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85 results for “characterization method”
Characterization of TiO2/Fe2O3 nanocomposites prepared via impregnation-calcination method
<p>The link contains XRD, SEM-EDX, UV-DRS, PL, Electrochemical measurements of the prepared TiO<sub>2</sub>/Fe<sub>2</sub>O<sub>3</sub> photocatalyst</p>
Generated WSP: Validation of a water-sensitive paper-based method for the characterization of agricultural spray droplets
<p>Synthetic images were generated in a Python environment using the OpenCV library to replicate the distribution of droplets in WSP. The images display droplet stains represented by blue circles (255,0,0) on a yellow background (0,255,255) to enhance contrast and enable more precise analysis. The synthetic images were created in two distinct resolutions, namely 640x480 and 2560x1440 pixels, with the aim of reproducing the output of two specific digital microscopes: the Jiusion 640x480 and the Jiusion HD 2560x1440 (Shenzen, China). The resolution is chosen based on the expected practical application, ensuring that any image analysis algorithm developed can effectively process images with similar characteristics to those obtained under real conditions by these microscopes. Each pixel in this configuration corresponds to a physical size of 18.125 µm in images with a resolution of 640x480, and a size of 6.875 µm in images with a resolution of 2560x1440. Multiple patterns were created to simulate various configurations of droplet stains in WSP. The sizes of single droplet stains varied between 100 and 600 µm, with spacings of either 1000 µm or 2000 µm between drops (see attached figure). Furthermore, the same size range was utilised to generate patterns with double and overlaid droplet stains, with a consistent spacing of 2800 µm between each stain (see attached figure). The implementation of this systematic method guarantees the accurate calibration and application of image analysis algorithms in real-world situations. This allows for the representation of precise measurements and spacing that would be encountered in actual experimental conditions.</p>
Experimental characterization of transversal-heterogeneous clay mixtures by the spectral induced polarization method
<p>In this folder you will find multiple datasets (*.txt) from SIP measurements of transversal-heterogeneous clay mixtures using spectral induced polarization acquired between April and May 2022. Additionally, we include two python codes to read and process the data.</p> <p>SIP_Plot_ReWrite.py is a python program aimed to process a .res file from a SIP Fuchs III.<br> It gives a .txt file with the frequency, the resistivity, the phase and the associated errors.<br> In order for the program to give the resistivity, you will need to enter the geometric factor of the studied sample.</p> <p><br> The six text files in the folder (excluding README.txt) were created using SIP_Plot_ReWrite.py.</p> <p>IL_1by1.txt and IL_1by1_V2.txt are from two different homogeneous mixtures of illite and water with a concentration of initially 0.01 mol/L of NaCl.<br> MtR_1by1.txt is from a homogeneous mixture of red montmorillonite and water with a concentration of initially 0.01 mol/L of NaCl.</p> <p>IL_MtR_1by2.txt, IL_MtR_1by4.txt and IL_MtR_1by8.txt are from three transversal-heterogeneous mixtures of illite and red montmorillonite with water containing a concentration of initially 0.01 mol/L of NaCl.</p> <p><br> For IL_MtR_1by2.txt, there was one portion of each clay types, occupying a half of the cylindrical container each.</p> <p><br> For IL_MtR_1by4.txt, there was two portions of each clay types, occupying a quarter of the cylindrical container each.</p> <p><br> These two samples were made using the same mixtures as for IL_1by1.txt and MtR_1by1.txt.</p> <p><br> For IL_MtR_1by8.txt, there was four portions of each clay types, occupying an eighth of the cylindrical container each.<br> This sample was made using the same mixtures as for IL_1by1_V2.txt and MtR_1by1.txt.</p> <p><br> TestDoubleColeColeFit.py is a python program which optimizes a double Cole-Cole model by multiplication on SIP data.<br> This program needs a file with the same structure as the .txt file made by SIP_Plot_ReWrite.py.</p>
The dataset for publication "Characterization of scintillating materials in use for brachytherapy fiber based dosimeters" by S. Commeti, et al., Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2022.
<p>This dataset is related to paper journal paper with DOI: <a href="http://dx.doi.org/10.1016/j.nima.2022.167083">10.1016/j.nima.2022.167083</a>.</p> <p>The dataset contains raw txt file and matlab files on the transmittance and the attenuation of Gadox and YVO specimens. </p> <p>Data files were prepared by agnieszka.gierej@vub.be</p>
Data for Scan-Centric, Frequency-Based Method for Characterizing Peaks from Direct Injection Fourier transform Mass Spectrometry Experiments
<p>Input and output files from the manuscript analysis titled "Scan-Centric, Frequency-Based Method for Characterizing Peaks from Direct Injection Fourier transform Mass Spectrometry Experiments"</p>
Figure 4 in Prevalence of Blastocystis sp. in Morocco: Comparative assessment of three diagnostic methods and characterization of parasite forms in Jones' culture medium
Figure 4. Observation under the light microscope (×400) of different forms of cultured Blastocystis sp. in Jones' medium. Panel A: Different sizes of the vacuolar form. Panel B: Granular form (blue arrow) and cystic form (black arrow). Panel C: Granular form (blue arrow) and vacuolar form (red arrow). Panel D: Granular form (black arrow) and vacuolar form (red arrow) stained with methylene blue. Panel E: Illustrates the process of transformation of vacuolar cells into multivacuolar forms in culture, showing the division of the central vacuole into smaller vacuoles. Panel D: Different aspects of the amoeboid form with the presence of a single or several pseudopodia (red arrow).
Figure 5 in Prevalence of Blastocystis sp. in Morocco: Comparative assessment of three diagnostic methods and characterization of parasite forms in Jones' culture medium
Figure 5. Representative gel image of PCR products from Blastocystis isolates. Lanes 1 to 13: Blastocystis isolates; lane NC: negative control; lane PC: positive control; DNA ladder – 50 bp.
Figure 3 in Prevalence of Blastocystis sp. in Morocco: Comparative assessment of three diagnostic methods and characterization of parasite forms in Jones' culture medium
Figure 3. Various forms of Blastocystis sp. were observed under the light microscope during the direct examination of stool specimens. Panel A: Vacuolar form (red arrow) and cyst form (black arrow) of Blastocystis in an unstained wet mount. N: Nuclei situated at the periphery of the organism. C. b: Central body. Panels B, C, and D: Vacuolar form (red arrow), Granular form (blue arrow), and cyst form (black arrow) stained with Lugol's iodine (×400).
Figure 2 in Prevalence of Blastocystis sp. in Morocco: Comparative assessment of three diagnostic methods and characterization of parasite forms in Jones' culture medium
Figure 2. Occurrence of Blastocystis sp. infection on its own or in conjunction with other protozoan species.
Data used in "The Backscatter Gating method for time, energy, and position resolution characterization of long form factor organic scintillators" by Hunter N. Ratliff et al.
<p>This repository contains the raw experimental and PHITS-simulated data used in the JINST article “The Backscatter Gating method for time, energy, and position resolution characterization of long form factor organic scintillators” by Hunter N. Ratliff et al., available at <a href="https://doi.org/10.1088/1748-0221/19/07/P07002">https://doi.org/10.1088/1748-0221/19/07/P07002</a> (the accepted manuscript can also be found at <a href="https://hdl.handle.net/11250/3145287">https://hdl.handle.net/11250/3145287</a> and <a href="https://hratliff.com/publications/">https://hratliff.com/publications/</a>).</p> <p> </p> <p>The data consists of three top-level directories, each with various subdirectories. Within the “PHITS-simulated-data” directory are the PHITS simulations (including input and output files) used in producing Figures 4 and 5 in the manuscript, showing energy spectra in the bar for BSG events from a Cs-137 emission for placement of the source on the bar and on the BSG detector and with spacings between the bar and BSG detector of 20, 80, and 150 mm, along with the energy-dependent spatial distribution of these recoil electrons in the bar.</p> <p> </p> <p>The other two top-level directories contain raw data produced by the CAEN CoMPASS software when acquiring data experimentally. In the analysis for each measurement, the contents of the “RAW” folders were used. The “Energy-calibrations-of-CeBr3” directory contains the energy spectra of the CeBr3 detector (used as the BSG detector) when exposed to a variety of radioactive sources, used together to energy-calibrate the CeBr3 detector. The “Backscatter-gating-measurements” directory contains all of the list-mode data acquired with CoMPASS used for all of the other experimental measurements presented in the manuscript. It contains subdirectories for varied sources, source positions along the bar, distances between the bar and BSG detector, measurements with the source affixed to the BSG detector instead, and a few miscellaneous measurements. The “images” directories within each measurement’s directory (at the same level as the “RAW” folders) contain images produced by the analysis script written for this work used for diagnostics and presenting analyzed data.</p> <p> </p>
Data and results for manuscript "Small scale characterization of vine plant root water uptake via 3D electrical resistivity tomography and Mise-à-la-Masse method"
<p>This package contains measured raw ERT and MALM data used to generate the plots in the manuscript.</p> <p> </p>
Figure. Interferon alpha-A based phylogenetic tree (neighbor joining method) constructed by MEGA 6.1 for Punjab urial in comparison with other mammalian species sequences available from GenBank (NCBI). in Characterization of interferon alpha of major histocompatibility complex class I in Punjab urial (Ovis vignei punjabiensis)
Figure. Interferon alpha-A based phylogenetic tree (neighbor joining method) constructed by MEGA 6.1 for Punjab urial in comparison with other mammalian species sequences available from GenBank (NCBI).
Fig. 14. Relief high, rounded cusps. A in Functional Characterization of Ungulate Molars Using the Abrasion-Attrition Wear Gradient: A New Method for Reconstructing Paleodiets
Fig. 14. Relief high, rounded cusps. A: Kobus ellipsiprymnus AMNH 53484, left M1-M2; B: 53476, left M2; C: 53479, right M2; D: 53496, right M2; E: 53455, right M2; F: 53496, right M3; G: 53479, right M1; H: 53496, right M2; I: 53496, left M1; J: 53496, right M2; K: 53497, right M2.
Fig. 19. Relief low, blunt cusps. A in Functional Characterization of Ungulate Molars Using the Abrasion-Attrition Wear Gradient: A New Method for Reconstructing Paleodiets
Fig. 19. Relief low, blunt cusps. A: Equus grevyi AMNH 277427, right M1-M3; B: Equus burchelli AMNH 83601, left M1; C: 27749, right M1-M3; D: 165064, left M1; E: 82313, left M1- M3; F: 182315, right M1; G: 82316, left M2-M3; H: 82314, left M2-M3.
Fig. 18. Relief low, blunt cusps. A in Functional Characterization of Ungulate Molars Using the Abrasion-Attrition Wear Gradient: A New Method for Reconstructing Paleodiets
Fig. 18. Relief low, blunt cusps. A: Ceratotherium simum TE 5919, left M2; B: 5926, left M2; C: 5923, right M1; D: Equus burchelli AMNH 82036, right M2-M3; E: 82037, left M1; F: 119669, left M3; G: 54247, right M3; H: 119669, left M1; I: 165065, right M1-M2; J: 16062, left M1.
Data archive for the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method"
<p>Data archive accompanying the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method". In 2020 this article was accepted for publication in the journal <em>Atmospheric Measurement Techniques</em>. Data are uploaded in the form of ascii text files, Igor Pro experiment files (.pxp), and Jupyter notebook files. In addition, a Jupyter notebook file is included containing an implementation of the error model used in the paper.</p>
Characterizing high quality test methods, MSR'22
<p>Replication Kit for "Characterizing high quality test methods" paper.</p> <p>Number of records: 15970;</p> <p>Number of columns: 50;</p> <p>Columns list:</p> <ul> <li>Id;</li> <li>Project;</li> <li>Class;</li> <li>Method;</li> <li>Killed;</li> <li>Survived;</li> <li>TimedOut;</li> <li>Total;</li> <li>Score;</li> <li>WhileCount;</li> <li>ConditionCount;</li> <li>RedundantCount;</li> <li>AssertCount;</li> <li>IfCount;</li> <li>ExceptionCount;</li> <li>ForeachCount;</li> <li>PrintCount;</li> <li>SwitchCount;</li> <li>MysteryCount;</li> <li>ForCount;</li> <li>VerboseCount;</li> <li>ResourceOptimismCount;</li> <li>ThreadSleepCount;</li> <li>SensitiveCount;</li> <li>MagicNumberCount;</li> <li>Assertion Roulette;</li> <li>Mystery Guest;</li> <li>Sleepy Test;</li> <li>Unknown Test;</li> <li>Redundant Assertion;</li> <li>Dependent Test;</li> <li>Magic Number Test;</li> <li>Conditional Test Logic;</li> <li>EmptyTest;</li> <li>General Fixture;</li> <li>Sensitive Equality;</li> <li>Verbose Test;</li> <li>IgnoredTest;</li> <li>Resource Optimism;</li> <li>Duplicate Assert;</li> <li>Exception Catching Throwing;</li> <li>Print Statement;</li> <li>SLOC;</li> <li>Complexity;</li> <li>ModifyingCommits;</li> <li>Contributors;</li> <li>MaxExperienced;</li> <li>MinExperienced;</li> <li>MeanExperience;</li> <li>MedianExperience;</li> <li>StdevExperience</li> </ul> <p>Format: CSV</p> <p>Attributes per category:</p> <p>Size & Complexity: number of lines of code, cyclomatic complexity, loop count and conditional count;</p> <p>Exception: exception count and resource optimism;</p> <p>Contributors: Developers' expertise and number of contributors;</p> <p>Changes: Number of modifications;</p> <p>Quality: Number of asserts, mystery guest count, magic number count, print count, sleep count,<br> sensitive count</p> <p>Test Smells: Assertion Roulette, Mystery Guest, Sleepy Test, Unknown Test, Redundant Assertion, Dependent Test, Magic Number Test, Conditional Test Logic, EmptyTest, General Fixture, Sensitive Equality, Verbose Test, IgnoredTest, Resource Optimism, Duplicate Assert, Exception Catching Throwing, Print Statement; </p>
Methods for Extracting and Characterizing RNA from Urine: for downstream PCR and RNAseq Analysis
<p>Readily accessible samples such as urine or blood are seemingly ideal for differentiating and stratifying patients, however, it has proven a daunting task to identify reliable biomarkers in such samples. Noncoding RNA holds great promise as a source of biomarkers distinguishing physiologic wellbeing or illness.</p>
Seasonal footprints on ecological time series and jumps in dynamic states of protein configurations from a nonlinear forecasting method characterization (DataSet)
<p>Data from the article: <br>"Seasonal footprints on ecological time series and jumps in dynamic states of protein configurations from a nonlinear forecasting method characterization", L. Reyes, K. Campos, G. D. Avendaño, L. González-Paz, A. Vivas, Y. J. Alvarado, and S. Flores.</p> <p>Data to be used with some implementation of the forecasting method of reference:<br>Sugihara G. and May R. M., Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series, <em>Nature</em> <strong>344</strong>, 734–741 (1990).</p>
Figure 1 in Prevalence of Blastocystis sp. in Morocco: Comparative assessment of three diagnostic methods and characterization of parasite forms in Jones' culture medium
Figure 1. Dispersion of intestinal parasitic species among infected individuals.
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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.