cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3386336
title: COOS-7 (Cells Out Of Sample 7-Class)

description: This repository contains the version 1.0 of the COOS-7 dataset (to be presented as a poster at NeurIPS 2019; see preprint at https://arxiv.org/abs/1906.07282). COOS-7 contains 132,209 crops of mouse cells, stratified into a training dataset, and four test datasets representing increasing degrees of covariate shift from the training dataset. In the classification task associated with COOS-7, the aim is to build a classifier robust to covariate shifts typically seen in microscopy. Methods developers must train and optimize machine learning models using the training dataset exclusively, and evaluate performance on each of the four test datasets. <strong>Each HDF5 file contains two dictionaries:</strong><br> 'data' - contains all of the images in a four-dimensional array (images, channels, height, width)<br> 'labels' - contains the labels for each image, in the same order as the images in 'data' The value for labels indicates the class of the image, which can be one of seven values:<br> 0 - Endoplasmic Reticulum (ER)<br> 1 - Inner Mitochondrial Membrane (IMM)<br> 2 - Golgi<br> 3 - Peroxisomes<br> 4 - Early Endosome<br> 5 - Cytosol<br> 6 - Nuclear Envelope The h5py package is required to read these files with Python. We provide a Python script, unpackage_COOS.py, that will automatically save the archives as directories of tiff files, organized by class. The two channels for each image will be saved as separate images, with a suffix of "_protein.tif" and "_nucleus.tif", respectively. <strong>To run the unpackaging script, issue the command line argument:</strong><br> python unpackage_COOS.py [path of HDF5 file] [path of directory to save images to]<br> e.g. python unpackage_COOS.py ./COOS7_v1.0_training.hdf5 ./COOS7_v1.0_training_images/ <strong>Full information about the test sets and the images can be found at https://arxiv.org/abs/1906.07282.</strong>
DOI: 10.17632/yvwdspt5bb.1
title: Data for: Group singing has multiple benefits in the context of chronic pain: an exploratory pilot study

description: Interview data
DOI: 10.6073/pasta/8168e51daba2b7f7a978d2f6a27e22a4
title: Bacterial properties in discrete water column samples collected during Palmer LTER station seasons at Palmer Station Antarctica, 2002 - 2019.

description: The microbial biogeochemistry component of PAL focuses on marine bacterioplankton, and is thus a counterpart to the phytoplankton and zooplankton components, which together provide a detailed and comprehensive description of plankton ecology in PAL-LTER. Bacteria and Archaea (hereafter called "bacteria") are taxonomically and metabolically diverse. In coastal and offshore surface waters Bacteria generally predominate over Archaea, but Archaea are equal or greater in abundance in the mesopelagic layer below the euphoric zone. We focus on aerobic, heterotrophic bacteria in the upper 65 m at Palmer Station which oxidize recently-produced low molecular weight dissolved organic compounds released by phytoplankton and zooplankton, decomposing them back into CO2 and inorganic nutrients. Globally, marine bacteria respire an amount of carbon roughly equal to about half the daily photosynthetic production. In cold polar waters, relative bacterial activity is lower, with bacterial biomass production being equal to &lt;5% of the daily photosynthesis. The ratio at lower latitudes is 10-20%. The factors responsible for this contrast are not entirely clear. Resolving this pattern is a key aim of the PAL microbial component. At Palmer Station, bacterial production is low (&lt; 10 mgC/m2/d) in the winter (polar night) when there is little if any photosynthesis. There is a climatological (2003-14 average) summer peak of 50-60 mgC/m2/d in January-February but with considerable seasonal and annual variability. The 2016/2017 season data contains bacteria abundances for preserved samples for comparison to abundances from live samples. See the documentation for this in the accompanying file, 2016_live_vs_preserved.pdf.
DOI: 10.5281/zenodo.3401706
title: PROTAC virtual screening: A retrospective screening exercise

description: My goal is to test whether retrospective virtual screening approaches can guide the design of PROTACs. As a first step, I showed that HADDOCK was the best protein-protein docking tool among those I tested to predict how E3 ligases interact with their protein substrates. Here, I ask whether docking virtual libraries of PROTAC candidates to these E3 ligase – substrate protein interfaces can be used to predict which PROTACs are active.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation, and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.5281/zenodo.3401707
title: PROTAC virtual screening: A retrospective screening exercise

description: My goal is to test whether retrospective virtual screening approaches can guide the design of PROTACs. As a first step, I showed that HADDOCK was the best protein-protein docking tool among those I tested to predict how E3 ligases interact with their protein substrates. Here, I ask whether docking virtual libraries of PROTAC candidates to these E3 ligase – substrate protein interfaces can be used to predict which PROTACs are active.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation, and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.17632/gncknw3g7h.3
title: Data for: Ethnomedicine of Tetun ethnic people in West Timor Indonesia; Philosophy and practice in the treatment of malaria

description: Supplementary data PLANTS USED FOR THE TREATMENT OF MALARIA BY TETUN ETHNIC PEOPLE IN WEST TIMOR (INDONESIA) Note: 1. Data collected in April 20017 to December 2017 in Belu and Malaka Districts (West Timor, Indonesia). 2. Data collected by interview on 94 informants of Tetun ethnic people.
DOI: 10.7910/dvn/vmr7ms/t1mox5
title: clinical_data.tab

description: Includes demographic and clinical annotation
DOI: 10.25345/c53d3q
title: MassIVE MSV000084297 - GIMap_Carnitine_Benzinidizole_Treatment_SamllIntestine_SeptNov2019_PositivePolarity
title: Treatment of mice after being infected with C2C12 with carnitine and benzinidizole involving small intestine only.
DOI: 10.7910/dvn/wcpgau/0aadup
title: replication syntax for each table.sps

description: SPSS syntax
DOI: 10.7910/dvn/wcpgau/kzo5le
title: PloS Tables replication data.tab

description: SPSS data fo;e
DOI: 10.7910/dvn/wcpgau/w6h5kd
title: ReadMe for Friends.docx

description: :unav
DOI: 10.25345/c5zq0f
title: MassIVE MSV000084298 - Data for "A practical guide for analysis of histone post-translational modifications by mass spectrometry: best practices and pitfalls"
title: Histone proteomics from 5 human cell lines, discussed in publication: "A practical guide for analysis of histone post-translational modifications by mass spectrometry: best practices and pitfalls". Further explanation of data types, methods, and analysis are available in Data Explanation document in the Methods and Protocols folder.
DOI: 10.25345/c5tw8z
title: MassIVE MSV000084299 - GAS_Sprotein_Spleens_Timecourse_Proteomics
title: Quantitative proteomic analysis of mouse spleens harvested at various time points during infection with wild type and mutant strain.
DOI: 10.5281/zenodo.3393265
title: A Self-Adaptive Deep Learning Method for Automated Eye Laterality Detection Based on Color Fundus Photography

description: The data for "A Self-Adaptive Deep Learning Method for Automated Eye Laterality Detection Based on Color Fundus Photography", including original image data and labels, DL model files, training logs and validation results. <strong>Content</strong>: - <strong>Ex1_Preprocessing</strong> # the first experiment: preprocessing methods comparison - <strong>history</strong> # validation results of different metrics of models - <strong>log</strong> # training record of models. Read by TensorBoard - <strong>model</strong> # model file. Read by Keras - <strong>Ex2_Self-adaptive model</strong> # the second experiment: development of eye laterality detection model - <strong>data</strong> # serialized image data, including data and ground-truth label. Read by Python Pickle package. - <strong>Xy.h5</strong> # training data - <strong>test_Xy.h5</strong> # testing data - <strong>history</strong> # validation results of different metrics of models - <strong>log</strong> # training record of models. Read by TensorBoard - <strong>model</strong> # model file. Read by Keras - <strong>with_adaptive</strong> # with self-adaptive strategy - <strong>without_adaptive</strong> # without self-adaptive strategy For code review, please see: https://github.com/keepgallop/Eye-laterality-detection For more information, please contact liuchi_email@foxmail.com
DOI: 10.5281/zenodo.3401572
title: weecology/portalPredictions 2019-09-06

description: Using various models to forecast abundances at Portal
DOI: 10.5281/zenodo.3401574
title: weecology/forecasts 2019-09-06

description: Archived forecasts for future analysis
DOI: 10.17632/nhgbdhp2vy.1
title: Data for: A new spinosaurid theropod (Dinosauria: Megalosauroidea) from the late Barremian of Vallibona, Spain: Implications for spinosaurid diversity in the Early Cretaceous of the Iberian Peninsula

description: Datamatrix
DOI: 10.17632/gvpffvp75f.1
title: Data for: Lipid biomarkers in lacustrine sediments of the subtropical northeast Mexico and inferred ecosystem changes during the late Pleistocene and Holocene

description: Total lipid analysis concentration in percentages and Principal Component Analysis Figure.
DOI: 10.7910/dvn/zkeg5f/m8fqc0
title: River_data.tab

description: Hydroclimatic data for 91 basins
DOI: 10.5061/dryad.74p77q7/1
title: R code and data for running SDMs in biomod2

description: Zip file containing: (1) raw butterfly locality data used in the species distribution models (SDMs)('ButterflyDataBorneo_UniqueRecordsSITE1950s.csv'), (2) R script file for processing Worldclim climate variables ('WorldclimData_CorrelationScript.R'), and (3) R script file for running SDMs in biomod2 ('Biomod2SDMs_77Butterflies.R').
DOI: 10.5061/dryad.74p77q7/2
title: SDM output maps for 77 butterfly species

description: Zip file containing species distribution model (SDM) ensemble output maps for 77 range-restricted butterfly species on Borneo. Output maps include binary range maps ('BinaryRangeMaps' sub-folder) and probability of occurrence maps ('ProbabilityOccurrenceMaps' sub-folder) for the 77 butterfly species modelled. The 'BinaryMaps_Summed' and 'ProbabilityOccurrenceMaps_Summed' sub-folders contain maps depicting summed species ranges (i.e., species richness) and probability of occurrence (i.e., species occurrence) values, respectively, for: (1) all species (n=77), and (2) all species endemic to Borneo (n=15). Maps for each species are labelled with a unique number; see 'ButterflySpeciesNumbers.csv' for a list of butterfly numbers and corresponding species names.
DOI: 10.5061/dryad.74p77q7/3
title: R code and data for prioritization analyses

description: Zip file containing prioritization R code and species distribution model output maps used as input layers in prioritization analyses. The 'InputMaps_1kmSabah' folder includes probability of occurrence maps for: (1) the 15 endemic butterfly species ('Endemic_15' sub-folder), and (2) the 62 Sundaland-restricted (but non-endemic) butterfly species ('NonEndemic_62' sub-folder) across Sabah. R code for prioritization analyses using the prioritizr package is provided in the 'Prioritization_butterflies.R' R script file.
DOI: 10.5061/dryad.74p77q7/4
title: Output maps from prioritization analyses

description: Zip file containing output maps depicting the final prioritized area in Sabah for range-restricted butterflies. Files include: (1) the prioritized area for all 77 butterfly species ('PrioritizedArea_AllSpecies.tif'); (2) the prioritized area for all 77 butterfly species with the inclusion of a boundary length modifier (BLM) ('PrioritizedArea_AllSpeciesBLM.tif'); (3) the prioritized area for the 15 butterfly species that are endemic to Borneo ('PrioritizedArea_EndemicSpecies.tif'); and (4) the prioritized area for the 15 endemic butterfly species with the inclusion of a BLM ('PrioritizedArea_EndemicSpecies.tif').
DOI: 10.25345/c5kd32
title: MassIVE MSV000084301 - kcat_estimation_quantitative_Proteomics
title: Label-free quantitative proteomic analysis of laboratory-evolved E. coli strains.
DOI: 10.7910/dvn/yghcrg/0dp3o7
title: MGNTFIS3.BA980LLT.DMI.1972.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/ep8pwt
title: DMI.1974.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/y2cbek
title: MGNTFIS3.VTPKYNFB.DMI.1970.TXT

description: :unav
DOI: 10.17632/n9yptvjsv7.1
title: Data for: Making Tough Choices: A Policy Capturing Approach to Evaluating the Tradeoffs in Sustainable Supplier Development Initiatives

description: Data from Studies 1 and 2 - both primary (MBA students) and executive (ISM members and Executive MBA students) data
DOI: 10.17632/vm849t6ws3.1
title: Data for: Assessing the Sustainability of High-, Middle-, and Low-Income Countries: A Network DEA Model in the Presence of both Zero Data and Undesirable Outputs

description: Data and Codes
DOI: 10.7910/dvn/yghcrg/aqyq3c
title: MGNTFIS3.CQ6C51GU.DMI.1973.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/awlxfp
title: MGNTFIS3.IXF54KAL.DMI.1971.TXT

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DOI: 10.7910/dvn/yghcrg/bnivuy
title: MGNTFIS3.EKD3YY1Z.DMI.1969.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/gmcefr
title: MGNTFIS3.LIKQ5Z2G.DMI.1974.TXT

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DOI: 10.7910/dvn/yghcrg/icywz6
title: DMI.1975.CSV

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DOI: 10.7910/dvn/yghcrg/lodbqm
title: DMI.1971.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/nyozlz
title: DMI.1970.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/uw6uu4
title: DMI.1973.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/vxlobk
title: DMI.1972.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/0dvvcu
title: DMI.1969.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/1xvh0c
title: MGNTFIS3.RZDDJHEF.DMI.1978.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/butdrz
title: MGNTFIS3.DBSUYJJE.DMI.1979.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/ev7jbx
title: DMI.1976.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/g8yquz
title: MGNTFIS3.RXMNGLZ3.DMI.1977.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/hi4nci
title: DMI.1977.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/p81sol
title: DMI.1978.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/xmomrb
title: MGNTFIS3.O1P4R13L.DMI.1975.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/18dmbh
title: DMI.1982.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/2a0nlc
title: DMI.1987.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/bozuut
title: MGNTFIS3.D9XT59OP.DMI.1985.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/fcncmk
title: DMI.1979.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/gsz0tr
title: MGNTFIS3.IALS03WT.DMI.1986.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/kwybyv
title: MGNTFIS3.NV7AHEZH.DMI.1982.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/mzpbcm
title: DMI.1988.TXT.zip

description: :unav
DOI: 10.7910/dvn/yghcrg/nrrgje
title: MGNTFIS3.K79MNWED.DMI.1976.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/q6gldj
title: MGNTFIS3.FBMPBZ6C.DMI.1983.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/suyqig
title: DMI.1986.CSV

description: :unav
DOI: 10.17632/2mpkr9hzrw.1
title: Data for: Hydrogeochemical Controls and Human Health Risk Assessment of Groundwater Fluoride and Boron in the Semi-arid Northeastern Region of Ghana

description: This data is supplementary material to our manuscript submitted to the Journal of Geochemical Exploration. It includes concentrations of hydrochemical parameters and health risk assessment.
DOI: 10.17632/8p47cj89vh.1
title: Data for: An automatic smart measurement system with signal decomposition to partition dual-source CO2 flux from maize silage
DOI: 10.7910/dvn/yghcrg/1b2qio
title: DMI.1992.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/2wbamz
title: DMI.1989.CSV.zip

description: :unav
DOI: 10.7910/dvn/yghcrg/eppnd0
title: DMI.1983.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/h1oysr
title: MGNTFIS3.X9GR27Z4.DMI.1987.TXT

description: :unav
DOI: 10.7910/dvn/yghcrg/ihgdbi
title: DMI.1985.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/jz6dbl
title: DMI.1980.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/qwveq2
title: MGNTFIS3.T7XZ29OG.DMI.1980.TXT

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DOI: 10.7910/dvn/yghcrg/wckd6e
title: DMI.1988.CSV

description: :unav
DOI: 10.7910/dvn/yghcrg/clxbuo
title: DMI.1989.TXT.zip

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DOI: 10.7910/dvn/yghcrg/lwjne5
title: DMI.1994.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/nujtfb
title: DMI.1993.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/row0ur
title: DMI.1991.TXT.zip

description: :unav
DOI: 10.7910/dvn/yghcrg/v6pcrg
title: DMI.1990.CSV.zip

description: :unav
DOI: 10.7910/dvn/yghcrg/wmfhak
title: DMI.1990.TXT.zip

description: :unav
DOI: 10.7910/dvn/yghcrg/zg1dqb
title: DMI.1991.CSV.zip

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DOI: 10.7910/dvn/yghcrg/zk4r6l
title: DMI.1992.CSV.tar

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DOI: 10.7910/dvn/yghcrg/3refrb
title: DMI.1997.TXT.tar

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DOI: 10.7910/dvn/yghcrg/byusd2
title: DMI.1997.CSV.tar

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DOI: 10.7910/dvn/yghcrg/cafinb
title: DMI.1993.CSV.tar

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DOI: 10.7910/dvn/yghcrg/jgtucm
title: DMI.1994.CSV.tar

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DOI: 10.7910/dvn/yghcrg/nprszv
title: DMI.1995.TXT.tar

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DOI: 10.7910/dvn/yghcrg/rf5lt6
title: DMI.1996.CSV.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/yguhpt
title: DMI.1998.CSV.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/zlziwn
title: DMI.1995.CSV.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/zma0jt
title: DMI.1996.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/09jxaz
title: DMI.2001.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/3u03ku
title: DMI.1998.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/bkor7v
title: DMI.1999.CSV.zip.filepart

description: :unav
DOI: 10.7910/dvn/yghcrg/cej3ea
title: DMI.1999.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/okqoy0
title: DMI.2002.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/ptxg9i
title: DMI.2000.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/w0tne7
title: DMI.2003.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/yh5r6j
title: DMI.2004.TXT.tar

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DOI: 10.17632/n4p5kpgh3w.1
title: Data for: Experimental characterization and hyperelastic constitutive modeling of open-cell elastomeric foams

description: Various experimental and model datasets for capturing the quasi-static constitutive response of three densities of Poron XRD (Rogers Corp, Rogers, CT) elastomeric polymer foam. Uniaxial, multi-modal, and inhomogeneous loading modes are included. For more details on data collection and post-processing see the relevant sections of the full paper. For additional details please contact the authors directly or via GitHub.
DOI: 10.7910/dvn/yghcrg/d8lmnf
title: DMI.2006.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/hgzzys
title: DMI.2005.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/ialcek
title: DMI.2010.TXT.tar.003

description: :unav
DOI: 10.7910/dvn/yghcrg/leinp8
title: DMI.2014.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/wqjiov
title: DMI.2010.TXT.tar.001

description: :unav
DOI: 10.7910/dvn/yghcrg/yknkrq
title: DMI.2007.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/yymjkd
title: DMI.2009.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/zj1lab
title: DMI.2008.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/zoyu94
title: DMI.2010.TXT.tar.002

description: :unav
DOI: 10.17632/rg2f35w5sk.1
title: Data for: Weather index-based insurance as a meteorological risk management alternative in viticulture
DOI: 10.7910/dvn/yghcrg/203kbj
title: DMI.2011.TXT.tar.003

description: :unav
DOI: 10.7910/dvn/yghcrg/4ufpcu
title: DMI.2017.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/8gufxg
title: DMI.2016.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/fyz1av
title: DMI.2012.TXT.tar.002

description: :unav
DOI: 10.7910/dvn/yghcrg/pfrshj
title: DMI.2012.TXT.tar.001

description: :unav
DOI: 10.7910/dvn/yghcrg/ruuih5
title: DMI.2011.TXT.tar.002

description: :unav
DOI: 10.7910/dvn/yghcrg/sivbxd
title: DMI.2012.TXT.tar.003

description: :unav
DOI: 10.7910/dvn/yghcrg/sqgshx
title: DMI.2011.TXT.tar.001

description: :unav
DOI: 10.7910/dvn/yghcrg/yvoali
title: DMI.2013.TXT.tar

description: :unav
DOI: 10.6073/pasta/8c7d60315c6513aece2b0e9b949608cc
title: PIE LTER, Year 2017-2018, locations, date, sediment concentration and spectral reflectance measurement methods of 40 water samples at Plum Island Sound and deep ocean, Massachusetts.

description: PIE LTER, Year 2017-2018, locations, date, sediment concentration and spectral reflectance measurement methods of 40 water samples at Plum Island Sound and deep ocean, Massachusetts
DOI: 10.7910/dvn/yghcrg/b6sxdx
title: DMI.2018.TXT.tar

description: :unav
DOI: 10.7910/dvn/yghcrg/dzt8m8
title: DMI.2015.TXT.tar

description: :unav
DOI: 10.5281/zenodo.3402176
title: Numerical simulations on electron wing-like structures formed at a negatively-charged spacecraft moving in a magnetized plasma

description: Numerical and observational data presented in Miyake et al. (2019): Electron wing-like structures formed at a negatively-charged spacecraft moving in a magnetized plasma. The format of the dataset is described in the PDF document (2019JA027379_supporting_information.pdf).
DOI: 10.5281/zenodo.3402177
title: Numerical simulations on electron wing-like structures formed at a negatively-charged spacecraft moving in a weakly-magnetized plasma

description: Numerical and observational data presented in Miyake et al. (2019): Electron wing-like structures formed at a negatively-charged spacecraft moving in a weakly-magnetized plasma, in review. The format of the dataset is described in the PDF document (2019JA027379_supporting_information.pdf).
DOI: 10.5281/zenodo.3401599
title: Functional connectivity in the face of congenital structural changes – a case of homozygous LAMC3 Mutation

description: Results of diffusion tensor imaging analysis for each participant. These results were summarized in a manuscript titled as " <strong>Functional connectivity in the face of congenital structural changes – a case of homozygous <em>LAMC3</em> Mutation</strong> "
DOI: 10.5281/zenodo.3401600
title: Functional connectivity in the face of congenital structural changes – a case of homozygous LAMC3 Mutation

description: Results of diffusion tensor imaging analysis for each participant. These results were summarized in a manuscript titled as " <strong>Functional connectivity in the face of congenital structural changes – a case of homozygous <em>LAMC3</em> Mutation</strong> "