cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21739703
title: Supplementary Material for: Artifacts Can Be Deceiving: The Actual Location of Deep Brain Stimulation Electrodes Differs from the Artifact Seen on Magnetic Resonance Images

description: <b><i>Introduction:</i></b> Deep brain stimulation (DBS) is a common treatment for a variety of neurological and psychiatric disorders. Recent studies have highlighted the role of neuroimaging in localizing the position of electrode contacts relative to target brain areas in order to optimize DBS programming. Among different imaging methods, postoperative magnetic resonance imaging (MRI) has been widely used for DBS electrode localization; however, the geometrical distortion induced by the lead limits its accuracy. In this work, we investigated to what degree the difference between the actual location of the lead’s tip and the location of the tip estimated from the MRI artifact varies depending on the MRI sequence parameters such as acquisition plane and phase encoding direction, as well as the lead’s extracranial configuration. Accordingly, an imaging technique to increase the accuracy of lead localization was devised and discussed. <b><i>Methods:</i></b> We designed and constructed an anthropomorphic phantom with an implanted DBS system following 18 clinically relevant configurations. The phantom was scanned at a Siemens 1.5 Tesla Aera scanner using a T<sub>1</sub>MPRAGE sequence optimized for clinical use and a T<sub>1</sub>TSE sequence optimized for research purposes. We varied slice acquisition plane and phase encoding direction and calculated the distance between the caudal tip of the DBS lead MRI artifact and the actual tip of the lead, as estimated from MRI reference markers. <b><i>Results:</i></b> Imaging parameters and lead configuration substantially altered the difference in the depth of the lead within its MRI artifact on the scale of several millimeters − with a difference as large as 4.99 mm. The actual tip of the DBS lead was found to be consistently more rostral than the tip estimated from the MR image artifact. The smallest difference between the tip of the DBS lead and the tip of the MRI artifact using the clinically relevant sequence (i.e., T<sub>1</sub>MPRAGE) was found with the sagittal acquisition plane and anterior-posterior phase encoding direction. <b><i>Discussion/Conclusion:</i></b> The actual tip of an implanted DBS lead is located up to several millimeters rostral to the tip of the lead’s artifact on postoperative MR images. This distance depends on the MRI sequence parameters and the DBS system’s extracranial trajectory. MRI parameters may be altered to improve this localization.
DOI: 10.6084/m9.figshare.21739892
title: Supplementary Material for: First Report of Mexican Patients with <b><i>PACS1</i></b>-Related Neurodevelopmental Disorder and Review of the <b><i>PACS1</i></b>-, <b><i>PACS2</i></b>-, and <b><i>WDR37</i></b>-Related Ophthalmological Manifestations

description: <b><i>Introduction:</i></b> <i>PACS1</i>-related neurodevelopmental disorder (<i>PACS1-</i>related NDD) is caused by pathogenic variants in the <i>PACS1</i> gene and is characterized by a distinctive facial appearance, intellectual disability, speech delay, seizures, feeding difficulties, cryptorchidism, hernias, and structural anomalies of the brain, heart, eye, and kidney. There is a marked facial resemblance and a common multisystem affectation with patients carrying pathogenic variants in the <i>WDR37</i> and <i>PACS2</i> genes, although they vary in terms of severity and eye involvement. <b><i>Case Presentation:</i></b> Here, we describe 4 individuals with <i>PACS1</i>-related NDD from Mexico, all of them carrying a de novo <i>PACS1</i> variant c.607C&gt;T; p.(Arg203Trp) identified by exome sequencing. In addition to eye colobomata, this report identified corneal leukoma, cataracts, and tortuosity of retinal vessels as ophthalmic manifestations not previously reported in patients with <i>PACS1</i>-related NDD. <b><i>Discussion:</i></b> We reviewed the ocular phenotypes reported in 74 individuals with <i>PACS1</i>-related NDD and the overlaps with <i>WDR37-</i> and <i>PACS2</i>-related syndromes. We found that the 3 syndromes have in common the presence of colobomata, ptosis, nystagmus, strabismus, and refractive errors, whereas microphthalmia, microcornea, and Peters anomaly are found only among individuals with <i>PACS1</i>-related NDD and <i>WDR37</i> syndrome, being more severe in the latter. This supports the previous statement that the so-called <i>WDR37</i>-<i>PACS1</i>-<i>PACS2</i> axis might have an important role in ocular development and also that the specific ocular findings could be useful in the clinical differentiation between these related syndromes.
DOI: 10.17632/54p84dj5jj.1
title: Eastern Greater Caucasus Thermochronometry

description: These are the data files for eastern Greater Caucasus thermochronometry, as described in the manuscript: Tye, A. R., Niemi, N. A., Cowgill, E., Kadirov, F. A., and Babayev, G. R. Diverse deformation mechanisms and lithologic controls in an active orogenic wedge: Structural geology and thermochronometry of the eastern Greater Caucasus. Tectonics (in revision).

The data include apatite and zircon (U-Th-Sm)/He age data, apatite fission track count data, and apatite fission track length data from samples collected throughout the eastern Greater Caucasus.
DOI: 10.20387/bonares-qzck-n54v
title: Soil values from the agricultural soil valuation for Brandenburg
DOI: 10.25345/c5w950s0w
title: MassIVE MSV000089159 - nPOP Droplet sample preparation v3.
title: Single cell proteomic analysis of Monocyte and Melanoma cancer cell lines
DOI: 10.5281/zenodo.6654670
title: Gaseous elementary mercury and other air pollutants data during COVID-19

description: This dataset contains gaseous elementary mercury, particulate ions, organics, and trace metals, and meteorological parameters measured at the Dianshan Lake site in Shanghai during the 2020 COVID-19 period.
DOI: 10.5281/zenodo.7090887
title: Datasets for ``Dissipative magnetic structures and scales in small-scale dynamos''

description: <pre>This directory contains an index.html file with links to the run directories and idl plotting routines with secondary data for the other figures for the paper "Dissipative magnetic structures and scales in small-scale dynamos" by A. Brandenburg, I. Rogachevskii, and J. Schober. If anything turns out to be incomplete, please email brandenb@nordita.org. </pre>
DOI: 10.17188/1195334
title: Materials Data on CeO2 by Materials Project

description: CeO2 is Fluorite structured and crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. Ce4+ is bonded in a body-centered cubic geometry to eight equivalent O2- atoms. All Ce–O bond lengths are 2.37 Å. O2- is bonded to four equivalent Ce4+ atoms to form a mixture of edge and corner-sharing OCe4 tetrahedra.
DOI: 10.17632/wsfrgbd5t8.3
title: Eddy Covariance measurements over the Gulf of Eilat (Aqaba) fringing coral reef

description: eddy covariance measurement and micro-meteorological parameters over the gulf of Eilat reef during the 13/09/2020-07/10/2020 and 01/07/2021-31/08-2021 at the Interuniversity Institute for Marine Research (IUI).
DOI: 10.5281/zenodo.5058620
title: Daily precipitation and temperature for 2021–2050 over China: multiple RCMs and emission scenarios corrected by a trend-preserving method

description: The datasets with spatial resolution of 0.5˚×0.5˚ were corrected from CORDEX-EA regional climate models based on a trend–preserving bias correction method, including daily daily maximum and minimum temperature, and precipitation (Tmax, Tmin and Pre). The datasets cover the main land area of China and two periods, the historical period (from 1980 to 2005 ) and future period (from 2021 to 2050). The observations used in the correction were obtained from China Meteorological Administration (http://cdc.cma.gov.cn), and were derived from 2472 weather stations over China. The evaluation indicated that the corrected datasets are reliable for the investigations related to climate change across China.
DOI: 10.5281/zenodo.53169
title: Collection Of Textures In Colorectal Cancer Histology

description: <strong>Content</strong>

This data set represents a collection of textures in histological images of human colorectal cancer. It contains two files:


	"Kather_texture_2016_image_tiles_5000.zip": a zipped folder containing 5000 histological images of 150 * 150 px each (74 * 74 µm). Each image belongs to exactly one of eight tissue categories (specified by the folder name). 
	"Kather_texture_2016_larger_images_10.zip": a zipped folder containing 10 larger histological images of 5000 x 5000 px each. These images contain more than one tissue type. 


<strong>Image format</strong>

All images are RGB, 0.495 µm per pixel, digitized with an Aperio ScanScope (Aperio/Leica biosystems), magnification 20x. Histological samples are fully anonymized images of formalin-fixed paraffin-embedded human colorectal adenocarcinomas (primary tumors) from our pathology archive (Institute of Pathology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany).

<strong>Ethics statement</strong>

All experiments were approved by the institutional ethics board (medical ethics board II, University Medical Center Mannheim, Heidelberg University, Germany; approval 2015-868R-MA). The institutional ethics board waived the need for informed consent for this retrospective analysis of anonymized samples. All experiments were carried out in accordance with the approved guidelines and with the Declaration of Helsinki.

<strong>More information / data usage</strong>

For more information, please refer to the following article. <strong>Please cite this article when using the data set.</strong>

Kather JN, Weis CA, Bianconi F, Melchers SM, Schad LR, Gaiser T, Marx A, Zollner F: Multi-class texture analysis in colorectal cancer histology (2016), Scientific Reports (in press)

<strong>Contact</strong>

For questions, please contact:<br>
Dr. Jakob Nikolas Kather<br>
http://orcid.org/0000-0002-3730-5348<br>
ResearcherID: D-4279-2015
DOI: 10.5281/zenodo.6578575
title: CRM Variance Transport validation in E3SM-MMF - analysis code and condensed data

description: This tarball contains a collection of code and data used to performa a detailed analysis of the CRM variance transport feature added to E3SM-MMF. The data subset is condensed from the model output and observational datasets, so the ability to reproduce results directly is limited, but this archive mainly serves to document the methods used for our analysis.
DOI: 10.5281/zenodo.7142392
title: supplementary-material-for-egusphere-2022-1032

description: This repository contains the codes and data necessary to reproduce the results of the following manuscript: Title: Detection of slow changes in terrestrial water storage with GRACE and GRACE-FO satellite gravity missions<br> Author(s): Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, and Anne Barnoud<br> MS No.: egusphere-2022-1032<br> MS type: Research article<br> Iteration: Initial submission The codes require a working installation of python3 with the following packages installed: numpy, scipy, matplotlib, netCDF4, astropy, geopandas, datetime and basemap. Once a working environment is installed, the user may simply run the python script in the same directory as the data, shapefiles and Figures directory. The data include the fully processed datasets, as described in the section 2 of the manuscript, including: - 9 GRACE solutions (JPL mascon, CSR mascon, GSFC mascon, JPL spherical harmonics, CSR spherical harmonics, GFZ spherical harmonics, ITSG spherical harmonics, COST-G spherical harmonics, CNES-GRGS spherical harmonics), - 2 global hydrological models (ISBA-CTRIP and WGHM) ,and, - a correction for lake water storage changes based on the hydroweb database. The detailed processing is described in the section 2 of manuscript. All datasets have been monthly averaged, interpolated on aregular 1 degree grid using a conservative algorithm, seasonal signals (modeled as the sum of an annual and a semi-annual sinusoids) have been removed and an isotropic diffusive filter has been applied at 250 km. Users interested intermediate processing steps will find a Python implementation of the diffusion filter in open access at https://github.com/ogoux/diffusion_filter.
DOI: 10.5281/zenodo.7336311
title: Multi-region sequencing with spatial information enables accurate heterogeneity estimation and risk stratification in liver cancer

description: We performed multi-region sampling and sequencing on 14 patients with HCC, collecting a total of 75 tumor samples with spatial information and molecular data. In addition, 21 matched adjacent liver samples were also collected. All samples were subjected to RNA sequencing (RNA-seq). RNA sequencing was performed on Illumina NovaSeq 6000 platform with 40M pair-end 150bp reads per sample. Whole-exome sequencing (WES) was performed on 36 samples from patients T10, T13 and T18 (n = 26) as well as adjacent non-tumor tissues (n = 10). Paired end, 150bp read-length sequencing was then performed on Illumina NovaSeq 6000 platform with a mean sequencing coverage of 100X. Raw sequencing data has been deposited at the National Omics Data Encyclopedia (NODE) under the accession code OEP002956 ( http://www.biosino.org/node/project/detail/OEP002956).
DOI: 10.7265/p9yk-6m11
title: Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 1
DOI: 10.5281/zenodo.4679175
title: Arca - Evaluation

description: Dataset of Arca evaluation.
DOI: 10.17632/wnk2wt8fv7.1
title: Pure Shift Quantification - NMR Datasets

description: NMR data sets from the article: "Absolute Metabolite Quantification Using Pure Shift NMR: Towards Quantitative Metabolic Profiling of Aqueous Biological Samples"
Including: Reference Library spectra (14 metabolites in 7 dilutions), Model Mixtures (mixture of 14 metabolites in 6 dilutions), Biological samples for quantitative applications (Cell culture medium, Extracellular media from DLBCL cancer cells).
DOI: 10.17632/zchmzmkbmf.2
title: Amelioration of hepatic steatosis by dietary essential amino acid-induced ubiquitination, Zhang et al., 2021

description: Dataset statistical analyses, unprocessed blots and unprocessed gels.
DOI: 10.6084/m9.figshare.21641300.v3
title: Young Hoon Soong & Chung, E-S. Monthly potential evapotranspiration dataset based on CMIP6 GCM. Figshare,

description: Regridding Global CMIP6 GCMs datasets <br> https://drive.google.com/drive/folders/1PVjq6elvyKpyg2ekz_k0rvqzX2Kk_qrD?usp=share_link
DOI: 10.6084/m9.figshare.13140371
title: Arctic COSMO-CLM hindcast 2004

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13140371.v6
title: Arctic COSMO-CLM hindcast 2004

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13140371.v5
title: Arctic COSMO-CLM hindcast 2004

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.5281/zenodo.7450884
title: Thaliaceans data in the global ocean and the South China Sea

description: This dataset contains two sheets, one is the global presence-absence records of some typical thaliacean species with environmental data and the other one is the abundance of thaliaceans with environmental data in the South China Sea.
DOI: 10.5281/zenodo.7450883
title: Thaliaceans data in the global ocean and the South China Sea

description: This dataset contains two sheets, one is the global presence-absence records of some typical thaliacean species with environmental data and the other one is the abundance of thaliaceans with environmental data in the South China Sea.
DOI: 10.34740/kaggle/dsv/4735362
title: Elon Musk Tweets
DOI: 10.5281/zenodo.5748142
title: InPhyT/COVID19-Italy-Integrated-Surveillance-Data: v1.0.0

description: COVID-19 integrated surveillance data provided by the Italian Institute of Health and processed via UnrollingAverages.jl to deconvolve the weekly moving averages.
description: {"references": ["Pietro Monticone, Claudio Moroni, UnrollingAverages.jl (2021) https://doi.org/10.5281/zenodo.5725301", "Tom Breloff, Plots.jl (2021) https://doi.org/10.5281/zenodo.5747251"]}
DOI: 10.5281/zenodo.6401328
title: InPhyT/COVID19-Italy-Integrated-Surveillance-Data: v18.0.0

description: COVID-19 integrated surveillance data provided by the Italian Institute of Health and processed via UnrollingAverages.jl to deconvolve the weekly moving averages.
DOI: 10.5281/zenodo.7191926
title: InPhyT/COVID19-Italy-Integrated-Surveillance-Data: v39.0.0

description: Data updated as of 2022-10-12
DOI: 10.5281/zenodo.7226712
title: InPhyT/COVID19-Italy-Integrated-Surveillance-Data: v40.0.0

description: Data updated as of 2022-10-19
DOI: 10.5281/zenodo.7255810
title: InPhyT/COVID19-Italy-Integrated-Surveillance-Data: v41.0.0

description: Data updated as of 2022-10-26
DOI: 10.5281/zenodo.7275192
title: Italian COVID-19 Integrated Surveillance Dataset (v42.0.0)

description: <strong>Abstract</strong> COVID-19 integrated surveillance data provided by the Italian National Institute of Health and processed via UnrollingAverages.jl to deconvolve the weekly simple moving averages. <strong>Overview</strong> Every week the National Institute for Nuclear Physics (INFN) imports an anonymous individual-level dataset from the Italian National Institute of Health (ISS) and converts it into an incidence time series data organized by date of event and disaggregated by sex, age and administrative level with a consolidation period of approximately two weeks. The information available to the INFN is summarised in the following meta-table. <strong>Output Data </strong> The output data has been stored here and contain the following information: Reconstructed daily time series of <strong>confirmed cases by date of diagnosis</strong> stratified by sex and age at the regional level; Reconstructed daily time series of <strong>symptomatic cases by date of symptoms onset</strong> stratified by sex and age at the regional level; Reconstructed daily time series of <strong>ordinary hospital admissions</strong> by date of admission stratified by sex and age at the regional level; Reconstructed daily time series of <strong>intensive hospital admissions</strong> by date of admission stratified by sex and age at the regional level; Reconstructed daily time series of <strong>deceased cases by date of death</strong> stratified by sex and age at the regional level.
DOI: 10.5281/zenodo.7451195
title: Data used in the paper: Heatwaves, droughts, and fires: Exploring compound and cascading dry T hazards at the pan-European scale

description: These datasets were used to analyze European compound and cascading dry hazards. The scripts are publicly available on GitHub: https://github.com/sjsutanto/Dryhazards.git. File Daily_SM_drought_WB_Converted.nc is for soil moisture drought, fwi_1990_2016_binary_95th_lowThreshold.nc is for wildfires, and datacube_2mtpp_19902016_HW.nc is for heatwaves.
DOI: 10.5281/zenodo.7451196
title: Data used in the paper: Heatwaves, droughts, and fires: Exploring compound and cascading dry T hazards at the pan-European scale

description: These datasets were used to analyze European compound and cascading dry hazards. The scripts are publicly available on GitHub: https://github.com/sjsutanto/Dryhazards.git. File Daily_SM_drought_WB_Converted.nc is for soil moisture drought, fwi_1990_2016_binary_95th_lowThreshold.nc is for wildfires, and datacube_2mtpp_19902016_HW.nc is for heatwaves.
DOI: 10.6084/m9.figshare.13148069
title: Arctic COSMO-CLM hindcast 2005

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13148069.v5
title: Arctic COSMO-CLM hindcast 2005

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13148069.v4
title: Arctic COSMO-CLM hindcast 2005

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.5281/zenodo.5748141
title: Italian COVID-19 Integrated Surveillance Dataset (v42.0.0)

description: <strong>Abstract</strong> COVID-19 integrated surveillance data provided by the Italian National Institute of Health and processed via UnrollingAverages.jl to deconvolve the weekly simple moving averages. <strong>Overview</strong> Every week the National Institute for Nuclear Physics (INFN) imports an anonymous individual-level dataset from the Italian National Institute of Health (ISS) and converts it into an incidence time series data organized by date of event and disaggregated by sex, age and administrative level with a consolidation period of approximately two weeks. The information available to the INFN is summarised in the following meta-table. <strong>Output Data </strong> The output data has been stored here and contain the following information: Reconstructed daily time series of <strong>confirmed cases by date of diagnosis</strong> stratified by sex and age at the regional level; Reconstructed daily time series of <strong>symptomatic cases by date of symptoms onset</strong> stratified by sex and age at the regional level; Reconstructed daily time series of <strong>ordinary hospital admissions</strong> by date of admission stratified by sex and age at the regional level; Reconstructed daily time series of <strong>intensive hospital admissions</strong> by date of admission stratified by sex and age at the regional level; Reconstructed daily time series of <strong>deceased cases by date of death</strong> stratified by sex and age at the regional level.
DOI: 10.5281/zenodo.7451316
title: Overview of drift rights for eight Icelandic counties according to Jarðabók Árna Magnússonar og Páls Vídalíns

description: Overview of information on drift rights for the historical Icelandic counties of Borgarfjarðarsýsla, Strandasýsla, Ísafjarðarsýsla, Skagafjarðarsýsla, Eyjafjarðarsýsla, Norður-Þingeyjarsýsla, Snæfellsnessýsla, and Rangárvallasýsla according to the 18th century land register <em>Jarðabók Árna Magnússonar og Páls Vídalíns.</em>
DOI: 10.5281/zenodo.7451315
title: Overview of drift rights for eight Icelandic counties according to Jarðabók Árna Magnússonar og Páls Vídalíns

description: Overview of information on drift rights for the historical Icelandic counties of Borgarfjarðarsýsla, Strandasýsla, Ísafjarðarsýsla, Skagafjarðarsýsla, Eyjafjarðarsýsla, Norður-Þingeyjarsýsla, Snæfellsnessýsla, and Rangárvallasýsla according to the 18th century land register <em>Jarðabók Árna Magnússonar og Páls Vídalíns.</em>
DOI: 10.34740/kaggle/dsv/4735438
title: Flowering Stage-Grape quality prediction
DOI: 10.34740/kaggle/dsv/4735466
title: Growing Stage-Grape quality prediction
DOI: 10.34740/kaggle/dsv/4735472
title: Harvesting Stage-Grape quality prediction
DOI: 10.34740/kaggle/dsv/4735482
title: YouTube Daily
DOI: 10.34740/kaggle/dsv/4735503
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.18716/nmrshiftdb2/20054811
title: NMR data for 2-oxo-1,3-dihydroindole-5-carbonitrile
DOI: 10.18716/nmrshiftdb2/20054812
title: NMR data for 2-methylisoquinolin-1-one
DOI: 10.18716/nmrshiftdb2/20054816
title: NMR data for InChI=1S/C11H15NO/c1-8-6-10-4-3-5-11(13)12(10)7-9(8)2/h7,10H,1,3-6H2,2H3
DOI: 10.18716/nmrshiftdb2/20054813
title: NMR data for InChI=1S/C7H9NO/c9-7-4-5-2-1-3-6(5)8-7/h1-2,5-6H,3-4H2,(H,8,9)
DOI: 10.18716/nmrshiftdb2/20054814
title: NMR data for InChI=1S/C11H15NO3/c1-12-10(14)8-4-2-3-7(5-6-13)9(8)11(12)15/h2-3,7-9,13H,4-6H2,1H3
DOI: 10.18716/nmrshiftdb2/20054817
title: NMR data for 2-methyl-3,4-dihydroisoquinolin-1-one
DOI: 10.18716/nmrshiftdb2/20054819
title: NMR data for (5E)-5-ethylidene-2,3-dihydro-1H-cyclopenta[b]pyridin-4-one
DOI: 10.18716/nmrshiftdb2/20054818
title: NMR data for InChI=1S/C10H11NO/c1-7-6-8-4-2-3-5-9(8)11-10(7)12/h2-5,7H,6H2,1H3,(H,11,12)
DOI: 10.18716/nmrshiftdb2/20054820
title: NMR data for 5-chloro-1,3-dihydroindol-2-one
DOI: 10.18716/nmrshiftdb2/20054815
title: NMR data for InChI=1S/C11H17N/c1-8-4-5-10-9(2)6-12(3)7-11(8)10/h4,9H,5-7H2,1-3H3