Medical Subject Headings (MeSH) is a hierarchically-organized terminology for indexing and cataloging of biomedical information. It is used for the indexing of PubMed and other NLM databases. Please see the Terms and Conditions for more information regarding the use and re-use of MeSH. NLM produces Medical Subject Headings XML, ASCII, MARC 21 and RDF formats. Updates to the data files are made according to the following schedule: MeSH XML MeSH Descriptor files updated annually MeSH Qualifier files updated annually MeSH Supplemental Concept Records (SCR) updated daily (Monday - Friday) MeSH ASCII MeSH Descriptor files updated annually MeSH Qualifier files updated annually MeSH Supplemental Concept Records (SCR) updated daily (Monday - Friday) MeSH MARC21 All files posted monthly MeSH RDF All files posted daily (Monday - Friday)

3D mesh models can be downloaded for free using the index maps available on the service www.geoportal.gov.pl in group of layers „Data for download”

This benchmark aims to provide tools to evaluate 3D Interest Point Detection Algorithms with respect to human generated ground truth. Using a web-based subjective experiment, human subjects marked 3D interest points on a set of 3D models. The models were organized in two datasets: Dataset A and Dataset B. Dataset A consists of 24 models which were hand-marked by 23 human subjects. Dataset B is larger with 43 models, and it contains all the models in Dataset B. The number of human subjects who marked all the models in this larger set is 16. Some of the models are standard models that are widely used in 3D shape research; and they have been used as test objects by researchers working on the best view problem. We have compared five 3D Interest Point Detection algorithms. The interest points detected on the 3D models of the dataset can be downloaded from the link below. Please refer to README for details in the download. Mesh saliency [Lee et al. 2005] : Interest points by mesh saliency Salient points [Castellani et al. 2008] : Interest points by salient points 3D-Harris [Sipiran and Bustos, 2010] : Interest points by 3D-Harris 3D-SIFT [Godil and Wagan, 2011] : Interest points by 3D-SIFT (Please note that some models in the dataset are not watertight, hence their volumetric representations could not be generated. Therefore, 3D-SIFT algorithm wasn't able to detect interest points for those models.) Scale-dependent corners [Novatnack and Nishino, 2007] : Interest points by SD corners HKS-based interest points [Sun et al. 2009] : Interest points by HKS method Please Cite the Paper: Helin Dutagaci, Chun Pan Cheung, Afzal Godil, ?Evaluation of 3D interest point detection techniques via human-generated ground truth?, The Visual Computer, 2012. References: [Lee et al. 2005] Lee, C.H., Varshney, A., Jacobs, D.W.: Mesh saliency. In: ACM SIGGRAPH 2005, pp. 659?666 (2005) [Castellani et al. 2008] Castellani, U., Cristani, M., Fantoni, S., Murino, V.: Sparse points matching by combining 3D mesh saliency with statistical descriptors. Comput. Graph. Forum 27(2), 643?652 (2008) [Sipiran and Bustos, 2010] Sipiran, I., Bustos, B.: A robust 3D interest points detector based on Harris operator. In: Eurographics 2010 Workshop on 3D Object Retrieval (3DOR?10), pp. 7?14 (2010) [Godil and Wagan, 2011] Godil, A., Wagan, A.I.: Salient local 3D features for 3D shape retrieval. In: 3D Image Processing (3DIP) and Applications II, SPIE (2011) [Novatnack and Nishino, 2007] Novatnack, J., Nishino, K.: Scale-dependent 3D geometric features. In: ICCV, pp. 1?8, (2007) [Sun et al. 2009] Sun, J., Ovsjanikov, M., Guibas, L.: A concise and provably informative multi-scale signature based on heat diffusion. In: Eurographics Symposium on Geometry Processing (SGP), pp. 1383?1392 (2009)

Description of the INSPIRE Download Service (predefined Atom): Change of the development plan Im Maschereg, Ortsgemeinde Plaidt - The link(s) for downloading the data sets is/are dynamically generated from Get Map calls to a WMS interface

BodyParts3D organ model data with the polygon reduction rate of 99%. The zip-compressed download files contain multiple files of ELEMENT file ID-specific polygon data in Wavefront OBJ format.

3D textured mesh (photomesh) representing all physical features (e.g. buildings, trees and terrain) across City of Melbourne. The 3D textured mesh is provided in both ESRI scene layer package (SLPK) format and object file format (.obj) accompanied by material (.mtl) and image texture (.jpg) files.

The data has been split into a series of tiles covering the entire municipality. To find the geo-spatial location of each tile, please follow the links below under 'Preview Data' Capture Information - Capture Date: May 2020 - Capture Pixel Size: 2cm ground sample distance - Map Projection: MGA Zone 55 (MGA55) - Vertical Datum: Australian Height Datum (AHD) - Spatial Accuracy (XYZ):Estimated accuracies 0.05m (X), 0.6m (Y), 0.04m (Z).

Preview Data and Download Data: For an interactive sample of the data please see the link below (WebGL browser required - Google Chrome recommended).ESRI Scene Layer Package (SLPK) Format:Photomesh 2020 - SLPK (arcgis.com)Wavefront OBJ Format: Photomesh 2020 - OBJ (arcgis.com)Click on a region of interest within the sample and a ‘Download_URL’ link will display in the pop-up. Usage: Through the download an use of this data you agree to the licensing and disclaimer conditions. While all due care has been taken to ensure the data of this website is accurate, current and available please note: · there may be errors or omission in it · there may be occasions where the data is not available and/or the website will be unavailable. The City of Melbourne and its employees accept no responsibility for any loss, damage, claim, expense, cost or liability whatsoever (including in contract, tort including negligence, pursuant to statue and otherwise) arising in respect of or in connection with accessing, using or reliance upon the data in this website, or the unavailability of the data or the website.

MeSH-CZ-2025-base - training dataset

Czech translation of Medical Subject Headings version 2025 Download more MeSH-CZ data here @ nlk.cz

  License

MeSH-CZ-2025 - training dataset © 2025 by National Medical Library is licensed under Creative Commons Attribution 4.0 International

  Structure

"text1","text2","value","category" "term1","term2","1.0","cat1|cat2"

category - multiple values-codes separated by a pipe… See the full description on the dataset page: https://huggingface.co/datasets/NLK-NML/MeSH-CZ-2025-base.

3D textured mesh (photomesh) representing all physical features (e.g. buildings, trees and terrain) across City of Melbourne. The 3D textured mesh is provided in object file format (.obj) and is accompanied by material (.mtl) and image texture (.jpg) files.

The data has been split into a series of tiles covering the entire municipality. An index file (Tile_Index.kml) is included to indicate the geo-spatial location of each tile. To position the mesh in its real world location, use the origin coordinates found in the metadata file (metadata.xml).

The 3D textured mesh is provided in different levels of detail, as indicated in the file name of the .obj filename. The levels of detail vary from L13 (lowest level of detail) to L20 (highest level of detail).

Capture Information
- Capture Date: May 2018
- Capture Pixel Size: 7.5cm ground sample distance
- Map Projection: MGA Zone 55 (MGA55)
- Vertical Datum: Australian Height Datum (AHD)
- Spatial Accuracy (XYZ): Supplied survey control used for control (Madigan Surveying)

Contents
The download is a zip file containing compressed:
- Object files (.obj)
- Material files (.mtl)
- Image textures (.jpg)
- Metadata (.xml)
- Tile index (.kml)

Preview Data:
For an interactive sample of the data please see the link below (WebGL browser required - Google Chrome recommended).
https://cityofmelbourne.maps.arcgis.com/apps/webappviewer3d/index.html?id=b555219a327b4535a89d8ec6e97780cf

Usage:
Through the download an use of this data you agree to the licensing and disclaimer conditions.
While all due care has been taken to ensure the data of this website is accurate, current and available please note:
· there may be errors or omission in it
· there may be occasions where the data is not available and/or the website will be unavailable.
The City of Melbourne and its employees accept no responsibility for any loss, damage, claim, expense, cost or liability whatsoever (including in contract, tort including negligence, pursuant to statue and otherwise) arising in respect of or in connection with accessing, using or reliance upon the data in this website, or the unavailability of the data or the website.

Download Photomesh data:

A zip file containing all relevant files representing the 3D city mesh model.

Download .ZIP file (9.7GB)

3D mesh models can be downloaded for free using the index maps available on the service www.geoportal.gov.pl in group of layers „Data for download”

The MPAS_Ocean_Shallow_Water_Meshes directory contains planar hexagonal mesh files in NetCDF format necessary for running a verification suite of shallow water test cases for the barotropic solver of ocean models using a mimetic finite volume spatial discretization based on the TRiSK scheme. It also contains mesh plots showing the cell centers, edge centers, vertices, and orientation of the normal vectors at the edges; plots of high resolution meshes superimposed on low resolution ones; plots of state variables interpolated from edges and vertices to cell centers along with the interpolation error; plots of state variables interpolated from a high resolution mesh to a low resolution one; and plots of various spatial operators of the TRiSK scheme applied to the state variables along with their error and convergence plots. The associated code can be cloned from the Github repository Rotating_Shallow_Water_Verification_Suite. Please download the MPAS_Ocean_Shallow_Water_Meshes.zip file, unzip it, and place the resulting directory within the meshes directory of Rotating_Shallow_Water_Verification_Suite.

3D mesh models are three-dimensional visualizations of objects covered with image textures from oblique aerial imagery. The model is created by applying algorithms for automatically matching common points on all images - both oblique and vertical, using data from laser scanning.

3D mesh models can be downloaded for free using the index maps available on the service www.geoportal.gov.pl in group of layers „Data for download”

3D textured mesh (photomesh) representing all physical features (e.g. buildings, trees and terrain) across City of Melbourne. The 3D textured mesh is provided in object file format (.obj) and is accompanied by material (.mtl) and image texture (.jpg) files.

The data has been split into a series of tiles covering the entire municipality. An index file (Tile_Index.kml) is included to indicate the geo-spatial location of each tile. To position the mesh in its real world location, use the origin coordinates found in the metadata file (metadata.xml).

The 3D textured mesh is provided in different levels of detail, as indicated in the file name of the .obj filename. The levels of detail vary from L13 (lowest level of detail) to L20 (highest level of detail).

Capture Information
- Capture Date: May 2020
- Capture Pixel Size: 7.5cm ground sample distance
- Map Projection: MGA Zone 55 (MGA55)
- Vertical Datum: Australian Height Datum (AHD)
- Spatial Accuracy (XYZ): Supplied survey control used for control (Madigan Surveying)

Contents
The download is a zip file containing compressed:
- Object files (.obj)
- Material files (.mtl)
- Image textures (.jpg)
- Metadata (.xml)
- Tile index (.kml)

Preview Data:
For an interactive sample of the data please see the link below (WebGL browser required - Google Chrome recommended).
Photomesh 2020 - SLPK (arcgis.com)

Photomesh 2020 - OBJ (arcgis.com)

Usage:
Through the download an use of this data you agree to the licensing and disclaimer conditions.
While all due care has been taken to ensure the data of this website is accurate, current and available please note:
· there may be errors or omission in it
· there may be occasions where the data is not available and/or the website will be unavailable.
The City of Melbourne and its employees accept no responsibility for any loss, damage, claim, expense, cost or liability whatsoever (including in contract, tort including negligence, pursuant to statue and otherwise) arising in respect of or in connection with accessing, using or reliance upon the data in this website, or the unavailability of the data or the website.

Download Photomesh data:

To download the zip file containing all relevant files representing the 3D city mesh model, please click on the provided link.

MeSH-CZ-2025 RDF

Czech translation of Medical Subject Headings version 2025 published as RDF N-triples Documentation:

https://hhs.github.io/meshrdf/ https://github.com/filak/MTW-MeSH/wiki/RDF-MTW-Data-model

Source and support:

https://github.com/NLK-NML/MeSH-CZ-RDF

Docker:

https://github.com/NLK-NML/MeSH-CZ-RDF-Docker

Download more MeSH-CZ data here @ nlk.cz

  License

MeSH-CZ-2025 RDF © 2025 by National Medical Library is licensed under Creative Commons Attribution… See the full description on the dataset page: https://huggingface.co/datasets/NLK-NML/MeSH-CZ-2025-RDF.

The repository contains 3D meshes of 83 wood samples derived from X-ray computed tomography (CT) data. The samples are a part of the LEIZA reference collection, which were created within the framework of the project "Mass Finds in Archaeological Collections", which was funded by the "Kulturstiftung des Bundes" and the "Kulturstiftung der Länder" from 15.04.2008 to 31.12.2011 as part of the "Program for the Conservation and Restoration of Mobile Cultural Property" (KUR, see www.rgzm.de/kur).

Around 10 years later, the wood samples were digitized using an in-house laboratory X-ray CT system (Diondo d2, Germany) at HSLU with a nominal voxel size between 27 and 44 μm in order to analyse the structure of the interior. 3D models were derived from the CT data and these were cleaned in post-processing, holes closed and the resolution reduced to 0.2 mm. You can download these 3D models here. For each wood sample the following files are available: a file of the 3D mesh in *.stl format and two files with metadata in *.json and *.ttl format. The 3D data acquisition was carried out during November 2019 - April 2021.

The CuTAWAY project was funded by the German Research Foundation (DFG) and the Swiss National Science Foundation (SNSF) from 2019 to 2023 (CuTAWAY - Conservation and Wood Analyses, DFG - 416877131 and SNSF - 200021E_183684).

Access 'Exports by MESH ENTERPRISES' with data on 4 shipments from 1 exporters to 2 importers. Search, filter and download detailed trade records.

Meshback_new

## Overview

Meshback_new is a dataset for object detection tasks - it contains Mesh annotations for 400 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Conceptual novelty analysis data based on PubMed Medical Subject Headings ---------------------------------------------------------------------- Created by Shubhanshu Mishra, and Vetle I. Torvik on April 16th, 2018 ## Introduction This is a dataset created as part of the publication titled: Mishra S, Torvik VI. Quantifying Conceptual Novelty in the Biomedical Literature. D-Lib magazine : the magazine of the Digital Library Forum. 2016;22(9-10):10.1045/september2016-mishra. It contains final data generated as part of our experiments based on MEDLINE 2015 baseline and MeSH tree from 2015. The dataset is distributed in the form of the following tab separated text files: * PubMed2015_NoveltyData.tsv - Novelty scores for each paper in PubMed. The file contains 22,349,417 rows and 6 columns, as follow: - PMID: PubMed ID - Year: year of publication - TimeNovelty: time novelty score of the paper based on individual concepts (see paper) - VolumeNovelty: volume novelty score of the paper based on individual concepts (see paper) - PairTimeNovelty: time novelty score of the paper based on pair of concepts (see paper) - PairVolumeNovelty: volume novelty score of the paper based on pair of concepts (see paper) * mesh_scores.tsv - Temporal profiles for each MeSH term for all years. The file contains 1,102,831 rows and 5 columns, as follow: - MeshTerm: Name of the MeSH term - Year: year - AbsVal: Total publications with that MeSH term in the given year - TimeNovelty: age (in years since first publication) of MeSH term in the given year - VolumeNovelty: : age (in number of papers since first publication) of MeSH term in the given year * meshpair_scores.txt.gz (36 GB uncompressed) - Temporal profiles for each MeSH term for all years - Mesh1: Name of the first MeSH term (alphabetically sorted) - Mesh2: Name of the second MeSH term (alphabetically sorted) - Year: year - AbsVal: Total publications with that MeSH pair in the given year - TimeNovelty: age (in years since first publication) of MeSH pair in the given year - VolumeNovelty: : age (in number of papers since first publication) of MeSH pair in the given year * README.txt file ## Dataset creation This dataset was constructed using multiple datasets described in the following locations: * MEDLINE 2015 baseline: https://www.nlm.nih.gov/bsd/licensee/2015_stats/baseline_doc.html * MeSH tree 2015: ftp://nlmpubs.nlm.nih.gov/online/mesh/2015/meshtrees/ * Source code provided at: https://github.com/napsternxg/Novelty Note: The dataset is based on a snapshot of PubMed (which includes Medline and PubMed-not-Medline records) taken in the first week of October, 2016. Check here for information to get PubMed/MEDLINE, and NLMs data Terms and Conditions: Additional data related updates can be found at: Torvik Research Group ## Acknowledgments This work was made possible in part with funding to VIT from NIH grant P01AG039347 and NSF grant 1348742 . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ## License Conceptual novelty analysis data based on PubMed Medical Subject Headings by Shubhanshu Mishra, and Vetle Torvik is licensed under a Creative Commons Attribution 4.0 International License. Permissions beyond the scope of this license may be available at https://github.com/napsternxg/Novelty

Data generated and analyzed of our work titled "A computational model of rabbit geometry and ECG: Optimizing ventricular activation sequence and APD distribution". Please see the respective publication for more context.

• BSPM_filtered.dat
  • Contains the filtered ECG Data
• BSPM_original.bdf
  • Contains the originally recorded signal.
    Information on the file format itself can be found here: https://www.biosemi.com/faq/file_format.htm
    Links to various toolboxes to open the file can be found here: https://www.biosemi.com/download.htm
• CT_DataDCM.zip
  • Contains the recorded CT images of heart and torso in DCM file format
• ECG_NodeIndices.txt
  • Contains the the node IDs of the torso mesh corresponding to the electrode positions of the ECG Vest
• Endocardial_Surface_Papillary.stl
  • Segmented endocardial surface including papillary muscles
• Mat_LeadField.dat
  • Contains the calculated lead field matrix to be used in combination with the provided Mesh_Ven.vtu. Make sure to keep the node order

  • # Python example of usage
    # Define a read_vm_vec function which reads your calculated data beforehand
    import numpy as np
    
    t_begin = 0
    t_end = 400
    LF_mat = np.loadtxt('Mat_LeadField.dat')
    times = np.linspace(t_begin, t_end, t_end-t_begin)
    result = np.zeros((len(times), 31))
    for i,t in enumerate(times):
      vm_vec = read_vm_vec(t)
      result[i, :] = LF_mat.dot(vm_vec)[0:31]
    result = np.insert(result, 0, times, axis=1)
    np.savetxt('BSPM.dat', result)

• Mesh_PurkinjeTree.vtp
  • The resulting optimized Purkinje Node tree. We recommend using ParaView for visualization
• Mesh_StimPoints.vtp
  • The resulting points of stimulation.
• Stim_IndexTime.dat
  • Contains the stimulation pattern in terms the node index of Mesh_Ven.vtu and the respective stimulation time
• Mesh_Ven.vtu
  • Contains the ventricular mesh as well as the repective lead field matrix values for each surface node.
  • Material:
    Right Ventricle 30
    Left Ventricle 31
• Mesh_Torso.vtu
  • Contains the whole torso mesh.
  • Material:
    Fat 2
    Bones 3
    Blood 9
    Cartilage 14
    Liver 20
    Lungs 17
    Right Ventricle 30
    Left Ventricle 31
    Right Atrium 32
    Left Atrium 33
    Aorta 60
    Pulmonary artery 61
    Left Vena Jugularis 62
    Right Vena Jugularis 62
    Post Vena Cava 62

PubChem database was searched for compounds that had a MeSH annotation. It is great that PubChem now allows a direct download for these compounds in a rich CSV file.

This dataset includes measurements of carbon-14 transfer from plants to soil within mesh cores. Measurements were taken in roots, shoots, soil and from respiration. Mesh cores were either static or rotated to provide plus and minus mycorrhizal mycelial systems. Carbon-14 was traced through cores as respiration using KOH (Potassium hydroxide) traps. The experiment was carried out at the University of Sheffield using soil from the NERC Soil Biodiversity site in Scotland. The work was part of the NERC Soil Biodiversity Thematic Programme, which was established in 1999 and was centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (now the James Hutton Institute) farm at Sourhope in the Scottish Borders. During the experiment, the site was monitored to assess changes in above-ground biomass production (productivity), species composition and relative abundance (diversity).