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277 results for “infrared spectroscopy”
FIGURE 6. A in Barcoding without DNA? Species identification using near infrared spectroscopy
FIGURE 6. A) First interval, between 1019.56–1088.50 nm. B) Interval 15, 2052.22–2121.15 nm. DF (1, 2, 3) indicate the first three discriminant functions.
FIGURE 7 in Barcoding without DNA? Species identification using near infrared spectroscopy
FIGURE 7. Discriminant analysis based on 50 points between 2052.22–2086.69 nm. This region comprises the first half of the region used in Figure 4B. DF indicates discriminant functions.
FIGURE 1. A in Barcoding without DNA? Species identification using near infrared spectroscopy
FIGURE 1. A fly in the accessory for diffuse reflectance (see text). The fly is pinned on a piece of Styrofoam.
FIGURE 1 in Fourier transform infrared spectroscopy (FTIR) characteristics of ancient amber artifacts of the Han Dynasty from Hunan, China
FIGURE 1. Possible ancient trade roadmap of both the Eurasian Steppe Silk Road and the Maritime Silk Road. 1, the present Capital, Beijing; 2, the ancient Capital city during the Han Dynasty, Xi'an, Shaanxi Province; 3, Nanyang, Henan Province, where unearthed artifacts of Han Dynasty made by Burmese amber (Chen et al., 2019); 4, Tomb Changchen M010, Changsha, Hunan Province; 5, Tomb Chentie M001, Chenzhou, Hunan Province.
FIGURE 3 in Fourier transform infrared spectroscopy (FTIR) characteristics of ancient amber artifacts of the Han Dynasty from Hunan, China
FIGURE 3. FTIR spectra of amber samples. A, SYS20220716-1. B, SYS20020716-2. C, SYS20220716-4. D, SYS20220716-5.
Experimental and analytical methods for thermal infrared spectroscopy of complex dust coatings in a simulated asteroid environment
<p>The spectral and thermophysical effects of thin-continuous, macro-discontinuous, and micro-discontinuous dust cover are not understood and require relevant laboratory analyses to be deconvolved in an orbital setting. We have constructed a custom environment chamber that enables the controlled deposition of size-regulated dust particles in coatings with varying continuity and thickness. TIR spectra of coated substrates acquired in a simulated asteroid environment (SAE) are used to investigate the extent to which dust coatings of different thicknesses and arrangements contribute to orbital spectral signatures of airless body surfaces. </p> <p>TIR (5-50 𝜇m) spectra of each sample are acquired under SAE conditions using the Planetary and Asteroid Regolith Spectroscopy Environmental Chamber (PARSEC) at Stony Brook University. PARSEC is designed to measure samples under environmental conditions typical of airless bodies. The chamber houses a sample wheel with six sample cups and a calibration target coated with Nextel black. There is also a black body target under the wheel. All sample cup and black body targets can be individually heated and rotated into position from outside of the chamber. Temperature is controlled through two Eurotherm Mini8 Loop Controllers and managed on an in-lab computer with the Eurotherm iTools interface. Samples are illuminated at 55° incidence by a quartz halogen lamp connected to a Bentham 610 power source. Surrounding the sample wheel is a cold shield actively cooled by the input of liquid nitrogen into an internal dewar to reach temperatures < 150 K. Pressure in the chamber is controlled by a Pfeiffer HiCube turbo vacuum pump to reach 10<sup>-6</sup> mbar. In line with the vacuum chamber is a pressure regulated tank of N<sub>2</sub> used for purging and ambient pressure measurements. The PARSEC chamber is connected to a Nicolet 6700 FTIR spectrometer equipped with a Cesium Iodide (CsI) beamsplitter and a deuterated L-alanine doped triglycine sulfate (DLaTGS) detector with a CsI window. The spectrometer is actively purged with air scrubbed of CO<sub>2</sub> and water vapor and sealed at the interface with PARSEC. A total of 256 scans from 2,200 to 400 cm<sup>-1</sup> are integrated for a 10-minute measurement period, using a spectral sampling of 2 cm<sup>-1</sup>. During each experimental session, all samples and the black body are measured under SAE conditions. Calibration measurements of the blackbody target at 70 and 100°C are acquired, then the integrated sample cup heaters and solar lamp are adjusted to achieve the desired sample brightness temperature of 80°C. Samples are allowed to reach temperature under the lamp for more than 45 minutes until the spectral maximum stabilizes and the calculated brightness temperature at the CF is within ~10 K of the target 353 K. This procedure is repeated for all samples while ensuring the chamber temperature remains stable under 150 K through continued addition of liquid nitrogen. The Radiance-to-emissivity conversion method used determines the maximum brightness temperature between 500 and 1700 cm-1 and divides the radiance by a Planck function of the same temperature. This assures the maximum brightness temperature is the kinetic temperature of the same, and its emissivity is unity at the frequency of this maximum. This dataset includes 15 different samples acquired under SAE and ambient pressure/temperature conditions. These samples range in layer thickness and continuity and are intended to test and demonstrate the range of the coating process.</p>
Dataset for Intermediate Infrared Spectroscopy of Pyroxene
<p>Spectra of pyroxene samples used in paper entitled Intermediate Infrared Spectroscopy of Pyroxene: Determination of Ca-Mg-Fe Composition in the 4-8 Micron Wavelength Range</p>
Fig. 4 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 4. ATR-FTIR spectra of (i) P. ponderosa pollen, (ii) enzymatically-isolated sporopollenin, (iii) sporopollenin isolated by acidolysis with phosphoric acid, and (iv) sporopollenin isolated by acetolysis. Original data files are deposited with the accompanying Data in Brief article (Lutzke et al., 2019).
Fig. 6 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 6. ATR-FTIR spectra of (i) enzymatically-isolated sporopollenin, (ii) trans- 4-hydroxycinnamic acid, (iii) trans-4-hydroxy-3-methoxycinnamic acid, (iv) trans-4-methoxycinnamic acid, and (v) methyl trans-4-hydroxycinnamate. Original data files are deposited with the accompanying Data in Brief article (Lutzke et al., 2019).
Fig. 2 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 2. Examples of (a) α-pyrone biosynthesis in the exine and (b) carotenoids that may be oxidatively polymerized to form sporopollenin according to the hypothesis of Brooks and Shaw (1968).
Fig. 7 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 7. Scheme depicting the synthesis of acetonides (cyclic ketals) from 1,2- or 1,3-diols naturally present in sporopollenin, followed by hydrolysis under acidic conditions. This process corresponds to the spectroscopic changes observed in Figure S21.
Fig. 1 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 1. Scheme depicting enzymes involved in sporopollenin synthesis and selected degradation products. (a) Mid-chain oxidation of fatty acid substrates by CYP703A2, ω-oxidation by CYP704B1 and CYP704B2, and reduction of an activated fatty acid substrate by MS2. (b) Proposed sporopollenin monomer identified by Li et al. (2019). (c) The sporopollenin degradation products trans-4-hydroxycinnamic acid, trans-4-hydroxy-3-methoxycinnamic acid, and 7-hydroxyhexadecanedioic acid.
Fig. 8 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 8. ATR-FTIR spectra of (i) enzymatically-isolated sporopollenin, (ii) trans- 4-hydroxycinnamic acid, (iii) trans-4-hydroxy-3-methoxycinnamic acid, (iv) trans-4-methoxycinnamic acid, and (v) methyl trans-4-hydroxycinnamate. Original data files are deposited with the accompanying Data in Brief article (Lutzke et al., 2019).
Fig. 9 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 9. The relationship between IR band assignments and hypothesized structural components of sporopollenin.
Fig. 5 in Detailed characterization of Pinus ponderosa sporopollenin by infrared spectroscopy
Fig. 5. ATR-FTIR spectra of (i) enzymatically-isolated sporopollenin, (ii) sporopollenin isolated by acidolysis with phosphoric acid, and (iii) sporopollenin isolated by acetolysis. Distinct bands or shoulders with diagnostic importance are assigned a unique identifier in Table 3. Original data files are deposited with the accompanying Data in Brief article (Lutzke et al., 2019).
NEMO: A Database for Emotion Analysis Using Functional Near-infrared Spectroscopy
<p>The data from publication "NEMO: A Database for Emotion Analysis Using Functional Near-infrared Spectroscopy".<br> <br> <code>nemo-bids.zip</code> contains the raw optical density (OD) recordings and corresponding metadata for each participant.</p> <p><code><task_id>_csv.zip</code> provides an easy way to access the processed <a href="https://mne.tools/stable/auto_tutorials/epochs/10_epochs_overview.html">epochs</a> data without needing any code from the code repository or other BIDS tools.</p> <p><code>NEMO_additional_metadata.tsv</code> contains additional details, such as subject's age, monitor refresh rate, gender, handedness, recording date and time, specifics about different trial types, and more. Detailed descriptions of each column can be found in the <code>NEMO_additional_metadata_column_descriptions.tsv</code> file.</p> <p>For how to use the data, refer to <a href="https://github.com/Cognitive-Computing-Group/NEMO">https://github.com/Cognitive-Computing-Group/NEMO</a></p>
data for "A machine-learned approach to monitor chemical reaction via in-situ infrared spectroscopy"
<p>Source spectral and structural data of the AIMD trajectory and NEB calculation</p> <p>1. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/180-structure-IR.zip">180-structure-IR</a>.zip Source spectral and structural data of the AIMD trajectory for the selected 180 configurations</p> <p>2. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/md-pos-1.xyz?versionId=1a43760b-5cba-4548-85e6-6a45252403fc">md-pos-1.xyz</a> AIMD trajectories</p> <p>3. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-0-5100.tar.gz</a> <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-5101-7500.tar.gz</a> <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-7501-9500.tar.gz</a> Source spectral and structural data of the AIMD trajectory for the extracted 9500 configurations</p> <p>4. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/split-neb-75.zip?versionId=a30f0f34-3ce2-4619-abd3-62e71174069b">split-neb-75.zip</a> Source spectral and structural data of the AIMD trajectory for the CO-CO dimerization reaction</p>
The Effect of Percutaneous Superior Venae Cava Cannulation Clamping on Cerebral Near Infrared Spectroscopy in MICS
ClinicalTrials.gov study NCT01166841. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Identifying Cerebral Hemodynamic Patterns in Mood Disorders and Mild Cognitive Impairment: A Functional Near-Infrared Spectroscopy (fNIRS) Study
ClinicalTrials.gov study NCT06897670. IPD Sharing: NO. Countries: 1. Publications: 7.
Multi-site Near Infrared Spectroscopy (NIRS) Monitoring of Children During Exercise
ClinicalTrials.gov study NCT00556231. IPD Sharing: Not stated. Countries: 1. Publications: 3.
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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)
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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.