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911 results for “SI”
Primary producer biomarker profiles of bulk carbon and nitrogen stable isotopes (SI), compound specific stable isotopes of carbon in essential amino acids (CSIA-EAA) and their fatty acid (FA) collected from the Beaufort Sea coastal lagoons,2021-2024
Within Stefansson Sound in Prudhoe Bay, AK various organic matter sources were collected to determine multiple biomarker baseline profiles (i.e., bulk carbon and nitrogen stable isotopes (SI), compound specific stable isotopes of carbon in essential amino acids (CSIA-EAA), fatty acids (FA)). Some organic matter sources were collected from Elson lagoon in Utqiaġvik, AK and Kaktovik and Jago lagoons in Kaktovik, AK to supplement low sample sizes in some organic matter source groups. Kelp, red algae, terrestrial plants, phytoplankton, and ice algae were collected in 2024 with some supplement samples collected in 2021 - 2023. Stable isotope values of δ13C and δ15N are reported as “del_13c” and “del_15n”, respectively. Individual fatty acids are reported as the percent relative to total fatty acids for 23 fatty acids: C11:0, C12:0, C14:0, C15:1, C15:0, C16:0, C16:1n7, C17:0, C17:1, C18:0, C18:1n9 trans, C18:2n6 cis, C18:1n7, C18:3n3, C20:0, C18:3n6, C20:4n6, C21:0, C22:0, C22:1n9, C23:0, C24:0, C22:6n3. Stable isotope values of δ13C are reported in the following essential amino acids: Valine (Val), Leucine (Leu), iLeu (isoleucine), Methionine (Met), Phenylalanine (Phe). Additionally, we used ice algal diatoms collected in the Arctic (landfast ice near Utqiaġvik, Alaska) and cultured in a laboratory setting at the University of Alaska Fairbanks to compare the CSIA-EAA fingerprints of field (composites) ice algal samples and isolate diatoms samples.
Data for "Nano-scale characterisation of sheared β'' precipitates in a deformed Al-Mg-Si alloy"
<p>This dataset contains data used in the publication entitled "<strong>Nano-scale characterisation of sheared β'' precipitates in a deformed Al-Mg-Si alloy</strong>". This publication concerns how β'' precipitates are sheared by dislocations during deformation. The data contained in this repository are data acquired on various transmission electron microscopes of specimens of the aluminium alloy AA6060 in peak aged condition after uniaxial compression to 5%, 10%, and 20%, in addition to the undeformed reference alloy.</p> <p>There are five main types of data:</p> <ul> <li>Transmission electron microscopy (TEM) images</li> <li>High-resolution TEM images</li> <li>High angle annular dark field (HAADF) scanning TEM (STEM) images</li> <li>Scanning precession electron diffraction (SPED) data.</li> <li>Cross-sectional data of precipitates in undeformed and 20% compressed conditions.</li> </ul> <p>Data for the TEM, HRTEM, and STEM images are kept in zipped folders due to the large number of images (several hundreds for each compression condition). Folders are named following the format of "<alloy>_<compression>_<technique>", where technique refers to TEM, HRTEM, or STEM. Images are provided in both .hdf format and .jpg format (to aid in navigating the data). Please see <a href="https://www.hdfgroup.org/">HDF Group</a> for more information regarding the HDF file format, and <a href="https://www.hdfgroup.org/downloads/hdfview/">HDF View</a> for softaware to read and show HDF data. The Python package <a href="http://hyperspy.org/">HyperSpy</a>, is also useful for loading the HDF data for inspection, analysis, and presentation.</p> <p>For some STEM images, a stack of short-exposure STEM images acquired and analysed using the <a href="http://lewysjones.com/software/smart-align/"><em>SmartAlign</em></a> plugin to <a href="http://www.gatan.com/products/tem-analysis/gatan-microscopy-suite-software"><em>Gatan Digital Micrograph</em></a> is available. SmartAlign offers the possibility of rigidly and non-rigidly aligning the STEM images in the stack in order to reduce effect of specimen drift and scan noise during acquisition. The conventional STEM images are found in the zip archive labelled "STEM". When the filenames of the STEM images include "SAstack" and/or "SAimage", a STEM SmartAlign stack or the average through a non-rigidly aligned stack is available of the same field of view. In such cases, both the SmartAlign stack and the through-stack image is provided in the metadata in the .hdf file (note that not all stacks have been aligned, and in such cases no through-stack image is available). In addition, the SmartAlign stacks themselves are available in the subfolder "STEM\SmartAlign\" within each STEM folder. The through-stack images of the smart align stacks are also provided separately in the subfolder "STEM\SmartAlign\Aligned\". For the 20% compressed case, a lowloss electron energy loss spectroscopy (EELS) spectrum and thickness maps of the imaged areas are also provided, in the subfolder "STEM\EELS\".</p> <p>The SPED data, acquired using the <em>ASTAR</em> system of <em><a href="https://www.nanomegas.com/">NanoMegas</a></em>, is provided as .hdf5 files in the root directory of the repository. They should be read using and <a href="https://github.com/pyxem/pyxem">pyXem</a>. The attached Jupyter Notebook "SPED_data_inspection.ipynb" can be used to access the SPED datasets. These datasets are 4D datasets, with two spatial and two reciprocal dimensions. They have been decomposed using the non-negative matrix factorization algorithm (NMF) used in HyperSpy. These decomposition results are included in the .hdf5 files. In addition, parameters used in the preprocessing of the datasets are attached in the metadata in these files. The metadata of these files are also provided separately as .txt files.</p> <p>Finally, measurements of the precipitate cross-sectional area and circularity is available as .csv files with the first column being the row index, the second the cross-sectional areas of precipitates measured in nanometers squared, the third column is the perimeters of the precipitates measured in nanometers, and column four is the <a href="https://imagej.nih.gov/ij/plugins/circularity.html">circularity</a> of the precipitates.</p>
Schedatura dei notai dell'Italia meridionale e insulare dei secc. XIII-XV di cui si conservano i rispettivi registri
<p>L’obiettivo della schedatura dei notai nell'ambito del progetto NotMed (EL NOTARIAT PÚBLIC EN LA MEDITERRÀNIA OCCIDENTAL: ESCRIPTURA, INSTITUCIONS, SOCIETAT I ECONOMIA (SEGLES XIII-XV) - Ministerio de Ciencia e Innovación. PID2019-105072GB-I00 - <a href="https://www.ub.edu/notmed/">https://www.ub.edu/notmed/</a>) era quello di conoscere il numero di volumi in legatura (protocolli notarili, bastardelli, etc.) esistenti nell’Italia meridionale e insulare per i secoli medievali e di creare una base per ulteriori ricerche.</p> <p>Hanno contribuito:</p> <p>Giuliano Capriolo, Andrea Casalboni, Gemma Teresa Colesanti, Martina Del Popolo, Corinna Drago, Alessandro Gaudiero, Antonio Macchione, Eleni Sakellariou, Daniela Santoro, Vera Isabell Schwarz-Ricci, Chiara Sciarroni, Alessandro Soddu, Maria Elisabetta Vendemia, Elisa Turrisi e Maurizio Vesco.</p> <p>NB.</p> <ul> <li> Nella dicitura “volumi in legatura” rientrano sia veri e proprio protocolli notarili sia bastardelli sia fascicoli rilegati.</li> <li> Il limite cronologico è l’anno 1500, tuttavia nei casi di notai che iniziano a rogare nella seconda metà del ‘400 sono confluiti nel censimento anche i registri dei primi decenni del ‘500.</li> <li> Per ogni notaio è stata compilata una singola scheda, tranne in due casi nei quali i protocolli si conservano in due istituzioni diverse.</li> <li> I volumi miscellanei sono stati conteggiati e schedati con una nota specifica inserita nel campo commento.</li> <li> È da tener presente che la base di rilevamento è eterogenea: alcune indicazioni si basano sull’esame autoptico del materiale, altre sulle indicazioni dell’inventario on line dell’archivio o su lavori pubblicati in precedenza. Per questo motivo si consiglia di consultare sempre le osservazioni del compilatore nel campo commento e le indicazioni sulla fonte dell’informazione.</li> </ul>
Data for a publication "Exploring the microstructure, mechanical properties, and corrosion resistance of innovative bioabsorbable Zn-Mg-(Si) alloys fabricated via powder metallurgy techniques"
<p><span><span>These data are published as part of the paper: “</span><span>Exploring the microst</span><span>ructure, mechanical properties, </span><span>and corrosion resistance of innovative bioabsorbable Zn-Mg-(S</span><span>i) alloys fabricated via powder </span><span>metallurgy techniques</span><span>” published in journal: “</span><span>Journal of Materials Research and Technology</span><span>”.</span></span><span> </span></p>
Global River BankFull Discharge (GQBF) - Siberia(SI) & South Pacific/Australia(SP)
<p>The GQBF is the estimated bankfull discharge across ~2.87 million km (length) of global river reaches. The bankfull discharge here is defined as the maximum flow rate contained within a river just before inundation occurs in the surrounding floodplain. We based our river bankfull discharge estimation on a newly developed river network, Global RIver Topology (GRIT), using GRIT’s river reaches as the spatial scale to represent the variation in bankfull discharge. We included all GRIT river reaches that coincided with the Global River Width from Landsat (GRWL) river masks (with overlapping ratio >=0.5). This selects river reaches with satellite-derived width measurements >=30 m, resulting in a total length of ~2.87 million km. Here, the GQBF represents the time-averaged bankfull discharge at <1 km (river length) spatial resolution.</p> <p><strong>Regions</strong></p> <p>Added regions SI, SP Vector files.</p> <ul> <li>SI - Siberia</li> <li>SP - South Pacific/Australia</li> </ul> <p>The subcontinental catchment groups (vector, polygons) can be found at <a href="https://zenodo.org/records/11219313">GRIT domain polygon</a> (GRITv06_domain_GLOBAL.gpkg.zip). They allow for more fine-grained subsetting of data .</p> <p>Vector files are provided in geographic WGS84 coordinates (EPSG:4326).</p> <p><strong>Change log</strong></p> <ul> <li>v0.1 - 2024-09-29<br> <ul> <li>First globally complete dataset published</li> </ul> </li> <li>v0.1 - 2024-11-19 <ul> <li>Add vector files for regions SI, SP</li> </ul> </li> </ul>
Large-Area MOVPE Growth of Topological Insulator Bi2Te3 Epitaxial Layers on i-Si(111) (data)
<p>This dataset contains the raw data files connected with the figures included in the paper "<em>Large-Area MOVPE Growth of Topological Insulator Bi<sub>2</sub>Te<sub>3</sub> Epitaxial Layers on i-Si(111)</em>" by <a href="https://pubs.acs.org/doi/10.1021/acs.cgd.1c00328">A. Kumar et al., <em>Cryst. Growth Des.</em> 2021, 21, 7, 4023–4029</a> </p>
Near-infrared (NIR) soil spectral library using the NeoSpectra Handheld NIR Analyzer by Si-Ware
<p>Up-to-date information on soil properties and the ability to track changes in soil properties over time are critical for improving multiple decisions on soil security at various scales, ranging from global climate change modeling and policy to national level environmental and development planning, to farm and field level resource management. Diffuse reflectance infrared spectroscopy has become an indispensable laboratory tool for the rapid estimation of numerous soil properties to support various soil mapping, soil monitoring, and soil testing applications. Recent advances in hardware technology have enabled the development of handheld sensors with similar performance specifications as laboratory-grade near-infrared (NIR) spectrometers.</p> <p>Here, we've compiled a hand-held NIR spectral library (1350-2550 nm) using the NeoSpectra Handheld NIR Analyzer developed by <a href="https://www.si-ware.com/">Si-Ware</a>. Each scanner is fitted with Fourier-Transform technology based on the semiconductor Micro Electromechanical Systems (MEMS) manufacturing technique, promising accuracy, and consistency between devices.</p> <p>This library includes 2,106 distinct mineral soil samples scanned across 9 of these portable low-cost NIR spectrometers (indicated by serial no). 2,016 of these soil samples were selected to represent the diversity of mineral soils found in the United States, and 90 samples were selected across Ghana, Kenya, and Nigeria. 519 of the US samples were selected and scanned by <a href="https://www.woodwellclimate.org/">Woodwell Climate Research Center</a>. These samples were queried from the <a href="https://ncsslabdatamart.sc.egov.usda.gov/">USDA NRCS NSSC-KSSL Soil Archives</a> as having a complete set of eight measured properties (TC, OC, TN, CEC, pH, clay, sand, and silt). They were stratified based on the major horizon and taxonomic order, omitting the categories with less than 500 samples. Three percent of each stratum (i.e., a combination of major horizon and taxonomic order) was then randomly selected as the final subset retrieved from KSSL's physical soil archive as 2-mm sieved samples. The remaining 1,604 US samples were queried from the USDA NRCS NSSC-KSSL Soil Archives by the <a href="https://www.unl.edu/">University of Nebraska - Lincoln</a> to meet the following criteria: Lower depth <= 30 cm, pH range 4.0 to 9.5, Organic carbon <10%, Greater than lower detection limits, Actual physical samples available in the archive, Samples collected and analyzed from 2001 onwards, Samples having complete analyses for high-priority properties (Sand, Silt, Clay, CEC, Exchangeable Ca, Exchangeable Mg, Exchangeable K, Exchangeable Na, CaCO3, OC, TN), & MIR scanned.</p> <p>All samples were scanned dry 2mm sieved. ~20g of sample was added to a plastic weighing boat where the NeoSpectra scanner would be placed down to make direct contact with the soil surface. The scanner was gently moved across the surface of the sample as 6 replicate scans were taken. These replicates were then averaged so that there is one spectra per sample per scanner in the resulting database.</p> <p>A subset of 1,976 US topsoil samples was used to create Cubist models for 8 soil properties including bulk density (BD, <2mm fraction, 1/3 Bar, units in grams per cubic centimeter), calcium carbonate (CaCO3, <2mm fraction, units in weight percent), clay content (percent), buffered ammonium-acetate exchangeable potassium (Ex. K, units in centimoles of charge per kilogram of soil), pH, sand content (percent), silt content (percent), and estimated organic carbon (SOC, estimated after inorganic carbon removal, units in weight percent). Two strategies were evaluated for handling scanner-to-scanner variability: averaging scans per sample (avg) versus retaining replicate scans across all scanners (reps) during model building. Cubist avg models and cubist reps models are provided here for the 8 soil properties outlined in “.qs” file format and can be opened and worked with in the R programming language. The subset of 1,976 samples has also been provided here for reproducibility (1976_NSlibrary_withmetadata.csv).</p> <p>The repository contains:</p> <ul> <li><em>Neospectra_database_column_names.csv</em>: describes the variables (columns) of site and soil data, and the range of near-infrared (NIR, 1350-2550 nm) and mid-infrared (MIR, 600-4000 cm-1) spectra. The CSV is composed of the file name, column name, type, example, and description with measurement unit.</li> <li><em>Neospectra_WoodwellKSSL_MIR.csv</em>: the equivalent MIR spectra of neospectra samples fetched from the KSSL database and formatted to the OSSL specifications.</li> <li><em>Neospectra_WoodwellKSSL_soil+site+NIR.csv</em>: soil, site, and Neospectra's NIR. Each row contains one replicated spectra of a given scanner (6 repeats per scanner per soil sample). Soil and site info is filled within the same soil sample.</li> <li>1976_NSlibrary_withmetadata.csv: data matrix for reproducible model calibration.</li> <li>Models: <ul> <li>log..bd_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for log(1+BD).</li> <li> <p>log..caco3_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for log(1+CaCO3).</p> </li> <li> <p>clay_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for clay.</p> </li> <li> <p>log..k.ex_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for log(1+Ex. K).</p> </li> <li> <p>ph.h2o_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for pH.</p> </li> <li> <p>sand_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for sand.</p> </li> <li> <p>silt_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for silt.</p> </li> <li> <p>log..soc_model_nir.neospectra_cubist_AVG_ossl_na_v1.2.qs: Cubist average NIR model for log(1+SOC).</p> </li> <li> <p>log..bd_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for log(1+BD).</p> </li> <li> <p>log..caco3_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for log(1+CaCO3).</p> </li> <li> <p>clay_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for clay.</p> </li> <li> <p>log..k.ex_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for log(1+Ex. K).</p> </li> <li> <p>ph.h2o_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for pH.</p> </li> <li> <p>sand_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for sand.</p> </li> <li> <p>silt_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for silt.</p> </li> <li> <p>log..soc_model_nir.neospectra_cubist_REPS_ossl_na_v1.2.qs: Cubist replicates NIR model for log(1+SOC).</p> </li> </ul> </li> </ul>
Si data files for Galaxy materials science tutorials
<p>This is a training dataset for use in Galaxy materials science tutorials. These files can be used to demonstrate the AIRSS (Ab-Initio Random Structure Searching) method for finding muon stopping sites, using the UEP (Unperturbed Electrostatic Potential) technique for the optimisation stage of that method.</p> <p>The files included are:</p> <ul> <li><strong>Si.cell:</strong> structure file containing atom locations</li> <li><strong>Si.den_fmt:</strong> electron density data, generated with CASTEP</li> <li><strong>Si.castep:</strong> CASTEP log file for the electron density calculation</li> <li><strong>Si-muairss-uep.yaml:</strong> configuration file for the AIRSS / UEP workflow</li> </ul>
Influence of Framework n(Si)/n(Al) Ratio on the Nature of Cu Species in Cu-ZSM-5 for NH3-SCR-DeNOx
<ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements, computer simulation and analysis</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>m</strong>, <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA.</strong></li> <li>EPR spectroscopic simulation and analyses with filename extension <strong>m</strong>.</li> <li>EPR spectra are exported as <strong>txt</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li><strong>If the dataset includes multiple files that relate to each other:</strong> <ul> <li>Files in <strong>PARACAT_WP3_20220705_01_CW_Experimental</strong> folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and txt formats.</li> <li>Files in <strong>PARACAT_WP3_20220705_02_CW_Simulations</strong> folder includes computer simulations/analyses of the EPR measurements; data are in m and txt formats.</li> </ul> </li> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>EPR</strong> – Electron Paramagnetic Resonance, <strong>CW</strong> – Continuous Wave EPR, <strong>exp </strong>– experimental data, <strong>hyd </strong>– cw-EPR spectra related to hydrated state, <strong>dehyd </strong>– cw-EPR spectra related to the dehydrated state, <strong>sim </strong>– simulation data. <strong>Sys </strong>– copper species used for constructing the spin-Hamiltonian in EPR simulations. <strong>Cu-ZSM-5-com </strong>– commercial Cu-ZSM-5. <strong>Cu-ZSM-5-100</strong> – Cu-ZSM-5 synthesized at 100 °C. <strong>Cu-ZSM-5-120</strong> – Cu-ZSM-5 synthesized at 120 °C. <strong>Cu-ZSM-5-150</strong> – Cu-ZSM-5 synthesized at 150 °C.</li> </ul> </li> <li>– Cu-ZSM-5 synthesized at 170 °C. <ul> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> </ul> </li> </ul>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai (Thai: สุโขทัย) Sukhothai province, Thailand, as documented in 2014,</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai (Thai: สุโขทัย) Sukhothai province, Thailand.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Dharmacakra.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Dharmacakra, now in the Ramkhamhaeng National Museum, Sukhothai, as documented in 2014.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Dharmacakra, detail.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Dharmacakra, detail, now in the Ramkhamhaeng National Museum, Sukhothai, as documented in 2014.</p> <p> </p>
N-SI-121 spectra
<p>HDF5 file containing experiment N-SI-121 spectra (gamma, gamma-gamma, etc.), used for data analysis for publication. Experiment used O-18 beam on a thick Au-197 target, and was primarly focused on fission of the compound nucleus (Fr-215).</p> <p>HDF5 file has a flat structure of collection of 2D spectra:</p> <ul> <li>Eloc - Energy vs. location (detector number)</li> <li>bgo_time - BGO anti-compton energy vs. time realtive to the beam pulse</li> <li>gM - gamma energy in Germanium detectors vs. multiplicity</li> <li>gM_delayed - as above but for delayed gamma emission </li> <li>ge_time - Ge detector energy vs. time relative to the beam pulse</li> <li>gg - all gamma-gamma coincidences (Ge detectors)</li> <li>gg_delayed - as above but only delayed coincidences</li> <li>gg_prompt - as above but only prompt coincidences</li> <li>la_time - LaBr3 detectors vs. time relative to the beam pulse</li> <li>tloc - time relative to the beam pulse vs. detector location</li> <li>totM_delayed - total energy (sum of all kind of detectors), delayed radiation only</li> <li>totM_prompt- total energy (sum of all kind of detectors), prompt radiation only</li> </ul> <p>Each event is 400 ns long, beam pulse is set to position 40 ns. Delayed radiation is in range 80-350 ns relative to beam pulse, prompt is 35-65 ns.</p>
Data and results of the example used in the SI-Hg D1 protocol for the SI-traceable calibration of elemental mercury (Hg0) gas generators used in the field
<p>During the SI-Hg project a metrological traceable protocol for the calibration of mercury gas generators used in the field was developed and validated. The SI-Hg calibration protocol specifies the procedures for establishing traceability to the SI units for the quantitative output of elemental mercury generators that are employed in regulatory applications for emission monitoring or testing. This protocol provides methods for</p><ul><li>the experimental procedures to compare the output of elemental mercury gas generators</li><li>the data processing for determination of mercury concentration and the expanded uncertainty of the mercury concentration obtained from the elemental mercury gas generator.</li></ul><p>In the protocol examples are given to explain the data processing, determining the mercury concentration and corresponding uncertainty. In this repository the raw data and results used for the example calculated with the data processing script can be found.</p>
Não-conformidades ao SI em textos técnico-científicos (vídeo da apresentação)
<p>Vídeo da palestra realizada a pedido do <strong>Forum Internacional para Metrologia e Examinologia em Química</strong> (https://formeq.org/):</p> <p>Tema: <strong>Não-conformidades ao SI em textos técnico-científicos</strong><br> Enlace da gravação: <strong>https://www.youtube.com/watch?v=3xssyQPYh7E</strong></p> <p>Palestrante: Dr. Ricardo de Araújo Kalid<br> E-mail: kalid@ufsb.edu.br<br> Data: 20 de dezembro de 2021<br> Horário: das 14 h 30 min às 16 h 30 min</p> <p>Tópicos abordados:</p> <ol> <li>Linha do tempo do Sistema Internacional de Unidades (<strong>SI</strong>)</li> <li>Grafia e pronúncia de nomes e símbolos de unidades de grandezas conforme o <strong>SI</strong></li> <li>Operações matemáticas e valores numéricos de grandezas e suas incertezas conforme o <strong>SI</strong></li> <li>Tabelas e gráficos conforme o <strong>SI</strong></li> <li>Incertezas de grandezas e intervalos de medidas conforme o <strong>SI</strong></li> <li>Discussões</li> </ol> <p> </p> <p>Contato:</p> <p>Ricardo de Araújo Kalid<br> Pesquisador Emérito do CNPq <strong><a href="https://wwws.cnpq.br/cvlattesweb/PKG_MENU.menu?f_cod=7D48BC187965582AF96A5D11E7FD2636#">http://lattes.cnpq.br/2562159376424787</a></strong><br> Professor Associado IV da UFSB <strong><strong><a href="https://orcid.org/0000-0001-9265-5263">https://orcid.org/0000-0001-9265-5263</a></strong></strong><br> E-mail institucional: kalid@ufsb.edu.br<br> E-mail profissional: ricardokalid@gmail.com<br> Tel/Wap: +55(73)99844-1308</p>
Reactive pressure infiltration of Cu-46at.pct. Si into carbon
<p>Raw data linked to the paper published in Acta Materialia :Reactive pressure infiltration of Cu-46at.pct. Si into carbon (DOI:h<a href="https://doi.org/10.1016/j.actamat.2019.07.010">ttps://doi.org/10.1016/j.actamat.2019.07.010</a>)</p>
Supplementary Information and EBSD data for 'Intermetallic phase layers in cold metal transfer aluminium-steel welds with an Al-Si-Mn filler alloy'
<p>Supplementary information and electron backscatter diffraction (EBSD) data for the article entitled 'Intermetallic phase layers in cold metal transfer aluminium-steel joints with an Al-Si-Mn filler alloy'. There are three EBSD datasets, I-III, named "I_EBSD.dat" - "III_EBSD.dat", each with corresponding calibration and background patterns, as well as secondary electron scanning electron microscopy images showing the scanned area and text files containing the acquisition parameters. The data analysis workflow has been published on GitHub, see References.</p>
ScienceDex guides
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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.