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251 results for “Temperature Dependency”
Fig. 2 in Retrieving climate change dependent Sea Surface Temperature (SST) in Southern Turkey by using Landsat thermal imagery
Fig. 2 — The four sections of the sampling site Table 1 — Landsat images features (29) Product Type Pixel size (collected) Pixel size (resampled) Thermal band Landsat 4-5 TM L1 120-meters 30-meters Band 6 Landsat 7 ETM+ L1 60-meters 30-meters Band 6 Landsat 8 OLI/TIRS L1 100-meters 30-meters Band 10/ Band11
Fig. 3 in Retrieving climate change dependent Sea Surface Temperature (SST) in Southern Turkey by using Landsat thermal imagery
Fig. 3 — SST anomalies: a) T1 Cross-section, b) T2 Cross-section, c) T3 Cross-section, and d) T4 Cross-section
Fig. 4 in Temperature-dependent development of Xyleborus glabratus (Coleoptera: Curculionidae: Scolytinae)
Fig. 4. Mean ± SE number of teneral adults per 5 galleries per log encountered every other day in the avocado logs at 4 constant temperatures.
Fig. 3 in Temperature-dependent development of Xyleborus glabratus (Coleoptera: Curculionidae: Scolytinae)
Fig. 3. Mean ± SE number of pupae per 5 galleries per log encountered every other day in the avocado logs at 4 constant temperatures.
Fig. 1 in Temperature-dependent development of Xyleborus glabratus (Coleoptera: Curculionidae: Scolytinae)
Fig. 1. Mean ± SE number of eggs per 5 galleries per log observed every other day in the avocado logs at 4 constant temperatures.
A quantitative model of temperature-dependent diapause progression
<p>R-code and data for reproducing the results of von Schmalensee, Süess et al. 2024 <em>PNAS</em></p> <p>Scripts will run/load the models and save the raw figures in the figure folder.</p> <p>Remember to install the required packages (see 'functions_packages.R' in the functions folder).</p> <p>R version 4.3.3 and brms version 2.21.0 was used.</p>
Figure 9 in The web amount and quality of web spiders (Agelenidae, Pholcidae), Agelena labyrinthica (Clerck, 1757) and Holocnemus pluchei (Scopoli, 1763), depending on food and temperature
Figure 9. Amounts of food consumed by Holocnemus pluchei at 25–30 °C (1: Drosophyla melanogaster; 2: food caught with insect net).
Figure 8 in The web amount and quality of web spiders (Agelenidae, Pholcidae), Agelena labyrinthica (Clerck, 1757) and Holocnemus pluchei (Scopoli, 1763), depending on food and temperature
Figure 8. Food amounts of Holocnemus pluchei at 20–25 °C (1: Drosophila melanogaster; 2: food caught with insect net).
Figure 7 in The web amount and quality of web spiders (Agelenidae, Pholcidae), Agelena labyrinthica (Clerck, 1757) and Holocnemus pluchei (Scopoli, 1763), depending on food and temperature
Figure 7. Food amounts of Agelena labyrinthica at 25–30°C (1: Drosophila melanogaster; 2: food caught with insect net).
Figure 6 in The web amount and quality of web spiders (Agelenidae, Pholcidae), Agelena labyrinthica (Clerck, 1757) and Holocnemus pluchei (Scopoli, 1763), depending on food and temperature
Figure 6. Food amounts of Agelena labyrinthica at 20–25°C (1:Drosophila melanogaster; 2: food caught with insect net). Table 4. The Mann–Whitney U test results of the amounts of food consumed under different conditions.
Data Repository - Thermal-electrochemical parametrisation of a lithium-ion battery: mapping Li concentration and temperature dependencies
<p>Datasets from "Thermal-electrochemical parametrisation of a lithium-ion battery: mapping Li concentration and temperature dependencies" - Journal of Electrochemical Society.</p> <p>This repository contains parameter values for the electrode solid-state diffusivity, entropic term, exchange current density, electronic conductivity, specific heat capacity, and thermal conductivity.</p>
Data from: Temperature-dependent mechanical behavior of aluminum AM structures generated via multi-layer friction surfacing
<p>This dataset contains the data for the publication " Temperature-dependent mechanical behavior of aluminum AM structures generated via multi-layer friction surfacing "</p>
Tailoring magnetic hysteresis of Fe-Ni additive manufactured permalloy via multiphysics-multiscale simulations: Temperature-dependent parameters, thermodynamic database, results, and utilities
<p>This dataset contains temperature-dependent parameters and thermodynamic database, supplementary data and utilities of the publication "Tailoring magnetic hysteresis of additive manufactured Fe-Ni permalloy via multiphysics-multiscale simulations of process-property relationships" (<a href="http://doi.org/10.1038/s41524-023-01058-9">Yang et al., 2023</a>).</p> <p>We performed non-isothermal phase-field simulations of SLS process of the Fe<sub>21.5</sub>Ni<sub>78.5</sub> permalloy and subsequential mesoscopic thermo-elasto-plastic calculations and nanoscopic chemical order-disorder (<span>\(\gamma/\gamma'\)</span>) transition simulations as well as micromagnetic hysteresis calculations on nanostructures. Temperature-dependent parameters are employed. We then investigate the dependence of the fusion zone size, the residual stress and plastic strain, and the magnetic hysteresis of AM-produced Fe<sub>21.5</sub>Ni<sub>78.5 </sub>on beam power and scan speed.</p> <p>This dataset contains:</p> <ul> <li><em>feni_cac.tdb</em>: Thermodynamic database of the Fe-Ni binary system based on <a href="https://doi.org/10.1016/j.intermet.2010.02.026">Cacciamani et al., 2010</a></li> <li><em>average_values.csv</em>: Average quantities for creating the contours in Fig. 6a, 6b, 7a, 7b, 8a, and Supp. Fig. 10a, 10b.</li> <li><em>mesostructures.zip</em>: Containing resampled mesostructures from SLS single scan simulations (final timestep) with associated temperature, stress, and strain evolution. Nodal values are explained in Table 1. Naming pattern is <ul> <li>SLS-TEP__<power>-<scan_speed>__.e</li> </ul> </li> <li><em>parameters.zip</em>: Containing temperature-dependent parameters for performing SLS simulations and thermo-elasto-plastic calculations with fine (1K) temperature increments. The same temperature-dependent parameters with coarse temperature increments are already listed as Supp. Table 1, 2.</li> <li><em>sampled_point_data.zip</em>: Containing mechanical quantities on sampled points and corresponding results of nanoscopic <span>\(\gamma'\)</span> phase fraction (<span>\(\Psi_{\gamma'}\)</span>) and magnetic coercivity <span>\(H_\mathrm{c}\)</span>. Naming pattern is <ul> <li>mech__<power>-<scan_speed>__.csv</li> <li>Psi__<power>-<scan_speed>__.csv</li> <li>Hc__<power>-<scan_speed>__.csv</li> </ul> </li> <li><em>utilities.zip</em>: Containing Python utilities to perform calculations of free energy density and related thermodynamic quantities, extracting parameters from <em>feni_cac.tdb. </em><br><strong>Notice: </strong><a href="https://pycalphad.org/docs/latest/">pyCALPHAD</a> (ver 0.8.4) is requested for performing the Python utilities.</li> </ul> <p>Table 1. Nodal values in an exodus file Nodal value name Symbol Meaning Unit T <span>\(T\)</span> Normalized Temperature by <span>\(T_\mathrm{M}\)</span> - c <span>\(\rho\)</span> Substance order parameter - pb <span>\(\xi\)</span> Fusion zone indicator - eps (eps_11, eps_12, eps_13, eps_22, eps_23, eps_33) <span>\({\varepsilon}\)</span> Strain - epsp (epsp_11, epsp_12, epsp_13, epsp_22, epsp_23, epsp_33) <span>\({\varepsilon}_\mathrm{pl}\)</span> Plastic Strain - peeq <span>\(p_\mathrm{e}\)</span> Accumulated plastic strain - sigma (sigma_11, sigma_12, sigma_13, sigma_22, sigma_23, sigma_33) <span>\({\sigma}\)</span> Stress MPa vonmises <span>\(\sigma_\mathrm{e}\)</span> von Mises stress MPa u (u_X, u_Y, u_Z) <span>\(\mathbf{u}\)</span> Displacement μm</p> <p> </p> <p><strong>Notice</strong>: The raw transient outputs are not cured in this dataset due to the vast file size. Please contact the authors to acquire related files/utilities.</p>
Model output from "The chance of freezing – a conceptional study to parameterize temperature-dependent freezing by including randomness of ice-nucleating particle concentrations"
<p>Model output from "The chance of freezing – a conceptional study to parameterize temperature-dependent freezing by including randomness of ice-nucleating particle concentrations", accepted for publication in Atmospheric Chemistry and Physics, 2023, same authors.<br> The simulations were done using MIMICA version4 (Savre at el., 2014) and the data includes all model output presented in the publication.</p>
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
<ol> <li><span>Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics.</span></li> <li><span>We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. </span></li> <li><span>Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronising effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. </span></li> <li><span>Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting. </span></li> </ol>
Data from: Temperature dependent effects of cutaneous bacteria on a frog's tolerance of fungal infection
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Data from: The thermal sensitivity of growth and survival in a wild reptile with temperature-dependent sex determination
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Temperature-dependent evolutionary speed shapes the evolution of biodiversity patterns across tetrapod radiations
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Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
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Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination
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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.
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.