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482 results for “Digital data”
Nimbus High Resolution Infrared Radiometer Remapped Digital Data Daily L3, GeoTIFF V001
This data set (NmHRIR3G) consists of daily composites constructed from Nimbus 1, Nimbus 2, and Nimbus 3 satellites High Resolution Infrared Radiometer (HRIR) data for the region between 60 N and 60 S. Measurements were obtained during 1964, 1966, and 1969. Data are available as GeoTIFFs and browse images. For the HDF5 formatted version of these data, see the <a href="http://dx.doi.org/10.5067/NIMBUS/NmHRIR3H">Nimbus High Resolution Infrared Radiometer Remapped Digital Data Daily L3, HDF5</a> data set.
PSP FIELDS Digital Fields Board (DFB) AC-coupled Searchcoil Magnetometer, SCM, Spectra, Low Frequency, High Gain, f-component, Sensor coordinates, Level 2 (L2), 0.873813 s Data
PSP FIELDS Digital Fields Board, DFB, SCMflfhg data:The DFB is the low frequency, less than 75 kHz, component of the FIELDS experiment on the Parker Solar Probe spacecraft, see reference [1] below. For a full description of the FIELDS experiment, see reference [2]. For a description of the DFB, see reference [3].DFB AC spectra data consist of power spectral densities as a function of frequency and time. These spectra are averaged over both frequency and time as described in [3]. The spectra have pseudo-logarithmically spaced frequency bins with the bin central frequencies reported in the metadata. The AC spectra are duty-cycled such that spectral averaging takes place over the first 1/8 of any given NYsecond when the data cadence is equal to one NYsecond. Less data are averaged by a factor of 2^N for data cadences that are faster than one NYsecond by 2^N. For cadences slower than one NYsecond, the first 1/8 of each NYsecond of data included are averaged together to construct the reported data.The Level 2 data products contained in this data file have been calibrated for:* 1) The Hanning window used in the spectral calculation* 2) DFB in-band gain* 3) DFB analog filter gain response* 4) DFB digital filter gain response* 5) The search coil preamplifier response, when applicable* 6) The bandwidth of each spectral binNote that compensation for the DFB digital filters will introduce a non-physical positively sloped power trend at high frequencies when the non-corrected signal is dominated by noise. This effect should be examined carefully when determining spectral slopes and features at the highest frequencies. Calibrations for the FIELDS preamplifiers have not been implemented as the preamplifier response is flat and equal to one through the DFB frequency range. Corrections for plasma sheath impedance gain and antenna effective length have not been applied to voltage sensor signals. These corrections will be applied in the Level 3 DFB data products. Therefore, all voltage sensor quantities when present in these Level 2 data products are expressed by using units of Volts squared per Hertz. Likewise, all magnetic field quantities when present in these Level 2 data product are expressed by using units of nanoTesla squared per Hertz.The Level 2 data products contained in this data file are expressed in sensor coordinates: e.g. dV12, dV34 for voltage measurements. For solar orbits 1 and 2, the search coil magnetometer spectral data are rotated into a non-intuitive coordinate system with components [d,e,f]. For solar orbits 3 and beyond, the magnetic field spectral data are in expressed in search coil magnetometer sensor coordinates with components [u,v,w].To rotate from [d,e,f] coordinates into [u,v,w] search coil sensor coordinates, use the following matrix, written in IDL notation, and the following equation: spectra_uvw_vector = R ## spectra_def_vector.R = [[ 0.46834856, -0.81336422 , 0.34509170] [ -0.66921924, -0.071546954, 0.73961249] [ -0.57688408, -0.57733845 , -0.57782790]]The time resolution of the DFB AC spectral data can vary by multiples of 2^N. During encounter when PSP is within 0.25 AU of the Sun, the DFB AC spectra data cadence is typically NYsecond NYsecond [2]. Timestamps correspond to the center time of each window.References:* 1) Fox, N.J., Velli, M.C., Bale, S.D. et al., Space Sci Rev (2016) 204:7. https://doi.org/10.1007/s1121401502116* 2) Bale, S.D., Goetz, K., Harvey, P.R. et al., Space Sci Rev (2016) 204:49. https://doi.org/10.1007/s1121401602445* 3) Malaspina, D.M., Ergun, R.E., Bolton, M. et al., JGR Space Physics (2016), 121, 5088-5096. https://doi.org/10.1002/2016JA022344
Nimbus Temperature-Humidity Infrared Radiometer 6.7 µm Water Vapor Remapped Digital Data Daily L3, HDF5 V001
This data set (NmTHIR67-3H) consists of daily, global composites of radiative temperatures measured in the 6.7 µm water vapor window (6.5 µm - 7.0 µm) by the Temperature-Humidity Infrared Radiometer (THIR) onboard the Nimbus 4 satellite. The composites were constructed from Nimbus 4 THIR <a href="http://nsidc.org/data/nmthir67-1h/">swath data</a> and show water vapor distribution in the upper troposphere and stratosphere.
PSP FIELDS Digital Fields Board (DFB) DC-coupled Searchcoil Magnetometer, SCM, Bandpass filtered, Low Frequency, High Gain, v-component, Sensor coordinates, Level 2 (L2), 0.873813 s Data
PSP FIELDS Digital Fields Board, DFB, SCMvlfhg data:The DFB is the low frequency, less than 75 kHz, component of the FIELDS experiment on the Parker Solar Probe spacecraft, see reference [1] below. For a full description of the FIELDS experiment, see reference [2]. For a description of the DFB, see reference [3].DFB DC bandpass data consist of peak and average values of the absolute value of bandpassed time series waveform data over a time interval equal to the reporting cadence. The DC bandpass data have the peak response frequency of each bin reported in the metadata. The frequency response curves for these bins are given in [3].The Level 2 data products contained in this data file have been calibrated for:* 1) The ~6.3 dB loss associated with forming the bandpass signal, see reference [3]* 2) DFB in-band gain* 3) The search coil preamplifier response, when applicable* 4) DFB digital filter time delays, the DFB filter time delays become significant in the lowest frequency DC bandpass binsCalibrations for the DFB digital filter gains and analog filter gains have not been implemented as it was determined that these could not be applied accurately to single numerical values representing a broadband signal response and because all bins except the highest frequency bin have a flat gain response equal to one due to these filters. Calibrations for the FIELDS preamplifiers have not been implemented as the preamplifier response is flat and equal to one through the DFB frequency range. Corrections for plasma sheath impedance gain and antenna effective length have not been applied to voltage sensor signals. These corrections will be applied in the Level 3 DFB data products. Therefore, all voltage sensor quantities when present in these Level 2 data products are expressed by using units of Volts. Likewise, all magnetic field quantities when present in these Level 2 data products are expressed by using units of nanoTelsas.The Level 2 data products contained in this data file are expressed in sensor coordinates: e.g. dV12, dV34 for voltage measurements and [u,v,w] for the searchcoil magnetometer.The time resolution of the DFB DC bandpass filtered data can vary by multiples of 2^N. During encounter when PSP is within 0.25 AU of the Sun, the DFB DC bandpass filtered data cadence is typically 1 NYsecond [2]. Timestamps correspond to the center time of each window.References:* 1) Fox, N.J., Velli, M.C., Bale, S.D. et al., Space Sci Rev (2016) 204:7. https://doi.org/10.1007/s1121401502116* 2) Bale, S.D., Goetz, K., Harvey, P.R. et al., Space Sci Rev (2016) 204:49. https://doi.org/10.1007/s1121401602445* 3) Malaspina, D.M., Ergun, R.E., Bolton, M. et al., JGR Space Physics (2016), 121, 5088-5096. https://doi.org/10.1002/2016JA022344
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_SW1783_batchF
GEO Series GSE245911. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_SW1783_batchA
GEO Series GSE245896. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HT29_batchE
GEO Series GSE244693. Homo sapiens. 33 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_SW1783_batchE
GEO Series GSE245910. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HepG2_batchB
GEO Series GSE244703. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_SW1783_batchB
GEO Series GSE245898. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_A549_batchA
GEO Series GSE244682. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_A549_batchB
GEO Series GSE244683. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HepG2_batchD
GEO Series GSE244705. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HT29_batchD
GEO Series GSE244692. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Expression data of e13.5 Sox-GFP forming digit, e14.5 Lgr5-GFP+ interzone and e14.5 GFP- surrounding tissues in digit
GEO Series GSE110281. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HT29_batchA
GEO Series GSE244689. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HepG2_batchE
GEO Series GSE244706. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_HepG2_batchA
GEO Series GSE244702. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_SW1783_batchC
GEO Series GSE245903. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using tonifying herbal medicine-induced transcriptome sequencing_A549_batchE
GEO Series GSE244686. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
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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)
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.