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167 results for “public relations”
Divergent Characteristics of Biomedical Research across Publication Types: A Quantitative Analysis on the Aging-related Research
<p>Attached in pdf here.</p>
Dataset related to the publication "Procedure for automated low uncertainty assessment of empty cavity mode frequencies in Fabry-Pérot cavity based refractometry"
<p>The data set consists of; The published paper, all figures that present measurement or simulation data in .png and .fig format and the underlying data plotted in the figures in text format. The published plots were generated from the fig files. The text files were generated by reading the plotted data from the fig files. The files are named Fig_XX were XX corresponds to the figure number in the publication. The format of the text file is as follows. Before every data set there is a header consisting of; The number of the subplot where the data is plotted (Plot: XX), the number of the data set in the sub plot (DataSet: XX), and the color of the line or marker in the plot (Color: XX). The description of what each color represents can be found in the publication.</p>
Dataset related to the publication "An Invar-based dual Fabry–Perot cavity refractometer for assessment of pressure with a pressure independent uncertainty in the sub-mPa region"
<p>The data set consists of; The published paper, all figures that present measurement or simulation data in .png and .fig format and the underlying data plotted in the figures in text format.<span> </span>The published plots were generated from the fig files. The text files were generated by reading the plotted data from the fig files. The files are named Fig_XX were XX corresponds to the figure number in the publication.<span> </span>The format of the text file is as follows. Before every data set there is a header consisting of; The number of the subplot where the data is plotted (Plot: XX), the number of the data set in the sub plot (DataSet: XX), and the color of the line or marker in the plot (Color: XX). The description of what each color represents can be found in the publication.</p>
Dataset (I.) related to publication: PIP4K2C inhibition reverses autophagic flux arrest induced by SARS-CoV-2
<p>MD simulation data (PIKfyve simulations) related to publication: </p> <p>Karim, M., Mishra, M., Lo, CW. <em>et al.</em> PIP4K2C inhibition reverses autophagic flux impairment induced by SARS-CoV-2. <em>Nat Commun</em> <strong>16</strong>, 6397 (2025). https://doi.org/10.1038/s41467-025-61759-1</p> <ul> <li>The .zip files contain raw Desmond simulation trajectories of PIKfyve in complex with RMC-113 [18 replicas; each 4 us] (-out.cms files and trajectories).</li> </ul> <p> </p>
Dataset related to the publication Rotbarth et al 2024, "Boreal forests are heading for an open state", PNAS
<p>This dataset contains all variables involved in data analysis in the publication Rotbarth et al 2024, "Boreal forests are heading for an open state", PNAS. </p> <p>The meta data file contains explanations for each variable in the main dataset. The second dataset includes mean annual temperatures for the years 2020-2100 based in projections from the EC-Earth3-Veg-LR model. More details on both datasets are provided in the Supplementary information Table S1. </p>
Data related to publication "Coherent phase transfer for real-world twin-field quantum key distribution"
<p>These datasets have been used to produce Figure 3, 4 and 5 of manuscript: "Coherent phase transfer for real-world twin-field quantum key distribution". The files contain two arrays: time in seconds and normalised intensity.</p> <p>Explanation for "Data_fig3_XXX.txt": the files contains the raw data used to produce Fig. 3. The following timespans have been used:</p> <p>Data_fig3_stabilised.txt: t_start= 0.29 s, t_stop=0.292 s</p> <p>Data_fig3_unstabilised.txt: t_start=0.00225 s, t_stop=0.00424 s</p> <p>Explanation for "Data_fig4_XXX.txt" files: the procedure to obtain the phase deviation from the normalised interference is detailed in the text (Methods section). Datasets with different sampling rate have been combined to obtain the phase deviation on the long and short term.</p> <p>Explanation for "Data_fig5.txt": the files contains the raw data used to produce Fig. 5.</p>
Datasets related to publication: Microbial Consortia for Effective Biocontrol of Root and Foliar Diseases in Tomato
<p>Datasets underlying the results presented in the Original Research Article "Microbial Consortia for Effective Biocontrol of Root and Foliar Diseases in Tomato", Frontiers in Plant Science, Volume 12, Article 756368, https://www.frontiersin.org/articles/10.3389/fpls.2021.756368/full, <a href="https://doi.org/10.3389/fpls.2021.756368">https://doi.org/10.3389/fpls.2021.756368</a></p> <p>This research has received funding from the European Union’s Horizon 2020 research and Innovation programme under grant agreement No 765290 (Name of the action: Microbe induced resistance to agricultural pests, Acronym: MiRA).</p>
Dataset (II) related to publication: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist
<p>MD simulation data related to the publication Rashidian et al.: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist. <a href="https://doi.org/10.1016/j.csbj.2022.06.020">https://doi.org/10.1016/j.csbj.2022.06.020</a></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files)</p> <p>dataset I: systems SRL+Co, C-100 and BAY-1797</p> <p>dataset I: each file contains all branched replicas and the main replica.</p> <p>dataset1: C_100_Replica1 contains four branched replicas and the main replica. The two of four branched replicas which stem from the middle of the main replica named: b_c_D1_r1_2285 (corresponding name in the SI data is R1_a) and b_c_D1_2285_r1_2 (corresponding name in the SI data is R1_b).</p> <p>dataset1: C_100_Replica2–5 , each file contains one main replica and the two branches.</p> <p>dataset I: system SRL+Co ;each file contains one main replica</p> <p>dataset I: system BAY-1797; each file contains one main replica</p> <p>dataset II:system SRL ; each file contains one main replica.</p>
Dataset (I) related to publication: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist
<p>MD simulation data related to the publication Rashidian et al.: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist. <a href="https://doi.org/10.1016/j.csbj.2022.06.020">https://doi.org/10.1016/j.csbj.2022.06.020</a></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files)</p> <p>dataset I: systems SRL+Co, C-100 and BAY-1797</p> <p>dataset I: each file contains all branched replicas and the main replica.</p> <p>dataset1: C_100_Replica1 contains four branched replicas and the main replica. The two of four branched replicas which stem from the middle of the main replica named: b_c_D1_r1_2285 (corresponding name in the SI data is R1_a) and b_c_D1_2285_r1_2 (corresponding name in the SI data is R1_b).</p> <p>dataset1: C_100_Replica2–5 , each file contains one main replica and the two branches.</p> <p>dataset I: system SRL+Co ;each file contains one main replica</p> <p>dataset I: system BAY-1797; each file contains one main replica</p> <p>dataset II:system SRL ; each file contains one main replica.</p>
Dataset (III) related to publication: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist
<p>MD simulation data related to the publication Rashidian et al.: Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist. <a href="https://doi.org/10.1016/j.csbj.2022.06.020">https://doi.org/10.1016/j.csbj.2022.06.020</a></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files)</p> <p>dataset I: systems SRL+Co, C-100 and BAY-1797</p> <p>dataset I: each file contains all branched replicas and the main replica.</p> <p>dataset1: C_100_Replica1 contains four branched replicas and the main replica. The two of four branched replicas which stem from the middle of the main replica named: b_c_D1_r1_2285 (corresponding name in the SI data is R1_a) and b_c_D1_2285_r1_2 (corresponding name in the SI data is R1_b).</p> <p>dataset1: C_100_Replica2–5 , each file contains one main replica and the two branches.</p> <p>dataset I: system SRL+Co ;each file contains one main replica</p> <p>dataset I: system BAY-1797; each file contains one main replica</p> <p>dataset II:system SRL ; each file contains one main replica.</p> <p>dataset III:system C-100+Co (compound 100 in presence of SRC-1 coactivator) ; each file contains one main replica.</p>
Dataset related to the publication "New Technique for Probing the Protecting Character of the Solid Electrolyte Interphase as a Critical but Elusive Property for Pursuing Long Cycle Life Lithium-Ion Batteries"
<p>The formation of a protecting nano-layer, so-called Solid Electrolyte Interphase (SEI), on the negative electrode of Li-ion batteries (LIBs) from product precipitation of the cathodic decomposition of the electrolyte is a blessing since the electrically-insulating nature of this nano-layer protect the electrode surface preventing continuous electrolyte decomposition and enabling the large nominal cell voltage of LIBs, e.g. 3.3 – 3.8 V. Thus, the protecting performance of the nano-layer SEI is essential for LIBs to achieve long cycle life. Unfortunately, evaluation of this critical property of the SEI is not trivial. Herein, a new, cheap and easily-implementable methodology is presented to estimate the protecting quality of the SEI; the redox-mediated enhanced coulometry. The key element of the methodology is the addition of a redox-mediator in the electrolyte during degassing step (after the SEI formation cycle). The redox-mediator leads to an internal self-discharge process that is inversely proportional to the protecting character of the SEI. And the self-discharge process results in an easily-measurable decrease in coulombic efficiency. The influence of vinylene carbonate as electrolyte additive in the resulting SEI is used as case study to showcase the potential of the proposed methodology</p>
Data and scripts related to Cottaar, Martin, Li, Parai (2022) publication in Seismica
<p><strong>Codes and data for<br> Cottaar, Martin, Li, Parai, 2022, The root to the Galápagos mantle plume on the core-mantle boundary, Seismica</strong></p> <p>The four tar files with data (20161225.tar, 20190929.tar, 20150519.tar, 20170224.tar) need to be unpacked and moved into the ‘Data’ directory. Separate tar files were created to aid the upload process.</p> <p><br> Warning: These are not well-commented codes, but should run after dependencies are installed. Unfortunately, I do not currently have time to clean and comment them. Do feel free to get in touch at sc845@cam.ac.uk about anything.</p> <p>Figures from the paper:</p> <ul> <li>Figure 1- plot_map_paper.py</li> <li>Figures 2-5 - plot_everything_single_event.py</li> <li>Figure 6 - plot_beamresults.py</li> <li>Figure 7 - Cross-sections are obtained from http://www.earth.ox.ac.uk/~smachine/</li> <li>Figure 8 - Geochem_plot/plot_ulvzs.py Uses results from various publications as indicated in the paper.</li> </ul> <p><br> Dependencies (besides ‘standard’ python libraries)</p> <ul> <li>ObsPy - www.obspy.org - library for seismic data processing</li> <li>Basemap - https://matplotlib.org/basemap/ - now deprecated library for map plotting in matplotlib</li> </ul> <p>Observed data and synthetics are stored PICKLE format. Metadata are stored within. Using the data and accessing metadata is demonstrated in the various script. The process to download and process the data from the IRIS database, is included in the folder ‘Download_processing_codes’. Note that after this process quality control of the traces is applied by eye. This is why the final data set is included in the repository. </p> <p>Synthetics are made with the ‘sandwiched’ coupled-spectral element method (‘sandwiched’-CSEM). For access, please contact the authors of Capdeville, Y., To, A. and Romanowicz, B. (2003) ‘Coupling spectral elements and modes in a spherical Earth: an extension to the “sandwich” case’, Geophysical Journal International, 154(1), pp. 44–57. doi: 10.1046/j.1365-246X.2003.01959.x.</p> <p><br> Data is provided for the four events presented in the main paper. Synthetic data are stored in the subdirectory CSEM for each event. Input of the ULVZ model for each synthetic case are stored in the folder ‘Synthetic_ULVZ_input_files’. Model directories are named ULVZ160 to ULVZ180 and input files are anomalies.ULVZ160 to anomalies.ULVZ180.</p> <p>Vik colormap is from https://www.fabiocrameri.ch/colourmaps/</p> <p> </p> <p> </p> <p> </p> <p> </p>
Dataset related to the publication "Thermal properties of nanocrystalline silicon nanobeams", DOI: 10.1002/adfm.202105767
<p>This folder contains the raw data from which the graphs in paper "Thermal properties of nanocrystalline silicon nanobeams", DOI: 10.1002/adfm.202105767, have been obtained.</p>
Dataset (VII) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of compound <strong>1</strong> in MSM <strong>2-<em>S</em><sub>3</sub></strong> conformations of the related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset (VIII) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of compound <strong>1</strong> in MSM <strong>2-<em>S</em><sub>3</sub></strong> conformations of the related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset (V) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of <strong>SB203580</strong> related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset II related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP3P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7342311</p>
Dataset III related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP4P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7341954</p>
Tourists' perceptions of water quality in Finland, dataset, related to article "Browning of Boreal Lakes: Do Public Perceptions and Governance Meet the Biological Foundations?"
<p>Tourists' perceptions of water quality in Finland, dataset, related to article "Browning of Boreal Lakes: Do Public Perceptions and Governance Meet the Biological Foundations?" by Albrecht et al. (2022).<br> <br> <strong>Article abstract:</strong><br> "Surface water browning, also known as brownification, is an acute environmental issue concerning inland waters. We adopt an interdisciplinary perspective and combine limnology, ecology, environmental law, tourism, and economics to build a theoretical framework to understand the consequences and management needs concerning water browning, generate a research agenda, and pinpoint acute research needs. Using a systematic review approach, we identify gaps of knowledge and address the impacts of browning on lake ecosystem functioning. To support the biological information, we present primary survey data to define the recreational use and public perception of waters in Finland. We identified an urgent need for the development of indicators of brownification beyond EU’s Water Framework Directive (WFD) to be able to balance the costs of browning with terrestrial activities that increase browning. Despite a considerable body of research already exists, there is still a need for better understanding of the biogeochemical processes related to browning to progress towards ecosystem-based management of inland waters. Public perception of the quality of waterbodies in Finland was largely in agreement with the proportion of waterbodies classified to meet the good or excellent ecological status, but recreational fishers may value different aspects of water quality compared to the classification based on WFD. Consequently, to build an interdisciplinary understanding of how browning affects boreal lakes and their uses, we suggest improvements for environmental regulation concerning the impact assessment of terrestrial land use activities and ecosystem-based management of inland waters."</p>
Dataset related to the publication "Recent advances in Fabry-Perot-based refractometry utilizing gas modulation for assessment of pressureDataset related to the publication"
<p>The data set consists of; The published paper, all figures that present measurement or simulation data in .png and .fig format and the underlying data plotted in the figures in text format. The published plots were generated from the fig files. The text files were generated by reading the plotted data from the fig files. The files are named Fig_XX were XX corresponds to the figure number in the publication. The format of the text file is as follows. Before every data set there is a header consisting of; The number of the subplot where the data is plotted (Plot: XX), the number of the data set in the sub plot (DataSet: XX), and the color of the line or marker in the plot (Color: XX). The description of what each color represents can be found in the publication.</p>
ScienceDex guides
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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.