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2,208 results for “coupling”
Network files and Python code used in "Designing a sector-coupled European energy system robust to 60 years of historical weather data"
<p><strong>Description</strong></p> <p>This repository contains data presented in the paper <a href="https://www.nature.com/articles/s41467-024-54853-3" target="_blank" rel="noopener">Designing a sector-coupled European energy system robust to 60 years of historical weather data</a>. It contains the derived metrics (.csv) files from a:</p> <ol> <li>joint capacity and dispatch optimization with weather years (design years) from 1960 to 2021 as input</li> <li>dispatch optimization of the 62 capacity layouts using weather years (operational years) different from the design year.</li> </ol> <p>All results from (1) are found in "Capacity_optimization.zip" and results from (2) are found in "Dispatch_optimization.zip".</p> <p>The resulting network files (both from the capacity and dispatch optimization) are located <a href="https://anon.erda.au.dk/cgi-sid/ls.py?share_id=DuGvDWlkeI">here</a>.</p> <p>We also provide the Python code used to derive the metrics and to create the visualizations included in the paper. This is located in "Jupyter_notebooks". The Jupyter notebooks refer to Python scripts located <a href="https://github.com/ebbekyhl/multi-weather-year-assessment">here</a>.</p> <p><strong>Revisions:</strong></p> <p>This version includes the following additions compared to the previous versions: </p> <ul> <li>Timeseries of nodal loads for all years</li> <li>Timeseries of nodal heat pump Coefficient of Performance (COP) </li> <li>Nodal capacity and hourly capacity factors </li> </ul>
Data associated with the study: Unlocking DAS amplitude information through coherency coupling quantification
<p>Data associated with the study: Unlocking DAS amplitude information through coherency coupling quantification</p> <p>Here we include all DAS data used in the study that is not included in an open access repository elsewhere.</p> <p>Contents of this repository are:<br>Rutford icestream data:<br>1. Rutford_ice_stream_das_data/icequakes_information.csv - A csv file containing icequake information, including origin times and seismic moment.<br>2. Rutford_ice_stream_das_data/tdms/*.tdms - Raw DAS data recordings over the time periods when the icequakes occured. Data is recorded by a Silixa iDas.<br>(All other information on the deployment can be found in Hudson et al. (2021), JGR).</p> <p>Gornergletscher data:<br>3. Gornergletscher_das_data/gornerglethscer_das_qm_stations.csv - A file containing coordinates of all the fibre channels.<br>4. Gornergletscher_das_data/segy/*.sgy - Raw data files for the time periods used in this study. </p> <p> </p>
Strain partitioning, interseismic coupling, and shallow creep along the Ganzi-Yushu fault from Sentinel-1 InSAR data
<p>The dataset includes the InSAR velocity data and fault coupling model in the article "Strain partitioning, interseismic coupling, and shallow creep along the Ganzi-Yushu fault from Sentinel-1 InSAR data" (<a href="https://doi.org/10.1029/2024GL111469">https://doi.org/10.1029/2024GL111469</a>). The "insardata.zip" file includes original data of 5 tracks export from MintPy software, and the detailed format of the data can be found in the instruction provided by the MintPy software (<a href="https://github.com/insarlab/MintPy">GitHub - insarlab/MintPy: Miami InSAR time-series software in Python</a>). The "couplingmodel.gmt" is the fault coupling distribution along the Ganzi-Yushu fault, formatted for utilization in GMT software (<a href="https://github.com/GenericMappingTools/gmt">GitHub - GenericMappingTools/gmt: The Generic Mapping Tools</a>).</p>
Computational data for Structure of G protein-coupled receptor GPR1 bound to full-length chemerin adipokine reveals a chemokine-like reverse binding mode
<p>MD simulation data for the research article titled "Structure of G protein-coupled receptor GPR1 bound to full-length chemerin adipokine reveals a chemokine-like reverse binding mode".</p>
Data for "Controlling Plasmonic Catalysis via Strong Coupling with Electromagnetic Resonators"
<p>This upload includes the data presented and analyzed in the article "Controlling Plasmonic Catalysis via Strong Coupling with Electromagnetic Resonators" by Jakub Fojt, Paul Erhart, and Christian Schäfer.</p> <p>The codes for reproducing the data are provided at <a href="https://doi.org/10.5281/zenodo.13374591">doi:10.5281/zenodo.13374591</a>.</p> <p>See <em>README.md</em> in <em>data.zip</em> for a detailed description.</p>
Dataset for ''Tuning the proximity induced spin - orbit coupling in bilayer graphene/WSe2 heterostructures with pressure''
<p>This is the measurement dataset for the article ''Tuning the proximity induced spin - orbit coupling in bilayer graphene/WSe2 heterostructures with pressure''. The .py file is also included which is used for the modelling.</p>
The Seasonality of the Heat Budget on the Ross Sea Continental Shelf in a Coupled Regional Ocean-Sea Ice-Ice Shelf Model
<p>This dataset includes the model data used in our paper entitled 'The Seasonality of the Heat Budget on the Ross Sea Continental Shelf in a Coupled Regional Ocean-Sea Ice-Ice Shelf Model'</p>
Air–Sea Coupling Feedbacks over Tropical Instability Waves
<p>This dataset contains a selection of the CROCO-WRF regional coupled model simulation output created and published in the article:</p> <p>Holmes, R., Renault, L., Maillard, L. and Boucharel, J. (2024) Air-sea coupling feedbacks over Tropical Instability Waves, J. Phys. Oceanogr., https://doi.org/10.1175/JPO-D-24-0010.1</p> <p>This dataset contains monthly-averaged output of several key surface variables analysed in the above article. These variables are provided for each of the 5 ensemble members of each of the 4 experiments: 1) the Control, 2) the NoMesoTFB experiment, 3) the NoMesoCFB experiment and 4) the NoCFB experiment. Each of the included tar archives contains all the variables for that experiment. For each experiment, this consists of the following files:</p> <p>croco_out_mon_exp**.ncrcat.nc: 5 files, one for each ensemble member, containing monthly mean SST (temp), zonal velocity (u), meridional velocity (v) and sea level (zeta).</p> <p>croco_out_mon_hp_exp**.ncrcat.nc: 5 files, one for each ensemble member, containing monthly mean high-pass (using the longitude filter described in the article) variances of SST (SST_hp_var), zonal velocity (U_hp_var), meridional velocity (V_hp_var), eddy wind work zonal component (high-pass(u)*high-pass(tau_x), EWWU) and eddy wind work meridional component (high-pass(v)*high-pass(tau_y), EWWV). </p> <p>wrf3d_1M_hp_exp**.ncrcat.nc: 5 files, one for each ensemble member, containing monthly mean high-pass (net surface heat flux) * high-pass (SST), computed on the WRF grid using the longitude filter described in the article [QofSST_hp]. This can be used to compute the APE production by surface heat flux anomalies.</p> <p>This is only a subset of the data used in the article, the largest subset of useful variables that fits within the 50GB Zenodo limit. If other variables are of interest, please contact the lead author.</p> <p>An extensive set of analysis scripts is available on github at https://github.com/rmholmes/PAC12_75_cpl-analysis.</p>
Data Supporting "Air-Sea Momentum Exchange with Explicit Wind-Wave-Current Coupling and Effects on Hurricane Structure and Impacts"
<p>This dataset produced the figures for the Air-Sea Momentum Exchange with Explicit Wind-Wave-Current Coupling and Effects on Hurricane Structure and Impacts Manusrcipt.</p>
Fully coupled thermo-hydro-mechanical loading cycles
<p>Date for "Fully coupled thermo-hydro-mechanical loading cycles".</p>
Dataset for the publication: Synthesis, Characterization and Interconversion of p-Tolylsulfone-Functionalized Norbornadiene/Quadricyclane Couples
<p>Overview of all collected data used for the publication "Synthesis, Characterization and Interconversion of p-Tolylsulfone-Functionalized Norbornadiene/Quadricyclane Couples" in the journal Chemistry - A European Journal.</p>
Inlists for the paper "Mixed-mode coupling in the Red Clump: I. Standard single star models"
<p>This repository contains the inlists and run_star_extras used for the paper "Mixed-mode coupling in the Red Clump: I. Standard single star models" by Walter E. van Rossem, Andrea Miglio, and Josefina Montalban for use with MESA-11701. The grid cycles through masses first (0.7, 1.0, 1.5, 2.3, 3.0 msol) and then metallicity ([Fe/H] = -1.0, -0.5, 0.0, 0.25, 0.4).</p> <p>Runs 0000-0004 have initial [Fe/H] = -1.0 and masses 0.7, 1.0, 1.5, 2.3, 3.0 solar masses respectively. The next five runs (0005-0009) have [Fe/H] = -0.5 and the same order of masses, and so on.</p> <p>The previous version had an error in the calculation for the non-parallel approximation and was missing a squareroot in the subroutine <code>calc_dlnc_ds_s0_part_ap</code> when calculating <code>Nred_km1</code> and <code>Nred_k</code>.</p>
A new target capture phylogeny elucidates the systematics and evolution of wing coupling in sack‐bearer moths
<p>The frenulum is a wing coupling structure that is found on the wings of most families of Lepidoptera. It is a single bristle or set of bristles that originate from the base of the hindwing that often interlocks with the forewing during flight. This wing coupling mechanism is thought to have been a major evolutionary innovation that allowed for enhanced flight in Lepidoptera. The sack-bearer moths (Mimallonidae) are unusual among Lepidoptera in that not all species within the family have a frenulum. We test the hypothesis that the frenulum is not necessary and is therefore lost in mimallonids that have longer male forewings because such wings are perhaps better suited to be coupled by other means. To understand the evolution of the frenulum, we inferred the most taxonomically and genetically sampled anchored hybrid enrichment-based phylogeny of Mimallonidae, including 604 loci from all 41 genera and from 120 species, covering about 40% of the described species in the family. The maximum likelihood tree robustly supports major relationships within the family, and ancestral state reconstruction clearly recovers the frenulum as the plesiomorphic condition in Mimallonidae. Our results show that the frenulum is more often observed in species that have shorter, rather than longer, male forewings. The frenulum has historically been used as an important character for intrafamilial classification in Mimallonidae, but our results conclusively show that this character system is more variable than previously thought. Based on our results, we erect two new subfamilies, Roelofinae St Laurent & Kawahara, <b>subfam. n.</b> and Meneviinae St Laurent, Herbin, & Kawahara, <b>subfam. n.</b>, for four genera previously considered <i>incertae sedis.</i> In the predominantly frenulum-lacking clade Cicinninae, we describe a new genus, <i>Cerradocinnus </i>St Laurent, Mielke, & Kawahara, <b>gen. n.</b>, and the genus <i>Gonogramma </i><b>stat. rev.</b> is revalidated to include many species previously placed in <i>Cicinnus sensu lato</i>. With these changes, <i>Cicinnus </i>can now be considered monophyletic. Thirty-three species are transferred to <i>Gonogramma </i>from <i>Cicinnus sensu lato</i>.</p>
Robust surface-to-mass coupling and turgor-dependent cell width determine bacterial dry-mass density
<p><span>During growth, cells must expand their cell volumes in coordination with biomass to control the level of cytoplasmic macromolecular crowding. Dry-mass density, the average ratio of dry mass to volume, is roughly constant between different nutrient conditions in bacteria, but it remains unknown whether cells maintain dry-mass density constant at the single-cell level and during non-steady conditions. Furthermore, the regulation of dry-mass density is fundamentally not understood in any organism. Using quantitative phase microscopy and a new image-analysis pipeline, we measured absolute single-cell mass and shape of the model organisms </span><i><span>Escherichia coli</span></i><span> and </span><i><span>Caulobacter crescentus</span></i><span> with improved precision and accuracy. We found that cells control dry-mass density indirectly, by expanding their surface, rather than volume, in direct proportion to biomass growth – according to a new surface growth law. At the same time, cell width is controlled independently. Therefore, cellular dry-mass density varies systematically with cell shape, both during the cell cycle or after nutrient shifts, while the surface-to-mass ratio remains nearly constant on the generation time scale. </span><span><span>Transient deviations from constancy during nutrient shifts can be reconciled with turgor-pressure variations and the resulting elastic changes in surface area.</span></span><span> Finally, we find that plastic changes of cell width after nutrient shifts are likely driven by turgor variations, demonstrating an important regulatory role of mechanical forces for width regulation. In conclusion, turgor-dependent cell width and a new, slowly varying surface-to-mass coupling constant are the independent variables that determine dry-mass density.</span></p>
FESOM output supporting: Atmospheric wind biases: A challenge for simulating the Arctic Ocean in coupled models?
<p>AWI-CM1 and FESOM1.4 simulation results used in the manuscript "Atmospheric wind biases: A challenge for simulating the Arctic Ocean in coupled models?".</p>
Supporting data for "Spin-valley coupling in single-electron bilayer graphene quantum dots"
<p>Supporting data and analysis scripts for all figures in the article "Spin-valley coupling in single-electron bilayer graphene quantum dots", preprint: https://arxiv.org/abs/2103.04825</p> <p>The files are sorted according to the figures/panels in the publication with a "0-README.txt" file including further information. </p> <p>The following versions of Pyhton and the packages have been used:<br> python: 3.6.10<br> numpy: 1.18.1<br> matplotlib: 3.1.3<br> scipy: 1.4.1</p>
Body size, trophic position, and the coupling of different energy pathways across a saltmarsh landscape
<p>Here, we listed the bulk stable isotope values (δ13C and δ15N) and body size measurements of organisms that were analyzed in the manuscript "Body size, trophic position, and the coupling of different energy pathways across a saltmarsh landscape", published in Limnology and Oceanography Letters. Our dataset is a compilation of samplings obtained by the Southern Louisiana marsh food webs project within the Coastal Waters Consortium (CWC) II (Lopez-Duarte et al. 2017a [https://doi.org/10.7266/N7XS5SGD], Lopez-Duarte et al. 2017b [https://doi.org/10.7266/N79W0CJW], Polito et al. 2019 [https://doi.org/10.7266/n7-6277-1216]). The dataset consists of 1563 individual samples from 77 taxa, including basal sources (plants, phytoplankton, detritus, and microphytobenthos), fishes, invertebrates (insects, crustaceans, and spiders), infauna, seaside sparrows (Ammospiza maritima), and marsh rice rats (Oryzomys palustris). Samplings were conducted in three sites, Bay Sansbois, Bay Batiste, and West Pointe à la Hache, located in northeastern Barataria Bay. Bay Sansbois and Bay Batiste were sampled in May and October 2015, and May 2016, whereas West Pointe à la Hache was sampled only in May 2016. Body size measurements are available for 59% of all samples (52 taxa) while δ13C and δ15N are available for all samples.</p>
Dataset for "Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice sheet -- climate coupled model"
<p>This archive contains the source data of the figures presented in the manuscript "Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice sheet -- climate coupled model".</p> <p>Contact: aurelien.quiquet@lsce.ipsl.fr</p>
Roach et al. (2019) coupled wave-ice model output (hourly coupling version): Beaufort Sea 2012-2019
<p>Wavewatch III model output from Roach et al. (2019) coupled wave-ice model with hourly coupling from the central Beaufort Sea, spanning 2012-2019.</p> <p>See manuscript below for further details:</p> <p>Roach, L., C. Bitz, C. Horvat, and S. Dean (2019), Advances in modelling interactions between sea ice and ocean surface waves. Journal of Advances in Modeling Earth Systems</p>
Towards highly accurate calculations of parity violation in chiral molecules: relativistic coupled-cluster method including QED-effects
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Towards highly accurate calculations of parity violation in chiral molecules: relativistic coupled-cluster method including QED-effects", by Ayaki Sunaga and Trond Saue.</p>
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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)
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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.