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81 results for “Raman data”
Raman carbonaceous-material spectrum data used to estimate the peak temperatures of the samples
<p>Open files are Raman carbonaceous-material spectrum data obtained from the Ohyamamisaki conglomerate and the Higashigo Formation (eastern Shikoku) as well as the Nyunokawa conglomerate and the Ryujin Formation (central-western Kii Peninsula), Shimanto Accretionary Complex. The data can be analysed using the code proposed by Kaneki and Kouketsu (Island Arc, 2022, https://doi.org/10.1111/iar.12467) or PeakFit ver. 4.12. The data have been used in Shimura et al. (submitted to Tectonics).</p>
Data of: Polarization-Insensitive Integration of Nanoparticle-on-a-Slit Cavities with Dielectric Waveguides for On-chip Surface Enhanced Raman Spectroscopy
<p>Original data of the work called Polarization-Insensitive Integration of Nanoparticle-on-a-Slit Cavities with Dielectric Waveguides for On-chip Surface Enhanced Raman Spectroscopy which it wa submitted to a jounal. The file.zip (called ZENODO.zip) includes the experimental and simulated data.</p>
Raman data and corresponding radiosonde from Beijing Institute of Technology
<p>Uploaded data includes: </p> <p>1. data of pure rotational Raman lidar system arranged in Beijing Institute of Technology from the day of Feb. 27 to Mar. 2, 2017,</p> <p>2. radiosonde data for the above dates,</p> <p>3. README files.</p> <p> </p>
Raman data for "Mechanisms and seasonal drivers of calcification in the temperate coral Turbinaria reniformis at its latitudinal limits"
<p>This file contains all the Raman data and code for "Mechanisms and seasonal drivers of calcification in the temperate coral <em>Turbinaria reniformis</em> at its latitudinal limits" by Ross et al. in Proceedings of the Royal Society B. Run the file, "run.R" in R to reproduce the analysis.</p> <p>Please see the published paper for methods and details: http://rspb.royalsocietypublishing.org/content/285/1879/20180215</p>
Raman data for "Similar controls on calcification under ocean acidification across unrelated coral reef taxa"
<p>This file contains the Raman data and code for "Similar controls on calcification under ocean acidification across unrelated coral reef taxa" by Comeau et al. in Global Change Biology. Run the file, "run.R" in R to reproduce the analysis.</p> <p>Please see the published paper for methods and details: https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.14379</p>
Data from "Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering"
<p>Data from "Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering" published in PNAS.</p>
Raman data for "Flow-driven micro-scale pH variability affects the physiology of corals and coralline algae under ocean acidification"
<p>This file contains the Raman data and code for "Flow-driven micro-scale pH variability affects the physiology of corals and coralline algae under ocean acidification" by Comeau et al. in Scientific Reports. Run the file, "run.R" in R to reproduce the analysis.</p> <p>Please see the published paper for methods and details: https://doi.org/10.1038/s41598-019-49044-w</p>
Raman data for "Resistance to ocean acidification in coral reef taxa is not gained by acclimatization"
<p>This file contains the Raman data and code for "Resistance to ocean acidification in coral reef taxa is not gained by acclimatization" by Comeau et al. in Nature Climate Change. Run the file, "run.R" in R to reproduce the analysis.</p> <p>Please see the published paper for methods and details: https://doi.org/10.1038/s41558-019-0486-9</p>
Raman data for "Resistance of corals and coralline algae to ocean acidification: physiological control of calcification under natural pH variability"
<p>This file contains the Raman data and code for "Resistance of corals and coralline algae to ocean acidification: physiological control of calcification under natural pH variability" by Cornwall et al. in Proceedings of the Royal Society B. Run the file, "run.R" in R to reproduce the analysis.</p> <p>Please see the published paper for methods and details: <a href="https://doi.org/10.1098/rspb.2018.1168">https://doi.org/10.1098/rspb.2018.1168</a></p>
Research data supporting "Surface Enhanced Raman Scattering Artificial Nose for High Dimensionality Fingerprinting"
<p>Experimental raw research data supporting the publication: Kim N., Thomas M.R. et al., 2019, Nature Communications.</p>
Raman spectral data for ''The evaluation of space weathering effects on lunar samples from a Raman spectroscopic perspective''
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Research Data for "Kinetic Analysis of the Self-Discharge of the NiOOH OER Active Phase in KOH Electrolyte: Insights from In-Situ Raman and UV-Vis Reflectance Spectroscopies"
<p>This dataset provides the underlying experimental and simulation raw data supporting the figures of both main text and supporting information of the paper "Kinetic Analysis of the Self-Discharge of the NiOOH OER Active Phase in KOH Electrolyte: Insights from In-Situ Raman and UV-Vis Reflectance Spectroscopies" appearing in <em>Journal of Catalysis</em> under DOI: <a href="https://doi.org/10.1016/j.jcat.2024.115823" rel="noreferrer">https://doi.org/10.1016/j.jcat.2024.115823</a>.</p>
Raw data for "Signatures of Intra- and Intermolecular Vibrational Coupling in Halogenated Liquids Revealed by Two-Dimensional Raman-Terahertz Spectroscopy"
<p>Raw data for "Signatures of Intra- and Intermolecular Vibrational Coupling in Halogenated Liquids Revealed by Two-Dimensional Raman-Terahertz Spectroscopy"</p>
Estimating Modal Mineralogy using Raman Spectroscopy: Multivariate Analysis Models and Raman Cross-Section Proxies - Chapter 4 Data
<p>I provide supplementary data for Chapter 4 of my dissertation including electron microprobe analysis data as well as the Raman spectra and associated metadata of the mineral end-members, the mineral-mineral mixtures, and the diamond-mineral mixtures.</p>
Raman Data for "Coral growth persistence amidst bleaching events"
<p>This dataset includes codes and data used in "Coral growth persistence amidst bleaching events" by Mantanona and DeCarlo (2023). Methods are included in the publication and supplementary material. To reproduce the analysis, run the file, "run_me.R". </p>
LIBS and raman spectral data in the qaidam analog
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Data from: Chemo-mechanical characterisation of carious dentine using Raman microscopy and Knoop microhardness
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Data from: Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation
<p class="AbstractSummary"><b>Background</b></p> <p class="AbstractSummary">Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Pathologists are in critical need of accurate biomarkers to characterize PC, particularly to confirm the presence of intraductal carcinoma of the prostate (IDC-P), an aggressive histopathological variant for which therapeutic options are now available. Our aim was to identify IDC-P with Raman micro-spectroscopy and machine learning technology following a protocol suitable for routine clinical histopathology laboratories.</p> <p class="AbstractSummary"><b>Methods and findings</b></p> <p class="AbstractSummary">We used Raman micro-spectroscopy to differentiate IDC-P from PC, as well as PC and IDC-P from benign tissue on formalin-fixed paraffin-embedded first-line radical prostatectomy specimens (embedded in tissue microarrays, TMAs) from 483 patients treated in three Canadian institutions between 1993 and 2013. The main measures were the presence or absence of IDC-P and of PC, regardless of the clinical outcomes. Most of the 483 patients were pT2 stage (44–69%), and pT3a (22–49%) was more frequent than pT3b (9–12%). After approval of the construction of the TMAs by local ethics review board, the diagnostic accuracy study was approved by the Centre hospitalier de l'Université de Montréal (CHUM) ethics review board. Briefly, two consecutive sections of each TMA block were cut. The first section was transferred onto a glass slide to perform immunohistochemistry with H&E counterstaining for cell identification. The second section was placed on an aluminum slide, dewaxed, and then used to acquire an average of 7 Raman spectra per specimen (between 4 and 24 Raman spectra, 4 acquisitions / TMA core). Raman spectra of each cell type were then analyzed to retrieve tissue-specific molecular information and to generate classification models using machine learning technology. <span>Models were trained and cross-validated using data from one institution. Accuracy, sensitivity and specificity were respectively of 87 ± 5%, 86 ± 6% and 89 ± 8% to differentiate PC from benign tissue, and of 95 ± 2%, 96 ± 4% and 94 ± 2% respectively to differentiate IDC-P from PC. The trained models were then tested on data from two independent institutions, reaching accuracies, sensitivities and specificities of 84 and 86%, 84 and 87%, and 81 and 82%, respectively</span><span> to diagnose PC, and of 85 and 91%, 85 and 88%, and 86 and 93% respectively for the identification of IDC-P.</span> IDC-P could further be differentiated from high-grade prostatic intraepithelial neoplasia (HGPIN), a pre-malignant intraductal proliferation which can be mistaken as IDC-P, with accuracies, sensitivities and specificities >95% in both training and testing cohorts. As we used stringent criteria to diagnose IDC-P, the main limitation of our study is the exclusion of borderline, difficult to classify lesions from our datasets.</p> <p class="AbstractSummary"><b>Conclusions</b></p> <p>In this study, we developed classification models for the analysis of Raman micro-spectroscopy data to differentiate IDC-P, PC and benign tissue, including HGPIN. Raman micro-spectroscopy could be a next-generation histopathological technique used to <span>reinforce the identification of high-risk PC patients and lead to more precise diagnosis of IDC-P.</span></p>
EMPA, temperature-dependent Raman, FTIR data and breakdown temperature of phlogopite
<p>This dataset contains all new data corresponding to figures in the manuscript and the supporting information, including EMPA, temperature-dependent FTIR, Raman data, and breakdown temperature from previous studies and this study.</p>
EMPA, temperature-dependent Raman, FTIR data and breakdown temperature of phlogopite
<p>This dataset contains all new data corresponding to figures in the manuscript and the supporting information, including EMPA, temperature-dependent FTIR, Raman data, and breakdown temperature from previous studies and this study.</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.