cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-3058/27
title: S9994H1-10.dx

description: :unav
DOI: 10.18419/darus-3058/28
title: S9994H1-3.dx

description: :unav
DOI: 10.18419/darus-3058/29
title: S9994H1-11.dx

description: :unav
DOI: 10.18419/darus-3058/30
title: S9974H1-1.dx

description: :unav
DOI: 10.18419/darus-3058/31
title: Note of the data.txt

description: :unav
DOI: 10.18419/darus-3058/32
title: Na-ZSM-5.txt

description: :unav
DOI: 10.18419/darus-3058/33
title: S9890H1-6.dx

description: :unav
DOI: 10.18419/darus-3058/34
title: S9890H1-5.dx

description: :unav
DOI: 10.18419/darus-3058/35
title: S9974H1-4.dx

description: :unav
DOI: 10.18419/darus-3058/36
title: 210921S2 A200P.pdf

description: :unav
DOI: 10.18419/darus-3058/37
title: S9890H1-3.dx

description: :unav
DOI: 10.18419/darus-3058/38
title: H[Al]SBA15.txt

description: :unav
DOI: 10.18419/darus-3058/39
title: S9974H1-3.dx

description: :unav
DOI: 10.18419/darus-3058/40
title: 190204S1_SBA-15-AKB.pdf

description: :unav
DOI: 10.18419/darus-3058/41
title: S9890H1-11.dx

description: :unav
DOI: 10.18419/darus-3058/42
title: S9890H1-9.dx

description: :unav
DOI: 10.18419/darus-3058/43
title: 210923S2 STA@A200P.pdf

description: :unav
DOI: 10.18419/darus-3058/44
title: S9994H1-8.dx

description: :unav
DOI: 10.18419/darus-3058/45
title: 191022S2_Na-ZSM-5.pdf

description: :unav
DOI: 10.18419/darus-3058/46
title: S9974H1-10.dx

description: :unav
DOI: 10.18419/darus-3058/47
title: S9994H1-7.dx

description: :unav
DOI: 10.18419/darus-3058/48
title: S9974H1-8.dx

description: :unav
DOI: 10.18419/darus-3058/49
title: 200204S3_H[Al]SBA-15-AKB.pdf

description: :unav
DOI: 10.18419/darus-3058/50
title: S9994H1-6.dx

description: :unav
DOI: 10.6084/m9.figshare.22304803
title: Table S2: Monitoring volcano deformation at La Soufrière, St Vincent during the 2020–21 eruption with insights into its magma plumbing system architecture

description: (a) ALOS-2 data points used for modelling the pre-eruptive (effusive) phase at La Soufrière volcano. Radar image dates are 15/01/2020–13/01/2021. (b) SAOCOM data points used for modelling the syn-eruptive (explosive) phase at La Soufrière volcano. Radar image dates are 06/01/2021–14/03/2022.
DOI: 10.6084/m9.figshare.22304803.v1
title: Table S2: Monitoring volcano deformation at La Soufrière, St Vincent during the 2020–21 eruption with insights into its magma plumbing system architecture

description: (a) ALOS-2 data points used for modelling the pre-eruptive (effusive) phase at La Soufrière volcano. Radar image dates are 15/01/2020–13/01/2021. (b) SAOCOM data points used for modelling the syn-eruptive (explosive) phase at La Soufrière volcano. Radar image dates are 06/01/2021–14/03/2022.
DOI: 10.6084/m9.figshare.22304809
title: Table S1: Monitoring volcano deformation at La Soufrière, St Vincent during the 2020–21 eruption with insights into its magma plumbing system architecture

description: (a) InSAR time-series used in study; (b) InSAR interferogram data used in study.
DOI: 10.6084/m9.figshare.22304809.v1
title: Table S1: Monitoring volcano deformation at La Soufrière, St Vincent during the 2020–21 eruption with insights into its magma plumbing system architecture

description: (a) InSAR time-series used in study; (b) InSAR interferogram data used in study.
DOI: 10.6084/m9.figshare.22304821
title: Dataset for statistical analysis

description: Dataset used to generate models.
DOI: 10.22002/hjfx4-a8r81
title: The Materials Provenance Store

description: A PostgreSQL dump of the Materials Provenance Store (MPS), a database containing metadata and experimental provenance from synthesis to measurement of primarily metal oxide solid state materials resulting from high throughput experimentation.
description: This material is based on work performed by the Liquid Sunlight Alliance, which is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Fuels from Sunlight Hub under Award DE-SC0021266. Development of the database schema was supported by Toyota Research Institute. Much of the underlying data was generated by research in the Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy (Award No. DE-SC0004993). Storage for MEAD is provided by the Open Storage Network via XSEDE allocation INI210004. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-76SF00515.
DOI: 10.34740/kaggle/dsv/5202278
title: NFL Player Data
DOI: 10.5281/zenodo.7753141
title: Design Strategies for Oxy-Combustion Power Plant Captured CO2 Purification

description: This submission contains Aspen Plus files for the design and systems performance analysis of oxy-combustion power plant captured CO2 purification using different techniques. This data is taken from https://psecommunity.org/LAPSE:2021.0570
DOI: 10.5281/zenodo.7753140
title: Design Strategies for Oxy-Combustion Power Plant Captured CO2 Purification

description: This submission contains Aspen Plus files for the design and systems performance analysis of oxy-combustion power plant captured CO2 purification using different techniques. This data is taken from https://psecommunity.org/LAPSE:2021.0570
DOI: 10.6073/pasta/dd75aba9ea4a87904091c49b77795588
title: Manually-collected discharge data for multiple inflow tributaries entering Falling Creek Reservoir, Beaverdam Reservoir, and Carvins Cove Reservoir, Virginia, USA from 2019-2022

description: Discharge rates at multiple inflow streams into Falling Creek Reservoir (Vinton, Virginia, USA), Beaverdam Reservoir (Vinton, Virginia, USA), and Carvins Cove Reservoir (Roanoke, Virginia, USA) were measured manually using multiple methods from 2019-2022. Falling Creek Reservoir, Beaverdam Reservoir, and Carvins Cove Reservoir are owned and operated by the Western Virginia Water Authority as drinking water sources for Roanoke, Virginia. The dataset consists of discharge rates calculated using one of four methods: handheld flowmate, salt injection, velocity float or bucket method. Data were collected weekly to monthly from February through October 2019 at Falling Creek and Beaverdam Reservoir, and approximately monthly at Falling Creek in 2020-2021, and approximately monthly at Carvins Cove in 2021-2022.
DOI: 10.6084/m9.figshare.22304869.v1
title: Platycnemis protein set

description: Annotated protein set for Platycnemis pennipes.
DOI: 10.6084/m9.figshare.22304869
title: Platycnemis protein set

description: Annotated protein set for Platycnemis pennipes.
DOI: 10.21227/x2xm-xh92
title: Industrial Internet of Things embedded devices fault detection and classification. A case study

description: Industries transition to the Industry 4.0 paradigm requires solutions based on devices attached to machines that allow monitoring and control of industrial equipment. Monitoring is essential to ensure devices' proper operation against different aggressions. We propose a novel approach to detect and classify faults, that are typical in these devices, based on machine learning techniques that use as features the energy, the processing, and the time consumed by device main application functionality. The proposal was validated using a dataset collected from a testbed executing a typical equipment monitoring application. The proposal machine learning pipeline uses a decision tree-based model for fault detection (99.4% accuracy, 99.7% precision, 99.6% recall, 75.2% specificity, and 99.7% F1) followed by a Semi-Supervised Graph-Based model (99.3% accuracy, 96.4% precision, 96.1% recall, 99.6% specificity, and 96.2% F1) for further fault classification. Those results demonstrate that machine learning techniques, based on easily obtainable metrics, help coping with common device faults.
DOI: 10.6084/m9.figshare.22304872
title: Platycnemis pennipes annotation

description: Gff file of Platycnemis pennipes annotation.
DOI: 10.6084/m9.figshare.22304872.v1
title: Platycnemis pennipes annotation

description: Gff file of Platycnemis pennipes annotation.
DOI: 10.6084/m9.figshare.22304635
title: Data_PCV13_OM Impact analysis_12 Dec 2021.csv

description: This dataset consist of socia-demographic information and tympanograms obtained from 2-3 year-old Cameroonian children during two rounds of retrospective cohort studies conducted following the introduction of the 13-valent pneumococcal conjugate vaccine (PCV13) in Cameroon since July 2011.
DOI: 10.6084/m9.figshare.22304635.v1
title: Data_PCV13_OM Impact analysis_12 Dec 2021.csv

description: This dataset consist of socia-demographic information and tympanograms obtained from 2-3 year-old Cameroonian children during two rounds of retrospective cohort studies conducted following the introduction of the 13-valent pneumococcal conjugate vaccine (PCV13) in Cameroon since July 2011.
DOI: 10.34740/kaggle/dsv/5202386
title: AdultoMayor_7_fc
DOI: 10.25934/pr00007372.10
title: Available IPD datapackage for study 'A Phase III, Open-Label, Randomized Study of Atezolizumab in Combination With Bevacizumab Compared With Sorafenib in Patients With Untreated Locally Advanced or Metastatic Hepatocellular Carcinoma'

description: This study will evaluate the efficacy and safety of atezolizumab in combination with bevacizumab compared with sorafenib in participants with locally advanced or metastatic Hepatocellular Carcinoma (HCC) who have received no prior systemic treatment.
DOI: 10.5281/zenodo.7753472
title: OPERA RTC-S1 SAS test dataset over Los Angeles

description: This dataset is part of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR backscatter from Sentinel-1 (S1) product Software Application Software (SAS) developed by the OPERA algorithm development team (ADT). It includes a subset of a Sentinel-1B Interferometric Wide (IW) 2 swath-mode dataset (ID `S1B_IW_SLC__1SDV_20200926T135152_20200926T135219_023547_02CBCC_F988`) acquired on September 26, 2022 over Los Angeles (US). The RTC-S1 SAS is publicly available at: https://github.com/opera-adt/RTC <strong>License</strong> Copyright (c) 2021 California Institute of Technology (“Caltech”). U.S. Government sponsorship acknowledged. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. Neither the name of Caltech nor its operating division, the Jet Propulsion Laboratory, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
DOI: 10.5281/zenodo.7753471
title: OPERA RTC-S1 SAS test dataset over Los Angeles

description: This dataset is part of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR backscatter from Sentinel-1 (S1) product Software Application Software (SAS) developed by the OPERA algorithm development team (ADT). It includes a subset of a Sentinel-1B Interferometric Wide (IW) 2 swath-mode dataset (ID `S1B_IW_SLC__1SDV_20200926T135152_20200926T135219_023547_02CBCC_F988`) acquired on September 26, 2022 over Los Angeles (US). The RTC-S1 SAS is publicly available at: https://github.com/opera-adt/RTC <strong>License</strong> Copyright (c) 2021 California Institute of Technology (“Caltech”). U.S. Government sponsorship acknowledged. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. Neither the name of Caltech nor its operating division, the Jet Propulsion Laboratory, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
DOI: 10.7284/150535
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise KM2203 using a Hawaii UHDAS instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150542
title: Anemometer data collected during research cruise KM2203 using a RMYoung 85106 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150543
title: Anemometer data collected during research cruise KM2203 using a RMYoung 85106 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150539
title: Barometer data collected during research cruise KM2203 using a Vaisala PTB220 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150538
title: Fluorometer data collected during research cruise KM2203 using a WETLabs WETStar instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150536
title: Gravimeter data collected during research cruise KM2203 using a Bell BGM-3 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150537
title: Gyrocompass data collected during research cruise KM2203 using a Sperry NAVIGAT X MK 1 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150544
title: INS (Inertial Navigation System) data collected during research cruise KM2203 using a Applanix POS/MV-320 V4 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150534
title: Meteorological Station data collected during research cruise KM2203 using a Hawaii MET-System instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150540
title: Meteorological Station data collected during research cruise KM2203 using a Hawaii MET-System instrument system onboard the platform RV Kilo Moana

description: Processed data created by vessel technician during a Field_expedition
DOI: 10.7284/150541
title: Multibeam Echosounder data collected during research cruise KM2203 using a Kongsberg EM122 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150531
title: SSV (Sound Speed Velocimeter) data collected during research cruise KM2203 using a AML SV&P instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/150532
title: TSG (Thermosalinograph) data collected during research cruise KM2203 using a SeaBird SBE-45 instrument system onboard the platform RV Kilo Moana

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.25934/pr00007557.6
title: Available IPD datapackage for study 'A Phase III, Double-Blinded, Randomized, Placebo-Controlled Study of Atezolizumab Plus Cobimetinib and Vemurafenib Versus Placebo Plus Cobimetinib and Vemurafenib in Previously Untreated BRAFV600 Mutation-Positive Patients With Unresectable Locally Advanced or Metastatic Melanoma'

description: This is a Phase III, double-blinded, placebo-controlled, randomized, multicenter study designed to evaluate the efficacy, safety, and pharmacokinetics of atezolizumab + cobimetinib + vemurafenib compared with placebo + cobimetinib + vemurafenib in patients with previously untreated BRAFv600 mutation-positive metastatic or unresectable locally advanced melanoma.
DOI: 10.25934/pr00007402.9
title: Available IPD datapackage for study 'A Phase I/III, Randomized, Double-Blind, Placebo-Controlled Study of Carboplatin Plus Etoposide With or Without Atezolizumab (Anti-PD-L1 Antibody) in Patients With Untreated Extensive-Stage Small Cell Lung Cancer'

description: This randomized, Phase I/III, multicenter, double-blinded, placebo-controlled study was designed to evaluate the safety and efficacy of atezolizumab (anti-programmed death-ligand 1 [PD-L1] antibody) in combination with carboplatin plus (+) etoposide compared with treatment with placebo + carboplatin + etoposide in chemotherapy-naive participants with ES-SCLC. Participants will be randomized in a 1:1 ratio to receive either atezolizumab + carboplatin + etoposide or placebo + carboplatin + etoposide on 21-day cycles for four cycles in the induction phase followed by maintenance with atezolizumab or placebo until progressive disease (PD) as assessed by the investigator using Response Evaluation Criteria in Solid Tumors Version 1.1 (RECIST v1.1). Treatment can be continued until persistent radiographic PD or symptomatic deterioration.
DOI: 10.5066/p9pjv6wo
title: Images and Identifications of Wild Bees Collected in Eastern Iowa, 2019

description: Bees were collected in 24 fields across eastern Iowa in summer 2019. This data collection was part of a pesticide study funded by the USGS Ecosystems Mission Area- Environmental Health Program. Bees were collected using the sweep net method and then were immediately placed on dry ice in the field. Bees were kept frozen to prevent degradation. In the lab, each wild bee was photographed from one or more angles using an AmScope microscope fitted with an MU1400 digital camera at 20x magnification. Bees were then morphologically identified based on the images. All images were checked for quality control before they were archived on this site. This data release includes 1) a text file with bee identifications and image names, 2) zipped images of the bees, and 3) a text file with alternative text for each image.
DOI: 10.25345/c55m62h5h
title: MassIVE Reanalysis RMSV000000687.1 - Metadata File addition Roach et al Single Polyp Metabolomics
title: Addition of metadata to study Roach et al of single polyp metabolomics data from Montipora capitata
DOI: 10.25934/pr00007871.3
title: Available IPD datapackage for study 'A Phase III, Open-Label, Randomized Study of Atezolizumab (MPDL3280A, Anti-Pd-L1 Antibody) in Combination With Carboplatin or Cisplatin + Pemetrexed Compared With Carboplatin or Cisplatin + Pemetrexed in Patients Who Are Chemotherapy-Naive and Have Stage IV Non-Squamous Non-Small Cell Lung Cancer'

description: This is a randomized, Phase III, multicenter, open-label study designed to evaluate the safety and efficacy of atezolizumab in combination with cisplatin or carboplatin + pemetrexed compared with treatment with cisplatin or carboplatin + pemetrexed in participants who are chemotherapy-naive and have Stage IV non-squamous NSCLC. Eligible participants will be randomized by a 1:1 ratio into 2 groups: Arm A (Atezolizumab + Carboplatin or Cisplatin + Pemetrexed) and Arm B (Carboplatin or Cisplatin + Pemetrexed). The study will be conducted in two phases: Induction Phase and Maintenance Phase.
DOI: 10.6084/m9.figshare.19931582
title: <i>In</i><i>silico</i> models to predict tubular secretion or reabsorption clearance pathway using physicochemical properties and structural characteristics

description: Renal clearance is one of the main pathways for a drug to be cleared from plasma. The aim of this study is to develop <i>in-silico</i> models to find out the relationship between the type of renal clearance, and structural parameters.Literature data were used to categorise the drugs into those that undergo tubular secretion and those that undergo reabsorption. Different structural descriptors (VolSurf descriptors, Abraham solvation parameters, data warrior descriptors, logarithm of distribution coefficient at pH = 7.4 (logD<sub>7.4</sub>)) were applied to develop a mechanistic model for estimating renal clearance class whether its secretion or reabsorption.The results of this study show that logD<sub>7.4</sub> and the number of hydrogen bond donors, as well as available uncharged species (AUS<sub>7.4</sub>), are the most effective descriptors to establish mechanistic models for predicting renal clearance class. The classification models were established with a level of accuracy of more than 75%.Developed models of this study can be helpful to predict renal clearance class for new drug candidates with an acceptable error. Hydrophilicity and hydrogen bond formation ability of drugs are among the main descriptors. Renal clearance is one of the main pathways for a drug to be cleared from plasma. The aim of this study is to develop <i>in-silico</i> models to find out the relationship between the type of renal clearance, and structural parameters. Literature data were used to categorise the drugs into those that undergo tubular secretion and those that undergo reabsorption. Different structural descriptors (VolSurf descriptors, Abraham solvation parameters, data warrior descriptors, logarithm of distribution coefficient at pH = 7.4 (logD<sub>7.4</sub>)) were applied to develop a mechanistic model for estimating renal clearance class whether its secretion or reabsorption. The results of this study show that logD<sub>7.4</sub> and the number of hydrogen bond donors, as well as available uncharged species (AUS<sub>7.4</sub>), are the most effective descriptors to establish mechanistic models for predicting renal clearance class. The classification models were established with a level of accuracy of more than 75%. Developed models of this study can be helpful to predict renal clearance class for new drug candidates with an acceptable error. Hydrophilicity and hydrogen bond formation ability of drugs are among the main descriptors.