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1,018 results for “past”
Academy of Program/Project & Engineering Leadership ASK the Academy Past Issues
Academy of Program/Project & Engineering Leadership's Ask the Academy magazine past issues.
Academy of Program/Project & Engineering Leadership ASK the Academy Past Issues
Academy of Program/Project & Engineering Leadership's Ask the Academy magazine past issues.
Echoes from the past: Influence of collective memory and historical victimhood on ethnic and national identities
<p>Collective memories which is a group’s shared representations of its past and which has the potentiality of shaping identity was examined in the context of a highly pluralistic society in the study. The research was conducted among 650 purposively selected participants from the three major ethnic groups in Nigeria through an online survey. The study seeks to know if pleasant collective memories will positively influence ethnic (subgroup) identification and national (superordinate) identification, and if on the other hand, unpleasant collective memories will be positively associated with ethnic identification but negatively associated with national identification. The study also seeks to know if victim beliefs will influence engagement in collective actions against authorities for justice. Respondents were measured on collective memories, victim beliefs, ethnic and national identifications scales. Findings of the study through a Latent Class Analysis (LCA) and Path Model Analysis indicate that pleasant collective memories positively influenced ethnic identification and national identification b = .56, SE = .15, p < .001, b = .67, SE = .14, p < .004, respectively. Also, result indicates that unpleasant collective memories has a significant positive influence on ethnic identification, but a significant negative influence on national identity. (b= 0.239, -0.058), respectively. Furtherance to this, Victim belief was found to be a predictor of collective action. (b = 0.251, p-value = 0.009 95% CI [0.12, 0.90], although, pleasant collective memories reduce the likelihood of collective action, (b = -0.716, p-value = 0.000). The study discusses how these dynamics influence ethnic group’s relations with other ethnic groups and the government of a pluralistic society.</p>
Soil salinity measured as electrical conductivity (ec, saturated paste method) soil maps of the Upper Colorado River Basin
<p>The data here were originally posted to facilitate timely and transparent peer review. The final public data release with formal metadata is now available from at the following location:</p> <p>Nauman, T.W., and Duniway, M.C., 2020, Predictive soil property maps with prediction uncertainty at 30 meter resolution for the Colorado River Basin above Lake Mead: U.S. Geological Survey data release,<a href="http://https//doi.org/10.5066/P9SK0DO2"> https://doi.org/10.5066/P9SK0DO2</a>.</p> <p>Associated publication:</p> <p>Nauman, T. W., and Duniway, M. C., 2020, A hybrid approach for predictive soil property mapping using conventional soil survey data: Soil Science Society of America Journal, v. 84, no. 4, p. 1170-1194. <a href="https://doi.org/10.1002/saj2.20080">https://doi.org/10.1002/saj2.20080</a>.</p> <p>Repository includes maps of soil saturated paste electrical conductivity (ec) as defined by United States soil survey program. </p> <p>These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.</p> <p>This data should be used in combination with a soil depth or depth to restriction layer map (both layers that will be released soon as part of this project) to eliminate areas mapped at deeper depths than the soil actually goes. This is a limitation of this data which will hopefully be updated in future updates. </p> <p>The creation and interpretation of this data is documented in the following article. Please note this article has not been reviewed yet and this citation will be updated as the peer review process proceeds.</p> <p>Nauman, T. W., Duniway, M. C., In Preparation. Predictive reconstruction of soil survey property maps for field scale adaptive land management. Soil Science Society of America Journal.</p> <p>File Name Details:</p> <p>ACCURACY!! Please see manuscript and Github repository (https://github.com/naumi421/SoilReconProps) for full details on accuracy. We do provide cross validation (CV) accuracy plots in this repository for both the overall sample (NRCS field pedons plus NRCS laboratory pedons; file ending _CV_plots.tif) and for just the CV results at laboratory pedons (file ending _CV_SCD_plots.tif). These plots compare CV predictions with observed values relative to a 1:1 line. Values plotted near the 1:1 line are more accurate. Note that values are plotted in hex-bin density scatter plots because of the large number of observations (most are >3000).</p> <p>Elements are separated by underscore (_) in the following sequence:</p> <p>property_r_depth_cm_geometry_model_additional_elements.extension</p> <p>Example: ec_r_0_cm_2D_QRF_bt.tif</p> <p>Indicates soil electircal conductivity (ec) at 0 cm depth using a 2D model (separate model for each depth) employing a quantile regression forest. This file is the raster prediction map for this model. There may be additional GIS files associated with this file (e.g. pyramids) that have the same file name, but different extensions. The _bt indicates that the map has been back transformed from ln or sqrt transformation used in modeling.</p> <p>The following elements may also exist on the end of filenames indicating other spatial files that characterize a given model's uncertainty (see below).</p> <p>_95PI_h: Indicates the layer is the upper 95% prediction interval value.</p> <p>_95PI_l: Indicates the layer is the lower 95% prediction interval value.</p> <p>_95PI_relwidth: Indicates the layer is the 95% relative prediction interval (RPI). The RPI is a standardization of the prediction interval that indicates that model is constraining uncertainty relative to the original sample. RPI values less than one represent uncertainty is being improved by the model relative to the original sample, and values less than 0.5 indicate low uncertainty in predictions. See paper listed above and also Nauman and Duniway (In revision) for more details on RPI.</p> <p>References</p> <p> Nauman, T. W., and Duniway, M. C., In Revision, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma</p>
The biodiversity of birch stands in agricultural landscapes of Estonia is associated with past land use, restoration approach, site and landscape variables
<p>The dataset includes vascular plant, bryophyte and lichen species data and environmental data collected from 33 birch stands in Estonia representing three stand types with different restoration approach (birch plantations on previous agricultural land, naturally regenerated stands on previous agricultural land and birch stands on native forest land).</p>
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
Academy of Program/Project & Engineering Leadership ASK Magazine Past Issues
Academy of Program/Project & Engineering Leadership's ASK Magazine archive.
ScienceDex guides
Understand access before you commit
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.