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205 results for “explicit”
Instructor Perspectives on APA Style in Nursing Education: Implicit and Explicit Value
<p><strong>OBJECTIVE:</strong> Disparities in how nursing faculty teach APA Style can confuse students and the librarians who help them. To clarify faculty expectations of and approaches to APA </p><p>Style, this study seeks to answer the following questions: (1) What do nursing faculty perceive as the impact or value of APA Style? (2) How do nursing faculty teach and grade APA Style? By revealing the unspoken assumptions about APA Style and the value it adds to nursing education, it is hoped that health sciences librarians can more intentionally and effectively support this aspect of the nursing curriculum.</p><p><strong>METHODS: </strong>A mixed-methods study was designed to investigate potential gaps between nursing instructors' expectations for APA and their teaching/grading practices. The study incorporated an online survey of 75 nursing faculty at 14 Carnegie institutions with nursing programs, as well as qualitative interviews with 12 faculty at those institutions. A grounded theory approach was used to uncover salient themes.</p><p><strong>RESULTS:</strong> Nursing instructors consistently emphasized the importance of APA for referencing/in-text citations in both the survey and the interviews. When discussing the value of APA Style in nursing education, interviewees stressed APA Style as essential in developing professional nursing communication skills and evidence-based practice. However, faculty expectations for students' APA skills were not in line with their teaching and grading practices.</p><p><strong>CONCLUSION:</strong> Given the wide range of reporting teaching and grading practices for APA Style, nursing programs should work to clarify expectations for APA Style, and standardize how it is taught.</p>
Explicit FE simulation results for orthopedic screw-bone interaction, for different screw geometries and bone quality
<p>The dataset disclosed herein was employed to train artificial neural network surrogate models, specifically for tasks related to screw optimization. Please read "_readMe.txt" before using.</p>
Modeling the effect of explicit vs implicit representation of grazing on ecosystem carbon and nitrogen cycling in response to elevated carbon dioxide and warming in arctic tussock tundra, Alaska - Dataset A
We use a simple model of coupled carbon and nitrogen cycles in terrestrial ecosystems to examine how explicitly representing grazers versus having grazer effects implicitly aggregated in with other biogeochemical processes in the model alters predicted responses to elevated carbon dioxide and warming. The aggregated approach can affect model predictions because grazer-mediated processes can respond differently to changes in climate from the processes with which they are typically aggregated. We use small-mammal grazers in arctic tundra as an example and find that the typical three-to-four-year cycling frequency is too fast for the effects of cycle peaks and troughs to be fully manifested in the ecosystem biogeochemistry. We conclude that implicitly aggregating the effects of small-mammal grazers with other processes results in an underestimation of ecosystem response to climate change relative to estimations in which the grazer effects are explicitly represented. The magnitude of this underestimation increases with grazer density. We therefore recommend that grazing effects be incorporated explicitly when applying models of ecosystem response to global change.
Modeling the effect of explicit vs implicit representation of grazing on ecosystem carbon and nitrogen cycling in response to elevated carbon dioxide and warming in arctic tussock tundra, Alaska - Dataset B
We use a simple model of coupled carbon and nitrogen cycles in terrestrial ecosystems to examine how explicitly representing grazers versus having grazer effects implicitly aggregated in with other biogeochemical processes in the model alters predicted responses to elevated carbon dioxide and warming. The aggregated approach can affect model predictions because grazer-mediated processes can respond differently to changes in climate from the processes with which they are typically aggregated. We use small-mammal grazers in arctic tundra as an example and find that the typical three-to-four-year cycling frequency is too fast for the effects of cycle peaks and troughs to be fully manifested in the ecosystem biogeochemistry. We conclude that implicitly aggregating the effects of small-mammal grazers with other processes results in an underestimation of ecosystem response to climate change relative to estimations in which the grazer effects are explicitly represented. The magnitude of this underestimation increases with grazer density. We therefore recommend that grazing effects be incorporated explicitly when applying models of ecosystem response to global change.
2007 Environmental Protection Agency (EPA) National Lakes Assessment dataset plus derived data and additional spatially explicit ancillary environmental data.
Lake water quality is known to be affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology conceptual framework using a random forest algorithm on large, national-scale, spatially explicit dataset, the United States Environmental Protection Agency 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity).
An Explicit Primitive Conservative Solver for the Euler Equations with Arbitrary Equation of State: Dataset
<p>Contains the files for all simulations related to the publication:</p> <p>"An Explicit Primitive Conservative Solver for the Euler Equations with Arbitrary Equation of State: Dataset"</p> <p>paper: https://doi.org/10.1016/j.compfluid.2024.106340</p> <p>pre-print: https://doi.org/10.48550/arXiv.2404.07710</p>
Supplementary File: Entertainment interspersed with propaganda: How non-legacy-news accounts deliver explicitly political content to mass audiences on Russia's most popular social network VK
<p>Supplementary file and dataset for the paper "Entertainment interspersed with propaganda: How non-legacy-news accounts deliver explicitly political content to mass audiences on Russia’s most popular social network VK"</p>
MCR LTER: Coral Reef: Turbinaria CHN from a spatially explicit sampling campaign in lagoons of Moorea, French Polynesia
Nutrients are important for ecosystem structure and community dynamics. To quantify time-integrated patterns of nutrient regimes in tropical lagoon ecosystems, concentrations of nitrogen, hydrogen, and carbon were measured from tissues of the macroalga Turbinaria ornata collected in lagoons around Moorea, French Polynesia in 2016, 2017, and annually starting in 2019. These sampling periods initially corresponded with distinct seasonal shifts in rainfall and wave forcing and later focused on the rainy season. Results showed that N enrichment was highest nearshore in fringing reef habitats, as well as in bays and at reef passes.
Implicit and explicit measurement of pre-service teachers' attitudes toward autism spectrum disorder
<p>This database corresponds to the results of the paper:</p><p>Lacruz-Pérez, I., Pastor-Cerezuela, G., Tárraga-Mínguez, R. & Lüke, T. (2023): Implicit and explicit measurement of pre-service teachers' attitudes toward autism spectrum disorder, <i>European Journal of Special Needs Education</i>. <a href="https://doi.org/10.1080/08856257.2023.2185858">https://doi.org/10.1080/08856257.2023.2185858</a> </p><p> </p>
Global spatially explicit critical nitrogen surpluses and critical nitrogen inputs, and their exceedances
<p>Data files belonging to manuscript:</p> <p>Schulte-Uebbing, LF, AHW Beusen, AF Bouwman & W de Vries (2022): From planetary to regional boundaries for agricultural nitrogen pollution. <strong>Nature</strong>, Vol 610 (7932), https://doi.org/10.1038/s41586-022-05158-2</p> <p>* Input datafiles: Contains complete set of input files used in the calculations of global, spatially explicit critical nitrogen surpluses and critical nitrogen inputs. All input files are output from the IMAGE-GNM model. For further information on IMAGE-GNM, see: Beusen, A. H. W., Van Beek, L. P. H., Bouwman, A. F., Mogollón, J. M., & Middelburg, J. J. (2015). Coupling global models for hydrology and nutrient loading to simulate nitrogen and phosphorus retention in surface water - Description of IMAGE-GNM and analysis of performance. Geoscientific Model Development, 8(12), 4045–4067. https://doi.org/10.5194/gmd-8-4045-2015</p> <p>* Output datafiles: Selection of output datafiles, supporting results presented in the paper. </p> <p>For more information, see file "README.xlsx".</p>
Butcher's tableaux of the optimized explicit Runge-Kutta schemes for high-order collocated discontinuous Galerkin methods for compressible fluid dynamics
<p>This folder contains the Butcher's tableaux of the optimized explicit Runge-Kutta schemes for high-order collocated discontinuous Galerkin methods for compressible fluid dynamics presented in Al Jahdali et al., "Optimized explicit Runge--Kutta schemes for high-order collocated discontinuous Galerkin methods for compressible fluid dynamics," Computers & Mathematics with Applications, 2022.</p> <p>Specifically,</p> <p><a href="https://zenodo.org/api/files/754318a5-0881-4252-9059-086da4607b49/Butcher_coefficients_ADV.txt">Butcher_coefficients_ADV.txt</a> contains the Butcher's tableaux of the explicit Runge-Kutta schemes optimized using the spectra of the 2D advection equation.</p> <p><a href="https://zenodo.org/api/files/754318a5-0881-4252-9059-086da4607b49/Butcher_coefficients_IEV.txt">Butcher_coefficients_IEV.txt</a> contains the Butcher's tableaux of the explicit Runge-Kutta schemes optimized using the spectra of the isentropic vortex propagation for the compressible Euler equations.</p> <p> </p> <p> </p> <p> </p>
Artifact for the ESEC/FSE 2019 Paper: Effects of Explicit Feature Traceability on Program Comprehension
<p>This is the artifact for our ESEC/FSE 2019 paper "Effects of Explicit Feature Traceability on Program Comprehension", providing 1) the experiment as reusable source code and 2) the anonymized results of our experiment. For more details on how to use the source code and interpret the data, please refer to the readme file.</p>
Data and code from: Evaluating spatially explicit density estimates of unmarked wildlife detected by remote cameras.
<p>Detection data from American black bears and code used in "Evaluating spatially explicit density estimates of unmarked wildlife detected by remote cameras" published in the Journal of Applied Ecology (Evans & Rittenhouse 2018). Unmarked detection data was collected using remote cameras in northwest Connecticut in 2014, and individual detection data was determined from unique genotypes obtained from non-invasive hair snares constructed at camera sampling locations.</p> <p>EN14.rds contains detection data as an R list:</p> <p>$y (num): J (sites) x K (occasions) matrix containing detection counts</p> <p>$X (int): 2 x J matrix of site coordinates</p> <p>$xlims (num): bounding x-coordinates</p> <p>$ylims (num): bounding y-coordinates</p> <p>$M (int): upper bound for super population of individuals</p> <p>$nTraps (int): number of sampling sites (J)</p> <p>$nReps (int): number of MCMC interations</p> <p>$forest (num): vector of site-specific covariates</p> <p>$mark (int): K x I matrix storing site numbers at which individual (i) was detected on occasion k</p> <p>FullModel.R provides functions used to fit constant density models to unmarked detections incorporating covariates of detection probability.</p> <p>partialID.R provides functions and code used to estimate density from mixtures of marked and unmarked detection data</p> <p>VariableDensity.R provides functions and code used to fit variable density models to unmarked detection data incorporating spatial covariates of density.</p> <p> </p>
Setting files from: Spatially explicit paleogenomic simulations support cohabitation with limited admixture between Bronze Age Central European populations.
<p><strong>Simulated Data and Custom Scripts</strong></p> <p>This dataset release permits to simulate the expansion of populations from the Pontic Steppes to Central Europe with the version of SPLATCHE3 which is included. There are 2 main zipped folders: i) the one called "SPLATCHE3executableAndSettings" contains a "ReadMe.txt" file that contains all required information to make the simulations: the resulting ".prop" file contains proportions of genomic ancestry of the P2 layer, ancestry from P1 layer is equal to 1-(proportion from P2) ; ii) the other one called "HowToMakeFigure2" contains the R script and the tables necessary to reproduce Figure 2. See Rio J, Quilodrán CS & Currat M., Communications Biology (2021), for background.</p> <p><strong>Acknowledgments</strong></p> <p>This project was financially supported by the Swiss National Research Foundation grants n° 31003A_182577 to MC and n° P400PB_183930 to CQ, as well as the IGE3 Student Salary Award to JR.</p>
Processing differences in Explicit and Transition Cues in Task Switching
<p>This dataset consists of 5 experiments that compare cue and task processing performance in task switching with explicit and transition cues. Experiments 1-3 have been published in Van Loy, Liefooghe and Vandierendonck (2010). The entire data set is used in a study on the utility of integrated measures of speed and accuracy (Vandierendonck, submitted).</p>
Simulated spatially-explicit above ground biomass of forests (larch) in the vicinity of the Ilirney lake system region, Chukotka, Russia
<p>The model LAVESI (Kruse et al. 2016) was updated (Kruse 2023) and forced with historical and future climate forcing for 3 simulation repeats. The data set contains simulated larch above ground biomass (AGB, in kg m<sup>-2</sup>) for the three climate forcings RCP 2.6, 4.5 and 8.5 and each complemented with a hypothetical cooling scenario from year 2300 CE onwards. The data provided is from years 2020, 2050, 2100 and proceeding in 100-year steps until 3000 CE.</p> <p>Format: Geotiff; projection UTM58N and 30x30 m tiles; extent: 640008.2, 649998.2, 7475006, 7494716 m (xmin, xmax, ymin, ymax)</p>
NEMO v4.2 eORCA1 data with RIS, FRIS and LCIS explicit
<p><strong>PROJECT OPEN</strong></p> <p>https://www.katofthesea.com/project-open</p> <p><strong>OBJECTIVES</strong></p> <p>As a first step towards better representing AABW source waters in NEMO global ocean 1° (eORCA1), we explicitly simulate circulation beneath Filchner-Ronne (FRIS), Larsen C (LCIS), and Ross (RIS) ice shelves. These ice shelves were chosen due to their role in the formation and setting of properties of the parent waters of AABW.</p> <p><strong>METHODOLOGY</strong></p> <ul> <li> <p>NEMO version 4.2 Beta</p> </li> </ul> <p>Forced with 2 cycles of CORE forcing for a reference “Closed” cavity run and an “Open” run with FRIS, LCIS and RIS represented.</p> <ul> <li> <p>Inform initial conditions using an idealized regional configuration of each ice shelf.</p> </li> </ul> <p><strong>PROVIDED HERE:</strong></p> <p><strong>NAMELISTS: </strong></p> <p>- NEMO reference namelist (namelist_ref; also available with NEMO code), OPEN configuration (namelist_core_ia_cfg) namelist and sea ice namelists (namelist_ice_ref and namelist_ice_cfg). </p> <p>Unless stated otherwise in the “cfg” namelist, the simulation uses the namelist choices provided in the “ref” namelist. The namelist_core_ia_cfg is a namelist specific to a global ocean configuration (ORCA2, ORCA1, ORCA025 etc) forced by interannual core winds. For more information on all the namelist parameters included in these namelists, please refer to the NEMO reference manual available on Zenodo (10.5281/zenodo.6334656). </p> <p><strong>DOMAIN FILES AND INITIAL CONDITIONS: </strong></p> <p>- Initial conditions where data inside the cavity is informed using an idealized regional configuration with World Ocean Atlas (WOA; <a href="https://www.nodc.noaa.gov/OC5/woa18/woa18data.html">https://www.nodc.noaa.gov/OC5/woa18/woa18data.html</a>) restoring at the boundaries. The data in the cavities is merged with WOA with a smoothing spline applied along the ice shelf front.</p> <p>- A domain file containing bathymetry and ice shelf draft with FRIS, LCIS and RIS open along with accompanying mesh mask file.</p> <p>- The adapted eddy viscosity files where viscosity varies south of 65 degrees South according to grid cell size.</p> <p>- A freshwater flux file where the melt rate from all cavities except FRIS, LCIS and RIS is prescribed. Inside the "Open" cavities, the melt paramaterization is turned off and the location of melt is moved to the grounding line in case in the future we would like to include the flux from grounding line rives. </p> <p><strong>MODEL OUTPUT:</strong></p> <p>The data uploaded in this zip file is split into the output from the "Closed" and "Open" runs and is listed under eORCA1_output. Here the temperature and salinity fields used for comparison with WOA are provided (1981-2009), along with specific sections extracted using the PAGO functions (<a href="https://www.whoi.edu/science/PO/pago/">https://www.whoi.edu/science/PO/pago/</a>) along FRIS and RIS for certain dates that correspond to CTD sections in the area. To facilitate easy plotting of the example scripts provided, we have also extracted the thermohaline and velocity fields for FRIS cavity and adjacent continental shelf. The user can use these for a first try with the scripts provided and then move on to extracting their areas and dates of interest from the regional 1981-2009 files. </p> <p><strong>EXAMPLE SCRIPS:</strong></p> <p>To get the user familiar with the provided data, we have provided example scripts for extracting the data (open_eORCA_FRIS), plotting bathymetry and T-S (plot_bathy_T_S) and plotting the meridional overturning function and barotropic stream function in the cavity (plot_MOC_BSF_melt). In this same script the melt rate pattern is plotted and the net melt over various time periods corresponding to observational studies is calculated using calculating_net_melt.</p> <p>Additionally, a script plotting temperature and salinity across FRIS ice shelf front for the period February-March 1995 is provided and can be adapted and used to plot the other sections of data provided in this zip. </p> <p><strong>ACKNOWLEDGEMENTS AND FINANCIAL SUPPORT</strong></p> <p>Katherine Hutchinson received financial support of the European Union’s Horizon 2020 research and innovation programme Marie Skłodowska-Curie grant agreement No 898058 (Project OPEN). Nicolas Jourdain received support from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 101003536 (ESM2025). Pierre Mathiot acknowledges support from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 820575 (TiPACCs). This work was performed using HPC resources from GENCI–IDRIS (Grant 2021- A0100107451) and from the IPSL Mesocentre ESPRI.</p> <p>Project OPEN is a participant in the h2020 open access data pilot.</p>
Simulated spatially explicit dataset (300 m) on future forest cover changes in Southeast Asia projected under the baseline shared socioeconomic pathways
<p>This is a simulated spatially explicit dataset on future forest cover changes in Southeast Asia projected under the baseline shared socioeconomic pathways. It includes six raster maps at a spatial resolution of 300 m: (1) 2015 baseline forest and non-forest map; (2) SSP1 2050 projected net forest gain map; (3) SSP2 2050 projected net forest gain map; (4) SSP3 2050 projected net forest loss map; (5) SSP4 2050 projected net forest gain map; and SSP5 2050 projected net forest loss map. This dataset is the result of a study published in Nature Communications (2019) (https://doi.org/10.1038/s41467-019-09646-4).</p>
A method for generating coherent spatially explicit maps of seasonal palaeoclimates from site-based reconstructions
<p>Reconstruction of climate anomalies in southern Europe for the Last Glacial Maximum (LGM, ca 21,000 years ago), made by combining pollen based reconstructions (from Bartlein et al. 2011) and averaged outputs of LGM simulations from the 3rd round of the Palaeoclimate Model Intercomparison Project (PMIP, Braconnot et al. 2011), under a variational data assimilation technique. Reconstructions made using this technique are designed to be used for data-model comparison, specifically against the results of PMIP4. The dataset consists of 6 variables: moisture index (the ratio precipitation and equilibrium evapotranspiration), mean annual precipitation (mm), mean annual temperature (degrees C), mean temperature of the coldest month (degrees C), mean temperature of the warmest month (degrees C), growing degree days above 5 degrees C (day degrees C). The standard deviation of these variables is also given.</p>
Planmap's Deliverable 6.2- 3D geo-models based on multiple datasets of the Moon (implicit or explicit modelling)
<p>Outputs of the 3D geomodelling of the shallow-surface layered deposits on the Chang'e 3 landing site. This is based on the Yutu rover GPR channel 2B data gathered along its traverse in Sinus Iridum on the Moon.</p> <p> </p> <p>Notebooks at https://doi.org/10.5281/zenodo.4055213</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.