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545 results for “synchronization”
Raw data for "Fluorescence crosstalk reduction by modulated excitation-synchronous acquisition for multispectral analysis in high-throughput droplet microfluidics."
<p>Raw data to quantify the crosstalk reduction and signal resolution improvement by MESA used in Figure 3 and 4.</p> <p><br> </p>
Code and data related to semi-synchronous growth changes and the similarity of tree-ring patterns
<p>This dataset contains the data and code related to Visser, RM. 2021 On the similarity of tree-ring patterns: Assessing the influence of semi-synchronous growth changes on the Gleichläufigkeitskoeffizient for big tree-ring data sets. <em>Archaeometry 63(1)</em>: 204–215. DOI: <a href="https://doi.org/10.1111/arcm.12600">https://doi.org/10.1111/arcm.12600</a>.</p>
Synchronously recorded gait kinematic data with Inertial Measurement Units and a photogrammetry system for a validation assessment
<h3>Description</h3> <p>A gait database of 32 healthy adult subjects was built , volunteers were between 20 and 63 y.o. (33.64 ± 12.44) and 71.88% were females. Every individual underwent a barefoot walking test recorded simultaneously with Inertial Measurement Units (IMUs) and the photogrammetry system Vicon. The dataset contains the kinematic gait information of the hip, knee, and ankle joints in the three planes of motion: sagittal, frontal, and transversal. </p> <p>The signals recorded by the IMUs are referred to as I(t) and were captured with a sampling frequency of 50 Hz, and those recorded by the photogrammetry system are called V(t) and were captured with a sampling frequency of 100 Hz. To perform a comparative study of both systems, the V(t) signals must be resampled to 50 Hz. Then, the delay between the two signals must be corrected to align them. Finally, gait cycles can be extracted for each pair of trials following the data information provided, obtaining a pair of waveforms for each gait cycle [I(t), V(t)]. A total of 268 synchronous gait cycles [I(t), V(t)] can be recovered and analyzed in the three planes of motion per limb.</p> <h3>Data information</h3> <ul> <li><em>raw_data</em>: folder containing the 32 subjects raw kinematic signals recorded with IMUs (sampling frequency 50 Hz) and photogrammetry system (sampling frequency 100 Hz) synchronously.<br> <ul> <li>For IMUs records: <ul> <li>Z: sagittal plane.</li> <li>X: frontal plane.</li> <li>Y: transversal plane.</li> </ul> </li> <li>For photogrammetry system records: <ul> <li>X: sagittal plane.</li> <li>Y: frontal plane.</li> <li>Z: transversal plane.</li> </ul> </li> </ul> </li> </ul> <ul> <li><em>captures_information.xlsx</em>: table containing the delay correction and the samples corresponding to the events of the gait cycles. The delay correction is the number of samples for which each photogrammetry signal V(t), after being resampled to 50 Hz, must be moved to be completely aligned with its synchronous IMUs signal couple I(t). <ul> <li>If the delay is positive (+) the V(t) signal must be delayed by adding zeros at the beginning.</li> <li>If the delay is negative (-) the V(t) signal must be moved forward by removing zeros at the beginning.</li> </ul> </li> </ul>
Dataset and software for "Optimizing beat synchronized running to music"
<p>These are the dataset and Matlab scripts that were used for analysis as described in the publication on "<strong>Optimizing beat synchronized running to music"</strong></p>
Data set for "Measuring synchronization and anticipation between individual investors from their daily performance"
<p>The data stored here is used as a support of the paper "Measuring<br> synchronization and anticipation between individual investors from their<br> daily performance" where a measure based on Mutual Information and<br> Transfer of Entropy is used in order to map investors' behaviour and which<br> ones are following same behavioural patterns.</p> <p>The study linked to this data is published on pre-print Arxiv.org<br> with the following citation:</p> <p><br> Mario Gutiérrez-Roig, Javier Borge-Holthoeffer, Alex Arenas and<br> Josep Perelló. Measuring synchronization and anticipation between<br> individual investors from their daily performance (2018)</p>
Synchronous generator experimental data (voltage, current and rotor position data)
<p>This database is composed of stator voltages and currents, field voltage and rotor position of a three-phase synchronous generator under resistive load. The data were acquired by means of two Tektronix MSO 2014B oscilloscopes with 4 channels each. Data were collected on 8 channels corresponding to phase voltages (Va,Vb,Vc), phase currents (Ia,Ib,Ic), field current of the generator (Ifd) and a pulse signal for angular position reference of the rotor (theta_m). For the simultaneous collection of the signals, a trip circuit was designed and implemented, the output of which was used as the triggering signal for the oscilloscopes. The synchronous generator was connected to a synchronous motor (Y-Y) and to a resistive circuit (18 units of 40W lamps) which served as loads. Voltage data were collected by means of a Keysight N2791 voltage probes; current data were collected using Tektronix A622 current tips. An PHCT203 optical key was used to collect rotor position pulse signal. The generator model is MOTROM M610-75-B-1K8-GS of 0.5 cv, 1800 rpm, 4 poles. The generator parameters obtained by means of physical bench tests were:</p> <p>Rs = 32.5 ohms (stator winding resistance)</p> <p>Rfd = 358.9 ohms (field winding resistance)</p> <p>Ld = 0.803H (direct axis stator inductance)</p> <p>Lq = 0.691H (quadrature axis stator inductance)</p> <p>Lls = 0.12H (stator winding leakage inductance)</p> <p>Lfd = 2.23H (field winding inductance)</p> <p>Vf = 64V (field voltage applied during the experiment, supplied by an regulated DC source)</p> <p> </p> <p>The database is composed by the following files of preprocessed data sampled at 10kHz in which the following variables are given, respectively, time, Va, Vb, Vc, Theta_r, Ia, Ib, Ic:</p> <p>1) data0001.txt</p> <p>2) data0002.txt</p> <p>3) data0003.txt</p> <p>4) data0001.csv</p> <p>5) data0002.csv</p> <p>6) data0003.csv</p> <p> </p> <p>Further, the database contains the following files of raw data:</p> <p>1) T0001A.txt</p> <p>2) T0001B.txt</p> <p>3) T0002A.txt</p> <p>4) T0002B.txt</p> <p>5) T0003A.txt</p> <p>6) T0003B.txt</p> <p>Each realization is contained in two files (suffixes A,B) and contain:</p> <p>Suffix A</p> <p>time</p> <p>CH1 (Va)</p> <p>CH1_peak (Va peak)</p> <p>CH2 (Vb)</p> <p>CH2_peak (Vb peak)</p> <p>CH3 (Vc)</p> <p>CH3_peak (Vc peak)</p> <p>CH4 (Theta_r)</p> <p>CH4_peak (Theta_r peak)</p> <p> </p> <p>Suffix B</p> <p>time</p> <p>CH1 (Ia)</p> <p>CH1_peak (Ia peak)</p> <p>CH2 (Ib)</p> <p>CH2_peak (Ib peak)</p> <p>CH3 (Ic)</p> <p>CH3_peak (Ic peak)</p> <p>CH4 (EMPTY)</p> <p>CH4_peak (EMPTY)</p> <p> </p> <p>When using the raw data, it is important to consider that the values were acquired in the following conditions:</p> <p>- Voltage probe scale: 100:1</p> <p>- Current probe scale: 100mV/A</p> <p>- Oscilloscope probe scale: 10x<br> <br> - Oscilloscope configuration: check header of raw files.</p> <p> </p> <p>Contact information: jose.grzybowski@uffs.edu.br</p>
Seed based phase synchronization data
<p>The aim of this research was to investigate how fear predicts the phase synchronization of regions within the brain, and how fear affects the synchronization of functional connectivity between individuals.</p> <p>Participants viewed one of two horror movies in the fMRI scanner (The Conjuring 2 or Insidious). A separate sample of participants viewed the movies and provided continuous measures of experience fear.</p> <p>Seed-based phase synchronization (SBPS): The phase synchronization between each of 116 region pairs of the AAL atlas was computed and correlated with the fear ratings. The result matrix of the correlation coefficients reveal the extent to which fear predicts phase synchronization between regions.</p> <p>Inter-subject phase synchronization (ISBPS): The phase synchronization of the SBPS was conducted between individuals and correlated with the fear ratings. The result matrix of the correlation coefficients reveal the extent to which fear predicts between-individual synchronization of regional phase synchronization.</p>
GPS-synchronized recordings of 5 MHz during October 2, 2024 eclipse from Tortel, Aysén, Chile
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Optomechanical Synchronization across Multi-Octave Frequency Spans
<p>Supplementary data for the article "Optomechanical Synchronization across Multi-Octave Frequency Spans". ArXiv: https://arxiv.org/abs/2105.01791v2</p> <p> </p> <p> </p>
RoboFinch: a versatile audio-visual synchronized robotic bird model for laboratory and field research on songbirds
<p>Raw data and R script for the behavioral data published in the Journal Methods in Ecology and Evolution with the title: RoboFinch: a versatile audio-visual synchronized robotic bird model for laboratory and field research on songbirds</p> <p>All data and source files for the RoboFinch construction can be found here: https://doi.org/10.5281/zenodo.7520589</p> <p> </p>
Spatially Resolved Transcriptomics Deconvolutes Prognostic Histological Subgroups in Patients with Colorectal Cancer and Synchronous Liver Metastases
<p>Spatial transcriptomic data (counts.csv) derived using the Nanostring GeoMx digital spatial profiler platform to analyse matched colonic primary and liver metastases from 4 patients with metastatic colorectal cancer. 48 AOIs of cancer transcriptome atlas data. Normalised using Q3 normalisation. In addition, normalised data (Counts - ncounter.csv) from ncounter bulk experiment comparing matched colonic primary and liver metastases</p>
Moonlight synchronous flights across three western palearctic swifts mirror size dependent prey preferences
<p><strong>Abstract</strong></p> <p>Recent studies have suggested the presence of moonlight mediated behaviour in avian aerial insectivores, such as swifts. At the same time swift species also show differences in prey (size) preferences. Here, we use the combined analysis of state-of-the-art activity logger data across three swift species, the Common, Pallid and Alpine swifts, to quantify flight height and activity responses to crepuscular and nocturnal light conditions. Our results show a significant response in flight heights to moonlight illuminance for Common and Pallid swifts, while a moonlight driven response is absent in Alpine swifts. Swift flight responses followed the size dependent altitude gradient of their insect prey. We show a weak relationship between night-time illuminance driven responses and twilight ascending behaviour, suggesting a decoupling of both crepuscular and night-time behaviour. We suggest that swifts optimise their flight behaviour to adapt to favourable night-time light conditions, driven by light responsive and size-dependent vertical insect stratification and weather conditions.</p> <blockquote> <p>You are required to cite both the Zenodo data repository as well as the BioRXiv pre-print when using this data, as:</p> <p>Hufkens et al. 2023. Moonlight synchronous flights across three western palearctic swifts mirror size dependent prey preferences. doi://10.5281/zenodo.7814214</p> <p>Hufkens et al. 2023. Moonlight synchronous flights across three western palearctic swifts mirror size dependent prey preferences. bioRxiv 2023.04.25.538243; doi: https://doi.org/10.1101/2023.04.25.538243</p> </blockquote> <p><strong>Use</strong></p> <p>This is a deposited version of the releases on Github.</p> <p>Either download this Zenodo repository or clone or download the project Github <a href="https://github.com/bluegreen-labs/swift_lunar_synchrony/archive/refs/heads/main.zip">zip file</a>.</p> <pre><code class="language-bash">git clone https://github.com/bluegreen-labs/swift_lunar_synchrony.git</code></pre> <p>Unzip the downloaded data if required. The repository is an `R` project and can be opened in <a href="https://posit.co/download/rstudio-desktop/">RStudio</a>, which will set the correct relative path.</p> <p><strong>Data structure & analysis</strong></p> <p>Analysis data is saved as compressed R serial files (.rds) in the <a href="https://github.com/bluegreen-labs/swift_lunar_synchrony/tree/main/data">`data` folder</a>. Scripts to reproduce the main statistical results are provided in the <a href="https://github.com/bluegreen-labs/swift_lunar_synchrony/tree/main/analysis">`analysis` folder</a>. A matching render of the analysis using the shared data is provided as <a href="http://bluegreen-labs.github.io/swift_lunar_synchrony/">dynamic webpage</a>.</p> <p><strong>Licensing</strong></p> <p>Be mindful of the CC-BY 4.0 license of the data and figures. Reuse is permitted on the condition of proper attribution and documentation of any changes.</p>
"Presenting Euroqcharm project outcomes to foster global database synchronization" Zoom Webinar video recording
<p>Video recording of the "Presenting Euroqcharm project outcomes to foster global database synchronization" Zoom Webinar</p>
Dataset for "Synchronous multi-segmental activity between metachronal waves controls locomotion speed in Drosophila larvae"
<p>Dataset for publication "Synchronous multi-segmental activity between metachronal waves controls locomotion speed in Drosophila larvae". </p>
Data set for the article "Synchronous replication initiation of multiple origins"
<p>This data set contains the data of the submitted article "Synchronous replication initiation of multiple origins". The data was generated using simulations in python that are linked below. Experiments indicate that E. coli initiates DNA replication at multiple origins synchronously in fast growth conditions. We study by mathematical modelling under what conditions replication is initiated synchronously.</p>
Demonstrator of a rotor-fed asynchronous start for a Salient Pole Wound Field Synchronous Machine
<p>The video shows the asynchronous run-up (up to ca. 620 rpm) of a four pole, 60 kVA, 400V, 50 Hz salient pole synchronous generator. The run-up is obtained by AC-supplying a special rotor winding arrangement, capable of both exciting the machine at synchronism and providing a multiphase rotating MMF during the run-up. The armature phases, which have two parallel current paths, are conveniently short-circuited during the rotor acceleration. </p>
Experimental Database of deterministic wave prediction built from synchronous measurements from an X-band pulse radar and met-ocean sensors deployed on the Floatgen floating wind turbine and its vicinity on SEM-REV test site.
<p>This dataset is a deliverable of the FLOATECH project, funded under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101007142.<br> The aim of this dataset is a result of the field experiments carried out at the Floatgen FOWT located at the SEM-REV test site.</p>
Data from: Coincident development and synchronization of sleep-dependent delta in the cortex and medulla
<p>In early development, active sleep is the predominant sleep state before it is supplanted by quiet sleep. In rats, the developmental increase in quiet sleep is accompanied by the sudden emergence of the cortical delta rhythm (0.5-4 Hz) around postnatal day 12 (P12). We sought to explain the emergence of cortical delta by assessing developmental changes in the activity of the parafacial zone (PZ), a medullary structure thought to regulate quiet sleep in adults. We recorded from PZ in P10 and P12 rats and predicted an age-related increase in neural activity during increasing periods of delta-rich cortical activity. Instead, during quiet sleep we discovered sleep-dependent rhythmic spiking activity—with intervening periods of total silence—phase-locked to a local delta rhythm. Moreover, PZ and cortical delta were coherent at P12, but not at P10. PZ delta was also phase-locked to respiration, suggesting sleep-dependent modulation of PZ activity by respiratory pacemakers in the ventral medulla. Disconnecting the main olfactory bulbs from the cortex did not diminish cortical delta, indicating that the influence of respiration on delta at this age is not mediated indirectly through nasal breathing. Finally, we observed an increase in parvalbumin-expressing terminals in PZ across these ages, supporting a role for local GABAergic inhibition in PZ's rhythmicity. The unexpected discovery of delta-rhythmic neural activity in the medulla—when cortical delta is also emerging—provides a new perspective on the brainstem's role in regulating sleep and promoting long-range functional connectivity in early development.</p>
Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations
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Mitigation of urbanisation effects on aquatic ecosystems by synchronous ecological restoration
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