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3,264 results for “FAST”
Fast Intratumor Heterogeneity Inference from Single-Cell Sequencing Data (simulated data - Extended Data Figures)
<p>This data repository contains simulated data used for benchmarking HUNTRESS against the existing alternative tools. Results of the benchmarking are shown in Extended Data Figures 1-10 of the paper "Fast Intratumor Heterogeneity Inference from Single-Cell Sequencing Data" (to appear in Nature Computational Science). </p>
Fast Improvement of TEM Images with Low-Dose Electrons by Deep Learning
<p>This is a dataset of High-Dose-Electron (HDE) images and Low-Dose-Electron (LDE) images taken with a transmission electron microscopy used in <a href="https://doi.org/10.1017/S1431927621013799">H. Katsuno, Y. Kimura, T. Yamazaki and I Takigawa, Microsc. Microanal. <strong>28</strong> (2022), pp 138--144</a> (<a href="https://arxiv.org/abs/2106.01718">arXiv:2106.01718</a>).</p> <p>There are two LDE images for each HDE image.</p> <p>cf) HDE image is 0001.tif and corresponding LDE images are 0002.tif and 0003.tif.</p> <p> </p> <p>Equipment of TEM:</p> <p>field-emission gun (JEM-2100F, JEOL, Tokyo)</p> <p>OneView IS (Gatan, Inc., Pleasanton, CA, USA)</p> <p> </p> <p>Typical magnification was 25,000x and 30,000x.</p> <p> </p> <p>HDE image</p> <p>The resolution was 4096 x 4096 pixels and its exposure time was 5 s.</p> <p>The typical total doses was 10<sup>10</sup> e<sup>-.</sup></p> <p> </p> <p>LDE image</p> <p>The resolution was 512 x 512 pixels and its exposure time was 3.3 ms.</p> <p>The typical total doses was 10<sup>6</sup> e<sup>-</sup>.</p> <p> </p> <table> <tbody> <tr> <td>Filename</td> <td>Material</td> <td>Total number of images</td> <td>Total number of a pair of HDE and LDE</td> </tr> <tr> <td>train1_Ni.zip</td> <td>Ni</td> <td>336</td> <td>224</td> </tr> <tr> <td>train2_FeNi.zip</td> <td>FeNi</td> <td>390</td> <td>260</td> </tr> <tr> <td>train3_SiC.zip</td> <td>SiC</td> <td>210</td> <td>140</td> </tr> <tr> <td>train4_Silicate</td> <td>Silicate</td> <td>264</td> <td>176</td> </tr> <tr> <td>train5_Alumina</td> <td>Alumina</td> <td>300</td> <td>200</td> </tr> <tr> <td>val1_Ni.zip</td> <td>Ni</td> <td>54</td> <td>36</td> </tr> <tr> <td>val2_FeNi.zip</td> <td>FeNi</td> <td>60</td> <td>40</td> </tr> <tr> <td>val3_SiC.zip</td> <td>SiC</td> <td>30</td> <td>20</td> </tr> <tr> <td>val4_Silicate</td> <td>Silicate</td> <td>36</td> <td>24</td> </tr> <tr> <td>val5_Alumina</td> <td>Alumina</td> <td>60</td> <td>40</td> </tr> </tbody> </table> <p> </p> <p> </p> <p>The ipynb file and model parameters for machine learning are located in <a href="https://github.com/hiroyasukatsuno/Fast-Improvement-Low-Dose-TEMimages">the GitHub page</a>.</p> <p> </p>
Data for: Fast adjustment of POLS to food quality
<p><span>The pace-of-life syndrome hypothesis provides a framework for the adaptive integration of behaviour, physiology and life history at between and within species. It suggests that behaviours involving a risk of death or injury should co-vary with a higher allocation to fast reproduction. Empirical support for this hypothesis is mixed, presumably because important influencing factors such as environmental variation, are usually neglected. By experimentally manipulating the food quality of wild mice living under semi-natural conditions for three generations, we show that individuals adjust their life history strategies and risk-taking behaviours as well as trait covariation (N<sub>individuals</sub> = </span><span>1442)</span><span>. These phenotypic differences are correlated to differences in transcriptomic gene expression of primarily metabolic processes in the liver while no changes in gene frequencies occurred. Our discussion emphasizes the need to integrate the role of environmental conditions and phenotypic plasticity in shaping relationships among behaviour, physiology and life-history in response to changing environmental conditions.</span></p>
FIGURE 3 in Life-stage association of black flies, using a fast-evolving nuclear gene sequence, and description of the larva of Simulium lampangense Takaoka & Choochote (Diptera: Simuliidae) from Thailand
FIGURE 3. Larva of Simulium lampangense. A. Cephalic apotome, dorsal view. B. Mandible, apex. C. Hypostoma. D. Head capsule showing postgenal cleft, ventral view. Scale bars = 0.1 mm for A and D and 0.05 mm for B and C.
FIGURE 2. Bayesian tree for nuclear elongation complex protein 1 in Life-stage association of black flies, using a fast-evolving nuclear gene sequence, and description of the larva of Simulium lampangense Takaoka & Choochote (Diptera: Simuliidae) from Thailand
FIGURE 2. Bayesian tree for nuclear elongation complex protein 1 (ECP1) sequences of five nominal species and unknown (Unk) larvae in the Simulium multistriatum species group in Thailand. Bootstrap values for neighbor-joining and maximum likelihood and posterior probability of Bayesian analysis are shown above or near the branches. -- denotes bootstrap support less than 50%. Scale bar represents 0.03 substitutions per nucleotide position.
FIGURE 1 in Life-stage association of black flies, using a fast-evolving nuclear gene sequence, and description of the larva of Simulium lampangense Takaoka & Choochote (Diptera: Simuliidae) from Thailand
FIGURE 1. Bayesian tree based on cytochrome c oxidase subunit I (COI) sequences of six nominal species and unknown (Unk) larvae in the Simulium multistriatum species group in Thailand. Bootstrap values for neighbor-joining and maximum likelihood (ML) and posterior probability of Bayesian analysis are shown above or near the branches. -- denotes bootstrap support less than 50%. Scale bar represents 0.03 substitutions per nucleotide position.
Contrasting fast and slow ITCZ migration linked to delayed Southern Ocean warming
<p>Codes and data for the figures in the paper: Contrasting fast and slow ITCZ migration linked to delayed Southern Ocean warming</p>
Second Opinion Machine Learning for Fast-Track Pathway Assignment in Hip and Knee Replacement Surgery
<p>This is the anonymized training dataset for the article "Second Opinion Machine Learning for Fast-Track Pathway Assignment in Hip and Knee Replacement Surgery: The Use of Patient-Reported Outcome Measures", aimed at developing Machine Learning models for deciding on optimal pathway assignment for total joint replacement patients.</p>
Influence of Ramadan Fasting on Acute and Delayed Postural Control in Elite Judokas
Open the record for dataset details and reuse information.
GC-MS Combined with Fast GC e-nose for the Analysis of Volatile Components of Chamomile (Matricaria chamomilla L.) - Supplementary Materials
Open the record for dataset details and reuse information.
Electric Vehicle Fast-Charging Software: Architectural Considerations Towards Trustworthiness
Open the record for dataset details and reuse information.
Diverse root strategies associated with fast to slow resource acquisition vary among plant growth forms
<p>Root acquisition strategies at regional and global scales are largely associated with climate, soil resource availability, and plant phylogeny, yet the drivers at the local scale are not well-quantified. We sampled 115 species across five growth forms (i.e. trees, shrubs, lianas, herbs, and ferns) from a temperate forest and measured seven key functional traits of first-order roots, including root morphology, anatomy, and chemistry. Most trait variations were greater among growth forms than within them. Importantly, species aggregated in root economics space separately by growth forms, illustrating consistent differences in soil resource strategies among growth forms from fast to slow acquisition. Such diverse strategies among plant growth forms may allow species to avoid strong competition and promote species coexistence in a local forest community. These findings improve our understanding of the mechanisms underlying community assembly and stability from a below-ground perspective.</p>
HoVer-NeXt: A Fast Nuclei Segmentation and Classification Pipeline for Next Generation Histopathology - Datasets
<p>This repository contains training and validation data for</p> <p><strong>HoVer-NeXt: A Fast Nuclei Segmentation and Classification Pipeline for Next Generation Histopathology </strong></p> <p><strong>Accepted for Oral Presentation at MIDL2024: <a href="https://openreview.net/pdf?id=3vmB43oqIO">https://openreview.net/pdf?id=3vmB43oqIO</a> <br></strong></p> <p><strong>More information and code are available at <a href="https://github.com/digitalpathologybern/hover_next_inference" target="_blank" rel="noopener">https://github.com/digitalpathologybern/hover_next_inference</a></strong></p> <p>Modified Lizard dataset to include mitosis (lizard_mitosis.zip), mitosis dataset (mitosis_ds.zip) and a holdout eosinophil validation set (eos_eval.zip)</p> <p>mitosis_ds.zip also contains the hold-out H&E mitosis test set.</p> <p>The original lizard dataset was createdy by Simon Graham et al. and was shared under CC BY-NC-SA 4.0. The tile-based dataset can be downloaded from <a href="https://conic-challenge.grand-challenge.org/Data/">https://conic-challenge.grand-challenge.org/Data/</a> after registering for the challenge. We modify the dataset by including an additional mitosis class, however note that there are a number of mitosis which are still not (correctly annotated).</p>
Fast Attack Graph Defense Localization via Bisimulation
<p>The submission will include the following artifacts:</p> <ul> <li>Paper: Fast Attack Graph Defense Localization via Bisimulation</li> <li>Datasets I-IV: hodlings security findings which used to generate attack graphs</li> <li>Evaluation script: used to create the tables and figure in the evaluation section from Results.csv</li> <li>Results and Figures: data analysis and visualization presented in the evaluation section<br><br></li> </ul>
Neural Substrates for Early Data Reduction in Fast Vision: A Psychophysical Investigation
<p><span>The name of each ‘.mat’ file reports the subject code, the condition (Baseline or Flicker), and the task (Sketch, Motion, or Orientation).</span></p> <p><strong><span>For Motion and Orientation tasks:</span></strong></p> <p><span>The matrices contain one row per trial and four columns:</span></p> <p>o <strong>Column 1:</strong> trial number</p> <p>o <strong>Column 2:</strong> tested contrast</p> <p><span>o </span><strong><span>Column 3:</span></strong><span> response (1 = left moving/oriented gabor, 2 = right moving/oriented gabor)</span></p> <p><span>o </span><strong><span>Column 4:</span></strong><span> correct response (1 = correct, 0 = wrong).</span></p> <p><strong><span>For the Sketch task:</span></strong></p> <p><span>The matrices contain one row per trial and seven columns:</span></p> <p>o <strong>Column 1:</strong> trial number</p> <p>o <strong>Column 2:</strong> tested contrast</p> <p>o <strong>Column 3:</strong> sketch number</p> <p>o <strong>Column 4:</strong> target image number</p> <p>o <strong>Column 5:</strong> distractor image number</p> <p><span>o </span><strong><span>Column 6:</span></strong><span> response (1 = left image, 2 = right image)</span></p> <p><span>o </span><strong><span>Column 7:</span></strong><span> correct response (1 = correct, 0 = wrong).</span></p> <p><span> </span></p>
Fast emulator of changes in crop yields at different levels of global warming
<p>This is the Online Supplement to the following publication: Ostberg, S., Schewe, J., Childers, K.,<br> and Frieler, K.: Changes in crop yields and their variability at different levels of global warming, Earth System<br> Dynamics, 9, 2018. The Supplement contains a number of additional figures as well as the emulator coefficients<br> needed to apply the emulators presented in the paper to derive yield changes for any given pair of global mean<br> temperature change (<span class="math-tex">\(\Delta\)</span>GMT) and atmospheric CO<sub>2</sub> concentration (pCO<sub>2</sub>). See readme.pdf for details.</p>
Dataset for "Particle-in-cell simulations of the fast magnetosonic mode in a dipole magnetic field: 1D along the radial direction"
<p>Dataset used to produce figures in the paper "Particle-in-cell simulations of the fast magnetosonic mode in a dipole magnetic field: 1D along the radial direction"</p>
Fast Ion Transport in the Quasi-Single Helical Reversed-Field Pinch Raw Figure Data
<p>The raw figure data is in a .xls or .xslx file. Each figure or sub-figure is denoted by sheet title in the .xls file. For 2D data plots, the data for the x-array, y-array, x-error, and y-error are provided. For 3D data plots, the data for x-array, y-array, and z-array are provided. Each dataset within a figure or sub-figure is appropriately labeled with an identifier as the column header.</p>
Sodium channels enable fast electrical signaling and regulate phagocytosis in the retinal pigment epithelium
<p>This dataset contains all patch clamp, confocal and mass spectrometry datasets of our publication 'Sodium channels enable fast electrical signaling and regulate phagocytosis in the retinal pigment epithelium', published in BMC Biology. The data for each figure (fig 1-7) and supplementary figure (1-3) has been collected to an individual zipped folder. For additional information, please contact the corresponding author (Soile Nymark).</p>
Data for "Fast delivery of heralded atom-photon quantum correlation over 12 km fiber through multiplexing enhancement"
<p><span>This dataset is for the research article "Fast delivery of heralded atom-photon quantum correlation over 12 km fiber through multiplexing enhancement".</span></p> <p><span> </span></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.