cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/vh5m-4965
title: Environment Recognition and Wearable RGB Cameras: Applications for Autonomous Lower-Limb Biomechatronic Devices

description: This RGB image dataset was experimentally collected using a wearable camera system and postprocessed for image classification of different walking environments conducive to controlling autonomous lower-limb biomechatronic devices (e.g., robotic lower-limb prostheses and exoskeletons). Overall, 34,254 sampled images were collected and individually labelled. The authors request that prospective users reference the following publication: Laschowski B, McNally W, Wong A, and McPhee J. (2019). Preliminary Design of an Environment Recognition System for Controlling Robotic Lower-Limb Prostheses and Exoskeletons. IEEE International Conference on Rehabilitation Robotics. Toronto, Canada.
DOI: 10.15468/decfjq
title: Community diversity in microbial eukaryotes from lakes in the the Vestfold Hills, Antarctica

description: Amplicon sequencing dataset (454 pyrosequencing) of microbial eukaryotes (18Sssu rRNA marker gene) in water samples along a salinity gradient (0-250 psu) from the Vestfold Hills, East Antarctica (68°S, 78°E).
DOI: 10.17638/datacat.liverpool.ac.uk/667
title: On Proactive, Transparent and Verifiable Ethical Reasoning for Robots
DOI: 10.21227/5vpm-br51
title: Environment Recognition and Wearable RGB Cameras: Applications for Autonomous Lower-Limb Biomechatronic Devices

description: This RGB image dataset was experimentally collected using a wearable camera system and postprocessed for image classification of different walking environments conducive to controlling autonomous lower-limb biomechatronic devices (e.g., robotic lower-limb prostheses and exoskeletons). Overall, 34,254 sampled images were collected and individually labelled. The authors request that prospective users reference the following publication: Laschowski B, McNally W, Wong A, and McPhee J. (2019). Preliminary Design of an Environment Recognition System for Controlling Robotic Lower-Limb Prostheses and Exoskeletons. IEEE International Conference on Rehabilitation Robotics. Toronto, Canada.
DOI: 10.21227/cwbb-et63
title: Software Development Effort Estimation (SDEE) dataset

description: The dataset contains Software Development Effort Estimation (SDEE) metrics values extracted from around 1800 Open Source Software (OSS) repositories of GitHub. SDEE metrics capture the developer activity information associated with various OSS repositories. The dataset is deployed for building a SDEE system, which given an input set of requirements, is capable of providing effort estimates for the required novel software.
DOI: 10.21227/d6qp-2n13
title: Software Development Effort Estimation (SDEE) dataset

description: The dataset contains Software Development Effort Estimation (SDEE) metrics values extracted from around 1800 Open Source Software (OSS) repositories of GitHub. SDEE metrics capture the developer activity information associated with various OSS repositories. The dataset is deployed for building a SDEE system, which given an input set of requirements, is capable of providing effort estimates for the required novel software.
DOI: 10.6073/pasta/151921245d972570fed3bcc1a478416c
title: Replaced by: . Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 Young of the year Arctic Grayling for the Kuparuk River near Toolik Field Station, Alaska 1986-2012

description: Repalced by: . Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 Arctic grayling young-of-the-year (YOY) were caught multiple times during each summer and measured and weighed. Fish were caught at designated stations from the Kuparuk River were collected during each summer from 1986 to current time. Phosphorus addition has occurred since 1983; station sites are relative distance from the original 1983 phosphorus dripper. Stations include sites in a reference, recovery, and fertilized reach. Reaches were defined based on the location of phosphorous addition (see methods). Phosphoric acid is added to the stream to increase the soluble reactive phosphorus by 0.32 uM. YOY were caught and transported to Toolik Field Station for measurements of weight and mass. Note no data is available for 2006.
DOI: 10.6073/pasta/822098392f6e0a40219d9e1d6a754617
title: Replaced by: Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 Long-term tagging file for arctic grayling on the Kuparuk River, Arctic LTER 1985-2012.

description: Replaced By: Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 1985 to 2012 long-term tagging file for Arctic Grayling (Thymallus arcticus) on the Kuparuk River. Phosphorus addition has occurred since 1983; station sites are relative distance from the original 1983 phosphorus dripper. Stations include sites in a reference, recovery, and fertilized reach. Reaches were defined based on the location of phosphorous addition (see methods). All grayling adults and juveniles captured during the field season are measured, weighed, tagged and released. Grayling were tagged originally with a colored tag with a number. In 1993, researchers started pit tagging the grayling. These pit tags can be read with an antenna to track the migration of the grayling throughout the Kuparuk River system. Note no data is available for years 2005 & 2006.
DOI: 10.6073/pasta/961be27548ed9de3266b581a262182c0
title: Replaced by: Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 Long-term tagging file for arctic grayling on the Oksrukuyik Creek, Arctic LTER 1989-2011

description: Replaced by: Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 1989 to 2002; 2005; 2010-2011 long-term tagging file for Arctic Grayling (Thymallus arcticus) on the Oksrukuyik. All grayling adults and juveniles captured during the field season are measured, weighed, tagged and released. Grayling were tagged with a colored tag with a number. . In 1993, researchers started pit tagging the grayling. These pit tags can be read with an antenna to track the migration of the grayling throughout the Kuparuk River system
DOI: 10.5281/zenodo.2530788
title: Histological images for tumor detection in gastrointestinal cancer

description: This is a set of 11977 image patches of hematoxylin & eosin stained histological samples of human colorectal cancer. It is a subset of the data set "100,000 histological images of human colorectal cancer and healthy tissue" which is accessible at http://dx.doi.org/10.5281/zenodo.1214456. Further information on the samples is available there.

This set contains three classes:

ADIMUC - adipose tissue and mucus, i.e. loose non-tumor tissue

STRMUS - stroma and muscle, i.e. dense non-tumor tissue

TUMSTU - colorectal cancer epithelial tissue and stomach cancer epithelial tissue, i.e. tumor tissue

All images are 512x512 px at 0.5 µm/px

We are using this data set to train a deep neural network to detect tumor cells in histological whole slide images of colorectal and stomach cancer.

If you use these images in your research, please consider citing our previous [1] and upcoming publication.

For information on ethics board approval, see [1].

-------------

[1] http://dx.doi.org/10.1371/journal.pmed.1002730
DOI: 10.5281/zenodo.2530789
title: Histological images for tumor detection in gastrointestinal cancer

description: This is a set of 11977 image patches of hematoxylin & eosin stained histological samples of human colorectal cancer. It is a subset of the data set "100,000 histological images of human colorectal cancer and healthy tissue" which is accessible at http://dx.doi.org/10.5281/zenodo.1214456. Further information on the samples is available there.

This set contains three classes:

ADIMUC - adipose tissue and mucus, i.e. loose non-tumor tissue

STRMUS - stroma and muscle, i.e. dense non-tumor tissue

TUMSTU - colorectal cancer epithelial tissue and stomach cancer epithelial tissue, i.e. tumor tissue

All images are 512x512 px at 0.5 µm/px

We are using this data set to train a deep neural network to detect tumor cells in histological whole slide images of colorectal and stomach cancer.

If you use these images in your research, please consider citing our previous [1] and upcoming publication.

For information on ethics board approval, see [1].

-------------

[1] http://dx.doi.org/10.1371/journal.pmed.1002730
DOI: 10.5517/ccdc.csd.cc21454j
title: CCDC 1880836: Experimental Crystal Structure Determination

description: Related Article: Lathewdeipor Shadap, Siewdorlang Diamai, Venkanna Banothu, D.P.S. Negi, Uma Adepally, Werner Kaminsky, Mohan Rao Kollipara|2019|J.Organomet.Chem.|884|44|doi:10.1016/j.jorganchem.2019.01.019
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc21455k
title: CCDC 1880837: Experimental Crystal Structure Determination

description: Related Article: Lathewdeipor Shadap, Siewdorlang Diamai, Venkanna Banothu, D.P.S. Negi, Uma Adepally, Werner Kaminsky, Mohan Rao Kollipara|2019|J.Organomet.Chem.|884|44|doi:10.1016/j.jorganchem.2019.01.019
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc21456l
title: CCDC 1880838: Experimental Crystal Structure Determination

description: Related Article: Lathewdeipor Shadap, Siewdorlang Diamai, Venkanna Banothu, D.P.S. Negi, Uma Adepally, Werner Kaminsky, Mohan Rao Kollipara|2019|J.Organomet.Chem.|884|44|doi:10.1016/j.jorganchem.2019.01.019
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc21457m
title: CCDC 1880839: Experimental Crystal Structure Determination

description: Related Article: Lathewdeipor Shadap, Siewdorlang Diamai, Venkanna Banothu, D.P.S. Negi, Uma Adepally, Werner Kaminsky, Mohan Rao Kollipara|2019|J.Organomet.Chem.|884|44|doi:10.1016/j.jorganchem.2019.01.019
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc21458n
title: CCDC 1880840: Experimental Crystal Structure Determination

description: Related Article: Lathewdeipor Shadap, Siewdorlang Diamai, Venkanna Banothu, D.P.S. Negi, Uma Adepally, Werner Kaminsky, Mohan Rao Kollipara|2019|J.Organomet.Chem.|884|44|doi:10.1016/j.jorganchem.2019.01.019
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21227/kg54-m827
title: ANiTH: A Novel Intelligent Text Hiding Technique

description: In this research, we propose an intelligent watermarking technique called ANiTH which conceals an invisible watermark through a digital text such that the hidden watermark can be extracted whenever there is an inquiry about the accuracy and reliability of digital texts shared on social media.
DOI: 10.5281/zenodo.2530834
title: Histological images for MSI vs. MSS classification in gastrointestinal cancer, FFPE samples

description: This repository contains 411,890 unique image patches derived from histological images of colorectal cancer and gastric cancer patients in the TCGA cohort (original whole slide SVS images are freely available at https://portal.gdc.cancer.gov/). All images in this repository are derived from formalin-fixed paraffin-embedded (FFPE) diagnostic slides ("DX" at the GDC data portal). This is explained well in this blog: http://www.andrewjanowczyk.com/download-tcga-digital-pathology-images-ffpe/

<strong>Preprocessing</strong>

All SVS slides were preprocessed as follows

1. automatic detection of tumor

2. resizing to 224 px x 224 px at a resolution of 0.5 µm/px

4. color normalization with the Macenko method (Macenko et al., 2009, http://wwwx.cs.unc.edu/~mn/sites/default/files/macenko2009.pdf)

5. assignment of patients to either "MSS" (microsatellite stable) or "MSIMUT" (microsatellite instable or highly mutated)

6. randomization of patients to training and testing sets (~70% and ~30%). Randomization was done on a patient level rather than on a slide or tile level

7. equilibration of training sets by undersampling (removing excess tiles in MSS class in a random way)

<strong>File description</strong>

1. STAD_TRAIN_MSS - training images (~70% of all patients) for gastric (stomach) cancer TCGA patients with MSS (microsatellite stable) tumors, 50285 unique image patches; FFPE samples

2. STAD_TRAIN_MSIMUT - training images ( (~70% of all patients) for gastric (stomach) cancer TCGA patients with MSI (microsatellite instable) or highly mutated tumors, 50285 unique image patches; FFPE samples

3. STAD_TEST_MSS - test images (~30% of all patients) for gastric (stomach) cancer TCGA patients with MSS (microsatellite stable) tumors, 90104 unique image patches; FFPE samples

4. STAD_TEST_MSIMUT - test images ( ~30% of all patients) for gastric (stomach) cancer TCGA patients with MSI (microsatellite instable) or highly mutated tumors, 27904 unique image patches; FFPE samples

5. CRC_DX_TEST_MSIMUT - test images (~30% of all patients) for colorectal cancer TCGA patients with MSI (microsatellite instable) or highly mutated tumors, 29335 unique image patches; FFPE samples

6. CRC_DX_TEST_MSS - test images (~30% of all patients) for colorectal cancer TCGA patients with MSS (microsatellite stable) tumors, 70569 unique image patches; FFPE samples

7. CRC_DX_TRAIN_MSIMUT - training images (~70% of all patients) for colorectal cancer TCGA patients with MSI (microsatellite instable) or highly mutated tumors, 46704 unique image patches; FFPE samples

8. CRC_DX_TRAIN_MSS - training images (~70% of all patients) for colorectal cancer TCGA patients with MSS (microsatellite stable) tumors, 46704 unique image patches; FFPE samples
DOI: 10.5281/zenodo.2532611
title: Histological images for MSI vs. MSS classification in gastrointestinal cancer, snap-frozen samples

description: This repository contains 218,578 unique image patches derived from histological images of colorectal cancer patients in the TCGA cohort (original whole slide SVS images are freely available at https://portal.gdc.cancer.gov/). All images in this repository are derived from snap-frozen tissue slides ("TS" or "BS" at the GDC data portal).

<strong>Preprocessing</strong>

All SVS slides were preprocessed as follows

1. automatic detection of tumor

2. resizing to 224 px x 224 px at a resolution of 0.5 µm/px

4. color normalization with the Macenko method (Macenko et al., 2009, http://wwwx.cs.unc.edu/~mn/sites/default/files/macenko2009.pdf)

5. assignment of patients to either "MSS" (microsatellite stable) or "MSIMUT" (microsatellite unstable or hypermutated)

6. randomization of patients to training and testing sets (~70% and ~30%). Randomization was done on a patient level rather than on a slide or tile level

7. equilibration of training sets by undersampling (removing excess tiles in MSS class in a random way)

<strong>File description</strong>

1. STAD_TRAIN_MSS - training images (~70% of all patients) for gastric (stomach) cancer TCGA patients with MSS (microsatellite stable) tumors, 50285 unique image patches; FFPE samples

2. STAD_TRAIN_MSIMUT - training images ( (~70% of all patients) for gastric (stomach) cancer TCGA patients with MSI (microsatellite instable) or highly mutated tumors, 50285 unique image patches; FFPE samples

3. STAD_TEST_MSS - test images (~30% of all patients) for gastric (stomach) cancer TCGA patients with MSS (microsatellite stable) tumors, 90104 unique image patches; FFPE samples

4. STAD_TEST_MSIMUT - test images ( ~30% of all patients) for gastric (stomach) cancer TCGA patients with MSI (microsatellite instable) or highly mutated tumors, 27904 unique image patches; FFPE samples
DOI: 10.6073/pasta/52ca086ad90689db0c789caf39a84811
title: Replaced by: Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 Young-of-year Arctic grayling caught on the Kuparuk River

description: Replaced by: Arctic Grayling length, weight and tag data from Arctic LTER Streams project, Toolik Field Station Alaska, 1985 to Present. Environmental Data Initiative. http://dx.doi.org/10.6073/pasta/54f1c01e79ea7c573263b8b12115eb46 Arctic grayling young-of-the-year (YOY) were caught multiple times during each summer and measured and weighed. Fish were caught at designated stations from the Kuparuk River were collected during each summer from 1986 to current time. YOY growth could be calculated by using data from the first day fish were caught compared to the last day in a field season. This data can be compared to where phosphorous additions occured in the Kuparuk River. Phosphorus addition has occurred since 1983; station sites are relative distance from the original 1983 phosphorus dripper. Stations include sites in a reference, recovery, and fertilized reach. Reaches were defined based on the location of phosphorous addition (see methods). Phosphoric acid is added to the stream to increase the soluble reactive phosphorus by 0.32 uM. YOY were caught and transported to Toolik Field Station for measurements of weight and mass.
DOI: 10.5281/zenodo.2559687
title: Ecological traits of the world's primates database

description: Here we present a database on some important ecological traits of the world’s primates, including home range size, locomotion type, diel activity, trophic guild, body mass, habitat type, current conservation status, population trend, and geographic realm. We compiled this information through a review of 1216 studies published between 1941 and 2018, resulting in a comprehensive, easily accessible and user-friendly database.
DOI: 10.6073/pasta/091e7fcd9d01166052a1131829194624
title: CSM02 Seasonal summary of numbers of small mammals on the four LTER gallery forest and limestone ledges traplines in wooded habitats at Konza Prairie

description: Data set contains seasonal summaries (spring, summer and autumn) of the number of individuals of each species of small mammal captured (relative abundance) on each woodland trapline. Each record contains year, season, trapline and number of individuals captured of each species. These live trap records are based on daily captures during a single 4-day trapping period in spring (early March to early April), summer (early July to late July) and autumn (mid-October to early December) for each of four permanent traplines established in two habitats (two traplines in gallery forest and two on limestone ledges). Bison did not graze any of the treatment units during the period of study.
DOI: 10.5281/zenodo.2560273
title: Dehydrogenative Silylation - Marie Curie SILYCAT

description: The datasheet contains spectroscopic data (<sup>1</sup>H, <sup>13</sup>C, <sup>29</sup>Si NMR, infra-red and high-resolution mass spectrometry) of compounds prepared for the following publication :

S. Pramanik, A. Fernandes, V. Liautard, M. Pucheault, F. Robert, Y. Landais, <em>Chem. Eur. J. </em><strong>2019</strong>, <em>25</em>, 728-732. 

DOI: 10.1002/chem.201803989

A copy of the paper is available in open access at https://hal.archives-ouvertes.fr/  :

〈<strong>hal-02012175, v1</strong>〉
DOI: 10.5258/soton/d0803
title: Data for Chemical Consequences of the Mechanical Bond

description: Characterisation data for novel compounds reported and mechanistic studiesThis file contains the data from Chemical Consequences of the Mechanical Bond: A Tandem Active Template‐Rearrangement Reaction (DOI:10.1002/anie.201813950). In the folders can be found the characterisation data for the compounds reported. In addition, MS and NMR data is provided for the mechanistic studies and XYZ coordinates are provided for the modelling study.
DOI: 10.5281/zenodo.2560272
title: Dehydrogenative Silylation - Marie Curie SILYCAT

description: The datasheet contains spectroscopic data (<sup>1</sup>H, <sup>13</sup>C, <sup>29</sup>Si NMR, infra-red and high-resolution mass spectrometry) of compounds prepared for the following publication :

S. Pramanik, A. Fernandes, V. Liautard, M. Pucheault, F. Robert, Y. Landais, <em>Chem. Eur. J. </em><strong>2019</strong>, <em>25</em>, 728-732. 

DOI: 10.1002/chem.201803989

A copy of the paper is available in open access at https://hal.archives-ouvertes.fr/  :

〈<strong>hal-02012175, v1</strong>〉
DOI: 10.15468/19w5uz
title: POPA- Fisheries Observer Program of the Azores: Sea bird sightings in the Azores between 2004 and 2013 recorded by Biosphere Expedition

description: Sightings (snap shots) of sea birds collected by Biosphere Expeditions collaborators specifically for POPA. Since 2004 that Biosphere Expeditions (www.biosphere-expeditions.org) collects data for POPA in the Azores central group in April and May.
DOI: 10.15468/8penj5
title: POPA- Fisheries Observer Program of the Azores: Marine mammal sightings in the Azores between 2004 and 2013 recorded by Biosphere Expedition

description: Sightings (snap shots) of marine mammals collected by Biosphere Expeditions collaborators specifically for POPA. Since 2004  Biosphere Expeditions (www.biosphere-expeditions.org) collects data for POPA in the Azores central group in April and May.
DOI: 10.15468/oihejt
title: POPA- Fisheries Observer Program of the Azores: Sea turtle sightings in the Azores between 2004 and 2013 recorded by Biosphere Expedition

description: Sightings (snap shots) of sea turtles collected by Biosphere Expeditions colaborators specifically for POPA. Since 2004 that Biosphere Expeditions (www.biosphere-expeditions.org) collects data for POPA in the Azores central group in April and May.