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318 results for “pictures”
PsPM-HRM5: SCR, ECG and respiration measurements in response to positive/negative IAPS pictures, and neutral/aversive sounds
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements for each of 19 healthy unmedicated participants (8 males and 11 females aged 26.1 +/- 5.4 years) in response to 65 dB and 85 dB sounds as well as the 60 most arousing negative and the 60 most arousing positive (excluding explicit nude) IAPS pictures, presented for 1 s each. ITI was between 4-16 s.</p>
PsPM-trSP1: SCR, and heart beat measurement in response to aversive/neutral IAPS pictures while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) and pulse time stamp (HB) measurements for each of 60 healthy unmedicated participants (30 males and 30 females aged 23.7 +/- 4.8 years) in response to the 45 most arousing negative, and 45 least arousing neutral IAPS pictures, each presented for 1 s each, while listening to regular or random distractor sounds, as described in Bach et al. (2015). ITI was selected randomly on each trial from 7.65 s, 9 s, or 10.35 s. The experiment was preceded by a 2-minute resting period and divided into 3 blocks, separated by resting periods. Each resting period begins and ends with an event marker in the psychophysiological recordings.</p>
PAN-AR: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures
<h1>PAN-AR</h1> <p>This is <strong>PAN-AR</strong> (Panoramas, Ambient Noise & Ambisonics RIRs), a dataset described in the following <a href="https://doi.org/10.1145/3678299.3678332" target="_blank" rel="noopener">paper</a>:</p> <blockquote> <p>Filippo Denti, Davide Fantini, Federico Avanzini and Giorgio Presti. PAN-AR: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures. In <em>Proceedings of the 19th International Audio Mostly Conference</em>, Milan, Italy, September 2024.</p> </blockquote> <p>The dataset includes Spatial Room Impulse Responses (SRIRs) in second-order Ambisonics format, ambient noise recordings, and spherical photos. These data have been captured in four environments with different configurations of the source and listener positions:</p> <ol> <li>Printer room</li> <li>Meeting room</li> <li>Classroom</li> <li>Underground parking area</li> </ol> <p>Panoramas and planimetries are provided in a temporary version. The final version with post-processed panoramas and complete planimetries will be available soon. An example of the final panoramas is provided for position A of the printer room, while an example of complete planimetry is provided for the printer and the meeting rooms.</p> <h2>SOFA</h2> <p>The SRIRs are also provided in SOFA format <a href="https://sofacoustics.org/data/database/pan-ar/" target="_blank" rel="noopener">here</a>.</p> <h2>How to cite</h2> <p>If you use the PAN-AR dataset, please cite the following <a href="https://doi.org/10.1145/3678299.3678332" target="_blank" rel="noopener">paper</a>:</p> <pre><code>@inproceedings{denti2024panar,</code><br><code> title = {{PAN-AR}: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures},</code><br><code> author = {Denti, Filippo and Fantini, Davide and Avanzini, Federico and Presti, Giorgio},</code><br><code> year = {2024},</code><br><code> month = {September},</code><br><code> booktitle = {Proceedings of the 19th International Audio Mostly Conference (AM '24)},</code><br><code> location = {Milan, Italy},</code><br><code> publisher = {ACM},</code><br><code> isbn = {979-8-4007-0968-5/24/09},</code><br><code> doi = {10.1145/3678299.3678332}</code><br><code>}</code></pre>
HyPer SMM wind tunnel tests: PIV pictures
<p>In this study, windblown sand transport on flat ground is reproduced by means of Wind-Sand Tunnel Tests (WSTT) carried out in the wind tunnel L-1B of von Karman Institute for Fluid Dynamics. The aim of WSTT is twofold. On one hand, they are intended to characterize the incoming sand flux in open field conditions. On the other hand, they allow to properly tune cheaper Wind-Sand Computational Simulations. The wind tunnel setup implements a uniform 5-meter-long sand fetch as sand source. The wind speed boundary layer is characterized through 2D Particle Image Velocimetry (PIV) technique. Wind flow state variables are assessed along the sand fetch by setting the wind speed equal to 1.3, 1.5, 2 times the threshold one. For the complete wind tunnel setup and data analysis please refer to: Raffaele L., Coste, N., and Glabeke G. "Life-Cycle Performance and Cost Analysis of Sand Mitigation Measures: Toward a Hybrid Experimental-Computational Approach." Journal of Structural Engineering 148.7 (2022): 04022082.</p> <p>The study has been developed in the framework of the MSCA-IF-2019 research project Hybrid Performance Assessment of Sand Mitigation Measures (HyPer SMM, https://hypersmm.vki.ac.be/). This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant Agreement No. 885985</p>
Collection of Algae pictures - sea sample campain - Liguria 2020-2021
<p>The present dataset is the output of the project Euro Trans Bio @lgawarning (ETB-2017-028).</p> <p>@lgawarning amied to develop a web platform to collect all the water sample information obtained, i.e. algal cell type, number and toxicity potential, in order to rapidly observe Harmful Algal Bloom (HABs) distribution and risk.</p> <p>The project consisted of the design and development of a portable integrated hardware/software system for in situ monitoring of algal cells consisting of a glass plankton counting chamber, a portable microscpe to be used with a smartphone (DIPLE) and a specific mobile application for the acquisition and management of images. This system allow to view and photograph, in real time and in situ, individual microalgae and discriminating them from other non-hazardous organisms or organic matter (e.g. pollens). Images are automatically tracked on a dedicated web platform for data collection and analysis.</p> <p>The system was then adopted for mass use in the citizen-science activity of NAUTILOS project (European Union’s Horizon 2020 101000825)</p>
HyPer SMM wind tunnel tests: PTV pictures
<p>In this study, windblown sand transport on flat ground is reproduced by means of Wind-Sand Tunnel Tests (WSTT) carried out in the wind tunnel L-1B of von Karman Institute for Fluid Dynamics. The aim of WSTT is twofold. On one hand, they are intended to characterize the incoming sand flux in open field conditions. On the other hand, they allow to properly tune cheaper Wind-Sand Computational Simulations. The wind tunnel setup implements a uniform 5-meter-long sand fetch as sand source. The sand flux saltation layer are characterized through Particle Tracking Velocimetry (PTV) technique. Sand transport is assessed along the sand fetch by setting the wind speed equal to 1.3, 1.5, 2 times the threshold one. For the complete wind tunnel setup and data analysis please refer to: Raffaele L., Coste, N., and Glabeke G. "Life-Cycle Performance and Cost Analysis of Sand Mitigation Measures: Toward a Hybrid Experimental-Computational Approach." Journal of Structural Engineering 148.7 (2022): 04022082.</p> <p>The study has been developed in the framework of the MSCA-IF-2019 research project Hybrid Performance Assessment of Sand Mitigation Measures (HyPer SMM, https://hypersmm.vki.ac.be/). This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant Agreement No. 885985</p>
Sample dataset: ovitrap sticks pictures and observed egg count
<p>This dataset consists of 300 ovitrap sticks pictures that contain at least one <em>Aedes aegypty</em> egg. The pictures were taken with an iPhone 7 mobile phone and were used to assess the performance of a mosquito egg counter algorithm and application (<a href="https://ovitrap-monitor.netlify.app/">https://ovitrap-monitor.netlify.app/</a>). The ovitraps are part of a weekly surveillance program carried out in the city of Córdoba (Argentina) by the Health Ministry authorities. This dataset is a smaple obtained between December 2021 and March 2022. We also include a text file with the code of the ovitraps and the number of eggs counted by a technician under magnifying glasses (i.e., observed counts).</p>
Dataset: Eigenmike-DRIRs, KEMAR 45BA-BRIRs, RIRs and 360° pictures captured at five positions of a small conference room
<p>A data set was created to study the position dependent perception of room acoustics in case of a small conference room. Binaural room impulse responses (BRIRs) were measured with KEMAR 45BA at 5 different potential listening positions. To keep the direct sound similar the Genelec 1030A two-way loudspeaker was always placed at a distance of 2.5m. In one condition, the loudspeaker was turned towards the listening position, in the other condition it was turned by 180° to achieve an indirect reproduction with low direct sound energy. Furthermore, an mh acoustics Eigenmike was placed at each of the five listening positions and 32-channel directional room impulses responses (DRIRs) as well as an omnidirectional room impulse response (RIR) were captured where the center of the head was placed before.</p> <p>Additionally, 360° visual footages were captured with a GoPro Omni spherical camera array to provide audiovisual impressions of the listening situation at the five positions. </p>
PsPM-RRM3: SCR, ECG and respiration measurement in response to aversive/arousing IAPS pictures, and neutral/aversive sounds
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements for each of 20 healthy unmedicated participants (10 males and 10 females aged 25.3 +/- 5.1 years; male/female numbers were misprinted in Bach et al. 2016) in response to negatively and positively arousing IAPS pictures and neutral (65 dB) and aversive (85 dB) white noise sounds. All stimuli had 1 s duration. ITI was selected randomly on each trial from 40 s, 45 s or 50 s.</p>
Gamma-ray picture book.
<p>A set of plots related to gamma-ray and hadron initated air showers.</p> <p>Note that this is a rather random selection of plots and prepared a long time ago (in 2005).</p> <p><a href="https://github.com/GernotMaier/gamma-ray-picturebook/blob/main/gamma_picturebook.pdf">gamma_picturebook.pdf</a> gives an overview of typical distributions important for ground-based gamma-ray astronomy. Additional distributions can be found in the folder <a href="https://github.com/GernotMaier/gamma-ray-picturebook/blob/main/shower-distributions">shower-distributions</a>.</p>
Code and data associated with: Searching the web builds fuller picture of arachnid trade
<p>Data and code used in the paper: Searching the web builds fuller picture of arachnid trade. Throughout the methods we have indicated the stage of analysis each data component was used and the code script connected. We have numbered to code and data supplements to reflect as closely as possible the order in which data generation and summary was undertaken. The following provide additional details linked to each of the data files.</p> <p>Data S1 - Website data: lang = language of the search engine used, ad hoc websites had language described after discovery; engine = the search engine used; page = the page on which the website appeared from the search engine; searchdate = search date in YYYY-mm-dd HH:MM:SS; link = link to the webpage, redacted to protect website identity; reviewdate = date revewied for arachnids being sold and search strategy; sells = whether the website sells arachnids (1 == sells); allow = whether the site explcicilt forbids automated searching (1 == allows, NA when search method was not fully automated, e.g., single page); type = the type of the website (e.g., trade, classified ads); order = whether arachnids where organised in a particular ways; target = a refined target URL to start search; method = the search method chosen, see methods for details; refine = any refinement or filter than could constrain the scope of the website to be searched; spages = the number of pages required to cycle through to cover the entire stock (also separated by ; if multiple cycles where needed or multiple single pages could be easily collected); prelimCheck = whether the website passed initial checks for arachnid selling; notes = any details that might need special attention during searches; webID = code used for subsequent data summary.</p> <p>Data S2 - Raw keyword searches outputs: species keywords. sp = the modern species or genus that a keyword is associated with; page = the number of the page the keyword was detected on; keyw = the exact keyword that was detected; spORgen = whether the keyword was a species binomial or just genus; termsSurrounding = the words surrounding a genus keyword detection (only applies to Data S3); webID = the website ID.</p> <p>Data S3 – Raw keyword searches outputs: genus keywords. sp = the modern species or genus that a keyword is associated with; page = the number of the page the keyword was detected on; keyw = the exact keyword that was detected; spORgen = whether the keyword was a species binomial or just genus; termsSurrounding = the words surrounding a genus keyword detection (multiple detections separated by ;); webID = the website ID.</p> <p>Data S4 - Raw keyword search outputs: temporal sample. sp = the modern species or genus that a keyword is associated with; page = the number of the page the keyword was detected on; keyw = the exact keyword that was detected; spORgen = whether the keyword was a species binomial or just genus; termsSurrounding = the words surrounding a genus keyword detection (multiple detections separated by ;); webID = the website ID; timestamp.parse = the timestamp extracted from the archived web page; year = a simplified timestamp including only the year.</p> <p>Data S5 - LEMIS data used. An arachnid filtered version of <sup>74,75</sup>.</p> <p>Data S6 - CITES trade database data used <sup>76</sup>.</p> <p>Data S7 - CITES appendices data used <sup>77</sup>.</p> <p>Data S8 - IUCN Redlist data used <sup>78</sup>.</p> <p>Data S9 - Compiled final dataset, with data deriving from WSC, Scorpion files, ITIS, WAM and the data collection process. speciesId = a numeric code, one per species; clade = the clade the species belongs to; family = the family the species belongs to; genus = the genus of the species; species = the species epithet; author = the species authority name; year = the species authority year; parentheses = whether parentheses are needed with the authority; distribution = WSC original distribution descriptions; invalid = whether the species is considered valid; source = the species source, either World Spider Catalogue, Scorpion files, ITIS or WAM; accName = the species binomial being used as our accepted name; allNames = the accepted species binomial and all synonyms; allGenera = the accepted genus, and all other genera the species has belonged to at one point; onlineTradeSnap = whether the species was detected via a match to the accName in the snapshot data; onlineTradeSnap_Any = whether the species was detected via any synonym in the snapshot data; onlineTradeSnap_genus = whether the genus was detected via a match to the genus in the snapshot data; onlineTradeSnap_genusAny = whether the genus was detected via any synonym in the snapshot data; onlineTradeTemp = whether the species was detected via a match to the accName in the temporal data; onlineTradeTemp_Any = whether the species was detected via any synonym in the temporal data; onlineTradeTemp_genus = whether the genus was detected via a match to the genus in the temporal data; onlineTradeTemp_genusAny = whether the genus was detected via any synonym in the temporal data; onlineTradeEither = whether the species was detected via a match to the accName in the temporal data or snapshot data; onlineTradeEither_Any = whether the species was detected via any synonym in the temporal data or snapshot data; LEMIStrade = whether the species was detected via a match to the accName in the LEMIS data; LEMIStrade_Any = whether the species was detected via any synonym in the LEMIS data; LEMIStrade_genus = whether the genus was detected via any synonym in the LEMIS data; LEMIStrade_genusAny = whether the genus was detected via any synonym in the LEMIS data; CITEStrade = whether the species was detected via a match to the accName in the CITES trade database data; CITEStrade_Any = whether the species was detected via any synonym in the CITES trade database data; CITEStrade_genus = whether the genus was detected via any synonym in the CITES trade database data; CITEStrade_genusAny = whether the genus was detected via any synonym in the CITES trade database data; CITESapp = the CITES appendix the species is listed under using an exact match to the accName; CITESapp_Any = the CITES appendix the species is listed under using any match to any of the species’ synonyms; redlist = the IUCN Redlist category the species is listed under using an exact match to the accName; redlist_Any = the IUCN Redlist category the species is listed under using any match to any of the species’ synonyms; extactMatchTraded = the species is detected in any of the trade sources via a match to the accName; anyMatchTraded = the species is detected in any of the trade sources via a match to any species’ synonym.</p> <p>Data S10 - Forum listings of “What species are you currently keeping” from an online fora posted between 9th September 2021 and 9th October 2021, to provide an idea of online discussions. Each user with a separate list is provided in a separate tab. Morph_collector is the same as poster1, but the potential cryptic species or morphs are noted separately to make them clearer.</p> <p>Data S11 – Distribution information for spiders. Only two columns used in summaries: accName = the accepted name used throughout summaries; NAME = the country name the spider occurs in.</p> <p>Data S12 - Distribution information for scorpions. species = the accepted name used throughout summaries; NAME = the country name the scorpions occurs in.</p> <p>Code S1 - Search URL Extract.R</p> <p>Code S2 - Retrieve web data.R</p> <p>Code S3 - Temporal Classified Ads.R</p> <p>Code S4 - Keyword Generation.R</p> <p>Code S5 - Keyword Search.R</p> <p>Code S6 - LEMIS filter and summary.R</p> <p>Code S7 - Compiling results.R</p> <p>Code S8 - Summary Figures.R</p> <p>Code S9 - Temporal Figures.R</p> <p>Code S10 - New description figure.R</p> <p>Code S11 - Term exploration.R</p> <p>Code S12 - LEMIS summary and mapping.R</p>
Krefeld_Framed_Pictures_Silk_Museum_Mingei
<p>Documentation material from the Silk pilot of the Mingei project</p>
Menchukha valley - picture files
<p>These pages and the accompanying files contain some initial information regarding the history, ethnography, ethnobotany and language of the Menchukha valley in West Siang district of Arunachal Pradesh, India.</p> <p>This information was collected between November 7<sup>th</sup> and 10<sup>th</sup> 2017.</p>
Global Empirical Picture of Magnetospheric Substorms Inferred from Multi-Mission Magnetometer Data
<p>Data associated with Journal of Geophysical Research: Space Physics article titled: "Global Empirical Picture of Magnetospheric Substorms Inferred from Multi-Mission Magnetometer Data". This includes all the digital data that was used in constructing the Figures from the main and supplementary text, along with files containing the fit set of coefficients and parameters for the model, and files describing the subset of magnetometer used for fitting the model. </p>
PsPM-trSP3: SCR measurement in response to aversive/arousing/neutral IAPS pictures while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) measurements for each of 40 healthy unmedicated participants (20 males and 20 females aged 21.9 +/- 3.8 years) in response to the 16 most arousing negative, and most arousing positive (excluding explicit nude) and 16 least arousing neutral IAPS pictures, presented for 1 s each in 1 block, while listening to regular or random distractor sounds, as described in Bach et al. (2015). ITI was 4 s, plus a variable delay of around 0.4 s for image loading.</p>
Fig. 2.28. Picture for H in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.28. Picture for H-RTI digitisation. The highlights on the black spheres allow the algorithm to reconstruct a RTI model.
How many words is a picture worth? Attention allocation on thumbnails versus title text regions: Dataset
<p>Dataset for the following publication: https://jainlab.cise.ufl.edu/eyetrack-onlineux.html</p> <p>How many words is a picture worth? Attention allocation on thumbnails versus title text regions, Yandandul, Chaitra and Paryani, Sachin and Le, Madison and Jain, Eakta, ACM Symposium on Eye Tracking Research & Applications. (ETRA)</p> <p> </p>
Functional Brain Networks of Picture Naming in Broca's Aphasia and Healthy Controls
<p>The data were from the picture-naming task with MEG scanning. </p> <p>Brain networks of ".net" format: Each network has 776 regions that were derived by subdividing USCBrain Atlas. Phase-locking values (PLV) were calculated between the 776 regions in a gamma-band of 30-45Hz. PLVs were normalized (z-PLVs) by using the mean and standard deviation of the 200-ms pre-stimulus baseline. The edges were weighted by z-PLVs. </p> <p>Vector files of ".vec" format: Each file contains activations, viz., amplitude, of regions. There are two types of amplitude. One is the estimated electric density in a physical unit of picoampere. Another is the z-score of amplitude calculated through comparison with a baseline of –200 ms.</p> <p>We provided both the group-averaged files (named as b999 for the Broca group and c999 for the control group) and the individuals' files (b1 to b5 for the Broca's aphasia and c1 to c5 for the control persons).</p> <p>We also provided two ".clu" files. One is the partition file of eight functional modules in two hemispheres. Another is the partition file of two hemispheres. </p> <p>The .net, .vec., and .clu files can be imported to Pajek for further interpretations and visualizations. </p> <p> </p>
Fig. 1 in TreePics: visualizing trees with pictures
Fig. 1. Screenshot of the page with tree visualizations and associated images, showing the phylogenetic trees and the associated thumbnails. The selected thumbnails (red squares) also appear in the list below the tree.
PsPM-trSP2: SCR measurement in response to neutral IAPS pictures while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) measurements for each of 61 healthy unmedicated participants (30 males and 31 females, misprinted in Bach et al. 2015, aged 25.7 +/- 4.5 years) in response to the 45 least arousing neutral IAPS pictures, presented for 1 s each in 3 blocks, while listening to regular or random distractor sounds, as described in Bach et al. (2015). Inter stimulus interval was randomly determined as 7.65 s, 9 s, or 10.35 s. Each recording starts with a 2-minute baseline interval.</p>
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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.