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635 results for “Attributes”
HydroPenIndia: A catalogue of streamflow metrics, meteorological time series and catchment attributes of Peninsular India
<p><em>HydroPenIndia, </em>a catalogue of streamflow metrics, hydro-meteorological time series and landscape attributes of 204 catchments of Peninsular India is introduced. This catalogue consists of daily hydro-meteorological time series (rainfall, soil moisture, potential evapotranspiration, actual evapotranspiration, maximum temperature, minimum temperature, longwave radiation, shortwave radiation, wind speed and humidity) for a period of 36 years from 1980-2015. The time series of 26 streamflow metrics, 13 topographic metrics, 12 climate indices, 15 hydrologic signatures, 8 land cover descriptors, 6 geologic characteristics, 6 soil characteristics (see table 8) and 13 human intervention indices are also included in this dataset. <em>HydroPenIndia</em> is an initiative to encourage hydrologists to advance knowledge of hydrological processes by contributing to fundamental research questions on Indian catchments. Free availability of the dataset will provide access to global users to represent India in large-sample hydrology studies. <em>HydroPenIndia</em> is derived from multiple databases to help researchers start their research without wasting time on collecting and processing datasets. This catalogue will motivate researchers to solve pertinent issues related to water management, quantification and risk assessment of hydrologic extremes, unravelling regional scale hydrologic functioning and climate change impact assessment over Peninsular India.</p>
Habitat attributes mediate herbivory and influence community development in algal metacommunities
<p>Data in support of accepted Article in Ecology. Information regarding data collection can be found in linked publication. Code performed on data can be found in the attached Github (<a href="http://github.com/gsrednick/herbivory_assembly">github.com/gsrednick/herbivory_assembly</a>).</p> <p>Metadata</p> <ul> <li>biomass_change_data.csv — algal biomass data per settlement tile over time</li> <li>block_data.csv — block and settlement tile metadata</li> <li>experiment_data_V2.csv — raw algal community structure data per settlement tile over time</li> <li>meta_table.csv — complete tile and treatment metadata</li> </ul>
RiboGL Dataset and Attributions
<p>Dataset and attributions for the paper "Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations". It has the following: </p> <ol> <li>Input gene sequence</li> <li>Gene deprivation conditions</li> <li>Ground Truth Labels</li> <li>RiboGL Attributions</li> <li>RiboGL predictions</li> </ol> <p>Additionally, we have included the ensembl genome file for mice. </p>
A flux tower site attribute dataset intended for land surface modeling
<p><span>Land surface models (LSMs) should have reliable forcing, validation, and surface attribute data as the foundation for effective model development and improvement. Eddy covariance flux tower data are considered the benchmarking data for LSMs. We conducted a comprehensive quality screening of the existing reprocessed flux tower dataset, including the proportion of gap-filled data, external disturbances, and energy balance closure (EBC), leading to 90 high-quality sites. For these sites, we collected vegetation, soil, topography information, and wind speed measurement height from literature, regional networks, and Biological, Ancillary, Disturbance, and Metadata (BADM) files. Then we obtained the final flux tower attribute dataset by global data product complement and plant functional types (PFTs) classification.</span></p> <p><span>The dataset comprises a total of 90 NetCDF files. Each site's data is formatted within a NetCDF file named according to the site name, database, and attributes (vegetation, soil, topography, and reference height), such as ‘AT-Neu_FLUXNET2015_Veg_Soil_ Topography_ReferenceHeight.nc’. This dataset addresses the lack of site attribute data to some extent, reduces uncertainty in LSMs data source, and aids in diagnosing parameter as well as process deficiencies.</span></p>
Figure 1 in Relations between soil attributes and the abundance of Bacillus thurigiensis in the Cerrado of Maranhão state, Brazil
Figure 1. Soil sampling areas in the Cerrado, Maranhão state, Brazil.
Figure 2 in Effect of season and housing systems on various physiobehavioral attributes of local breed of rabbits (Oryctolagus cuniculus) in Southern Punjab, Pakistan
Figure 2. Mean values for meteorological attributes during different study seasons.
Scripts for "Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model"
<p>The scripts used to generate the main figures and results of the work entitled ''Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model'' by Michalezyk et al., submitted for publication in JAMES - AGU in 2024.</p> <p>If you have any questions, please contact Nicolas MICHALEZYK : nicolas.michalezyk@locean.ipsl.fr</p>
Luminoso Input Data for SemEval-2018 Task 10: "Capturing Discriminative Attributes"
<p>This is the data required to run Luminoso's entry to the SemEval-2018 task on Capturing Discriminative Attributes.</p> <p>This data includes:</p> <ul> <li>A recently-computed version of the <a href="https://github.com/commonsense/conceptnet-numberbatch">ConceptNet Numberbatch</a> word embeddings</li> <li>The output of an implementation of Semantic Matching Energy over ConceptNet</li> <li>A SQLite database containing the lead section of all articles on the <a href="http://en.wikipedia.org">English Wikipedia</a> on 2017-12-20</li> <li>The text file that that database is constructed from</li> <li>A SQLite database of words that co-occur in <a href="http://storage.googleapis.com/books/ngrams/books/datasetsv2.html">Google Books 2-grams</a></li> <li>The text file containing total counts of 2-grams in the Google Books data, which that database is constructed from</li> </ul> <p>For more information, see the paper "Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge", by Robyn Speer and Joanna Lowry-Duda, to appear in the proceedings of the SemEval workshop at NAACL 2018.</p>
Input Data for "Distinguishing attributes using ConceptNet Numberbatch"
<p>In a post on blog.conceptnet.io, we're showing how to use ConceptNet Numberbatch alone to create a good solution to SemEval-2018 Task 10, Capturing Discriminative Attributes. This is an alternative, simplified implementation of a result presented in the SemEval paper <a href="http://aclweb.org/anthology/S18-1162">Distinguishing Attributes Using Text Corpora and Relational Knowledge</a>, by Robyn Speer and Joanna Lowry-Duda.</p> <p>This data repository contains the data necessary to make the simplified implementation work.</p>
Figure 3 in The impact of chilling on selected attributes of the blowfly, Calliphora vicina (Robineau-Desvoidy, 1830) (Diptera: Calliphoridae), under laboratory conditions
Figure 3. Effect of chilling period on pupal (a) and adult (b) weight of Calliphora vicina.
Attributing human mortality from fire PM2.5 to climate change
<p>The dataset and scripts are for reanalysis the paper: Attributing human mortality from fire PM2.5 to climate change. </p> <p>The script is written in MATLAB. see Readme.txt and FireMort_SI_re.mlx for detail. </p> <p>Unzip files and make the folder (/Input, /Output, /Major_input, /Minor_input). </p> <p>Some original dataset (which can be directly driven from ISIMIP repository) were not included. </p> <p>If you need more information, please contact Chaeyeon Park (email- park.chaeyeon@aist.go.jp, or chaeyeon528@gmail.com)</p>
The accelerating loss of resilience in suburban woodlands can largely be attributed to changes in urban precipitation patterns
<p><span>Vegetation resilience holds significant importance for stabilizing ecosystem service functions in a changing climate. While global land surface vegetation resilience changes have been extensively studied, the impact of urbanization on the resilience of suburban woodlands remains inadequately understood.</span> <span>In this study, we utilized two Critical Slowing Down (CSD) indicators, namely lag-one autocorrelation (LOA) and variance (VA), to assess the vegetation resilience, its long-term trends, and influencing factors in suburban woodlands across 1,356 cities worldwide. The recovery rates estimated by LOA (r<sub>r1</sub>) and VA (r<sub>r2</sub>) showed close alignment in suburban woodlands with low suburban forest coverage (SFC) areas (correlation coefficient (r)=0.95). However, a notable divergence was observed in areas with high SFC (r=0.73). Suburban woodlands with high SFC typically exhibited lower recovery rate estimates, thus indicating greater vegetation resilience compared to areas with lower SFC. From 1986 to 2022, the recovery rates of suburban woodland areas in over 83% of the cities demonstrated a significant upward trend, with an average of 3.23×10<sup>−3</sup> yr<sup>−1</sup> for both r<sub>r1</sub> and r<sub>r2</sub>, signifying a widespread decline in vegetation resilience. The accelerating pace of urbanization led to higher rising rates of r<sub>r1</sub> and r<sub>r2</sub> during 2010-2022 (5.11×10<sup>−3</sup> yr<sup>−1</sup>) compared to 1986-1999 (0.49×10<sup>−3</sup> yr<sup>−1</sup>). The notable decrease in resilience of forestland was primarily attributed to reduced precipitation in urban suburbs, which can be explained by urbanization-induced heat island and building barrier effects, causing a shift of precipitation center from urban suburbs to central cities. In summary, this study revealed that urbanization diminishes the vegetation resilience of urban suburban woodlands by altering urban precipitation patterns. These findings underscore the necessity of augmenting water availability in urban suburbs to restore resilience in these woodlands, thereby enhancing their ecosystem service value.</span></p>
The accelerating loss of resilience in suburban woodlands can largely be attributed to changes in urban precipitation patterns
<p><span>Vegetation resilience holds significant importance for stabilizing ecosystem service functions in a changing climate. While global land surface vegetation resilience changes have been extensively studied, the impact of urbanization on the resilience of suburban woodlands remains inadequately understood.</span> <span>In this study, we utilized two Critical Slowing Down (CSD) indicators, namely lag-one autocorrelation (LOA) and variance (VA), to assess the vegetation resilience, its long-term trends, and influencing factors in suburban woodlands across 1,356 cities worldwide. The recovery rates estimated by LOA (r<sub>r1</sub>) and VA (r<sub>r2</sub>) showed close alignment in suburban woodlands with low suburban forest coverage (SFC) areas (correlation coefficient (r)=0.95). However, a notable divergence was observed in areas with high SFC (r=0.73). Suburban woodlands with high SFC typically exhibited lower recovery rate estimates, thus indicating greater vegetation resilience compared to areas with lower SFC. From 1986 to 2022, the recovery rates of suburban woodland areas in over 83% of the cities demonstrated a significant upward trend, with an average of 3.23×10<sup>−3</sup> yr<sup>−1</sup> for both r<sub>r1</sub> and r<sub>r2</sub>, signifying a widespread decline in vegetation resilience. The accelerating pace of urbanization led to higher rising rates of r<sub>r1</sub> and r<sub>r2</sub> during 2010-2022 (5.11×10<sup>−3</sup> yr<sup>−1</sup>) compared to 1986-1999 (0.49×10<sup>−3</sup> yr<sup>−1</sup>). The notable decrease in resilience of forestland was primarily attributed to reduced precipitation in urban suburbs, which can be explained by urbanization-induced heat island and building barrier effects, causing a shift of precipitation center from urban suburbs to central cities. In summary, this study revealed that urbanization diminishes the vegetation resilience of urban suburban woodlands by altering urban precipitation patterns. These findings underscore the necessity of augmenting water availability in urban suburbs to restore resilience in these woodlands, thereby enhancing their ecosystem service value.</span></p>
Transcripts (+attributions) from a mixed-presence user study with two wall-sized displays
<p>Transcripts from a mixed-presence experiment with two wall-sized displays.<br>Automatic transcription (and translation when necessary) using Whisper large v3. Resulting sentences were then attributed to individuals.<br>Comes from a study ran in Q4 2023. Accompanies a paper.</p> <p>As for the abbreviations/acronyms used in the file:</p> <ul> <li>Conditions C0 and C1 correspond respectively to "no cues" and "cues enabled" (see paper)</li> <li>Sides A and V respectively correspond to Arena (=circular display) and Viswall (flat display)</li> <li>Speakers CEO, FIN, ICU and LOG respectively correspond to the roles given to these speakers (i.e. CEO, Head of Finance, Head of Intensive Care Unit, and Head of Logistics)</li> <li>Speakers TECH_VIZWALL and FACILITATOR_VIZWALL correspond to members of the research team (see protocol)</li> </ul>
Electrospun Fiber Experimental Attributes Dataset (FEAD)
<p>Understanding the intricate relationships between the structure and properties of electrospun PVDF fibers is crucial for designing effective devices. However, the complexity of these relationships makes them challenging to model through traditional trial-and-error experiments. Machine learning has emerged as a powerful tool for modeling multidimensional relationships, but it requires a diverse and high-quality training dataset to effectively learn these intricate connections.</p> <p>To comprehensively investigate the intricate relationships between the structure and properties of electrospun PVDF fibers, a high-quality training dataset is imperative, encompassing a wide array of experimental conditions. There is no single comprehensive source that provides a holistic understanding of how the various parameters impact the PVDF fiber properties. Existing studies predominantly present results from a limited range of parameter variations, necessitating the creation of a meta dataset for robust insights. In response to this gap, we introduce the "Electrospun Fiber Experimental Attributes Dataset (FEAD)," a meticulously curated compilation that collates data from diverse literature sources and complements with our own experimental findings and computations.</p> <p>FEAD comprises a total of 745 data points sourced from 52 distinct references. This dataset encapsulates a broad spectrum of solvents and solvent systems, including DMAC, DMF, DMAC/Acetone, DMSO/Acetone, DMF/Acetone, NMP/Acetone, among others. While certain parameters such as polymer concentration, solvent ratio, feed rate, and applied voltage were directly extracted from the literature, other critical factors like solubility parameters, interaction radii, and RED were computed.</p> <p>Experiments involving the use of surfactants and electrolytes to alter polymer viscosity and electrical conductivity are not included in the dataset. This exclusion ensures a focus on understanding the genuine impact of polymer concentration and solubility factors on the resulting fibers. The development of this novel materials database is an ongoing effort, and we anticipate its continual improvement over time as more datapoints are incorporated.</p>
Table 5. Analytical data for miscellaneously attributed samples from Broken Hill, including the Broken Hill Consols Mine. a in Compositions of silver halides from the Broken Hill district, New South Wales
<p><b>Table</b> 5. Analytical data for miscellaneously attributed samples from Broken Hill, including the Broken Hill Consols Mine.a</p><table><tbody><tr><th>No.</th><th><b>Analyses</b></th></tr></tbody><tbody><tr><th>D46338b</th><td>Cl</td><td>60</td><td>57</td><td>57</td><td>53</td><td>56</td><td>57</td><td>58</td><td>68</td><td>56</td><td>66</td><td></td></tr><tr><th></th><td>Br</td><td>32</td><td>35</td><td>34</td><td>37</td><td>35</td><td>34</td><td>32</td><td>31</td><td>35</td><td>33</td><td></td></tr><tr><th></th><td>I</td><td>8</td><td>8</td><td>9</td><td>10</td><td>9</td><td>9</td><td>10</td><td>1</td><td>9</td><td>1</td><td></td></tr><tr><th>D26168c</th><td>Cl</td><td>72</td><td>76</td><td>63</td><td>65</td><td>60</td><td>77</td><td>77</td><td>72</td><td>66</td><td>65</td><td></td></tr><tr><th></th><td>Br</td><td>28</td><td>24</td><td>37</td><td>35</td><td>40</td><td>22</td><td>23</td><td>28</td><td>34</td><td>35</td><td></td></tr><tr><th>D28184d</th><td>I Cl</td><td>75</td><td>68</td><td>86</td><td>70</td><td>70</td><td>1 70</td><td>78</td><td>70</td><td>84</td><td></td><td></td></tr><tr><th></th><td>Br</td><td>25</td><td>30</td><td>14</td><td>28</td><td>30</td><td>29</td><td>21</td><td>30</td><td>16</td><td></td><td></td></tr><tr><th>D28185d</th><td>I Cl</td><td>55</td><td>2 56</td><td>55</td><td>2 56</td><td>55</td><td>155</td><td>1 60</td><td>50</td><td>45</td><td>50</td><td>56</td></tr><tr><th></th><td>Br</td><td>43</td><td>43</td><td>44</td><td>43</td><td>44</td><td>43</td><td>40</td><td>46</td><td>45</td><td>45</td><td>41</td></tr><tr><th></th><td>I</td><td>2</td><td>1</td><td>1</td><td>1</td><td>1</td><td>2</td><td></td><td>4</td><td>10</td><td>5</td><td>3</td></tr></tbody></table><p>a Analyses reported as in Table I. b Trace S detected. C Traces Pb, Cu, S, As detected. d Consols Mine; traces Pb, As, S, Fe detected.</p>
Predation, functional response and demographic parameters of Orius albidipennis (Hemiptera:Anthocoridae) on Schizaphis graminum (Hemiptera:Aphididae): effect of host plant morphological attributes
<p>Plant attributes like leaf hairiness and trichome compactness diversely affect the biocontrol agents of phytophagous insect pests. In the current study, effect of physical plant features on life table characteristics and functional response of <em>Orius albidipennis </em>(Rueter) females feeding on <em>Schizaphis graminum </em>(Rondani) was investigated on two common wheat cultivars (Falat and Pishtaz) differing in leaf morphological features. The trichome density of wheat cultivars considerably influenced a broad spectrum of attributes related to the performance of <em>O. albidipennis</em>. The intrinsic rate of increase (<em>rm</em>) was significantly greater on Falat (0.09±0.006) than on Pishtaz (0.06±0.008) cultivar. Similarly, the net reproductive rate and finite rate of increase were greater on Falat (16.72±3.38 and 1.083±7.54) than on Pishtaz (8.08±2.04 and 1.067±9.49). Although <em>Orius </em>predators exhibited type III of functional response on both wheat cultivars, they had lesser searching efficiencies and higher handling times on Pishtaz than those on Falat cultivar. Moreover, the maximum attack rate (<em>T</em>/<em>Th</em>) was greater on Falat than on Pishtaz. Lesser maximum predation and greater handling time of the <em>Orius </em>predators on Pishtaz cultivar might be imputed to the significantly more condensed surface trichomes of its leaves than that of Falat leaves, which physically prevented movement of the <em>Orius </em>bugs and decreased prey encounter rate. Moreover, increase of trichome density negatively influenced on foraging behavior of the predatory bug. Females were also found to prefer wheat leaves with fewer trichomes as oviposition hosts. It seems that trichomes provided hinderance to the <em>orius </em>bug. To recapitulate, it could be stated that the efficiency of <em>O. albidipennis </em>in controlling <em>S. graminum </em>on wheat may be more beneficial in cultivars with lower trichome density.</p>
Data from: Urban street lighting differentially affects community attributes of airborne and ground-dwelling invertebrate assemblages
<p><span>The introduction of artificial light at night (ALAN) into natural and urbanised landscapes is a known and highly pervasive disruptor of invertebrate communities. However, the effect of variation in intensity and spectra of ALAN on invertebrate communities inhabiting different spatial niches is little understood. Further, the remarkable ability of ALAN to continue to disrupt biodiversity even in chronically-illuminated urban landscapes is not often acknowledged. </span></p> <p><span>Here, we simultaneously sampled airborne and ground-dwelling invertebrate assemblages under and between urban streetlights to explore the effects on community composition and abundance of a) proximity to decadal (i.e long-illuminated) nocturnal street lighting and b) variation in the spectral output of light. </span></p> <p><span>The two assemblages responded differently. For airborne invertebrates, night-time abundance doubled, and night-time assemblage composition was significantly different for traps under, compared with between, streetlights. These differences in abundance were not affected by streetlight intensity, and were absent in day samples, suggesting that even weak ALAN may be causing short-term redistribution of nocturnal invertebrates. Further, the abundance (but not composition) effects of ALAN on airborne invertebrates increased when the streetlights emitted a higher proportion of short-wavelength light. </span></p> <p><span>In contrast, for ground-dwelling invertebrates, we found only marginal effects of proximity and spectrum of lighting on abundance and no effect on assemblage composition. However, more intense streetlighting reduced abundance and altered composition at traps both under and between lights. </span></p> <p><span><i>Synthesis and Applications: </i>Public lighting managers must consider ALAN impacts on invertebrate communities not only when introducing ALAN to naïve environments, but also when changing lighting in areas that are highly urbanised and exposed to decades of artificial light at night. Further, lighting proposals and environmental monitoring of invertebrate communities must take into account effects on both ground-dwelling and airborne assemblages, as these may respond very differently to the presence, intensity and spectrum of ALAN. </span></p>
Data from: Mammal-bearing gastric pellets potentially attributable to Troodon formosus at the Cretaceous Egg Mountain locality, Two Medicine Formation, Montana, U.S.A.
<p>Fossil gastric pellets (regurgitalites) have distinct taphonomic characteristics that facilitate inferences of behavioural ecology in deep time, despite their rarity in the fossil record. Using the taphonomic patterns of both extant and fossil small mammals from more recent geologic deposits as a guide, we assess the taphonomy of three unusual multi-individual aggregates of mammal skeletons from paleosols at Egg Mountain, a dinosaur nesting locality from the Upper Cretaceous Two Medicine Formation, Montana, USA. One aggregate consists of two individuals of the multituberculate <i>Filikomys primaevus</i>. This specimen is characterized by brecciated crania, articulated postcrania, and an absence of digestive markings, all suggestive of a non-predatory origin. Two additional aggregates consist of three and eleven individuals, respectively, primarily of the marsupialiform <i>Alphadon halleyi</i>. High proportions of crania and indigestible elements (e.g. teeth), extensive disarticulation and breakage, digestive corrosion patterns, and the absence of a phosphatic ground mass are indicative of regurgitalites and align with features of extant prey in diurnal raptor gastric pellets. We interpret these specimens as the oldest known mammal-bearing regurgitalites. The discrepancy in taphonomic features implies behavioural separation between the two mammalian taxa at the locality. Abundant shed teeth and nesting evidence at the locality favors <i>Troodon formosus </i>as the predator responsible for the regurgitalites, congruent with previous inferences of a small-bodied prey diet, manipulation of prey during feeding, heightened metabolic processes, and potential nocturnality for this taxon.</p>
Costs of attributable burden disease to PM2.5 ambient air pollution exposure in Medellín, Colombia, 2010-2016
<pre>The repository includes the consolidated databases design to analyze the economic cost of local attributable burden disease to PM2.5 ambient air pollution in Medellín from 2010-2016.</pre>
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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.
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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.