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1,937 results for “Resonator”
Supplementary data for "Resonant or asymmetric: The status of sub-GeV dark matter"
<p>The files in this record contain supplementary data for the study, "Resonant or asymmetric:<br>The status of sub-GeV dark matter". Samples have been created using <a href="https://gambitbsm.org/" target="_blank" rel="noopener">GAMBIT</a> and figures can be reproduced with <a href="https://github.com/tegonzalo/pippi" target="_blank" rel="noopener">pippi</a>.</p>
MetaboScope: A statistical toolbox for analyzing 1H nuclear magnetic resonance spectra from human clinical studies.
<p>MetaboScope is purposefully built as a pipeline where each module accepts the output generated by the previous one. This provides flexibility and simplicity of use, while being straightforward to maintain. The system and its libraries were developed in JavaScript and run as a web app; therefore, all the operations are performed on the local computer, circumventing the need to upload data. The code is open source (DOI: https://www.cheminfo.org/flavor/metabolomics/index.html) and can be readily installed locally. We provide module notes and video tutorials, in addition to clinical spectral datasets for modelling purposes.</p> <p>View data:</p> <p><a title="nmrium.org" href="https://www.nmrium.org/nmrium#?toc=https://zenodo.org/api/records/12916741/files/toc.json/content" target="_blank" rel="noopener">https://www.nmrium.org/nmrium#?toc=https://zenodo.org/api/records/12916741/files/toc.json/content</a></p>
Role of energy migration in the efficiency of upconversion-based resonance energy transfer to organic acceptors
<p>Graphs, data set and algorithms (in Matlab) for the article:</p> <div>Kotulska, A. M., Prorok, K., Bezkrovnyi, O., Pilch-Wrobel, A., & Bednarkiewicz, A. (2024). Role of energy migration in the efficiency of upconversion-based resonance energy transfer to organic acceptors. <em>Journal of Luminescence</em>, <em>275</em>, 120823. https://doi.org/10.1016/J.JLUMIN.2024.120823</div> <p>(https://www.sciencedirect.com/science/article/pii/S0022231324003879)<br>Abstract: Lanthanide (Ln)-doped upconverting nanocrystals (LnNPs) exhibit suitable features as energy donors for Förster resonance energy transfer (FRET). The sensitivity of biosensors can be improved by optically active materials with anti-Stokes emission, narrowband absorption and emission spectral lines, and long luminescence lifetimes. In contrast to energy reabsorption, energy transfer between the upconversion nanocrystals (UCNPs) and organic dyes attached to their surface can be observed through donor emission quenching and acceptor emission and decreases in the luminescence lifetimes of donors. Although the emission spectra confirmed that FRET occurred from the Er3+ ions to the Rose Bengal acceptor, the luminescence lifetimes were generally not affected by the presence of the acceptor. The Ln3+ dopant in LnNPs, which typically has 20–100 % Yb3+ sensitizer ions and 0.2–2% activator (Er3+/Tm3+/Ho3+) ions, results in hundreds to thousands of Ln3+ ions in a single UCNP. The interaction between multiple Ln3+ ions results in significant energy migration and storage in the Yb3+ sensitizer network, which is often recharged with the energy of the Er3+ ions when they emit and nonradiatively transfer their energy to acceptor species. However, the energy transfer mechanisms could not be unambiguously determined through spectroscopic data due to the nature the upconversion process. Studies confirmed that the energy migration distance was significantly shortened when the LnNP surface contained acceptors; this affected the energy storage and ‘recharging’ capability of the Yb3+ sensitizer network within the UCNPs. These results provide hints on the future use of LnNP as effective FRET probes, in which the highest possible absorption cross section and possibly lowest dopant concentration should be maintained.<br>Keywords: Nanocrystals; Resonance energy transfer; FRET; Monte Carlo; Lanthanide ions</p>
Light-Induced Metallic and Paramagnetic Defects in Halide Perovskites from Magnetic Resonance
<p>EPR and NMR data for the research article titled "Light-Induced Metallic and Paramagnetic Defects in Halide Perovskites from Magnetic Resonance". For further details see the readme.txt file. DOI: https://doi.org/10.1021/acsenergylett.4c02557</p>
Integration of High-Tc Superconductors with High-Q-Factor Oxide Mechanical Resonators (Dataset)
<p>Micro-mechanical resonators are building blocks of a variety of applications in basic science and consumer electronics. This device technology is mainly based on well-established and reproducible silicon-based fabrication processes with outstanding performances in term of mechanical <em>Q</em>-factor and sensitivity to external perturbations. Broadening the functionalities of micro-electro-mechanical systems (MEMS) by the integration of functional materials is a key step for both applied and fundamental science. However, combining functional materials with silicon-based devices is challenging. An alternative approach is directly fabricating MEMS based on compounds inherently showing non-trivial functional properties, such as transition metal oxides. Here, a full-oxide approach is reported, where a high-Tc superconductor YBa<sub>2</sub>Cu<sub>3</sub>O<sub>7</sub> (YBCO) is integrated with high <em>Q</em>-factor micro-bridge resonators made of single-crystal LaAlO<sub>3</sub> (LAO) thin films. LAO resonators are tensile strained, with a stress of about 350 MPa, show a <em>Q</em>-factor above 200k, and have low roughness. YBCO overlayers are grown ex situ by pulsed laser deposition and YBCO/LAO bridges show zero resistance below 78 K and mechanical properties similar to those of bare LAO resonators. These results open new possibilities toward the development of advanced transducers, such as bolometers or magnetic field detectors, as well as experiments in solid state physics, material science, and quantum opto-mechanics.</p>
On energy transfer of parametric resonance for wave energy conversion
<p>Parametric resonance has been observed, both numerically and experimentally, in various studies of wave energy converters (WECs). A large motion in heave induces a periodic variation in the metacentric height of a WEC body, and, consequently, causes a harmonic variation in pitch/roll restoring coefficients, which can parametrically excite the pitch/roll modes. Current studies have a specific focus to determine the occurrence conditions of parametric resonance, by detecting the boundaries between stable and unstable regions in the parameter space. In the literature, some studies aim to make use of parametric resonance for improving power capture. In contrast, some studies try to suppress the effect of parametric resonance, as it reduces power capture efficiency. However, how energy transfers from one mode to another is not fully understood. This study aims to analyse the energy transfer between heave and pitch/roll modes when parametric resonance occurs. A generic cylindrical point absorber is studied as a WEC floater to considering non-linear wave-structure interaction, including non-linear Froude-Krylov and viscous forces. A heave-pitch-roll three-degree-of-freedom model is derived for numerical study of the energy transfer between different operation modes.</p>
Nuclear Magnetic resonance Dataset of 2D spectra of S100B and Tau to study their protein-protein interaction
<p>Nuclear Magnetic resonance dataset of 2D spectra corresponding to raw data of research published in Nature Communication in a communication entitled "Dynamic interactions and Ca2+ 1 -binding modulate the holdase-type chaperone activity of S100B preventing tau aggregation and seeding" by Moreira G. et al.</p> <p>Dataset corresponds to</p> <p>raw data files in Bruker format of NMR 2D spectra (ser), associated with files of acquisition parameters and processing parameters (pdata),</p> <p>files in .ucsf format that can be read with NMRFAM-Sparky (free download) of 2D spectra (in sub-directory pdata/1)</p> <p>files of chemical shift value lists that can be read as text files or in NMRFAM sparky together with the corresponding ucsf files.</p> <p>physico-chemical conditions are found in title in pdata\1</p> <p>Data were acquired on a Bruker 900-MHz spectrometer equipped with a triple-resonance cryogenic probe (Bruker, Karlsruhe, Germany)</p>
Magnetic Resonance Imaging Copper Sulfate Dataset
<p>The data has been produced by the Institut für Mikrostrukturtechnik (IMT) at Karlsruher Institut für Technologie (KIT). This dataset represents the DICOM (Digital Imaging and Communications in Medicine) files, which belong to one MRI (Magnetic Resonance Imaging) study and contain a series of images that have been measured with different protocols. The samples shown by the images are tubes, which contain different concentrations of CuSO4. The DICOM file headers have metadata tags, which embody additional information about the study and the particular series.</p>
BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution
<p><strong>BigBrain-MR</strong> is a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI contrasts and properties that affect image generation. This phantom was generated from the publicly available <a href="https://bigbrainproject.org/">BigBrain histological dataset</a> and from lower-resolution in-vivo 7T-MRI data, using a new image processing framework that allows mapping the general properties of in-vivo data into the fine anatomical scale of BigBrain.</p> <p>The <strong>dataset</strong> includes:</p> <ul> <li>BigBrain original contrast and a new atlas with 20 ROIs;</li> <li>T<sub>1</sub>-weighted image and T<sub>1</sub> map;</li> <li>T<sub>2</sub>*-weighted images and R<sub>2</sub>* map;</li> <li>Magnetic susceptibility map (QSM);</li> <li>Background magnetic field map;</li> <li>Complex coil sensitivity maps (32ch-receive RF array);</li> <li>Bias field map.</li> </ul> <p>Information about each image/map (including data type and amplitude scaling) is provided in <em>data_info.txt</em>.</p> <p>Additionally, we have included a script with <strong>usage examples</strong> in Python that illustrate how the data can be loaded, processed and combined for diverse simulation purposes.</p> <p>BigBrain-MR is presented, described and tested in the following <strong>peer-reviewed article</strong>:</p> <p>C. Sainz Martinez, M. Bach Cuadra, J. Jorge. <em>BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development</em>. NeuroImage 2023. <strong>DOI:</strong> <a href="https://doi.org/10.1016/j.neuroimage.2023.120074">10.1016/j.neuroimage.2023.120074</a></p> <p> </p>
Source code and simulation results for computing resonance expansions of quadratic quantities with regularized quasinormal modes
<p>This data publication supplements the article "Resonance expansion of quadratic quantities with regularized quasinormal modes" [1]. Tabulated data related to the figures in the manuscript is provided along with the Matlab scripts used to generate the results. The Riesz projection software package RPExpand [2] has been extended to support quasi normal modes (QNMs) and, in particular, the proposed method for quadratic quantities. A current version is contained in the directory <code>Code</code>. Furthermore, the input files required for scattering and resonance simulations with the finite element method (FEM) solver JCMsuite [3] are contained.</p> <p><strong>Requirements</strong></p> <ul> <li>JCMsuite (version 5.2.1 or newer)</li> <li>MATLAB (tested with version R2019b)</li> </ul> <p>In order to run the scripts you must replace the corresponding place holders in the files by a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of <a href="https://jcmwave.com/">JCMwave</a>. </p> <p><strong>References</strong></p> <p>[1] Fridtjof Betz, Felix Binkowski, Martin Hammerschmidt, Lin Zschiedrich, Sven Burger: Resonance expansion of quadratic quantities with regularized quasinormal modes, Physica Status Solidi A <strong>220</strong>, 2370013 (2023)</p> <p>[2] Fridtjof Betz, Felix Binkowski, Sven Burger, RPExpand: Software for Riesz projection expansion of resonance phenomena, SoftwareX <strong>15</strong>, 100763 (2021), https://doi.org/10.1016/j.softx.2021.100763</p> <p>[3] Jan Pomplun, Sven Burger, Lin Zschiedrich, Frank Schmidt, Adaptive finite element method for simulation of optical nano structures, Physica Status Solidi B <strong>244</strong>, 3419 (2007), http://dx.doi.org/10.1002/pssb.200743192</p>
Data for Schröder et al., J. Magn. Reson. 335:107140, 2022
<p>This directory contains the example data for the following publication:</p> <ul> <li>Mirjam Schröder, Till Biskup: cwepr – a Python package for analysing cw-EPR data focussing on reproducibility and simple usage. Journal of Magnetic Resonance 335:107140, 2022. doi:10.1016/j.jmr.2021.107140</li> </ul>
Magnetic Resonance Imaging Glucose Study Dataset
<p>The data has been produced by the Institut für Mikrostrukturtechnik (IMT) at Karlsruher Institut für Technologie (KIT). This dataset represents the DICOM (Digital Imaging and Communications in Medicine) files, which belong to one MRI (Magnetic Resonance Imaging) study and contain a series of images that have been measured with different protocols. The samples shown by the images are tubes, which contain different concentrations of Glucose. The DICOM file headers have metadata tags, which embody additional information about the study and the particular series.</p>
Reconstructing dust provenance from quartz optically stimulated luminescence (OSL) and electron spin resonance (ESR) signals: Preliminary results on loess from around the world
<p>Dataset for publication</p> <p><strong>Reconstructing dust provenance from quartz optically stimulated luminescence (OSL) and electron spin resonance (ESR) signals: </strong></p> <p><strong>Preliminary results on loess from around the world</strong></p> <p> </p> <p>Quantitative provenance analysis studies are instrumental in understanding the tectonic and climatic processes that shape the earth’s landscape. Although the most abundant mineral in the sedimentary system is quartz, almost all studies in provenance analysis investigate accessory minerals. Quartz crystals contain a vast number of point defects, intrinsic or due to impurities. For a signal to be an accurate indicator of provenance one needs to show that it is either dose independent or reaches a quantifiable steady state characteristic of the source rock. For signals used by trapped charge dating methods (optically stimulated luminescence (OSL) and electron spin resonance (ESR)), the latter option is the feasible one. By using quartz samples collected from the Chinese Loess Plateau (Luochuan loess-paleosol section), we show that the laboratory and natural dose response curves of E`<sub>1</sub> and and peroxy electron spin resonance signals of quartz (as defined later) overlap and reach a steady state for doses over about 1000 Gy. For E’<sub>1</sub> signals we attribute this steady state to reaching an equilibrium state between diamagnetic oxygen vacancies (the oxygen deficiency centre (ODC), Si=Si<em>)</em> and paramagnetic oxygen vacancies (E’<sub>1</sub>). For sedimentary quartz irradiated naturally or artificially in this dose range we show a strong linear relationship with zero intercept between E’<sub>1</sub> and peroxy signals for samples worldwide, supporting the hypothesis that these defects are Frenkel pairs. Further, we show significant correlations between the optically stimulated (OSL) sensitivity and the above two mentioned ESR signals. The very strong correlations (Pearson`s r ˃0.9) between E’<sub>1</sub>, peroxy and OSL sensitivity remain valid after the samples have been heated for 15 min to 350 ˚C for E’<sub>1</sub> to reach its maximum value, believed to be a result of the conversion of diamagnetic oxygen vacancies to E’<sub>1</sub>, clearly suggesting a relationship between OSL sensitivity and oxygen vacancies in general. Samples collected from different loess sites around the world can be distinguished based on both these OSL and ESR properties. An empirical increase in OSL sensitivity as well as oxygen related defect concentrations is observed in areas where the source material has components with older detrital zircon U-Pb ages, inferring a positive correlation between OSL sensitivity, as well as the signal intensity for E<sub>1</sub>` and peroxy defects and the age of the source rocks.</p>
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.
<p>This multi-center dataset consists of 250 expert-annotated magnetic resonance imaging stroke cases. It is the training dataset for the Ischemic Stroke Lesion Segmentation Challenge (ISLES'22).</p> <p>For each case, an expert level annotation of the stroke lesions is included along with the following three imaging sequences: Fluid attenuated inversion recovery (FLAIR), diffusion weighted imaging (DWI, b=1000) and its corresponding apparent diffusion coefficient (ADC) map. All imaging data and annotations are released in the Neuroimaging Informatics Technology Initiative (NIfTI) format (https://nifti.nimh.nih.gov/nifti-1), according to the BIDS convention. All imaging data are released in the native space without prior registration. Prior to release, skull-stripping was performed to de-identify patients.</p> <p>Image acquisition was performed on one of the following devices: 3T Philips MRI scanners (Achieva, Ingenia), 3T Siemens MRI scanner (Verio) or 1.5T Siemens MAGNETOM MRI scanners (Avanto, Aera). All images were obtained by healthcare professionals as part of the clinical imaging routine for stroke patients at three different stroke centers and imaging data was collected retrospectively for different clinical studies. Computer-readable scanner metadata from the Digital Imaging and Communications in Medicine (DICOM) header in the JSON file format is provided with the datasets if available.</p> <p>For a full dataset description, see the <a href="https://arxiv.org/abs/2206.06694">ISLES'22 preprint</a>.</p> <p>More information about the ISLES'22 challenge can be found in <a href="https://isles22.grand-challenge.org/">grand challenge</a> and in our official <a href="http://www.isles-challenge.org/">challenge website</a>.</p> <h3>Please cite the following works when using this dataset:</h3> <ul> <li>de la Rosa, Ezequiel, et al. <strong>DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES'22 challenge.</strong> <em>Nature Communications</em> 16.1 (2025): 7357.</li> <li>Hernandez Petzsche, Moritz R., et al. <strong>ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.</strong> <em>Scientific data</em> 9.1 (2022): 762.</li> </ul>
Field Line Resonances estimated using Machine Learning methods
<p>This data set contains the machine learning input matrix (composed by 1D Fourier cross-spectra) + additional information, for the Classification algorithm implemented in Foldes et al. (Automatic Detection of Field Line Resonance Frequencies in the Earth’s Plasmasphere, 2023) for the pair of station Tartu-Birzai (TAR-BRZ).</p> <p>Each file contains the following header at line 1. Columns are:</p> <p>- P(f0)-P(f211): Cross-phase value per frequency bin</p> <p>- YEAR</p> <p>- DOY (Day Of Year)</p> <p>- HOUR</p> <p>- ToD_flag: "Umbra", "Penumbra", 'Light'</p> <p>- L: McIllwain parameter</p> <p>- stat_tag: "tarbrz"</p> <p>- Kp</p> <p>- Kp_w_05d: Kp index weighted on a 12hrs time window</p> <p>- Kp_w_10d: Kp index weighted on a 24hrs time window</p> <p>- Kp_w_15d: Kp index weighted on a 36hrs time window</p> <p>- Kp_w_20d: Kp index weighted on a 2-day time window</p> <p>- Kp_w_25d: Kp index weighted on a 2.5-day time window</p> <p>- Kp_w_30d: Kp index weighted on a 3-day time window</p> <p>- Kp_m_05d: Kp index max on a 12hrs time window</p> <p>- Kp_m_10d: Kp index max on a 24hrs time window</p> <p>- Kp_m_15d: Kp index max on a 36hrs time window</p> <p>- Kp_m_20d: Kp index max on a 2-day time window</p> <p>- Kp_m_25d: Kp index max on a 2.5-day time window</p> <p>- Kp_m_30d: Kp index max on a 3-day time window</p> <p>- DST</p> <p>- DST_m_05d: DST index min on a 12hrs time window</p> <p>- DST_m_10d: DST index min on a 24hrs time window</p> <p>- DST_m_15d: DST index min on a 36hrs time window</p> <p>- DST_m_20d: DST index min on a 2-day time window</p> <p>- DST_m_25d: DST index min on a 2.5-day time window</p> <p>- DST_m_30d: DST index min on a 3-day time window</p> <p>- F107: F10.7 solar activity proxy</p> <p>- EField: Earth Electric co-rotation field</p> <p>- f(mHz): FLR frequency in mHz</p> <p>- df(mHz): Uncertainty on the validated frequency</p> <p>- class: 0 for "NoFreq", 1 for "Freq" and 2 for "PBL"</p>
The photooxidation of dissolved organic matter in surface waters analyzed by Fourier-transform ion cyclotron resonance mass spectrometry.
Dissolved organic matter (DOM) plays an important role in carbon cycling in natural waters. The processing of DOM in these waters can occur via photooxidation, or interaction with sunlight. This processing can lead to the production of CO2, and also the alteration of organic compounds that make up DOM. It is likely that the extent of photooxidation is at least partially determined by the chemical composition of DOM. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used to characterize the dissolved organic matter at the molecular level for all water samples, both before and after light exposure to better understand the photooxidation of DOM. Chemical formulas were assigned to mass to generated mass to charge ratios using a custom script in R, resulting in a list of chemical formula assignments for each DOM sample, at multiple light exposure time points.
Dataset related to the publication "Electromagnetic Amplification of Microwave Phonons in Nonlinear Resonant Microcavities", DOI: 10.1109/TMTT.2018.2855176
<p>This folder contains the raw data from which the graphs in paper "Electromagnetic Amplification of Microwave Phonons in Nonlinear Resonant Microcavities", DOI: 10.1109/TMTT.2018.2855176, have been obtained.</p>
Dataset related to the publication "Transformation Optics: Large Multiphysics Simulation of Nonlinear Optomechanical Coupling in Microstructured Resonant Cavities", DOI: 10.1109/MMM.2018.2821086
<p>This folder contains the raw data from which the graphs in paper "Transformation Optics: Large Multiphysics Simulation of Nonlinear Optomechanical Coupling in Microstructured Resonant Cavities", DOI: 10.1109/MMM.2018.2821086, have been obtained.</p>
Numerical code and data for: Suppressed Charge Dispersion via Resonant Tunneling in a Single-Channel Transmon
<p>The numerical code and data accompanying the analysis of Figs. 4 and 5 of Suppressed Charge Dispersion via Resonant Tunneling in a Single-Channel Transmon, Phys. Rev. Lett. (2020)</p>
Application of contact-resonance AFM methods to polymer samples (Raw Data)
<p>Raw data and figures of the article "Application of contact-resonance AFM methods to polymer samples", published in Beilstein Journal of Nanotechnology on 12 Nov 2020</p> <p> </p> <p>The raw data can be opened with the software "Igor Pro"</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.