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3,264 results for “FAST”
High Speed Recordings of 10 healthy untrained subjects during slow and fast Messa di Voce
<p>This dataset contains data of 10 healthy untrained subjects performing Messa di Voce on the vowel /a/. This was done slow and fast. The instruction on the slow task were 3s increasing and 3s decreasing SPL. For the fast task, subjects were instructed to increase and decrease the SPL during 1s each. Data contains all raw data and voice parameters calculated using the Multi Signal Analyzer (MSA) software.</p>
[Dataset for] Whole-brain meso-vein imaging in living humans using fast 7 T MRI
<p>This dataset is associated with:</p> <ul> <li>Gulban, Stirnberg, Tse, Pizzuti, Koiso, Archila-Melendez, Huber, Bollmann, Goebel, Kay, Ivanov, 2025. Whole-brain meso-vein imaging in living humans using fast 7 T MRI (Preprint).</li> </ul> <p>This dataset is also used in:</p> <ul> <li>Pizzuti, Bazin, Ivanov, Dresbach, Peter, Goebel, Gulban, 2024. Multimodal laminar characterization of visual areas along the cortical hierarchy (Preprint).</li> </ul> <p>More data are going to be be added as we progress with our manuscripts though their publications or upon request (please contact Omer Faruk Gulban).</p>
Dataset for On the Relevance of Static Cells for Fast Scale-Up of New Redox Flow Battery Chemistries
<p>Dataset for the results shown in the publications "On the Relevance of Static Cells for Fast Scale-Up of New Redox Flow Battery Chemistries"</p>
External cavity quantum cascade laser vibrational circular dichroism spectroscopy for fast and sensitive analysis of proteins at low concentrations (Data analysis)
<p>This record contains a docker container image of the data evaluation shown in the publication "External cavity quantum cascade laser vibrational circular dichroism spectroscopy for fast and sensitive analysis of proteins at low concentrations". The evaluations can be accessed by running the container and accessing the contained Jupyter Lab via a browser. The calculations are contained in 'Eval_protein_D2O.ipynb'.</p> <p>To run the container (requires docker):</p> <p>1.download 'd2o_vcd.tar'</p> <p>2. in the command line, execute 'docker load -i d2o_vcd.tar'. This will return something like 'Loaded image: <image_name>' with image_name probably being "drhermann/vcd_d2o_00:trial_03"</p> <p>3. then 'docker run -p 8889:8889 <image_name>' replacing the brackets with the actual name of the image, such as drhermann/vcd_d2o_00:trial_03</p> <p>4.In your command line a link starting in 'http://127.0.0.1:8888/lab?token=...' will appear. Open this link in your browser to access the evaluation.</p>
Data for "Fast Warming over the Mongolian Plateau a Catalyst for Extreme Rainfall over North China"
<p>Data and plot scripts for this manuscript <strong>"Fast Warming over the Mongolian Plateau a Catalyst for Extreme Rainfall over North China".</strong></p> <blockquote> <p>The md5 value of this compressed file is b04d6476796901687317045be4abba70</p> </blockquote>
Quantification of Electric Fields in Fast Breakdown during Lightning Initiation from VHF-UHF Power Spectra
<p>The data support the manuscript entitled “Quantification of Electric Fields in Fast Breakdown during Lightning Initiation from VHF-UHF Power Spectra” that is submitted to GRL. These files can be opened by MATLAB. The data can be used freely for scientific purposes with appropriate citation.</p>
NMR assignment of methyl groups in solid-state using 1H-detection and fast MAS - NMR raw and processed data
<p>This data set contains raw NMR data in Bruker format for experimental series on (1) 2,3-13C-labelled microcrystalline alanine, (2) U-13C,15N-labelled N-fomylated microcrystalline tripeptide Met-Leu-Phe, and (3,4) two differently labelled (ILV-C4 and ILV-C5) microcrystalline chicken-alpha-spectrin SH3 domain. Measurements were performed at 14.4 T and 55.5 kHz MAS (alanine), 18.8 T and 55.5 and 98 kHz MAS (fMLF), 23.5 T and 55.5 kHz (SH3 C5), 18.8T and 55.5 and 94.5 kHz MAS (SH3 C5) and 18.8T and 55.5 and 94.5 kHz MAS (SH3 C4). The data set also contains Fourier processed data (spectra) in UCSF format, Sparky project, save and peak list files. Pulse programs for Bruker spectrometers are provided. The data set is complemented with SIMPSON scripts for simulation of spin dynamics under aformentioned conditions.</p>
Fast Hierarchical Games for Image Explanations
<p>As modern complex neural networks keep breaking records and solving harder problems, their predictions also become less and less intelligible. The current lack of interpretability often undermines the deployment of accurate machine learning tools in sensitive settings. In this work, we present a model-agnostic explanation method for image classification based on a hierarchical extension of Shapley coefficients–Hierarchical Shap (h-Shap)–that resolves some of the limitations of current approaches. Unlike other Shapley-based explanation methods, h-Shap is scalable and can be computed without the need of approximation. Under certain distributional assumptions, such as those common in multiple instance learning, h-Shap retrieves the exact Shapley coefficients with an exponential improvement in computational complexity. We compare our hierarchical approach with popular Shapley-based and non-Shapley-based methods on a synthetic dataset, a medical imaging scenario, and a general computer vision problem, showing that h-Shap outperforms the state of the art in both accuracy and runtime. Code and experiments are made publicly available.</p>
Visualizing local fast ionic conduction pathways in nanocrystalline lanthanum manganite by isotope exchange-atom probe tomography - dataset
<p>Raw data for atom probe tomography 2D elemental reconstructions of 18O-exchanged La0.8Sr0.2MnO3 thin films. LSM thin films were deposited by large-area PLD (PVD Systems – PLD 5000) using a 248 nm KrF excimer laser (Lambda Physics – COMPex PRO 205). The layers were deposited on Al<sub>2</sub>O<sub>3</sub> (0001) single crystal substrate (Crystec GmbH). A thin barrier layer of Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>1.9</sub> (SDC) was deposited before the LSM film in order to avoid cationic intermixing at the interface. Both layers were deposited at 700 °C, under an oxygen pressure of 2.6 × 10<sup>−2</sup> mbar, target–substrate distance of 95 mm, laser fluency ≈1.2 J cm<sup>−2</sup> and 5 Hz of laser frequency. The thickness of LSM and SDC layers deposited was ≈45 nm and ≈35 nm, respectively, as measured by spectroscopy ellipsometry (UVISEL, Horiba scientific).The nominal oxygen exchange temperature and time were 550 °C and 1 h and 40 min, respectively. Instrument Cameca LEAP 4000X Si. APT performed at 45.5 K using a 30 pJ laser energy and 500 kHz pulse rate. The flight path length was 90 mm and the ion detection rate was set to 5 ions per 1000 pulses, resulting in a bias range of 5000–7400 V during the data collection. Reconstructions were generated in Cameca's IVAS 3.6.18 software. A systematic energy deficit correction was employed to improve the mass spectral resolution.</p>
Simulation files to accompany the manuscript "Two-dimensional basin-scale seismic site effects in the Kitimat Valley, British Columbia, Canada: A practical example of using a fast hybrid FE/BE method"
<p>Simulation files to accompany the two-dimensional basin-scale seismic site effects investigation in the Kitimat valley, located in the northern coastal region of British Columbia, Canada.</p>
Fig. 1. Spanish slug from Kyiv, August 2017 in Fast Recent Expansion Of The Spanish Slug (Gastropoda, Stylommatophora, Arionidae) Across Ukraine
Fig. 1. Spanish slug from Kyiv, August 2017 (photo I. Balashov).
Dataset of "Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes"
<p>Dataset of the article <em>Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes </em>(<a href="https://doi.org/10.1016/j.expthermflusci.2022.110647">https://doi.org/10.1016/j.expthermflusci.2022.110647</a>). A data-driven method is applied to combine non-time-resolved velocity field and fast probe data, and achieve time-resolved velocity and pressure field.</p> <p>The codes processing data here are on https://github.com/erc-nextflow/Data-driven-pressure-estimation-with-EPOD.</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 949085, NEXTFLOW).</p>
Innate heuristics and fast learning support escape route selection in mice
<p>### Dataset structure</p> <p>Each experimental session (from one mouse on one arena) was composed of one or more recording. Each recording<br> was saved as a separate video and as such the tracking data and stimuli metadata are saved separately for each<br> recording.</p> <p>The tracking data for each recording is saved in a file `DATE_SESSION_RECORDING_tracking.h5` with DLC pose position for<br> four body parts: nose, neck, body and base of the tail.<br> The video data was acquired at 30 or 40 FPS, 30FPS recordings were upsampled so that all tracking data<br> saved here is at 40 FPS.<br> If `_recording` is missing from the filename, the session had only one recording.</p> <p>The `DATE_SESSION_RECORDING_stimuli.csv` files store stimuli metadata for each recording.<br> The columns `overview_frame` and `overview_frame_end` denote stimulus onset and offset.</p> <p>The `session_metadata.csv` stores metadata about all sessions and recordings in the data set.<br> Metadata include mouse name, arena type (1-5) and if the mouse was naive or not (1/0).</p> <p><br> For the analyses in the manuscript, stimulus times were used to define trials and the tracking data in the few seconds<br> after the stimulus onbset was analzed (from stimulus onset to mouse entering the shelter). For convenience we provide<br> `trials.h5` which stores all tracking data and metadata for all trials and `trials_metadata.csv` that stores the metadata only.</p>
Dataset: Code Comparison for Fast Flavor Instability Simulation
<p>This is the data provided in the article "Code Comparison for Fast Flavor Instability Simulation". The python scripts produce all of the plots present in the publication from the *.txt data files. The filenames of the *.txt files indicate the author of the dataset and the figure that the data/script produces. The meaning of each column of data is described in README.md. README.md also contains the git repository locations and commit hashes for the open-source codes used to produce this data.</p> <p>Figure 1: Psur-t</p> <p>Figure 2: P-u-t5000</p> <p>Figure 3: Sfft-k-t0 and Sfft-k-t5000</p> <p>Figure 4: deltaELN-t</p> <p>Figure 5: deltaP-t</p> <p> </p>
REIP: a Reconfigurable Environmental Intelligence Platform and Software Framework for Fast Sensor Network Prototyping - use case dataset
<p>Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, they process it and transform into something useful before uploading to the cloud. However, building sensor networks is costly and very time consuming. It is difficult to build upon other people’s work and there are only a few open-source solutions for integrating different devices and sensing modalities. We introduce REIP, a Reconfigurable Environmental Intelligence Platform for fast sensor network prototyping. REIP’s first and most central tool, implemented in this work, is an open-source software framework, an SDK, with a flexible modular API for data collection and analysis using multiple sensing modalities. REIP is developed with the aim of being user-friendly, device-agnostic, and easily extensible, allowing for fast prototyping of heterogeneous sensor networks. Furthermore, our software framework is implemented in Python to reduce the entrance barrier for future contributions. We show the potential and versatility of REIP in real world applications, along with performance studies and benchmark REIP SDK against similar systems.</p> <p>This dataset was created for the case study in Section 5 of the paper.</p>
Positive effects of fast growth on locomotor performance in pelagic fish juveniles
<p><span>Many laboratory experiments on aquatic vertebrates that inhabit closed water or coastal areas have highlighted negative effects of fast growth on swimming performance. Nonetheless, field studies on pelagic fishes have provided evidence of survival advantages of faster growing individuals. To reconcile this contradiction, we examined the relationship between growth rate and swimming performance as a continuous function for juveniles of chub mackerel (<em>scomber japonicus</em>) using 3D tracking analysis. For experiments, 20, 24, 27, and 30 days post-hatch individuals within the size range of 14.5–25.3 mm were used. We found that the growth–swimming (burst speed) relationship in chub mackerel was substantially positive and it was supported by morphological traits such as muscle area, which were also positively related with growth rate. This finding is consistent with field observations showing selective survival of fast-growing individuals of this species, reconciling the current contradiction between laboratory experiments and field observations. A dome-shaped quadratic curve described the relationship between growth rate and burst speed better than a linear or cubic function, suggesting that growth may trade off with swimming performance, as reported in many previous studies, when it is extremely fast. These results, obtained from the rarely tested offshore species, strongly suggests the importance of experimental verification using animals that inhabit various types of habitats in understanding the principles underlying the evolution of growth–locomotor relationship.</span></p>
A fast, precise, in-vivo method for micron-level 3D models of corals using dental scanners
<p>1. Several sampling and measurement strategies have been developed to assess biological forms in three dimensions (3D), including corals. However, the effectiveness (in speed and precision) of current 3D methods in scanning and model construction are challenging at small scales (μm – mm).</p> <p>2. In this paper, a practical 3D scanning and model construction tool using an intra-oral dental scanner was assessed to measure the surface area and volume of coral juveniles across multiple species. Intra-oral scanners using confocal imaging are fast, precise to the μm scale, and safe to use with live tissue, thereby eliminating the need to harm or kill the animals. The trial was conducted at the National Sea Simulator at the Australian Institute of Marine Science.</p> <p>3. High-quality 3D scans of individual coral juveniles were successfully generated and integrated automatically into high-resolution (μm) mesh from point clouds. The attained average scanning efficiency was < 2 min./individual, without a significant difference in speed given coral complexity or between live colonies or dead coral skeleton.</p> <p>4. Overall, this fast and precise system could become a promising tool for marine environmental surveys and restoration initiatives. This tool also removes the need to sacrifice animals for measurement analysis, thereby increasing conservation and animal welfare.</p>
Multiphysics analysis of an in-core fission product removal system for the Molten Salt Fast Reactor - Dataset
<p>Dataset associated to the conference paper "Multiphysics analysis of an in-core fission product removal system for the Molten Salt Fast Reactor", Proceedings of the International Conference Nuclear Energy for New Europe (NENE2022), Portoroz, Slovenia, September 12–15, 2022.</p>
A fast machine-learning-guided primer design pipeline for selective whole genome amplification
<p>Addressing many of the major outstanding questions in the fields of microbial evolution and pathogenesis will require analyses of populations of microbial genomes. Although population genomic studies provide the analytical resolution to investigate evolutionary and mechanistic processes at fine spatial and temporal scales – precisely the scales at which these processes occur – microbial population genomic research is currently hindered by the practicalities of obtaining sufficient quantities of the relatively pure microbial genomic DNA necessary for next-generation sequencing. Here we present swga2.0, an optimized and parallelized pipeline to design selective whole genome amplification (SWGA) primer sets. Unlike previous methods, swga2.0 incorporates active and machine learning methods to evaluate the amplification efficacy of individual primers and primer sets. Additionally, swga2.0 optimizes primer set search and evaluates strategies, including parallelization at each stage of the pipeline, to dramatically decrease program runtime from weeks to minutes. Here we describe the swga2.0 pipeline, including the empirical data used to identify primer and primer set characteristics, that improve amplification performance. Additionally, we evaluated the novel swga2.0 pipeline by designing primers sets that successfully amplify <em>Prevotella melaninogenica</em>, an important component of the lung microbiome in cystic fibrosis patients, from samples dominated by human DNA.</p>
Companion data of Multi-Phase Task-Based HPC Applications: Quickly Learning how to Run Fast
<p>This is the companion data repository for the paper entitled <strong>Multi-Phase Task-Based HPC Applications: Quickly Learning how to Run Fast</strong> by Lucas Leandro Nesi, Lucas Mello Schnorr, and Arnaud Legrand. The manuscript has been accepted for publication in the <a href="https://www.ipdps.org/ipdps2022/2022-organization.html">IPDPS 2022</a>.</p>
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.