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235 results for “spectroscopic”
Data from: A multiscale vibrational spectroscopic approach for identification and biochemical characterization of pollen
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Data from: Spectroscopic analysis of myoglobin and cytochrome c dynamics in isolated cardiomyocytes during hypoxia and reoxygenation
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Figure 1 from: Dovhanyk V, Mahlovanyy A, Harkov S, Synytsa V, Hrynovets V, Hrynovets I, Chaban I, Lelyukh M (2020) Spectroscopic criteria for early diagnosis of changes in the mineral and organic matrix of hard dental tissues. Pharmacia 67(1): 5-12. https://doi.org/10.3897/pharmacia.67.e35126
Figure 1 The infrared spectrum of intact enamel.
Codes for "From megahertz to terahertz qubits encoded in molecular ions: theoretical analysis of dipole-forbidden spectroscopic transitions in N2+"
<p>In folder "CreateBasisSet" are functions for diagonalizing the molecular Hamiltonian. Use "create_vec_v3.m". Adjust the size of the basis set inside the code.</p> <p>A complied coefficient matrix that was used in the paper is given: "BasisSet_v4_B70G0p2G_v01_N024_I02_E2_M1aS_M1S_v7p3.mat". This matrix can be used to plot all graphs that appear in the paper. </p> <p>The plotting scripts are also given: "Plots... .m"</p> <p>The script "Table_magic_v4.m" is used to find "magic" transitions.</p>
Figure 4 from: Abarova S, Stoitchkova K, Tzonev S, Argirova M, Yancheva D, Anastassova N, Tenchov B (2024) Spectroscopic and thermodynamic characterization of the interaction of a new synthesized antitumor drug candidate 2H4MBBH with human serum albumin. Pharmacia 71: 1-5. https://doi.org/10.3897/pharmacia.71.e112385
Figure 4 Modified Stern-Volmer plots for 2H4MBBH-HSA complexes at 15 and 25 °C.
Figure 1 from: Abarova S, Stoitchkova K, Tzonev S, Argirova M, Yancheva D, Anastassova N, Tenchov B (2024) Spectroscopic and thermodynamic characterization of the interaction of a new synthesized antitumor drug candidate 2H4MBBH with human serum albumin. Pharmacia 71: 1-5. https://doi.org/10.3897/pharmacia.71.e112385
Figure 1 Synthesis of 2-(2-hydroxy-4-methoxybenzylidene)-1-(1H-benzimidazol-2-yl)hydrazine.
Data and software for "Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument"
<p>Supplementary material to the DESI publication "Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument".</p> <p>The main "turbfigures.py" script generates the figures in the paper from the included data files.</p> <p>Contents:</p> <p><strong>Software files</strong></p> <ul> <li>turbfigures.py: Turbulence plotting and analysis plotting routines.</li> <li>turbulence.py: Analysis routines called by turbfigures.py. The live version of this code in production for desi is in the desimeter package (https://github.com/desihub/desimeter/blob/main/py/desimeter/turbulence.py)</li> </ul> <p><strong>Data files</strong></p> <ul> <li>coord-summary-20240124-pm.fits <ul> <li>Measured centroids of fibers in for 400 consecutive images of the focal plane while at zenith. File contains the following columns: <ul> <li>expid - exposure ID</li> <li>location - "location" of fiber in focal plane; ranges from 0 - 10000. Fibers on petal 0 have numbers between 0 and 1000, etc. There are only 500 positioners per petal, so most locations are not populated.</li> <li>move - in real data, this indexes over the moves in a DESI positioning loop; garbage information here.</li> <li>fpa_{x,y} - measured position of the fiber in this exposure</li> <li>req_{x,y} - requested position of the fiber in this exposure; not used for this data set where positioners are fixed in location</li> <li>{x,y}turb - empty in this file; gets filled in by turbfigures.py with measured turbulence</li> <li>flags_cor - flags indicating that a positioner or fiber may be problematic</li> <li>postype - flags indicating that a location corresponds to a real positioner vs. a fiducial</li> <li>expected_{x,y} - empty in this file; gets filled in by turbfigures.py with "expected" positions of each fiber, so that fpa_{x,y} - expected_{x,y} is a noisy estimate of the turbulence seen by the fiber.</li> </ul> </li> <li>Note that this file has an awkward structure. It has 10000 rows, one for each possible location. Most fields are then 400 element arrays that gives the corresponding values, corresponding to the 400 exposures present in the file.</li> </ul> </li> <li>coordinates-stats.ecsv <ul> <li>statistics of positioning accuracy and turbulence amplitude in DESI positioning loops. Measured RMSes are the 5-sigma clipped root-mean-square positioning offset in 2D: sqrt(mean(dx^2 + dy^2)). Measured medians are median(sqrt(dx^2 + dy^2)).</li> <li>Contents: <ul> <li>coord_filename - file name of DESI coordinates file statistics were drawn from</li> <li>rms_turbulence - RMS for the turbulent contribution to the positioning error</li> <li>rms_positioning - RMS for positioning after removing turbulence</li> <li>rms_total - Total RMS</li> <li>med_turbulence - median turbulence in exposure</li> <li>med_positioning - median positioning error in exposure</li> <li>med_total - median total turbulence + positioning error in exposure</li> <li>expid - exposure id number</li> </ul> </li> </ul> </li> </ul> <p>Dependencies: The included software uses the DESI software stack and otherwise the usual python astronomy packages: numpy scipy matplotlib astropy. Alternatively, people with access to NERSC can load the default DESI environment and pull in all needed dependencies.</p>
Deep-Learned Broadband Encoding Stochastic Filters for Computational Spectroscopic Instruments
<p>Abstract</p> <p>Computational spectroscopic instruments with broadband encoding stochastic (BEST) filters allow the reconstruction of the spectrum at high precision with only a few filters. However, conventional design manners of BEST filters are often heuristic and may fail to fully explore the encoding potential of BEST filters. The parameter constrained spectral encoder and decoder (PCSED)—a neural network-based framework—is presented for the design of BEST filters in spectroscopic instruments. By incorporating the target spectral response definition and the optical design procedures comprehensively, PCSED links the mathematical optimum and practical limits confined by available fabrication techniques. Benefiting from this, a BEST-filter-based spectral camera presents a higher reconstruction accuracy with up to 30 times enhancement and better tolerance to fabrication errors. The generalizability of PCSED is validated in designing metasurface- and interference-thin-film-based BEST filters.</p> <p> </p> <p>Please refer to https://github.com/Hao-Laboratory/PCSED for the source code for data analysis and visualization.</p>
Free and defect-bound (bi)polarons in LiNbO3: Atomic structure and spectroscopic signatures from ab initio calculations
<p>Dataset of the publication “Free and defect-bound (bi)polarons in LiNbO<sub>3</sub>: Atomic structure and spectroscopic signatures from ab initio calculations“, F. Schmidt, A. L. Kozub, T. Biktagirov, C. Eigner, C. Silberhorn, A. Schindlmayr, W. G. Schmidt, and U. Gerstmann, Physical Review Research 2, 043002 (2020) ( <a href="https://doi.org/10.1103/PhysRevResearch.2.043002">https://doi.org/10.1103/PhysRevResearch.2.043002</a> ). The tar file includes the data on which the plots shown in figures 2, 3, 4, 6, 7, 8, and 9 are based.</p>
Figure 3 from: Giurginca A, Šustr V, Tajovský K, Giurginca M, Matei I (2015) Spectroscopic parameters of the cuticle and ethanol extracts of the fluorescent cave isopod Mesoniscus graniger (Isopoda, Oniscidea). In: Taiti S, Hornung E, Štrus J, Bouchon D (Eds) Trends in Terrestrial Isopod Biology. ZooKeys 515: 111–125. https://doi.org/10.3897/zookeys.515.9395
Figure 3 - IR spectra of the ethanol extract of Mesoniscus graniger graniger.
HD 110067 photometric and spectroscopic data
<p>Data accompanying the discovery paper of a six-planet system transiting the bright star HD 110067, published in Nature (Luque et al. 2023, DOI: 10.1038/s41586-023-06692-3).</p>
Spectroscope
Jagiellonian University Museum Collegium Maius Inventory number: 16987; 2110/V Time of creation: 1st half of the 20th century Place of creation: Germany https://muzea.malopolska.pl/en/objects-list/2769 Source: Objaverse 1.0 / Sketchfab
MR Correlated Spectroscopic Imaging for Diagnosing Breast Cancer
ClinicalTrials.gov study NCT06090630. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Spectroscopic and Colorimetric Analysis of Acanthosis Nigricans in Patients With Hyperinsulinemia
ClinicalTrials.gov study NCT01125150. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pilot Study for Noninvasive Spectroscopic Detection of Adipose Tissue Inflammation in Obesity
ClinicalTrials.gov study NCT01900366. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Spectroscopic Profiling of Extracellular Vesicles By Resonant Gold Nanostructures in the Infrared
ClinicalTrials.gov study NCT06266195. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Optimization of Spectroscopic Imaging Parameters and Procedures for Prostate at 3 Tesla Using an External Probe
ClinicalTrials.gov study NCT00314522. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparative Spectroscopic Analysis of Synovial Fluid From the Stable and Unstable Ankle
ClinicalTrials.gov study NCT06228378. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Spectroscopic Analysis of Tongue Tumor Samples.
ClinicalTrials.gov study NCT05104619. IPD Sharing: NO. Countries: 1. Publications: 0.
Spectroscopic Assessment of Intramyocardial Oxygen Saturation Feasibility During Open-heart Surgery
ClinicalTrials.gov study NCT05479968. IPD Sharing: NO. Countries: 1. Publications: 0.
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.