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1,506 results for “objects”
Soapstone Object (604-1p5)
**Soapstone object** Location: Unknown site, North Carolina. Period: unknown. Material: soapstone. Dimensions: length, 122.1 mm; width, 114.2 mm; thickness, 79 mm. Notes: Catalog no. 604.1p5. North Carolina Archaeological Collection, Research Laboratories of Archaeology, University of North Carolina at Chapel Hill. Model by Chris LaMack. Source: Objaverse 1.0 / Sketchfab
Guerrero Iron Objects Feature No.1 (2019)
Site 2-04-8MO02343 Multiple Iron Concretions on Bedrock No.1 (2019). Along the eastern edge of the site, closest to where the reef meets deeper water, there are clusters of iron artifacts fused to the bedrock. This is one of two features of concreted iron objects documented in 2019. This particular feature was also modeled in 2108 (see https://skfb.ly/6AL9V), but this newer version shows a slightly broader view. Items observed within this group of artifacts are ship's fasteners, rigging elements, and many unidentified items. Black & white scale = 20 centimeters. Source: Objaverse 1.0 / Sketchfab
Poverty Point Object
Baked earth cooking ball. Poverty Point culture. 1700-1200 BCE 56mm x 43mm x 39 mm, 85.7g From the collection of Billy Guthrie PPO_01 Source: Objaverse 1.0 / Sketchfab
Mystery Object
An object I found while on a walk. * 3D model created by Meshroom, from images taken with an iPhone 8. * Some clean-up to the OBJ was done in Rhino 6 (deleting background noise). Source: Objaverse 1.0 / Sketchfab
ANTH 246 - Object Gallery
Sources: Bard, Kathryn A. *An Introduction to the Archaeology of Ancient Egypt.* West Sussex: John Wiley & Sons, Inc., 2015. Ushabti: http://dms.wellesley.edu/detail.php?term=shabti&module=objects&type=keyword&x=0&y=0&kv=28451&record=9&module=objects Palette: http://cartelfr.louvre.fr/cartelfr/visite?srv=car_not_frame&idNotice=671 Predynastic Vase: http://petriecat.museums.ucl.ac.uk/detail.aspx Ushabti created through photogrammetry on Agisoft Metashape. Palette and vase downloaded from Sketchfab. Gallery created through Blender. Source: Objaverse 1.0 / Sketchfab
Objecte de plom, MAC Ullastret
**CAT**: Possible amulet de plom trobat al fossat de la ciutat ibèrica d'Ullastret. La inscripció, que data de finals del s. III o principis del s. II aC, està escrita en la llengua més antiga coneguda originada al territori català. Encara es desconeix el seu significat. **ES**: Posible amuleto de plomo encontrado en el foso de la ciudad ibérica de Ullastret. La inscripción, que data de finales del s. III o principios del s. II aC, está escrita en la lengua más antigua conocida originada en el territorio catalán. Aún se desconoce su significado. **ENG**: Presumed amulet made of lead found in a trench of the Iberian site of Ullastret. Its inscription, engraved between the 3rd and 2nd century BC, was writen in the oldest native language known in the catalan territory. Its meaning is still unknown. [MAC ULLASTRET](http://macullastret.cat) Source: Objaverse 1.0 / Sketchfab
Guerreo Iron Objects Feature No.2 (2019)
Site 2-04-8MO02343 Multiple Iron Concretions on Bedrock No.2 (2019). Along the eastern edge of the site, closest to where the reef meets deeper water, there are clusters of iron artifacts fused to the bedrock. This is one of two features of concreted iron objects documented in 2019. Items observed within this feature include ship's fasteners, rigging elements, and many unidentified items. Black & white scale = 20 centimeters. Source: Objaverse 1.0 / Sketchfab
Wooden Object, Kirkjubø - Træ 11
Høgdur trælutur úr Kirkjubø. *Carved wooden object from Kirkjubø, Faroe Islands.* Created by Petur Hansen, using Artec Eva scanner and Artec Studio 16. Dimensions: 146cm x 39.5cm x 5cm. Source: Objaverse 1.0 / Sketchfab
Spike-timing based coding in neuromimetic tactile system enables dynamic object classification
<p>Coding dynamic tactile information in spike timing is essential to human haptic exploration and dexterous object manipulation. Conventional electronic skins generate frames of tactile signals upon interaction with objects and are unfortunately ill-suited for efficient coding of temporal information and rapid feature extraction. Here, we report a neuromorphic tactile system that uses spike timing, especially the first-spike timing, to code dynamic tactile information about touch and grasp. This strategy enables the system to seamlessly code highly dynamic information with millisecond temporal resolution on par with the biological nervous system, yielding dynamic extraction of tactile features. Upon interaction with objects, the system rapidly classifies them in the initial phase of touch and grasp, thus paving the way to fast tactile feedback desired for neuro-robotics and neuro-prosthetics.</p>
Multi-objective optimization of a renewable fuel supply chain regarding cost, land use, and water use - Supplementary Materials
<p><strong>This repository contains supporting data for: "Multi-objective optimization of a renewable fuel supply chain regarding cost, land use, and water use"</strong></p> <ol> <li> <p><strong>Input Data</strong>: This file includes the model input data.</p> </li> <li> <p><strong>Payoff Matrix Solution</strong>: This file contains all decision variables of payoff matrix solutions (Cost optimal, Land-use optimal, and Water-use optimal solution).</p> </li> <li><strong>Compromise solution</strong>: This file contains all decision variables of the compromise solution.</li> <li> <p><strong>Pareto Curve</strong>: This file presents the Pareto curve solution. </p> </li> <li><strong>Pareto Curve Solution</strong>: This file contains all decision variables in each of the Pareto curve solutions. </li> </ol>
Figure 18 in Objective identification of Lepidocyclina (Foraminifera) species from the Eocene of Cuba based on growth-invariant morphometric characters
Figure 18. Mean growth functions of row measurements.
Figure 16 in Objective identification of Lepidocyclina (Foraminifera) species from the Eocene of Cuba based on growth-invariant morphometric characters
Figure 16. Mean growth functions of chamberlet measurements.
Figure 9 in Objective identification of Lepidocyclina (Foraminifera) species from the Eocene of Cuba based on growth-invariant morphometric characters
Figure 9. Cluster analysis based on Ward's method. Sample locations indicated by colours.
Observation of Gravitational Waves from the Coalescence of a 2.5-4.5 Msun Compact Object and a Neutron Star --- Data Release
<p>This data release contains the analysis results and data behind the figures of the GW230529 discovery paper (<a href="https://urldefense.com/v3/__https://dcc.ligo.org/LIGO-P2300352/public/__;!!Dq0X2DkFhyF93HkjWTBQKhk!W4i4x3JfGgemcFsnnEYP5qxiknddvrG1LWpTLjs_JGK907kTrEBkS8o6i5T6RUFMX0v04jCPhtTq9K2SLcv_4g$" target="_blank" rel="nofollow noreferrer noopener">https://dcc.ligo.org/LIGO-P2300352/public/</a>). Strain data for this event (the L1:GDS-CALIB_STRAIN_CLEAN_AR channel) can be downloaded on GWOSC (<a href="https://doi.org/10.7935/6k89-7q62" target="_blank" rel="noopener">https://doi.org/10.7935/6k89-7q62</a>).</p> <p>The PESummary metafile containing the parameter estimation posterior samples for all analyses performed in the paper (<strong>posterior_samples.h5</strong>) and skymap fits file (<strong>skymap_combined_PHM_high_spin.fits</strong>) for the preferred parameter estimation analysis (high-spin, combined samples using binary black hole waveforms) can be downloaded directly as individual files.</p> <p>The other analysis results are grouped by type: rates, populations, searches, and tidal. The <strong>figure_scripts.tar.gz</strong> file contains all the paper figures in jpeg format along with a Jupyter notebook to reproduce them and additional required helper scripts. Example code for working with the individual result files is given in the <strong>PaperPlots.ipynb</strong> notebook included in this tar file.</p> <p>In brief, the <strong>rates.tar.gz</strong> file contains two files that each include a subset of the rates probability distributions shown in Fig. 3 of the paper. The <strong>populations.tar.gz</strong> file contains all the data behind Figs. 4-8, with subdirectories for each of the three population analyses considered in the paper: Binned Gaussian Process, NSBH-pop, and Power-Law + Dip + Break. In addition to the data behind the figures, the Power-Law + Dip + Break subdirectory additionally includes two *result.json files for the hyper-parameter posterior samples. These files have the same format as the corresponding NSBH-pop *result.json files and can be manipulated in the same way, as shown in the figures notebook.</p> <p>The <strong>searches.tar.gz</strong> file contains the data behind Figs. 9-11 for each of the three search pipelines whose results are included in the paper. Finally, the <strong>tidal.tar.gz</strong> file contains the four probability distributions plotted in Fig. 14. All other figures are produced only using the posterior_samples.h5 file.</p>
HRRR Convective Objects for "Comparing Distributions of Overshooting Convection in HRRR Forecasts to Observations"
<p>Data files for all convective objects identified from High-Resolution Rapid Refresh (HRRR) model forecasts for the Contiguous United States initialized at 06 UTC every day of May and July 2021. Convection was defined in the following two ways, one corresponding to each file uploaded here:</p> <ul> <li>Meeting the criteria for convection defined by the Storm Labelling in Three-Dimensions (SL3D; Starzec et al. 2017) algorithm</li> <li>Satisfying two vertical velocity thresholds (2 m/s at 4 km altitude and 5 m/s at 8 km altitude)</li> </ul>
Developmental Mouse Brain scRNAseq Giotto Object
<p>Giotto object created from the single cell mouse brain atlas dataset from <a href="https://www.nature.com/articles/s41586-021-03775-x">Manno et al. 2021</a> (https://doi.org/10.1038/s41586-021-03775-x). This object contains expression information and cell annotations of developmental mouse brain cell types that are used with spatial DWLS deconvolution of Stereo-seq data in the Giotto Suite manuscript.</p> <p>The original data was downloaded from <a href="http://mousebrain.org/development/downloads.html">http://mousebrain.org/development/downloads.html </a>as a .loom file, and then loaded into Giotto.</p>
Himax Dataset for Object Detection of Bottles and Tin-Cans
<p>Object detection Dataset was collected with a Himax HM01B0 greyscale camera. The datasets contain QVGA images of Bottles and Tin-Cans and their respective labels. The labels follow the PascalVOC format specification. The dataset also include tfrecod files for ease of use with tensorflow. This dataset was used in our paper Bio-inspired Autonomous Exploration Policies with CNN-based Object Detection on Nano-drones</p>
Supplementary methods and data for: Dogs with a vocabulary of object label remember labels for at least two years
<p>Long-term memory of words has a crucial role in the developing abilities of young children to acquire language. In dogs, the ability to learn object labels is present in only a small group of uniquely Gifted Word Learner (GWL) dogs. The ability of these dogs to acquire large vocabularies consisting of hundreds of names of dog toys through naturally occurring interactions in human families presents them as a valid model for studying language-related cognitive mechanisms. As they are very rare, little is known about the mechanisms through which they acquire such large vocabularies. In the current study, we tested the ability of five GWL dogs to retrieve 12 labelled objects two years after the object-label mapping acquisition. The dogs proved to remember the labels of between 3-9 objects. The results shed light on the process by which GWL dogs acquire an exceptionally large vocabulary of object names. As memory plays a crucial role in language development, these dogs supply a unique opportunity to study label retention in a non-linguistic species.</p>
Brain Transcriptome Single-cell (BTS) Atlas: Anndata, Seurat Object, CellTypist model, and Disorder Risk Geneplot
<p>Brain Transcriptome Single-cell Atlas (BTS) Anndata, Seurat object, and Celltypist model for further use of the atlas. The Celltypist model can be utilized to accurately annotate cell types in new datasets based on the atlas. Plots illustrating the expression profile for 3,380 neurological disorder risk genes across the atlas are also uploaded. Further availability for the data can be requested by the corresponding author.<br><br>This dataset is published in Kim, S., Lee, J., Koh, I.G. <em>et al.</em> An integrative single-cell atlas for exploring the cellular and temporal specificity of genes related to neurological disorders during human brain development. <em>Exp Mol Med</em> <strong>56</strong>, 2271–2282 (2024). https://doi.org/10.1038/s12276-024-01328-6</p>
Phillips 2023 acute & repeated cocaine object
<p>Contains the integrated acute & repated cocaine R object published in Phillips et al 2023 <em>Molecular Cellular Neuorscience</em></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.