cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5855512
title: Tropospheric delays and precipitable water vapor retrieved from global radiosonde observations from 2014 to 2019

description: The data consists of a set of meteorological quantities including tropospheric delays (zenith wet delay, zenith hydrostatic delay, and zenith total delay), precipitable water vapor, and surface temperature and pressure. The data is retrieved from the observations of 414 globally distributed radiosonde stations from 2014 to 2019. In addition to the geographic information of radiosonde stations, the profiles of tropospheric delays and precipitable water vapor are contained in the data file. This data has a wide range of applications, e.g., validating the tropospheric delays and precipitable water vapor derived from other techniques, investigating the spatial-temporal variations of water vapor, and acting as training data of machine learning to build tropospheric delay models. In the manuscript "Machine Learning-based Model for Real-time GNSS Precipitable Water Vapor Sensing", this data is used to train a machine learning model to map the zenith total delays to precipitable water vapor. The data is split into training data and test data, where the data from 2014 to 2018 are employed for model training, and the data of 2019 are used for testing. The developed models and the results for the manuscript are saved in the directories of Models and Results, respectively.
DOI: 10.5281/zenodo.5854311
title: Tropospheric delays and precipitable water vapor retrieved from global radiosonde observations from 2014 to 2019

description: The data consists of a set of meteorological quantities including tropospheric delays (zenith wet delay, zenith hydrostatic delay, and zenith total delay), precipitable water vapor, and surface temperature and pressure. The data is retrieved from the observations of 414 globally distributed radiosonde stations from 2014 to 2019. In addition to the geographic information of radiosonde stations, the profiles of tropospheric delays and precipitable water vapor are contained in the data file. This data has a wide range of applications, e.g., validating the tropospheric delays and precipitable water vapor derived from other techniques, investigating the spatial-temporal variations of water vapor, and acting as training data of machine learning to build tropospheric delay models. In the manuscript "Machine Learning-based Model for Real-time GNSS Precipitable Water Vapor Sensing", this data is used to train a machine learning model to map the zenith total delays to precipitable water vapor. The data is split into training data and test data, where the data from 2014 to 2018 are employed for model training, and the data of 2019 are used for testing. The developed models and the results for the manuscript are saved in the directories of Models and Results, respectively.
DOI: 10.6084/m9.figshare.18495170.v1
title: Aberration Correction: Raw Ultrasound Data and Computer Program

description: The archive contains a raw per-channel ultrasound data captured at the beamformer input of a custom scanner Sonomed-500. The data consists of the radio-frequency signals received in the phantom experiments with ATS Laboratories Model 539 and custom made aberrating layers using a 64-element phased array transducer operating at 2MHz.
DOI: 10.6084/m9.figshare.18495170
title: Aberration Correction: Raw Ultrasound Data and Computer Program

description: The archive contains a raw per-channel ultrasound data captured at the beamformer input of a custom scanner Sonomed-500. The data consists of the radio-frequency signals received in the phantom experiments with ATS Laboratories Model 539 and custom made aberrating layers using a 64-element phased array transducer operating at 2MHz.
DOI: 10.5281/zenodo.5855576
title: K7STIFFNESS

description: No
DOI: 10.5281/zenodo.5855575
title: K7STIFFNESS

description: No
DOI: 10.6084/m9.figshare.18500294
title: Ultrasound Head Phantom

description: STL files containing skull and brain models for 3D printing. The phantom is intended for transcranial ultrasound training. <br>
DOI: 10.15161/oar.it/74412
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.3558852
title: Time series of gas, particle, and environmental variables measured at the Mäkelänkatu urban street canyon site in May 2017

description: Time series data of gas, particle, and environmental variables measured at the Mäkelänkatu urban street canyon site, in Helsinki, Finland, in May 2017.
DOI: 10.5281/zenodo.3558851
title: Time series of gas, particle, and environmental variables measured at the Mäkelänkatu urban street canyon site in May 2017

description: Time series data of gas, particle, and environmental variables measured at the Mäkelänkatu urban street canyon site, in Helsinki, Finland, in May 2017.
DOI: 10.5281/zenodo.5855699
title: Dati estratti da "Epidemia COVID-19", bollettino dell'Istituto Superiore di Sanità (ISS)

description: “EPIDEMIA COVID-19” è un bollettino prodotto dall’Istituto Superiore di Sanità (ISS) che riporta i dati della sorveglianza integrata concernente l’infezione da virus SARS-CoV-2. Si legge nella nota introduttiva che “Il conteggio dei casi viene effettuato sommando tutti i casi di infezione da virus SARS-CoV2 confermati tramite test molecolari e antigenici, e segnalati al sistema di sorveglianza attraverso una piattaforma web dedicata. Il database nazionale è quindi la somma dei casi presenti nei 21 sistemi informativi regionali/PPAA costruiti ad hoc per la sorveglianza COVID-19”. Seguono altre delucidazioni. Si riportano le tabelle estratte dai rapporti, concernenti casistica su persone di età ≥ 12 anni, ricoveri e vittime. Le tabelle indicano anche lo stato vaccinale e la fascia d’età. Si presti attenzione che le classi relative alla vaccinazione sono state ridefinite a seconda dei Decreti Legge del Governo.
DOI: 10.5281/zenodo.5853823
title: Dati estratti da "Epidemia COVID-19", bollettino dell'Istituto Superiore di Sanità (ISS)

description: “EPIDEMIA COVID-19” è un bollettino prodotto dall’Istituto Superiore di Sanità (ISS) che riporta i dati della sorveglianza integrata concernente l’infezione da virus SARS-CoV-2. Si legge nella nota introduttiva che “Il conteggio dei casi viene effettuato sommando tutti i casi di infezione da virus SARS-CoV2 confermati tramite test molecolari e antigenici, e segnalati al sistema di sorveglianza attraverso una piattaforma web dedicata. Il database nazionale è quindi la somma dei casi presenti nei 21 sistemi informativi regionali/PPAA costruiti ad hoc per la sorveglianza COVID-19”. Seguono altre delucidazioni. Si riportano le tabelle estratte dai rapporti, concernenti casistica su persone di età ≥ 12 anni, ricoveri e vittime. Le tabelle indicano anche lo stato vaccinale e la fascia d’età. Si presti attenzione che le classi relative alla vaccinazione sono state ridefinite a seconda dei Decreti Legge del Governo. Si veda la nuova versione con link a documenti archiviati.
DOI: 10.5281/zenodo.5855683
title: Dati estratti da "Epidemia COVID-19", bollettino dell'Istituto Superiore di Sanità (ISS)

description: “EPIDEMIA COVID-19” è un bollettino prodotto dall’Istituto Superiore di Sanità (ISS) che riporta i dati della sorveglianza integrata concernente l’infezione da virus SARS-CoV-2. Si legge nella nota introduttiva che “Il conteggio dei casi viene effettuato sommando tutti i casi di infezione da virus SARS-CoV2 confermati tramite test molecolari e antigenici, e segnalati al sistema di sorveglianza attraverso una piattaforma web dedicata. Il database nazionale è quindi la somma dei casi presenti nei 21 sistemi informativi regionali/PPAA costruiti ad hoc per la sorveglianza COVID-19”. Seguono altre delucidazioni. Si riportano le tabelle estratte dai rapporti, concernenti casistica su persone di età ≥ 12 anni, ricoveri e vittime. Le tabelle indicano anche lo stato vaccinale e la fascia d’età. Si presti attenzione che le classi relative alla vaccinazione sono state ridefinite a seconda dei Decreti Legge del Governo. Si veda la nuova versione con link a documenti archiviati.
DOI: 10.5281/zenodo.5854324
title: Dati estratti da "Epidemia COVID-19", bollettino dell'Istituto Superiore di Sanità (ISS)

description: “EPIDEMIA COVID-19” è un bollettino prodotto dall’Istituto Superiore di Sanità (ISS) che riporta i dati della sorveglianza integrata concernente l’infezione da virus SARS-CoV-2. Si legge nella nota introduttiva che “Il conteggio dei casi viene effettuato sommando tutti i casi di infezione da virus SARS-CoV2 confermati tramite test molecolari e antigenici, e segnalati al sistema di sorveglianza attraverso una piattaforma web dedicata. Il database nazionale è quindi la somma dei casi presenti nei 21 sistemi informativi regionali/PPAA costruiti ad hoc per la sorveglianza COVID-19”. Seguono altre delucidazioni. Si riportano le tabelle estratte dai rapporti, concernenti casistica su persone di età ≥ 12 anni, ricoveri e vittime. Le tabelle indicano anche lo stato vaccinale e la fascia d’età. Si presti attenzione che le classi relative alla vaccinazione sono state ridefinite a seconda dei Decreti Legge del Governo. Si veda la nuova versione con link a documenti archiviati.
DOI: 10.6084/m9.figshare.18506450
title: Replication Package for Student Challanges Data in Team Project Course

description: Replication package consisting of student feedback regarding the challenges encountered in two consecutive iterations of a Team Projects course (2019-2020 on-site, 2020-2021 online due to pandemic-related restrictions).
DOI: 10.6084/m9.figshare.12450089
title: Single-cell RNA sequencing revealed tumor heterogeneity in multiple pathologic types of renal cell carcinoma

description: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumour heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal tumour heterogeneity, especially single-cell RNA sequencing (scRNA-seq). However, the single-cell transcriptome of RCC has been poorly reported and type 2 papillary RCC (pRCC) and chromophobe RCC (chRCC) have not been reported yet. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on four different normal kidneys, providing 23,951 single-cell transcriptome information. Tumour heterogeneity was well revealed by the comparison between different pathological types of RCC and normal kidneys at the scRNA level. Some new tumour-specific markers for different pathologic types of RCC, such as <i>SPOCK1</i>, <i>PTGIS</i>, <i>NDUFA4L2</i>, <i>REG1A</i>, <i>RHCG</i> and <i>SPAG4 </i>were identified and validated. The subtypes of different pathological types of RCC were differentiated and tumour cell subtypes that affected the prognosis in chRCC were discovered. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as <i>POSTN</i> and <i>COL3A1</i>. The activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC. Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.
DOI: 10.6084/m9.figshare.12450089.v1
title: Single-cell RNA sequencing revealed tumor heterogeneity in multiple pathologic types of renal cell carcinoma

description: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumour heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal tumour heterogeneity, especially single-cell RNA sequencing (scRNA-seq). However, the single-cell transcriptome of RCC has been poorly reported and type 2 papillary RCC (pRCC) and chromophobe RCC (chRCC) have not been reported yet. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on four different normal kidneys, providing 23,951 single-cell transcriptome information. Tumour heterogeneity was well revealed by the comparison between different pathological types of RCC and normal kidneys at the scRNA level. Some new tumour-specific markers for different pathologic types of RCC, such as <i>SPOCK1</i>, <i>PTGIS</i>, <i>NDUFA4L2</i>, <i>REG1A</i>, <i>RHCG</i> and <i>SPAG4 </i>were identified and validated. The subtypes of different pathological types of RCC were differentiated and tumour cell subtypes that affected the prognosis in chRCC were discovered. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as <i>POSTN</i> and <i>COL3A1</i>. The activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC. Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.
DOI: 10.5281/zenodo.5855808
title: Variant Forks -- Motivations and Impediments

description: Social coding platforms centred around git provide explicit facilities to share code between projects: forks, pull requests, cherry-picking to name but a few. Variant forks are an interesting phenomenon in that respect, as it permits for different projects to peacefully co-exist, yet explicitly acknowledge the common ancestry. Several researchers analysed forking practices on open source platforms and observed that variant forks get created frequently. However, today little is known on the motivations for launching such a variant fork. Is it mainly technical (e.g., diverging features), governance (e.g., diverging interests), legal (e.g., diverging licences), or do other factors come into play? In this paper we report the results of an exploratory qualitative analysis on the motivations behind variants creation and maintenance. We surveyed 105 maintainers of different active open source variant projects hosted on GitHub. Our study extends previous findings, identifying a number of fine-grained common motivations for launching a variant fork and listing concrete impediments for maintaining the co-existing projects.
DOI: 10.5281/zenodo.5855807
title: Variant Forks -- Motivations and Impediments

description: Social coding platforms centred around git provide explicit facilities to share code between projects: forks, pull requests, cherry-picking to name but a few. Variant forks are an interesting phenomenon in that respect, as it permits for different projects to peacefully co-exist, yet explicitly acknowledge the common ancestry. Several researchers analysed forking practices on open source platforms and observed that variant forks get created frequently. However, today little is known on the motivations for launching such a variant fork. Is it mainly technical (e.g., diverging features), governance (e.g., diverging interests), legal (e.g., diverging licences), or do other factors come into play? In this paper we report the results of an exploratory qualitative analysis on the motivations behind variants creation and maintenance. We surveyed 105 maintainers of different active open source variant projects hosted on GitHub. Our study extends previous findings, identifying a number of fine-grained common motivations for launching a variant fork and listing concrete impediments for maintaining the co-existing projects.
DOI: 10.6084/m9.figshare.17209613.v4
title: Appraising the effect of potential risk factors on thyroid cancer: A Mendelian randomization study

description: Appraising the effect of potential risk factors on thyroid cancer: A Mendelian randomization study
DOI: 10.6084/m9.figshare.17209613.v5
title: Appraising the effect of potential risk factors on thyroid cancer: A Mendelian randomization study

description: Appraising the effect of potential risk factors on thyroid cancer: A Mendelian randomization study
DOI: 10.34740/kaggle/dsv/3049087
title: Formula One Cars
DOI: 10.6084/m9.figshare.13435913
title: Ribeira Houses Shrubs 16:52 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.
DOI: 10.6084/m9.figshare.13435760
title: Ribeira Houses Concrete 16:05 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.
DOI: 10.6084/m9.figshare.13435826
title: Ribeira Houses Concrete 16:11 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.
DOI: 10.6084/m9.figshare.13435736
title: Ribeira Hotel 15:05 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.
DOI: 10.6084/m9.figshare.13435850
title: Ribeira Houses Shrubs 16:49 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.
DOI: 10.6084/m9.figshare.13434338
title: Tibães Corridor 16:05 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.
DOI: 10.6084/m9.figshare.13434359
title: Tibães Corridor 16:10 - Hyperspectral Radiance Image

description: Hyperspectral radiance data. The zipped file contains an unaveraged hyperspectral radiance image in Matlab MAT format, size 1024 × 1344 × 33, and spectral radiance in W m<sup>−2</sup> sr<sup>−1</sup> nm<sup>−1</sup>. The image is one of a pair of images acquired at different times. The zipped file also contains a BMP colour image, rendered from the radiance image, and an information document, which includes geographic location. The separate JPG image of the scene is for illustration only. Padding artefacts may be visible at the image edges. The hyperspectral images were acquired by Sérgio Nascimento, Kinjiro Amano, and David Foster from the Minho region of Portugal in 2002 and 2003.<br>This data item is part of a collection. For details see the data item "README Hyperspectral radiance image pairs 2021" and the published article https://rdcu.be/cd15y.