cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8394882
title: The evolvement of ULVZ at LLSVP margins--selected models with various buoyancy number and compositional viscosity

description: This tar.gz file is created and uploaded for the submission of the manuscript titled '<em>The evolvement of dense ULVZs at LLSVP margins and implications</em>' to the journal <em>Geophysical Research Letters</em>. This tar.gz file is for selected models with various buoyancy number (B) and compositional viscosity (etaC), which are described and compared with the reference model (in doi 10.5281/zenodo.8394637) in the manuscript. The collection includes the raw output data and post-processed data illustrated in Figures 3. 1. the /scratch directory This directory contains the raw output data of three models listed below. All models are calculated by CitcomS (modified from the CitcomS-3.3.1 version) and the data follows the CitcomS output convention. Please read the description of a previous upload (doi 10.5281/zenodo.8394637, titled 'The evolvement of ULVZ at LLSVP margins--reference model with B=3.0 and etaC=1.0') for more information. The ULVZ-v1B6_h10l10/ directory: the model with B=6.0 and etaC=1.0, illustrated in the top panel of Figure 3 The ULVZ-v1B1-5_h10l10/ directory: the model with B=1.5 and etaC=1.0, illustrated in the middle panel of Figure 3 The ULVZ-v01B3_h10l10/ directory: the model with B=3.0 and etaC=0.1, illustrated in the bottom panel of Figure 3 2. the data_plots/ directory: data extracted from the raw outputs and plotted in Figure 3. The time frame of 14800 is for the left column in Figure 3, and the other time frames are for the right column in Figure 3. temperature: *temp* files composition: *comp* files velocity: *velo_Sv* files density anomaly: *density* files
DOI: 10.5281/zenodo.8394881
title: The evolvement of ULVZ at LLSVP margins--selected models with various buoyancy number and compositional viscosity

description: This tar.gz file is created and uploaded for the submission of the manuscript titled '<em>The evolvement of dense ULVZs at LLSVP margins and implications</em>' to the journal <em>Geophysical Research Letters</em>. This tar.gz file is for selected models with various buoyancy number (B) and compositional viscosity (etaC), which are described and compared with the reference model (in doi 10.5281/zenodo.8394637) in the manuscript. The collection includes the raw output data and post-processed data illustrated in Figures 3. 1. the /scratch directory This directory contains the raw output data of three models listed below. All models are calculated by CitcomS (modified from the CitcomS-3.3.1 version) and the data follows the CitcomS output convention. Please read the description of a previous upload (doi 10.5281/zenodo.8394637, titled 'The evolvement of ULVZ at LLSVP margins--reference model with B=3.0 and etaC=1.0') for more information. The ULVZ-v1B6_h10l10/ directory: the model with B=6.0 and etaC=1.0, illustrated in the top panel of Figure 3 The ULVZ-v1B1-5_h10l10/ directory: the model with B=1.5 and etaC=1.0, illustrated in the middle panel of Figure 3 The ULVZ-v01B3_h10l10/ directory: the model with B=3.0 and etaC=0.1, illustrated in the bottom panel of Figure 3 2. the data_plots/ directory: data extracted from the raw outputs and plotted in Figure 3. The time frame of 14800 is for the left column in Figure 3, and the other time frames are for the right column in Figure 3. temperature: *temp* files composition: *comp* files velocity: *velo_Sv* files density anomaly: *density* files
DOI: 10.5281/zenodo.8394637
title: The evolvement of ULVZ at LLSVP margins--reference model with B=3.0 and etaC=1.0

description: This tar.gz file is created and uploaded for the submission of the manuscript titled '<em>The evolvement of dense ULVZs at LLSVP margins and implications</em>' to the journal <em>Geophysical Research Letters</em>. This tar.gz file is for the reference model in the manuscript, which employs a buoyancy number B=3.0 and a compositional viscosity eta_C=1.0 for the ULVZ. The collection includes the raw output data and post-processed data illustrated in Figures 1 and 2. 1. the /scratch directory This directory contains the raw output data of an numerical experiment calculated by CitcomS (modified from the CitcomS-3.3.1 version) for the evolvement of a ULVZ initially beneath a mantle downwelling. All data follow the CitcomS output convention. Files named *coord* are for the coordinate, *.buoy* are for the density anomaly, *comp_nd* are for the compositional fields (LLSVP and ULVZ), *temp* are for the temperature and velocity fields, *visc* are for the viscosity field. The time frame 12000 is the initial condition of this calculation with one stable LLSVP, having already evolved for ~2 Gyrs, at the bottom center of the model domain, as well as a newly emplaced ULVZ near one sidewall beneath a cold downwelling. The calculation is done for 10000 time steps till the time frame of 20000. 2. the data_plots/ directory In Fig1/ directory: data for the illustration of Figure 1, the model initial condition. temperature: ULVZ-v1B3_h10l10.a.temp.12000.dat composition: ULVZ-v1B3_h10l10.a.comp.12000.dat velocity: ULVZ-v1B3_h10l10.a.velo_Sv.12000.dat density anomaly: ULVZ-v1B3_h10l10.a.density.12000.dat topography: ULVZ-v1B3_h10l10.a.botm.12000.dat In Fig2/ directory: data for the illustration of Figure 2, the evolvement of ULVZ at the LLSVP margin, including the *botm*, *density*, *velo_Sv*, *botm*, *postp.tracers-plume* for selected time frames. 296 Myrs: time frame 14000 519 Myrs: time frame 14800 888 Myrs: time frame 16800 1036 Myrs: time frame 17600 1332 Myrs: time frame 19200
DOI: 10.5281/zenodo.8394636
title: The evolvement of ULVZ at LLSVP margins--reference model with B=3.0 and etaC=1.0

description: This tar.gz file is created and uploaded for the submission of the manuscript titled '<em>The evolvement of dense ULVZs at LLSVP margins and implications</em>' to the journal <em>Geophysical Research Letters</em>. This tar.gz file is for the reference model in the manuscript, which employs a buoyancy number B=3.0 and a compositional viscosity eta_C=1.0 for the ULVZ. The collection includes the raw output data and post-processed data illustrated in Figures 1 and 2. 1. the /scratch directory This directory contains the raw output data of an numerical experiment calculated by CitcomS (modified from the CitcomS-3.3.1 version) for the evolvement of a ULVZ initially beneath a mantle downwelling. All data follow the CitcomS output convention. Files named *coord* are for the coordinate, *.buoy* are for the density anomaly, *comp_nd* are for the compositional fields (LLSVP and ULVZ), *temp* are for the temperature and velocity fields, *visc* are for the viscosity field. The time frame 12000 is the initial condition of this calculation with one stable LLSVP, having already evolved for ~2 Gyrs, at the bottom center of the model domain, as well as a newly emplaced ULVZ near one sidewall beneath a cold downwelling. The calculation is done for 10000 time steps till the time frame of 20000. 2. the data_plots/ directory In Fig1/ directory: data for the illustration of Figure 1, the model initial condition. temperature: ULVZ-v1B3_h10l10.a.temp.12000.dat composition: ULVZ-v1B3_h10l10.a.comp.12000.dat velocity: ULVZ-v1B3_h10l10.a.velo_Sv.12000.dat density anomaly: ULVZ-v1B3_h10l10.a.density.12000.dat topography: ULVZ-v1B3_h10l10.a.botm.12000.dat In Fig2/ directory: data for the illustration of Figure 2, the evolvement of ULVZ at the LLSVP margin, including the *botm*, *density*, *velo_Sv*, *botm*, *postp.tracers-plume* for selected time frames. 296 Myrs: time frame 14000 519 Myrs: time frame 14800 888 Myrs: time frame 16800 1036 Myrs: time frame 17600 1332 Myrs: time frame 19200
DOI: 10.5281/zenodo.8389446
title: Three scores by Giovanni Battista Pergolesi and Domenico Sarro

description: The dataset contains three scores (as Finale and PDF files) transcribed from two handwritten sources. Also contained is a brief report on the edition of the third item (in German). Giovanni Battista Pergolesi (attr.), No. 1, "Sol resplendet", from GB-Ob Tenbury 312 Giovanni Battista Pergolesi (attr.), No. 6, "In hac die tam decora", from GB-Ob Tenbury 312 Domenico Sarro, Mass in F major, from D-MÜs Hs. 1469 These scores are the music examples for the following publication: Claudio Bacciagaluppi, Laus Deo: Autorschaft in der neapolitanischen Kirchenmusik, in: Original und Fälschung? Umstrittene Autorschaften in Musik, Kunst und Literatur, ed. by Arnold Jacobshagen and Friederike Mühle, Würzburg: Königshausen & Neumann, in preparation. The choruses attributed to Pergolesi were edited and transcribed by Claudio Bacciagaluppi and Rodolfo Zitellini, the Sarro Mass by Claudio Bacciagaluppi and Irène Zuest.
DOI: 10.5281/zenodo.8389445
title: Three scores by Giovanni Battista Pergolesi and Domenico Sarro

description: The dataset contains three scores (as Finale and PDF files) transcribed from two handwritten sources. Also contained is a brief report on the edition of the third item (in German). Giovanni Battista Pergolesi (attr.), No. 1, "Sol resplendet", from GB-Ob Tenbury 312 Giovanni Battista Pergolesi (attr.), No. 6, "In hac die tam decora", from GB-Ob Tenbury 312 Domenico Sarro, Mass in F major, from D-MÜs Hs. 1469 These scores are the music examples for the following publication: Claudio Bacciagaluppi, Laus Deo: Autorschaft in der neapolitanischen Kirchenmusik, in: Original und Fälschung? Umstrittene Autorschaften in Musik, Kunst und Literatur, ed. by Arnold Jacobshagen and Friederike Mühle, Würzburg: Königshausen & Neumann, in preparation. The choruses attributed to Pergolesi were edited and transcribed by Claudio Bacciagaluppi and Rodolfo Zitellini, the Sarro Mass by Claudio Bacciagaluppi and Irène Zuest.
DOI: 10.5281/zenodo.8394847
title: Semantic-Discrepant Outliers on CIFAR-10 Dataset

description: We provide synthetic Out-of-distibution (OOD) dataset, which is called Semantic-Discrepant (SD) outliers, on CIFAR-10 dataset. SD outliers can be utilized for boosting OOD detection model performance. For the details, SD outliers are realistic OOD samples that contains incoherent semantic shift while preserving nuisances with in-distribution (ID). SD-outliers are generated from ID training samples using semantic-discrepant sampling in the diffusion model. so SD-outliers on CIFAR-10 contains 50000 32X32 images which is same as CIFAR-10 training dataset size. The dataset has a capacity of 768MB.
DOI: 10.5281/zenodo.8394846
title: Semantic-Discrepant Outliers on CIFAR-10 Dataset

description: We provide synthetic Out-of-distibution (OOD) dataset, which is called Semantic-Discrepant (SD) outliers, on CIFAR-10 dataset. SD outliers can be utilized for boosting OOD detection model performance. For the details, SD outliers are realistic OOD samples that contains incoherent semantic shift while preserving nuisances with in-distribution (ID). SD-outliers are generated from ID training samples using semantic-discrepant sampling in the diffusion model. so SD-outliers on CIFAR-10 contains 50000 32X32 images which is same as CIFAR-10 training dataset size. The dataset has a capacity of 768MB.
DOI: 10.5281/zenodo.8394958
title: Results - Exploratory behavior and PCA

description: These data shows the results obtained from the analysis of the exploratory behaviour variables (DO) and the principal components (PCA), for each of the participants (12 in total) in the study, in the four situations analysed (ISE=IWOM; ICE=IWM; PSE=PWOM; PCE=PWM).
DOI: 10.5281/zenodo.8394957
title: Results - Exploratory behavior and PCA

description: These data shows the results obtained from the analysis of the exploratory behaviour variables (DO) and the principal components (PCA), for each of the participants (12 in total) in the study, in the four situations analysed (ISE=IWOM; ICE=IWM; PSE=PWOM; PCE=PWM).
DOI: 10.6084/m9.figshare.22336666
title: Supplementary Tables and Text

description: Supplementary Tables and Text for Forgarty et al 2023.
DOI: 10.6084/m9.figshare.22336666.v2
title: Supplementary Tables and Text

description: Supplementary Tables and Text for Forgarty et al 2023.
DOI: 10.6084/m9.figshare.22336666.v1
title: Supplementary Tables and Text

description: Supplementary Tables and Text for Forgarty et al 2023.
DOI: 10.5281/zenodo.7746093
title: CRUMB: the Collected Radiogalaxies Using MiraBest dataset

description: The CRUMB dataset is a machine learning image dataset of Fanaroff-Riley galaxies, constructed by combining the datasets of MiraBest, FR-DEEP, AT17 and a supplementary MiraBest hybrid dataset. Sources are labelled using a unified "basic" label system with the following classes: 0: FRI 1: FRII 2: Hybrid source The original labels of each of the parent datasets are also retained as a "complete" label which is accessible using the built-in "complete_labels" method on the dataloader. These labels are as follows: MiraBest: 0 (confidently-classified FRI), 1 (confidently-classified wide-angle-tail), 2 (confidently-classified head-tail), 3 (uncertainly-classified FRI), 4 (uncertainly-classified wide-angle-tail), 5 (confidently-classified FRII), 6 (confidently-classified double-double), 7 (uncertainly-classified FRII), 8 (confidently-classified hybrid), 9 (uncertainly-classified hybrid) FR-DEEP: 0 (FRI), 1 (FRII) AT17: 0 (FRI), 1 (FRII), 2 (bent) MiraBest Hybrid: 0 (confidently-classified hybrid), 1 (uncertainly-classified hybrid) For examples of how to use CRUMB, please see its Github. CRUMB 2.0 fixes an issue where images' class labels were not correctly assigned, removes several duplicate sources, and realigns several images to reduce ambiguity about which source is of interest. Use of CRUMB 1.0 is not recommended as a result of this labelling issue.
DOI: 10.5281/zenodo.7746094
title: CRUMB: the Collected Radiogalaxies Using MiraBest dataset

description: The CRUMB dataset is a machine learning image dataset of Fanaroff-Riley galaxies, constructed by combining the datasets of MiraBest, FR-DEEP, AT17 and a supplementary MiraBest hybrid dataset. Sources are labelled using a unified "basic" label system with the following classes: 0: FRI 1: FRII 2: Hybrid source The original labels of each of the parent datasets are also retained as a "complete" label which is accessible using the built-in "complete_labels" method on the dataloader. These labels are as follows: MiraBest: 0 (confidently-classified FRI), 1 (confidently-classified wide-angle-tail), 2 (confidently-classified head-tail), 3 (uncertainly-classified FRI), 4 (uncertainly-classified wide-angle-tail), 5 (confidently-classified FRII), 6 (confidently-classified double-double), 7 (uncertainly-classified FRII), 8 (confidently-classified hybrid), 9 (uncertainly-classified hybrid) FR-DEEP: 0 (FRI), 1 (FRII) AT17: 0 (FRI), 1 (FRII), 2 (bent) MiraBest Hybrid: 0 (confidently-classified hybrid), 1 (uncertainly-classified hybrid) For examples of how to use CRUMB, please see its Github.
DOI: 10.5281/zenodo.7948346
title: CRUMB: the Collected Radiogalaxies Using MiraBest dataset

description: The CRUMB dataset is a machine learning image dataset of Fanaroff-Riley galaxies, constructed by combining the datasets of MiraBest, FR-DEEP, AT17 and a supplementary MiraBest hybrid dataset. Sources are labelled using a unified "basic" label system with the following classes: 0: FRI 1: FRII 2: Hybrid source The original labels of each of the parent datasets are also retained as a "complete" label which is accessible using the built-in "complete_labels" method on the dataloader. These labels are as follows: MiraBest: 0 (confidently-classified FRI), 1 (confidently-classified wide-angle-tail), 2 (confidently-classified head-tail), 3 (uncertainly-classified FRI), 4 (uncertainly-classified wide-angle-tail), 5 (confidently-classified FRII), 6 (confidently-classified double-double), 7 (uncertainly-classified FRII), 8 (confidently-classified hybrid), 9 (uncertainly-classified hybrid) FR-DEEP: 0 (FRI), 1 (FRII) AT17: 0 (FRI), 1 (FRII), 2 (bent) MiraBest Hybrid: 0 (confidently-classified hybrid), 1 (uncertainly-classified hybrid) For examples of how to use CRUMB, please see its Github. CRUMB 2.0 fixes an issue where images' class labels were not correctly assigned, removes several duplicate sources, and realigns several images to reduce ambiguity about which source is of interest. Use of CRUMB 1.0 is not recommended as a result of this labelling issue.
DOI: 10.5281/zenodo.8394986
title: CRUMB: the Collected Radiogalaxies Using MiraBest dataset

description: The CRUMB dataset is a machine learning image dataset of Fanaroff-Riley galaxies, constructed by combining the datasets of MiraBest, FR-DEEP, AT17 and a supplementary MiraBest hybrid dataset. Sources are labelled using a unified "basic" label system with the following classes: 0: FRI 1: FRII 2: Hybrid source The original labels of each of the parent datasets are also retained as a "complete" label which is accessible using the built-in "complete_labels" method on the dataloader. These labels are as follows: MiraBest: 0 (confidently-classified FRI), 1 (confidently-classified wide-angle-tail), 2 (confidently-classified head-tail), 3 (uncertainly-classified FRI), 4 (uncertainly-classified wide-angle-tail), 5 (confidently-classified FRII), 6 (confidently-classified double-double), 7 (uncertainly-classified FRII), 8 (confidently-classified hybrid), 9 (uncertainly-classified hybrid) FR-DEEP: 0 (FRI), 1 (FRII) AT17: 0 (FRI), 1 (FRII), 2 (bent) MiraBest Hybrid: 0 (confidently-classified hybrid), 1 (uncertainly-classified hybrid) For examples of how to use CRUMB, please see its Github. CRUMB 2.0 fixes an issue where images' class labels were not correctly assigned, removes several duplicate sources, and realigns several images to reduce ambiguity about which source is of interest. Use of CRUMB 1.0 is not recommended as a result of this labelling issue.
DOI: 10.34820/fk2/ge7xgv/ki935y
title: Cahyaningsih & Tri Utami Lestari-RIGEO-Q3-Scopus-2021.pdf

description: :unav
DOI: 10.34820/fk2/ge7xgv/0po6hz
title: The Effect of CSR and Higher Academic Education Experts on Audit Opinion in Light of the Company Profile Perspective-Cahyaningsih-Dataset.tab

description: :unav
DOI: 10.34820/fk2/ge7xgv
title: Replication Data for The Effect of Corporate Social Responsibility and Higher Academic Education Experts on Audit Opinion in Light of the Company Profile Perspective

description: Table: The Effect of Corporate Social Responsibility and Higher Academic Education Experts on Audit Opinion in Light of the Company Profile Perspective
DOI: 10.6084/m9.figshare.24224284
title: <b>Analytic code directory for study, "</b><b>Changes in care associated with integrating Medicare and Medicaid for dual eligible individuals: Examination of a Fully Integrated Special Needs Plan"</b>

description: This directory contains analytic code used to build cohorts, dependent variables, and covariates, and run all statistical analyses for the study, "Changes in care associated with integrating Medicare and Medicaid for dual eligible individuals: Examination of a Fully Integrated Special Needs Plan."The code files enclosed in this directory are:<b>SAS_Cohorts_Outcomes 23-9-30.sas.</b> This SAS code file builds study cohorts, dependent variables, and covariates. This code produced a person-by-month level database of outcomes and covariates for individuals in the integration and comparison cohorts.<b>STATA_Models_23-6-5_weight_jama.do.</b><b> </b>This Stata program reads in the person-by-month level database (output from SAS) and conducts all statistical analyses used to produce the main and supplementary analyses reported in the manuscript.We have provided this code and documentation to disclose our study methods. Our Data Use Agreements prohibit publishing of row-level data for this study. Therefore, researchers would need to obtain Data Use Agreements with data providers to implement these analyses. We also note that some measures reference macros with proprietary code (e.g., Medispan® files) which require a separate user license to run. Interested readers should contact the study PI, Eric T. Roberts (eric.roberts@pennmedicine.upenn.edu) for further information.
DOI: 10.6084/m9.figshare.24224284.v1
title: <b>Analytic code directory for study, "</b><b>Changes in care associated with integrating Medicare and Medicaid for dual eligible individuals: Examination of a Fully Integrated Special Needs Plan"</b>

description: This directory contains analytic code used to build cohorts, dependent variables, and covariates, and run all statistical analyses for the study, "Changes in care associated with integrating Medicare and Medicaid for dual eligible individuals: Examination of a Fully Integrated Special Needs Plan."The code files enclosed in this directory are:<b>SAS_Cohorts_Outcomes 23-9-30.sas.</b> This SAS code file builds study cohorts, dependent variables, and covariates. This code produced a person-by-month level database of outcomes and covariates for individuals in the integration and comparison cohorts.<b>STATA_Models_23-6-5_weight_jama.do.</b><b> </b>This Stata program reads in the person-by-month level database (output from SAS) and conducts all statistical analyses used to produce the main and supplementary analyses reported in the manuscript.We have provided this code and documentation to disclose our study methods. Our Data Use Agreements prohibit publishing of row-level data for this study. Therefore, researchers would need to obtain Data Use Agreements with data providers to implement these analyses. We also note that some measures reference macros with proprietary code (e.g., Medispan® files) which require a separate user license to run. Interested readers should contact the study PI, Eric T. Roberts (eric.roberts@pennmedicine.upenn.edu) for further information.
DOI: 10.5281/zenodo.8393342
title: LocoMuJoCo Supplementary

description: LocoMuJoCo Supplementary Matierial.
DOI: 10.5281/zenodo.8393341
title: LocoMuJoCo Supplementary

description: LocoMuJoCo Supplementary Matierial.
DOI: 10.5281/zenodo.8395051
title: LocoMuJoCo Supplementary

description: LocoMuJoCo Supplementary Matierial.
DOI: 10.34740/kaggle/dsv/6577335
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5281/zenodo.8325729
title: Economic Analysis_RawData

description: This .zip file contains the .xlsx raw data that where used for the completion of the deliverable 5.3
DOI: 10.5281/zenodo.8325730
title: Economic Analysis_RawData

description: This .zip file contains the .xlsx raw data that where used for the completion of the deliverable 5.3
DOI: 10.5281/zenodo.8395057
title: Is the sentiment priced? Evidence from the Korean stock market

description: SAS files. 1) dtset_ks.KOSPI 2) dtset_kq: KOSDAQ Data description: This datasets are the common stock of non-financial companies traded on KOSPI(dtset_ks) and KOSDAQ(dtset_kq), including delisted stocks. KOSPI comprises primarily of large, established firms, whereas KOSDAQ comprises young, entrepreneurial firms. The spans from February 2000 to June 2022 and is based on the stock excess return. This dataset utilizes data from FnGuide and the yields of CD (91-day) provided by the Bank of Korea as a risk-free rate. Please look at the paper to see specific variables.
DOI: 10.5281/zenodo.8395056
title: Is the sentiment priced? Evidence from the Korean stock market

description: SAS files. 1) dtset_ks.KOSPI 2) dtset_kq: KOSDAQ Data description: This datasets are the common stock of non-financial companies traded on KOSPI(dtset_ks) and KOSDAQ(dtset_kq), including delisted stocks. KOSPI comprises primarily of large, established firms, whereas KOSDAQ comprises young, entrepreneurial firms. The spans from February 2000 to June 2022 and is based on the stock excess return. This dataset utilizes data from FnGuide and the yields of CD (91-day) provided by the Bank of Korea as a risk-free rate. Please look at the paper to see specific variables.
DOI: 10.34740/kaggle/dsv/6577495
title: 2021 World Population (updated daily)
DOI: 10.34740/kaggle/dsv/6577516
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.57967/hf/1162
title: Featureextractor