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789 results for “display”
Accessible Oceans: Auditory Display. Ocean Response to Extratropical Storm Hermine
<p>The twenty-one tracks make up an auditory display of the ocean response to extratropical storm Hermine in 2016. The tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/VGWHypmrFPZ1NqzeqZuM">listen online here</a>.</p> <p>The ocean data comes from the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) and the display is based on the <a href="https://datalab.marine.rutgers.edu/ooi-nuggets/extratropical-storm-hermine/">OOI Nugget</a> developed by Dr. Leslie Smith. Please note that the Ocean Labs data nugget does not include sea wave height as part of its graph that we sonified. Storms also impact sea wave height, and Dr. Leslie Smith acquired this data from the OOI so that we could include it in the sonification and auditory display.</p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
Experimental data for the study: "Naturalistic visualization of reaching movements using head-mounted displays improves movement quality and proves high usability compared to conventional computer screens"
<p>The datasets contains the motor performance metrics and the questionnaire responses for two experiments involving a motor task with a VR controller (experiment 1, healthy old participants) or a rehabilitation assistive device (experiment 2, brain-injured patients) and three visualization technologies: an immersive virtual reality (IVR) head-mounted display (HMD), an augmented reality (AR) HMD, and a computer screen (2D screen). The study was performed in the Motor Learning and Neurorehabilitation Laboratory at the University of Bern. All data are stored in “csv” files. The variables inside the files are explained in “DataFrameDescription.rtf”. For questions, please contact L.MarchalCrespo@tudelft.nl.</p>
Humans display a reduced set of consistent behavioral phenotypes in dyadic games
<p>Socially relevant situations that involve strategic interactions are widespread among animals and humans alike. To study these situations, theoretical and experimental research has adopted a game theoretical perspective, generating valuable insights about human behavior. However, most of the results reported so far have been obtained from a population perspective and considered one specific conflicting situation at a time. This makes it difficult to extract conclusions about the consistency of individuals’ behavior when facing different situations and to define a comprehensive classification of the strategies underlying the observed behaviors. We present the results of a lab-in-the-field experiment in which subjects face four different dyadic games, with the aim of establishing general behavioral rules dictating individuals’ actions. By analyzing our data with an unsupervised clustering algorithm, we find that all the subjects conform, with a large degree of consistency, to a limited number of behavioral phenotypes (envious, optimist, pessimist, and trustful), with only a small fraction of undefined subjects. We also discuss the possible connections to existing interpretations based on a priori theoretical approaches. Our findings provide a relevant contribution to the experimental and theoretical efforts toward the identification of basic behavioral phenotypes in a wider set of contexts without aprioristic assumptions regarding the rules or strategies behind actions. From this perspective, our work contributes to a fact-based approach to the study of human behavior in strategic situations, which could be applied to simulating societies, policy-making scenario building, and even a variety of business applications.</p> <p> </p> <p>The data from the "dr Brain" experiment is organized in two separated files: drbrain_users.csv<br> and drbrain_decisions.csv.</p> <p><br> 1.) drbrain_users.csv contains information about the participants of the experiment (or users).<br> There is one row per user, with the following information about each one of them:</p> <p>User_ID: unique ID number to identify the user.<br> Age: user's age<br> Gender: user's gender<br> Experiment_number: Number of the experiment the user participated in. For organizational reasons, our research actually was made 45 experiments (or replicas) run over a period of 2 days, each one run with differnt users. A user was only allowed to participate in one experiment. Each experiment included between 10-25 users typically, and they played around 13-18 game rounds, typically. Each round and each couple of users played in different games (that is, different values of S, Sucker's payoff, and T, Temptation to defect, while the values of P=5 , Punishment, and R=10, Reward, were always fixed).<br> Earnings: number of points the user obtained in total, over all rounds.</p> <p><br> 2.) drbrain_decisions.csv contains the information of the all game rounds for all experiments and all users.<br> User_ID: unique ID number to identify the user. <br> Experiment_number: Number of the experiment the user participated in.<br> Round_number: Number of the round within a given experiment.<br> S: Value for the "Sucker's payoff" in the game of that round.<br> T: Value for the "Temptation to defect" in the game of that round. <br> Game: Name of the game corresponding to those values of S and T for that round<br> Action: Action chosen by the user (C: cooperate, D: defect)<br> Opponent_ID: ID number of the user's opponent in that round. <br> Opponent_Action: Action (C or D) chosen by the user's opponent in that round.</p> <p>--------</p> <p>For more details, see our research article:</p> <p>Humans display a reduced set of consistent behavioral phenotypes in dyadic games.<br> Julia Poncela-Casasnovas, Mario Gutiérrez-Roig, Carlos Gracia-Lázaro, Julian Vicens, Jesús Gómez-Gardeñes, Josep Perelló, Yamir Moreno, Jordi Duch and Angel Sánchez.<br> Science Advances Vol. 2, no. 8, 2016.<br> DOI: 10.1126/sciadv.1600451<br> http://advances.sciencemag.org/content/2/8/e1600451</p>
Papers on Google Scholar using "sonification, auditory display, audification, sonify" as search terms
<p>Data set from a Google Scholar search in January 2023 on the terms "sonification, auditory display, audification, sonify" and added abstracts from various online ressources and keywords (automatically extracted from the abstracts only), containing:</p> <ul> <li>their title,</li> <li>a website/URL (as referenced by Google scholar),</li> <li>author(s),</li> <li>publisher information,</li> <li>their google rank in our search,</li> <li>publication year,</li> <li>the number of citations;</li> <li>paper abstracts;</li> <li>keywords generated from abstracts.</li> </ul>
Accessible Oceans: Auditory Display. Zooplankton Daily Vertical Migration Gets Eclipsed!
<p>The nine tracks make up an auditory display of the daily vertical migration of zooplankton off the coast of Oregon. The tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/92HixRBFY6YEyUgjzO1Y">listen online here</a>.</p> <p>The ocean data comes from the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) and the display is based on the <a href="https://datalab.marine.rutgers.edu/ooi-nuggets/zooplankton-eclipse/">OOI Nugget</a> developed by Dr. Leslie Smith and Dr. Lori Garzio. Please note that there is no track 1B in this version. We removed track 1B in order to reduce redundancy in the display. </p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
Accessible Oceans: Auditory Display. Longterm Axial Seamount Inflation Record
<p>The thirteen tracks make up an auditory display of the Longterm Axial Seamount Inflation Record. The tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/MViV0dJLZjJpFXEHN8EA">listen online here</a>.</p> <p>The display leverages data from NOAA PMEL that extend the record of the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) data back to 1997. This audio display focuses on the long-term pattern observed by bottom pressure recorders where the seafloor inflates (lifts), then an eruption event occurs, and the seafloor drops.</p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
Accessible Oceans: Auditory Display. 2015 Axial Seamount Eruption
<p>The ten tracks make up an auditory display of the 2015 Axial Seamount Eruption. The ten tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/qRKlQUoRe1n8TWDZOhTn">listen online here</a>.</p> <p>The data comes from the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) and the display is based on the OOI Nugget developed by Dr. Leslie Smith. (<a href="https://datalab.marine.rutgers.edu/ooi-nuggets/axial-eruption/">https://datalab.marine.rutgers.edu/ooi-nuggets/axial-eruption/</a>)</p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
Accessible Oceans: Auditory Display. Net flux of CO2 between Ocean and Atmosphere
<p>The seven tracks make up an auditory display of the net flux of carbon dioxide between the ocean and the atmosphere. The seven tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/RhkRBKbRTueE2F86b5QS">listen online here</a>.</p> <p>The data comes from the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) and the display is based on the OOI Nugget developed by Dr. Leslie Smith. (<a href="https://datalab.marine.rutgers.edu/ooi-nuggets/co2-flux/">https://datalab.marine.rutgers.edu/ooi-nuggets/co2-flux/</a>)</p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
Morpho-sedimentary outlines displayed in Figures 1, S1, and S6-S15 of the article "Source-to-sink aeolian fluxes from arid landscape dynamics in the Lut Desert"
<p>Morpho-sedimentary outlines of the aeolian landforms in the Lut Desert.</p>
User Study Data from "Point-and-Shake: Selecting from Levitating Object Displays"
<p>This dataset contains anonymous user study data from the two experiments described in the corresponding CHI 2018 publication.</p>
ALICE Pb-Pb Run 3 event displays (2022 edition)
<p>ALICE Pb-Pb event displays produced with 2022 Pb-Pb data from the third run of the LHC. Multiple points of view and multiple resolutions of the baseline image are provided for completeness.</p>
ALICE Pb-Pb Run 2 event display with red/blue tracks
<p>This event display shows tracks in a Pb-Pb event recorded during Run 2 of the LHC. Individual tracks are shown following a red/blue colour code according to their charge.</p>
Optimizing the Shelling Process of InP/ZnS Quantum Dots Using a Single-Source Shell Precursor: Implications for Lighting and Display Applications
<p>This is the data supporting the manuscript "Optimizing the Shelling Process of InP/ZnS Quantum Dots Using a Single-Source Shell Precursor: Implications for Lighting and Display Applications".</p> <p>Abstract</p> <p>InP/ZnS core/shell quantum dots (QDs), recognized as highly promising heavy-metal-free emitters, are increasingly utilized in lighting and display applications. Their synthesis in a tubular flow reactor enables production in a highly efficient, scalable, and reproducible manner, particularly when combined with a single-source shell precursor, such as zinc diethyldithiocarbamate (Zn(S2CNEt2)2). However, the photoluminescence quantum yield (PLQY) of QDs synthesized with this route remains significantly lower compared to those synthesized in batch reactors involving multiple steps for the shell growth. Our study identifies the formation of absorbing, yet non-emissive ZnS nanoparticles during the ZnS shell formation process as a main contributing factor to this discrepancy. By varying the shelling conditions, especially the shelling reaction temperature and InP core concentration, we investigated the formation of pure ZnS nanoparticles and their impact on the optical properties, particularly PLQY, of the resultant InP/ZnS QDs through UV-vis absorption, steady-state and time-resolved photoluminescence (PL) spectroscopy, scanning transmission electron microscopy (STEM) and analytical ultracentrifugation (AUC) measurements. Our results suggest that process conditions, such as lower shelling temperatures or reduced InP core concentrations (resulting in a lower external surface area), encourage the homogeneous nucleation of ZnS. This reduces the availability of shell precursors necessary for an effective passivation of the InP core surfaces, ultimately resulting in lower PLQYs. These findings explain the origin of persistently underperformed PLQY of InP/ZnS QDs synthesized from this synthesis route and suggest further optimization strategies to improve their emission for lighting and display applications.</p> <p>The data are sorted per techniques used for characterization. Information about the measurement details can be found in README files attached to each technique folder.</p>
NIR spectra display of flexible packaging
<p>Display of NIR spectras of flexible packaging</p> <p>Analysis obtained with Lab Spectrometer Antaris II</p> <p>Coming from flexible packaging waste (french yellow bins) </p>
Suppl. Information to "The tropical coral Pocillopora acuta displays an unusual chromatin structure and shows histone H3 clipping plasticity upon bleaching"
<p><strong>Supplementary File 1:</strong> Multiple alignment for protein sequences of core histones with Pocillopora acuta, Pocillopora damicornis, Acropora digitifera, Nematostella vectensis, Hydra vulgaris, Schistosoma mansoni and Mus musculus. A. Histone H2A; B. Histone H2B; C. Histone H3; D. Histone H4. An asterisk (*) means that the amino acid is conserved between all species.</p> <p><strong>Supplementary File 2</strong>: Original (uncropped and unedited) images used for Figures 1 to 4.</p> <p><strong>Supplementary File 3:</strong> <em>P. acuta</em> nuclei and <em>Symbiodinium</em> count on a Thoma cell counting chamber done over three different nuclei extractions. For each extraction, two counts were performed. P. acuta nuclei were stained with Hoechst 33342 and display a blue fluorescence at 350 nm. Symbiodinium are not damaged by our extraction method and are not permeable to Hoechst. They display a red fluorescence because of their chlorophyl content. Observations were done on a Leica DMLB with objective PL Fluotar 40x and 100x. A text version of the data in the Excel file below.</p> <p>Extraction #1 replicate 1: 102 <em>P. acuta</em> nuclei (Blue) ; 2 <em>Symbiodinium</em> (Red)<br> Extraction #1 replicate 2: 112 <em>P. acuta</em> nuclei (Blue) ; 2 <em>Symbiodinium</em> (Red)</p> <p>Extraction #1 replicate 1: 42 <em>P. acuta </em>nuclei (Blue) ; 0 <em>Symbiodinium</em> (Red)<br> Extraction #1 replicate 2: 55 <em>P. acuta </em>nuclei (Blue) ; 1 <em>Symbiodinium</em> (Red)</p> <p>Extraction #1 replicate 1: 215 <em>P. acuta </em>nuclei (Blue) ; 3 <em>Symbiodinium</em> (Red)<br> Extraction #1 replicate 2: 257 <em>P. acuta</em> nuclei (Blue) ; 5 <em>Symbiodinium</em> (Red)</p> <p>Made at IHPE.</p>
A Systematic Review on the Visualization of Avatars and Agents in AR & VR displayed using Head-Mounted Displays
<p>This repository contains the data for the article "Systematic Review on the Visualization of Avatars and Agents in<br> AR & VR displayed using Head-Mounted Displays" including a BibTex file and supporting figures.</p>
Annotation of inverted repeats displaying features of pble STIR or IR in the hg38 genome model
<p>Annotation of inverted repeats displaying features of pble STIR or IR in the hg38 genome model. The annotation of <em>pble</em>-like inner inverted repeats was done using Palindrome (EMBOSS package). The output file was then filtered using pal2gff (https://github.com/Leelouh/pal2gff/blob/main/pal2gff.py), using as parameters a repeat size between 5 and 15 nucleotides, a spacer between pairs of inverted repeats (IRs) of 2 to 10 nucleotides, and a number of mismatches within repeats ranging from 0 to 1. These parameters were chosen taking into account those of the inner IRs found at ends of invertebrate pbles.</p>
Display of grave goods from the Nilgiri Hills in the British Museum
<p>Graved goods from the burial sites on the tops of the Nilgiri Hills are on permanent display in the Sir Joseph E. Hotung Gallery of China and South Asia at the British Museum.</p>
UBC2019 - A dataset of subjective image quality of head-mounted displays
<p>This is the dataset described in the following publication:</p> <p>"A subjective method for evaluating foveated image quality in HMDs", V. Thirumalai, J. Ribera, J. Xiang, J. Zhang, M. Azimi, J. Kamali, P. Nasiopoulos, <em>Society of Information Display, Display Week</em> - May 2020, San Francisco, CA</p>
Dataset for "Structural diversity with varying disorder enables the multicolored display in the longhorn beetle Sulawesiella rafaelae"
<p><strong>Dataset for</strong> "Structural diversity with varying disorder enables the multicolored display in the longhorn beetle <em>Sulawesiella rafaelae</em>"</p> <p>The data is arranged into a .zip folder, containing the following files (.txt, .tif, jpg files). This data and the descriptions below should be read in conjunction with the manuscript and “Supporting Info”, both of which may be found on the <em>iScience</em> homepage.</p> <p>Doi: https://doi.org/10.1016/j.isci.2020.101339</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.