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52 results for “Data Training Sets”

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zenodo48/100

PANDEM-2 European COVID-19 training data set

<p>The PANDEM-2 COVID-19 European training dataset is a large collection of time series either of real or realistic synthetic (generated) data and indicators associated with the European pandemic response to the COVID-19 pandemic. It is intended to be used for training in pandemic management.</p> <p>&nbsp;</p> <p>This dataset is the result of a data gathering requirement process for pandemic management involving feedback and inputs from several public health and first responder professionals as well as researchers and military personnel directly involved in the European COVID-19 pandemic response. This work is part of the PANDEM-2 project funded by the <em>Horizon 2020 Secure Societies</em> program. To collect this data, an open source software was developed named PANDEM-Source allowing reproducibility and customisation of this dataset.&nbsp;</p> <p>&nbsp;</p> <p>The dataset includes indicators for cases, deaths, hospitalisation, testing and laboratory data including pathogen genomic information, vaccination, non-pharmaceutical interventions, participatory surveillance, social media, flights resources (human and material such as beds or vaccines), and contact tracing activities. When no open available data was found, realistic synthetic data and indicators were generated with the goal of producing a data set to be used for pandemic management&nbsp; training.&nbsp;</p> <p>The project received funding from the European Union&rsquo;s Horizon 2020 Research and Innovation programme under the Grant Agreement No. 883285. The material presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out.<br> References</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2023View details →
zenodo44/100

ShiftCrypt training data set for training ConforMine

<p>Data set containing the ShiftCrypt values of the proteins used for training ConforMine. This set is not to be confused the the Molecular Dynamics (MD) data set, also used for training of this model.&nbsp;</p> <p>The data set also contains a python script which recreates the filtering of sequences performed in the training steps of ConforMine, which discards all proteins for which no valid ShiftCrypt predictions were obtained.&nbsp;</p>

opencc-by-4.0Feb 2023View details →
zenodo40/100

Data set - Practical teacher-training program on STEAM activity planning

<p>Data set of answers of 14 Brazilian teachers who took part in a&nbsp;practical teacher-training program on STEAM activity planning.&nbsp;</p>

opencc-by-4.0Feb 2022View details →
zenodo40/100

In silico data-set used to train the PGNNIV

<p>The folder contains the data used to train PGNNIVs to unravel the go or grow behaviour of glioblastoma under 4 different parametric models. These data consist on the solutions (in time and space)&nbsp;of eleven simulations with different oxygen boundary conditions.</p> <p>Each folder is named as DATA_&quot;ModelName&quot;, where &quot;ModelName&quot; can be: &quot;Sigmoid&quot;, &quot;ReLU&quot;, &quot;MichaelisMenten&quot; or &quot;Heaviside&quot;. Inside each folder, the multidimensional arrays for input and output data for the network training can be found. These&nbsp;arrays have dimension [nExp,TimeStep,x,field], where:</p> <ul> <li>nExp = 11&nbsp; and corresponds to the number of different configurations or experiments simulated.</li> <li>TimeStep = 1000 and correspond to the different temporal frames where the solution is given.</li> <li>x = 51 and corresponds to the different spatial points where the solution is given.</li> <li>field = 2 and correspond to the different solution fields (1: cells, 2: oxygen).</li> </ul>

opencc-by-4.0Mar 2022View details →
zenodo40/100

MItosis DOmain Generalization Challenge 2022 (MICCAI MIDOG 2022), Training data set (PNG version)

<p>This is the training dataset of the MItosis DOmain Generalization (MIDOG) challenge 2022, held in conjunction with MICCAI 2022. Please find the structured challenge description at 10.5281/zenodo.6362337.</p> <p>The training set consists of 405 tumor cases in total across six tumor types:</p> <ul> <li>Canine Lung Cancer (44 cases, scanned with 3DHistech Pannoramic Scan II)</li> <li>Human Breast Cancer (150 cases, scanned using three scanners, part of MIDOG2021 dataset)</li> <li>Canine Lymphoma (55 cases, scanned with 3DHistech Pannoramic Scan II)</li> <li>Human neuroendocrine tumor (55 cases, scanned with Hamamatsu NanoZoomer XR)</li> <li>Canine Cutaneous Mast Cell Tumor (50 cases, scanned with Aperio ScanScope CS2)</li> <li>Human melanoma (51 cases, scanned with Hamamatsu NanoZoomer XR) (no labels provided)</li> </ul> <p>From each WSI, a trained pathologist selected an area of 2mm&sup2; corresponding to approximately 10 high power fields, according to the grading scheme of Elston and Ellis. We cropped this area and provide it as PNG files in this data set due to restrictions in data set size on zenodo. Each file includes the resolution (in dots per inch, DPI) of the original scanned images.</p> <p>The training set contains 9501 mitotic figures (MF) and 11051 hard examples (non-mitotic figures). All annotations are provided in MS COCO JSON format and as SQLITE database (SlideRunner format).</p>

opencc-by-4.0Apr 2022View details →
zenodo40/100

Galaxy Training Data for "Evaluating and ranking a set of pathways based on multiple metrics"

<pre>This dataset provides the inputs needed for the Galaxy Pathway Analysis workflow training tutorial (<a href="https://galaxy-synbiocad.org">https://galaxy-synbiocad.org</a>). This workflow asseses the performance of predicted pathways by computing 4 criteria (target product flux, thermodynamic feasibility, pathway length, and enzyme availability). A score inform the user about the best candidate pathways to produce a compound of interest. The generated output is a collection of scored and ranked heterologous pathways. The content of the dataset is as follows: - A set of pathways provided in the SBML format (Systems Biology Markup Language) to be ranked, modeling heterologous pathways such as those outputted by the RetroSynthesis workflow (<a href="https://galaxy-synbiocad.org">https://galaxy-synbiocad.org</a>). - The GEM (Genome-scale metabolic models) which is a formalized representation of the metabolism of the host organism (the model is E. coli iML1515), provided in the SBML format.</pre>

opencc-by-4.0Jun 2022View details →
dryad40/100

Data from: How many specimens make a sufficient training set for automated three dimensional feature extraction?

<p>Deep learning has emerged as a robust tool for automating feature extraction from 3D images, offering an efficient alternative to labour-intensive and potentially biased manual image segmentation methods. However, there has been limited exploration into the optimal training set sizes, including assessing whether artificial expansion by data augmentation can achieve consistent results in less time and how consistent these benefits are across different types of traits. In this study, we manually segmented 50 planktonic foraminifera specimens from the genus Menardella to determine the minimum number of training images required to produce accurate volumetric and shape data from internal and external structures. The results reveal unsurprisingly that deep learning models improve with a larger number of training images with eight specimens being required to achieve 95% accuracy. Furthermore, data augmentation can enhance network accuracy by up to 8.0%. Notably, predicting both volumetric and shape measurements for the internal structure poses a greater challenge compared to the external structure, due to low contrast differences between different materials and increased geometric complexity. These results provide novel insight into optimal training set sizes for precise image segmentation of diverse traits and highlight the potential of data augmentation for enhancing multivariate feature extraction from 3D images. </p>

opencc-zeroMay 2024View details →
zenodo40/100

Data sets of multi-body models for conventional, articulated, and equidistant-axles trains and single span bridges

<p>Information about characteristics of multi-body models of conventional, articulated, and equidistant-axles trains.</p> <p>Information about bridge data set, used for vehicle-bridge interaction investigations.</p>

opencc-by-4.0Aug 2024View details →
zenodo40/100

Unipen data set of on-line (vectorial) handwriting - train_r01_v07

<p>/*****************************************************************************\<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp; This is the first UNIPEN distribution of the iUF&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp; This distribution comprises NIST train_r01_v07&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; http://www.unipen.org/&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; Source code: C/Linux at&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; http://www.sourcefiles.org/Scientific/Other_Sciences/uptools3.tar.gz&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The International Unipen Foundation, December 1999&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *******************************************************************************<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; DISCLAIMER AND COPYRIGHT NOTICE FOR ALL DATA CONTAINED ON THIS CDROM:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; 1) PERMISSION IS HEREBY GRANTED TO USE THE DATA FOR RESEARCH&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; PURPOSES. IT IS NOT ALLOWED TO DISTRIBUTE THIS DATA FOR COMMERCIAL&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; PURPOSES.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; Copyright 1999, International Unipen Foundation - All rights reserved&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; 2) PROVIDER GIVES NO EXPRESS OR IMPLIED WARRANTY OF ANY KIND AND ANY&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR PURPOSE ARE&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; DISCLAIMED.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; 3) PROVIDER SHALL NOT BE LIABLE FOR ANY DIRECT, INDIRECT, SPECIAL,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF ANY USE OF THIS&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; DATA.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp; 4) THE CONDITIONS OF USE REQUIRE PROPER REFERENCE TO THIS DATABASE&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp; AS DESCRIBED IN ACCOMPANYING DOCUMENT &#39;unipen-conditions-of-use.html&#39;&nbsp;&nbsp; *<br> *&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *<br> \*****************************************************************************/</p> <p>Contents of the CDROM:<br> ----------------------</p> <p>1) This file, called CDROM-README<br> 2) The nist distribution, of which part of the directory tree is listed here.</p> <p>train_r01_v07<br> &nbsp;&nbsp; &nbsp;include<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;abm&nbsp; apb&nbsp; app&nbsp; atu&nbsp; bbd&nbsp; ced&nbsp; gmd&nbsp; ibm&nbsp; kai&nbsp; lou&nbsp; pap&nbsp; pri&nbsp; sta&nbsp; uqb<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;aga&nbsp; apc&nbsp; art&nbsp; bba&nbsp; cea&nbsp; cee&nbsp; hpb&nbsp; imp&nbsp; kar&nbsp; mot&nbsp; par&nbsp; rim&nbsp; syn&nbsp; val<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;anj&nbsp; apd&nbsp; ata&nbsp; bbb&nbsp; ceb&nbsp; cef&nbsp; hpp&nbsp; imt&nbsp; lav&nbsp; nic&nbsp; pcl&nbsp; scr&nbsp; tos<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;apa&nbsp; ape&nbsp; att&nbsp; bbc&nbsp; cec&nbsp; dar&nbsp; huj&nbsp; int&nbsp; lex&nbsp; not&nbsp; phi&nbsp; sie&nbsp; ugi</p> <p>&nbsp;&nbsp; &nbsp;data<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;1a<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;aga&nbsp; apb&nbsp; art&nbsp; ceb&nbsp; gmd&nbsp; imp&nbsp; pri&nbsp; tos&nbsp; val<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;apa&nbsp; app&nbsp; cea&nbsp; ced&nbsp; ibm&nbsp; lou&nbsp; syn&nbsp; uqb<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;1b&nbsp; 1c&nbsp; 1d&nbsp; 2&nbsp;&nbsp; 3&nbsp;&nbsp; 4&nbsp;&nbsp; 5&nbsp;&nbsp; 6&nbsp;&nbsp; 7&nbsp;&nbsp; 8</p> <p>All files on the the CDROM were tested on UNIPEN integrity using uplib.<br> The description of the contents is given below:</p> <p><br> Description of the contents:<br> ----------------------------</p> <p>For a description and examples of the UNIPEN format, see http://www.unipen.org/</p> <p>The UNIPEN files contained in this release are organized in 10 categories, listed<br> below. The number of .SEGMENTS and number of files for each category are given:</p> <p>&nbsp;cat&nbsp;&nbsp; nsegm&nbsp; nfiles<br> &nbsp; 1a&nbsp; 15953&nbsp;&nbsp;&nbsp;&nbsp; 634&nbsp; isolated digits<br> &nbsp; 1b&nbsp; 28069&nbsp;&nbsp;&nbsp; 1423&nbsp; isolated upper case<br> &nbsp; 1c&nbsp; 61351&nbsp;&nbsp;&nbsp; 2145&nbsp; isolated lower case<br> &nbsp; 1d&nbsp; 17286&nbsp;&nbsp;&nbsp; 1222&nbsp; isolated symbols (punctuations etc.)<br> &nbsp; 2&nbsp; 122628&nbsp;&nbsp;&nbsp; 2735&nbsp; isolated characters, mixed case<br> &nbsp; 3&nbsp;&nbsp; 67352&nbsp;&nbsp;&nbsp; 1949&nbsp; isolated characters in the context of words or texts<br> &nbsp; 4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp; isolated printed words, not mixed with digits and symbols<br> &nbsp; 5&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp; isolated printed words, full character set<br> &nbsp; 6&nbsp; 75529&nbsp;&nbsp;&nbsp;&nbsp; 3298&nbsp; isolated cursive or mixed-style words (without digits and symbols)<br> &nbsp; 7&nbsp; 85213&nbsp;&nbsp;&nbsp;&nbsp; 3393&nbsp; isolated words, any style, full character set<br> &nbsp; 8&nbsp; 14544&nbsp;&nbsp;&nbsp;&nbsp; 4563&nbsp; text: (minimally two words of) free text, full character set</p> <p>In each directory representing a category, e.g., data/1a, a number of<br> sub-directories are contained. The name of a subdirectory is a<br> three-letter word identifying the contributor of the data.</p> <p>Consider for example the UNIPEN files contributed by &#39;aga&#39; of category<br> 1a (isolated digits). The files containing .SEGMENT entries are contained<br> in the &#39;data&#39; directory:<br> &nbsp;&nbsp; &nbsp;data/1a/aga</p> <p>Most files in this distribution contain one or more .INCLUDE statements.<br> The corresponding files are found in the &#39;include&#39; directory, in this case:<br> &nbsp;&nbsp; &nbsp;include/aga<br> Some files (such as the &#39;imp&#39; contributions) use nested .INCLUDE statements.<br> The software contained in the uptools3 distribution contains code to find<br> files to be included based on an environment variable.</p> <p><br> Distribution of categories per contributor:<br> -------------------------------------------</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1a&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 1b&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 1c&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 1d&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 2&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 6&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 7&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 8<br> --------------------------------------------------------------------------------------------------------------<br> abm |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 628&nbsp;&nbsp;&nbsp; 4 |&nbsp;&nbsp; 646&nbsp;&nbsp;&nbsp; 4 |&nbsp;&nbsp;&nbsp; 7&nbsp;&nbsp; 3 |<br> aga |&nbsp; 405&nbsp; 14 | 1115&nbsp; 14 | 1063&nbsp; 14 |&nbsp; 221&nbsp; 14 |&nbsp; 2804&nbsp; 14 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 605&nbsp; 14 |<br> anj |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1435&nbsp;&nbsp;&nbsp; 6 |&nbsp; 1435&nbsp;&nbsp;&nbsp; 6 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> apa |&nbsp; 692&nbsp; 74 | 2236 247 | 7414 391 | 1953 268 | 12295 527 | 12295 527 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 527 527 |<br> apb | 2033 138 | 3450 466 | 8869 434 |&nbsp; 946 233 | 15298 590 | 15298 590 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 590 590 |<br> apc |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1724&nbsp; 441 |&nbsp; 1798&nbsp; 444 |&nbsp; 444 444 |<br> apd |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1958&nbsp; 453 |&nbsp; 2448&nbsp; 507 |&nbsp; 507 507 |<br> ape |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1384&nbsp; 286 |&nbsp; 1848&nbsp; 322 |&nbsp; 322 322 |<br> app | 1046 115 | 3010 353 |10370 556 | 2886 400 | 17312 745 | 17312 745 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 745 745 |<br> art |&nbsp; 170&nbsp;&nbsp; 6 | 1042&nbsp;&nbsp; 6 | 2301&nbsp;&nbsp; 6 |&nbsp; 202&nbsp;&nbsp; 6 |&nbsp; 3715&nbsp;&nbsp; 6 |&nbsp; 3715&nbsp;&nbsp; 6 |&nbsp;&nbsp; 687&nbsp;&nbsp;&nbsp; 6 |&nbsp;&nbsp; 933&nbsp;&nbsp;&nbsp; 6 |&nbsp; 186&nbsp;&nbsp; 6 |<br> att |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 932&nbsp;&nbsp; 29 |&nbsp; 2253&nbsp;&nbsp; 29 |&nbsp; 819&nbsp; 30 |<br> atu |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 92&nbsp; 92 |<br> bba |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 63&nbsp; 63 |<br> bbb |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 51&nbsp; 51 |<br> bbc |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 61&nbsp; 61 |<br> bbd |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 858 858 |<br> cea |&nbsp;&nbsp;&nbsp; 7&nbsp;&nbsp; 3 |&nbsp;&nbsp; 57&nbsp;&nbsp; 6 | 1402&nbsp;&nbsp; 6 |&nbsp;&nbsp; 35&nbsp;&nbsp; 6 |&nbsp; 1501&nbsp;&nbsp; 6 |&nbsp; 1501&nbsp;&nbsp; 6 |&nbsp;&nbsp; 311&nbsp;&nbsp;&nbsp; 6 |&nbsp;&nbsp; 345&nbsp;&nbsp;&nbsp; 6 |&nbsp;&nbsp; 38&nbsp;&nbsp; 6 |<br> ceb |&nbsp;&nbsp; 16&nbsp;&nbsp; 2 |&nbsp;&nbsp; 30&nbsp;&nbsp; 4 |&nbsp; 488&nbsp;&nbsp; 4 |&nbsp;&nbsp;&nbsp; 8&nbsp;&nbsp; 3 |&nbsp;&nbsp; 542&nbsp;&nbsp; 4 |&nbsp;&nbsp; 542&nbsp;&nbsp; 4 |&nbsp;&nbsp; 116&nbsp;&nbsp;&nbsp; 4 |&nbsp;&nbsp; 129&nbsp;&nbsp;&nbsp; 4 |&nbsp;&nbsp; 22&nbsp;&nbsp; 4 |<br> cec |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 4880&nbsp;&nbsp; 35 |&nbsp; 5625&nbsp;&nbsp; 35 |&nbsp; 604&nbsp; 35 |<br> ced | 1369&nbsp; 42 | 2691&nbsp; 42 | 2619&nbsp; 43 | 1077&nbsp; 43 |&nbsp; 7756&nbsp; 43 |&nbsp; 7756&nbsp; 43 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 1100&nbsp; 43 |<br> cee |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 3977&nbsp;&nbsp; 29 |&nbsp; 3978&nbsp;&nbsp; 29 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> dar |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 277&nbsp;&nbsp;&nbsp; 2 |&nbsp;&nbsp; 316&nbsp;&nbsp;&nbsp; 2 |&nbsp;&nbsp; 36&nbsp;&nbsp; 2 |<br> gmd | 1145&nbsp;&nbsp; 3 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 2921&nbsp;&nbsp; 3 |&nbsp; 832&nbsp;&nbsp; 3 |&nbsp; 4898&nbsp;&nbsp; 3 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> hpb |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1524&nbsp;&nbsp;&nbsp; 7 |&nbsp; 2292&nbsp;&nbsp;&nbsp; 7 | 1832&nbsp; 23 |<br> hpp |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 8323&nbsp;&nbsp; 32 | 10820&nbsp;&nbsp; 32 | 2591&nbsp; 29 |<br> huj |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 104&nbsp;&nbsp;&nbsp; 1 |&nbsp;&nbsp; 104&nbsp;&nbsp;&nbsp; 1 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> ibm | 1571&nbsp; 22 | 4264&nbsp; 22 | 4354&nbsp; 22 | 1994&nbsp; 22 | 12183&nbsp; 22 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1196&nbsp;&nbsp;&nbsp; 9 |&nbsp; 1196&nbsp;&nbsp;&nbsp; 9 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> imp |&nbsp; 257&nbsp; 50 |&nbsp; 645&nbsp; 50 |&nbsp; 656&nbsp; 50 |&nbsp; 851&nbsp; 50 |&nbsp; 2409&nbsp; 50 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1119&nbsp;&nbsp; 22 |&nbsp; 1119&nbsp;&nbsp; 22 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> imt |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 242&nbsp;&nbsp;&nbsp; 1 |&nbsp;&nbsp; 242&nbsp;&nbsp;&nbsp; 1 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> int |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 2012&nbsp;&nbsp;&nbsp; 4 |&nbsp; 2012&nbsp;&nbsp;&nbsp; 4 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> kai |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 1961&nbsp; 28 | 8663&nbsp; 46 | 1585&nbsp; 22 | 12209&nbsp; 57 |&nbsp; 8933&nbsp; 28 |&nbsp; 1013&nbsp;&nbsp; 28 |&nbsp; 1663&nbsp;&nbsp; 28 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> kar |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1809&nbsp;&nbsp; 33 |&nbsp; 1860&nbsp;&nbsp; 33 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> lav |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 1324&nbsp;&nbsp; 9 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1324&nbsp;&nbsp; 9 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 213&nbsp;&nbsp;&nbsp; 5 |&nbsp;&nbsp; 213&nbsp;&nbsp;&nbsp; 5 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> lex |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 5660&nbsp;&nbsp; 13 |&nbsp; 7235&nbsp;&nbsp; 13 | 1937&nbsp; 13 |<br> lou |&nbsp;&nbsp;&nbsp; 7&nbsp;&nbsp; 1 |&nbsp;&nbsp; 11&nbsp;&nbsp; 1 |&nbsp;&nbsp; 15&nbsp;&nbsp; 1 |&nbsp;&nbsp;&nbsp; 2&nbsp;&nbsp; 1 |&nbsp;&nbsp;&nbsp; 35&nbsp;&nbsp; 1 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1538&nbsp;&nbsp;&nbsp; 7 |&nbsp; 1599&nbsp;&nbsp;&nbsp; 7 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> mot |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 2701&nbsp;&nbsp; 8 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 2701&nbsp;&nbsp; 8 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> nic |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 6813&nbsp;&nbsp; 66 |&nbsp; 6813&nbsp;&nbsp; 66 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> not |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1452&nbsp;&nbsp;&nbsp; 8 |&nbsp; 1452&nbsp;&nbsp;&nbsp; 8 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> pap |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 2203&nbsp;&nbsp; 39 |&nbsp; 2213&nbsp;&nbsp; 41 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> par |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 496&nbsp;&nbsp;&nbsp; 8 |&nbsp;&nbsp; 512&nbsp;&nbsp;&nbsp; 8 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> pcl |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 616&nbsp;&nbsp; 21 |&nbsp;&nbsp; 616&nbsp;&nbsp; 21 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> phi |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 2506&nbsp;&nbsp; 12 |&nbsp; 2506&nbsp;&nbsp; 12 |&nbsp;&nbsp; 91&nbsp;&nbsp; 4 |<br> pri |&nbsp;&nbsp; 78&nbsp; 15 |&nbsp; 212&nbsp; 15 |&nbsp; 191&nbsp; 15 |&nbsp; 230&nbsp; 15 |&nbsp;&nbsp; 711&nbsp; 15 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 106&nbsp;&nbsp;&nbsp; 3 |&nbsp;&nbsp; 110&nbsp;&nbsp;&nbsp; 3 |&nbsp;&nbsp; 49&nbsp; 18 |<br> rim |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 277&nbsp;&nbsp; 21 |&nbsp;&nbsp; 277&nbsp;&nbsp; 21 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> scr |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 211&nbsp; 44 |<br> sie |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 377 377 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 377 377 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp; 1593 1593 |&nbsp; 1593 1593 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> sta |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 15808&nbsp;&nbsp; 61 | 16415&nbsp;&nbsp; 61 |&nbsp; 156&nbsp; 29 |<br> syn | 4554&nbsp; 17 |&nbsp; 637&nbsp;&nbsp; 8 |&nbsp; 589&nbsp;&nbsp; 8 |&nbsp; 415&nbsp;&nbsp; 8 |&nbsp; 6195&nbsp; 17 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> tos |&nbsp; 543 108 | 1432 108 | 1381 108 | 1660 108 |&nbsp; 4985 108 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> ugi |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp; 597&nbsp;&nbsp;&nbsp; 3 |&nbsp;&nbsp; 597&nbsp;&nbsp;&nbsp; 3 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> uqb |&nbsp; 598&nbsp;&nbsp; 4 | 1514&nbsp;&nbsp; 4 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | 1327&nbsp;&nbsp; 4 |&nbsp; 3439&nbsp;&nbsp; 4 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> val | 1462&nbsp; 20 | 3762&nbsp; 49 | 3653&nbsp; 44 | 1062&nbsp; 16 |&nbsp; 9939 129 |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> --------------------------------------------------------------------------------------------------------------<br> &nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |<br> tot |15953 634 |28069 1423|61351 2145|17286 1222|122628 2735|67352 1949 | 75529 3298 | 85213 3393 |14544 4563|<br> --------------------------------------------------------------------------------------------------------------<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1a&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 1b&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 1c&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 1d&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 2&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp; 3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 6&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 7&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; |&nbsp;&nbsp;&nbsp;&nbsp; 8</p>

opencc-by-4.0Nov 1999View details →
zenodo40/100

Training data set for: Graph Neural Network based elastic deformation emulators for magmatic reservoirs of complex geometries

<h2>Overview</h2> <p>This is a synthetic volcano deformation dataset accompanying the publication of&nbsp;<em><strong>Graph Neural Network based elastic deformation emulators for magmatic reservoirs of complex geometries</strong></em>,<em><strong> </strong></em>on the journal <em>Volcanica</em>. Synthetic, quasi-static deformation is computed for magma chambers of various geometries, parameterized as spheroids or superpositions of spherical harmonics. Surface deformation is computed using the boundary element method (BEM) of Nikkhoo &amp; Walter (2015). Please reference our paper for details of computational methods.</p> <p>The dataset contains 50,000 realizations of magma chamber geometries/orientations/centroid depths and associated deformation fields. Surface deformation fields are sampled at discrete locations, with a uniform random distribution within [Lh x Lh], and a distribution that concentrates near the chamber (at radial distances, r = 10^(-3&nbsp;<em>&nbsp;random number) * </em>Lh/2). Note this dataset contains only a small fraction of the total dataset. In total, 824,393 realizations of magma chambers were used to train our emulators. For accessing the complete training data set, please contact the authors.&nbsp;</p> <p>Each .mat file contains the deformation field associated with a single chamber geometry. Use visData.m to visualize chamber geometry and associated surface displacement. Each file contains two MATLAB structures, "input" and "output".&nbsp;</p> <h2>Naming of each zip file</h2> <p>The numbers after the underscore, N:M, indicate that this file contains N of the M total chamber realizations for this particular setup.&nbsp;</p> <p><a href="../api/records/13800065/draft/files/sph_20AspRatios_1e4:151211.zip.zip/content" target="_blank" rel="noopener noreferrer">sph_20AspRatios_1e4:151211.zip</a>: deformation corresponding to spheroidal magma chambers parameterized by aspect ratios.&nbsp;</p> <p><a href="../api/records/13800065/draft/files/sh_complex_1e4:152283.zip/content" target="_blank" rel="noopener noreferrer">sh_complex_1e4:152283.zip</a>: deformation corresponding to chamber geometry produced by superposition of spherical harmonic modes.&nbsp;</p> <p><a href="../api/records/13800065/draft/files/sh_mode_approx_1e4:138380.zip/content" target="_blank" rel="noopener noreferrer">sh_mode_approx_1e4:138380.zip</a>: deformation corresponding to chamber geometries corresponding to individual spherical harmonic modes, combined with a spherical mode (the spherical mode prevents chamber surfaces from having zero radii locally)</p> <p><a href="../api/records/13800065/draft/files/sh_spheroid_approx1e4:202272.zip/content" target="_blank" rel="noopener noreferrer">sh_spheroid_approx1e4:202272.zip</a>: deformation corresponding to chambers approximating spheroids, but&nbsp;parameterized by spherical harmonics.</p> <p><a href="../api/records/13800065/draft/files/sh_spheroid_perturb_1e4:180247.zip/content" target="_blank" rel="noopener noreferrer">sh_spheroid_perturb_1e4:180247.zip</a>: same as above, but with additional random perturbations parameterized in spherical harmonics.</p> <h2>Variables in each file</h2> <p><strong>Input</strong> contains the following fields:</p> <p><strong>dp2mu</strong>: pressure change to shear modulus ratio.</p> <p><strong>dx</strong>, <strong>dy</strong>, <strong>dz</strong>: the coordinates of chamber centroid [meters]</p> <p><strong>mu:&nbsp;</strong>dimensionless crustal shear modulus (always set to 1)</p> <p><strong>nu</strong>: crustal Poisson's ratio (always set to 0.25)</p> <p><strong>Ns</strong>: number of points on the surface where displacements are computed</p> <p><strong>Lh</strong>, <strong>Lv</strong>: horizontal and vertical dimensions of the model domain [meters]. Lh is determined such that at the edge of the model domain, the displacement magnitude is below 10 percent of the maximum. Lv = Lh/2 + abs(dz)</p> <p>for the spheroids -----------------------------------------------------------------------------------------------------------</p> <p>the input files contain</p> <p><strong>asp</strong>: aspect ratio of chamber (length of the semi-major axis divided by that of the semi-minor axis)</p> <p><strong>ra</strong>, <strong>rb</strong>: semi-major, -minor, axis length [meters]</p> <p><strong>thetax</strong>, <strong>thetay</strong>, <strong>thetaz</strong>: counterclockwise rotation angles with regard to x, y, z axis [degrees]. thetax = [0, 90] degrees, thetay = 0 degrees, thetaz = 360 degrees.</p> <p>for the general geometries--------------------------------------------------------------------------------------------------</p> <p>the input files contain</p> <p><strong>ls</strong>, <strong>ms</strong>, <strong>fs</strong>: degree, order, coefficients of spherical harmonic modes. Spherical harmonics are sampled up to degree 5. fs is a complex vector of coefficients such that the resulting shape is real.&nbsp;</p> <p><strong>normF</strong>: normalization factor applied to the shape parameterized by ls, ms, fs, such that the shape as a maximum radius of unity.</p> <p><strong>rmax</strong>: scale factor to scale the spherical harmonics parameterized shape to real dimensions [meters].</p> <p>=============================================================================================</p> <p>Output contains the following fields,</p> <p><strong>X</strong>, <strong>Y</strong>, <strong>Z</strong>: coordinates of points where displacement vectors are computed [meters]</p> <p><strong>Ux</strong>, <strong>Uy</strong>, <strong>Uz</strong>: displacements in x, y, z directions [meters]</p> <p><strong>P</strong>, <strong>T</strong>: coordinates [meters] of vertices for the triangular mesh used in BEM calculation, and the connectivity matrix&nbsp;</p> <p><strong>C</strong>: coordinates [meters] of the center of each triangular element</p> <p><strong>that</strong>, <strong>dhat</strong>, <strong>nhat</strong>: unit vectors for orthogonal coordinate systems local to each triangular element. that ("t-hat") extends from vertex one to vertex two, nhat is outward normal, and dhat = cross (nhat, that).</p> <p>Reference:</p> <p>1. Nikkhoo, M., &amp; Walter, T. R. (2015). Triangular dislocation: an analytical, artefact-free solution.&nbsp;<em>Geophysical Journal International</em>,&nbsp;<em>201</em>(2), 1119-1141.</p>

opencc-by-4.0Sep 2024View details →
zenodo40/100

Training and test data set of thickness distribution of turbidites

<p>This is a data set of thickness distribution used for training and test of the inverse model of turbidites. Details were described in&nbsp;https://esurf.copernicus.org/preprints/esurf-2020-93/esurf-2020-93.pdf</p>

opencc-by-4.0Aug 2021View details →
zenodo40/100

Data Set on Content Excerpts from Relevant Literature for a Scoping Review of Evacuation Training Methods in Buildings

<p>This Excel-file contains a set of data&nbsp;from a scoping review on methods for fire evacuation training in buildings. The review&nbsp;follows the PRISMA approach (Transparent Reporting of Systematic Reviews and Meta-Analyses) and systematically identifies 73 sources among scientific literature published between 1997 and 2022. The dataset contains information excerpted through a custom template&nbsp;on the employed training methods and technology, study information, participants, and contents of the discussion of the 73 sources of evidence that were identified in the systematic review process.</p>

opencc-by-4.0Oct 2022View details →
zenodo40/100

Data Set on the Literature Screening for a Scoping Review of Evacuation Training Methods in Buildings

<p>This data set contains all retrieved literature records of a scoping review on fire evacuation training methods in buildings together with the reasoning for their in- or exclusion in the review.</p>

opencc-by-4.0Jan 2023View details →
zenodo40/100

Neural net training and test data set

<p>In this zip file you will find several folders as well&nbsp;as a readme file explaining the dataset. The neural net file can be directly used in cellpose to segment&nbsp;<strong>widefield</strong>&nbsp;<strong>20x objective</strong>&nbsp;imaging data of neutrophils. The neural net could be used for other types of data, but might perform below expectations.</p>

opencc-by-4.0May 2023View details →
dryad40/100

Data from: How many specimens make a sufficient training set for automated three dimensional feature extraction?

Open the record for dataset details and reuse information.

publicMay 2024View details →
zenodo36/100

Automated bio-AFM generation of large mechanome data set and their analysis by machine learning to classify prostatic cell lines_Training base 100 PC3-GFP

Open the record for dataset details and reuse information.

opencc-by-sa-4.0Nov 2023View details →
zenodo36/100

Data set of axle loads and distances for operating passenger and freight trains for development of load models

<p>Train data for moving load models of operating trains (5,007 passenger trains and 139,182 freight trains).</p> <ul> <li>axle distances [m] and axle loads [kN] for all trains included in zip-files as txt-files</li> <li>information on line categories (DIN EN 15528), loadcases and maximum speeds for passenger trains (and assignment to passenger train numbers in previous version of publication (used for development of load model)) in xlsx-file</li> </ul>

opencc-by-4.0Nov 2023View details →
zenodo36/100

rime fraction training data set extracted from BAECC

<p>training data set used in Vogl et al. (https://amt.copernicus.org/preprints/amt-2021-137/) to derive rime mass fraction from Doppler cloud radar observations. Extracted from the BAECC data set.</p> <p>rime mass fraction retrieved from PIP data</p> <p>cloud radar observations at Ka- and W-band (ARM KAZR and MWACR)</p> <p>attenuation estimated using the Passive and Active Microwave Remote Sensing Tool (PAMTRA)</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Weekly supervised Multilingual Data Set to train Named Entity Recognition for Symptom Extraction

<p>Data Sets were generated using the Weakly Supervised NER pipeline (https://github.com/HUMADEX/Weekly-Supervised-NER-pipline) to train the symptom extraction NER models.&nbsp;</p> <p><strong>Supported Languages and dataset locations for the specific language:</strong></p> <p>&nbsp; &nbsp; English (base language): https://huggingface.co/HUMADEX/english_medical_ner<br>&nbsp; &nbsp; German: https://huggingface.co/HUMADEX/german_medical_ner<br>&nbsp; &nbsp; Italian: https://huggingface.co/HUMADEX/italian_medical_ner<br>&nbsp; &nbsp; Spanish: https://huggingface.co/HUMADEX/spanish_medical_ner<br>&nbsp; &nbsp; Greek: https://huggingface.co/HUMADEX/german_medical_ner<br>&nbsp; &nbsp; Slovenian: https://huggingface.co/HUMADEX/slovenian_medical_ner<br>&nbsp; &nbsp; Polish: https://huggingface.co/HUMADEX/polish_medical_ner<br>&nbsp; &nbsp; Portuguese: https://huggingface.co/HUMADEX/portugese_medical_ner</p> <p>&nbsp;</p> <p><strong>Dataset Building&nbsp;</strong></p> <ul> <li>Data Integration and Preprocessing</li> <li>Data Cleaning</li> <li>Annotation with Stanza's i2b2 Clinical Model&nbsp;</li> <li>Translation into the targeted language</li> <li>Word Alignment&nbsp;</li> <li>Data Augmentation&nbsp;</li> </ul> <p><strong>Acknowledgement</strong><br>This dataset had been created as part of joint research of HUMADEX research group (https://www.linkedin.com/company/101563689/) and has received funding by the European Union Horizon Europe Research and Innovation Program project SMILE (grant number 101080923) and Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks, project BosomShield ((rant number 101073222). Responsibility for the information and views expressed herein lies entirely with the authors.</p> <p><strong>Authors:</strong><br>dr. Izidor Mlakar, Rigona Sallauka, dr. Umut Arioz, dr. Matej Rojc</p> <p><strong>Please cite as:</strong></p> <p><span>Article title: Weakly-Supervised Multilingual Medical NER For Symptom Extraction For Low-Resource Languages</span><br><span>Doi: 10.20944/preprints202504.1356.v1</span><br><span>Website:&nbsp;</span><a title="https://www.preprints.org/manuscript/202504.1356/v1" href="https://www.preprints.org/manuscript/202504.1356/v1">https://www.preprints.org/manuscript/202504.1356/v1</a></p>

opencc-by-4.0Oct 2024View details →
zenodo36/100

Training, Validation and Test Sets for paper 'A Little Data goes a Long Way: Automating Seismic Phase Arrival Picking at Nabro Volcano with Transfer Learning'

<p>Training, Validation and Test Data for model presented in&nbsp;paper &#39;A Little Data Goes A Long Way: Automating Seismic Phase Arrival Picking at Nabro Volcano with Transfer Learning&#39;, submitted to Journal of Geophysical Research: Solid Earth.</p> <p>Files:</p> <p>- train_events_2498.h5 = training set of seismic waveforms (events with P-/S-wave labelled arrivals only, i.e., no noise waveforms)</p> <p>- train_events_2498.pkl = event training set metadata (UTC P-/S-wave phase arrival times)</p> <p>- train_noise_2498.h5 = training set of seismic waveforms (noise sections only, i.e., no event waveforms)</p> <p>- train_noise_2498.pkl = noise training set metadata (UTC time&nbsp;for training noise waveforms)</p> <p>- val_events.h5 = validation set of seismic waveforms (events with P-/S-wave labelled arrivals only, i.e., no noise waveforms)</p> <p>- val_events.pkl = event validation set metadata (UTC P-/S-wave phase arrival times)</p> <p>- val_noise.h5 = validation&nbsp;set of seismic waveforms (noise sections only, i.e., no event waveforms)</p> <p>- val_noise.pkl = noise validation set metadata (UTC time&nbsp;for validation noise waveforms)</p> <p>- test.h5 = test&nbsp;set of seismic waveforms (events and noise)</p> <p>- test_events.pkl = event test set metadata (UTC P-/S-wave phase arrival times for test event waveforms)</p> <p>- test_noise.pkl = noise test set metadata (UTC time for test noise waveforms)</p> <p>- nabro_2011-247.mseed = 24 hours seismic data from Nabro Urgency Array (2011-09-04), saved in mseed format (e.g., can be read with obspy)</p> <p>- nabro_2011-269.mseed = 24 hours seismic data from Nabro Urgency Array (2011-09-26), saved in mseed format (e.g., can be read with obspy)</p> <p>&nbsp;</p> <p>Further details and code for reading and using&nbsp;these files can be found at the GitHub repo for this paper:&nbsp;<a href="https://github.com/sachalapins/U-GPD">https://github.com/sachalapins/U-GPD</a></p> <p>&nbsp;</p>

opencc-by-4.0Feb 2021View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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