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2,762 results for “Heating”
How to transport veterinary drugs in insulated boxes to avoid thermal damage by heating or freezing
<p><strong>Documentation of the empiric data, measured in the heating and cooling chamber to determine the thermal constant for the investigated transport boxes.</strong></p> <p> </p> <p><strong>Background: </strong>The transport of veterinary drugs must comply with the general standards for drug storage. Although many vehicles are equipped with active heating and/or cooling devices assuring recommended storage conditions, simple insulated transport boxes are also often used. In this study, measurements for typical transport boxes were performed under laboratory conditions by the use of a climate chamber for a temperature of -20°C and 45°C to investigate the impact of box size, insulation material, liquid vs. dry filling products, filling degree and other parameters on the thermal performance of insulated boxes. Model calculations and instructions are presented to predict the retention time of recommended drug storage temperatures.</p> <p><strong>Results: </strong>The measurements and the model calculations showed that the loading of the transport boxes with additional water bottles to increase the heat capacity is appropriate to prolong the retention time of the recommended temperature range of the drugs. Insulated transport boxes are not suitable to store drugs over a period of more than approximately 12 hours. For practical use, a recipe is presented to measure the thermal properties of a transport box and the related retention time for which the recommended storage temperatures can be assured.</p> <p><strong>Conclusions: </strong>The following principles for drug transportation in vehicles are recommended: (1) Before transfer into boxes, drugs should always be thermally preconditioned (2) Increase the filling degree of the boxes with thermally preconditioned water bottles or re-usable thermal packs will increase the heat capacity. Do not deep-freeze the bottles or packs below 0°C to avoid drug freezing due to contact. (3) Open the lid of the boxes only to uncase drugs that are immediately needed. (4) The bigger the box and the higher the filling degree, the longer the retention time of the transport box. (5) Wherever possible, place the drug box at a cool site inside the vehicle. (6) The monitoring of the inside temperature of the transport boxes is recommended. <br> By the proper use of such transport boxes the recommended temperatures can be maintained over one working day.</p> <p> </p>
Model Data for "Increased Ocean Heat Convergence into the High Latitudes with CO2-Doubling Enhances Polar-Amplified Warming."
<p>This is the data repository for the following published study:</p> <p>Singh HA, Rasch PJ, and Rose BEJ. "Increased Ocean Heat Convergence into the High Latitudes with CO<sub>2</sub>-Doubling Enhances Polar-Amplified Warming", Geophysical Research Letters, Oct 2017, doi: 10.1002/2017GL074561.</p> <p>Please see 'README.txt' for further details on the data files included.</p>
Heat wave and cold snap event library under various technical choices for NERC subregions in the conterminous U.S. (1980 - 2024)
<p>This <strong>Extreme Thermal Event Library</strong> provides comprehensive records of heat wave and cold snap events from 1980 to 2024, aggregated at the North American Electric Reliability Corporation (NERC) subregion level for the conterminous United States. A map of NERC subregions with county-level mean temperatures is included in the file <strong>'NERC_subregions_with_mean_temperature.tif'</strong>.</p> <p>The heat wave and cold snap events were identified using temperature data simulated by the Thermodynamic Global Warming (TGW) model. The raw TGW hourly temperature data (at a 12-km resolution) was aggregated to the county level using spatial averaging within county boundaries. Daily mean, maximum, and minimum temperatures were then derived from the hourly surface air temperature data for each county. Subsequently, the county-level daily temperatures were spatially aggregated to the NERC subregion level using three distinct spatial aggregation methods:</p> <ol> <li><strong>Simple Mean (SM)</strong>: A simple average of county-level temperatures.</li> <li><strong>Area-Weighted Mean (MWA)</strong>: Weighted by the area of each county.</li> <li><strong>Population-Weighted Mean (MWP)</strong>: Weighted by the population of each county.</li> </ol> <p>The database includes separate zipped files for each spatial aggregation method:</p> <ul> <li><strong>"heat_wave_library_NERC_average.zip"</strong> and <strong>"cold_snap_library_NERC_average.zip"</strong> contain events based on the SM method.</li> <li><strong>"heat_wave_library_NERC_average_area.zip"</strong> and <strong>"cold_snap_library_NERC_average_area.zip"</strong> contain events based on the MWA method.</li> <li><strong>"heat_wave_library_NERC_average_pop.zip"</strong> and <strong>"cold_snap_library_NERC_average_pop.zip"</strong> contain events based on the MWP method.</li> </ul> <p>Each zipped file includes 12 event libraries, corresponding to 12 different event definitions. Details about these definitions are provided in the file <strong>'Event definitions.docx'</strong>.</p> <p> </p> <h3><strong>Event Library Structure</strong></h3> <p>Each row in an event library represents one detected thermal event. The columns in the library are defined as follows:</p> <ul> <li><strong>start_date</strong>: Start date of the event.</li> <li><strong>end_date</strong>: End date of the event.</li> <li><strong>centroid_date</strong>: The centroid date, calculated as the midpoint between the start and end dates.</li> <li><strong>highest_temperature / lowest_temperature</strong>: The highest daily maximum temperature (for heat waves) or lowest daily minimum temperature (for cold snaps), in Kelvin.</li> <li><strong>duration</strong>: Duration of the event in days.</li> <li><strong>NERC_ID</strong>: Identifier for the NERC subregion.</li> <li><strong>spatial_coverage</strong>: The spatial coverage of the event within the NERC subregion, expressed as the percentage of counties experiencing the event relative to the total number of counties in the subregion.</li> </ul>
Energy and specific heat for J=7/2 magnetic crystals
<p>Complementary data for the manuscript "Specific heat of Gd3+ and Eu2+ -based magnetic compounds" by D.J. Garcia, J. Sereni and A.A. Aligia[1].</p> <p>We include the energy and specific heat for many magnetic lattices. The magnetic moment is S=7/2. Interactions are taken as Heisenberg-like</p> <p>H = Sum_{i,\delta} J_\delta S_i S_{i+\delta}</p> <p>and \delta is taken to consider first, second, and possibly more nearest neighbors.</p> <p>Interactions are either all FM or AF to keep the system non-frustrated. We take all |J_\delta|=1K unless otherwise stated.</p> <p>Computations are performed using quantum Monte Carlo (QMC) simulations from the ALPS libraries (“dirloop_sse” package) [2, 3]. Most calculations are done using 20^3 conventional unit cells.</p> <p><strong>Directory name</strong> convention is as follows:</p> <p>fig*data/{Lattice Name}( {effective z}) , J_2 = ... , J_3 =... , K=... , L={size of the linear length} )</p> <p>fig*data refers to data of the corresponding figure in reference [1].</p> <p><em>Lattice names</em> are BCC, Diamond, FCC, HCP, and SC with their classic meaning of Body-Centered Cubic, Face-centered cubic, Hexagonal close-packed, and simple cubic.</p> <p>LHc corresponds to a layered honeycomb lattice with three NN within the plane of the honeycomb layer and one above or below the layer in alternating sites.</p> <p><em>magnetic order</em> is either ferromagnetic (FM) or antiferromagnetic (AF).</p> <p><em>effective z </em>agree<em>s </em>with the<em> number of neighbors</em> when all J_\delta are equal. It is computed by increasing the considered neighbor radius. See [1].</p> <p>The file<strong> SpecificHeatAndEnergy.tgz</strong> contains the raw data for all lattices in txt format. This version updates results with larger statistics. An ALPS example directory is also included.</p> <p>Finite size effects are almost negligible in these cases except for the antiferromagnetic simple cubic lattice ( SC_AF(6) ).</p> <p> </p> <p>[1] D. J. Garcia, J. G. Sereni, A. A. Aligia, "Specific heat of Gd3+ and Eu2+-based magnetic compounds", arXiv:2410.23519</p> <p>[2] A. Albuquerque, F. Alet, P. Corboz, P. Dayal, A. Feiguin, S. Fuchs, L. Gamper, E. Gull, S. Gürtler, A. Honecker, R. Igarashi, M. Körner et al., The ALPS project release 1.3: Open- source software for strongly correlated systems, Journal of Magnetism and Magnetic Materials 310(2, Part 2), 1187 (2007), doi:https://doi.org/10.1016/j.jmmm.2006.10.304, Proceedings of the 17th International Conference on Magnetism. </p> <p>[3] B. Bauer, L. D. Carr, H. G. Evertz, A. Feiguin, J. Freire, S. Fuchs, L. Gamper, J. Gukelberger, E. Gull, S. Guertler, A. Hehn, R. Igarashi et al., The ALPS project release 2.0: open source software for strongly correlated systems, Journal of Statistical Mechanics: Theory and Experiment 2011(05), P05001 (2011), doi:10.1088/1742-5468/2011/05/P05001.</p>
Photosynthesis in newly-developed leaves of heat-tolerant wheat acclimates to long-term nocturnal warming
<p>We examined photosynthetic capacity of newly-developed and pre-existing flag leaves of four wheat genotypes under three night temperatures (15, 20 and 25 °C) and common day temperature of 26 °C in two controlled environment experiments. In newly-developed leaves which acclimated (i.e. maintained or increased) the maximum rate of net CO<sub>2</sub> assimilation (<em>A</em><sub>n</sub>) to long-term (9–13 weeks) nocturnal warming, acclimation was underpinned by greater capacity of Rubisco carboxylation (<em>V</em><sub>cmax</sub>) and photosynthetic electron transport (<em>J</em>). This indicates a night-dependent temperature sensitivity of the activation state of Rubisco. Metabolite profiling linked acclimation of <em>A</em><sub>n</sub> to greater accumulation of monosaccharides and saturated fatty acids in leaves, suggesting roles for osmotic adjustment of leaf turgor pressure and maintenance of cell membrane integrity. By contrast, warm night-induced inhibition of <em>A</em><sub>n</sub> was related to reductions in stomatal conductance of CO<sub>2</sub> and <em>J</em>, despite higher basal electron transport thermal stability: <em>T</em><sub>crit</sub> 51 of 45–46.5 °C in non-acclimated versus <em>T</em><sub>crit</sub> of 43.8–45 °C in acclimated leaves. Pre-existing leaves exposed to short-term nocturnal warming (5–7 nights) showed no change in instantaneous temperature responses of <em>A</em><sub>n</sub> and photosynthetic capacity, except for an elite heat-tolerant genotype. These findings can be used to support strategies for developing climate-resilient wheat.</p>
Data and code for: Acute heat priming promotes short-term climate resilience of early life stages in a model sea anemone
<p>Across diverse taxa, sublethal exposure to abiotic stressors early in life can lead to benefits such as increased stress tolerance upon repeat exposure. This phenomenon, known as hormetic priming, is largely unexplored in early life stages of marine invertebrates, which are increasingly threatened by anthropogenic climate change. To investigate this phenomenon, larvae of the sea anemone and model marine invertebrate <em>Nematostella vectensis</em> were exposed to control (18°C) or elevated (24°C, 30°C, 35°C, or 39°C) temperatures for 1 hour at 3 days post-fertilization (DPF), followed by return to control temperatures (18°C). The animals were then assessed for growth, development, metabolic rates, and heat tolerance at 4, 7, and 11 DPF. Priming at intermediately elevated temperatures (24°C, 30°C, or 35°C) augmented growth and development compared to controls or priming at 39°C. Indeed, priming at 39°C hampered developmental progression, with around 40% of larvae still in the planula stage at 11 DPF, in contrast to 0% for all other groups. Total protein content, a proxy for biomass, and respiration rates were not significantly affected by priming, suggesting metabolic resilience. Heat tolerance was quantified with acute heat stress exposures, and was significantly higher for animals primed at intermediate temperatures (24°C, 30°C, or 35°C) compared to controls or those primed at 39°C at all time points. To investigate a possible molecular mechanism for observed changes in heat tolerance, the expression of heat shock protein 70 (HSP70) was quantified at 11 DPF. Expression of HSP70 significantly increased with increasing priming temperature, with the presence of a doublet band for larvae primed at 39°C, suggesting persistent negative effects of priming on protein homeostasis. Interestingly, primed larvae in a second cohort cultured to 6 weeks post-fertilization continued to display hormetic growth responses, whereas benefits for heat tolerance were lost; in contrast, negative effects of short-term exposure to extreme heat stress (39°C) persisted. These results demonstrate that some dose-dependent effects of priming waned over time while others persisted, resulting in heterogeneity in organismal performance across ontogeny following priming. Overall, these findings suggest that heat priming may augment the climate resilience of marine invertebrate early life stages via the modulation of key developmental and physiological phenotypes, while also affirming the need to limit further anthropogenic ocean warming.</p>
Dataset for illustrative examples using the Lagrangian Atmospheric moisTure and heaT trackINg (LATTIN) tool
<p>This dataset provides the FLEXPART outputs for the illustrative examples of LATTIN usage. See the LATTIN GitHub repository (https://github.com/apalarcon/LATTIN) for details.</p><p>It was generated using FLEXPART model v9 fed by ERA-Interim reanalysis at the Environmental Physics Laboratory (EPhysLab) at the University of Vigo. See the list of publications of the EPhysLab research group for details on these simulations (https://ephyslab.uvigo.es/moisturetransport/index.php/Publications). </p>
Datasets used for "Heat Pump - Heating Electrification and Climate Change - Grid Impact Studies"
<h2> Summary</h2> <p> </p> <p>In this work, we explore long term patterns in electricity demand driven by the dual effects of space heating electrification and climate change. We use an open source nodal power system model of the Electric Reliability Council of Texas (ERCOT) system to investigate a wide range of future climate and technology scenarios that evolve over time, and report results in terms of market prices, reliability and corresponding relative capacity requirements </p> <h2> About </h2> <p>The technical analysis aimed to:</p> <h3>1) Understand the Long-Term Patterns:</h3> <p>We aim to analyze patterns in peak load, total load, loss of load, and the seasonality of these phenomena, driven by widespread heat pump adoption alongside climate change.</p> <h3>2) Use Extensive Scenario Analysis:</h3> <p>Explore a wide range of future scenarios, including variations in climate pathways, to capture the uncertainty associated with these long-term changes. In total, 1280 simulation years.</p> <h3>3) Use a validated open source DC OPF model(reproducibility)</h3> <p>Use an open-source nodal power system model of the ERCOT system to simulate and understand the potential impacts on market prices, reliability, and relative capacity requirements. Similar models are available for all interconnections of the conterminous US.</p> <h3>4) Assess Grid Vulnerability:</h3> <p>Assess the vulnerability of the grid to these simultaneous changes, identify potential vulnerability.</p> <h3>5) Provide Insights for System Planners:</h3> <p>Offer results that can assist long-term system planners in anticipating and preparing for potential shifts in grid reliability.</p>
Paper data and code of manuscript: Intraspecific variation on heat tolerance in a model ectotherm: effects of body mass, cell size, oxygen and sex
<p>When using the data or code from this manuscript, please cite it as:</p><p><strong>Leiva FP</strong>, Santos M, Rezende E, & Verberk WCEP. 2021. Paper data and code of manuscript: Intraspecific variation on heat tolerance in a model ectotherm: effects of body mass, cell size, oxygen and sex. Zenodo. <a href="https://doi.org/10.5281/zenodo.5120028">https://doi.org/10.5281/zenodo.5120028</a>.</p>
Dataset and analysis file for 3-factor solution for heat pump perception study using Q-methodology in Groningen, the Netherlands
<p>Dataset and analysis using KEN-Q method for a 3-factor solution for heat pump perception study using Q-methodology in Groningen, the Netherlands</p>
Data from: Ability of seedlings to survive heat and drought portends future demographic challenges for five southwestern US conifers
<p>Climate change and disturbance are altering forests and the rates and locations of tree regeneration. We examined seedling survival of five southwestern United States (US) conifer species found in warmer and drier woodlands (<em>Pinus edulis</em>, <em>P. ponderosa</em>) and cooler and wetter subalpine forests (<em>Pseudotsuga menziesii</em>, <em>Abies concolor</em>, and <em>Picea engelmanii</em>) under hot and dry conditions in incubators. We constructed models that explained 53% to 76% of the species-specific survival variability, then applied these to recent climate (1980-2019) and projected climate (1980-2099) for the southwestern US. We found that lower elevations within species' range would have low survival under projected climate and that range contraction would be greatest for species that currently occupy warm-dry conditions. These results demonstrate that empirically derived physiological limitations can be used to identify where species composition or vegetation type change are likely to occur in the southwest US.</p>
Data for "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis"
<p>Raw data associated with the publication "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis". Temperature profile, daily measurements, physiological measurements, elemental analysis, NanoSIMS data, and cell density data are included as individual tabs in the Excel file. </p>
Data from: Testing the heat treatment dose for Agrilus planipennis prepupae using the Humble water bath
<p>The lethal heat treatment dose (time and temperature) for the pre-pupal life stage of <em>Agrilus planipennis</em> Fairmaire (Coleoptera: Buprestidae), emerald ash borer, was determined through an in vitro application using a carefully calibrated heat treatment apparatus. The lethal and sublethal effects of heat on A. planipennis prepupae were assessed through a ramped heat delivery application, simulating industrial kilns and conventional heat chamber operations, for treatments combining target temperatures of 54 °C, 55 °C, and 56 °C, and exposure durations of 0 min (i.e., kiln temperature ramp only), 15 min, or 30 min. Prepupal emerald ash borer larvae did not survive exposure to 56 °C for 15 min or longer, or to 55 °C for 30 min. Sublethal effects were observed for all other treatments. Sublethal effects included delayed development and failure to complete the pupal and adult life stages. The datasets and associated R statistical computing langauge code are deposited here.</p>
CIGAR-CS Global Ocean Reanalysis 1961-2022 Ocean Heat Content
<p>Dataset describing the <strong>CIGAR-CS (v1) </strong>reanalysis Ocean Heat Content.</p> <p><strong>CIGAR</strong>: The CNR ISMAR Global Historical Reanalysis (<a href="http://cigar.ismar.cnr.it">http://cigar.ismar.cnr.it</a>)</p> <p><strong>CS</strong>: Contemporary Stream</p> <p>CIGAR-CS is an ensemble ocean reanalysis with 32 members, covering the period from 1959 to real-time, and based on the NEMO4 model, a variational data assimilation scheme with variational quality control of in-situ profiles and time-varying background-error covariances, a surface correction scheme of air-sea fluxes, a deep-ocean bias correction scheme, and an advanced ensemble generation scheme with stochastic physics and perturbation of input datasets.</p> <p>It includes yearly mean files for each of the <strong>32 ensemble members</strong> from 1961-2022 for these selected variables:<br> - Ocean heat content (full column)<br> - Temperature analysis increments<br> - Surface net air-sea heat fluxes</p> <p>Heat fluxes and analysis increments are provided for potential use in ocean warming attribution studies.</p> <p>To ease the use of the OHC data, all fields are remapped from the irregular ORCA1 tripolar grid (1/3deg to 1deg of spatial resolution) to a regular 0.5degx0.5deg grid through bilinear interpolation.</p> <p>(Note: all diagnostics in the reference paper were computed on the native irregular grid; possible differences, therefore, may exist and are due to the errors introduced by the interpolation)</p>
Dataset for A Statistical Survey of E-region Anomalous Electron Heating Using Poker Flat Incoherent Scatter Radar Observations
<p>This archive contains the complete list of anomalous electron heating (AEH) events in PFISR data between 2010 and 2023 identified by Zhang and Varney (2024), along with the code necessary to reproduce the results. The main list of AEH events is in the file AEH_event_list.csv, and the rest of this archive is supporting information for reproducibility.</p> <p>The files contained are:</p> <p>algo1.ipynb: Python notebook implementing algorithm 1.</p> <p>algo2.py: Python script implementing algorithm 2.</p> <p>algo3.ipynb: Python notebook implementing algorithm 3.</p> <p>algo4.ipynb: Python notebook implementing algorithm 4.</p> <p>cal_velo.py: Python function to calculate ion velocity.</p> <p>io_utils.py: Python functions for manipulating AMISR hdf5 files.</p> <p>Fig1.ipynb: Python notebook to recreate figure 1.</p> <p>Fig2,5.ipynb: Python notebook to recreate figures 2 and 5.</p> <p>Fig3,11.ipynb: Python notebook to recreate figures 3 and 11.</p> <p>Fig4.ipynb: Python notebook to recreate figure 4.</p> <p>Fig6.ipynb: Python notebook to recreate figure 6.</p> <p>Fig7,8,9,10.ipynb: Python notebook to recreate figures 7, 8, 9, and 10.</p> <p>PFISR_Data_Quality_Checker.ipynb: Python notebook with data preprocessing and quality checking.</p> <p>Table1.ipynb: Python notebook to extract the beamcode information needed for table 1.</p> <p>AEH_events_list.csv: Complete list of AEH events identified by algorithms 1, 3, and 4. The first column indicates the UT time of the start of the event, and 1 or 0 in the three columns denote whether the event was or was not detected by the algorithm, respectively.</p> <p>AEH_in_2010&2011.csv: Spreadsheet to facilitate direct comparisons with previous work on AEH in 2010 and 2011.</p> <p>f107.json: Smoothed F10.7 data used in this study.</p> <p>AEH_Detection_Outputs.zip: Archive of all of the raw output of the python scripts running the detection algorithms.</p> <p>AE&PAE.zip: Archive of all AE data used in this study.</p>
Data from: Extreme heat reduces host and parasite performance in a butterfly-parasite interaction
<p>Environmental temperature fundamentally shapes insect physiology, fitness, and interactions with parasites. Differential climate warming effects on host versus parasite biology could exacerbate or inhibit parasite transmission, with far-reaching implications for pollination services, biocontrol, and human health. Here, we experimentally test how controlled temperatures influence multiple components of host and parasite fitness in monarch butterflies (<em>Danaus plexippus</em>) and their protozoan parasites <em>Ophryocystis elektroscirrha</em>. Using five constant temperature treatments spanning 18-34°C, we measured monarch development, survival, size, immune function, and parasite infection status and intensity. Monarch size and survival declined sharply at 34°C, as did infection probability, suggesting that hot temperatures decrease both host and parasite performance. The lack of infection at 34°C was not due to greater host immunity or faster larval development but could instead reflect the thermal limits of parasite invasion and within-host replication. In the context of ongoing climate change, our experiment suggests that temperature increases above the upper thermal range will reduce the fitness of both monarchs and their parasites, with lower infection rates potentially mitigating the impact of extreme heat on future monarch abundance and distribution.</p>
Data from: The interactive effects of heat stress, parasitism, and hostplant quality in a host-parasitoid system
<p>Species interactions are expected to change in myriad ways as the frequency and magnitude of extreme temperature events increase with anthropogenic climate change. The relationships between endosymbionts, parasites, and their hosts are particularly sensitive to thermal stress, which can have cascading effects to other trophic levels. We investigate the interactive effects of heat stress and parasitism on a terrestrial tritrophic system consisting of two hostplants (one common, high-quality plant and one novel, low-quality plant), a caterpillar herbivore, and a specialist parasitoid wasp. We used a fully-factorial experiment to determine the bottom-up effects of the novel hostplant on both the caterpillars' life history traits and the wasps' survival, and the top-down effects of parasitism and heat shock on caterpillar developmental outcomes and herbivory levels. Hostplant identity interacted with thermal stress to affect wasp success, with wasps performing better on the low-quality hostplant under constant temperatures but worse under heat shock conditions. Surprisingly, caterpillars consumed less leaf material of the low-quality hostplant to reach the same final mass across developmental outcomes. In parasitized caterpillars, heat shock reduced parasitoid survival and increased both caterpillar final mass and development time on both hostplants. These findings highlight the importance of studying community-level responses to climate change from a holistic and integrative perspective and provide insight into potential substantial interactions between thermal stress and diet quality in plant-insect systems.</p>
Heat pumps for all? Distributions of the costs and benefits of residential air-source heat pumps in the United States
<p>Dataset for the "<span>Heat pumps for all? Distributions of the costs and benefits of residential air-source </span><span>heat pumps in the United States" paper</span></p>
Replication data for: Operating Strategies of an Industrial R717 Heat Pump Recovering Waste Heat of a Chiller
<p>This dataset contains the data of the publication:<br> Verdnik, M., Wagner, P., Rieberer, R., 2022. Operating Strategies of an Industrial R717 Heat Pump Recovering Waste Heat of a Chiller. Proc. International Congress of Refrigeration 2023, Paris, France</p>
Changes in core-mantle boundary heat flux patterns throughout the supercontinent cycle: Data
<p>This repository accompanies the paper</p> <p> </p> <p>```</p> <p>Dannberg, J., Gassmoeller, R., Thallner, D., LaCombe, F., Sprain, C.: Changes in core-mantle boundary heat flux patterns throughout the supercontinent cycle.</p> <p>```</p> <p> </p> <p>This repository contains instructions for how to obtain the boundary conditions from GPlates, ASPECT code, data and model setups, and scripts for converting the ASPECT model output to spherical harmonics so it can be used in geodynamic simulations. To reproduce the workflow follow the steps:</p> <p> </p> <p>- To create the velocity boundary conditions for the ASPECT models, download the plate reconstruction from 'Merdith, A.S., Williams, S.E., Collins, A.S., Tetley, M.G., Mulder, J.A., Blades, M.L., Young, A., Armistead, S.E., Cannon, J., Zahirovic, S. and Müller, R.D., 2021. Extending full-plate tectonic models into deep time: Linking the Neoproterozoic and the Phanerozoic. Earth-Science Reviews, 214, p.103477', which can be found here:</p> <p> </p> <p>https://doi.org/10.5281/zenodo.4485738</p> <p> </p> <p>To create the 'lat_lon_velocity' files, take the following steps in GPlates:</p> <p> </p> <p>1. Load all of the files from the Merdith et al, 2021 plate reconstruction into a Feature Collection which can be saved as a project (the project for our visualization is 'project.gproj').</p> <p>2. Establish the output grid (ours is lat_lon_velocity_domain_91_181): Features -> Generate Velocity Domain Points -> Latitude Longitude -> Number of latitudinal grid intervals=91, Number of longitudinal grid intervals=181, number of nodes=16652.</p> <p>3. To output the point velocities we used for the models: Reconstruction -> Export -> Add Export -> Velocities, GPML(*.gpml), velocity_%nMa</p> <p>- The data files we created following this workflow are part of this data publication and can be found in the `lat_lon_velocity` folder.</p> <p> </p> <p>- The global spherical convection models of the publication were created using two different ASPECT configurations:</p> <p> </p> <p>Models `thermal`, `thermochemical`, and `p-T-dependent` were run using:</p> <p> </p> <p>```</p> <p>-----------------------------------------------------------------------------</p> <p>-- This is ASPECT, the Advanced Solver for Problems in Earth's ConvecTion.</p> <p>-- . version 2.4.0-pre (limit_shear_heating, 4f45a72fe)</p> <p>-- . using deal.II 9.4.0-pre (3d869ba6cd1fd462624e09dc232e34ed17880701)</p> <p>-- . with 64 bit indices and vectorization level 2 (256 bits)</p> <p>-- . using Trilinos 12.18.1</p> <p>-- . using p4est 2.3.2</p> <p>-----------------------------------------------------------------------------</p> <p>```</p> <p> </p> <p>Models `strong basalt` and `weak ppv` were run using:</p> <p> </p> <p>```</p> <p>-----------------------------------------------------------------------------</p> <p>-- This is ASPECT, the Advanced Solver for Problems in Earth's ConvecTion.</p> <p>-- . version 2.5.0-pre (limit_shear_heating_and_ppv, a4812c95a)</p> <p>-- . using deal.II 9.4.2</p> <p>-- . with 64 bit indices and vectorization level 3 (512 bits)</p> <p>-- . using Trilinos 13.2.0</p> <p>-- . using p4est 2.3.2</p> <p>-----------------------------------------------------------------------------</p> <p>```</p> <p> </p> <p>- The two modified ASPECT versions are included in this data package. The repository including full</p> <p>version history is until further notice available as branch `limit_shear_heating` and branch `limit_shear_heating_and_ppv`</p> <p>in the repository `https://github.com/jdannberg/aspect.git`.</p> <p> </p> <p>- Running these models also requires plugins that are located in the `shared_libs` folder in this repository and that need to be compiled. Navigate into this directory and follow the steps:</p> <p> </p> <p>1. `cmake -D Aspect_DIR=PATH_TO_ASPECT` (replace `PATH_TO_ASPECT` with the directory where you compiled ASPECT).</p> <p>2. `make`</p> <p>- Now the models in this repository can be started. You should start them from the `input_files` directory so that all paths are set correctly and you can start them with the ASPECT executable in your build folder.</p> <p> </p> <p>- The files in `aspect_input_files` correspond to the models presented in the paper following the same naming scheme.</p> <p> </p> <p>- To convert the ASPECT heat flux output to spherical harmonics we used the script `analyze_heatflux_mpi_gmt.py` in `SPH_scripts`,</p> <p>which requires modification to point to the correct ASPECT statistics file and the correct output directory.</p> <p> </p> <p>- The final heat flux output is included in this data package in the `heat_flux` folder, which includes archives of the processed heat flux output in 1 Myr time intervals with 0 being the start of the model run and the highest timestep number representing the present day state.</p>
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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.