Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
13
datasets available to search
ShareScore release 0.9.0
Dataset results
13 results for “frequency transfer”
Simulation data for "Characteristics of Wave-Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping" which will be submitted to Journal of Geophysical Research: Space Physics
<p>Simulation data for "Characteristics of Wave-Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping" which will be submitted to Journal of Geophysical Research: Space Physics.</p> <p>Including the simulation input parameter file and the necessary output data to plot each figure in the article. </p>
Supplement to "On the accuracy of RTTOV-SCATT for radiative transfer at all-sky microwave and submillimeter frequencies"
<p>This supplement contains a set of realistic cloudy and precipitating conditions from the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the corresponding simulated brightness temperatures for the journal article “On the accuracy of RTTOV-SCATT for radiative transfer at all-sky microwave and submillimeter frequencies”, which is under review at the Journal of Quantitative Spectroscopy and Radiative Transfer. These data are available as benchmark for model developers.</p> <p>The IFS profiles correspond to model data interpolated (using the IFS observation operator) to the locations of the Atmospheric Infrared Sounder (AIRS) for a 12 h period centred on 03 UTC on 1 November 2018. Note that only a subset of the full set of AIRS locations are supplied here. The IFS model version cycle 46r1 was used, in a research experiment, to generate these profiles. The model was configured to T1279co resolution (about 8-9 km) with 137 levels in the vertical. The forecast was initialized from operational analyses at 18 UTC on 31 October 2018, and hence corresponds to the 12 h forecast "background" used in the data assimilation cycle.</p> <p>The following information concerns only the IFS model data:</p> <ul> <li>Copyright statement: Copyright "© 2022 European Centre for Medium-Range Weather Forecasts (ECMWF)".</li> <li>Source: www.ecmwf.int.</li> <li>Disclaimer: ECMWF does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use.</li> <li>Licence Statement: This data is published under a Creative Commons Attribution 4.0 International (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/.</li> <li>Further information on the ECMWF data policy, and guidance on how to comply with it, is at https://apps.ecmwf.int/datasets/licences/general/.</li> </ul> <p>The simulated brightness temperatures are also distributed under Creative Commons Attribution 4.0 International (CC BY 4.0).</p> <p>The full journal description of this dataset is currently under review, with the current citation:</p> <p>Barlakas, V., Galligani, V. S., Geer, A. J., Eriksson, P., 2022. On the accuracy of RTTOV-SCATT for radiative transfer at all-sky microwave and submillimeter frequencies. Submitted to Journal of Quantitative Spectroscopy and Radiative Transfer.</p> <p>The work of Vasileios Barlakas at Chalmers University of Technology is funded by a EUMETSAT fellowship program.</p>
Antiviral activity of HIV-1 integrase strand-transfer inhibitors against mutants with integrase resistance-associated mutations and their frequency in treatment-naïve individuals
<p>The development of resistance to human immunodeficiency virus 1 (HIV-1) integrase strand-transfer inhibitors (INSTI) has been documented; however, knowledge of the impact of pre-existing integrase (IN) mutations on INSTI resistance (INSTI-R) is still evolving. The frequency of HIV-1 IN mutations in 2177 treatment-naïve subjects was investigated, along with the INSTI susceptibility of site-directed mutant viruses containing major and minor INSTI-R mutations. Total 6 of 39 minor INSTI-R mutations (M50I, S119P/G/T/R, and E157Q) were found in >1% of IN-treatment-naïve subjects with no impact on INSTI susceptibility. When each combined with major INSTI-R mutation, M50I, S119P, and E157Q led to decreased susceptibility to elvitegravir but remained sensitive to dolutegravir and bictegravir.</p>
Dataset underlying publication "Optical-comb-based frequency stability transfer across the spectrum with a multi-channel FPGA
<p>This archive contains datasets underlying plots of the publication "Optical-comb-based frequency stability transfer across the spectrum with a multi-channel FPGA".</p> <p>Datasets contain header, and a minimum script to reproduce figures is provided</p> <p>This work was supported by the European Metrology Program for Innovation and Research (EMPIR), Project 20FUN08 Nextlasers, which<br>received funding from the EMPIR programme cofinanced by the Participating States and from the European Union’s Horizon 2020 research and innovation program. </p>
Data for: Both Conifer II and Gnetales are characterized by a high frequency of ancient mitochondrial gene transfer to the nuclear genome
<p><strong>Background:</strong> Mitochondrial gene transfer/loss is common in land plants, and therefore the fate of missing mitochondrial genes has attracted more and more attention. The gene content of gymnosperm mitochondria varies greatly, supplying a system for studying the evolutionary fate of missing mitochondrial genes.</p> <p><strong>Results:</strong> Here we studied the tempo and pattern of mitochondrial gene loss/transfer in gymnosperms represented by all 13 families, using high-throughput sequencing of both DNA and cDNA. All 41 mitochondrial protein-coding genes were found in cycads, <em>Ginkgo</em> and Pinaceae, whereas multiple mitochondrial genes were absent in Conifer II and Gnetales. In Conifer II, gene transfer from mitochondria to the nucleus followed by loss of the mitochondrial copy was common, but complete loss of a gene in both mitochondrial and nuclear genomes was rare. In contrast, both gene transfer and loss were commonly found in Gnetales. Notably, in Conifer II and Gnetales, the same five mitochondrial genes were transferred to the nuclear genome, and these gene transfer events occurred, respectively, in ancestors of the two lineages. A two-step transfer mechanism (retroprocessing and subsequent DNA-mediated gene transfer) may be responsible for mitochondrial gene transfer in Conifer II and Gnetales. Moreover, the mitochondrial gene content variation is correlated with gene length, GC content, hydrophobicity, and nucleotide substitution rates in land plants.</p> <p><strong>Conclusions: </strong>This study reveals a complete evolutionary scenario for mitochondrial genes of gymnosperms and the factors responsible for mitochondrial gene content variation in land plants.</p>
Data for: Both Conifer II and Gnetales are characterized by a high frequency of ancient mitochondrial gene transfer to the nuclear genome
Open the record for dataset details and reuse information.
Data from: Sharpening coarse-to-fine stereo vision by perceptual learning: asymmetric transfer across the spatial frequency spectrum
Neurons in the early visual cortex are finely tuned to different low-level visual features, forming a multi-channel system analysing the visual image formed on the retina in a parallel manner. However, little is known about the potential 'cross-talk' among these channels. Here, we systematically investigated whether stereoacuity, over a large range of target spatial frequencies, can be enhanced by perceptual learning. Using narrow-band visual stimuli, we found that practice with coarse (low spatial frequency) targets substantially improves performance, and that the improvement spreads from coarse to fine (high spatial frequency) three-dimensional perception, generalizing broadly across untrained spatial frequencies and orientations. Notably, we observed an asymmetric transfer of learning across the spatial frequency spectrum. The bandwidth of transfer was broader when training was at a high spatial frequency than at a low spatial frequency. Stereoacuity training is most beneficial when trained with fine targets. This broad transfer of stereoacuity learning contrasts with the highly specific learning reported for other basic visual functions. We also revealed strategies to boost learning outcomes 'beyond-the-plateau'. Our investigations contribute to understanding the functional properties of the network subserving stereovision. The ability to generalize may provide a key principle for restoring impaired binocular vision in clinical situations.
Nextlasers WP4 - FPGA control for comb-assisted frequency transfer
<p>This dataset contains the VHDL and Matlab code developed in Nextlasers WP4 - frequency transfer using a comb</p> <p> </p> <p>This work was partly supported by the European Metrology Program for Innovation and Research (EMPIR), Project 20FUN08 NextLasers, which received funding from the EMPIR programme cofinanced by the Participating States and from the European Union's Horizon 2020 research and innovation program. </p> <p> </p>
Data from: Sharpening coarse-to-fine stereo vision by perceptual learning: asymmetric transfer across the spatial frequency spectrum
Open the record for dataset details and reuse information.
Comparison of Uterine Peristaltic Wave Frequencies Between Pregnant and Non-pregnant Women in Embryo Transfer Cycles
ClinicalTrials.gov study NCT03587246. IPD Sharing: NO. Countries: 1. Publications: 0.
Alexithymia Frequency and Interhemispheric Transfer in Patients With a First Demyelinating Event
ClinicalTrials.gov study NCT03796247. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Defective transfer of parental histone decreases frequency of homologous recombination in budding yeast
GEO Series GSE240331. Saccharomyces cerevisiae. 92 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
Data set for "Stability limitations of optical frequency transfer in telecommunication DWDM networks"
<p>Here we share the relevant data of the manuscript “Stability limitations of optical frequency transfer in telecommunication DWDM networks”.</p> <p>The files:</p> <ul> <li>“fig_2a_total.txt”</li> <li>“fig_2a_diff.txt”</li> </ul> <p>contains respectively the timeseries data of phase fluctuations of total delay and differential delay between two fibers in 50 km-long soil-deployed cable. Same results for 110 km-long aerial cable are in files:</p> <ul> <li>“fig_2b_total.txt”</li> <li>“fig_2b_diff.txt”</li> </ul> <p>The files:</p> <ul> <li>“fig_3_aerial_MDEV_points.txt”</li> <li>“fig_3_soil_MDEV_points.txt”</li> </ul> <p>contains respectively points of modify Allan deviation of the differential delay fluctuations in 110 km-long aerial and 70 km-long soil-deployed cable. For short averaging the stability is limited by the noise of time interval counter (MTC 108). Before MDEV calculations the differential delay fluctuations was divided by factor of two, as a half of these fluctuations is present at the output of a stabilized system.</p> <p>The files:</p> <ul> <li>“fig_4_soil_MDEV_points_CW-total.txt”</li> <li>“fig_4_soil_MDEV_points_CW-diff.txt”</li> </ul> <p>contains respectively points of modify Allan deviation of the total and differential delay fluctuations in 70km soil-deployed cable, measured with the unmodulated coherent optical carrier.</p> <p>The files:</p> <ul> <li>“fig_7a_EDFA_phase.txt” and “fig_7a_EDFA_temp.txt”</li> <li>“fig_7b_Raman_phase.txt” and “fig_7b_Raman_temp.txt”</li> <li>“fig_7c_ROADM_phase.txt” and “fig_7c_ROADM_temp.txt”</li> </ul> <p>contains the timeseries data of simultaneous measurement of phase and temperature changes in individual cards (modules) of the DWDM system: EDFA amplifier, card containing the Raman module, as well as ROADM (Reconfigurable Optical Add Drop Multiplexer) module.</p> <p>Time series data of the fluctuations of the total and differential propagation delay of the signal transfer in the unmodified DWDM system (over 1500 km long route) include files:</p> <ul> <li>“fig_9_total_phase_fluct_part1”, “fig_9_total_phase_fluct_part2”, “fig_9_total_phase_fluct_part1” </li> <li>“fig_9_diff_phase_fluct_part1”, “fig_9_diff_phase_fluct_part2”, “fig_9_diff_phase_fluct_part3”</li> </ul> <p>The files:</p> <ul> <li>“fig_10_mdev_acusticNOISE.txt”</li> <li>“fig_10_mdev_air-conditioning_ON.txt”</li> <li>“fig_10_mdev_air-conditioning_MODIFIED.txt”</li> </ul> <p>contains points of modify Allan deviation that shows respectively: the influence of acoustic noise, stability of the frequency transfer in DWDM network in the case of sub-optimal (asymmetric) cooling within a single ILA node, while the last file shows the stability of the transfer after optimizing the airflow within this node.</p> <ul> </ul>
ScienceDex guides
Understand access before you commit
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.