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1,937 results for “Resonator”
Fano Interference in Microwave Resonator Measurements
<p>Data, Python notebooks and figures associated with the paper "Fano Interference in Microwave Resonator Measurements" by D. Rieger & S. Günzler et al. at Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.</p> <p>The data is saved in NumPy binary compressed .npz format. The notebooks and data reproduce the figures of the manuscript. Moreover, we provide an example implementation and measurement analysis notebook for the circle fit discussed in the manuscript.</p> <p>For any additional information please contact: dennis.rieger@kit.edu, simon.guenzler@kit.edu or ioan.pop@kit.edu</p>
Magnetic resonance spectroscopy data acquired in tinnitus subjects and healthy volunteers using PRESS sequence
<p>This dataset contains raw free induction decay (FID) signals collected during 1H magnetic resonance spectroscopy (MRS) study in 52 individuals with tinnitus (24 with unilateral and 28 with bilateral tinnitus) and 25 healthy volunteers (described in detail in a separate article doi:10.1038/s41598-023-45024-3).</p><p>Data acquisition was performed using 3T Siemens Prisma Fit scanner with a 20-channel receiver head-coil. A single voxel spectroscopy (SVS) PRESS (Point-Resolved Spectroscopy Sequence) sequence was applied for collection of MRS data, using standard Siemens water suppression (water saturation, 50 Hz bandwidth) and no lipid suppression. MRS data was collected from four cubic 3.75 cm3 (1.5 cm x 1.5 cm x 1.5 cm) regions-of-interest in the brain, placed in the left temporal lobe, right temporal lobe, left frontal lobe, and right frontal lobe. The MRS sequence parameters were: TR (time of repetition) = 2000 ms, TE (time of echo) = 40 ms, TA (time of acquisition) = 4 min 26 s, 128 averages with 1024 time points and 1200 Hz bandwidth.</p><p>MRS data is stored in RDA file format, developed by Siemens (see doi:10.1002/nbm.4257, Table 1). Each RDA file contains a text header (which can be viewed using a standard notepad application) and binary FID signal under the header. Data can be imported for analysis using several open-source packages (tested with FID-A doi:10.1002/mrm.26091 and spant doi:10.21105/joss.03646). </p><p>Naming scheme of files is as follows:</p><p><participant ID>_<hemisphere: L or R>_<region: F (frontal) or T (temporal)>.rda</p><p>For example: <i>001_L_F.rda</i> is data from participant 001 collected from a voxel placed in a ROI in the left frontal lobe.</p><p>In order to allow replication of the results from the original article, we also added information about the group of each of the subjects. This information is stored in a TSV file containing two columns: <i>participant_ID</i> and<i> group</i> (C – control, TU – unilateral tinnitus, TB – bilateral tinnitus).</p><p>Aside from replication of our results this dataset may be used e.g. for testing of different MRS data processing pipelines.</p>
Data for resonator behavior in the paper "Self-sensing, tunable monolayer MoS2 nanoelectromechanical resonators"
<p>Data for resonator behavior in the paper "Self-sensing, tunable monolayer MoS2<br> nanoelectromechanical resonators", <em>Nat. Commun.</em> 10, 4831 (2019); DOI:<a href="https://doi.org/10.1038/s41467-019-12795-1">10.1038/s41467-019-12795-1</a>.</p>
Data for: Physics-based Reconstruction Methods for Magnetic Resonance Imaging
<p>Magnetic Resonance Imaging measurement data used in our paper about 'Physics-based Reconstruction Methods for Magnetic Resonance Imaging' (DOI: 10.1098/rsta.2020.0196). (In version 2 the IR-FLASH data set was replaced with one which is from the same volunteer and slice as the ME-SE data set.) </p> <p>The data is acquired from healthy volunteers and stored in the format of the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>).</p> <p>The acquisition parameters are shown in the following table:</p> <p>flip angle[◦] TR/TE/ Delta TE[ms] bandwidth [Hz/px] matrix spokes TA[s] FOV[mm] slice[mm]</p> <p>IR-FLASH 6 4.10/2.58 630 256 × 256 1020 4 192 5<br> ME-SE 90/180 2500/9.9/9.9 390 256 × 256 25 × 16 80 192 3<br> ME-FLASH 5 10.60/1.37/1.34 960 200× 200 33 × 7 0.35a 320 5<br> PC-FLASH 10 4.46/2.96 1250 210 × 210 2 × 7 15 320 5<br> fmSSFPb 15 4.5/2.25 840 192× 192 4 × 101 × 40 137 192 1</p>
Higher-Mode Contact Resonance Operation of a High-Aspect- Ratio Piezoresistive Cantilever Microprobe (Data)
<p>Raw data, Ansys Workbench Projects and figures used for the article "Higher-Mode Contact Resonance Operation of a High-Aspect- Ratio Piezoresistive Cantilever Microprobe", published in the proceedings of SMSI 2020, which did not take place because of Covid-19 virus pandemic.</p> <p>The data can be opened by a text editor<br> Ansys projects are compressed using 7-Zip and can be opened by Ansys Workbench.</p>
Optimizing a Cantilever Measurement System towards High Speed, Nonreactive Contact-Resonance-Profilometry (Data)
<p>Raw data, scripts and figures used for the article "Optimizing a Cantilever Measurement System towards High Speed, Nonreactive Contact-Resonance-Profilometry", published in <em>Proceedings </em>on 21 Nov 2018.</p> <p>The data/scripts can be opened/executed by the software "Matlab"</p>
RESONANCES Database : Experiment no. 1 — VR Settings
<p>This dataset is an output of the RESONANCES physiological signal-based testing protocol aimed at recognizing and measuring atmospheric emotions. It contains the virtual reality (VR) settings designed to carry out the experiment: a dark, blue, amber, and bright corridor. The training configuration is helpful to teach participants to memorize the protocol, become familiar with the VR technology, and interact with the questionnaire interface.</p> <p>This dataset is made of 7 files:<br>no. 1 dataset summary (.pdf)<br>no. 1 instructions sheet (.txt)<br>no. 5 zipped folders (.zip) including files to run the VR settings (00_Corridor_Training; 01_Corridor_Dark; 02_Corridor_Amber; 03_Corridor_Blue; 04_Corridor_Bright)</p>
Exploring localized ENZ resonances and their role in superscattering, wideband invisibility, and tunable scattering
<p>The files contain the data generated by MATLAB and a sample MATLAB code for the selected figures. </p> <p>Research founded by Narodowe Centrum Nauki, project no UMO-2020/39/I/ST3/02413.</p>
Energy Harvesting Using a Nonlinear Resonator with Asymmetric Potential Wells
<p><strong><span>This repository contains</span></strong><span> the results of numerical simulations of a nonlinear bistable system for harvesting energy from ambient vibrating mechanical sources. Detailed model tests were carried out on an inertial energy harvesting system consisting of a piezoelectric beam with additional springs attached. The mathematical model was derived using the bond graph approach. Depending on the spring selection, the shape of the bistable potential wells was modified including the removal of wells’ degeneration. Consequently, the broken mirror symmetry between the potential wells led to additional solutions with corresponding voltage responses. The probability of occurrence for different high voltage/large orbit solutions with changes in potential symmetry was investigated. In particular, the periodicity of different solutions with respect to the harmonic excitation period were studied and compared in terms of the voltage output. The results showed that a large orbit period-6 subharmonic solution could be stabilized while some higher subharmonic solutions disappeared with the increasing asymmetry of potential wells. Changes in frequency ranges were also observed for chaotic solutions.</span></p>
RESONATE_T3.2_datasets_exemplars
<p>The files contain datasets filled out by relevant exemplars from the Case study regions, as defined in deliverable 3.3 of the RESONATE project. The data has been anonymized and agreed upon by case study representatives of the RESONATE project. </p>
Self-excited Contact Resonance Operation of a Tactile Piezoresistive Cantilever Microprobe with Diamond Tip (Data)
<p>Raw data and figures used for the article "Self-excited Contact Resonance Operation of a Tactile Piezoresistive Cantilever Microprobe with Diamond Tip", published in the proceedings of Sensor and Measurement Science International 2021; 2021-05-03 - 2021-05-06; digital.</p>
Real-Time Frequency Tracking of an Electro-Thermal Piezoresistive Cantilever Resonator with ZnO Nanorods for Chemical Sensing (Data)
<p>Origin projects, figures and COMSOL simulation used for the article "Real-Time Frequency Tracking of an Electro-Thermal Piezoresistive Cantilever Resonator with ZnO Nanorods for Chemical Sensing", published in <em>Chemosensors</em> on 03 Jan 2019.</p>
Performance of an Electrothermal MEMS Cantilever Resonator with Fano-Resonance Annoyance under Cigarette Smoke Exposure (Data)
<p>Origin projects, figures and LabVIEW software used for the article "Performance of an Electrothermal MEMS Cantilever Resonator with Fano-Resonance Annoyance under Cigarette Smoke Exposure", published in <em>Sensors </em>on 14 Jun 2021.</p>
Phase characteristic optimization of resonant MEMS environmental sensors (Data)
<p>Origin projects and figures used for the article "Phase characteristic optimization of resonant MEMS environmental sensors", published in the proceedings of Sensoren und Messsysteme 2018, 19. ITG/GMA-Fachtagung; 26.06.2018 to 27.06.2018; Nürnberg, Germany.</p>
Automotive Lidar and Vibration: Resonance, Inertial Measurement Unit and Effects on the Point Cloud
<p>This data repository contains vibration tests of an Ouster OS1-64 lidar including a docker based python environment and documentation.</p> <p>It consists of movement data, Fotos, IMU data, pointclouds and a ground truth measurements with an Riegl VZ6000 laser scaner.</p> <p>For further details see the linked publication and the example.ipynb notebook.</p> <p><strong>Quick start</strong></p> <ul> <li> <p>download the repo</p> </li> <li> <p>unzip the archive</p> </li> <li> <p>install VS code with the remote development extension</p> </li> <li> <p>install docker desktop</p> </li> <li> <p>open the folder in a new VS code window</p> </li> <li> <p>Say "yes" to open the folder inside a docker container</p> </li> <li> <p>wait for the container to start</p> </li> <li> <p>open the example jupyter notebook</p> </li> </ul> <p><strong>Structure</strong></p> <blockquote> <pre>├── .devcontainer .... VS code devcontainer (arm64 and amd64)</pre> <pre>├── Acceleromenter_A_z_deflection .... Accelerometer data</pre> <pre>├── Foto .... Fotos of the setup</pre> <pre>│ ├── VZ6000 .... Fotos of the ground truth measurements</pre> <pre>│ └── test_setup .... Fotos of the test setup</pre> <pre>├── Notebook .... A jupyter notebook with examples</pre> <pre>├── OS1_64_IMU .... Ouster IMU data</pre> <pre>├── OS1_64_pointcloud .... point cloud data</pre> <pre>├── VZ6000_groundtruth .... Ground truth data from Riegl VZ6000</pre> <pre> └── targets .... contains 2 different sets of reference</pre> <pre>│ ├── scene_aligned_by_reflectors</pre> <pre>│ └── targets_aligned</pre> <pre>└── files.csv .... an overview of the files and meta data</pre> </blockquote>
Data for: Probing electron and hole co-localization by resonant four-wave mixing spectroscopy in the extreme-ultraviolet
<p>Data for: Probing electron and hole co-localization by resonant four-wave mixing spectroscopy in the extreme-ultraviolet</p>
Phase separation of hnRNP A1 upon specific RNA-binding observed by magnetic resonance
<p>Experimental data, <a href="https://mmmx.info">MMMx</a> restraint and ensemble analysis files (.mcx), restraint data, raw ensembles, and ensemble lists with populations (.ens) pertaining to the manuscript "Phase separation of hnRNP A1 upon specific RNA-binding observed by magnetic resonance" <a href="https://www.biorxiv.org/content/10.1101/2022.03.21.485092v1">available at bioRxiv</a> and submitted to a peer-reviewed journal.</p>
Source code and simulation results for the computation of eigenfrequency sensitivities using Riesz projections for efficient optimization of nanophotonic resonators
<p><strong>Summary</strong></p> <p>Data and source code relate to the article "Computation of eigenfrequency sensitivities using Riesz projections for<br> efficient optimization of nanophotonic resonators" [<a href="https://doi.org/10.1038/s42005-022-00977-1">1</a>]. It combines direct differentiation of scattering problems with a contour integral method [<a href="https://doi.org/10.1016/j.jcp.2020.109678">2</a>] to compute eigenfrequency sensitivities. An optimization is used to demonstrate the relevance of the method.</p> <p><strong>Structure</strong></p> <p>The most important elements of this publication are the MATLAB scripts 'sensitivities.m' and 'optimization.m', which can be used to reproduce the most important results of the paper. The directories <strong>code</strong>, <strong>scattering</strong> and <strong>results </strong>contain the software RPExpand [<a href="https://doi.org/10.1016/j.softx.2021.100763">3</a>], input files for JCMsuite [<a href="https://doi.org/10.1002/pssb.200743192">4</a>] and results produced with the scripts, respectively. Furthermore, the latter contains the subfolder <strong>tabulated,</strong> which contains text files tabulating data presented in Figures 2 and 4 of the paper. Eventually, the function 'code/observation.m' evaluates the target for the optimization.</p> <p><strong>Additional Information</strong></p> <p>The applicaton is based on an example from the literature [<a href="https://doi.org/10.1126/science.aaz3985">5</a>]. Using apriori knowledge about the eigenmode of interest, we chose the scalar observable, as defined in Section B of the paper, to be the component of the electric field normal to the plane defining the solid of revolution.</p> <p>The convergence studies are based on the discrete, circular contour <span>\(\tilde{C} = \big\{ c_n~|~ c_n=r_0 e^{2\pi i n/8}, n \in \{0,1,...,7\}\big\}\)</span> with center <span>\(\omega_0 = 2 \pi c/(1600~\mathrm{nm})\)</span> and radius <span>\(r_0 = \omega_0\times10^{-2}\)</span>. For finite element degrees <span>\(d\)</span> higher than 5, the error saturates. For this reason, the differences between results for <span>\(d=5\)</span> and <span>\(d = 6\)</span> may depend on the hardware architecture.</p> <p>A larger radius <span>\(r = 4\times10^{13}\)</span> has been chosen for the optimization to include information from poles located further away from the frequency of interest. The target function <span>\(t(p_1,\dots,p_5) = -q_n \left(1 - \frac{(\omega_n-\omega_0)^2}{r^2} \right)\)</span>is minimized. The first factor is the negative <em>Q-</em>Factor and the second factor ensures that the target is zero at the boundary. If no eigenfrequency <span>\(\omega_n\)</span> is located inside the contour, the target is set to zero. For the purpose of this data publication some numerical parameters have been improved. This resulted in a faster convergence of the optimization.</p> <p><strong>Requirements</strong></p> <ul> <li>JCMsuite (version 5.2.0 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] Felix Binkowski, Fridtjof Betz, Martin Hammerschmidt, Philipp-Immanuel Schneider, Lin Zschiedrich, Sven Burger, Computation of eigenfrequency sensitivities using Riesz projections for efficient optimization of nanophotonic resonators, Communications Physics <strong>5</strong>, 202 (2022), https://doi.org/10.1038/s42005-022-00977-1</p> <p>[2] Felix Binkowski, Lin Zschiedrich, Sven Burger, A Riesz-projection-based method for nonlinear eigenvalue problems, Journal of Computational Physics <strong>419</strong>, 109678 (2020), https://doi.org/10.1016/j.jcp.2020.109678</p> <p>[3] 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>[4] 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> <p>[5] Kirill Koshelev, Sergey Kruk, Elizaveta Melik-Gaykazyan, Jae-Hyuck Choi, Andrey Bogdanov, Hong-Gyu Park, Yuri Kivshar, Subwavelength dielectric resonators for nonlinear nanophotonics, Science <strong>367</strong>, 288 (2020), http://dx.doi.org/%2010.1126/science.aaz3985</p>
theoretical and experimental study of the deposition of dielectric stacks on twin-hole silica fibers for implementation of compact all-fiber resonators
<p>This dataset includes the Matlab code to engineer theoretically a Bragg stack made of different dielectric layers. By changing the number of alternating stacks, their thickness and the refractive index of each layer it is possible to obtain the transmission curve of the Bragg stack versus the wavelength of the light in a certain range of values. The dataset includes also the experimental measurements of the resonances related to one of the fabricated compact resonators (based on the twin-hole fiber not poled) and obtained sweeping the wavelength of the input light injected through one of the two Bragg stacks and collecting the power at the exit of the other Bragg stack. </p>
Data and code for figures: Temperature dependence of microwave losses in lumped-element resonators made from superconducting nanowires with high kinetic inductance
<p>This directory contains the datasets and code (if applicable) for generating the figures in the research article: Temperature dependence of microwave losses in lumped-element resonators made from superconducting nanowires with high kinetic inductance, <em>Supercond. Sci. Technol.</em> <strong>37</strong> 075013</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.