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1,041 results for “Spectroscopy”
Raman spectra from "Discrimination of immune cell activation using Raman micro-spectroscopy in an in-vitro & ex-vivo model"
<p>The uploaded files are data from Chaudhary et al, 2021 (Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, Discrimination of immune cell activation using Raman micro-spectroscopy in an in-vitro & ex-vivo model, https://doi.org/10.1016/j.saa.2020.119118).</p> <p>There are two files in .mat format. In one (Preprocessed.mat) the data has been completely pre-processed according to the methods described in the paper.</p> <p>In the second (Unpreprocessed.mat) the data has been calibrated using the methods described in the paper, but has not received further pre-processing.</p> <p>Within both files there are datasets for the spectral measurement from each cell (‘spectra’), together with the treatment which was applied to each sample (‘treatment’) and the wavenumber at which the spectral measurements were made (‘wavenumber’).</p>
Deciphering the impacts of main inflowing rivers on dissolved organic matter in Lake Daye using isotopes, optical spectroscopy, and FT-ICR-MS during non-flood season
<p>The uploaded data include water quality data, isotopes, DOM fluorescence index and FT ICR MS data of Daye Lake and its inflowing rivers.</p>
FAIRmat Tutorial 15: Use of pynxtools with Examples from Optical Spectroscopy
<p>The FAIRmat Tutorial 15 will address the necessity of FAIR research data management when working with experimental data in materials science. FAIRmat provides NOMAD (https://nomad-lab.eu/nomad-lab/) to the scientific community as a platform specifically developed for this purpose. </p> <p>NOMAD integrates the NeXus Ontology based on the NeXus community standard (https://www.nexusformat.org/). The NeXus standard has been significantly expanded over the years and now includes a comprehensive range of metadata definitions, making it applicable to various experimental techniques used in materials science. </p> <p>FAIRmat, in collaboration with the scientific community and technology partners, has developed pynxtools. These software tools simplify the conversion of experimental data and metadata according to the community standard, making it easy to integrate experimental data into NOMAD. </p> <p>This tutorial will cover using the pynxtools and how such datasets are managed within NOMAD. To demonstrate the functionality of pynxtools in combination with NOMAD, we will use ellipsometry and Raman spectroscopy data as examples.</p> <p>The main topics to be covered are: <br>• FAIR research data management <br>• NeXus data modelling <br>• Data conversion and verification using pynxtools<br>• Data management with NOMAD </p> <p>Disclaimer: NOMAD is being continuously developed based on input and feedback from the scientific community. Hence the features, services or interface may have changed since the time of recording of this video. For up-to-date information please consult our latest tutorials and the NOMAD documentation https://nomad-lab.eu/prod/v1/docs/</p>
External cavity quantum cascade laser vibrational circular dichroism spectroscopy for fast and sensitive analysis of proteins at low concentrations (Data analysis)
<p>This record contains a docker container image of the data evaluation shown in the publication "External cavity quantum cascade laser vibrational circular dichroism spectroscopy for fast and sensitive analysis of proteins at low concentrations". The evaluations can be accessed by running the container and accessing the contained Jupyter Lab via a browser. The calculations are contained in 'Eval_protein_D2O.ipynb'.</p> <p>To run the container (requires docker):</p> <p>1.download 'd2o_vcd.tar'</p> <p>2. in the command line, execute 'docker load -i d2o_vcd.tar'. This will return something like 'Loaded image: <image_name>' with image_name probably being "drhermann/vcd_d2o_00:trial_03"</p> <p>3. then 'docker run -p 8889:8889 <image_name>' replacing the brackets with the actual name of the image, such as drhermann/vcd_d2o_00:trial_03</p> <p>4.In your command line a link starting in 'http://127.0.0.1:8888/lab?token=...' will appear. Open this link in your browser to access the evaluation.</p>
Modeling Protein Conformations by Guiding AlphaFold2 with Distance Distributions. Application to Double Electron Electron Resonance (DEER) Spectroscopy.
<p>We describe a modified version of AlphaFold2 that incorporates experiential distance distributions into the network architecture for protein structure prediction. Harnessing the OpenFold platform, we fine-tuned AlphaFold2 on a small number of structurally dissimilar proteins to explicitly model distance distributions between spin labels determined from Double Electron-Electron Resonance (DEER) spectroscopy. We demonstrate the performance of the modified AlphaFold2, referred to as DEERFold, in switching the predicted conformations guided by experimental or simulated distance distributions. Remarkably, the intrinsic performance of AlphaFold2 substantially reduces the number and the accuracy of the widths of the distributions needed to drive conformational selection thereby increasing the experimental throughput. The blueprint of DEERFold can be generalized to other experimental methods where distance constraints can be represented by distributions. </p>
Supporting data for boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy
<p>This dataset includes the properties necessary to reproduce the analysis of water vapour statistics derived from imaging spectroscopy as in:</p> <p>Richardson et al. (2021a) DOI: 10.5194/amt-14-5555-2021<br> Richardson et al. (2021b) DOI: 10.5194/amt-2021-163 (pre-acceptance DOI, follow links to published version)</p> <p>Files include the retrieval emulator parameters, atmospheric profiles used in the emulator development, column-mean water vapour and cloud water both for the total column water vapour (TCWV) and "effective" TCWV, which accounts for the water vapour integrated along the direct solar path at a range of solar zenith angles, see Richardson 2021b, Eq. (7).</p>
Data and Code for Spin and Orbital Spectroscopy in the Absence of Coulomb Blockade in Lead Telluride Nanowire Quantum Dots
<p>This repository contains combined data for two papers. </p> <p>Growth of PbTe nanowires by Molecular Beam Epitaxy<br> Authors: Sander G. Schellingerhout, Eline J. de Jong, Maksim Gomanko, Xin Guan, Yifan Jiang, Max S.M. Hoskam,<br> Sebastian Koelling, Oussama Moutanabbir, Marcel A. Verheijen, Sergey M. Frolov, Erik P.A.M. Bakkers</p> <p><br> Spin and Orbital Spectroscopy in the Absence of Coulomb Blockade in Lead Telluride Nanowire Quantum Dots<br> Authors: M. Gomanko, E.J. de Jong, Y. Jiang, S.G. Schellingerhout, E.P.A.M. Bakkers, and S.M. Frolov</p> <p><br> Content of this repository: </p> <p>Readme file. </p> <p>/RawData/<br> Original data obtained at the time of measurement separated into 3 folders from different chips/cooldowns<br> Data from devices 1,3 and 4 can be found in "RawData/PbTe_chip1", device 2 in "RawData/PbTe_chip2" and devices 5-8 in "RawData/PbTe_GBg"</p> <p>/Measurement notebooks/<br> OneNote notebook with 4 different sections for 3 chips (two sections for backgate chip). Pages in these sections contain the device number in the name.<br> Also, the same notebook is exported in pdf format for convenience.</p> <p>/Data processing/<br> Readme file, Jupiter notebooks, data files, and pictures, that were used to extract g-factors for different field orientations in device2.</p> <p>/Data summaries/<br> Powerpoints, that were used to overview data during the measurement stage.<br> Not all data from these powerpoints are present in the repository or paper (specifically excluding early data used in "additional backgate devices.pptx" and "PbTe 3rd device.pptx").</p> <p>Data file types:</p> <p>data_NNN.dat - the original data file obtained at the time of the experiment<br> dataNNN.py - the original QTLab data acquisition script saved with data<br> data_NNN.set - settings of measurement instruments at the time of measurement<br> data_NNN.meta - auxillary file necessary for plotting data using SpyView (see below) <br> data_NNN.MTX - a simple 2D/3D matrix format developed for Spyview</p> <p>NNN stands for dataset number, automatically indexed by QTLab</p> <p><br> How to plot data:</p> <p>1) Spyview - a free data plotting program written by Gary Steele</p> <p>Data in this repository can be simply dropped into Spyview for plotting. </p> <p>Spyview also produces and can read .mtx files which are available for some of the data in this repository.</p> <p>https://nsweb.tn.tudelft.nl/~gsteele/spyview/</p> <p><br> 2) QTPlot - a Python plotter written by Ruben van Gulik</p> <p>Data in this repository can be directly opened with QTPlot, which will read axis labels.</p> <p>https://github.com/Rubenknex/qtplot</p> <p>Note: requires PyQT4</p>
Local Ultrasonic Resonance Spectroscopy: A Demonstration on Plate Inspection - Dataset
<p><em><strong>The peer-reviewed publication using this dataset has been published in the Journal of Nondestructive Evaluation, and can be accessed via <a href="https://doi.org/10.3390/epidemiologia2030024">https://doi.org/10.1007/s10921-020-00674-5</a>. Please cite this article when using the dataset.</strong></em></p>
Training data for benchtop NMR and UV/vis spectroscopy for Artificial Neural Networks
<p>Data set of low-field NMR spectra and UV/vis spectra for the synthesis of mesalazine intermediates, which were used as training or validation data for data processing with artificial neural networks development</p> <p><strong>Low-field NMR spectra for the nitration step:</strong></p> <p>The pure component spectrum of 2ClBA, 3N-2ClBA, and 5N-2ClBA are marked as NMR_pure_spectrum. The concentration levels for 2ClBA, 3N-2ClBA and 5N-2ClBA are in row 1, 2, and 3, respectively.</p> <p>The data sets marked as NMR_ represents low-field NMR-spectra recorded. The reference values for 2ClBA, 3N-2ClBA and 5N-2ClBA are in column 1, 2, and 3, respectively.</p> <p><strong>Datafusion data sets for the hydrolysis and nitration step</strong></p> <p>The NMR data are either recorded or simulated from the pure NMR spectrum of each individual component. The reference values for 2ClBA, 3N-2ClBA, 5N-2ClBA, 3-NSA and 5-NSA are either assigned with UHPLC measurements or calculated from the prepared solutions.</p> <p>The NMR spectra are depicted in datafusion_NMR_training. The reference values for 2ClBA, 3N-2ClBA and 5N-2ClBA are in column 1, 2, and 3, respectively.</p> <p>The UV/vis spectra are depicted in datafusion_UVvis_training. The reference values for 2ClBA, 3N-2ClBA, 5N-2ClBA, 3-NSA and 5-NSA are in column 1, 2, 3, 4, and 5, respectively.</p> <p><strong>Process data</strong></p> <p>The NMR spectra for the stability run and the run with dynamic changes are depicted in process_NMR_. The first column is the time stamp.</p> <p>The UV/vis spectra for the stability run and the run with dynamic changes are depicted in process_UV_. The first column is the time stamp.</p>
Data for Crystallographic orientation mapping of lizardite serpentinite by Raman spectroscopy
<p>The serpentine mineral lizardite displays strong Raman anisotropy in the OH-stretching region, resulting in significant wavenumber shifts (up to c. 14.5 cm <sup>-1</sup>) that depend on the orientation of the impinging excitation laser relative to the crystallographic axes. We quantified the relationship between crystallographic orientation and Raman wavenumber using well-characterised samples of Monte Fico lizardite by applying Raman spectroscopy and electron backscatter diffraction (EBSD) mapping on thin sections of polycrystalline samples and grain mounts of selected single crystals, as well as by a spindle stage Raman study of an oriented cylinder drilled from a single crystal. We demonstrate that the main band in the OH-stretching region undergoes a systematic shift that depends on the inclination of the c-axis of the lizardite crystal. The data are used to derive an empirical relationship between the position of this main band and the c-axis inclination of a measured lizardite crystal: y = 14.5 cos<sup>4 </sup>(0.013 x + 0.02) + (3670 ± 1), where y is the inclination of the c-axis with respect to the normal vector (in degrees) and x the main band position (wavenumber in cm <sup>-1</sup>) in the OH-stretching region. This new method provides a simple and cost-effective technique for measuring and quantifying the crystallographic orientation of lizardite-bearing serpentinite fault rocks, which can be difficult to achieve using EBSD alone. In addition to the samples used to determine the above empirical relationship, we demonstrate the applicability of the technique by mapping the orientations of lizardite in a more complex sample of deformed serpentinite from Elba Island, Italy.</p>
Low-frequency anharmonic couplings in bromoform revealed from 2D Raman-THz spectroscopy: From the liquid to the crystalline phase
<p>Raw data for "Low-frequency anharmonic couplings in bromoform revealed from 2D Raman-THz spectroscopy: From the liquid to the crystalline phase"</p>
Data for 'Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy'
<p>This folder contains all the raw data needed to generate the figures in the paper '<em>Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy.</em>' The data are seperated by the figures in which they appear, with a text folder in each folder that contains any relevant additional information. </p>
Data for "Direct Observation of Ultrafast Exciton Localization in an Organic Semiconductor with Soft X-ray Transient Absorption Spectroscopy"
<p>Underlying data for figures 1-3 and supplementary figures S1-S7 for the paper entitled 'Direct Observation of Ultrafast Exciton Localization in an Organic Semiconductor with Soft X-ray Transient Absorption Spectroscopy'.</p>
The effect of spin polarization in DEER spectroscopy
<p>This works examines the physics underlying double electron-electron resonance (DEER) spectroscopy, a magnetic-resonance method that provides nanoscale data about protein structure and conformations. Here, the data files are presented that were used for publication, both main text and supplement.</p>
Data for Vibrational Couplings between Protein and Co-factor in Bacterial Phytochrome Agp1revealed by 2D-IR Spectroscopy
<p>2D-IR data for the bacteriophytochrome Agp1 in the Pr and Pfr states </p>
Correlative Raman Imaging and Scanning Electron Microscopy: The Role of Single Ga Islands in Surface-Enhanced Raman Spectroscopy of Graphene_experimental dataset
<p>This dataset contains the raw unprocessed data for Piastek et al., Correlative Raman Imaging and Scanning Electron Microscopy: The Role of Single Ga Islands in Surface-Enhanced Raman Spectroscopy of Graphene, <em>J. Phys. Chem. C</em> 2022, 126, 9, 4508–4514. </p>
Original data for publication: Luminescence spectroscopy of CaAl12O19:Eu3+ and SrAl12O19:Eu3+ nanoparticles
<p>Original data for publication:</p> <p>Luminescence spectroscopy of CaAl12O19:Eu3+ and SrAl12O19:Eu3+ nanoparticles<br> Jafar Afshani, Teresa Delgado, Gheorghe Paveliuc, Hans Hagemann, Journal of Luminescence 246 (2022) 118805.</p>
Sensitivity-enhanced multidimensional solid-state NMR spectroscopy by optimal-control-based transverse mixing sequences
<p>The dataset here contains the raw data and pulse programs used for the publication "Sensitivity-enhanced multidimensional solid-state NMR spectroscopy by optimal-control-based transverse mixing sequences" submitted to JACS.</p> <p>All data is in a native Bruker TopSpin format. Data is organized in folders corresponding to Figures of the original publication. Detailed description is included in the file description.txt.</p> <p>We reccomend to visit our website optimal-nmr.net for additional information about optimal control methods applied to pulse sequence development for solid-state magic-angle-spinning NMR studies of proteins.</p>
Data for "Ultrafast Spin-Charge Conversion at SnBi2Te4/Co Topological Insulator Interfaces Probed by Terahertz Emission Spectroscopy"
<p>Data for "Ultrafast Spin-Charge Conversion at SnBi2Te4/Co Topological Insulator Interfaces Probed by Terahertz Emission Spectroscopy"</p> <p>(<a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adom.202102061">https://onlinelibrary.wiley.com/doi/abs/10.1002/adom.202102061</a> and <a href="https://arxiv.org/pdf/2203.08756.pdf">https://arxiv.org/pdf/2203.08756.pdf</a>)</p> <p> </p> <p>E Rongione, S Fragkos, L Baringthon, J Hawecker, E Xenogiannopoulou, P Tsipas, C Song, M Mičica, J Mangeney, J Tignon, T Boulier, N Reyren, R Lebrun, J‐M George, P Le Fèvre, S Dhillon, A Dimoulas, H Jaffrès</p>
Raw data for 'Increasing the Modulation Depth of Gd(III)-based Pulsed Dipolar EPR Spectroscopy (PDS) with Porphyrin-GdIII Laser Induced Magnetic Dipole Spectroscopy'
<p>Raw data for 'Increasing the Modulation Depth of Gd(III)-based Pulsed Dipolar EPR Spectroscopy (PDS) with Porphyrin-GdIII Laser Induced Magnetic Dipole Spectroscopy'</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.