cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1409013
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-TAMU maize

description: This is model output from EPIC-TAMU for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408622
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS wheat

description: This is model output from LPJ-GUESS for wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408629
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS soy

description: This is model output from LPJ-GUESS for soy as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.17632/jrwx2z25bj.1
title: Data for: Rheological and mucoadhesive properties of polysaccharide from Bletilla striata with potential use in pharmaceutics as bioadhesive excipient

description: inititial data for viscostiy and bioadensive properties of BSP
DOI: 10.5281/zenodo.1410334
title: Supplementary Data: Combined Collider Constraints On Neutralinos And Charginos

description: <strong>Supplementary Data</strong><br>
<em>Combined collider constraints on neutralinos and charginos.</em>

The files in this record contain data for the EWMSSM model considered in the GAMBIT paper on constraints on electroweakinos.
DOI: 10.5281/zenodo.1410335
title: Supplementary Data: Combined Collider Constraints On Neutralinos And Charginos

description: <strong>Supplementary Data</strong><br>
<em>Combined collider constraints on neutralinos and charginos.</em>

The files in this record contain data for the EWMSSM model considered in the GAMBIT paper on constraints on electroweakinos.
DOI: 10.5281/zenodo.1411506
title: Datasets for practical model selection for prospective virtual screening

description: This repository contains datasets for the manuscript "Practical model selection for prospective virtual screening":


	<strong>pria_rmi_cv.tar.gz</strong>: A compressed directory containing chemical screening data for the <strong>PriA-SSB AS</strong>, <strong>PriA-SSB FP</strong>, and <strong>RMI-FANCM FP</strong> binary datasets.  The files also contain the associated continuous % inhibition values and chemical features represented as SMILES and Morgan fingerprints.  The dataset has been split into five folds for cross validation.
	<strong>pria_rmi_pcba_cv.tar.gz</strong>: A compressed directory containing chemical screening data for the <strong>PriA-SSB AS</strong>, <strong>PriA-SSB FP</strong>, and <strong>RMI-FANCM FP</strong> binary datasets as well as public PubChem BioAssay datasets.  The files also contain the PriA-SSB and RMI-FANCM continuous % inhibition values and chemical features represented as SMILES and Morgan fingerprints.  The dataset has been split into five folds for cross validation.  Missing values are left blank.
	<strong>pria_prospective.csv.gz</strong>: A compressed file containing chemical screening data for the binary dataset <strong>PriA-SSB prospective</strong>.  The file also contains the continuous % inhibition values and chemical features represented as SMILES and Morgan fingerprints.


If you use these data in a publication, please cite:

Shengchao Liu<sup>+</sup>, Moayad Alnammi<sup>+</sup>, Spencer S. Ericksen, Andrew F. Voter, Gene E. Ananiev, James L. Keck, F. Michael Hoffmann, Scott A. Wildman, Anthony Gitter. Practical Model Selection for Prospective Virtual Screening. Journal of Chemical Information and Modeling. 2018 doi:10.1021/acs.jcim.8b00363

PubChem data were provided by the PubChem database.  Follow the PubChem citation guidelines if you use the PubChem data.  See Voter et al. 2017 (PubChem AID 1272365) for the PriA-SSB screening data and Voter et al. 2016 (PubChem AID 1159607) for RMI-FANCM.

Version 1.1.0 updates all of the data files.  We standardized the SMILES in all files by generating canonical SMILES with RDKit version 2016.03.4.  In addition, we removed 2845 chemicals from pria_prospective.csv.gz that were duplicates of compounds in pria_rmi_cv.tar.gz.
description: {"references": ["Liu et al. (2018) Practical Model Selection for Prospective Virtual Screening. Journal of Chemical Information and Modeling. doi:10.1021/acs.jcim.8b00363"]}
DOI: 10.17632/g99ppywhy3.1
title: Data for: Distinguishing Between Gleason 5 Adenocarcinoma and Intraductal Carcinoma of the Prostate with Tumor Necrosis: A Morphologic Study

description: Raw data and Fisher's Exact Test on contingency tables: Intraductal carcinoma of the prostate vs. Invasive adenocarcinoma of the prostate Gleason 5 with tumor necrosis
DOI: 10.5281/zenodo.1257046
title: Context-Aware 3D Object Anchoring For Mobile Robots Dataset

description: This dataset accompanies the following publication:

Günther, M.; Ruiz-Sarmiento, J. R.; Galindo, C.; González-Jiménez, J. & Hertzberg, J. <strong>Context-Aware 3D Object Anchoring for Mobile Robots.</strong> <em>Robot. Auton. Syst.</em>, 2018 (accepted)

The dataset consists of 15 scenes inspected by a robot equipped with a RGB-D camera driving around a table and turning towards it from different locations. The table contained a number of objects in varying table settings. In total, the dataset contains 1387 seconds of observation and 144 unique objects from 9 categories:


	SugarPot
	MilkPot
	CoffeeJug
	MobilePhone
	Mug
	Dish
	Fork
	Knife
	Spoon
	TableSign


Segmentation, tracking and local object recognition was run on the recorded sensor data, and its output (tracked objects and local recognition results) was added to the dataset. Since the objects were observed from multiple perspectives and tracking was lost while the robot was moving from one observation pose to another, the dataset contains more than one track ID for most objects (one for each subsequent observation of the object). Each track ID was manually labeled with the ground truth category of the object it represented. Additionally, all track IDs belonging to the same object were manually grouped together to allow evaluation of the anchoring process. Track IDs that did not correspond to any object on the table (but instead to objects on different tables, pieces of the table itself or other artifacts) were manually removed. In total, out of 432 track IDs, 410 (94.9 %) were associated with true objects, while 22 (5.1 %) were removed as artifacts.

<br>
<strong>File contents</strong>

All data is provided as rosbags. The naming scheme is as follows:


	`*-sensordata.bag.bz2`: The raw sensor data from the robot and all transform data, including localization in a map.
	`*-perception.bag.bz2`: The object recognition results and ground truth information for the tracked objects.
	`scene??-pr2-*.bag.bz2`: 5 scenes that were recorded using the PR2 robot.
	`scene??-calvin-*.bag.bz2`: 10 scenes that were recorded using the Calvin robot.


Both robots used an ASUS Xtion Pro Live as 3D camera.

`race_vision_msgs.tar.bz2`: The custom messages used in the `-perception` rosbags, as a ROS Kinetic package.

<br>
<strong>Videos</strong>

To get a first impression of the dataset, `scene10.mp4` and `scene19.mp4` show the corresponding scenes from the point of view of the robot's RGB camera.
DOI: 10.5281/zenodo.1257047
title: Context-Aware 3D Object Anchoring For Mobile Robots Dataset

description: This dataset accompanies the following publication:

Günther, M.; Ruiz-Sarmiento, J. R.; Galindo, C.; González-Jiménez, J. & Hertzberg, J. <strong>Context-Aware 3D Object Anchoring for Mobile Robots.</strong> <em>Robot. Auton. Syst.</em>, 2018 (accepted)

The dataset consists of 15 scenes inspected by a robot equipped with a RGB-D camera driving around a table and turning towards it from different locations. The table contained a number of objects in varying table settings. In total, the dataset contains 1387 seconds of observation and 144 unique objects from 9 categories:


	SugarPot
	MilkPot
	CoffeeJug
	MobilePhone
	Mug
	Dish
	Fork
	Knife
	Spoon
	TableSign


Segmentation, tracking and local object recognition was run on the recorded sensor data, and its output (tracked objects and local recognition results) was added to the dataset. Since the objects were observed from multiple perspectives and tracking was lost while the robot was moving from one observation pose to another, the dataset contains more than one track ID for most objects (one for each subsequent observation of the object). Each track ID was manually labeled with the ground truth category of the object it represented. Additionally, all track IDs belonging to the same object were manually grouped together to allow evaluation of the anchoring process. Track IDs that did not correspond to any object on the table (but instead to objects on different tables, pieces of the table itself or other artifacts) were manually removed. In total, out of 432 track IDs, 410 (94.9 %) were associated with true objects, while 22 (5.1 %) were removed as artifacts.

<br>
<strong>File contents</strong>

All data is provided as rosbags. The naming scheme is as follows:


	`*-sensordata.bag.bz2`: The raw sensor data from the robot and all transform data, including localization in a map.
	`*-perception.bag.bz2`: The object recognition results and ground truth information for the tracked objects.
	`scene??-pr2-*.bag.bz2`: 5 scenes that were recorded using the PR2 robot.
	`scene??-calvin-*.bag.bz2`: 10 scenes that were recorded using the Calvin robot.


Both robots used an ASUS Xtion Pro Live as 3D camera.

`race_vision_msgs.tar.bz2`: The custom messages used in the `-perception` rosbags, as a ROS Kinetic package.

<br>
<strong>Videos</strong>

To get a first impression of the dataset, `scene10.mp4` and `scene19.mp4` show the corresponding scenes from the point of view of the robot's RGB camera.
DOI: 10.5281/zenodo.1410712
title: Dwd European Weather

description: opendata.dwd.de - OpenData by Deutscher Wetter Dienst

Conditions: https://www.dwd.de/EN/service/copyright/copyright_node.html

dates and times are UTC.
DOI: 10.18169/papdeott007314
title: Roll Structure Capacitive Encoder
DOI: 10.18169/papdeott007321
title: Verfahren und Anordnung zum Reibungsschweißen mit einem Linearmotor als Erregereinrichtung
DOI: 10.18169/papdeott007340
title: Eye Focus Based Region of Interest for Collimation
DOI: 10.18169/papdeott007351
title: Lastgeführtes erneuerbares Kraftwerkskonzept
DOI: 10.18169/papdeott007352
title: Novel Rotor Structure for Magnet Fixation
DOI: 10.18169/papdeott007354
title: Integration eines verbesserten LNG- Regasifizierungsverfahrens in den GuD-Prozess
DOI: 10.18169/papdeott007355
title: Kühlung von elektrischen Luftfahrmotoren mittels an Bord vorhandenen Kraftstoffs
DOI: 10.18169/papdeott007357
title: Kombinierte Positionierungsvorrichtung für ein 2D/3D Bildgebungssystem
DOI: 10.18169/papdeott007358
title: Verfahren zur feldorientierten Regelung von zwei Carriern
DOI: 10.18169/papdeott007361
title: Bauart einer permanenterregten Synchronmaschine zur Vermeidung eines Totalausfalls bei Windungsschlüssen
DOI: 10.18169/papdeott007362
title: Modulares Säulensystem für Infrastrukturkomponenten in der Verkehrstechnik
DOI: 10.18169/papdeott007363
title: Verfahren zur Validierung der Belegungsberechtigung von Fahrzeugen an Ladeplätzen
DOI: 10.18169/papdeott007365
title: Verfahren zur Anzeige von BIM-Daten-Qualität
DOI: 10.18169/papdeott007366
title: Vakuumschaltröhre mit beidseitig bewegten Kontakten
DOI: 10.18169/papdeott007367
title: Online Parameterermittlung von Widerstand und Motorkonstante bei Elektromotoren
DOI: 10.18169/papdeott007369
title: Sensorless Control of a BLDC Motor
DOI: 10.18169/papdeott007370
title: Zonenbasierte Luftraumüberwachung für zivile Drohnen und Flugtaxis
DOI: 10.18169/papdeott007371
title: Leistungsgesteigerte Asynchronmotoren durch variablen Luftspalt
DOI: 10.18169/papdeott007373
title: Verfahren zur automatischen Berechnung von Versionskompatibilitäten zwischen Software Systemen beliebiger Komplexität und den dazu gehörigen Konfigurationsdaten
DOI: 10.18169/papdeott007375
title: Reduzierung von Energiebuskabelquerschnitten durch den Einsatz von Speichersystemen
DOI: 10.18112/openneuro.ds000114.v1.0.1
title: A test-retest fMRI dataset for motor, language and spatial attention functions.
DOI: 10.25919/5b91c8b150944
title: Graphene Oxide Structure Set

description: This is a set of graphene oxide nanoflake INITIAL CONFIGURATIONS, for use in computational studies. These structures have not been optimized or relaxed.  The size ranges from 294 carbon atoms to 1200 carbon atoms, all with a hexagonal shape and hydrogen edge terminations.  Four ZZ and four AC geometries are represented, each with 50 random coverages of OH and O (in the ether configuration).  The number of oxygen atoms is set to 25% of the number of carbon atoms, but other lower concentrations could be generated by randomly deleting the O or OH adsorbates. All files are in XYZ format, and the naming convention is C[number of carbon atoms]O[number of oxygen atoms]H[number of hydrogen atoms]-config[X].xyz, where X is the random configuration (0, ... 49).
DOI: 10.17632/px6sr52zpb.2
title: Data for: Co-management of small-scale fisheries and ecosystem services

description: Appendix A. Complete database of the 53 papers reviewed in this study coded by complete reference, abstract, keywords, web of science categories, subject, objective, method, outcome, biodiversity (if is addressed or not), type of ecosystem services addressed, ecosystem services, type of study (ecological, social or socio-ecological), social capital (if is addressed or not). In the Appendix we also provide the geographic location of the study cases and the references coded according to the number of ecosystem services addressed (60 entries). Appendix B. Sub-sample of papers that were used calculate the ratio response for ecosystem services and biodiversity. This analysis quantified the amount of ecosystem services and biodiversity provided inside TURFs and outside in open access areas (n=13). We included the effect size (lnR) for both samples considering the observed means of ecosystem services provision inside the TURFs and in open access.
DOI: 10.17632/d4js3h6zsx.1
title: Data for: Online and handwritten homework in Calculus for STEM majors

description: Anonymized data on student results.
DOI: 10.17632/k5686bfpcv.2
title: Spt6 is required for the fidelity of promoter selection. Doris et al.
DOI: 10.5281/zenodo.1411018
title: Data Underpinning "Coupling Between Cerebral Blood Flow And Cerebral Blood Volume: Contributions Of Different Vascular Compartments"

description: The data in this archive was acquired to investigate the coupling between cerebral blood flow and cerebral blood volume across different vascular compartments. These results will form the basis of a forthcoming publication. Please reference this dataset (version v1.1.0) if you use it in your work. Wesolowski R, Blockley NP, Driver ID, Francis ST, Gowland PA. Data underpinning "Coupling between cerebral blood flow and cerebral blood volume: Contributions of different vascular compartments". Zenodo 2018. doi: 10.5281/zenodo.1411018. 

This dataset contains measurements of the haemodynamic responses of different compartments to a visual stimulus (8Hz red LED goggles, 19.2s ON, 40.8s OFF). Time course data are cycle averaged for the following haemodynamic properties;


	Arterial cerebral blood volume (CBVa) measured using Look-Locker Flow-sensitive Alternating Inversion Recovery (LL-FAIR) sensitised to CBVa.
	Cerebral blood flow (CBF) measured using Look-Locker Flow-sensitive Alternating Inversion Recovery (LL-FAIR) sensitised to CBF.
	Total cerebral blood volume (CBVtot) measured using bolus injections of a Gadolinium based contrast agent combined with T2* weighed gradient echo EPI.


In addition, weighted mean and standard deviation of the changes in these parameters are presented using time windows of 9.6–19.2s and 40.8–60s for ON and OFF, respectively. Weighting is performed with respect to the number of voxels present in each of the subjects regions of interest.

Time course data were extracted from two different regions of interest;


	ROI<sub>CBF</sub>: defined using a CBF localiser
	ROI<sub>COMMON</sub>: defined using the overlap of CBF, CBV<sub>a</sub> and CBV<sub>tot</sub> localisers


Furthermore, the transit times for CBF and CBVa were estimated for an average stimulus cycle and mean values extracted using time windows of 9.6–19.2s and 40.8–60s for ON and OFF, respectively. These data were extracted from ROI<sub>CBF</sub>.

Changes

- Additional analysis using a common ROI (the overlap of CBF, CBV<sub>a</sub> and CBV<sub>tot</sub> responses)

- Inclusion of transit times for CBF and CBV<sub>a</sub> for the CBF ROI
DOI: 10.17632/n2h4sfmz4w.1
title: Encryption and Steganography of Synthetic Gene Circuits - Dataset

description: This is the raw data and FloJo analysis files for figures 2, 4 and 5 in the manuscript "Encryption and Steganography of Synthetic Gene Circuits". FlowJo files are .wsp and the layouts are available within those files when opened in FlowJo.
DOI: 10.17632/z45p65cs84.1
title: Nucleosomes stabilize ssRNA+dsDNA triple helices on human cells

description: This data correspond to the raw unmodified figures included on the revised manuscript "Nucleosomes stabilize ssRNA+dsDNA triple helices on human cells". Here determine the nucleosome stabilization of triple helix structures on the nucleosome entry/exit site. Additionally we designed a method to determine the RNA-dependent changes in chromatin through the formation of triple helices with a method called TRIP-seq.
DOI: 10.17632/fxf82gjbbx.1
title: CARM1 methylates GAPDH to regulate glucose metabolism and is suppressed in liver cancer. Xing-Yu Zhong
DOI: 10.17632/mcgywvn6cz.1
title: Schedule paper data

description: This data is used to help model the schedule of marine reserves being established over a 34 year period.