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17 results for “PSD”
Lake Tahoe Particle size distribution (PSD) Profile data
Profiles of particle size distribution (PSD) taken at Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details
Lake Tahoe particle size distribution (PSD) data for discrete water samples
Particle size distribution data measured on discrete water samples from Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 5. PSD (dB/Hz) vs freaquency (Hz) of each IMF showen in fig 4 in channel C4 (a) and in C3 (b)
<p> In Fig 5, we noted that ocular artifact frequency is generally low around 5Hz with high amplitude. This artifact appears mainly in IMF3 and IMF4. Finally, band power was applied for the new signal. As a last step, the logarithm of the BP is calculated in order to transform the distribution of this feature to a more Gaussian like shape, because the classifiers we used, such as HMMs and SVM assume normally distributed features.</p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 5b. PSD (dB/Hz) vs freaquency (Hz) of each IMF showen in fig 4 in channel C4 (a) and in C3 (b)
<p>Therefore, the new signal is reconstructed by keeping only the two first IMFs. EMD also allows eliminating the artifacts in the EEG during the recording sessions like eye blinks and eyeball movements. In Fig 5, we noted that ocular artifact frequency is generally low around 5Hz with high amplitude. This artifact appears mainly in IMF3 and IMF4. Finally, band power was applied for the new signal. As a last step, the logarithm of the BP is calculated in order to transform the distribution of this feature to a more Gaussian like shape, because the classifiers we used, such as HMMs and SVM assume normally distributed features.</p>
BRAIN Journal-Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed-Figure 5. SSVEP detection accuracies by using PSD, CV and VS features
<p>When the results in Figure 5 are analyzed, it is seen that CV and VS features provide detection results similar to PSD, which is a familiar feature. Considering that the chance level is 12.5% in these dataset, CV and VS can be used as discriminative features for SSVEP. Also on some subjects, like S3 on 1st and 4th datasets, and S11 on 1st, 2nd and 4th datasets, the proposed features have given clearly better detection results than PSD.</p>
PDF and PSD files of DiapixGEtv picture materials – German version adapted to elicit tense vowels
<p>This zipped folder contains PDF and PSD files of our translation of the DiapixUK picture materials by Baker & Hazan (2011) - adapted to elicit tense vowels in German (DiapixGEtv).</p> <p>For our purpose we only modified the written information when making adjustments to the original DiapixUK versions of the files. Our aim was to include as many tense vowels [i:, e:, a:, o:, u:] as possible while remaining subtle enough so as not to alert the participants to our research focus . The additional documentation contains information on the translation process and an overview over the adapted text parts containing target vowels in stressed syllables including the target word with its target vowel and pronunciation as well as its meaning in English.</p> <p>In order to facilitate further adaptation/modification each item in the PSD files is in a separate layer.</p> <p>Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1412, 416591334</p>
Fuzzy Supertertiary Interactions within PSD-95 Enable Ligand Binding
<p>This file details the folder structure for the data files provided corresponding to the experiments and analysis performed in <em>Fuzzy Supertertiary Interactions within PSD-95 Enable Ligand Binding</em>. Correction parameters, results, and methods are detailed in the manuscript. The file “Sample Reference.xlsx” details the naming conventions for different FRET labeling site variants. “RefitDistanceTables.xlsx” provides the distances for all global fits of subsets of samples performed for classification of DMD structures.</p> <p> </p> <p>The .zip file "PDBDev_adtl_Datasets.zip" Contains additional files corresponding to submissions of structures from the corresponding manuscript to wwPDB-Dev.</p> <table> <tbody> <tr> <td>Folder</td> <td> </td> </tr> <tr> <td><strong>1. Single Molecule Experimental Data</strong></td> <td>.ht3 and .ptu files corresponding to time-tagged photon records collected using single-photon detectors with Hydra Harp TCSPC software and hardware. Folders are provided for each sample. Selection criteria and correction parameters are detailed in the manuscript. DO data were taken from bursts with S<sub>PIE</sub><0.1 while AO data were S<sub>PIE</sub>>0.9.</td> </tr> <tr> <td>1.1 BG</td> <td>Background files from which background signals were calculated for each sample. Subfolder for each sample.</td> </tr> <tr> <td>1.2 IRF</td> <td>IRF data files used for generation of IRF curves for fluorescence decay histogram analysis and generation of fFCS filters. Subfolder for each sample.</td> </tr> <tr> <td><strong>Fluorescence Decay Histograms</strong></td> <td>Data files for photon counts in each time bin following donor excitation pulse for Donor-only (DO), FRET (DA), and Instrument Response Function (IRF) curves used in fluorescence decay histogram analysis.</td> </tr> <tr> <td>2.1 Fit Curves</td> <td>Curves fit to decay histograms, in xyxy format (time delay after pulse, fit curve counts, time, residual)</td> </tr> <tr> <td><strong>Filtered FCS Curves and Filter Files</strong></td> <td>Data corresponding to four fFCS curves per sample: low-FRET-high-FRET (lohi), high-FRET-low-FRET (hilo), low-FRET-low-FRET (lolo), and high-FRET-high-FRET (hihi), as well as filter files generated in the Kristine software package using the .ht3 and .ptu data and IRF files from <strong>Single Molecule Experimental Data</strong>.</td> </tr> <tr> <td>3.1 Fits</td> <td>Fit curves and residuals for all samples. .cor files are simple text files in xy format (third column unused). .res, .fit files follow likewise.</td> </tr> <tr> <td><strong>Simulation AV-Derived Distance Values</strong></td> <td>Structures from DMD simulations and AV-derived interdye distances used for structural classification against experimental FRET data. Also includes references files for associating distances correctly with structures and FRET pairs.</td> </tr> <tr> <td>4.1 CoM AV Contours and PCA Data</td> <td>Files contain AV-derived distance information for all simulation structures from DMD, in compact npy format loadable via numpy.load. The text files contain center-of-mass positions in xyz format for the indicated domains.</td> </tr> <tr> <td><strong>5. MFD Histograms</strong></td> <td>Contains text files for MFD contour plot data, as well as FRET line equations for each sample. Text files are in matrix representation, with the first row and column being the x/y axis values and all internal values representing a 2D bin.</td> </tr> <tr> <td><strong>6. PDA Histograms</strong></td> <td>Contains time-binned histograms of smFRET data and modeling outputs from PDA fitting.</td> </tr> </tbody> </table> <p> </p>
Effects and Central Mechanism of Electroacupuncture and MRI-navigated rTMS for PSD
ClinicalTrials.gov study NCT05516680. IPD Sharing: YES. Countries: 1. Publications: 1.
ElectroSense PSD Spectrum Dataset
<p>This is the dataset used in the paper A. Scalingi, D. Giustiniano, R. Calvo-Palomino, N. Apostolakis, G. Bovet, <em>"A Framework for Spectrum Classification using Crowdsensing Platforms"</em>. For each site, we collect 6 hours of the full spectrum scan, the RTL-SDR sweeps the full spectrum from 24 MHz to 1.7 GHz hopping over the frequencies with chunks of 2MHz of bandwidth. Then specific spectrum portions of the licence bands are filtered to label the dataset. The NumPy files then contain PSD data of licensed frequency bands e.g. FM Bands.</p> <p>The folders inside spectrum_bands.tar.gz are organized per each site and we publish the spectrum portions already labeled.</p> <p>Please cite our work if you use our dataset:</p> <pre><code> @INPROCEEDINGS{10228867, author={Scalingi, Alessio and Giustiniano, Domenico and Calvo-Palomino, Roberto and Apostolakis, Nikolaos and Bovet, Gérôme}, booktitle={IEEE INFOCOM 2023 - IEEE Conference on Computer Communications}, title={A Framework for Wireless Technology Classification using Crowdsensing Platforms}, year={2023}, volume={}, number={}, pages={1-10}, doi={10.1109/INFOCOM53939.2023.10228867} url=}</code></pre> <p> </p>
Peri-Strips Dry (PSD) Veritas Collagen Matrix Staple Line Reinforcement for Colorectal Surgery
ClinicalTrials.gov study NCT00559013. IPD Sharing: Not stated. Countries: 1. Publications: 0.
SBI for PSM and PSD
ClinicalTrials.gov study NCT06923384. IPD Sharing: NO. Countries: 1. Publications: 0.
Reinforcement of Surgical Staple Lines Using Peri-Strips Dry (PSD) With Veritas Collagen Matrix
ClinicalTrials.gov study NCT00566943. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Targeting postsynaptic glutamate receptor scaffolding proteins PSD-95 and PICK1 for obesity treatment
GEO Series GSE221549. Mus musculus. 47 samples. Type: Expression profiling by high throughput sequencing.
Targeting postsynaptic glutamate receptor scaffolding proteins PSD-95 and PICK1 for obesity treatment [2]
GEO Series GSE251836. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
PSD-based fingerprinting - dataset
<p>Signals and algorithm results for the article "A PSD-based fingerprint approach for IoT devices" submitted for PRDC2020. All the data inside this dataset is anonymised.</p>
PSD Microscopy Data
<p>These are the Matlab file data used in the PSD Microscopy paper.</p>
PSD
<p>Original dataset: <a href="https://doi.org/10.18112/openneuro.ds003944.v1.0.1">doi:10.18112/openneuro.ds003944.v1.0.1</a></p>
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Allen Brain Atlas
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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.