cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/14115461.v2
title: Data underlying the publication: Phytophthora pathogens exploit slicing action for host invasion

description: Host entry requires plant pathogens to breach the protective surface of the plant. <i>Phytophthora </i>species, classified as oomycetes, are among the most destructive filamentous plant pathogens worldwide and pose a substantial threat to food security. Little is known about the biomechanics of host invasion in oomycetes, yet this understanding is crucial to combat these pathogens more effectively. Here we unveil how <i>Phytophthora</i> spp. invade elastic surfaces by pressure application at an oblique angle without appressorium formation. This ‘slicing’ action, coined the <i>naifu</i>-mechanism, facilitates crack initiation by concentrating stresses towards the surface enabling host entry through the crack void. This contrasts the ‘brute’ force approach found in fungal filamentous plant pathogens capable of producing a melanized appressorium that generates tremendous turgor pressures. Measurements of surface deformations during invasion reveal an asymmetric geometry of decoupled adherence and indentation sites that is quantitatively described with a mathematical model. Moreover, we establish how polarized growth, surface adherence and turgor generation are each essential to accomplish host entry by this approach. The naifu-mechanism enables <i>Phytophthora </i>pathogens to penetrate their hosts without necessitating specialized pressure organs and vast turgor pressures. <b></b>
DOI: 10.4121/14115461
title: Data underlying the publication: Phytophthora pathogens exploit slicing action for host invasion

description: Host entry requires plant pathogens to breach the protective surface of the plant. <i>Phytophthora </i>species, classified as oomycetes, are among the most destructive filamentous plant pathogens worldwide and pose a substantial threat to food security. Little is known about the biomechanics of host invasion in oomycetes, yet this understanding is crucial to combat these pathogens more effectively. Here we unveil how <i>Phytophthora</i> spp. invade elastic surfaces by pressure application at an oblique angle without appressorium formation. This ‘slicing’ action, coined the <i>naifu</i>-mechanism, facilitates crack initiation by concentrating stresses towards the surface enabling host entry through the crack void. This contrasts the ‘brute’ force approach found in fungal filamentous plant pathogens capable of producing a melanized appressorium that generates tremendous turgor pressures. Measurements of surface deformations during invasion reveal an asymmetric geometry of decoupled adherence and indentation sites that is quantitatively described with a mathematical model. Moreover, we establish how polarized growth, surface adherence and turgor generation are each essential to accomplish host entry by this approach. The naifu-mechanism enables <i>Phytophthora </i>pathogens to penetrate their hosts without necessitating specialized pressure organs and vast turgor pressures. <b></b>
DOI: 10.4121/13379174.v1
title: Figures created during the work on "Multi-Δt approach for peak-locking error correction and uncertainty quantification in PIV"

description: This dataset contains figures.
DOI: 10.4121/13379174
title: Figures created during the work on "Multi-Δt approach for peak-locking error correction and uncertainty quantification in PIV"

description: This dataset contains figures.
DOI: 10.4121/14192429.v1
title: Dataset and related MATLAB scripts for the IEEE ICRA 2021 paper "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study"

description: This dataset contains impact data (recording of joint displacement encoders), together with related MATLAB scripts for visualization and post-processing, for several impact experiments performed on a KUKA IV+ collaborative robot colliding a wooden table with a spherical metallic end-effector.<br>The dataset is associated to the "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study" by Ilias Aouaj, Vincent Padois, and Alessandro Saccon, accepted to ICRA 2021.
DOI: 10.4121/14192429.v2
title: Dataset and related MATLAB scripts for the IEEE ICRA 2021 paper "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study"

description: This dataset contains impact data (recording of joint displacement encoders), together with related MATLAB scripts for visualization and post-processing, for several impact experiments performed on a KUKA IV+ collaborative robot colliding a wooden table with a spherical metallic end-effector.<br>The dataset is associated to the "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study" by Ilias Aouaj, Vincent Padois, and Alessandro Saccon, accepted to ICRA 2021.
DOI: 10.4121/14192429.v3
title: Dataset and related MATLAB scripts for the IEEE ICRA 2021 paper "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study"

description: This dataset contains impact data (recording of joint displacement encoders), together with related MATLAB scripts for visualization and post-processing, for several impact experiments performed on a KUKA IV+ collaborative robot colliding a wooden table with a spherical metallic end-effector.<br>The dataset is associated to the "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study" by Ilias Aouaj, Vincent Padois, and Alessandro Saccon, accepted to ICRA 2021.
DOI: 10.4121/14192429
title: Dataset and related MATLAB scripts for the IEEE ICRA 2021 paper "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study"

description: This dataset contains impact data (recording of joint displacement encoders), together with related MATLAB scripts for visualization and post-processing, for several impact experiments performed on a KUKA IV+ collaborative robot colliding a wooden table with a spherical metallic end-effector.<br>The dataset is associated to the "Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study" by Ilias Aouaj, Vincent Padois, and Alessandro Saccon, accepted to ICRA 2021.
DOI: 10.4121/14214236.v1
title: The Obstacle Detection and Avoidance Dataset for Drones

description: We introduce the Obstacle Detection and Avoidance Dataset for Drones, aiming at providing raw data obtained in a real indoor environment with sensors adapted for aerial robotics. Our micro air vehicle (MAV) is equipped with the following sensors: (i) an event-based camera, the dynamic performance of which make it optimized for drone applications; (ii) a standard RGB camera; (iii) a 24-GHz radar sensor to enhance multi-sensory solutions; and (iv) a 6-axes IMU. The ground truth position and attitude are provided by the OptiTrack motion capture system. The resulting dataset consists in more than 1350 samples obtained in four distinct conditions (one or two obstacles, full or dim light). It is intended for benchmarking algorithmic and neural solutions for obstacle detection and avoidance with UAVs, but also course estimation and therefore autonomous navigation. For further information, please visit: https://github.com/tudelft/ODA_Dataset <br>
DOI: 10.4121/14214236
title: The Obstacle Detection and Avoidance Dataset for Drones

description: We introduce the Obstacle Detection and Avoidance Dataset for Drones, aiming at providing raw data obtained in a real indoor environment with sensors adapted for aerial robotics. Our micro air vehicle (MAV) is equipped with the following sensors: (i) an event-based camera, the dynamic performance of which make it optimized for drone applications; (ii) a standard RGB camera; (iii) a 24-GHz radar sensor to enhance multi-sensory solutions; and (iv) a 6-axes IMU. The ground truth position and attitude are provided by the OptiTrack motion capture system. The resulting dataset consists in more than 1350 samples obtained in four distinct conditions (one or two obstacles, full or dim light). It is intended for benchmarking algorithmic and neural solutions for obstacle detection and avoidance with UAVs, but also course estimation and therefore autonomous navigation. For further information, please visit: https://github.com/tudelft/ODA_Dataset <br>
DOI: 10.4121/14223062
title: Matlab code supplementary to the MSc thesis: Nonlinear control of electronic converters; Fast and optimal control using sampling-driven nonlinear MPC

description: These Matlab files represent the application of the sampling-driven nonlinear MPC to two power electronic converters, namely the buck-boost converter connected to a resistive load and the three-phase VSI connected to a PMSM. Various methods are used to determine all the steps involved in this method which are the determination of the local controller with corresponding domain of attraction, the determination of an initial control sequence steering the initial state into this domain of attraction and the application of the online part of the SD-NMPC method.<br>
DOI: 10.4121/14247239.v1
title: Associated data underlying the article 'Implications of the Use of Artificial Intelligence in Public Governance: A Systematic Literature Review and a Research Agenda'

description: This dataset provides the data underlying the systematic literature review conducted for the article 'Implications of the Use of Artificial Intelligence in Public Governance: A Systematic Literature Review and a Research Agenda. This article was published in the journal Government Information Quarterly.
DOI: 10.4121/14247239
title: Associated data underlying the article 'Implications of the Use of Artificial Intelligence in Public Governance: A Systematic Literature Review and a Research Agenda'

description: This dataset provides the data underlying the systematic literature review conducted for the article 'Implications of the Use of Artificial Intelligence in Public Governance: A Systematic Literature Review and a Research Agenda. This article was published in the journal Government Information Quarterly.
DOI: 10.4121/13516841.v1
title: Data underlying the paper: Does morality predict aggressive driving? A conceptual analysis and exploratory empirical investigation

description: This dataset contains the data that were used for the analyses reported in the following published paper: van den Berg, T. G., Kroesen, M., & Chorus, C. G. (2020). Does morality predict aggressive driving? A conceptual analysis and exploratory empirical investigation. <i>Transportation research part F: traffic psychology and behaviour</i>, <i>74</i>, 259-271.<br>In this study we investigated the relation between people's general moral values and level of aggressive driving behavior. We measured people's general moral values using the Moral Foundation Questionnaire (MFQ) (moralfoundations.org) and people's level of aggressive driving behavior by the Aggressive Driving Behavior Scale (ADBS) (Houston, Harris & Norman, 2003). For entering the MFQ-items in the analysis we used the original 5 component structure that is given by the theoretical framework and computed sumscores for each of the 5 moral dimensions. These variables were included as the independent variables together with the control variables of age, gender, and education in a hierarchical linear regression model, where the control variables were entered first. For the ADBS-items, using principal component analysis, we found that our data produced a three component solution indicating three dimensions of aggressive driving: Speeding/ rushing; aggressive communication; thwarting. Somscores were computed for each variable and these were entered as the dependent variables in the linear regression model.
DOI: 10.4121/13516841
title: Data underlying the paper: Does morality predict aggressive driving? A conceptual analysis and exploratory empirical investigation

description: This dataset contains the data that were used for the analyses reported in the following published paper: van den Berg, T. G., Kroesen, M., & Chorus, C. G. (2020). Does morality predict aggressive driving? A conceptual analysis and exploratory empirical investigation. <i>Transportation research part F: traffic psychology and behaviour</i>, <i>74</i>, 259-271.<br>In this study we investigated the relation between people's general moral values and level of aggressive driving behavior. We measured people's general moral values using the Moral Foundation Questionnaire (MFQ) (moralfoundations.org) and people's level of aggressive driving behavior by the Aggressive Driving Behavior Scale (ADBS) (Houston, Harris & Norman, 2003). For entering the MFQ-items in the analysis we used the original 5 component structure that is given by the theoretical framework and computed sumscores for each of the 5 moral dimensions. These variables were included as the independent variables together with the control variables of age, gender, and education in a hierarchical linear regression model, where the control variables were entered first. For the ADBS-items, using principal component analysis, we found that our data produced a three component solution indicating three dimensions of aggressive driving: Speeding/ rushing; aggressive communication; thwarting. Somscores were computed for each variable and these were entered as the dependent variables in the linear regression model.
DOI: 10.4121/14247125.v1
title: Supporting information for 'A two-stage cooling of the Georgetown Inlier in NE Australia after 1.6 Ga Nuna assembly: new insights into the late-orogenic crustal tectono-magmatic history'

description: This document contains the supporting information for the manuscript 'A two-stage cooling of the Georgetown Inlier in NE Australia after 1.6 Ga Nuna assembly: new insights into the late-orogenic crustal tectono-magmatic history' we submitted to JGR: Solid Earth.In this document, we provide 40Ar/39Ar analytical data, previously argon results, and relative parameters for mineral closure temperature calculation and Monte Carlo simulation. Detail microscope images of the dated samples are also provided. <br>
DOI: 10.4121/14247125
title: Supporting information for 'A two-stage cooling of the Georgetown Inlier in NE Australia after 1.6 Ga Nuna assembly: new insights into the late-orogenic crustal tectono-magmatic history'

description: This document contains the supporting information for the manuscript 'A two-stage cooling of the Georgetown Inlier in NE Australia after 1.6 Ga Nuna assembly: new insights into the late-orogenic crustal tectono-magmatic history' we submitted to JGR: Solid Earth.In this document, we provide 40Ar/39Ar analytical data, previously argon results, and relative parameters for mineral closure temperature calculation and Monte Carlo simulation. Detail microscope images of the dated samples are also provided. <br>
DOI: 10.4121/14230238.v1
title: Data underlying research on Engineering of molybdenum-cofactor-dependent nitrate assimilation in Yarrowia lipolytica

description: Engineering a new metabolic function in a microbial host can be limited by the availability of the relevant co-factor. For instance, in <i>Yarrowia lipolytica</i>, the expression of a functional nitrate reductase is precluded by the absence of molybdenum cofactor (Moco) biosynthesis. In this study, we demonstrated that the <i>Ogataea parapolymorpha</i> Moco biosynthesis pathway associated with the expression of a high affinity molybdate transporter could lead to the synthesis of Moco in <i>Y. lipolytica</i>. This was achieved by coupling Moco biosynthesis to the Moco-dependent nitrate assimilation pathway of the same donor, <i>O. parapolymorpha</i>. In addition to 11 heterologous genes, fast growth on nitrate required adaptive laboratory evolution which, resulted in up to 100-fold increase in nitrate reductase activity and in up to 4-fold increase in growth rate. Genome sequencing of evolved isolates revealed the presence of a limited number of non-synonymous mutations or small insertions/deletions in annotated coding sequences. This study that builds up on a previous work establishing Moco synthesis in <i>S. cerevisiae</i> demonstrated that the Moco pathway could be successfully transferred in very distant yeasts and, potentially, to any other genera, which would enable the expression of new enzyme families and expand the nutrient range used by industrial yeasts.
DOI: 10.4121/14230238
title: Data underlying research on Engineering of molybdenum-cofactor-dependent nitrate assimilation in Yarrowia lipolytica

description: Engineering a new metabolic function in a microbial host can be limited by the availability of the relevant co-factor. For instance, in <i>Yarrowia lipolytica</i>, the expression of a functional nitrate reductase is precluded by the absence of molybdenum cofactor (Moco) biosynthesis. In this study, we demonstrated that the <i>Ogataea parapolymorpha</i> Moco biosynthesis pathway associated with the expression of a high affinity molybdate transporter could lead to the synthesis of Moco in <i>Y. lipolytica</i>. This was achieved by coupling Moco biosynthesis to the Moco-dependent nitrate assimilation pathway of the same donor, <i>O. parapolymorpha</i>. In addition to 11 heterologous genes, fast growth on nitrate required adaptive laboratory evolution which, resulted in up to 100-fold increase in nitrate reductase activity and in up to 4-fold increase in growth rate. Genome sequencing of evolved isolates revealed the presence of a limited number of non-synonymous mutations or small insertions/deletions in annotated coding sequences. This study that builds up on a previous work establishing Moco synthesis in <i>S. cerevisiae</i> demonstrated that the Moco pathway could be successfully transferred in very distant yeasts and, potentially, to any other genera, which would enable the expression of new enzyme families and expand the nutrient range used by industrial yeasts.
DOI: 10.4121/14151755
title: Repository of fake news detection datasets

description: The dataset contains a list of twenty-seven freely available evaluation datasets for fake news detection analysed according to eleven main characteristics (i.e., news domain, application purpose, type of disinformation, language, size, news content, rating scale, spontaneity, media platform, availability, and extraction time)
DOI: 10.4121/uuid:b5c1ef79-795e-42fc-b4b3-3487a0e6934e
title: Processed Data of Extreme Events for the Coastal Region of Southern Brazil

description: This dataset was created for the Danilo Couto de Souza's master thesis. It contains processed data of extreme events for the coastal region of southern Brazil. See also the publication containing the analysis of this dataset.
DOI: 10.4121/uuid:f33500a7-6bf4-45e7-8244-96dcbcb65a44
title: Data of dynamic downscaled extreme events for the coastal region of Southern Brazil

description: This dataset was created for the Danilo Couto de Souza's master thesis. The results were further sent to publication. In this dataset there is processed data of extreme events for the coastal region of southern Brazil. It also contains observed (form meteorological stations) and reanalysis data (GPM/TRMM and MERRA-2) for the same period, for model validation purposes. Those events were dynamically downscaled using the Ocean-Land Atmosphere Model (OLAM) set up with a high resolution grid for the study area. This dataset also contains Python language scripts used for comparing the modelled data and the observed/reanalysis equivalents. See also the publication containing the analysis of this dataset.
DOI: 10.4121/12721367.v3
title: Data of dynamic downscaled extreme events for the coastal region of Southern Brazil

description: This dataset was created for the Danilo Couto de Souza's master thesis. The results were further sent to publication. In this dataset there is processed data of extreme events for the coastal region of southern Brazil. It also contains observed (form meteorological stations) and reanalysis data (GPM/TRMM and MERRA-2) for the same period, for model validation purposes. Those events were dynamically downscaled using the Ocean-Land Atmosphere Model (OLAM) set up with a high resolution grid for the study area. This dataset also contains Python language scripts used for comparing the modelled data and the observed/reanalysis equivalents. See also the publication containing the analysis of this dataset.
DOI: 10.4121/12721367
title: Data of dynamic downscaled extreme events for the coastal region of Southern Brazil

description: This dataset was created for the Danilo Couto de Souza's master thesis. The results were further sent to publication. In this dataset there is processed data of extreme events for the coastal region of southern Brazil. It also contains observed (form meteorological stations) and reanalysis data (GPM/TRMM and MERRA-2) for the same period, for model validation purposes. Those events were dynamically downscaled using the Ocean-Land Atmosphere Model (OLAM) set up with a high resolution grid for the study area. This dataset also contains Python language scripts used for comparing the modelled data and the observed/reanalysis equivalents. See also the publication containing the analysis of this dataset.
DOI: 10.4121/13537001.v1
title: Autoclave measurement data of 2 autoclaves in rural hospitals

description: Measurement data of two autoclaves in rural hospitals. Each file contains temperature and pressure data of different sensors placed in the autoclave chambers.
DOI: 10.4121/13537001
title: Autoclave measurement data of 2 autoclaves in rural hospitals

description: Measurement data of two autoclaves in rural hospitals. Each file contains temperature and pressure data of different sensors placed in the autoclave chambers.
DOI: 10.4121/14217098.v1
title: Data underlying the publication: Application of liquid-infused membranes to mitigate biofouling

description: This data set includes:1- all the biofouling results obtained during membrane cross flow experiments using tab water and nutrient solution as the feed.2- Analysis of all the biofouling results in order to obtain the bacterial growth curve based on fitting to a sigmoidal model (logistic model) as well as linear regression.3- Liquid-liquid displacement analysis to better understand the liquid retention in the membrane after permeating water at high flux values.4- Water contact angle measurements of the pristine (dry) and liquid-infused membranes.5- Pores size distribution analysis of the pristine membrane.6- All the codes in order to obtain the final plots of the "transmembrane pressure (TMP) increase" and "feed pressure increase" as a function of time as well as effect of increased nutrient concentration on the TMP increase.
DOI: 10.4121/14217098
title: Data underlying the publication: Application of liquid-infused membranes to mitigate biofouling

description: This data set includes:1- all the biofouling results obtained during membrane cross flow experiments using tab water and nutrient solution as the feed.2- Analysis of all the biofouling results in order to obtain the bacterial growth curve based on fitting to a sigmoidal model (logistic model) as well as linear regression.3- Liquid-liquid displacement analysis to better understand the liquid retention in the membrane after permeating water at high flux values.4- Water contact angle measurements of the pristine (dry) and liquid-infused membranes.5- Pores size distribution analysis of the pristine membrane.6- All the codes in order to obtain the final plots of the "transmembrane pressure (TMP) increase" and "feed pressure increase" as a function of time as well as effect of increased nutrient concentration on the TMP increase.