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911 results for “SI”
Dataset for publication "Effects of Y and Ho doping on microstructure evolution during oxidation of extraordinary stable Hf-B-Si-Y/Ho-C-N films up to 1500 °C" in Materials & Design 237, (2024), 112589.
<p>Dataset for publication "Effects of Y and Ho doping on microstructure evolution during oxidation of extraordinary stable Hf-B-Si-Y/Ho-C-N films up to 1500 °C" in Materials & Design Volume 237, January 2024, 112589, DOI 10.1016/j.matdes.2023.112589.</p> <p>XRD patterns, SAED patterns, EDS spectra, TEM images, HRTEM images.</p>
In situ conductometry for studying the homogenization of Al-Mg-Si alloys and predicting extrudate grain structure through machine learning
<p>This dataset includes the <em>in situ</em> impedance and time/temperature data from [1], grain structure data created by extrusion simulation coupled with physically-based microstructural simulation [2], and the predictions of the feed-forward neural network GRAINN-1/2 [1].</p> <p>[1] Österreicher, J. A., Zivanovic, D., Walenta, W., Maimone, S.,Hofbauer, M., Hovden, S., Tükör, Z., Arnoldt, A., Cerny, A. Kronsteiner, A., Antic, M., Zickler, G., Ehmeier, F., Mikulovic, M., Kunschert, G. (2024) . In situ conductometry for studying the homogenization of Al-Mg-Si alloys and predicting extrudate grain structure through machine learning. <em>Materials & Design</em>, 113070.</p> <p>[2] Hovden, S., Kronsteiner, J., Arnoldt, A., Horwatitsch, D., Kunschert, G., & Österreicher, J. A. (2024). Parameter study of extrusion simulation and grain structure prediction for 6xxx alloys with varied Fe content. <em>Materials Today Communications</em>, <em>38</em>, 108128.</p>
SI Figure 4: SEM images of either unwashed (left) or washed (right) E. antarcticus nematodes. A. Unwashed head region with arrows pointing to attached material and possible fungal hyphae. B. Washed head region with arrows pointing to the remaining attached material. C. Unwashed annules with arrows pointing to commonly attached foreign material. D. Washed annules with arrows pointing to remaining attached material. E. Unwashed somatic pore with arrows pointing to the common organic material. F. Washed vulva with an arrow pointing to remaining attached organic material. G. Unwashed cuticle with arrows showing a possible biofilm. H. Washed cuticle showing single attached cells indicated with arrows. I. Unwashed cuticle showing an off-axis line of attached material. J. Washed cuticle showing a similar off-axis line of material (as indicated with arrow) but reduced in quantity compared to the unwashed. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 4: SEM images of either unwashed (left) or washed (right) E. antarcticus nematodes. A. Unwashed head region with arrows pointing to attached material and possible fungal hyphae. B. Washed head region with arrows pointing to the remaining attached material. C. Unwashed annules with arrows pointing to commonly attached foreign material. D. Washed annules with arrows pointing to remaining attached material. E. Unwashed somatic pore with arrows pointing to the common organic material. F. Washed vulva with an arrow pointing to remaining attached organic material. G. Unwashed cuticle with arrows showing a possible biofilm. H. Washed cuticle showing single attached cells indicated with arrows. I. Unwashed cuticle showing an off-axis line of attached material. J. Washed cuticle showing a similar off-axis line of material (as indicated with arrow) but reduced in quantity compared to the unwashed.
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream.
SI Figure 2: Compositional differences among bacterial microinvertebrate external and internal microbiomes as well as mats they were isolated from using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars show centroids of microbiome types for each animal host. All host microbiomes (internal and external) are distinct from mat communities (P<0.05), but external microbiomes are more similar to mats than internal microbiomes are to mats. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 2: Compositional differences among bacterial microinvertebrate external and internal microbiomes as well as mats they were isolated from using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars show centroids of microbiome types for each animal host. All host microbiomes (internal and external) are distinct from mat communities (P<0.05), but external microbiomes are more similar to mats than internal microbiomes are to mats.
SI Figure 1: Dispersion values (a boxplot using distance to centroids based on Bray Curtis distance matrix) of external and internal bacterial microbiome composition for different hosts. In a mixed linear model, microinvertebrates did not significantly impact dispersion (P=0.44), but microbiome type did (P=0.03). Pairwise contrasts show that while external microbiomes of P. murrayi and Tardigrada are more variable than their internal microbiomes, E. antarcticus external and internal microbiomes are equally variable. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 1: Dispersion values (a boxplot using distance to centroids based on Bray Curtis distance matrix) of external and internal bacterial microbiome composition for different hosts. In a mixed linear model, microinvertebrates did not significantly impact dispersion (P=0.44), but microbiome type did (P=0.03). Pairwise contrasts show that while external microbiomes of P. murrayi and Tardigrada are more variable than their internal microbiomes, E. antarcticus external and internal microbiomes are equally variable.
An SI-traceable protocol for the validation of radiative transfer model-based reflectance simulation: datasets
<p>This data record contains datasets used in the study "An SI-traceable protocol for the validation of radiative transfer model-based reflectance simulation":</p> <ul> <li>The <code><span>final_design.ply</span></code> file contains the mesh corresponding to the final artefact design.</li> <li>The <code><span>material_measurements.nc</span></code> file contains goniophotometer records for the material reflectance.</li> <li>The <code><span>artefact_measurements.nc</span></code> file contains goniophotometer records for the artefact reflectance.</li> </ul>
Raman spectra of Co3O4 and ZnO thin layers on Si
<p>The Raman spectra were recorded on samples consisting of a zinc oxide (ZnO) layer, a cobalt oxide (Co3O4) layer, and a silicon (Si) substrate. The thickness of the layers is as follows: 70 nm, 15 nm, and 200 µm. The sample was annealed at 400°C for 30 minutes.</p> <p>The Raman measurements were conducted using a T64000 Horiba Jobin-Yvon spectrometer at room temperature, operating in a single subtractive operation mode with an entrance slit width of 0.1 mm. For excitation, the 514.5 nm line of an Ar+ laser was utilized. Detection was performed using a silicon CCD camera cooled with liquid nitrogen.</p>
Dataset: SI-BONE, Inc. (SIBN) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Quantum-Si incorporated (QSIAW) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Quantum-Si incorporated (QSI) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Lower crustal extrusion in the distal continental margin of the South China Sea_SI_v2
<p>Supporting documents for submitted articles</p>
Optical Constants of a single AlN layer on Si
<p>Spectroscopic ellipsometry was used to determine the thickness and dielectric function of a Aluminium Nitride (AlN) layer on a Si wafer. The layer was determined to be 170 nm thick. The layer was provided by AIXTRON and manufactured by means of MOVPE.</p> <p>The data was created using a M2000DI spectroscopic ellipsometer from Woollam Co. Inc. Analysis was done using the CompleteEASE software. The model used is a multi-peak oscillator model for the AlN layer.</p> <p>The data resembles common database values for the material AlN.</p>
Fig. 2 in Isolation of wild yeasts from soils collected in Pochoen-si, Korea and characterization of unrecorded yeasts
Fig. 2. Neighbor-joining phylogenetic tree based on 26S rRNA gene sequences shows the relationship between the strains isolated in this study and their relatives of the genus Leucosporidium. Bar: 0.005 substitutions per site.
Fig. 1 in Isolation of wild yeasts from soils collected in Pochoen-si, Korea and characterization of unrecorded yeasts
Fig. 1. Phase-contrast micrographs of the unrecorded strains isolated in this study. Strains: A, YP204; B, YP205; C, YP211; D, YP215; E, YP189; F, YP196; G, YP329; H, YP76.
SI: A Guide to Automated Apoptosis Detection
<p>supplementary information of the article:</p> <p>"A Guide to Automated Apoptosis Detection:</p> <p>How to Make Sense of Imaging Flow Cytometry Data"</p> <p>D. Pischel et al., 2018</p>
N-gram dataset of Xu Xiu Si Ku Quan Shu (續修四庫全書)
<p>This dataset contains the N-grams (1-3) collected from Xu Xiu Si Ku Quan Shu (續修四庫全書).</p> <p>The dataset comprises of the following resources:</p> <ul> <li><strong>xuxiu<strong>_</strong>1.7z</strong> Unigram dataset in tab seperated format (one file per book, each row contains the N-gram and its count)</li> <li><strong>xuxiu</strong><strong>_2.7z</strong> Bigram dataset in tab seperated format (one file per book, each row contains the N-gram and its count)</li> <li><strong>xuxiu</strong><strong>_3.7z</strong> Trigram dataset in tab seperated format (one file per book, each row contains the N-gram and its count)</li> <li><strong>xuxiu_metadata.xlsx</strong> Metadata of each book</li> </ul> <p> </p> <p>Dieses Datenset enthält die im Xu Xiu Si Ku Quan Shu (續修四庫全書) enthaltenen N-Gramme (1-3). </p> <p>Das Datenset besteht aus den folgenden Dateien:</p> <ul> <li><strong>xuxiu_1.7z</strong> Monogramm-Datenset im .txt Dateiformat mit Tabstopp als Trennzeichen (jede Datei enthält ein Buch, jede Zeile ein N-Gramm mit der Anzahl der Vorkommnisse im Text)</li> <li><strong>xuxiu_2.7z</strong> Bigramm-Datenset im .txt Dateiformat mit Tabstopp als Trennzeichen (jede Datei enthält ein Buch, jede Zeile ein N-Gramm mit der Anzahl der Vorkommnisse im Text)</li> <li><strong>xuxiu_3.7z</strong> Trigramm-Datenset im .txt Dateiformat mit Tabstopp als Trennzeichen (jede Datei enthält ein Buch, jede Zeile ein N-Gramm mit der Anzahl der Vorkommnisse im Text)</li> <li><strong>xuxiu_metata.xlsx</strong> Metadaten der enthaltenen Bücher</li> </ul> <p> </p> <p>《續修四庫全書》n元語法統計資料 (N-gram Dataset)</p> <p>以下是檔案簡說:</p> <ul> <li><strong>xuxiu</strong><strong>_1.7z</strong> 《續修四庫全書》一元分詞(Unigram)的統計資料 (每本書一個檔案,以tab作欄區分,每一行紀錄該 N-gram 在書中出現的次數)</li> <li><strong>xuxiu</strong><strong>_2.7z</strong> 《續修四庫全書》二元分詞(Bigram)的統計資料 (每本書一個檔案,以tab作欄區分,每一行紀錄該 N-gram 在書中出現的次數)</li> <li><strong>xuxiu</strong><strong>_3.7z</strong> 《續修四庫全書》三元分詞(Trigram)的統計資料 (每本書一個檔案,以tab作欄區分,每一行紀錄該 N-gram 在書中出現的次數)</li> <li><strong>xuxiu</strong><strong>_metadata.xlsx</strong> 紀錄每本書的基本Metadata</li> </ul>
SI and ZooMS spectra Cassenade (MALDI-TOF-MS)
<p>Supplementary Information (SI) for the paper:</p> <p>Ruebens, K., Discamps, E., Smith, G. M., Hublin, J-J. Integrating ZooMS and zooarchaeology to assess the Châtelperronian and carnivore occupations at Cassenade (Dordogne, France), published in the gold open access journal PaleoAnthropology.</p> <ul> <li>SI 1: individual raw data files (10 .zip files with 2,550 mzxml files, representing 840 bone samples and 10 blanks, each spotted in triplicate, organised in 10 MALDI runs)</li> <li>SI 2: excel database listing information on plate number, MALDI run and triplicates (spot location), the identified peptide markers and ZooMS identifications (Barcode ID).</li> <li>SI 3: excel database with ZooMS identifications, zooarchaeological data (incl. body size classes) and taphonomic observations</li> <li>SI 4: excel database with the spatial coordinates for the piece-plotted bone fragments</li> <li>SI 5: tables for the statistical tests</li> <li>SI 6: R script used for making the figures and statistical tests</li> </ul> <p>Note: samples CAS-190-248 relate to bone fragments from old excavations which are not reported in this paper so not included in this database. </p> <p>Note: All samples were extracted using an AmBic protocol, except for samples 856-876 which were demineralised using HCl. </p> <p>For any questions please contact Karen Ruebens.</p> <p>Please use the DOI (10.5281/zenodo.11102785) when citing this dataset.</p>
Ultrafast photoresponse of vertically oriented TMD films probed in a vertical electrode configuration on Si chips
<p>This dataset contains the measurement data for figures published in the journal article: </p> <p> Ultrafast photoresponse of vertically oriented TMD films probed in a vertical electrode configuration on Si chips (https://doi.org/10.1039/D2NA00313A)</p> <p>by Topias Järvinen, Seyed-Hossein Hosseini Shokouh, Sami Sainio, Olli Pitkänen and Krisztian Kordas</p>
MSCA SHINE_Project: Numerical results of the soldification-melting of a Si-based alloy (Ultra-high temperature storage)
<p>Project 101145914 — SHINE has received funding withing the MSCA framework. The purpose of this project is to construct a generic model describing the solidification-melting process of ultra-high temperature latent heat thermal energy storage systems based on data-driven analysis and rigorous CFD models. Within the initial steps of the project a preliminary database is being created based on available results from previous UPM’s projects (Thermobat Project) as well as preliminary simulations by using a 2D CFD model. The present dataset contains information of FeSiB alloy solidification-melting close to 1250 oC inside a cylindrical container, under various heating conditions. Analysis of the present data can be also found in the manuscript entitled as ¨Numerical analysis on the state of charge of an ultra-high temperature latent heat energy storage system, SoraPaces, Rome, 2024¨</p>
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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
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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.