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Replication Data for: Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars
No full textThis dataset includes the scripts to reproduce the models presented in the paper. The cleaned data used for the analyses is also available.
Abstract of the article:
Precision farming technology, including GPS collars with biologging, has revolutionized remote livestock monitoring in extensive grazing systems. High resolution accelerometry can be used to infer the behavior of an animal. Previous behavioral classification studies using accelerometer data have focused on a few key behaviors and were mostly conducted in controlled situations. Here, we conducted behavioral observations of 38 beef cows (Hereford, Limousine, Charolais, Simmental/NRF/Hereford mix) free-ranging in rugged, forested areas, and fitted with a commercially available virtual fence collar (Nofence) containing a 10Hz tri-axial accelerometer. We used random forest models to calibrate data from the accelerometers on both commonly documented (e.g., feeding, resting, walking) and rarer (e.g., suckling calf, head butting, allogrooming) behaviors. Our goal was to assess pre-processing decisions including different running mean intervals (smoothing window of 1, 5, or 20 seconds), collar orientation and feature selection (orientation-dependent versus orientation-independent features). We identified the 10 most common behaviors exhibited by the cows. Models based only on orientation-independent features did not perform better than models based on orientation-dependent features, despite variation in how collars were attached (direction and tightness). Using a 20 seconds running mean and orientation-dependent features resulted in the highest model performance (model accuracy: 0.998, precision: 0.991, and recall: 0.989). We also used this model to add 11 rarer behaviors (each 98%). Our study suggests that the accelerometers in the Nofence collars are suitable to identify the most common behaviors of free-ranging cattle. The results of this study could be used in future research for understanding cattle habitat selection in rugged forest ranges, herd dynamics, or responses to stressors such as carnivores, as well as to improve cattle management and welfare. </p
Replication Data for: Label-free superior contrast with c-band ultra-violet extinction microscopy
No full textThis repository contains underlying image data, which was used for figures in the manuscript and MATLAB code to generate extinction coefficient maps as well as MATLAB code to determine the direction of "half-ring" illumination from differential phase contrast (DPC) raw data.Summary from the manuscript:
We presented a C-band UV microscope operating at 275 nm, which provides high-contrast high-resolution label-free microscopy. Through a series of oblique illuminations, we showed differential phase contrast (DPC) illumination in this wavelength regime and achieved a 7- to 300-fold improvement over other methods. The phase retrieval algorithm of quantitative DPC microscopy permitted us to calculate extinction coefficients within liver sinusoidal endothelial cells (LSECs). With a resolution down to 215 nm, we could resolve individual fenestrations within their sieve plates, and demonstrated the quantitative character extinction coefficient imaging. The UVC illumination allowed us to utilize intrinsic fluorescence from proteins and amino acids as an orthogonal imaging modality. We exploited this in performing correlative label-free imaging with both autofluorescence and differential phase contrast
Data of the i-MASTER project: A novel initiative in maritime education and training experience
No full texti-MASTER datasets.
The i-MASTER project is an EU funded project under grant agreement No. 101060107. The project's objective is to study and develop an AI-based intelligent learning system with learning analytics and adaptive learning function for students engaged in both remote (home-based) and on-site maritime simulator education and training. The project will give insights to simulation performances. The research will work on digitalised navigational performance assessments to provide unbiased student performance evaluation and to find new ways for students and instructors to understand the learning progress.
The project has a series of deliverables to reach the project objectives. Many deliverables have collected data as part of the studies of the respective deliverables. The data collected are part of simulation scenarios, interviews, questionnaires etc. The i-MASTER project is an open to public project.The data collected are stored in a database and made available to the public and researchers for re-use. Each deliverable has a ReadMe file to make it easy for users to understand the link between the data and project
Replication Data for: "eHealth literacy among hospital health care providers: a systematic review"
No full texteHealth literacy is a key concept in the implementation of eHealth resources. However, most eHealth literacy definitions and frameworks are designed from the perceptive of the individual receiving eHealth care, which do not include health care providers’ eHealth literacy or acceptance of delivering eHealth resources.
Systematic search strategies were developed in order to identify existing research on eHealth literacy domains and measurements and identify eHealth literacy scores and associated factors among hospital health care providers
Replication data for : Metasurface supporting quasi-BIC for optical trapping and Raman-spectroscopy of biological nanoparticles
No full textOptical trapping combined with Raman spectroscopy have opened new possibilities for analyzing biological nanoparticles. Conventional optical tweezers have proven successful for trapping of a single or a few particles. However, the method is slow and cannot be used for the smallest particles. Thus, it is not adapted to analyze a large number of nanoparticles, which is necessary to get statistically valid data. Here, we propose quasi-bound states in the continuum (quasi-BICs) in a silicon nitride (Si3N4) metasurface to trap smaller particles and many simultaneously. We use COMSOL Multiphysics version 6.0 for modelling and optimization of the proposed metasurface. The quasi-BIC metasurface contains multiple zones with high field-enhancement (‘hotspots’) at a wavelength of 785 nm, where a single nanoparticle can be trapped at each hotspot. We numerically investigate the optical trapping of a type of biological nanoparticles, namely extracellular vesicles (EVs), and study how their presence influences the resonance behavior of the quasi-BIC. It is found that perturbation theory and a semi-analytical expression gives good estimates for the resonance wavelength and minimum of the potential well, as function of the particle radius. This wavelength is slightly shifted relative to the resonance of the metasurface without trapped particles. The simulations show that the Q-factor can be increased by using a thin metasurface. The thickness of the layer and the asymmetry of the unit cell can thus be used to get a high Q-factor. Our findings show the tight fabrication tolerances necessary to make the metasurface. If these can be overcome, the proposed metasurface can be used for a lab-on-a-chip for mass-analysis of biological nanoparticles
Replication Data for: The increase of an allelopathic and unpalatable plant undermines Reindeer pasture quality, diversity and current management in the Norwegian tundra
No full textThese datasets contain original data on biomass and extent of vascular plant growth forms in plots from a range of sites in northern Fennoscandia collected in 2003 and in 2020. Main findings are presented in the following abstract:
Ongoing Arctic greening can increase productivity and reindeer pasture quality in the tundra. However, greening may also entail proliferation of unpalatable species, with consequences for pastoral social-ecological systems. Here we show extensive greening across 20 reindeer districts in Norway between 2003 and 2020, which has reduced pasture diversity. The allelopathic, evergreen dwarf-shrub crowberry increased its biomass by 60%, with smaller increases of deciduous shrubs and no increase in the most species rich growth forms (i.e., forbs and graminoids). There was no evidence for higher reindeer densities promoting crowberry. The current management decision-making process aims at sustainable pasture management but does not explicitly account for pasture changes and reduced diversity. Large-scale shifts towards evergreening and increased allelopathy may thus undermine the resource base for this key Arctic herbivore and the pastoral social-ecological system. Management that is sensitive to changes in pasture diversity could avoid mismanagement of a social-ecological system in transition
Replication data and code for: Measuring renewables' impact on biosphere integrity: A review
No full textThe contents of this dataset is divided into two main sections:
Files documenting the literature review process of search query development, screening results, and the form used during data extraction. These files are found under "data_supplementary".
Data files used in the analysis, using the R programming language in the form of R-markdown files. These files are found under "R-project".
The aim of the related publication was to review the indicators used in peer-reviewed research to measure impacts on biosphere integrity from renewable energy generation and utilization, and categorize them into biosphere approaches defined by the authors
Experimental data for the Nanoname project
No full textThis dataset contains experimental data collected for the Nanoname project: "Improving sodium ion battery performance with Nanostructured Na-metallate anodes". The dataset contains data from electrochemical and structural characterisation of Bi-metallates (mainly Bi2MoO6 and BiFeO3) as an anode materials for Na-ion batteries
Replication Data for Grammatical Gender in Norwegian Dialects: Variation, Acquisition and Change (GenVAC)
No full text[Dataset abstract:]
The dataset consists of data related to investigations of grammatical gender across multiple Norwegian dialects. The data has been collected as part of the GenVAC project, funded by the Research Council of Norway 2020-2025, grant number 301094. The goal of GenVAC is to study changes in grammatical gender through large-scale experimental studies. In particular, it scrutinizes to what extent feminine gender is disappearing from Norwegian dialects based on four production experiments and eye-tracking studies. The data will be made available towards the end of the project.
In addition, this dataset also includes files that enable scholars to use our methodology. The PowerPoint slides are available as original files and as pdfs for all four experiments. The background questionnaire has also been included, alongside a brief description of how to conduct the four experiments. These files are made available immediately.
Since this project focuses on Norwegian, the accompanying article alongside all the material in this dataset are in Norwegian. Since this kind of work is impossible to do without knowing Norwegian, the material has not been translated.</p
Replication data for: Collection and statistical analysis of a fixed-text keystroke dynamics authentication data set
No full textDATASET MIGRATED FROM FIGSHARE: Data set for keystroke dynamics authentication benchmarking and research, containing 6 passwords typed by a wide set of people, containing a large set of "attackers" and a smaller set of "legitimate users". This data set was collected for the paper "Collection and statistical analysis of a fixed-text keystroke dynamics authentication data set" for the CSNet23 conference.Article Abstract :Keystroke dynamics authentication is a promising method of improving account security with minimal detriment for user convenience. While there is an abundance of research, there is a lack of available data sets. In this study, data sets for keystroke dynamics authentication were collected for a set of 6 passwords from a group of participants, and a correlation algorithm was developed to analyze and use these data sets for authentication. The experiments aim to produce data for keystroke dynamics authentication benchmarking, and to show the effect of typing speed and consistency, password length and entropy on prediction accuracy. Through simple correlation methods, the authors achieve an Equal Error Rate varying between a range of 2.57% and 29.7%. These result give insight into what may cause the accuracy to vary depending on the person and the password.</p