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MEDDOPROF corpus: complete gold standard annotations for occupation detection in medical documents in Spanish
<p><strong>UPDATE 27/09/2022: </strong>A complete normalization of all mentions in the corpus to SNOMED CT has been added to the 'meddoprof-norm.tsv' file.</p> <p><strong>Description</strong></p> <p>This repository contains the complete MEDDOPROF Gold Standard, a collection of 1,844 clinical cases in Spanish with annotations for occupations, working statuses and activities. MEDDOPROF is a Shared Task celebrated in 2021 that explores the application of natural language processing to occupational health. If you'd like to learn more, please visit: <a href="https://temu.bsc.es/meddoprof">https://temu.bsc.es/meddoprof</a>.</p> <p><strong>Folder and File Structure</strong></p> <p>The corpus' files are presented in the format used by the annotation tool brat. That is, for each clinical case there is a .txt file with the text and a .ann file with its corresponding annotations.</p> <p><em>- meddoprof-ner/</em></p> <p>Clinical cases annotated with these labels: PROFESION (PROFESSION), SITUACION_LABORAL (WORKING_STATUS) or ACTIVIDAD (ACTIVIDAD).</p> <p><em>- meddoprof-class/</em></p> <p>Clinical cases with the same annotations as 'meddoprof-ner' but with these labels instead: PACIENTE (patient), FAMILIAR (family member), SANITARIO (health professional) or OTRO (other).</p> <p><em>- ner_class_joint/</em></p> <p>Clinical cases with both levels of annotation (ner and class) joint (that is, a mention classified as as PROFESOR in meddoprof-ner and as PACIENTE in meddoprof-class would be PROFESION-PACIENTE here).</p> <p><em>- meddoprof-norm.tsv</em></p> <p>Tab-separated file (.tsv) with the mapping of each mention in the corpus to ESCO and SNOMED CT. The file has five columns: filename, mention text, span, ESCO code and SNOMED code.</p> <p>Additionally, two files with the filenames of the train and test partitions are included.</p> <p> </p> <p><strong>Please cite if you use this resource:</strong></p> <p>Salvador Lima-López, Eulàlia Farré-Maduell, Antonio Miranda-Escalada, Vicent Brivá-Iglesias and Martin Krallinger. NLP applied to occupational health: MEDDOPROF shared task at IberLEF 2021 on automatic recognition, classification and normalization of professions and occupations from medical texts. In Procesamiento del Lenguaje Natural, 67. 2021.</p> <pre><code>@article{meddoprof, title={NLP applied to occupational health: MEDDOPROF shared task at IberLEF 2021 on automatic recognition, classification and normalization of professions and occupations from medical texts}, author={Lima-López, Salvador and Farré-Maduell, Eulàlia and Miranda-Escalada, Antonio and Brivá-Iglesias, Vicent and Krallinger, Martin}, journal = {Procesamiento del Lenguaje Natural}, volume = {67}, year={2021}, issn = {1989-7553}, url = {http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6393}, pages = {243--256} }</code></pre> <p><strong>Related Resources:</strong></p> <p>- <a href="http://temu.bsc.es/meddoprof">Web</a></p> <p>- <a href="https://doi.org/10.5281/zenodo.4694768">Training Data</a></p> <p>- <a href="https://doi.org/10.5281/zenodo.4889776">Test set</a></p> <p>- <a href="https://zenodo.org/record/4722741">Codes Reference List</a> (for MEDDOPROF-NORM)</p> <p>- <a href="https://zenodo.org/record/4720833">Annotation Guidelines</a></p> <p>- <a href="https://doi.org/10.5281/zenodo.4524658">Occupations Gazetteer</a></p> <p> </p> <blockquote> <p>MEDDOPROF is part of the IberLEF 2021 workshop, which is co-located with the SEPLN 2021 conference. For further information, please visit <a href="https://temu.bsc.es/meddoprof/">https://temu.bsc.es/meddoprof/</a> or email us at encargo-pln-life@bsc.es</p> <p>MEDDOPROF is promoted by the Plan de Impulso de las Tecnologías del Lenguaje de la Agenda Digital (Plan TL) and the Spanish government's 2020 Proyectos de I+D+i RTI Tipo A (AI4PROFHEALTH - DESCIFRANDO EL PAPEL DE LAS PROFESIONES EN LA SALUD DE LOS PACIENTES A TRAVES DE LA MINERIA DE TEXTOS (PID2020-119266RA-I00)).</p> </blockquote>
Complete pot, Enkelgraf-cultuur
Een vondst van de opgravingen op het industrieterrein Hattemerbroek in de gemeente Oldebroek. 'Bronstijd Opgespoord' is de titel van het archeologische rapport waarin de resultaten van de opgravingen worden beschreven. (Pagina 227 http://www.archol.nl/PDF/Archol_Rapport142_Bedrijvenpark_H2O.pdf) © Voerman Museum Source: Objaverse 1.0 / Sketchfab
Wmid-b799af - Complete die stamp
A complete lead alloy die stamp or punch of probable Late Medieval to Post Medieval dating (AD 1400 to AD 1800). The die stamp has been made from a sub conical shape. The base is circular and it tapers upwards to a flat horizontal handle. The shape is very similar to that of a human middle phalangeal (finger) bone. A circular hole (probably for suspension) is located slightly off centre, below the handle. It has an internal diameter of 3.0 mm. The base has a double curvilinear design in it, possibly representing the letters I C. For more information, please visit the online database record, available at: https://finds.org.uk/database/artefacts/record/id/1064547 Source: Objaverse 1.0 / Sketchfab
Supplementary figures and data for "Complete phylogeny of Micrathena spiders suggests multiple dispersal events among Neotropical rainforests, islands, and landmasses, and indicates Andean orogeny promotes speciation"
<p>Supplementary figures and data for "Complete phylogeny of <em>Micrathena</em> spiders suggests multiple dispersal events among Neotropical rainforests, islands, and landmasses, and indicates Andean orogeny promotes speciation" by Ivan L. F. Magalhaes, Pedro H. Martins, Bárbara T. Faleiro, Teofânia H. D. A. Vidigal, Fabrício R. Santos, Leonardo S. Carvalho, Adalberto J. Santos, submitted to <em>Cladistics</em>. </p> <p>Supplementary Figures S1 – S15</p> <p>Supplementary data S16: Complete specimen data of specimens used as vouchers for morphological scorings in Excel spreadsheet format.<br>Supplementary data S17: Discrete character matrix with morphological scorings in Nexus format.<br>Supplementary data S18: Complete specimen data of specimens used as vouchers for DNA sequencing in Excel spreadsheet format.<br>Supplementary data S19: Alignment of cytochrome oxidase I sequences in Fasta format.<br>Supplementary data S20: Alignment of histone H3 sequences in Fasta format.<br>Supplementary data S21: Alignment of 28S ribosomal sequences in Fasta format.<br>Supplementary data S22: Alignment of internal transcribed spacer sequences in Fasta format.<br>Supplementary data S23: Alignment of 16S ribosomal sequences in Fasta format.<br>Supplementary data S24: Zipped folder containing the inputs for estimating the phylogeny using morphological data in IQ-Tree: matrix in nexus format, partition file, and command file in plain text.<br>Supplementary data S25: Zipped folder containing the inputs for estimating the phylogeny using sequence data aligned with Muscle in IQ-Tree: matrix in nexus format, partition file, and command file in plain text.<br>Supplementary data S26: Zipped folder containing the inputs for estimating the phylogeny using sequence data aligned with MAFFT in IQ-Tree: matrix in nexus format, partition file, and command file in plain text.<br>Supplementary data S27: Zipped folder containing the inputs for estimating the phylogeny using morphological and sequence data aligned with MUSCLE in IQ-Tree: matrix in nexus format, partition file, and command file in plain text.<br>Supplementary data S28: Input Nexus for estimating the phylogeny using morphological data in MrBayes.<br>Supplementary data S29: Input Nexus for estimating the phylogeny using sequence data aligned with Muscle in MrBayes.<br>Supplementary data S30: Input Nexus for estimating the phylogeny using sequence data aligned with MAFFT in MrBayes.<br>Supplementary data S31: Input Nexus for estimating the phylogeny using morphological and sequence data aligned with Muscle in MrBayes.<br>Supplementary data S32: Input XML for estimating the dated phylogeny under Bayesian inference in BEAST.<br>Supplementary data S33: Distribution maps for all Micrathena species included in this study, the database with the original records and their source, and the R script used to generate the maps.<br>Supplementary data S34: Zipped folder containing all the inputs for estimating ancestral ranges and performing biogeographic stochastic mapping in R. This contains (0) the scripts for performing model selection and estimating ancestral states over a distribution of posterior trees, followed by stochastic mapping; (1) the geography and tree files (MMCT, and 100 trees randomly drawn from the posterior distribution); (2) the dispersal matrix and (3) the files for performing the time-stratified analysis to test the influence of the closure of the Isthmus of Panama on Micrathena dispersal.<br>Supplementary data S35: R script for generating the in-situ-speciation-through-time graphs from the results of biogeographic stochastic maps, as seen in Fig. 5.<br>Supplementary data S36: R script for getting and plotting elevations from individual records of Micrathena.<br>Supplementary data S37: R script for performing the GeoHiSSE estimation of net diversification rates among areas.<br>Supplementary data S38: Zipped folder containing the optimal trees found as a result of analysing inputs S24–S32 (IQ-Tree, MrBayes and BEAST).<br>Supplementary data S39: Zipped folder containing the ancestral range estimation results under competing models in BioGeoBEARS.<br>Supplementary data S40: Excel spreadsheet with parameter values of competing biogeographic models in BioGeoBEARS.<br>Supplementary data S41: Excel spreadsheet with results of biogeographic stochastic mapping over 100 different trees from the posterior distribution; includes all Micrathena species.<br>Supplementary data S42: Excel spreadsheet with results of biogeographic stochastic mapping over 100 different trees from the posterior distribution; includes only Micrathena species which had their DNA sequenced.<br>Supplementary data S43: Excel spreadsheet with the geography matrix, indicating which Micrathena species may be found in each area, and indicating the proportion of species from each area that are missing from the incomplete dataset (i.e., excluding species with unavailable DNA sequences).<br>Supplementary data S44: Excel spreadsheet with parameter values of competing biogeographic models estimated in GeoHiSSE.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S240422ed
<p>Attached in a .json file is the completed pointing information for 55 observation(s) for the EM counterpart search associated with the gravitational wave event S240422ed. These observations were taken on the ZTF, and WINTER instruments.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S240422ed
<p>Attached in a .json file is the completed pointing information for 24 observation(s) for the EM counterpart search associated with the gravitational wave event S240422ed. These observations were taken on the MLS10KCCD-CSS instrument.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S240422ed
<p>Attached in a .json file is the completed pointing information for 306 observation(s) for the EM counterpart search associated with the gravitational wave event S240422ed. These observations were taken on the Sinistro, and MuSCAT instruments.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event MS240429t
Attached in a .json file is the completed pointing information for 2 observation(s) for the EM counterpart search associated with the gravitational wave event MS240429t. These observations were taken on the DLT40 instrument.
Complete telomere-to-telomere genomes uncover virulence evolution conferred by chromosome fusion in oomycete plant pathogens
<p><span>Variations in chromosome number are occasionally observed among oomycetes, a group that includes many plant pathogens, but the emergence of such variations and their effects on genome and virulence evolution remain ambiguous. We generated complete telomere-to-telomere genome assemblies for <em>Phytophthora sojae</em>, <em>Globisporangium ultimum</em>, <em>Pythium oligandrum</em>, and <em>G. spinosum</em>. Reconstructing the karyotype of the most recent common ancestor in Peronosporales revealed that frequent chromosome fusion and fission drove changes in chromosome number. Centromeres enriched with <em>Copia</em>-like transposons may contribute to chromosome fusion and fission events. Chromosome fusion facilitated the emergence of pathogenicity genes and their adaptive evolution. Effectors tended to duplicate in the sub-telomere regions of fused chromosomes, which exhibited evolutionary features distinct to the non-fused chromosomes. By integrating ancestral genomic dynamics and structural predictions, we have identified secreted Ankyrin repeat-containing proteins (ANKs) as a novel class of effectors in <em>P. sojae</em>. Phylogenetic analysis and experiments further revealed that ANK is a specifically expanded effector family in oomycetes. These results revealed chromosome dynamics in oomycete plant pathogens, and provided novel insights into karyotype and effector evolution.</span></p>
Systematic DFT Modeling van der Waals Heterostructures from a Complete Configurational Basis Applied to γ-PC/WS2
<p>See the paper:</p> <p> </p> <p>Celis, J.; Cao, W. <em>J. Chem. Theory Comput.</em> <strong>2024</strong>, 20, 6, 2377-2389</p>
Supplementary files for: The oldest complete jawed vertebrates from the early Silurian of China
<p>Molecular studies suggest that the origin of jawed vertebrates was no later than the Late Ordovician period (around 450 million years ago (Ma)). Together with disarticulated micro-remains of putative chondrichthyans from the Ordovician and early Silurian period, these analyses suggest an evolutionary proliferation of jawed vertebrates before, and immediately after, the end-Ordovician mass extinction. However, until now, the earliest complete fossils of jawed fishes for which a detailed reconstruction of their morphology was possible came from late Silurian assemblages (about 425 Ma). The dearth of articulated, whole-body fossils from before the late Silurian has long rendered the earliest history of jawed vertebrates obscure. Here we report a newly discovered Konservat-Lagerstätte, which is marked by the presence of diverse, well-preserved jawed fishes with complete bodies, from the early Silurian (Telychian age, around 436 Ma) of Chongqing, South China. The dominant species, a 'placoderm' or jawed stem gnathostome, which we name <em>Xiushanosteus mirabilis</em> gen. et sp. nov., combines characters from major placoderm subgroups and foreshadows the transformation of the skull roof pattern from the placoderm to the osteichthyan condition. The chondrichthyan <em>Shenacanthus vermiformis</em> gen. et sp. nov. exhibits extensive thoracic armour plates that were previously unknown in this lineage, and include a large median dorsal plate as in placoderms, combined with a conventional chondrichthyan bauplan. Together, these species reveal a previously unseen diversification of jawed vertebrates in the early Silurian, and provide detailed insights into the whole-body morphology of the jawed vertebrates of this period.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event MS181101ab
Attached in a .json file is the completed pointing information for 25 observation(s) for the EM counterpart search associated with the gravitational wave event MS181101ab. These observations were taken on the DECam, ZTF, and DLT40 instruments.
Selection pressure analysis of dengue virus complete genome and E gene nucleotide sequences from Pakistan
<p>This dataset comprises 43 E gene and 44 complete genome nucleotide sequences of the dengue virus from serotypes DENV-1 to DENV-4, representing all documented sequences in Pakistan to date, sourced from the Virus Pathogen Resource (ViPR) database and NCBI. The E gene is critical as it is involved in serotype changes of the dengue virus, making it a pivotal target for understanding shifts in viral pathogenicity and immune escape mechanisms. The aim of compiling this dataset is to facilitate comprehensive genetic analysis and enhance understanding of the evolutionary dynamics of the dengue virus within the region. To assess the evolutionary pressures acting on these sequences, we conducted a selection pressure analysis utilizing computational methods. These methods include the Single Likelihood Ancestor Counting (SLAC), Fixed Effects Likelihood (FEL), adaptive Branch Site Random Effects Likelihood (aBSREL), Mixed Effects Model of Evolution (MEME), and the Genetic Algorithm for Recombination Detection (GARD), all implemented in the HyPhy software package. Our analysis focused on identifying genomic sites under both positive and negative selection pressures, providing insights into the adaptive evolutionary processes affecting the E gene of the dengue virus in Pakistan. Understanding the molecular evolution of this gene is crucial for predicting serotype evolution, potentially aiding in the development of effective vaccines and therapeutic strategies.</p>
Nucleotide sequence database of Copper-containing membrane monooxygenases genes for analysing primer pairs targeting the ammonia monooxygenase subunit A gene of complete ammonia oxidising Nitrospira
<p>Nucleotide sequences of 487 Cu-mmo genes, including amoA comammox clade A and clade B, amoA ammonia oxidizing bacteria as well as other Cu-mmo genes.</p>
NIS3D: A Completely Annotated Benchmark for Dense 3D Nuclei Image Segmentation
<p>NIS3D is an image segmentation benchmark containing over 22,000 manually annotated cells.</p> <p>Find more details here: https://github.com/yu-lab-vt/NIS3D</p>
Machine learning-based pulse wave analysis for classification of circle of Willis topology: an in silico study with 30,618 virtual subjects (database: Complete CoW)
<p>This repository contains the dataset for the complete CoW described in the article with the same name. MATLAB and Python codes for post-processing the dataset and the code for training and testing all machine learning models using the open-source library TensorFlow 2.12, the Keras application programming interface, and the Scikit-learn Python package can be found in here (<a href="https://zenodo.org/records/12519322" target="_blank" rel="noopener">https://zenodo.org/records/12519322</a>).</p>
Complete Data Set, Raman spectra for strains A/Nebraska/14/2019 and A/Hawaii/47/2014 collected at 785 nm and 532 nm
<p>This data contains Raman spectra for two different strains of Influenza A; A/Nebraska/14/2019 which is an H1N1 subtype and A/Hawaii/47/2014 which is an H3N2 subtype. There contains data for 10 separate growth cultures (i.e. 10 files) for each subtype, collected at two different wavelengths; 785 nm and 532 nm. This makes a total of 40 files. Each file has 400 spectra collected. All spectra were collected at 100x with a 5 second accumulation time. </p>
Complete classification of six-dimensional iso-edge domains
<p>This dataset contains the complete list of the 55.083.357 iso-edge domains in dimension 6. <br>The data is stored in a netCDF-4 data file. <br>For each iso-edge domain it contains 63 canonicalized 6-dimensional coordinates that represent the iso-edge domain.<br>Furthermore, for each iso-edge domain it contains the number of neighbouring iso-edge domains.</p> <p>The netCDF dimensions and variables are as follows:</p> <pre><code>netcdf ctype_dim6 { dimensions: number_ctype = UNLIMITED ; // (55083357 currently) n = 6 ; n_vect = 63 ; variables: int Ctype(number_ctype, n_vect, n) ; Ctype:long_name = "Ctype canonicalized coordinates" ; Ctype:units = "nondimensional" ; int nb_adjacent(number_ctype) ; nb_adjacent:long_name = "number of adjacent Ctypes" ; nb_adjacent:units = "nondimensional" ; }</code></pre> <p>The data can be extracted to a human readable format using for example the <em>ncdump</em> utility. </p>
DESI 2017_2022 ODDEA Project Complete Database
<p>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em><span>Project ID: HORIZON MSCA-SE 101086381)</span></em>. The file contains data for 27 EU countries in the years 2017 - 2022. The file contains 4 data sheets processed in the arrangement from general data (DESI Total) to detailed data (dimensions, sub-dimensions and indicators). The file also contains raw data collected in five sheets by topic and a sheet with a list of all indicators with their description.</p> <p>Dataset consist of two files. Excel file presents data and Word file presents DESI 2022 dimensions and indicators list. </p> <p> </p>
Data Set for Self-adapting short-range correlation functional for complete active space-based approximations
<p>Data Set to accompany:</p> <p> Self-adapting short-range correlation functional for complete active space-based approximations</p>
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