cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14535678.v1
title: Data Congress CL.xlsx

description: Data used to account for the effect of social movements and their legislative allies on the passage of amendments in Chile.
DOI: 10.5281/zenodo.4737398
title: The NGI Forward semantic social network data

description: The NGI Forward project is part of the European Union's Next Generation Internet Initiative. It is meant to provide European institutions with policy advice for how to shape the future, human-centric Internet. As part of it, a team of ethnographers coded a specially convened online conversation, then arranged its results into a semantic social network. This dataset encodes that conversation, as well as the results of the coding exercise, in raw data form for further exploration and replication purposes. The dataset is pseudonymized. Funnel website of the project. About semantic social networks. Data export and documentation process (contains links to the code used to export the data)
description: Revised after the Masters of Networks hackathon. Added some fields and regenerated the datapackage.json
DOI: 10.5281/zenodo.4733828
title: Texture Synthesis comparison of methods and results of the perceptual test

description: <strong>Description :</strong> The zip folder contains the 20 reference images of resolution 1024*1024 with the synthesis obtained by different methods.<br> Those 20 references images (in the folder named References) are the one used for the perceptual test.<br> The synthesis are in the folder corresponding to the name of the reference images. The DisplacementMaps folder contains the displacement maps for the different methods we compared in the main file. <strong>Nomemclature :</strong><br> Each synthesis is followed by a postfix that refers to a given methods as follows :<br> - DCor : Deep Corr Sendick et al. 2017<br> - EfrosFreeman : Efros et al. 2001<br> - EfrosLeung : Efros et al. 1999<br> - autocorr : Autocorrelation [Our]<br> - MSInit : Our Multi resolution strategy [Our]<br> - Gatys : Gatys et al. 2015<br> - spectrumTFabs_eps10m16 : use of a spectrum constraints (Liu et al. 2016)<br> - Ulyanov : ulyanov et al. 2016<br> - _Snelgorove_MultiScale_o5_l3_8_psame : Snelgrove 2017 <strong>Our method :</strong> Our methods are defined in the following research paper : "High resolution neural texture synthesis with long range constraints Gonthier et al. 2020" https://arxiv.org/abs/2008.01808 We introduce a simple multi-resolution framework that efficiently accounts for long-range dependency. Then, we show that additional statistical constraints further improve the reproduction of textures with strong regularity. This can be achieved by constraining both the Gram matrices of a neural network and the power spectrum of the image. Alternatively one may constrain only the autocorrelation of the features of the network and drop the Gram matrices constraints. <br> <strong>Perceptual Test : </strong> <br> The three csv files contains the results of the perceptual test conducted during our study to compared the differents methods. The files are named Number_of_wins_both.csv, Number_of_wins_local.csv and Number_of_wins_global.csv. <br>
description: This research was supported in part by the "IDI 2017" project funded by the IDEX Paris-Saclay, ANR-11-IDEX-0003-02.
description: {"references": ["Gonthier, Gousseau et al. (2020) HIGH RESOLUTION NEURAL TEXTURE SYNTHESIS WITH LONGRANGE CONSTRAINTS arXiv:2008.01808"]}
DOI: 10.5281/zenodo.4733827
title: Texture Synthesis comparison of methods and results of the perceptual test

description: <strong>Description :</strong> The zip folder contains the 20 reference images of resolution 1024*1024 with the synthesis obtained by different methods.<br> Those 20 references images (in the folder named References) are the one used for the perceptual test.<br> The synthesis are in the folder corresponding to the name of the reference images. The DisplacementMaps folder contains the displacement maps for the different methods we compared in the main file. <strong>Nomemclature :</strong><br> Each synthesis is followed by a postfix that refers to a given methods as follows :<br> - DCor : Deep Corr Sendick et al. 2017<br> - EfrosFreeman : Efros et al. 2001<br> - EfrosLeung : Efros et al. 1999<br> - autocorr : Autocorrelation [Our]<br> - MSInit : Our Multi resolution strategy [Our]<br> - Gatys : Gatys et al. 2015<br> - spectrumTFabs_eps10m16 : use of a spectrum constraints (Liu et al. 2016)<br> - Ulyanov : ulyanov et al. 2016<br> - _Snelgorove_MultiScale_o5_l3_8_psame : Snelgrove 2017 <strong>Our method :</strong> Our methods are defined in the following research paper : "High resolution neural texture synthesis with long range constraints Gonthier et al. 2020" https://arxiv.org/abs/2008.01808 We introduce a simple multi-resolution framework that efficiently accounts for long-range dependency. Then, we show that additional statistical constraints further improve the reproduction of textures with strong regularity. This can be achieved by constraining both the Gram matrices of a neural network and the power spectrum of the image. Alternatively one may constrain only the autocorrelation of the features of the network and drop the Gram matrices constraints. <br> <strong>Perceptual Test : </strong> <br> The three csv files contains the results of the perceptual test conducted during our study to compared the differents methods. The files are named Number_of_wins_both.csv, Number_of_wins_local.csv and Number_of_wins_global.csv. <br>
description: This research was supported in part by the "IDI 2017" project funded by the IDEX Paris-Saclay, ANR-11-IDEX-0003-02.
description: {"references": ["Gonthier, Gousseau et al. (2020) HIGH RESOLUTION NEURAL TEXTURE SYNTHESIS WITH LONGRANGE CONSTRAINTS arXiv:2008.01808"]}
DOI: 10.5523/bris.356boayld729v2snyncfoltt0w
title: Data from minimal gene set whole-cell modelling
title: Testing theoretical minimal genomes using whole-cell models

description: The minimal gene set for life has often been theorised, with at least ten produced for Mycoplasma genitalium (M. genitalium). Due to the difficulty of using M. genitalium in the lab, combined with its long replication time of 12 - 15 hours, none of these theoretical minimal genomes have been tested, even with modern techniques. The publication of the M. genitalium whole-cell model provided the first opportunity to test them, simulating the genome edits in-silico. We simulated minimal gene sets from the literature, finding that they produced in-silico cells that did not divide. Using knowledge from previous research, we reintroduced specific essential and low essential genes in-silico; enabling cellular division. This reinforces the need to identify species-specific low essential genes and their interactions. Any genome designs created using the currently incomplete and fragmented gene essentiality information, will very likely require in-vivo reintroductions to correct issues and produce dividing cells.
DOI: 10.48531/jbru.calmip/19xgry/c3yy31
title: Datapaper_collaborative_28_04_2021.pdf

description: :unav
DOI: 10.48531/jbru.calmip/19xgry/pp9qkr
title: Datapaper_collaborative_28_04_2021_1.pdf

description: :unav
DOI: 10.48531/jbru.calmip/19xgry/vbs4dk
title: Datapaper_collaborative_28_04_2021.pdf

description: :unav
DOI: 10.48531/jbru.calmip/19xgry
title: Datapaper - Aerodynamic performance in transonic regime around an A320 airfoil by means of electroactive morphing through vibration and slight deformation of the near-trailing edge region at high Reynolds number

description: The present article has been elaborated in the context of the Foundation’s STAE (http://www.fondation-stae.net/) -RTRA platform DATANOOS: “From Data to noosphere”, coordinated by IRIT, (Institut de recherché en Informatique de Toulouse, Michelle Sibilla Nathalie Aussenac). In this context, the present Datapaper has been prepared within the Use-Case DATANOOS-UC1, “Modélisation enrichie et intelligente de données Avion” coordinated by Marianna Braza, on the basis of INPT/IMFT’s data generated in the H2020 European research project N° 723402: SMS, “Smart Morphing and Sensing for aeronautical configurations”, www.smartwing.org/SMS/EU in collaboration with the CALMIP, (T. Louge) who launched the CALLISTO Interface for a Semantic Toolbox Online: https://callisto.calmip.univ-toulouse.fr/ This collaborative study offers access, interoperability and reuse of these data in the context of Open / FAIR research data in Horizon 2020. The present article studies through appropriate vibration and deformation of the near trailing edge region of a supercritical A320-type morphing airfoil the physical mechanisms related the aerodynamic performance modification, e.g. the change in the lift and drag coefficients due to modification of the near wake’s turbulence structure and of the shock-boundary layer interaction. The upstream Mach number is 0.78 and the wing is placed at an incidence of 1.8°, both parameters corresponding to nominal cruise operating conditions. The airfoil’s chord measures 15 cm, corresponding to the so-called tRS, “transonic Reduced Scale“ prototype of the H2020 N° 723402 SMS project “Smart Morphing and Sensing for aeronautical configurations”, www.smartwing.org/SMS/EU, coordinated by IMFT/INPT, the experiments of which have accomplished in the transonic wind tunnel of the IMP-PAN Institute at Gdansk, co-partner of the SMS project. The computations have been carried out in the Olympe supercomputer of the CALMIP Centre with the use of the Navier Stokes MultiBlock (NSMB) code of the European Consortium. The near trailing edge region of the airfoil is made to vibrate at different frequencies in the 700 Hz to 780 Hz range. This actuation is performed by the use of Macro Fiber Composite (MFC) type piezoactuators, operating at low deformation amplitudes (in the order of 0.5 mm).
DOI: 10.5281/zenodo.4737418
title: Supplemental Material: Page Length Calculations for BMJ EBM Manuscirpt on COVID-19 Vaccine Transparency

description: Supplemental Material: Page Length Calculations for COVID-19 Vaccine Transparency Manuscript
DOI: 10.5281/zenodo.4737434
title: High Resolution Texture Synthesis

description: <strong>Description :</strong> The References2048 folder contains the 14 reference images of resolution 2048*2048 whereas the other folder contains the synthesis obtained with different methods. <br> <strong>Nomemclature :</strong><br> Each synthesis is followed by a postfix that refers to a given methods as follows :<br> - MSInit : Our Multi resolution strategy [Our]<br> - Gatys : Gatys et al. 2015<br> - spectrumTFabs_eps10m16 : use of a spectrum constraints (Liu et al. 2016) Our methods are defined in the following research paper : "High resolution neural texture synthesis with long range constraints Gonthier et al. 2020" https://arxiv.org/abs/2008.01808 These images can be used to compare methods.
description: This research was supported in part by the "IDI 2017" project funded by the IDEX Paris-Saclay, ANR-11-IDEX-0003-02.
description: {"references": ["Gonthier et al. 2020 High resolution neural texture synthesis with long range constraints arXiv:2008.01808"]}
DOI: 10.5281/zenodo.4737433
title: High Resolution Texture Synthesis

description: <strong>Description :</strong> The References2048 folder contains the 14 reference images of resolution 2048*2048 whereas the other folder contains the synthesis obtained with different methods. <br> <strong>Nomemclature :</strong><br> Each synthesis is followed by a postfix that refers to a given methods as follows :<br> - MSInit : Our Multi resolution strategy [Our]<br> - Gatys : Gatys et al. 2015<br> - spectrumTFabs_eps10m16 : use of a spectrum constraints (Liu et al. 2016) Our methods are defined in the following research paper : "High resolution neural texture synthesis with long range constraints Gonthier et al. 2020" https://arxiv.org/abs/2008.01808 These images can be used to compare methods.
description: This research was supported in part by the "IDI 2017" project funded by the IDEX Paris-Saclay, ANR-11-IDEX-0003-02.
description: {"references": ["Gonthier et al. 2020 High resolution neural texture synthesis with long range constraints arXiv:2008.01808"]}
DOI: 10.7303/syn25671239.1
title: ModelAD-icon.e37944bf.svg
DOI: 10.5281/zenodo.4737062
title: IconArt Dataset

description: The dataset IconArt dataset was introduced in the following paper : "Weakly Supervised Object Detection in Artworks" Gonthier et al. ECCV 2018 Workshop Computer Vision for Art Analysis - VISART 2018. You can also find project page for the paper here. This dataset contains 5955 images (from WikiCommons) : a train set of 2978 images and a test set of 2977 images (for classification task). 1480 of the 2977 images are annotated with bounding boxes for 7 classes : ‘angel’,‘Child_Jesus’,‘crucifixion_of_Jesus’,‘Mary’,‘nudity’, ‘ruins’,‘Saint_Sebastien’. The version 2 of the database contains 10 classes with the same images. The classes are ‘angel’,‘beard’,‘capital’,‘Child_Jesus’,‘crucifixion_of_Jesus’,‘Mary’,‘nudity’,‘ruins’,‘Saint_Sebastien’,‘turban’.
description: This research was supported in part by the "IDI 2017" project funded by the IDEX Paris-Saclay, ANR-11-IDEX-0003-02.
description: {"references": ["Gonthier et al. (2018) Weakly Supervised Object Detection in Artworks arXiv:1810.02569"]}
DOI: 10.6084/m9.figshare.13266506.v2
title: Tables

description: <b></b>Table 1. Clinical demographicsSupplementary Table 1. Subjects not meeting inclusion criteriaSupplementary Table 2. Detailed clinical dataSupplementary Table 3. Clinical followup for subjects with no known diagnosis at dischargeSupplementary Table 4. Reads excluded as likely contaminationSupplementary Table 5. Detailed sequencing metrics by librarySupplementary Table 6. Detailed sequencing metrics by subjectSupplementary Table 7. Detection of reads matching Blacklegged Tick Picorna-Like Virus 2
DOI: 10.6084/m9.figshare.13126358.v2
title: Research Dataset.xlsx

description: This dataset includes major and trace elements, Sr-Nd-Fe isotopes for Neoproterozoic basaltic to andesitic dikes from the Yangtze Block, South China.
DOI: 10.6084/m9.figshare.9831077
title: Reasons for not participating in scleroderma patient support groups: a comparison of results from the North American and European scleroderma support group surveys

description: Many people with scleroderma rely on peer-led support groups as a coping resource. Reasons for not attending support groups in scleroderma have been investigated only in North American participants. This study assesses reasons for nonattendance in European countries and compares results with previously published North American findings. The same 21-item survey as used in the North American sample assessed possible reasons for not attending scleroderma support groups. Proportions of items rated <i>Important</i> or <i>Very Important</i> were compared between samples. Consistent with the North American survey findings (<i>N</i> = 242), the two items most commonly rated as (Very) Important reasons for nonattendance among 228 European participants were (1) already having enough support (57%), and (2) not knowing of any local scleroderma support groups (58%). Compared to North American non-attenders, European patients were significantly more likely to rate not knowing enough about what happens at support groups (46% vs 19%), not having reliable ways to get to meetings (35% vs 17%), and being uncomfortable sharing experiences with a group (22% vs 11%) as (Very) Important reasons for nonattendance. Improving access to European support groups, providing education about support groups and group leader training may encourage participation.IMPLICATIONS FOR REHABILITATIONRehabilitation professionals might help develop local support groups for people with systemic sclerosis (scleroderma) to address the lack of access to these groups for many patients.The need for transportation and limited local accessibility may also be addressed by implementing online systemic sclerosis support groups.Professionals in the field of rehabilitation may work with people with systemic sclerosis and patient organizations to provide education about support groups to improve support group attendance in Europe. Rehabilitation professionals might help develop local support groups for people with systemic sclerosis (scleroderma) to address the lack of access to these groups for many patients. The need for transportation and limited local accessibility may also be addressed by implementing online systemic sclerosis support groups. Professionals in the field of rehabilitation may work with people with systemic sclerosis and patient organizations to provide education about support groups to improve support group attendance in Europe.
DOI: 10.6084/m9.figshare.9831077.v1
title: Reasons for not participating in scleroderma patient support groups: a comparison of results from the North American and European scleroderma support group surveys

description: Many people with scleroderma rely on peer-led support groups as a coping resource. Reasons for not attending support groups in scleroderma have been investigated only in North American participants. This study assesses reasons for nonattendance in European countries and compares results with previously published North American findings. The same 21-item survey as used in the North American sample assessed possible reasons for not attending scleroderma support groups. Proportions of items rated <i>Important</i> or <i>Very Important</i> were compared between samples. Consistent with the North American survey findings (<i>N</i> = 242), the two items most commonly rated as (Very) Important reasons for nonattendance among 228 European participants were (1) already having enough support (57%), and (2) not knowing of any local scleroderma support groups (58%). Compared to North American non-attenders, European patients were significantly more likely to rate not knowing enough about what happens at support groups (46% vs 19%), not having reliable ways to get to meetings (35% vs 17%), and being uncomfortable sharing experiences with a group (22% vs 11%) as (Very) Important reasons for nonattendance. Improving access to European support groups, providing education about support groups and group leader training may encourage participation.IMPLICATIONS FOR REHABILITATIONRehabilitation professionals might help develop local support groups for people with systemic sclerosis (scleroderma) to address the lack of access to these groups for many patients.The need for transportation and limited local accessibility may also be addressed by implementing online systemic sclerosis support groups.Professionals in the field of rehabilitation may work with people with systemic sclerosis and patient organizations to provide education about support groups to improve support group attendance in Europe. Rehabilitation professionals might help develop local support groups for people with systemic sclerosis (scleroderma) to address the lack of access to these groups for many patients. The need for transportation and limited local accessibility may also be addressed by implementing online systemic sclerosis support groups. Professionals in the field of rehabilitation may work with people with systemic sclerosis and patient organizations to provide education about support groups to improve support group attendance in Europe.
DOI: 10.5281/zenodo.4737346
title: Replication Package for Understanding and Improving Artifact Sharing in Software Engineering Research

description: <strong>Replication Package for Understanding and Improving Artifact Sharing in Software Engineering Research</strong><br> This archive provides the associated publication analysis dataset and survey instrument for the research paper, <em>Understanding and Improving Artifact Sharing in Software Engineering Research</em>, published in Empirical Software Engineering. (http://dx.doi.org/10.1007/s10664-021-09973-5). A preprint for the paper is available on arXiv: https://arxiv.org/abs/2008.01046.<br> <br> This artifact is archived on Zenodo (https://doi.org/10.5281/zenodo.4737346) and hosted on GitHub (https://github.com/ChrisTimperley/se-artifact-sharing).<br> <br> <strong>Abstract</strong> In recent years, many software engineering researchers have begun to include artifacts<br> alongside their research papers. Ideally, artifacts, including tools, benchmarks, and data, support the dissemination of ideas, provide evidence for research claims, and serve as a starting point for future research. However, in practice, artifacts suffer from a variety of issues that prevent the realization of their full potential. To help the software engineering community realize the full potential of artifacts, we seek to understand the challenges involved in the creation, sharing, and use of artifacts. To that end, we perform a mixed-methods study including a survey of artifacts in software engineering publications, and an online survey of 153 software engineering researchers. By analyzing the perspectives of artifact creators, users, and reviewers, we identify several high-level challenges that affect the quality of artifacts including mismatched expectations between these groups, and a lack of sufficient reward for both creators and reviewers. Using Diffusion of Innovations as an analytical framework, we examine how these challenges relate to one another, and build an understanding of the factors that affect the sharing and success of artifacts. Finally, we make recommendations to improve the quality of artifacts based on our results and existing best practices.
DOI: 10.5281/zenodo.4737345
title: Replication Package for Understanding and Improving Artifact Sharing in Software Engineering Research

description: <strong>Replication Package for Understanding and Improving Artifact Sharing in Software Engineering Research</strong><br> This archive provides the associated publication analysis dataset and survey instrument for the research paper, <em>Understanding and Improving Artifact Sharing in Software Engineering Research</em>, published in Empirical Software Engineering. (http://dx.doi.org/10.1007/s10664-021-09973-5). A preprint for the paper is available on arXiv: https://arxiv.org/abs/2008.01046.<br> <br> This artifact is archived on Zenodo (https://doi.org/10.5281/zenodo.4737346) and hosted on GitHub (https://github.com/ChrisTimperley/se-artifact-sharing).<br> <br> <strong>Abstract</strong> In recent years, many software engineering researchers have begun to include artifacts<br> alongside their research papers. Ideally, artifacts, including tools, benchmarks, and data, support the dissemination of ideas, provide evidence for research claims, and serve as a starting point for future research. However, in practice, artifacts suffer from a variety of issues that prevent the realization of their full potential. To help the software engineering community realize the full potential of artifacts, we seek to understand the challenges involved in the creation, sharing, and use of artifacts. To that end, we perform a mixed-methods study including a survey of artifacts in software engineering publications, and an online survey of 153 software engineering researchers. By analyzing the perspectives of artifact creators, users, and reviewers, we identify several high-level challenges that affect the quality of artifacts including mismatched expectations between these groups, and a lack of sufficient reward for both creators and reviewers. Using Diffusion of Innovations as an analytical framework, we examine how these challenges relate to one another, and build an understanding of the factors that affect the sharing and success of artifacts. Finally, we make recommendations to improve the quality of artifacts based on our results and existing best practices.