from Cyprus and an updated key to species of the genus (Diplopoda: Chordeumatida: Anthroleucosomatidae). European Journal of Taxonomy 227: 1-19, DOI: http://dx.doi.org/10.5852/ejt.2016.227
DOI: 10.5281/zenodo.3841231
title: Standard Distributions of Blood Tests for Public Use

description: This dataset is the distribution parameters obtained by approximating the distribution of blood test values taken from inpatients in a Japanese hospital by a lognormal distribution or an exponential distribution. The parameters P1, P2 and P3 of the lognormal distribution are used in the following equation.<br> P1*exp(-(ln(x/P2)/P3)^2) The parameters P1 and P2 of the exponential distribution are used in the following.<br> P1*exp(-P2*x) This file is CSV with UTF-8 charset, and the columns are as follows. ---<br> Test name<br> Test name in Japanese<br> Unit of the value<br> Distribution type (LogNormal or Exp)<br> P1<br> P2<br> P3<br> P1 Error(1sigma)<br> P2 Error(1sigma)<br> P3 Error(1sigma)<br> Number of data points used to make this distribution<br> Bin width used to make the distribution<br> --- Any researchers can use this dataset without privacy issues.<br> CC BY-NC 4.0<br>
DOI: 10.5281/zenodo.3841232
title: Standard Distributions of Blood Tests for Public Use

description: This dataset is the distribution parameters obtained by approximating the distribution of blood test values taken from inpatients in a Japanese hospital by a lognormal distribution or an exponential distribution. The parameters P1, P2 and P3 of the lognormal distribution are used in the following equation.<br> P1*exp(-(ln(x/P2)/P3)^2) The parameters P1 and P2 of the exponential distribution are used in the following.<br> P1*exp(-P2*x) This file is CSV with UTF-8 charset, and the columns are as follows. ---<br> Test name<br> Test name in Japanese<br> Unit of the value<br> Distribution type (LogNormal or Exp)<br> P1<br> P2<br> P3<br> P1 Error(1sigma)<br> P2 Error(1sigma)<br> P3 Error(1sigma)<br> Number of data points used to make this distribution<br> Bin width used to make the distribution<br> --- Any researchers can use this dataset without privacy issues.<br> CC BY-NC 4.0<br>
DOI: 10.15468/c4fuvr
title: A new genus and species of axiid shrimp (Crustacea, Decapoda) from a southwestern Indian Ocean seamount

description: This dataset contains the digitized treatments in Plazi based on the original journal article Dworschak, Peter C. (2016): A new genus and species of axiid shrimp (Crustacea, Decapoda) from a southwestern Indian Ocean seamount. European Journal of Taxonomy 229: 1-11, DOI: http://dx.doi.org/10.5852/ejt.2016.229
DOI: 10.21227/qe4y-cg57
title: US data from in vivo rat kidney

description: This demo is intended to implement Ultrasound Localization Microscopy by a modified sub-pixel convolutional neural network (mSPCN-ULM). The detailed information can be referred in Liu et al. "Deep Learning for Ultrasound Localization Microscopy (DOI: 10.1109/TMI.2020.2986781)".
DOI: 10.5281/zenodo.3841636
title: A survey of Odonata of Puerto Rico

description: Data set associated with the manuscript: Ramírez, A., N. Maldonado-Benítez, A. Mariani-Ríos, J. Figueroa-Santiago. 2020. Dragonflies and damselflies (Odonata) from Puerto Rico: A checklist with notes on distribution and habitat. For additional information, visit: The Ramirez Lab web page PR-LSAMP Dragonfly project page
DOI: 10.5281/zenodo.3841637
title: A survey of Odonata of Puerto Rico

description: Data set associated with the manuscript: Ramírez, A., N. Maldonado-Benítez, A. Mariani-Ríos, J. Figueroa-Santiago. 2020. Dragonflies and damselflies (Odonata) from Puerto Rico: A checklist with notes on distribution and habitat. For additional information, visit: The Ramirez Lab web page PR-LSAMP Dragonfly project page
DOI: 10.5281/zenodo.3841073
title: Energiemessungen der Docker-Komponenten

description: Hier werden die Ergebnisse der Energiemessungen der Docker-Komponenten dargestellt. Zu finden sind alle Messungen der letzten Messreihe.
DOI: 10.5281/zenodo.3841074
title: Energiemessungen der Docker-Komponenten

description: Hier werden die Ergebnisse der Energiemessungen der Docker-Komponenten dargestellt. Zu finden sind alle Messungen der letzten Messreihe.
DOI: 10.15468/39daay
title: An unusually elongate endogeic centipede from Sardinia (Chilopoda: Geophilidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Bonato, Lucio, Zapparoli, Marzio, Drago, Leandro, Minelli, Alessandro (2016): An unusually elongate endogeic centipede from Sardinia (Chilopoda: Geophilidae). European Journal of Taxonomy 231: 1-19, DOI: http://dx.doi.org/10.5852/ejt.2016.231
DOI: 10.15468/u73uua
title: Taxonomic revision of the genus Arsipoda Erichson, 1842 (Coleoptera, Chrysomelidae) in New Caledonia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Samuelson, Allan, Biondi, Maurizio (2016): Taxonomic revision of the genus Arsipoda Erichson, 1842 (Coleoptera, Chrysomelidae) in New Caledonia. European Journal of Taxonomy 230: 1-61, DOI: http://dx.doi.org/10.5852/ejt.2016.230
DOI: 10.21227/s1en-t326
title: US data from in vivo rat kidney

description: This demo is intended to implement Ultrasound Localization Microscopy by a modified sub-pixel convolutional neural network (mSPCN-ULM). The detailed information can be referred in Liu et al. "Deep Learning for Ultrasound Localization Microscopy (DOI: 10.1109/TMI.2020.2986781)".
DOI: 10.21227/6pa6-e484
title: US data from in vivo rat kidney

description: This demo is intended to implement Ultrasound Localization Microscopy by a modified sub-pixel convolutional neural network (mSPCN-ULM). The detailed information can be referred in Liu et al. "Deep Learning for Ultrasound Localization Microscopy (DOI: 10.1109/TMI.2020.2986781)".
DOI: 10.21227/3r3b-b015
title: US data from in vivo rat kidney

description: This demo is intended to implement Ultrasound Localization Microscopy by a modified sub-pixel convolutional neural network (mSPCN-ULM). The detailed information can be referred in Liu et al. "Deep Learning for Ultrasound Localization Microscopy"(DOI: 10.1109/TMI.2020.2986781).
DOI: 10.6084/m9.figshare.12145842.v2
title: A novel multi-stage ensemble model with voting-based outlier adaptation and balanced sampling for credit scoring

description: Three datasets from the UC Irvine (UCI) machine learning repository, that is, the Australian, German, and Japanese datasets, were adopted for the current study. The Australian credit dataset contains 690 samples, of which 307 are positive and 383 are negative. The dimensions of its input features are 15. The German credit dataset contains 1000 samples, 700 of which are positive and 300 are negative. The dimensions of its input features are 21. The Japanese credit dataset contains 690 samples, of which 383 are positive and 307 are negative. The dimensions of its input features are 16.
DOI: 10.7910/dvn/vxjpn5/dsvqrn
title: Bechteletal_ED_Fig1B.pdf

description: :unav
DOI: 10.5281/zenodo.3840841
title: Replication Package for the Paper: "Code Smells Detection via Code Review: An Empirical Study"

description: This repository contains the data and results from the paper "Code Smells Detection via Code Review: An Empirical Study" submitted to ESEM 2020. <strong>1. data folder</strong> The data folder contains the retrieved 269 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell Term, Code Smell Discussion, and Source Code URL. <strong>2. scripts floder</strong> The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms. <em>smell-term/general_smell_terms.txt</em> contains general code smell terms, such as "code smell". <em>smell-term/specific_smell_terms.txt</em> contains specific code smell terms, such as "dead code". <em>smell-term/misspelling_terms_of_smell.txt</em> contains the misspelling terms of 'smell', such as "ssell". <em>get_changes.py</em> is used for getting code changes from OpenStack. <em>get_comments.py</em> is used for getting review comments for each code change. <em>smell_search.py</em> is used for searching review comments that contain code smell terms. <strong>3. project folder</strong> The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download. <em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool. <em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.
DOI: 10.5281/zenodo.3840842
title: Replication Package for the Paper: "Code Smells Detection via Code Review: An Empirical Study"

description: This repository contains the data and results from the paper "Code Smells Detection via Code Review: An Empirical Study" submitted to ESEM 2020. <strong>1. data folder</strong> The data folder contains the retrieved 269 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell Term, Code Smell Discussion, and Source Code URL. <strong>2. scripts floder</strong> The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms. <em>smell-term/general_smell_terms.txt</em> contains general code smell terms, such as "code smell". <em>smell-term/specific_smell_terms.txt</em> contains specific code smell terms, such as "dead code". <em>smell-term/misspelling_terms_of_smell.txt</em> contains the misspelling terms of 'smell', such as "ssell". <em>get_changes.py</em> is used for getting code changes from OpenStack. <em>get_comments.py</em> is used for getting review comments for each code change. <em>smell_search.py</em> is used for searching review comments that contain code smell terms. <strong>3. project folder</strong> The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download. <em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool. <em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.
DOI: 10.7910/dvn/vxjpn5/nfqfab
title: 03-01 time path choice analysis.do

description: :unav
DOI: 10.5281/zenodo.3463488
title: Diversity and distribution of intertidal marine species in Singapore

description: WildSingapore Wild Fact Sheets dataset
DOI: 10.5281/zenodo.3463489
title: Diversity and distribution of intertidal marine species in Singapore

description: WildSingapore Wild Fact Sheets dataset
DOI: 10.5519/qd.gaxennsc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.3840464
title: Variant analysis of SARS-CoV-2 genomes

description: These are supplemental files accompanying a publication.
DOI: 10.5281/zenodo.3840465
title: Variant analysis of SARS-CoV-2 genomes

description: These are supplemental files accompanying a publication.
DOI: 10.5281/zenodo.3840471
title: GitRec - Github Project Recommender Systems

description: This dataset contains the data collected using the Google API for the GHTorrent project and which were applied in the doctoral thesis directed to recommending projects on the GitHub platform
DOI: 10.5281/zenodo.3840472
title: GitRec - Github Project Recommender Systems

description: This dataset contains the data collected using the Google API for the GHTorrent project and which were applied in the doctoral thesis directed to recommending projects on the GitHub platform
DOI: 10.5281/zenodo.3835848
title: Data archive for "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network"

description: This datasets supports the paper "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network" submitted to IEEE Transactions in Geoscience and Remote Sensing. A preprint of the paper can be found here: https://arxiv.org/abs/2005.10374. The code that uses these data is available at https://github.com/jleinonen/downscaling-rnn-gan. The file "goes-samples-2019-128x128.nc" contains the training dataset called "GOES-COT" in the paper, consisting of cloud optical depth measurements from the GOES-16 satellite. The files "gen_weights*.nc" contain the generator weights saved at different time steps during training for the two different datasets described in the paper.<br>
DOI: 10.5281/zenodo.3835849
title: Data archive for "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network"

description: This datasets supports the paper "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network" submitted to IEEE Transactions in Geoscience and Remote Sensing. A preprint of the paper can be found here: https://arxiv.org/abs/2005.10374. The code that uses these data is available at https://github.com/jleinonen/downscaling-rnn-gan. The file "goes-samples-2019-128x128.nc" contains the training dataset called "GOES-COT" in the paper, consisting of cloud optical depth measurements from the GOES-16 satellite. The files "gen_weights*.nc" contain the generator weights saved at different time steps during training for the two different datasets described in the paper.<br>
DOI: 10.17909/t9-n9fp-gs62
title: All Kepler Documents

description: A collection of documents and documentation for the Kepler mission.
DOI: 10.18112/openneuro.ds002837.v1.0.0
title: Naturalistic Neuroimaging Database
DOI: 10.25345/c5n99x
title: MassIVE MSV000085459 - Changes in the strength of protein-protein interactions portend oncogenic activity and generate actionable targets for cancer
title: Stresses associated with disease may pathologically remodel the cellular proteins by increasing the interaction strength between chaperome members, and between the chaperome and the proteins it regulates. How these changes in protein-protein interaction strength are executed remains unknown. Our study shows that the ER chaperone GRP94 employs a specific glycosylation pattern to alter its conformational fitness and to stabilize a state most permissive for stable interactions with proteins at the plasma membrane.
DOI: 10.6073/pasta/9c5ff9a1d26b77e095e5caa98bb75c35
title: Alpine species transplant experiment within the sensor network for 2019, weekly

description: Weekly monitoring of survival and other fitness traits of 11 transplanted alpine species in addition to, non-transplanted, native, individuals. Individuals were monitored from early June to the end of August for survival and other fitness traits. Beginning in early July individuals from each species were transplanted to grids that were established near existing soil moisture sensors. Individuals were tracked until all had senesced however senescence was only indicated in transplants if it was irregular from native individuals.
DOI: 10.21227/q8pj-4x27
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets were captured by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's data sharing 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 with an exact location that contained any of the previously mentioned keywords.Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 100+ million tweets) shared in the Coronavirus (COVID-19) Tweets Dataset.If you need the geolocation-based data starting March 20, 2020, then use the Coronavirus (COVID-19) Tweets Dataset and hydrate the IDs while adding the following condition:data = json.loads(data) if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.
DOI: 10.15482/usda.adc/1518706
title: International Climate Benchmarks and Input Parameters for a Stochastic Weather Generator, CLIGEN

description: This dataset represents CLIGEN input parameters for locations in 68 countries. CLIGEN is a point-scale stochastic weather generator that produces long-term weather simulations with daily output. The input parameters are essentially monthly climate statistics that also serve as climate benchmarks. Three unique input parameter sets are differentiated by having been produced from 30-year, 20-year and 10-year minimum record lengths that correspond to 7673, 2336, and 2694 stations, respectively. The primary source of data is the NOAA GHCN-Daily dataset, and due to data gaps, records longer than the three minimum record lengths were often queried to produce the needed number of complete monthly records. The vast majority of stations used at least some data from the 2000's, and temporal coverages are shown in the Excel table for each station. CLIGEN has various applications including being used to force soil erosion models. This dataset may reduce the effort needed in preparing climate inputs for such applications.