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The attached file is a supplement to the author’s doctoral dissertation at https://circle.library.ubc.ca/handle/2429/71827.
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These guidelines aim to maximize the efficiency of data-sharing collaborations in pediatric sepsis research by facilitating the standardization of data collection in predictors captured in future studies.
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Flow activities (e.g. sports and gaming) have been associated with positive affect and prolonged engagement. In the gambling field, modern electronic gaming machines (EGMs, including modern slot machines) have drawn concern as a potentially flow inducing activity that may be associated with gambling-related harms. Current research has heavily relied on self-reported flow, and further insights may be afforded by physiological methods. We present data from three separate experiments in which self reported gambling flow and cardiac pre-ejection period (PEP; a measure of sympathetic nervous system arousal) were examined. Male undergraduate participants gambled on a genuine EGM in a laboratory setting for a period of at least 15 min, and completed the Flow subscale of the game experience questionnaire (GEQ). Aggregated data were analyzed using multilevel regression. Although EGM gambling was not associated with significant changes in PEP across participants, we found that self-reported flow states were associated with significant decreases in PEP during the first five minutes of EGM use. Thus, participants who experienced flow showed a greater sympathetic nervous system response to the onset of gambling. Though these effects were consistent in experiments 1 and 2, in experiment 3 the effect was inverted during the same time window. We conclude that flow during EGM gambling appears to be associated with early changes in sympathetic nervous system activity, but stress that more research is needed to characterize boundary conditions and moderating factors.
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This dataset comprises the source code to reproduce the 3D micro-mapping tool for plane adjustment at subsidence stations. In this project, users adjust a plane (height and orientation) at the positions of fixed poles, so-called subsidence stations, to provide information on the ground surface in 3D point clouds. The web-based tool was used to quantify vertical displacement of the ground surface from multitemporal Terrestrial Laser Scanning data acquired at two sites in the permafrost-underlain tundra at Trail Valley Creek, NWT, Canada (https://www.uni-heidelberg.de/permasar). A video of the online tool is provided in addition to the source code and data.
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  • Dataset
The attached files are supplements to the author’s doctoral dissertation at https://circle.library.ubc.ca/handle/2429/72922
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  • Dataset
This dataset contains model output, in netCDF format, from an MITgcm configuration used to simulate an upwelling event in an idealized submarine canyon. The upwelling event lasts 9 days and output is saved every half day. Output for two experiments (AST and BAR) with four runs each is provided. These results are the basis of the publication The impact of initial tracer profile on the exchange and on-shelf distribution of tracers induced by a submarine canyon which is under revision. The preprint is available in the ESSOAr repository.
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  • Dataset
The results of three runs of a 230-Th model coupled to the Arctic Ocean model ANHA4. These results are the basis of the publication Yu et al, Modeling dissolved and particulate 230-Th in the Canada Basin: Implications for recent changes in particle flux and intermediate circulation. Accepted by the Journal of Geophysical Research, Oceans in January 2020. The four runs are: * BaseRun.nc: base run with scavenging, variation in currents and variation in ice * Exp1.nc: base run but no extra bottom boundary scavenging * Exp2.nc : base run but with the circulation from 2002 used for every year * Exp3.nc : base run but with the ice field (used for particle flux) from 2002 used for every year
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Data, Maps, and Supplementary Information for the manuscript "Modelling the Putative Ancient Distribution of the Coastal Rock Pool Mosquito Aedes togoi
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A method for detecting noise in automatically annotated sequence-labelled data, combining MACE (Hovy et al. 2013) with Active Learning.
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A German UD Twitter treebank, with >12,000 tokens from 519 tweets, annotated in the Universal Dependencies framework
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  • Dataset