cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5472943.v1
title: Executable file for the Beast analysis (for Figure 4) Worthy et al. galloanseres from The evolution of giant flightless birds and novel phylogenetic relationships for extinct fowl (Aves, Galloanseres)

description: The executable file for the Beast analysis resulting in Figure 4.
DOI: 10.6084/m9.figshare.5480800.v1
title: Dataset S1 from Morphospaces of functionally analogous traits show ecological separation between birds and pterosaurs

description: Measurements and data sources for pterosaurs
DOI: 10.6084/m9.figshare.5480824.v2
title: Dataset S2 from Morphospaces of functionally analogous traits show ecological separation between birds and pterosaurs.

description: Measurements and data sources for Mesozoic birds
DOI: 10.6084/m9.figshare.5480881
title: Analysis Code from O brother, where art thou? Investment in siblings for inclusive fitness benefits, not father absence, predicts earlier age at menarche.

description: Stata code used to analyse the data
DOI: 10.6084/m9.figshare.5480824.v1
title: Dataset S2 from Morphospaces of functionally analogous traits show ecological separation between birds and pterosaurs

description: Measurements and data sources for Mesozoic birds
DOI: 10.6084/m9.figshare.5480881.v2
title: Analysis Code from O brother, where art thou? Investment in siblings for inclusive fitness benefits, not father absence, predicts earlier age at menarche.

description: Stata code used to analyse the data
DOI: 10.6084/m9.figshare.5480881.v1
title: Analysis Code from O brother, where art thou? Investment in siblings for inclusive fitness benefits, not father absence, predicts earlier age at menarche

description: Stata code used to analyse the data
DOI: 10.6084/m9.figshare.5501383
title: Dataset on fouling organisms and measurements from Macrofouling communities and the degradation of plastic bags in the sea: an <i>in situ</i> experiment.

description: Includes all data on fouling organisms identified to family level, organisms identified with another taxonomic resolution, as well as data on polymer disintegration.
DOI: 10.6084/m9.figshare.5501383.v2
title: Dataset on fouling organisms and measurements from Macrofouling communities and the degradation of plastic bags in the sea: an <i>in situ</i> experiment.

description: Includes all data on fouling organisms identified to family level, organisms identified with another taxonomic resolution, as well as data on polymer disintegration.
DOI: 10.6084/m9.figshare.5527036.v2
title: Model Code from Errors in mutagenesis and the benefit of cell-to-cell signalling in the evolution of stress-induced mutagenesis.

description: The full python code for this work
DOI: 10.6084/m9.figshare.5527087
title: full_data.zip from Frequency patterns of semantic change: corpus-based evidence of a near-critical dynamics in language change.

description: Raw data extracted from the Frantext database.
DOI: 10.6084/m9.figshare.5527036
title: Model Code from Errors in mutagenesis and the benefit of cell-to-cell signalling in the evolution of stress-induced mutagenesis.

description: The full python code for this work
DOI: 10.6084/m9.figshare.5501383.v1
title: Dataset on fouling organisms and measurements from Macrofouling communities and the degradation of plastic bags in the sea: an <i>in situ</i> experiment

description: Includes all data on fouling organisms identified to family level, organisms identified with another taxonomic resolution, as well as data on polymer disintegration.
DOI: 10.6084/m9.figshare.5527036.v1
title: Model Code from Errors in mutagenesis and the benefit of cell-to-cell signalling in the evolution of stress-induced mutagenesis

description: The full python code for this work
DOI: 10.6084/m9.figshare.5527087.v2
title: full_data.zip from Frequency patterns of semantic change: corpus-based evidence of a near-critical dynamics in language change.

description: Raw data extracted from the Frantext database.
DOI: 10.6084/m9.figshare.5527087.v1
title: full_data.zip from Frequency patterns of semantic change: corpus-based evidence of a near-critical dynamics in language change

description: Raw data extracted from the Frantext database.
DOI: 10.6084/m9.figshare.5532205
title: Supplementary file 3 from Long-term patterns of body mass and stature evolution within the hominin lineage.

description: Dataset for the test of major chronological and taxonomic body size changes regarding both mean values and coefficients of variation in Excel format.
DOI: 10.6084/m9.figshare.5532208
title: Supplementary file 1 from Long-term patterns of body mass and stature evolution within the hominin lineage.

description: Database of hominin body size estimates in Excel format.
DOI: 10.6084/m9.figshare.5532205.v1
title: Supplementary file 3 from Long-term patterns of body mass and stature evolution within the hominin lineage

description: Dataset for the test of major chronological and taxonomic body size changes regarding both mean values and coefficients of variation in Excel format.
DOI: 10.6084/m9.figshare.5532208.v2
title: Supplementary file 1 from Long-term patterns of body mass and stature evolution within the hominin lineage.

description: Database of hominin body size estimates in Excel format.
DOI: 10.6084/m9.figshare.5555140
title: Fig 1-PCMRI from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5532202
title: Supplementary file 2 from Long-term patterns of body mass and stature evolution within the hominin lineage.

description: Database of Atapuerca hominins ordered by different selection criteria in Excel format.
DOI: 10.6084/m9.figshare.5532208.v1
title: Supplementary file 1 from Long-term patterns of body mass and stature evolution within the hominin lineage

description: Database of hominin body size estimates in Excel format.
DOI: 10.6084/m9.figshare.5555140.v2
title: Fig 1-PCMRI from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555146
title: Fig 3 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5532202.v1
title: Supplementary file 2 from Long-term patterns of body mass and stature evolution within the hominin lineage

description: Database of Atapuerca hominins ordered by different selection criteria in Excel format.
DOI: 10.6084/m9.figshare.5555146.v2
title: Fig 3 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555149
title: Fig 7 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555140.v1
title: Fig 1-PCMRI from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555146.v1
title: Fig 3 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555143
title: Fig 8 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555149.v2
title: Fig 7 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data.

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.
DOI: 10.6084/m9.figshare.5555149.v1
title: Fig 7 from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data

description: Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support.