857 research outputs found
What Did Matthieu Beroald Transmit to François Béroalde de Verville?
No full text Many tangible and intangible goods were passed down within early modern families. The goods included texts and the knowledge that texts communicated. But how did they relate to the other goods transmitted within families? That question is explored in relation to the scholar Matthieu Beroald and his son François Béroalde de Verville, author of the famous Moyen de parvenir. Matthieu transmitted to François a humanist education, at least one printed volume (probably more), an interest in certain topics (especially chronology), a network of contacts, but little wealth. And François soon donated to his sisters what wealth he did receive. His relationship to his intellectual inheritance from his father was complex and ambivalent. Aspects of François's attitude towards knowledge may have stemmed, via his father, from two grandfather-figures: Matthieu's own father (a barber-surgeon) and Matthieu's relative and benefactor François Vatable (the Hebraicist). </jats:p
Looking at pore scale processes in geomaterials using time-resolved 3D imaging and multi-scale imaging
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X-ray micro-computed tomography based X-ray particle tracking velocimetry dataset in a porous glass filter
No full textAuthors: Tom Bultreys, Stefanie Van Offenwert, Wannes Goethals, Matthieu N. Boone, Jan Aelterman and Veerle Cnudde; Ghent University (Belgium)
Date: 8th February 2022
For any usage, please cite the accompanying publication: T. Bultreys, S. Van Offenwert, W. Goethals, M. N. Boone, J. Aelterman and V. Cnudde, "X-ray Tomographic Micro-Particle Velocimetry in Porous Media", Physics of Fluids, 34, 042008 (2022).
https://doi.org/10.1063/5.0088000
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Dataset of a micro-computed tomography based particle tracking velocimetry experiment performed on a glass filter (ROBU P0; sample size 4 mm diameter by 1 cm).
- The main data is contained in the directory "TimeFrames", containing the reconstructed 3D images at 59 time steps (35 seconds interval), with a voxel size of 11.8 µm, in 3D .tif format. This can be opened in for example Fiji/ImageJ.
- The directory "clearFrame" contains a high-quality pre-scan taken before the main experiment, which was registered and resampled to the time frame images, in the same format and with the same voxel size as the time frame images.
- The directory "SegmentedImage" contains two binary 3D images (same format as images before) which was created by segmenting the clearFrame image. There are two versions: the original segmentation, and a version where pores were eroded. The eroded segmentation was used to mask the pore space during particle detection (this avoids spurious detections near pore walls, caused by minor mis-alignments of the clearImage).
- The original segmentation was used as input to simulate the velocity fields in the directory "simulatedVelocityFields", which contains 3D .tif images that represent the three components of the velocity vector field (the X-direction was the axis of the sample, equaling the flow direction). There is also an input text file and an output text file. The simulation was performed with the code from single-phase OpenFOAM implementation from Ali Raeini and others at Imperial College London: http://www.imperial.ac.uk/earth-science/research/research-groups/perm/research/pore-scale-modelling/
- The trackingOutput folder contains the experimentally determined velocity points (.csv, only particles that could be tracked at least 20 time frames) and the experimentally determined velocity magnitude field (.tif, voxel size 23.6 µm
X-ray micro-computed tomography based particle tracking velocimetry dataset in a sandpack
No full textAuthors: Tom Bultreys, Stefanie Van Offenwert, Wannes Goethals, Matthieu N. Boone, Jan Aelterman and Veerle Cnudde; Ghent University (Belgium)
Date: 8th February 2022
For any usage, please cite the accompanying publication: T. Bultreys, S. Van Offenwert, W. Goethals, M. N. Boone, J. Aelterman and V. Cnudde, "X-ray Tomographic Micro-Particle Velocimetry in Porous Media", Physics of Fluids, 34, 042008 (2022).
https://doi.org/10.1063/5.0088000
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Dataset of a micro-computed tomography based particle tracking velocimetry experiment performed on a sand pack (grainsize 500-710 µm; sample size 4 mm diameter by 2 cm).
- The main data is contained in the directory "TimeFrames", containing the reconstructed 3D images at 79 time steps (35 seconds interval), with a voxel size of 11.8 µm, in 3D .tif format. This can be opened in for example Fiji/ImageJ.
- The directory "clearFrame" contains a high-quality pre-scan taken before the main experiment, which was registered and resampled to the time frame images, in the same format and with the same voxel size as the time frame images.
- The directory "SegmentedImage" contains two binary 3D images (same format as images before) which was created by segmenting the clearFrame image. There are two versions: the original segmentation, and a version where pores were eroded. The eroded segmentation was used to mask the pore space during particle detection (this avoids spurious detections near pore walls, caused by minor mis-alignments of the clearImage).
- The original segmentation was used as input to simulate the velocity fields in the directory "simulatedVelocityFields", which contains 3D .tif images that represent the three components of the velocity vector field (the X-direction was the axis of the sample, equaling the flow direction). There is also an input text file and an output text file. The simulation was performed with the code from single-phase OpenFOAM implementation from Ali Raeini and others at Imperial College London: http://www.imperial.ac.uk/earth-science/research/research-groups/perm/research/pore-scale-modelling/
- The trackingOutput folder contains the experimentally determined velocity points (.csv, only particles that could be tracked at least 20 time frames) and the experimentally determined velocity magnitude field (.tif, voxel size 23.6 µm
Simulated X-ray micro-computed tomography based particle tracking velocimetry dataset for validation purposes
No full textAuthors: Tom Bultreys, Stefanie Van Offenwert, Wannes Goethals, Matthieu N. Boone, Jan Aelterman and Veerle Cnudde; Ghent University (Belgium)
Date: 8th February 2022
For any usage, please cite the accompanying publication: T. Bultreys, S. Van Offenwert, W. Goethals, M. N. Boone, J. Aelterman and V. Cnudde, "X-ray Tomographic Micro-Particle Velocimetry in Porous Media", Physics of Fluids, 34, 042008 (2022).
https://doi.org/10.1063/5.0088000
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Validation dataset for micro-computed tomography based particle tracking velocimetry: a simulated micro-CT based velocimetry experiment with associated ground-truth particle trajectories
- The ground truth trajectories were based on randomly dropping virtual particles in the pore space, and tracking their movement through a CFD-based velocity field (see below). The positions were calculated for the time corresponding to each radiograph of a micro-CT experiment. The folder "GroundTruthData" contains the locations of all particles at the central time of each micro-CT scan, as well as their radii. Check the associated readme file to read the data file.
- The main data is contained in the directory "TimeFrames", containing the reconstructed 3D images at 7 time steps (70 seconds interval), with a voxel size of 11.8 µm, in 3D .tif format. This can be opened in for example Fiji/ImageJ.
- The directory "clearFrame" contains an image of the pore space without particles, matching with the time frame images, in the same format and with the same voxel size as the time frame images.
- The directory "SegmentedImage" contains two binary 3D images (same format as images before) which was created by segmenting the clearFrame image. There are two versions: the original segmentation, and a version where pores were eroded. The eroded segmentation was used to mask the pore space during particle detection (this avoids spurious detections near pore walls, caused by minor mis-alignments of the clearImage).
- The original segmentation was used as input to simulate the velocity fields in the directory "simulatedVelocityFields", which contains 3D .tif images that represent the three components of the velocity vector field (the X-direction was the axis of the sample, equaling the flow direction). There is also an input text file and an output text file. The simulation was performed with the code from single-phase OpenFOAM implementation from Ali Raeini and others at Imperial College London: http://www.imperial.ac.uk/earth-science/research/research-groups/perm/research/pore-scale-modelling/
- The trackingOutput folder contains the experimentally determined velocity points (.csv, only particles that could be tracked at least 6 time frames) and the experimentally determined velocity magnitude field (.tif, voxel size 23.6 µm
Social protection
No full textThis chapter analyses models of social protection. The author (Matthieu Clément) first discusses several recent programmes and proceeds by implementing Esping-Andersen’s analytical framework accounting for the plurality of social protection logics and actors. He finds that the two main dimensions that help differentiate social protection types across countries are the extent of decommodification and the extent of informal social protection. Four models of social protection are identified. Although China, India or Brazil, together with Latin American reformers, all fall into the USA-like liberal type, the other emerging countries fall into the social insecurity model, with migrant remittances playing a key role in bolstering family income in the country of origin. The last two models, which are specific to developing economies, are described in detail
Contrast enhanced X-ray micro-computed tomography imaging of biologically derived soils in porous substrates
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