cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9891515
title: Water chemistry and DIC isotope dataset of the Yangtze River source region

description: This is a water chemistry and DIC isotope dataset from the Yangtze River source region in Qinghai-Tibet Plateau.<br>Using this dataset, please cite: Song, C., Wang, G., Mao, T., Huang, K., Sun, X., Hu, Z., et al (2020). Spatiotemporal variability and sources of DIC in permafrost catchments of the Yangtze River source region: insights from stable carbon isotope and water chemistry. <i>Water Resources Research</i>, 56(1), e2019WR025343. https://doi.org/10.1029/ 2019WR025343<br>For more detailed information regarding the data, please contact Chunlin Song (songchunlin@scu.edu.cn)
DOI: 10.22008/fk2/b674ar/ogiqlo
title: SZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/km1etg
title: WV.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/6wxn1k
title: r_TOA_01.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/fp3lvf
title: r_TOA_02.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.5281/zenodo.3462435
title: European Literary Text Collection (ELTeC): April 2021 release with 14 collections of at least 50 novels.

description: This release contains 14 collections of at least 50 novels, 8 of which have reached 100 novels, and a total of over 1200 novels. Collections in this release include: Czech, German, English, French, Hungarian, Norwegian, Polish, Portuguese, Romanian, Slovenian, Spanish, Serbian, Swedish and Ukrainian. Note that this is an umbrella release, referencing the collections included in the release, but not containing the actual files. Citation suggestion for ELTeC: <em>European Literary Text Collection (ELTeC)</em>, version 1.1.0, April 2021, edited by Carolin Odebrecht, Lou Burnard and Christof Schöch. COST Action <em>Distant Reading for European Literary History</em> (CA16204). DOI: doi.org/10.5281/zenodo.4662444. (See also the citation suggestions for individual ELTeC collections in their respective repositories on Github.)
description: Note that this is an umbrella release, referencing the collections included in the release, but not containing the actual files. ELTeC has been created in the context of the COST Action 'Distant Reading for European Literary History' (CA16204), a COST Action funded by the COST Association as part of the Horizon 2020 Framework Programme of the EU.
DOI: 10.22008/fk2/b674ar/dvv1vl
title: r_TOA_03.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/3rbs7e
title: r_TOA_04.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/q0pcal
title: r_TOA_05.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/pxrqqm
title: r_TOA_06.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/8jlktl
title: r_TOA_07.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/4hbxvu
title: r_TOA_08.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/dholtp
title: r_TOA_09.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.6084/m9.figshare.14461834
title: Meta-data

description: Meta-data for the manuscript
DOI: 10.5281/zenodo.3404689
title: RNA-seq Dataset from Crowley et. al. 2015

description: This dataset was uploaded to this repository by Joshua P. Zitovsky and Michael I. Love with permission from the original authors, due to the fact that the original dataset is not currently hosted in a stable repository. If this dataset is used in original research leading to published work, please cite the Crowley et. al. 2015 paper. This repository contains an RNA-seq dataset based on the allelic expression study by Crowley et. al. (2015). The study took mice from three divergent inbred strains (CAST/EiJ, PWK/PhJ and WSB/EiJ) and performed a diallel cross. The data set contains allele-specific expression (ASE) counts for 72 mice and 23,297 genes in the resulting cross, with 12 mice of each possible parent combination, and an equal number of males and females within each parent combination. Sequencing was performed with the Illumina HiSeq 2000 platform to generate 100-bp paired-end reads and following the TruSeq RNA Sample Preparation v2 protocol.
description: {"references": ["James J. Crowley et. al. Analysis of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nature Genetics, 47(4):353\u2013360, March 2015. doi: 10.1038/ng.3222."]}
DOI: 10.6084/m9.figshare.14461834.v2
title: Meta-data

description: Meta-data for the manuscript
DOI: 10.5281/zenodo.3404688
title: RNA-seq Dataset from Crowley et. al. 2015

description: This dataset was uploaded to this repository by Joshua P. Zitovsky and Michael I. Love with permission from the original authors, due to the fact that the original dataset is not currently hosted in a stable repository. If this dataset is used in original research leading to published work, please cite the Crowley et. al. 2015 paper. This repository contains an RNA-seq dataset based on the allelic expression study by Crowley et. al. (2015). The study took mice from three divergent inbred strains (CAST/EiJ, PWK/PhJ and WSB/EiJ) and performed a diallel cross. The data set contains allele-specific expression (ASE) counts for 72 mice and 23,297 genes in the resulting cross, with 12 mice of each possible parent combination, and an equal number of males and females within each parent combination. Sequencing was performed with the Illumina HiSeq 2000 platform to generate 100-bp paired-end reads and following the TruSeq RNA Sample Preparation v2 protocol.
description: {"references": ["James J. Crowley et. al. Analysis of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nature Genetics, 47(4):353\u2013360, March 2015. doi: 10.1038/ng.3222."]}
DOI: 10.6084/m9.figshare.14461834.v1
title: Meta-data

description: Meta-data for the manuscript
DOI: 10.22008/fk2/b674ar/cyjqzf
title: r_TOA_10.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/z7fgqi
title: r_TOA_11.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/9orizx
title: r_TOA_12.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/0fkie0
title: r_TOA_13.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/wgzgvq
title: r_TOA_14.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/ff68kb
title: r_TOA_15.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/cd8dwu
title: r_TOA_16.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/5txrne
title: r_TOA_17.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/xm7ia5
title: r_TOA_18.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/rtlmek
title: r_TOA_19.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/gssutz
title: r_TOA_20.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/zwxsxc
title: r_TOA_21.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/xadj6x
title: O3.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/xvofgi
title: OAA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/za5vwx
title: OZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/kethre
title: SAA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/7ojbzn
title: SZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/jm8ujd
title: WV.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/hf7vg0
title: r_TOA_01.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/w9ti9m
title: r_TOA_02.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/1kvopy
title: r_TOA_03.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/yoau6o
title: r_TOA_04.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/der6uj
title: r_TOA_05.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/4fubde
title: r_TOA_06.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/nkxjlu
title: r_TOA_07.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/wymlc1
title: r_TOA_08.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/4pprxp
title: r_TOA_09.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/l2zkke
title: r_TOA_10.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/kg0c1z
title: r_TOA_11.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/55ro0s
title: r_TOA_12.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.25345/c5fr51
title: MassIVE MSV000087262 - Myofilament Glycation in Diabetes Reduces Contractility by Inhibiting Tropomyosin Movement, is Rescued by cMyBPC Domains
title: Diabetes doubles the risk of developing heart failure (HF). As the prevalence of diabetes grows, so will HF unless the mechanisms connecting these diseases can be identified. Methylglyoxal (MG) is a glycolysis by-product that forms irreversible modifications on lysine and arginine, called glycation. We previously found that myofilament MG glycation causes sarcomere contractile dysfunction and is increased in patients with diabetes and HF. The aim of this study was to discover the molecular mechanisms by which MG glycation of myofilament proteins cause sarcomere dysfunction and to identify therapeutic avenues to compensate. In humans with type 2 diabetes without HF, we found increased glycation of sarcomeric actin compared to non-diabetics and it correlated with decreased calcium sensitivity. Depressed calcium sensitivity is pathogenic for HF, therefore myofilament glycation represents a promising therapeutic target to inhibit the development of HF in diabetics. To identify possible therapeutic targets, we further defined the molecular actions of myofilament glycation. Skinned myocytes exposed to 100 uM MG exhibited decreased calcium sensitivity, maximal calcium-activated force, and crossbridge kinetics. Replicating MG functional affects using a computer simulation of sarcomere function predicted simultaneous decreases in tropomyosin blocked-to-closed rate transition and crossbridge duty cycle were consistent with all experimental findings. Stopped-flow experiments and ATPase activity confirmed MG decreased the blocked-to-closed transition rate. Currently, no therapeutics target tropomyosin, so as proof-of-principal, we used a n-terminal peptide of myosin-binding protein C, previously shown to alter tropomyosin position on actin. C0C2 completely rescued MG-induced calcium desensitization, suggesting a possible treatment for diabetic HF.
DOI: 10.22008/fk2/b674ar/s1mzqf
title: r_TOA_13.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/jy1crx
title: r_TOA_14.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/nabmi9
title: r_TOA_15.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/ye1y1d
title: r_TOA_16.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/spjewb
title: r_TOA_17.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.6084/m9.figshare.14461836.v1
title: Meta-data for the Manuscript

description: Meta-data for the Manuscript
DOI: 10.6084/m9.figshare.14461836
title: Meta-data for the Manuscript

description: Meta-data for the Manuscript
DOI: 10.22008/fk2/b674ar/yd3qew
title: r_TOA_18.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/fapjhh
title: r_TOA_19.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/punnav
title: r_TOA_20.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/gxf1yx
title: r_TOA_21.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/ljtuxg
title: O3.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/vpf4gc
title: OAA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/oq52ur
title: OZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/vamceo
title: SAA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/38xzyn
title: SZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/oim3rr
title: WV.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/pww3mv
title: r_TOA_01.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/3cuqbn
title: r_TOA_02.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/d9g6mb
title: r_TOA_03.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/sl9irh
title: r_TOA_04.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/sgpan7
title: r_TOA_05.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/drrud5
title: r_TOA_06.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/wjdirs
title: r_TOA_07.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/qsxymo
title: r_TOA_08.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/u5nfkc
title: r_TOA_09.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/2iwqpf
title: r_TOA_10.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/omtpy0
title: r_TOA_11.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/briprc
title: r_TOA_12.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/sl5cxy
title: r_TOA_13.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/wytfff
title: r_TOA_14.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/tcxp3g
title: r_TOA_15.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/gkiopm
title: r_TOA_16.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/5nn8ns
title: r_TOA_17.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/te7oyz
title: r_TOA_18.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/lalscc
title: r_TOA_19.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/g8m3ib
title: r_TOA_20.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/q9m0ou
title: r_TOA_21.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/3pryp3
title: O3.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.25345/c59z33
title: MassIVE MSV000087263 - proteowizard mzML Mascot mztab test test test test test test test test test test
title: test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test
DOI: 10.22008/fk2/b674ar/3hj3ec
title: OAA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/uw3ucx
title: OZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/jq3pgb
title: SAA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/nl9bae
title: SZA.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/kslxzu
title: WV.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/yuchiy
title: r_TOA_01.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/ztu2p5
title: r_TOA_02.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/o0uvzl
title: r_TOA_03.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/chqcqp
title: r_TOA_04.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/mblssp
title: r_TOA_05.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/qsj0wd
title: r_TOA_06.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/ut7d4y
title: r_TOA_07.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.5281/zenodo.3384091
title: LoDoPaB-CT Dataset

description: A Benchmark Dataset for Low-Dose CT Reconstruction Methods. The following Data Descriptor article provides full documentation: Leuschner, J., Schmidt, M., Baguer, D.O. <em>et al.</em> LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction. <em>Sci Data</em> <strong>8, </strong>109 (2021). https://www.nature.com/articles/s41597-021-00893-z The python library DIVαℓ (github.com/jleuschn/dival) can be used to download and access the dataset. Reconstructions from the LIDC/IDRI dataset are used as a basis for this dataset. The ZIP files included in the LoDoPaB dataset contain multiple HDF5 files. Each HDF5 file contains one HDF5 dataset named <code>"data"</code>, that provides a number of samples (128 except for the last file in each ZIP file). For example, the <code>n</code>-th training sample pair is stored in the files <code>"observation_train_%03d.hdf5"</code> and <code>"ground_truth_train_%03d.hdf5"</code> where <code>"%03d"</code> is <code>floor(n / 128)</code>, at row <code>(n mod 128)</code> of <code>"data"</code>. <em>Note:</em> each last ground truth file (i.e. <code>ground_truth_train_279.hdf5</code>, <code>ground_truth_validation_027.hdf5</code> and <code>ground_truth_test_027.hdf5</code>) still contains a HDF5 dataset of shape (128, 362, 362), although it contains less than 128 valid samples. Thus, the number of valid samples needs to be determined from the total samples numbers in the part (i.e. "train": 35820, "validation": 3522, "test": 3553), or from the corresponding observation file, for which the first dimension of the HDF5 dataset matches the number of valid samples in the file. The randomized patient IDs of the samples are provided as CSV files. The patient IDs of the train, validation and test parts are integers in the range of 0–631, 632–691 and 692–751, respectively. The ID of each sample is stored in a single row. <em>Acknowledgements</em> Johannes Leuschner, Maximilian Schmidt and Daniel Otero Baguer acknowledge the support by the Deutsche<br> Forschungsgemeinschaft (DFG) within the framework of GRK 2224/1 “π3: Parameter Identification – Analysis,<br> Algorithms, Applications”. We thank Simon Arridge, Ozan Öktem, Carola-Bibiane Schönlieb and Christian<br> Etmann for the fruitful discussion about the procedure, and Felix Lucka and Jonas Adler for their ideas and<br> helpful feedback on the simulation setup. The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study.
DOI: 10.5281/zenodo.3384092
title: LoDoPaB-CT Dataset

description: A Benchmark Dataset for Low-Dose CT Reconstruction Methods. The following Data Descriptor article provides full documentation: Leuschner, J., Schmidt, M., Baguer, D.O. <em>et al.</em> LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction. <em>Sci Data</em> <strong>8, </strong>109 (2021). https://www.nature.com/articles/s41597-021-00893-z The python library DIVαℓ (github.com/jleuschn/dival) can be used to download and access the dataset. Reconstructions from the LIDC/IDRI dataset are used as a basis for this dataset. The ZIP files included in the LoDoPaB dataset contain multiple HDF5 files. Each HDF5 file contains one HDF5 dataset named <code>"data"</code>, that provides a number of samples (128 except for the last file in each ZIP file). For example, the <code>n</code>-th training sample pair is stored in the files <code>"observation_train_%03d.hdf5"</code> and <code>"ground_truth_train_%03d.hdf5"</code> where <code>"%03d"</code> is <code>floor(n / 128)</code>, at row <code>(n mod 128)</code> of <code>"data"</code>. <em>Note:</em> each last ground truth file (i.e. <code>ground_truth_train_279.hdf5</code>, <code>ground_truth_validation_027.hdf5</code> and <code>ground_truth_test_027.hdf5</code>) still contains a HDF5 dataset of shape (128, 362, 362), although it contains less than 128 valid samples. Thus, the number of valid samples needs to be determined from the total samples numbers in the part (i.e. "train": 35820, "validation": 3522, "test": 3553), or from the corresponding observation file, for which the first dimension of the HDF5 dataset matches the number of valid samples in the file. The randomized patient IDs of the samples are provided as CSV files. The patient IDs of the train, validation and test parts are integers in the range of 0–631, 632–691 and 692–751, respectively. The ID of each sample is stored in a single row. <em>Acknowledgements</em> Johannes Leuschner, Maximilian Schmidt and Daniel Otero Baguer acknowledge the support by the Deutsche<br> Forschungsgemeinschaft (DFG) within the framework of GRK 2224/1 “π3: Parameter Identification – Analysis,<br> Algorithms, Applications”. We thank Simon Arridge, Ozan Öktem, Carola-Bibiane Schönlieb and Christian<br> Etmann for the fruitful discussion about the procedure, and Felix Lucka and Jonas Adler for their ideas and<br> helpful feedback on the simulation setup. The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study.
DOI: 10.22008/fk2/b674ar/aty3va
title: r_TOA_08.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/zs3djs
title: r_TOA_09.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/damtxh
title: r_TOA_10.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/ekxxoe
title: r_TOA_11.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/nkghaq
title: r_TOA_12.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/9pyz5n
title: r_TOA_13.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/3txpzs
title: r_TOA_14.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/baqvoa
title: r_TOA_15.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.22008/fk2/b674ar/x1sa86
title: r_TOA_16.tif

description: SICE version: Cloud removed, PPGC, SNAP7
DOI: 10.6084/m9.figshare.7636697.v1
title: Single-shot 3D shape reconstruction datasets

description: If you use the datasets for your research, please cite our paper below in your publication:<br><br>H. Nguyen, Y. Wang, and Z. Wang, “Single-Shot 3D Shape Reconstruction Using Structured Light and Deep Convolutional Neural Networks” Sensors 20(13), 3718, 2020.
DOI: 10.22008/fk2/b674ar/2pv14h
title: r_TOA_17.tif

description: SICE version: Cloud removed, PPGC, SNAP7