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1,028 results for “Protons”

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zenodo36/100

Effect of density gradients on the generation of a highly energetic and strongly collimated proton beam from a laser irradiated Gaussian-shaped Hydrogen microsphere

<p>Simulation input files and data sets of &quot;Effect of density gradients on the generation of a highly energetic and strongly collimated proton beam from a laser irradiated Gaussian-shaped Hydrogen microsphere&quot; by A. Bhagawati et al.</p> <p>Simulation code:&nbsp;</p> <p>Picpsi3D, Version 0.1 beta 11<br> (c) Copyright Kartik Patel, L &amp; PTD, BARC<br> &nbsp;</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

Dataset for the paper "High Loading of Single Atomic Iron Sites in Pyrolysed Fe-NC Oxygen Reduction Catalysts for Proton Exchange Membrane Fuel Cells", DOI:10.1038/s41929-022-00772-9

<p>The data in this spreadsheet was used to produce the figures in the paper&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p> <p>Authors:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Asad Mehmood, Mengjun Gong, Fr&eacute;d&eacute;ric Jaouen, Aaron Roy, Andrea Zitolo, Anastassiya Khan, Moulay-Tahar Sougrati, Mathias Primbs, Alex Martinez Bonastre, Dash Fongalland, Goran Drazic, Peter Strasser, Anthony Kucernak</p> <p>Title:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; High Loading of Single Atomic Iron Sites in Pyrolysed Fe-NC Oxygen Reduction Catalysts for Proton Exchange Membrane Fuel Cells</p> <p>Journal: Nature Materials</p> <p>DOI:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10.1038/s41929-022-00772-9</p> <p>Please cite the above reference if you wish to use this data&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p> <p>DOI of data:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10.5281/zenodo.6411262</p>

opencc-by-4.0Apr 2022View details →
zenodo36/100

Data release for the paper "Measurements of protons and charged pions emitted from the $\nu_{\mu}$ charged-current interactions on iron at a mean neutrino energy of 1.49 GeV using a nuclear emulsion detector"

<p>This data release is associated with the paper &quot;Measurements of protons and charged pions emitted from the <span class="math-tex">\(\nu_{\mu}\)</span>&nbsp;charged-current interactions on iron at a mean neutrino energy of 1.49 GeV using a nuclear emulsion detector&quot;. It is currently available on&nbsp;<a href="http://arxiv.org/abs/2203.08367">arXiv:2203.08367</a>&nbsp;and to be submitted to Phys. Rev. D.</p> <p><strong>When citing this data release, please cite as well the paper.</strong></p> <p>The provided zip file contains the data as below.</p> <ol> <li>event.root: Event by event information of 183 iron-target interactions.</li> <li>plot.root: Plot information as shown in the paper.</li> <li>detector_efficiency.root: Detectrion efficiencies for muons, charged pions, and protons.</li> <li>momentum_resolution.root: Relation between true and reconstructed momentum for muons, charged pions, and protons.</li> <li>misPID.root: Mis-PID rates of protons and pions.</li> <li>syscov.root: Covariance matrices of systematic uncertainties.</li> <li>flux.root: The neutrino flux and the covariance matrix of the flux error.</li> </ol> <p>The zip file&nbsp;also contains a README.pdf file with detailed information on the included files. Please read it.</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

Optimizing Nozzle Travel Time in Proton Therapy [Dataset]

<p>Dataset of instances taken into account by the paper, together with solutions and achieved computational time.</p> <p>Manuscript submitted to 2022 IEEE-CBMS.</p> <p><em>ABSTRACT - Proton therapy is an oncological therapy that is more expensive than classical radiotherapy but that is considered the gold standard in several situations. Moreover, since there is still a limited amount of delivering facilities for this techniques, it is fundamental to increase the number of treated patients over time.<br> The objective of this work is to offer an insight on the problem of the optimization of the part of the delivery time of a treatment plan that relates to the movements of the system. We denote it as the Nozzle Travel Time Problem (NTTP), in analogy with the Leaf Travel Time Problem (LTTP) in classical radiotherapy.<br> In particular this work: (i) describes a mathematical model for the delivery system and formalize the optimization problem for finding the optimal sequence of movements of the system (nozzle and bed) that satisfies the covering of the prescribed irradiation directions; (ii) provides an optimization pipeline that solves the problem for instances with an amount of irradiation directions much greater than those usually employed in the clinical practice; (iii) reports preliminary results about the effects of employing two different resolution strategies within the aforementioned pipeline, that rely on an exact Traveling Salesmna Problem (TSP) solver (Concorde) and an efficient heuristic Vehicle Routing Open-source Optimization Machine (VROOM).</em></p> <p>&nbsp;</p> <p>For each combination of system features (SF1, SF2, SF3) and distance metric (L1 and Linf), 50 runs (5 session by 10 runs) with prescribed fields from 5 to 100 (step 5) have been executed.</p> <p>- &#39;grph&#39; folder contains GTSP and ATSP instances in GraphML and txt format.</p> <p>- &#39;vrinst&#39; folder contains ATSP instances, expressed as VRP instances, in json format, to be fed into VROOM</p> <p>- &#39;tsps&#39; folder contains symmetric TSP instances in TSPLIB format to be fed into Concorde</p> <p>- &#39;ress&#39; folder contains result of optimizzation obtained by Concorde (.sol and .res formats) and VROOM (.json)</p> <p>all the files in these folders is named as [SF#]_[distanceMetric][[prescribedFields#]_[subrun]][Session8charsCode], so that, for example &quot;SF3_Linf[100_9]2e275d41&quot; represents the 100 fields result of the 9th subrun of the session with code 2e275d41, where SF3 and Linf norm have been taken into account.</p> <p>- &#39;resultsNPY&#39; folder contains .npy file about computation time and computed travel time for both solvers</p> <p>&nbsp;</p>

opencc-by-4.0May 2022View details →
zenodo36/100

Data release for "Measurements of muon-antineutrino and muon-neutrino+muon-antineutrino charged-current cross-sections without detected pions nor protons on water and hydrocarbon at mean antineutrino energy of 0.86 GeV"

<p>This data release is associated with the publication "Measurement of charged-current cross-sections on water and hydrocarbon without detected pions nor protons using the T2K anti-neutrino beam at an off-axis angle 1.5 degrees". It is available in <a href="https://doi.org/10.1093/ptep/ptab014">Progress of Theoretical and Experimental Physics</a> and <a href="https://arxiv.org/abs/2004.13989">arXiv:2004.13989 [hep-ex]</a>.<br><br>The data release contains:</p> <ul> <li>The "histograms.root" file contains several histograms related to the cross-sections. <ul> <li>flux_numubar_* -&gt; 1D histogram with the flux prediction at the WAGASCI module or the Proton Module of the T2K experiment.</li> <li>flux_numu_* -&gt; 1D histogram with the flux prediction at the WAGASCI module or the Proton Module of the T2K experiment.</li> <li>Err_numubar_* -&gt; 1D TGraphAsymmErrors with the measured flux-integrated numubar cross-sections and their uncertainties.</li> <li>Err_numu_numubar_* -&gt; 1D TGraphAsymmErrors with the measured flux-integrated numu+numubar cross-sections and their uncertainties.</li> <li>xsec_numubar_* -&gt; 1D histogram with the predicted flux-integrated numubar cross-sections by NEUT (5.3.3).</li> <li>xsec_numu_numubar_* -&gt; 1D histogram with the predicted flux-integrated numu+numubar cross-sections by NEUT (5.3.3).</li> </ul> </li> <li>The "Covariance_Matrix_Numubar.root" file contains the covariance matrix for the flux-integrated numubar cross-sections, considering all the uncertainties.</li> <li>The "Covariance_Matrix_Numu+Numubar.root" file contains the covariance matrix for the flux-integrated numu+numubar cross-sections, considering all the uncertainties.</li> <li>The "flux" file contains the (anti-)muon neutrino flux prediction at the WAGASCI module or the Proton Module of the T2K experiment</li> </ul>

opencc-by-4.0Sep 2022View details →
zenodo36/100

The coupling of the hydrated proton to its first solvation shell

<p>This repository contains tabulated raw data for figures 1, 2, and 4 for the manuscript entitled &quot;The coupling of the hydrated proton to its first solvation shell&quot;.&nbsp; Also, all necessary inputs and instructions to reproduce the data are provided.</p>

opencc-by-4.0Sep 2022View details →
zenodo36/100

Supporting Information for the Journal Article "The electrostatic potential as a descriptor for the protonation propensity in automated exploration of reaction mechanisms"

<p>This dataset contains the supporting information published together with the article &quot;The electrostatic potential as a descriptor for the protonation propensity in automated exploration of reaction mechanisms&quot; (<a href="https://doi.org/10.1039/C9FD00061E"><em>Faraday Discuss.</em>, <strong>2019</strong>, <em>220</em>, 443</a>).</p>

opencc-by-4.0Jun 2019View details →
zenodo36/100

Peripheral blood TCRseq data in AIRR-C format for cancer patients who received either photon or proton based radiation therapy

<p>These are the AIRR-C format converted data from the original Adaptive ImmunoSEQ v2 data format.</p> <p>See the analysis repo for more information: <a href="https://github.com/JamieHeather/radiation-induced-lymphopenia-paper-analysis" target="_blank" rel="noopener">https://github.com/JamieHeather/radiation-induced-lymphopenia-paper-analysis</a>.</p>

opencc-by-4.0Jun 2024View details →
zenodo36/100

Response of protons to Mercury's magnetotail reconfigurations

Open the record for dataset details and reuse information.

opencc-by-4.0May 2024View details →
zenodo36/100

Protonation state of proteins in crystals (CpHMD simulations)

<p>Input files to run simulations for:</p> <p>"What is the protonation state of proteins in crystals:&nbsp;insights from constant pH molecular dynamics simulations"</p> <p>by Noora Aho*<strong>&dagger;</strong><em>, </em>Gerrit Groenhof*<em>, </em>and Pavel Buslaev* (manuscript submitted in August 2024)</p> <p>*Nanoscience Center and Department of Chemistry, University of Jyv&auml;skyl&auml;, Finland</p> <p><strong>&dagger;</strong>Theoretical Physics and Center for Biophysics, Saarland University, Germany</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2024View details →
zenodo36/100

Aligning of water molecules into proton-conducing transmembrane water wires by oxygen atoms of phospholipid ester linkers

<p>A media AVI file that shows how oxygen atoms of ester linkers of the two converging phospholipid molecules form an &quot;oxygen passage&quot; along which water molecules align in a proton-conducting wire. Further details could be found in our article</p>

opencc-by-4.0Mar 2019View details →
zenodo36/100

Effects of Energetic Electron and Proton Precipitations on Thermospheric Nitric Oxide Cooling during shock-led Interplanetary Coronal Mass Ejections

<p>Satellite measurements have revealed significant enhancement of 5.3-&micro;m nitric oxide (NO) emission during shock-led interplanetary coronal mass ejections (ICMEs). Great discrepancies in modeled neutral density occur during these events, and may be attributed to the abnormally high NO cooling. Meanwhile, the relative significance of protons, soft electrons, and keV-electrons to NO emission is yet to be well determined. The goal of this study is to identify the contribution of electron and proton precipitations to the thermospheric NO cooling by using the Defense Meteorological Satellite Program (DMSP) data. The observed energetic electrons and protons (0.1&ndash;30.2 keV) during 36 shock-led ICME events in 2002&ndash;2010 are binned into geomagnetic grids to provide statistical distributions of the particle precipitation for polar regions. The distributions are incorporated into the Global Ionosphere-Thermosphere Model. The results show that electrons play a dominant role to NO cooling, but protons are also important and contribute to up to a quarter of NO cooling by electrons and ions combined. NO cooling enhancement during the events is proportional to the level of energy flux and is dominated by the electrons in the energy band of 1.4&ndash;3.1 keV. Both total electron content (TEC) and NO cooling enhance at the source regions, but they have different lifetime and correlation with the particle precipitations. Generally, NO cooling and TEC enhancements have a positive correlation with the precipitating energy. Cross correlation shows that particle precipitations have more direct and instantaneous impact on TEC while it takes longer for the atmosphere to heat up for cooling to proceed.</p>

opencc-by-4.0Sep 2019View details →
zenodo36/100

Collected Colorimetric Microscopy (C-Microscopy) Images of Melanocytes and Melanoma 3D Spheroids Irradiated with Different Type of Proton Beam as Used in Proton Radiotherapy

<p>Collected Colorimetric Microscopy (C-Microscopy) images, color calibrated (D65 illuminant), of melanocytes and melanoma 3D spheroids, irradiated with different type of proton beam as used in proton radiotherapy.<br>&nbsp;<br>The data are supplement to:</p> <p>Martyna Durak-Kozica, Ewa Stępień, Jan Swakoń, Benedykt R. Jany, Kamil Kawoń, Damian Wr&oacute;bel, Sebastian Kusyk, Małgorzata Grzesiak, Katarzyna Knapczyk-Stwora, Andrzej Wr&oacute;bel, Joanna Chwiejand&nbsp; Paweł Moskal, Short-term response of melanoma spheroids and melanocytes to FLASH proton therapy - colorimetric and FTIR microscopy study, Pol J Med Phys Eng 2024;30(4):263-268 (2024) <a href="https://doi.org/10.2478/pjmpe-2024-0031">https://doi.org/10.2478/pjmpe-2024-0031</a></p> <p>&nbsp;</p> <p><br>HEMA-Spheroids-C-Microscopy.zip - melanocytes 3D spheroids, (C-Microscopy) images, color calibrated (D65 illuminant), image width 435.87 microns</p> <p><br>WM-Spheroids-C-Microscopy.zip - melanoma 3D spheroids, (C-Microscopy) images, color calibrated (D65 illuminant), image width 1089.68 microns</p> <p><br>WM-Spheroids-Texture-C-Microscopy.zip - surface texture of melanoma 3D spheroids, (C-Microscopy) images, color calibrated (D65 illuminant), image width 108.97 microns</p> <p>&nbsp;</p> <p>Proton Beam Radiotherapy Irradiation Conditions:</p> <p>C - Control</p> <p>CC - Control minus 7days</p> <p>LP - conventional proton radiotherapy (CONV) final dose 3Gy (dose rate about 0.140 Gy/s)</p> <p>F - FLASH proton radiotherapy final dose 3Gy (dose rate &gt;60 Gy/s)</p> <p>F20 - FLASH proton radiotherapy final dose 20Gy (dose rate &gt;60 Gy/s)</p> <p>F40 - FLASH proton radiotherapy final dose 40Gy (dose rate &gt;60 Gy/s)</p> <p>&nbsp;</p> <p><br>The details about Colorimetric Microscopy (C-Microscopy) approach could be found in:</p> <p>Benedykt R. Jany, Quantifying Colors at Micrometer Scale by Colorimetric Microscopy (C-Microscopy) Approach, Micron 176, 103557 (2024) <a href="https://doi.org/10.1016/j.micron.2023.103557">https://doi.org/10.1016/j.micron.2023.103557</a></p>

opencc-by-4.0Sep 2024View details →
zenodo36/100

Enhanced_Precipitation_of_energetic_protons_due_to_Uranus_asymmetric_magnetic_field

<p>The dataset pertaining to Figures 1-4 in the academic paper titled: "Enhanced Precipitation of energetic protons due to Uranus asymmetric magnetic field" by Matthew Acevski and Adam Masters</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

3 MeV Proton Ion beam analysis of NCA/Si anode-cathode mapping

<p><span>The dataset presents 2140 ion-beam-analysis (IBA) measurements of a NCA cathode and a Si/G anode using 2970+-20 keV protons. Figure 1 shows an example of the result. The anode and cathode foils were cycled in a full liquid electrolyte cell for 340 cycles and analysed in the state-of-charge =0. The cell consisted of 20 cathode and 20 anode layer from which 2 cathode and 2 anode layers from the top (KT, AT) and middle (AM, KM) were extracted for IBA. For practical reasons each of the 110x80 mm&sup2; foils was cut into 9 equal parts. Four detectors acquire the data simultaneously for RBS, NRA, PIGE, and PIXE. The description of the end-station and detectors can be found here: </span><span><a href="https://doi.org/10.3390/instruments5010010"><span>https://doi.org/10.3390/instruments5010010</span></a></span><span>. </span></p> <p><span>Each point on the sample consists of 4 files, four detector spectra. The filename consists of the sample name, three positions in units of nm (X, Y, Z), a rotation in units of &micro;&deg; followed by an underscore ( _ ) and the type of data contained in the file (RBS, NRA, PIXE, PIGE, or Meta). Only X and Z positions are relevant in this case as indicated in the attached figure.</span></p> <p><span>The RBS, NRA, and PIGE detector files contain a header specifying the dead- and live-time followed by two columns. The first column represents the digital channel of the detector. The second column represents the counts acquired in this channel. This format is readable as ASCI by SimNRA7. SimNRA 7 reference evaluations are included in the dataset. The PIXE file contains the number of channels in the first row/header and only the counts in the subsequent rows. The channel is given by the row number. This format is readable by GUPIXWIN3. Example GUPIXWIN files are included</span></p> <p><span>The channels of the detector files can be re-calculated using a calibration shown in the following table 1. Certain drifts in the calibrations are possible, but should be limited to below 2% of the given value. All points are integrated to the same ion dose of 2 &micro;C. This corresponds to a Particle*Sr of about 5.0E+10 (RBS detector), 5.4E+11 (NRA).</span></p> <p><span>Table </span><span><span>1</span></span><span>: Detector calbration enabling a recalculation of channels to energy. Units are in keV</span></p> <table> <tbody> <tr> <td> <p><span>Detector</span></p> </td> <td> <p><span>Linear (multiply with channel)</span></p> </td> <td> <p><span>Offset (add to first result)</span></p> </td> </tr> <tr> <td> <p><span>RBS</span></p> </td> <td> <p><span>2.8</span></p> </td> <td> <p><span>10</span></p> </td> </tr> <tr> <td> <p><span>NRA</span></p> </td> <td> <p><span>5.5</span></p> </td> <td> <p><span>10</span></p> </td> </tr> <tr> <td> <p><span>PIXE</span></p> </td> <td> <p><span>0.184</span></p> </td> <td> <p><span>1.5</span></p> </td> </tr> <tr> <td> <p><span>PIGE</span></p> </td> <td> <p><span>0.85</span></p> </td> <td> <p><span>0</span></p> </td> </tr> </tbody> </table> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Pure Isotropic Proton Solid State NMR raw data

<p>This dataset contains all raw NMR data (in Topspin and JCAMP format) together with the MATLAB scripts used in the JACS publication named: &quot;Pure Isotropic Proton Solid State NMR&quot; (DOI: 10.1021/jacs.1c03315 )</p>

opencc-by-4.0Jun 2021View details →
zenodo36/100

Structures for "Protonation States of Molecular Groups in the Chromophore-Binding Site Modulate Properties of the Reversibly Switchable Fluorescent Protein rsEGFP2"

<p>Files with atomic coordinates of the structures obtained in geometry optimization of molecular systems within the protein and cluster models. Supplementary materials for the paper&nbsp;&quot;Protonation States of Molecular Groups in the Chromophore-Binding Site Modulate Properties of the Reversibly Switchable Fluorescent Protein rsEGFP2&quot;</p>

opencc-by-4.0Jul 2021View details →
zenodo36/100

Spectroscopic data and DFT coordinates for "The three-spin intermediate at the O–O cleavage and proton pumping junction in heme–Cu oxidases"

<p>This dataset includes spectroscopic data and atomic coordinates of DFT structures in&nbsp;the manuscript titled &quot;The three-spin intermediate at the O&ndash;O cleavage and proton pumping junction in heme&ndash;Cu oxidases&quot;. Spectroscopic data included are&nbsp;from magnetic circular dichroism (MCD), variable-temperature variable-field MCD, absorption and resonance Raman spectroscopies.</p>

opencc-by-4.0Aug 2021View details →
zenodo36/100

Supplementary data for: Does Phobos reflect solar wind protons? Mars Express special flyby operations with and without the presence of Phobos

<p>Supplementary data to reproduce figures for &quot;Does Phobos reflect solar wind protons? Mars Express special flyby operations with and without the presence of Phobos&quot;.</p>

opencc-by-4.0Sep 2021View details →
zenodo36/100

Supporting data for "Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics"

<p>Supporting data for &quot;<a href="https://www.nature.com/articles/s41467-023-36666-y">Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics</a>&quot; by M. Bocus, R. Goeminne, A. Lamaire, M. Cools-Ceuppens, T. Verstraelen and V. Van Speybroeck,&nbsp;<em>Nature Communications</em>,&nbsp;<strong>2023</strong>, 14, 1008.</p> <p>This dataset contains examples of input files, submission and analysis scripts to train and use&nbsp;a machine learning potential based on the Schnet architecture for the proton hopping reaction in the H-CHA zeolite. The complete DFT training set, obtained by unbiasing the forces printed by CP2K (with PLUMED coupling), is stored as extended xyz files&nbsp;in the folders DFT/A-B/training_data.xyz where A=1-3 and A&lt;B&lt;5. More details on the folder architecture can be found in the README.md file.</p>

opencc-by-4.0Oct 2022View details →

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Last verified 2026-04-30Open record

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dandi-nwb
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International Brain Laboratory public data

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ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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Last verified 2026-04-29Open record