cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/111183
title: Multiplexed data collected during research cruise AT15-34 using a Hawaii UHDAS instrument system onboard the platform RV Atlantis
DOI: 10.7284/108541
title: Multiplexed data collected during research cruise AT15-35 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/108544
title: Multiplexed data collected during research cruise AT15-36 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/111184
title: Multiplexed data collected during research cruise AT15-36 using a Hawaii UHDAS instrument system onboard the platform RV Atlantis
DOI: 10.7284/104597
title: Multibeam Echosounder data collected during research cruise AT15-36 using a SeaBeam 2112 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/108547
title: Multiplexed data collected during research cruise AT15-37 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/108551
title: Multiplexed data collected during research cruise AT15-38 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/111185
title: Multiplexed data collected during research cruise AT15-38 using a Hawaii UHDAS instrument system onboard the platform RV Atlantis
DOI: 10.7284/104598
title: Multibeam Echosounder data collected during research cruise AT15-38 using a SeaBeam 2112 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7722413
title: Global surface ocean CO2 in 1990-2017 reconstructed by neural network

description: This data set includes the global surface ocean CO2 fugacity and fluxes in 1990-2017 in 1x1 degree resolution. The monthly distributions were reconstruct using the feedforward neural network model of Zeng et al. (2014; DOI: 10.1175/JTECH-D-13-00137.1) with the SOCAT version-6 CO2 data (https://www.socat.info/index.php/data-access/). Please contact zeng at nies .go .jp for details.<br><br>
DOI: 10.7284/108554
title: Multiplexed data collected during research cruise AT15-39 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/111186
title: Multiplexed data collected during research cruise AT15-39 using a Hawaii UHDAS instrument system onboard the platform RV Atlantis
DOI: 10.6084/m9.figshare.7722413.v1
title: Global surface ocean CO2 in 1990-2017 produced by neural network

description: Global surfice ocean CO2;Ocean CO2 flux estimate;1x1 degree, 1990-2017.<br><br>
DOI: 10.7284/104599
title: Multibeam Echosounder data collected during research cruise AT15-39 using a SeaBeam 2112 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7722413.v2
title: Global surface ocean CO2 in 1990-2017 reconstruced by neural network

description: This data set includes the global surface ocean CO2 fugacity and fluxes in 1990-2017 in 1x1 degree resolution. The monthly distributions were reconstruct using the feedforward neural network model of Zeng et al. (2014; DOI: 10.1175/JTECH-D-13-00137.1) with the SOCAT version-6 CO2 data (https://www.socat.info/index.php/data-access/). Please contact zeng at nies .go .jp for details.<br><br>
DOI: 10.6084/m9.figshare.7722413.v3
title: Global surface ocean CO2 in 1990-2017 reconstructed by neural network

description: This data set includes the global surface ocean CO2 fugacity and fluxes in 1990-2017 in 1x1 degree resolution. The monthly distributions were reconstruct using the feedforward neural network model of Zeng et al. (2014; DOI: 10.1175/JTECH-D-13-00137.1) with the SOCAT version-6 CO2 data (https://www.socat.info/index.php/data-access/). Please contact zeng at nies .go .jp for details.<br><br>
DOI: 10.7284/108557
title: Multiplexed data collected during research cruise AT15-40 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7722233
title: PT - Aplicativos dos PPG brasileiros

description: Banco de dados referente a produção tecnológica do item – Aplicativos - da pós graduação brasileira, após análise e tratamento dos dados extraídos da Plataforma Sucupira para fins de desenvolvimento da Tese de Vívian Costa Alves, vinculada ao Programa de Pós Graduação em Engenharia e Gestão do Conhecimento da Universidade Federal de Santa Catarina.
DOI: 10.6084/m9.figshare.7722278
title: PONE-D-18-34216 Walker synchronization

description: Videos of pairs of people walking in cities (.avi files) with pose estimates in image coordinates (.pkl files)<br>Video files are provided for videos that have a Creative Commons license. URLs for all videos are provided in file S1.csv.<br>Walker data files (Python .pkl files) contain pose estimates from each frame in image coordinates<br>Python .pkl files contain columns with information for each frame of the video file.<br>Legend for .pkl files<br>Column : data frame : video frame index person : walker index with separate label for each walker belonging to the pair part : body part index of key point with separate labels for each body part (Neck: 1, Right ankle: 10, Left ankle: 13, Right ear: 16, Left ear: 17 ) x: x coordinates of key point in pixel units y: y coordinates of key point in pixel units c: confidence level for key point <br>
DOI: 10.6084/m9.figshare.7722233.v1
title: PT - Aplicativos dos PPG brasileiros

description: Banco de dados referente a produção tecnológica do item – Aplicativos - da pós graduação brasileira, após análise e tratamento dos dados extraídos da Plataforma Sucupira para fins de desenvolvimento da Tese de Vívian Costa Alves, vinculada ao Programa de Pós Graduação em Engenharia e Gestão do Conhecimento da Universidade Federal de Santa Catarina.
DOI: 10.7284/108560
title: Multiplexed data collected during research cruise AT15-41 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7722116
title: PT - Patentes dos PPG brasileiros.csv

description: Banco de dados referente a produção tecnológica do item – <b>Patentes</b> - da pós graduação brasileira, após análise e tratamento dos dados extraídos da Plataforma Sucupira para fins de desenvolvimento da Tese de Vívian Costa Alves, vinculada ao Programa de Pós Graduação em Engenharia e Gestão do Conhecimento da Universidade Federal de Santa Catarina.
DOI: 10.6084/m9.figshare.7722071
title: Drugs, Active Ingredients and Diseases databases, a resource for analysis on diversification of drugs

description: Quantitative and qualitative data on active-ingredient drug composition are essential information for characterizing near-?eld exposure. Equally as important is the characterization of the relationship between one or many active ingredients in terms of the diseases they are prescribed for. Such evaluations however require quantitative and well-classi?ed information at di?erent levels. Here we present a dataset which comprises public information of 53,475 records, and contains details of 5,739 drugs, 2,318 diseases and 4,679 active pharmaceutical ingredients. The data's primary intended use is for exposure, risk and safety assessments. This dataset will allow researchers, physicians and pharmacists to evaluate the active substances at an anatomical level allowing patients with comorbidities to infer the range of di?erent active substances and possible side e?ects. This dataset also contains information about clinical and pharmacological classi?cation, which may help clinical researchers and physicians to decide the best treatment, informing the patient of the possible risks and in a certain way, for the evaluation of drug quality by pharmarceutical specialists. <br>
DOI: 10.7284/104600
title: Multibeam Echosounder data collected during research cruise AT15-41 using a SeaBeam 2112 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7722068
title: ICSE artifact

description: Adaptation dataset and variation dataset generated in paper "Analyzing and Supporting Adaptation of Online Code examples", in proceedings of International Conference of Software Engineering 2019 (ICSE'19). p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 24.0px Helvetica}
DOI: 10.6084/m9.figshare.7722068.v2
title: ICSE artifact

description: Adaptation dataset and variation dataset generated in paper "Analyzing and Supporting Adaptation of Online Code examples", in proceedings of International Conference of Software Engineering 2019 (ICSE'19). p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 24.0px Helvetica}
DOI: 10.6084/m9.figshare.7722071.v1
title: Drugs, Active Pharmaceutical Ingredients and Diseases databases, a resource for exposure-relevant data on diversification of the drug for decision-making

description: Quantitative and qualitative data on active-ingredient drug composition are essential information for characterizing near- eld exposure. Equally as important is the characterization of the relationship between one or many active ingredients in terms of the diseases they are prescribed for. Such evaluations however require quantitative and well-classi ed information at di erent levels. Here we present a dataset which comprises public information of 53,475 records, and contains details of 5,739 drugs, 2,318 diseases and 4,679 active pharmaceutical ingredients. The data's primary intended use is for exposure, risk and safety assessments. This dataset will allow researchers, physicians and pharmacists to evaluate the active substances at an anatomical level allowing patients with comorbidities to infer the range of di erent active substances and possible side e ects. This dataset also contains information about clinical and pharmacological classi cation, which may help clinical researchers and physicians to decide the best treatment, informing the patient of the possible risks and in a certain way, for the evaluation of drug quality by pharmarceutical specialists. <br>
DOI: 10.7284/101383
title: Multiplexed data collected during research cruise AT15-42 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7722068.v1
title: ICSE artifact

description: Adaptation dataset and variation dataset generated in paper "Analyzing and Supporting Adaptation of Online Code examples", in proceedings of International Conference of Software Engineering 2019 (ICSE'19). p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 24.0px Helvetica}
DOI: 10.7284/101381
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AT15-42 using a Hawaii UHDAS instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7721963
title: COIPIScohort.xlsx

description: The dataset contains data from children from COIPIS cohort of sex, age, percent of body fat and body mass index. COIPIS cohort started in 2012 in response to the need for establishing a prospective childhood obesity epidemiologic study. The sample consisted of 1061 girls and 1121 boys, from 3 to 17 years old. Participants were invited among ISSSTE right-holder teachers who were also members of the union, and patients treated at ISSSTE clinics distributed in Mexico City. Participants were examined every 6 months, since they were recruited until they turned 17 years old.
DOI: 10.6084/m9.figshare.7720901
title: JRC2018U_JRC2018F_h5

description: Transformations between JRC 2018 Unisex template and the JFRC 2018 Female template.<br>
DOI: 10.6084/m9.figshare.7721963.v1
title: COIPIScohort.xlsx

description: The dataset contains data from children from COIPIS cohort of sex, age, percent of body fat and body mass index. COIPIS cohort started in 2012 in response to the need for establishing a prospective childhood obesity epidemiologic study. The sample consisted of 1061 girls and 1121 boys, from 3 to 17 years old. Participants were invited among ISSSTE right-holder teachers who were also members of the union, and patients treated at ISSSTE clinics distributed in Mexico City. Participants were examined every 6 months, since they were recruited until they turned 17 years old.
DOI: 10.7284/101380
title: Expendable Probe data collected during research cruise AT15-42 using a Sippican MK12 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7720901.v1
title: JRC2018U_JRC2018F_h5

description: Transformations between JRC 2018 Unisex template and the JFRC 2018 Female template.<br>
DOI: 10.6084/m9.figshare.7719428
title: Organisms Environmental Results New.xlsx

description: Goes with a manuscript . Using matrix-assisted laser desorption time-of-flight (MALDI-TOF) mass spectra to identify bacteria from the environment by matching to translated DNA databases, byJames Kostas, Kenneth C. Parker<b></b><i></i><sub></sub><sup></sup><br> <b></b><i></i><sub></sub><sup></sup><b></b><i></i><sub></sub><sup></sup><br>
DOI: 10.7284/104601
title: Multibeam Echosounder data collected during research cruise AT15-42 using a SeaBeam 2112 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7719410
title: An Iterative Sparse-Group Lasso

description: In high-dimensional supervised learning problems, sparsity constraints in the solution often lead to better performance and interpretability of the results. For problems in which covariates are grouped and sparse structure are desired, both on group and within group levels, the sparse-group lasso (SGL) regularization method has proved to be very efficient. Under its simplest formulation, the solution provided by this method depends on two weight parameters that control the penalization on the coefficients. Selecting these weight parameters represents a major challenge. In most of the applications of the SGL, this problem is left aside, and the parameters are either fixed based on a prior information about the data, or chosen to minimize some error function in a grid of possible values. However, an appropriate choice of the parameters deserves more attention, considering that it plays a key role in the structure and interpretation of the solution. In this sense, we present a gradient-free coordinate descent algorithm that automatically selects the regularization parameters of the SGL. We focus on a more general formulation of this problem, which also includes individual penalizations for each group. The advantages of our approach are illustrated using both real and synthetic datasets. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7719398
title: Sympatric speciation in the Simuluim arcticum complex (Diptera: Simuludae)

description: Five separate data sets were included in our analyses: Alaska (Shields and Procunier 1982), Montana, Idaho, and eastern Washington (Shields 2013; Shields 2014; Shields and Shields 2017 and Shields, unpub. data); throughout the range of <i>S. arcticum</i> (Conflitti <i>et al</i>. 2016); western Canada (Procunier, unpub.); and throughout the range of <i>S. arcticum</i> (Adler <i>et al</i>. 2004. <br>Locations for 299 sites were determined with varying accuracy. There were 125 sites associated with recent collections using GPS capture that have an accuracy of plus or minus 5 m. There were 90 legacy sites with good location descriptions with coordinates captured with Google Earth that we are confident are within 1 km of the collection location. Finally, 84 sites had poor location descriptions often listing only a county. We used the centroid of the county location for these sites resulting in a spatial accuracy of approximately 100 km. Both the GPS coordinates and the Google Earth capture location used the datum WGS 1984. <br>Locations for each site along with associated sibling species and cytotypes were used to create an attribute table. <br>
DOI: 10.6084/m9.figshare.7719410.v1
title: An Iterative Sparse-Group Lasso

description: In high-dimensional supervised learning problems, sparsity constraints in the solution often lead to better performance and interpretability of the results. For problems in which covariates are grouped and sparse structure are desired, both on group and within group levels, the sparse-group lasso (SGL) regularization method has proved to be very efficient. Under its simplest formulation, the solution provided by this method depends on two weight parameters that control the penalization on the coefficients. Selecting these weight parameters represents a major challenge. In most of the applications of the SGL, this problem is left aside, and the parameters are either fixed based on a prior information about the data, or chosen to minimize some error function in a grid of possible values. However, an appropriate choice of the parameters deserves more attention, considering that it plays a key role in the structure and interpretation of the solution. In this sense, we present a gradient-free coordinate descent algorithm that automatically selects the regularization parameters of the SGL. We focus on a more general formulation of this problem, which also includes individual penalizations for each group. The advantages of our approach are illustrated using both real and synthetic datasets. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7719428.v1
title: Organisms Environmental Results New.xlsx

description: Goes with a manuscript . Using matrix-assisted laser desorption time-of-flight (MALDI-TOF) mass spectra to identify bacteria from the environment by matching to translated DNA databases, byJames Kostas, Kenneth C. Parker<b></b><i></i><sub></sub><sup></sup><br> <b></b><i></i><sub></sub><sup></sup><b></b><i></i><sub></sub><sup></sup><br>
DOI: 10.7284/101476
title: Multiplexed data collected during research cruise AT15-43 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7719329
title: JFRC2018F_FCWB_h5

description: Transformations between JRC 2018 Female template and the FCWB template. <br>
DOI: 10.6084/m9.figshare.7719329.v1
title: JFRC2018F_FCWB_h5

description: Transformations between JRC 2018 Female template and the FCWB template. <br>
DOI: 10.6084/m9.figshare.7719398.v1
title: Sympatric speciation in the Simuluim arcticum complex (Diptera: Simuludae)

description: Five separate data sets were included in our analyses: Alaska (Shields and Procunier 1982), Montana, Idaho, and eastern Washington (Shields 2013; Shields 2014; Shields and Shields 2017 and Shields, unpub. data); throughout the range of <i>S. arcticum</i> (Conflitti <i>et al</i>. 2016); western Canada (Procunier, unpub.); and throughout the range of <i>S. arcticum</i> (Adler <i>et al</i>. 2004. <br>Locations for 299 sites were determined with varying accuracy. There were 125 sites associated with recent collections using GPS capture that have an accuracy of plus or minus 5 m. There were 90 legacy sites with good location descriptions with coordinates captured with Google Earth that we are confident are within 1 km of the collection location. Finally, 84 sites had poor location descriptions often listing only a county. We used the centroid of the county location for these sites resulting in a spatial accuracy of approximately 100 km. Both the GPS coordinates and the Google Earth capture location used the datum WGS 1984. <br>Locations for each site along with associated sibling species and cytotypes were used to create an attribute table. <br>
DOI: 10.6084/m9.figshare.7719236
title: hg19.refseq.final_sorted.gtf

description: The annotation (GTF) file of all human gene.
DOI: 10.6084/m9.figshare.7719296
title: ICJointLE software suite and the used data files

description: Software suite for the identification of protein complexes from PPI data sets and the evaluation of identified complexes matching CYC2008.
DOI: 10.6084/m9.figshare.7719236.v1
title: hg19.refseq.final_sorted.gtf

description: The annotation (GTF) file of all human gene.
DOI: 10.7284/101475
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AT15-43 using a Hawaii UHDAS instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/101479
title: Multiplexed data collected during research cruise AT15-44 using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7719185
title: JRC2018F_JFRC2013_h5

description: Transformations between JRC 2018 Female template and the JFRC 2013 template. <br>
DOI: 10.6084/m9.figshare.7719197
title: References for CROCI by ORCID 0000-0003-1588-9749

description: Citations for CROCI<br>
DOI: 10.6084/m9.figshare.7719200
title: Effects of Pesticides on Exposure and Susceptibility to Parasites can be Generalized to Pesticide Class and Type in Aquatic Communities

description: Data corresponding to Ecology Letters manuscript entitled "Effects of Pesticides on Exposure and Susceptibility to Parasites can be Generalized to Pesticide Class and Type in Aquatic Communities". All pertinent information regarding experimental design and analyses are contained within the manuscript. <br>Data is on first tab of excel file, metadata is on second tab of excel file.
DOI: 10.6084/m9.figshare.7719296.v3
title: ICJointLE software suite and the used data files

description: Software suite for the identification of protein complexes from PPI data sets and the evaluation of identified complexes matching CYC2008.
DOI: 10.6084/m9.figshare.7719185.v1
title: JRC2018F_JFRC2013_h5

description: Transformations between JRC 2018 Female template and the JFRC 2013 template. <br>
DOI: 10.6084/m9.figshare.7719296.v2
title: ICJointLE software suite and the used data files

description: Software suite for the identification of protein complexes from PPI data sets and the evaluation of identified complexes matching CYC2008.