cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/16619726
title: Photos of buildings taken on October 9th 2017 in San Jose canton, Costa Rica

description: First see the description of the Collection this item belongs to.<br>This item consists of images taken from the street and their respective GPS data of buildings in San Jose canton, Costa Rica, on October 9, 2017 by means of the GFZ Mobile Mapping System.<br>This was part of the generation of an exposure model for San Jose, by the Seismic Engineering Laboratory - Engineering Research Institute - University of Costa Rica (LIS-INII-UCR) in collaboration with GFZ - Potsdam.<br>
DOI: 10.4121/16619742.v1
title: Photos of buildings taken on October 7th 2017 in San Jose canton, Costa Rica

description: First see the description of the Collection this item belongs to.<br><br>This item consists of images taken from the street and their respective GPS data of buildings in San Jose canton, Costa Rica, on October 7, 2017 by means of the GFZ Mobile Mapping System.<br>This was part of the generation of an exposure model for San Jose, by the Seismic Engineering Laboratory - Engineering Research Institute - University of Costa Rica (LIS-INII-UCR) in collaboration with GFZ - Potsdam.<br>
DOI: 10.4121/16619742
title: Photos of buildings taken on October 7th 2017 in San Jose canton, Costa Rica

description: First see the description of the Collection this item belongs to.<br><br>This item consists of images taken from the street and their respective GPS data of buildings in San Jose canton, Costa Rica, on October 7, 2017 by means of the GFZ Mobile Mapping System.<br>This was part of the generation of an exposure model for San Jose, by the Seismic Engineering Laboratory - Engineering Research Institute - University of Costa Rica (LIS-INII-UCR) in collaboration with GFZ - Potsdam.<br>
DOI: 10.4121/16619747.v1
title: Photos of buildings taken on October 6th 2017 in San Jose canton, Costa Rica

description: First see the description of the Collection this item belongs to.<br>This item consists of images taken from the street and their respective GPS data of buildings in San Jose canton, Costa Rica, on October 6, 2017 by means of the GFZ Mobile Mapping System.<br>This was part of the generation of an exposure model for San Jose, by the Seismic Engineering Laboratory - Engineering Research Institute - University of Costa Rica (LIS-INII-UCR) in collaboration with GFZ - Potsdam.
DOI: 10.4121/16619747
title: Photos of buildings taken on October 6th 2017 in San Jose canton, Costa Rica

description: First see the description of the Collection this item belongs to.<br>This item consists of images taken from the street and their respective GPS data of buildings in San Jose canton, Costa Rica, on October 6, 2017 by means of the GFZ Mobile Mapping System.<br>This was part of the generation of an exposure model for San Jose, by the Seismic Engineering Laboratory - Engineering Research Institute - University of Costa Rica (LIS-INII-UCR) in collaboration with GFZ - Potsdam.
DOI: 10.4121/16619749.v1
title: Soil organic carbon concentration of Canada, at six soil depths, 250m spatial resolution

description: This dataset contains maps with the spatial distribution of soil carbon concentration (g/kg) in Canada at 6 soil depths: 0cm, 5cm, 15cm, 30cm, 60cm and 100cm. It is being made public to act as supplementary data for the publication 'Large scale mapping of soil organic carbon concentration with 3D machine learning and satellite observations', published in Geoderma: https://doi.org/10.1016/j.geoderma.2021.115402<br>The study is part of our project that aimed to produce the first wall-to-wall estimate of carbon stocks in plants and soils of Canada at 250 m spatial resolution using multisource satellite, climate and topographic data and a machine-learning algorithm. The soil organic carbon concentration maps are intermediate products to generate the soil organic carbon stock map in kg/m2.<br>To generate the soil carbon concentration maps, we used 6,533 ground soil samples, long-term climate data, multisource remote sensing data, topographic information, soil type, depth, and a 3D random forest regression model.<br>
DOI: 10.4121/16619749
title: Soil organic carbon concentration of Canada, at six soil depths, 250m spatial resolution

description: This dataset contains maps with the spatial distribution of soil carbon concentration (g/kg) in Canada at 6 soil depths: 0cm, 5cm, 15cm, 30cm, 60cm and 100cm. It is being made public to act as supplementary data for the publication 'Large scale mapping of soil organic carbon concentration with 3D machine learning and satellite observations', published in Geoderma: https://doi.org/10.1016/j.geoderma.2021.115402<br>The study is part of our project that aimed to produce the first wall-to-wall estimate of carbon stocks in plants and soils of Canada at 250 m spatial resolution using multisource satellite, climate and topographic data and a machine-learning algorithm. The soil organic carbon concentration maps are intermediate products to generate the soil organic carbon stock map in kg/m2.<br>To generate the soil carbon concentration maps, we used 6,533 ground soil samples, long-term climate data, multisource remote sensing data, topographic information, soil type, depth, and a 3D random forest regression model.<br>
DOI: 10.4121/16620577.v1
title: Data supplementary to the manuscript: “Verapamil induces autophagy to improve liver regeneration in non-alcoholic fatty liver mice”.

description: <pre>This study proved that autophagy plays a key role in promoting liver regeneration, alleviating liver injury, and prolonging mice's survival after PH. The pharmacological regulation of verapamil on autophagy effectively promoted liver regeneration, hepatocyte production, and survival in mice and reduced liver injury in mice after PH. Autophagy is expected to become a key target for NAFLD treatment and open up a new direction for the prevention and treatment of obesity, T2DM, Mets, and other diseases.</pre>
DOI: 10.4121/16620577
title: Data supplementary to the manuscript: “Verapamil induces autophagy to improve liver regeneration in non-alcoholic fatty liver mice”.

description: <pre>This study proved that autophagy plays a key role in promoting liver regeneration, alleviating liver injury, and prolonging mice's survival after PH. The pharmacological regulation of verapamil on autophagy effectively promoted liver regeneration, hepatocyte production, and survival in mice and reduced liver injury in mice after PH. Autophagy is expected to become a key target for NAFLD treatment and open up a new direction for the prevention and treatment of obesity, T2DM, Mets, and other diseases.</pre>
DOI: 10.4121/14994588.v1
title: Whiffle LES runs over 8x8 km^2 by 5.2 km domain around Cabauw, The Netherlands.

description: In our study we looked at the mixing impact on wind and momentum fluxes in relation to the cloud conditions overhead. We used both LES and observations in a nine-year long time-series, which is unique for LES. The following LES output files are provided between 2009 -- 2017:<br>Large Eddy Simulations for researching wind mixing at Cabauw run with GPU Resident Atmospheric Simulation Platform (GRASP) developed by Whiffle. For each year of simualtions, the four files are available: <br>1. Meteo values of at the location of the Cabauw tower<br>2. Domain and hourly averaged profiles of, among others, temperature, wind, humidity and their fluxes.<br>3. Slices of the integrated liquid water path for every 10 min4. Conditionally sampled average profiles for: <br> - updraughts (w&gt;0) <br> - cloudy updraughts (w&gt;0 and ql &gt;0 ) - cloud (ql&gt;0) - cloud core (w&gt;0, ql &gt;0 and th_v' &gt; 0)<br>
DOI: 10.4121/13089581.v1
title: Data of experimental study on dynamic stall control using vortex generators

description: This dataset includes experimental data for an oscillating, pitching airfoil. This data set is used to demonstrate the use of VGs to control and suppress dynamic stall. The details of the experiment and data analysis are provided in: D. De Tavernier, C. Ferreira, A. Viré, et al., Controlling dynamic stall using vortex generators on a wind turbine airfoil, Renewable Energy, 2021, 172:1194-1211.
DOI: 10.4121/14994588
title: Whiffle LES runs over 8x8 km^2 by 5.2 km domain around Cabauw, The Netherlands.

description: In our study we looked at the mixing impact on wind and momentum fluxes in relation to the cloud conditions overhead. We used both LES and observations in a nine-year long time-series, which is unique for LES. The following LES output files are provided between 2009 -- 2017:<br>Large Eddy Simulations for researching wind mixing at Cabauw run with GPU Resident Atmospheric Simulation Platform (GRASP) developed by Whiffle. For each year of simualtions, the four files are available: <br>1. Meteo values of at the location of the Cabauw tower<br>2. Domain and hourly averaged profiles of, among others, temperature, wind, humidity and their fluxes.<br>3. Slices of the integrated liquid water path for every 10 min4. Conditionally sampled average profiles for: <br> - updraughts (w&gt;0) <br> - cloudy updraughts (w&gt;0 and ql &gt;0 ) - cloud (ql&gt;0) - cloud core (w&gt;0, ql &gt;0 and th_v' &gt; 0)<br>
DOI: 10.4121/13089581.v2
title: Data of experimental study on dynamic stall control using vortex generators

description: This dataset includes experimental data for an oscillating, pitching airfoil. This data set is used to demonstrate the use of VGs to control and suppress dynamic stall. The details of the experiment and data analysis are provided in: D. De Tavernier, C. Ferreira, A. Viré, et al., Controlling dynamic stall using vortex generators on a wind turbine airfoil, Renewable Energy, 2021, 172:1194-1211.
DOI: 10.4121/14565228.v1
title: Data underlying the paper: InSbAs two-dimensional electron gases as a platform for topological superconductivity

description: This is the raw data that belongs to the manuscript 'InSbAs two-dimensional electron gases as a platform for topological superconductivity'.
DOI: 10.4121/14565228.v2
title: Data underlying the paper: InSbAs two-dimensional electron gases as a platform for topological superconductivity

description: This is the raw data that belongs to the manuscript 'InSbAs two-dimensional electron gases as a platform for topological superconductivity'.
DOI: 10.4121/14565228
title: Data underlying the paper: InSbAs two-dimensional electron gases as a platform for topological superconductivity

description: This is the raw data that belongs to the manuscript 'InSbAs two-dimensional electron gases as a platform for topological superconductivity'.
DOI: 10.4121/16587095.v1
title: Data to produce the results of the publication: “Reducing the Soleus Stretch Reflex with Conditioning: Exploring Game- and Impedance-based Biofeedback”

description: The work presents the exploration of the feasibility of two forms of biofeedback to obtain a within-session reduction of the Soleus stretch reflex with conditioning. First, we explored the feasibility of gamification and second, the feasibility of combined game- and impedance-based biofeedback.<br>In short, we showed feasibility of EMG-, game-based biofeedback within the operant conditioning paradigm, which calls for further research on gamification of conditioning paradigms to obtain improved participant motivation and engagement, while achieving long-term conditioning effects. Contrarily, the use of impedance-, game-based biofeedback did not result in a feasible conditioning paradigm, thus the time-intensiveness and slow learning curve of the conditioning paradigm remain an open challenge.
DOI: 10.4121/16587095
title: Data to produce the results of the publication: “Reducing the Soleus Stretch Reflex with Conditioning: Exploring Game- and Impedance-based Biofeedback”

description: The work presents the exploration of the feasibility of two forms of biofeedback to obtain a within-session reduction of the Soleus stretch reflex with conditioning. First, we explored the feasibility of gamification and second, the feasibility of combined game- and impedance-based biofeedback.<br>In short, we showed feasibility of EMG-, game-based biofeedback within the operant conditioning paradigm, which calls for further research on gamification of conditioning paradigms to obtain improved participant motivation and engagement, while achieving long-term conditioning effects. Contrarily, the use of impedance-, game-based biofeedback did not result in a feasible conditioning paradigm, thus the time-intensiveness and slow learning curve of the conditioning paradigm remain an open challenge.
DOI: 10.4121/16577627.v1
title: EgoRoutine: Topic modelling for routine discovery from egocentric photo-streams

description: Developing tools to understand and visualize lifestyle is of high interest when addressing the improvement of habits and well-being of people. Routine, defined as the usual things that a person does daily, helps describe the individuals’ lifestyle. With this paper, we are the first ones to address the development of novel tools for automatic discovery of routine days of an individual from his/her egocentric images. In the proposed model, sequences of images are firstly characterized by semantic labels detected by pre-trained CNNs. Then, these features are organized in temporal-semantic documents to later be embedded into a topic models space. Finally, Dynamic-Time-Warping and Spectral-Clustering methods are used for final day routine/non-routine discrimination. Moreover, we introduce a new <em>EgoRoutine</em>-dataset, a collection of 104 egocentric days with more than 100.000 images recorded by 7 users. Results show that routine can be discovered and behavioural patterns can be observed.<br>Published in:Estefania Talavera, Carolin Wuerich, Nicolai Petkov, Petia Radeva, Topic modelling for routine discovery from egocentric photo-streams, Pattern Recognition, Volume 104, 2020, 107330, ISSN 0031-3203, https://doi.org/10.1016/j.patcog.2020.107330.
DOI: 10.4121/16577627
title: EgoRoutine: Topic modelling for routine discovery from egocentric photo-streams

description: Developing tools to understand and visualize lifestyle is of high interest when addressing the improvement of habits and well-being of people. Routine, defined as the usual things that a person does daily, helps describe the individuals’ lifestyle. With this paper, we are the first ones to address the development of novel tools for automatic discovery of routine days of an individual from his/her egocentric images. In the proposed model, sequences of images are firstly characterized by semantic labels detected by pre-trained CNNs. Then, these features are organized in temporal-semantic documents to later be embedded into a topic models space. Finally, Dynamic-Time-Warping and Spectral-Clustering methods are used for final day routine/non-routine discrimination. Moreover, we introduce a new <em>EgoRoutine</em>-dataset, a collection of 104 egocentric days with more than 100.000 images recorded by 7 users. Results show that routine can be discovered and behavioural patterns can be observed.<br>Published in:Estefania Talavera, Carolin Wuerich, Nicolai Petkov, Petia Radeva, Topic modelling for routine discovery from egocentric photo-streams, Pattern Recognition, Volume 104, 2020, 107330, ISSN 0031-3203, https://doi.org/10.1016/j.patcog.2020.107330.
DOI: 10.4121/16592420.v1
title: EgoFoodPlaces: Hierarchical Approach to Classify Food Scenes in Egocentric Photo-Streams

description: Recent studies have shown that the environment where people eat can affect their nutritional behaviour. In this work, we provide automatic tools for personalised analysis of a person's health habits by the examination of daily recorded egocentric photo-streams. Specifically, we propose a new automatic approach for the classification of food-related environments, that is able to classify up to 15 such scenes. In this way, people can monitor the context around their food intake in order to get an objective insight into their daily eating routine. We propose a model that classifies food-related scenes organized in a semantic hierarchy. Additionally, we present and make available a new egocentric dataset composed of more than 33000 images recorded by a wearable camera, over which our proposed model has been tested. Our approach obtains an accuracy and F-score of 56% and 65%, respectively, clearly outperforming the baseline methods.<br>Published in:E. T. Martinez, M. Leyva-Vallina, M. M. K. Sarker, D. Puig, N. Petkov and P. Radeva, "Hierarchical Approach to Classify Food Scenes in Egocentric Photo-Streams," in <em>IEEE Journal of Biomedical and Health Informatics</em>, vol. 24, no. 3, pp. 866-877, March 2020, doi: 10.1109/JBHI.2019.2922390.<br>
DOI: 10.4121/16592420
title: EgoFoodPlaces: Hierarchical Approach to Classify Food Scenes in Egocentric Photo-Streams

description: Recent studies have shown that the environment where people eat can affect their nutritional behaviour. In this work, we provide automatic tools for personalised analysis of a person's health habits by the examination of daily recorded egocentric photo-streams. Specifically, we propose a new automatic approach for the classification of food-related environments, that is able to classify up to 15 such scenes. In this way, people can monitor the context around their food intake in order to get an objective insight into their daily eating routine. We propose a model that classifies food-related scenes organized in a semantic hierarchy. Additionally, we present and make available a new egocentric dataset composed of more than 33000 images recorded by a wearable camera, over which our proposed model has been tested. Our approach obtains an accuracy and F-score of 56% and 65%, respectively, clearly outperforming the baseline methods.<br>Published in:E. T. Martinez, M. Leyva-Vallina, M. M. K. Sarker, D. Puig, N. Petkov and P. Radeva, "Hierarchical Approach to Classify Food Scenes in Egocentric Photo-Streams," in <em>IEEE Journal of Biomedical and Health Informatics</em>, vol. 24, no. 3, pp. 866-877, March 2020, doi: 10.1109/JBHI.2019.2922390.<br>
DOI: 10.4121/16592756.v1
title: Computational data of Sustainability reporting indicators and Economic value added of listed manufacturing companies in Nigeria

description: This data are computations of the sustainability performance indicators and the economic value added of listed manufacturing companies in Nigeria.The data were obtained from the annual report of companies under review and used to analyze the effect of Sustainability reporting on shareholders wealth maximization.The sustainability performance indicators were derived through content analysis; while Economic value added was derived using the EVA formula.
DOI: 10.4121/16592756
title: Computational data of Sustainability reporting indicators and Economic value added of listed manufacturing companies in Nigeria

description: This data are computations of the sustainability performance indicators and the economic value added of listed manufacturing companies in Nigeria.The data were obtained from the annual report of companies under review and used to analyze the effect of Sustainability reporting on shareholders wealth maximization.The sustainability performance indicators were derived through content analysis; while Economic value added was derived using the EVA formula.
DOI: 10.4121/16571879.v1
title: Executive Compensation Data Set

description: This paper using panel data of 2008-2019 Shanghai and Shenzhen A-share listed companies as the research sample and employing the multiple regression method to tests the relationship between executive compensation incentives and R&D investment of listed companies in China, further investigates the path of the relationship between the two and the influence of government subsidy to the relationship. In this paper, the selected samples are excluded according to the following criteria: ①Companies with incomplete data on financial indicators and corporate governance indicators are excluded. ②Eliminate companies with negative asset-liability ratio or greater than 1. ③Exclude companies in the financial and insurance industry. ④Exclude listed companies less than 1 year. ⑤Exclude companies containing S, ST and *ST. ⑥Exclude the companies with extreme sample data. The risk-taking data involved in this paper came from the WIND database. Other data come from the CSMAR database.
DOI: 10.4121/16571879
title: Executive Compensation Data Set

description: This paper using panel data of 2008-2019 Shanghai and Shenzhen A-share listed companies as the research sample and employing the multiple regression method to tests the relationship between executive compensation incentives and R&D investment of listed companies in China, further investigates the path of the relationship between the two and the influence of government subsidy to the relationship. In this paper, the selected samples are excluded according to the following criteria: ①Companies with incomplete data on financial indicators and corporate governance indicators are excluded. ②Eliminate companies with negative asset-liability ratio or greater than 1. ③Exclude companies in the financial and insurance industry. ④Exclude listed companies less than 1 year. ⑤Exclude companies containing S, ST and *ST. ⑥Exclude the companies with extreme sample data. The risk-taking data involved in this paper came from the WIND database. Other data come from the CSMAR database.
DOI: 10.4121/14988084.v1
title: Images of the Port Variable Laparoscopic Environment Simulation Box Trainer

description: Images of the Port Variable Laparoscopic Environment Simulation Box Trainer. Here used in an open configuration as used in the SATA-LRS study. <br>The multiple-port box trainer contains a monitor, 3-DOF linear port sensor and a 5-DOF linear/torque task-bed. This configuration is loaded with a 5-port task with sensitive elements for instrument interaction detection using an Arduino Nano.
DOI: 10.4121/14988084
title: Images of the Port Variable Laparoscopic Environment Simulation Box Trainer

description: Images of the Port Variable Laparoscopic Environment Simulation Box Trainer. Here used in an open configuration as used in the SATA-LRS study. <br>The multiple-port box trainer contains a monitor, 3-DOF linear port sensor and a 5-DOF linear/torque task-bed. This configuration is loaded with a 5-port task with sensitive elements for instrument interaction detection using an Arduino Nano.
DOI: 10.4121/16440330.v1
title: Primary User Datasets of the SATA-LRS, a modular steerable hand-held laparoscopic surgical instrument

description: A collection of datasets of two user experiments used to validate the SATA-LRS modular steerable hand-held laparoscopic surgical instrument.<br>Task-1: the repeated dis- and re-assembly of the deviceTask-2: the use of the device in a steering experiment
DOI: 10.4121/16440330
title: Primary User Datasets of the SATA-LRS, a modular steerable hand-held laparoscopic surgical instrument

description: A collection of datasets of two user experiments used to validate the SATA-LRS modular steerable hand-held laparoscopic surgical instrument.<br>Task-1: the repeated dis- and re-assembly of the deviceTask-2: the use of the device in a steering experiment