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814 results for “Time Analysis”
Pulsations and eclipse-time analysis of HW Vir
<p>MESA inlist associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2018MNRAS.481.2721B">Pulsations and eclipse-time analysis of HW Vir</a></p>
Experimental data of "Analysis of battery-like and pseudocapacitive ion intercalation kinetics via distribution of relaxation times"
<p><span>Improving the kinetics of electrochemical ion intercalation processes is of interest for realizing high-power electrochemical energy storage. This includes classical battery-like intercalation and pseudocapacitive intercalation processes with a capacitor-like electrochemical signature. Electrochemical methods are needed to probe the kinetics of such complex multistep processes in detail. Here, we present the use of the Distribution of Relaxation Times (DRT) analysis of electrochemical impedance data to identify the kinetic limits of intercalation reactions. We study the lithium intercalation reaction in TiS<sub>2 </sub>from organic and aqueous electrolytes as a model system. The material can exhibit both battery-like and pseudocapacitive intercalation regimes depending on the potential range, variable diffusion lengths by adjusting its particle size, and a tunable degree of solvent cointercalation by choosing the electrolyte solvent. Using DRT, we can distinguish between the kinetic limitations imposed by solid-state ion diffusion, interfacial ion adsorption and transport, and ion desolvation processes. Thus, DRT analysis can complement existing methods, such as voltammetry or 3D-Bode analysis, to better understand the kinetics of intercalation reactions</span>.</p>
Figure 2 in Phylogenetic analysis and a time tree for a large drosophilid data set (Diptera: Drosophilidae)
Figure 2. Phylogenetic tree showing the reconstructed ancestral geographical distributions for extant and ancestral drosophilids estimated by the maximum-likelihood algorithm. Extant geographical distributions were retrieved from the Drosophila Stock Center or from the ZipcodeZoo database. See Table S2 for geographical distributions.
Figure 1 in Phylogenetic analysis and a time tree for a large drosophilid data set (Diptera: Drosophilidae)
Figure 1. Timescale for drosophilids based on a maximum-likelihood (ML) analysis using a concatenated alignment (9917 bp) of six protein-coding nuclear genes. Several monophyletic branches have been collapsed, indicating that all taxa within that taxonomic rank form a cluster. Support values above branches are bootstrap proportions performed on the ML tree; values less than 50 are not shown.
Attack time analysis in dynamic attack trees via integer linear programming
<p>Code and data corresponding to the paper "Attack time analysis in dynamic attack trees via integer linear programming"</p>
Time Dependent Analysis of Rat Microglial Markers in Traumatic Brain Injury Reveals Dynamics of Distinct Cell Subpopulations
<p>The repository contains seven zip files for flow cytometry data for rat microglia following Controlled cortical impact (CCI) collected at seven time points: 3 hours, 1 day, 2 days, 7 days 14 days, 21 days and 28 days.</p> <p>Each file contains 24 CSV files converted from the raw fcs file and text files that contain meta data about the file.</p> <p>Each file name depicts the information of whether it is Panel A (M1 in the file name) or Panel B (M2 in the file name) measurement and whether the measurement was conducted on the ipsilateral (ipsi) or contralateral (contra) side of the CCI, or sham conducted on the ipsilateral (ipsi) or contralateral (contra) sides.</p> <p>Below is the description of the columns of each file:</p> <table> <tbody> <tr> <td> <p><strong>File column name</strong></p> </td> <td> <p><strong>Original name</strong></p> </td> <td> <p><strong>Panel A (M1) context</strong></p> </td> <td> <p><strong>PAnel B (M2) context</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>F0</p> </td> <td> <p>FSC-A</p> </td> <td> <p>FSC-A</p> </td> <td> <p>FSC-A</p> </td> <td> <p>Forward scattering Area</p> </td> </tr> <tr> <td> <p>F1</p> </td> <td> <p>FSC-H</p> </td> <td> <p>FSC-H</p> </td> <td> <p>FSC-H</p> </td> <td> <p>Forward scattering Height</p> </td> </tr> <tr> <td> <p>F2</p> </td> <td> <p>FSC-W</p> </td> <td> <p>FSC-W</p> </td> <td> <p>FSC-W</p> </td> <td> <p>Forward scattering Width</p> </td> </tr> <tr> <td> <p>F3</p> </td> <td> <p>SSC-A</p> </td> <td> <p>SSC-A</p> </td> <td> <p>SSC-A</p> </td> <td> <p>Side scattering area</p> </td> </tr> <tr> <td> <p>F4</p> </td> <td> <p>FITC-A</p> </td> <td> <p>FITC-A</p> </td> <td> <p>FITC-A</p> </td> <td> <p>Fluorescein isothiocyanate</p> </td> </tr> <tr> <td> <p>F5</p> </td> <td> <p>PE-A</p> </td> <td> <p>CD32</p> </td> <td> <p>CD200R</p> </td> <td> <p>Protein expression</p> </td> </tr> <tr> <td> <p>F6</p> </td> <td> <p>PerCP-Cy5-5-A</p> </td> <td> <p>-</p> </td> <td> <p>CD163</p> </td> <td> <p>Protein expression</p> </td> </tr> <tr> <td> <p>F7</p> </td> <td> <p>PE-Cy7-A</p> </td> <td> <p>CD11</p> </td> <td> <p>CD11</p> </td> <td> <p>Protein expression</p> </td> </tr> <tr> <td> <p>F8</p> </td> <td> <p>BV421-A</p> </td> <td> <p>P2Y12</p> </td> <td> <p>P2Y12</p> </td> <td> <p>Protein expression</p> </td> </tr> <tr> <td> <p>F9</p> </td> <td> <p>BV510-A</p> </td> <td> <p>-</p> </td> <td> <p>-</p> </td> <td> <p>Dye </p> </td> </tr> <tr> <td> <p>F10</p> </td> <td> <p>Alexa Fluor 647-A</p> </td> <td> <p>CD86</p> </td> <td> <p>RT1B</p> </td> <td> <p>Protein expression</p> </td> </tr> <tr> <td> <p>F11</p> </td> <td> <p>APC-Cy7-A</p> </td> <td> <p>CD45</p> </td> <td> <p>CD45</p> </td> <td> <p>Protein expression</p> </td> </tr> <tr> <td> <p>F12</p> </td> <td> <p>Event Time</p> </td> <td> <p>Event Time</p> </td> <td> <p>Event Time</p> </td> <td>Event Time</td> </tr> </tbody> </table>
Experimental Data for: Machine learning enabled image analysis of time-temperature sensing colloidal arrays
<p>This dataset contains images of colloidal arrays functioning as time-temperature integrating, autonomous sensors. Each image shows a sensor consisting of multiple colloidal crystals with varying compositions of particles with different glass transition temperatures. Details on the composition and manufacturing procedures are explained in the corresponding publication. The data is organized into folders with different temperature setpoints. For each temperature, we investigated 10 samples. The name of the samples corresponds to their creation date. The name of the image files corresponds to their acquisition time. The first image in each sample folder was taken at the very start of the heating period. Hence, the heating time can be calculated by subtracting the start time from the acquisition time.</p>
Table 7. Results of calculation of epithelialization time statistics one-way analysis of variance (ANOVA) with SPSS 23.00
<p>Table 7. Results of calculation of epithelialization time statistics one-way analysis of variance (ANOVA) with SPSS 23.00</p>
Fig. 2 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 2. Workflow for sample preparation and injection. Culture samples were filtered and dried (A–B). Dried filter papers were placed in clean vials (C) and then resuspended in methanol (D) before being extracted with Chloroform (E). Water was added (F) and subsequently, the chloroform layer was aliquotted into GC vials (G) for further sample preparation. Extracts were dried (H) and then derivatized using a two-step methoximation/silylation process to yield derivatized extracts (I). 9-μL aliquots of derivatized extracts were automatically transferred to microvial inserts in thermal desorption tubes for injection (J) using an initial solvent vent step to remove excess solvent and derivatisation reagents (K), followed by thermal desorption to a cooled PTV inlet and subsequent splitless injection to the GC × GC-TOFMS system. Non-volatile residues from the extracts remained in the microvial insert for subsequent disposal (L). See text for details.
Fig. 4 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 4. From left to right: results of principal component analysis of the raw data (autoscaled), similarly scaled data normalised to class-specific TUPA, and the normalised, scaled data using the selected features from the FS-CR routine. Quality control samples were not included in the feature selection routine, and are displayed as filled icons connected to their corresponding replicate with a straight line, following projection into the optimised principal component space. Confidence ellipses were drawn about each sample class for a confidence interval of 0.95. Note the convention: DUN refers to D. tertiolecta samples, CO refers to co-culture samples, and BAC refers to P. italicus R11 samples.
FIGURE 2 in Divergence time analysis of the Neotropical wasp genus Protopolybia Ducke, 1905 (Vespidae, Polistinae, Epiponini) using a Multilocus Phylogenetic Approach
FIGURE 2. Chronogram of the Bayesian analysis and the divergence times for the Protopolybia species inferred from the relaxed molecular clock approach, based on the three mitochondrial markers and one nuclear locus sequenced in the present study. The numbers above the nodes represent the mean time in millions of years (Ma). The different clades are color-coded as follows: green = P. picteti-emortualis, red = P. chartergoides, blue = P. exigua, and yellow = P. sedula.
FIGURE 1 in Divergence time analysis of the Neotropical wasp genus Protopolybia Ducke, 1905 (Vespidae, Polistinae, Epiponini) using a Multilocus Phylogenetic Approach
FIGURE 1. Topology of the Bayesian Inference (BI) tree for the species of the genus Protopolybia based on a data matrix that includes sequences of three mitochondrial markers (16S rRNA, 12S rRNA, and COI) and one nuclear locus (28S rRNA). The numbers above the branches indicate the a posteriori probability (BI) and the bootstrap (ML) values. Bootstrap values lower than 50% were omitted (-). The different clades are color-coded as follows: green = P. picteti-emortualis, red = P. chartergoides, blue = P. exigua, and yellow = P. sedula.
Time-based Register and Analysis of COPD Endpoints
ClinicalTrials.gov study NCT03485690. IPD Sharing: NO. Countries: 1. Publications: 2.
Frozen Blastocyst Transfer Using Conventional Timing Versus Timing by Endometrial Receptivity Analysis
ClinicalTrials.gov study NCT03558399. IPD Sharing: NO. Countries: 1. Publications: 7.
Recognition of Early Pulmonary Structural Changes by Using Real-time High Fidelity Expiratory CO2 Analysis
ClinicalTrials.gov study NCT05092035. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Analysis of the Time Taken to Triple Therapy (NOVARTIS)
ClinicalTrials.gov study NCT01786720. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Temporal and Kinematic Analysis of Timed Up and Go Test in Chronic Low Back Pain Patients
ClinicalTrials.gov study NCT04588155. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Analysis of Biological Progression and Regression of HELLP Syndrome in Time
ClinicalTrials.gov study NCT06758960. IPD Sharing: YES. Countries: 1. Publications: 2.
Analysis of Risk in MDS Over Time - Comparison of Treated vs Untreated Patients
ClinicalTrials.gov study NCT04676945. IPD Sharing: NO. Countries: 1. Publications: 7.
Analysis of Trends Over Time of Hepatitis Related Incidence in Panama
ClinicalTrials.gov study NCT01159951. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.