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389 results for “Lifetime”
Dataset to manuscript Excitation's lifetime extracted from electron-photon (EELS-CL) nanosecond-scale temporal coincidences
<p>The datasets provided are raw data after the initial electron-photon temporal lists have been analyzed to determine the electron-photon pairs and their temporal delay. These lists are too long and not very meaningful to be provided in full.</p><p>The datasets were analyzed with the following Python libraries: Numpy 1.23.5, Matplotlib 3.6.2, Scipy 1.10.0, Hyperspy 1.7.3.</p><p>The provided jupyter notebooks were used to generate the figures in the manuscript.</p>
Data for "Heat treatment and fiber drawing effect on the matrix structure and fluorescence lifetime of Er- and Tm-doped silica optical fibers"
<p>Includes data for absorption and attenuation measurements and calculations, profiles of refractive index and concentrations, TEM images, XRD patters, and data for fluorescence decay curves presented in the graphs.</p>
data and codes for paper "Deriving mobility-lifetime products in halide perovskite films from spectrally- and time-resolved photoluminescence"
<p>These are the data and Matlab codes used in the paper "Deriving mobility-lifetime products in halide perovskite films from spectrally- and time-resolved photoluminescence".</p>
Fluorescence lifetime imaging of pH along the secretory pathway
<p>Many cellular processes are dependent on correct pH levels, and this is especially important for the secretory pathway. Defects in pH homeostasis in distinct organelles cause a wide range of diseases, including disorders of glycosylation and lysosomal storage diseases. Ratiometric imaging of the pH-sensitive mutant of green fluorescent protein (GFP), pHLuorin, has allowed for targeted pH measurements in various organelles, but the required sequential image acquisition is intrinsically slow and therefore the temporal resolution unsuitable to follow the rapid transit of cargo between organelles. We therefore applied fluorescence lifetime imaging microscopy (FLIM) to measure intraorganellar pH with just a single excitation wavelength. We first validated this method by confirming the pH in multiple compartments along the secretory pathway. Then, we analyze the dynamic pH changes within cells treated with Brefeldin A, a COPI coat inhibitor. Finally, we followed the pH changes of newly-synthesized molecules of the inflammatory cytokine tumor necrosis factor (TNF)-α while it was in transit from the endoplasmic reticulum via the Golgi to the plasma membrane. The toolbox we present here can be applied to measure intracellular pH with high spatial and temporal resolution, and can be used to assess organellar pH in disease models.</p>
Figures and datasets of paper titled "Bulk carrier lifetime surpassing 600 us in Upgraded Metallurgical-grade Silicon multicrystalline wafers after Phosphorus Diffusion Gettering"
<p>Datasets and figures of paper titled "Figures and datasets of paper titled "Bulk carrier lifetime surpassing 600 us in Upgraded Metallurgical-grade Silicon multicrystalline wafers after Phosphorus Diffusion Gettering" published in arXiv (<a href="https://arxiv.org/abs/2111.13522">https://arxiv.org/abs/2111.13522</a>).</p>
Accurate In Vivo Nanothermometry through NIR-II Lanthanide Luminescence Lifetime
<p>Dataset of https://zenodo.org/record/5805844#.YcmOK2jMJPY</p>
Dataset from paper "Weathering of plastic SODIS containers and the impact of ageing on their lifetime and disinfection efficacy"
<ul> <li>Evolution of the molar mass distribution curves for the samples of both polypropylenes for each time of weathering.</li> <li>Evolution of the Differential Scanning Calorimetry (DSC) curves for the first melting for both polypropylenes.</li> </ul>
Honeybee lifetime tracking data 2018
<p>Data from barcode-based tracking of honeybees during summer of 2018, taken in an observation hive located at University of Konstanz, Germany.</p> <p>Associated GitHub repository: <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2018data">https://github.com/jacobdavidson/bees_lifetimetracking_2018data</a></p> <p>Data usage example is on <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2018data/blob/main/Data%20usage%20example.ipynb">Github</a>, or can be run in a browser with <a href="https://mybinder.org/v2/gh/jacobdavidson/bees_lifetimetracking_2018data/HEAD?labpath=Data%20usage%20example.ipynb">Binder</a></p> <p><strong>File contents: </strong></p> <p><strong><a href="https://zenodo.org/record/6045860/files/2018_Quantity_Descriptions.xlsx?download=1">2018_Quantity_Descriptions.xlsx</a></strong></p> <p>List and description of quantities contained in the single-day summary metrics, and the metrics calculated at shorter intervals (hour, 5 minute, 1 minute). Also lists day number definitions, and cohort birthdates.</p> <p><strong><a href="https://zenodo.org/record/6045860/files/beetrajectories_days_000_to_049.zip?download=1">beetrajectories_days_000_to_049.zip</a>, <a href="https://zenodo.org/record/6045860/files/beetrajectories_days_050_to_085.zip?download=1">beetrajectories_days_050_to_085.zip</a></strong></p> <p>Single-day hdf files, each containing x-y trajectory data in the form:</p> <table> <thead> <tr> <th>daynum</th> <th>framenum</th> <th>uid</th> <th>x</th> <th>y</th> <th>camera</th> <th>theta</th> </tr> </thead> </table> <ul> <li>daynum: the day number of the observation period. See 'Day numbers and cohorts' sheet in 2018_Quantity_Descriptions.xlsx</li> <li>framenum: using the camera frame rate of 3fps, the frame number with respect to that particular day</li> <li>uid: the Unique ID of each bee</li> <li>x,y: pixel coordinate values of each bee. Conversion is 80 pixels/cm</li> <li>camera: which camera the bee was detected on: 0=exit side (with dance floor - shown at right in comb map images), 1=back side (show at left in comb map images)</li> <li>theta: orientation of the bee in the hive </li> </ul> <p><strong><a href="https://zenodo.org/record/6045860/files/comb-contents2018.zip?download=1">comb-contents2018.zip</a></strong></p> <p>Comb content color-coded png image files, as well as pkl files for using the comb data type (see <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2018data/blob/main/Data%20usage%20example.ipynb">Data Usage Example</a>)</p> <p><strong><a href="https://zenodo.org/record/6045860/files/daydatamat.csv?download=1">daydatamat.csv</a></strong></p> <p>Summary behavioral metrics calculated for each tracked bee on each day of the experiment. See 2018_Quantity_Descriptions.xlsx for full list and detail of quantities. Data is in the form:</p> <table> <thead> <tr> <th>Age</th> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th><metric1></th> <th><metric2></th> <th>...</th> </tr> </thead> </table> <p><strong><a href="https://zenodo.org/record/6045860/files/df_day1min_alldays.zip?download=1">df_day1min_alldays.zip</a>, <a href="https://zenodo.org/record/6045860/files/df_day5min_alldays.zip?download=1">df_day5min_alldays.zip</a>, <a href="https://zenodo.org/record/6045860/files/df_dayhour_alldays.zip?download=1">df_dayhour_alldays.zip</a> </strong></p> <p>Behavioral metrics calculated over different time intervals: 1 minute, 5 minute, or 1 hour divisions. See 2018_Quantity_Descriptions.xlsx for full list and detail of quantities. Files are organized as a single .hdf file for each day. Each file contains data in the form:</p> <p>Per-hour data:</p> <table> <thead> <tr> <th>Age</th> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th>Hour</th> <th><metric1></th> <th><metric2></th> <th>...</th> </tr> </thead> </table> <p>5-minute or 1-minute data: </p> <table> <thead> <tr> <th>Age</th> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th>timedivision</th> <th><metric1></th> <th><metric2></th> <th>...</th> </tr> </thead> </table> <p><strong> <a href="https://zenodo.org/record/6045860/files/dfxy_dayhour_alldays.zip?download=1">dfxy_dayhour_alldays.zip</a></strong></p> <p>x-y histogram data, calculated by using a 2cmx2cm grid and binning for each hour of each day. One file per day, and each file contains data in the form:</p> <table> <thead> <tr> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th>Hour</th> <th>hist0</th> <th>hist1</th> <th>...</th> <th>hist1434</th> </tr> </thead> </table> <p>Convert the flattened histogram structure into a shape of [41,35] in order to view as shown in the paper or in the <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2018data/blob/main/Data%20usage%20example.ipynb">Data Usage Example</a></p>
From structural phase transition to highly sensitive lifetime based luminescent thermometer: multifaceted modification of thermometric performance in Y0.9xNdxYb0.1PO4 nanocrystals
<p>The development of a highly sensitive luminescent thermometer requires a deep understanding of the correlation between the structural properties of the host material and the temperature-dependent luminescence properties of lanthanide emitters embedded in these matrices. In some cases, the presence or increased concentration of the co-dopant ions can alter not only the spectral features, but may additionally cause far-ranging structural changes that further, even more tremendously, modify the luminescence properties of the phosphor. In this work, the temperature dependent luminescence kinetics in response to structural changes induced by increasing Nd<sup>3+</sup> ion doping in Y<sub>0.9−<em>x</em></sub>Nd<sub><em>x</em></sub>Yb<sub>0.1</sub>PO<sub>4</sub> nanocrystals are investigated, which correspondingly demonstrated phase transitions from xenotime to monazite structures. Consequently, the low temperature lifetime of the <sup>2</sup>F<sub>5/2</sub> state of Yb<sup>3+</sup> elongates. Moreover, by increasing the Nd<sup>3+</sup> amount, the relative sensitivity of the Yb<sup>3+</sup> luminescence lifetime-based luminescent thermometer was enhanced and, simultaneously, the temperature at which high sensitivity is achieved was reduced. The maximal relative sensitivity was found to be 2%/K at 273 K for Nd<sub>0.9</sub>Yb<sub>0.1</sub>PO<sub>4</sub> nanocrystals.</p>
Data for 'Confined vacuum resonances as artificial atoms with tunable lifetime'
<p>This folder contains all the raw data needed to generate the figures in the paper '<em>Confined vacuum resonances as artificial<br> atoms with tunable lifetime</em><em>.</em>' The data are seperated by the figures in which they appear, with a text folder in each folder that contains any relevant additional information. </p>
Comprehensive database of fluorescence lifetime values for fluorochromes with emission peaks in the visible or near infrared
<p>Multiplexing techniques rely on fluorescent probes to simultaneously detect and visualise multiple mRNA or protein molecules in a single cell. Although more than 1200 fluorochromes are available in the visible and near-infrared spectral range, it is difficult to separate the different fluorochromes spectrally into orthogonal channels as their excitation and emission spectra often overlap. Fluorescence lifetimes can be used as an effective method to segregate fluorochromes for multiplex imaging. However, information on fluorescence lifetimes is not always easy to find as it is often only mentioned in passing on websites or in publications. In an effort to overcome this challenge, we performed a systematic literature review to make it easier to access the information required to attempt unmixing fluorochromes by fluorescence lifetime for multiplexed imaging. We found that at least 88 fluorochromes can be used, in principle, to attempt unmixing fluorochromes by lifetime and thus multiplexing. Our data are summarised in a table as well as in a graph in which we plotted the lifetime (tau) against the emission peak (Em). For all fluorochromes, we found that are available as NHS derivatives for easy coupling to DNA oligonucleotides or antibodies. Some additional, potentially very useful fluorophores, for which no lifetime data are available, are shown within a dashed line in a relatively “sparse” region of the spectrum above 800nm. A key is displayed to describe the colour code used to represent different fluorochrome classes, such as Alexa Fluor.</p>
Dataset: Phytoplankton Cell-States: multiparameter lifetime flow monitoring reveals cellular heterogeneity
<h1>Dataset for Multiparameter-based photosynthetic state transitions of single phytoplankton cells data.</h1> <h2>Creating environment</h2> <p>yaml and spec file are provided of the conda environment used. Most packages are typical, with the key exception of fretbursts</p> <p>A custom/development version of fretbursts was used, which contains support for more flexible photon selection (Ph_sel) objects, necessary for the larger parameter space. This version is in the polarization branch of harripd fork of fretbursts. The simple route to install is </p> <p><code>pip install git+https://https://github.com/harripd/FRETBursts@polarization</code></p> <p>however, if you want to ensure the exact same version is installed use:</p> <p><code>pip install git+https://github.com/harripd/FRETBursts@12a5168</code></p> <h2>Data organization</h2> <p>All zip files are meant to be unziped into the same destination folder (ie if a file is in a folder in the zip file, it should be in a subfolder inside the shared highest level folder, but if two files inside different zip folders are in the root of their respective zip files, they should be places in the same folder when all files are unzipped.</p> <p>After unzipping everything your folder for this article should contain the following items (normal text indicates file, <strong>bold text indicates folder</strong>).</p> <ol> <li>Flow_PhytoCellStates_figures.ipynb</li> <li><strong>mpAlgae</strong></li> <li><strong>figures</strong></li> <li>20230905_cyanoWH8102_diurnal</li> <li>20230707_cyanolightjump</li> <li>20230609_ppurp</li> <li>20230724_redalgaelightjump</li> <li>20231211_pmicans_6umol_diurnal</li> <li><strong>20231217_pmicans_6umol_lightjump</strong></li> <li><strong>20231019_WH8102_imaging</strong></li> <li><strong>bulk_cyano_lightjump</strong></li> <li>synWH8102_di_REPO_20230905.hdf5</li> <li>synWH8102_di_REPO_20230905.csv</li> <li>synWH8102_lj_REPO_20230707.hdf5</li> <li>synWH8102_lj_REPO_20230707.csv</li> <li>ppurp_di_REPO_20230609.hdf5</li> <li>ppurp_di_REPO_20230609.csv</li> <li>ppurp_lj_REPO_20230724.hdf5</li> <li>ppurp_lj_REPO_20230724.csv</li> <li>pmicans_di_REPO_20231211.hdf5</li> <li>pmicans_di_REPO_20231211.csv</li> <li>ppurp_lj_REPO_20230724.hdf5</li> <li>ppurp_lj_REPO_20230724.csv</li> </ol> <p>Flow_API_all.ipynb (item 1) is the jupyter notebook that analyses the data and produces the figures. It relies on having mpAlgae (item 2) in the same folder, as it contains the underlying code that adapts FRETBurts to work with the cell based data, adding functionality to combine multiple data files into one experiment, dynamic gating of data, storing calculated values to disk, which also reduces the memory requirements of the system, as well as a number of advanced plotting functions. Flow_API_all.ipynb also expects a figures folder (item 3) to exist so that it can save the produced figures. It also expects items 4-9 to exist, as those folder names are recorded as where the different raw data sets are stored. Even numbered items 12-22 (all items 12-23 that are hdf5 files) are produced by Flow_API_all.ipynb, and are where processed values of burst search are stored. the mpAlgae api makes it so that if these files are present, burst search is skipped, and instead loaded from these result files. Thus if you desire to examine the data, you only need the top level hdf5 files. These files also save results of histogram fittings, so that results can be loaded instead of recalculatd. </p> <p>The csv files are export of calculated parameters to csv format. Note that these are ungated, and thus proper gating must be implemented if plots are to be recapitulated from these files, this is done so that alternative gating strategies can also be explored.</p> <p> </p>
Overtone Transition 2ν1 of HCO+ and HOC+: Origin, Radiative Lifetime, Collisional Quenching
<p>Dataset and post processing scripts used in the ChemPhysChem paper entitled:</p> <p>"""Overtone Transition 2\nu_1 of HCO+^ and HOC^+: Origin, Radiative Lifetime, Collisional Quenching"""</p> <p>DOI: <a href="https://doi.org/10.1002/cphc.202400106">10.1002/cphc.202400106 </a></p>
Data for "Nanoparticle doping and molten-core methods towards highly thulium-doped silica fibers for 0.79 μm-pumped 2 μm fiber lasers – a fluorescence lifetime study"
<p>Includes data for basic characterization of the fibers (concentration profiles from EMPA, refractive index profiles of the preforms and fibers, attenuation of the fibers), as well as the measured fluorescence decay curves.</p>
Intermittent reproduction, mortality patterns and lifetime breeding frequency of females in a population of the adder (Vipera berus)
<p>Raw data used in paper by Dirk Bauwens & Katja Claus. 2019. Intermittent reproduction, mortality patterns and lifetime breeding frequency of females in a population of the adder (Vipera berus). PeerJ, DOI 10.7717/peerj.6912</p> <p>CH_data_AdultFemaleAdders.INP</p> <p>A text file with extension .INP for input in the program MARK (White & Burnham, 1999; Cooch & White, 2015)), containing the capture-recapture histories, including breeding status of individual adult female adders (n = 908). Each 18-digit string contains a 1-digit score (B/N/0 ; Breeding / Non-breeding / not captured) per year of study (2000 – 2017).</p> <p>SVL_BCI_RawData.xlsx</p> <p>Excell-file containing data for SVL, mass, BCI (body condition index) and breeding status (breeding/non-breeding) for individual females captured and measured during spring (March – half May; i.e., before ovulation) or late summer (August-September; i.e. after parturition or at end of activity season).</p> <p> </p>
Li1.8Na0.2TiO3:Mn4+: the highly sensitive probe for the low-temperature lifetime-based luminescence thermometry
<p>Dataset accompanying figures published in the publication <a href="https://zenodo.org/record/3552659">https://zenodo.org/record/3552659</a>.</p> <p> </p>
Real‐time fiber‐based fluorescence lifetime imaging with synchronous external illumination: A new path for clinical translation
<p>Time-correlated single photon counting is the “gold-standard” method for fluorescence lifetime measurements and has demonstrated potential for clinical deployment. Its clinical adoption is hindered by the use of high gain detectors, which make the fluorescence acquisition impractical with bright lighting conditions such as in clinical settings. We address this limitation by interleaving periodic fluorescence detection with synchronous out-of-phase externally modulated light source, thus guaranteeing specimen illumination and a fluorescence signal free from bright background light upon temporal separation. Fluorescence lifetime maps are generated in real-time from single-point measurements by tracking a reference beam and using the phasor approach. We demonstrate the feasibility and practicality of this technique in a number of biological specimens, including real-time mapping of degraded articular cartilage. This method is compatible and can be integrated with existing clinical microscopic, endoscopic and robotic modalities, thus offering a new pathway towards label-free diagnostics and surgical guidance in a number of clinical applications.</p>
Characterization of Patient Activation Among Childhood Cancer Survivors in the St. Jude Lifetime Cohort (SJLIFE)
<p>This dataset corresponds to a manuscript titled "Characterization of Patient Activation Among Childhood Cancer Survivors in the St. Jude Lifetime Cohort (SJLIFE) which can be found in the journal <em>Cancers.</em></p>
Experimental and simulated data for the article "Reassessing the role and lifetime of Qx in the energy transfer dynamics of Chlorophyll a"
<p>The .zip file contains:</p> <ul> <li>Linear absorption spectra of Chl a in EtOH, acetone, and benzonitrile (BN)</li> <li>Low-temperature emission and excitation anisotropy datasets of Chl a in isopropanol</li> <li>Transient absorption (TA) datasets of Chl a in EtOH, acetone, and BN after B- and Q-band excitation (including pump spectra)</li> <li>Transient absorption anisotropy (TAA) datasets of Chl a in acetone after B-band excitation (including a pump spectrum)</li> <li>Optimized geometries for the Q-band ESA calculations</li> <li><span>Geometries for normal modes used for PES construction</span></li> </ul>
Data for: Sub-tropical aerosols enhance tropical cloudiness – a remote aerosol-cloud lifetime effect
This data-set contains the data requires for the paper "Sub-tropical aerosols enhance tropical cloudiness – a remote aerosol-cloud lifetime effect" by Guy Dagan The variables containing *mean* in their name present time-average over the last 4-days of the simulations.
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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.
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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.