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545 results for “Latin”
Figure 27. Torrenticola dispersa. A–D in Studies on Latin American water mites of the genus Torrenticola Piersig, 1896 (Torrenticolidae, Hydrachnidia, Acari)
Figure 27. Torrenticola dispersa. A–D, female (CR 70). A, idiosoma, ventral view; B, idiosoma, dorsal view; C, capitulum with right palp, lateral view; D, left palp, medial view. Scale bars = 100 µm.
Figure 14. Torrenticola fontinale. A–D in Studies on Latin American water mites of the genus Torrenticola Piersig, 1896 (Torrenticolidae, Hydrachnidia, Acari)
Figure 14. Torrenticola fontinale. A–D, paratype female (CR 201). A, idiosoma, ventral view; B, idiosoma, dorsal view; C, capitulum with right palp, lateral view; D, left palp, medial view. Scale bars = 100 µm.
ICFHR 2016 Competition on the Classification of Medieval Handwritings in Latin Script - Dataset
<p>The ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script (CLaMM), jointly organized by Computer Scientists and Humanists (paleographers) provided a rich database of European medieval manuscripts to the community on Handwriting Analysis and Recognition.</p> <p>If you use this dataset, please cite:</p> <p>Florence Cloppet, Véronique Eglin, Van Cuong Kieu, Dominique Stutzmann, and Nicole Vincent, "ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script", <em>Proceedings of International Conference on Frontiers in Handwriting Recognition</em>, Los Alamos : IEEE, 2016, p. 590-595. [<a href="https://doi.org/10.1109/ICFHR.2016.0113">https://doi.org/10.1109/ICFHR.2016.0113</a>]</p> <p>At this competition, we proposed two independent classification tasks which attracted five participants with seven submitted classifiers. Those classifiers are trained on a set of 2000 images with their ground truths. In the first task of script crisp classification, the classifiers have been evaluated on a test set of 1000 single-type manuscripts. In the second task of “Fuzzy Classification”, the classifiers have been carried out on a set of 2000 multi-script-type manuscripts.</p> <p>The present dataset contains the training dataset, both test datasets (task 1 and task 2) and the matrices provided by the competitors. It was first published on a https://clamm.irht.cnrs.fr/icfhr2016-clamm/ in Oct. 2016.</p> <p> </p>
Dataset and evaluation for HTR models for Latin and French Medieval Documentary Manuscripts
<p><strong>1. Dataset presentation.</strong></p> <p>This is the dataset used to produce the HTR models applied to documentary Latin and French manuscripts presented in the paper: Sergio Torres Aguilar, Vincent Jolivet. <strong>Handwritten Text Recognition for Documentary Medieval<br> Manuscripts. </strong>2022. https://hal.science/hal-03892163</p> <p>The dataset contains mostly charters and registers from the Late-medieval period (12th-15th). The training and evaluation, entailing 1855 pages, 120k lines of text and almost 1M tokens, were conducted using three freely available ground-truth corpora :</p> <p><strong>The Alcar-HOME database </strong>: https://zenodo.org/record/5600884</p> <p><strong>The e-NDP corpus </strong>: https://github.com/chartes/e-NDP_HTR</p> <p><strong>The Himanis project </strong>: https://zenodo.org/record/5535306</p> <p>The final model operates in a multilingual environment (Latin and French) and it is able to recognize several Latin script families (mostly <em>Textualis</em> and <em>Cursiva</em>) in documents produced in ca. 12th - 15th centuries. During the evaluation the models shows an accuracy of <strong>94.01%</strong> on the validation set and a CER (character error ratio) of about <strong>0.12</strong> to <strong>0.17</strong> on four external unseen datasets. A fine-tuning exercise using 10 ground-truth pages can raise these results to a CER between <strong>0.06</strong> to <strong>0.10</strong> respectively.</p> <p> </p> <p><strong>2. Dataset contents .</strong></p> <p>a) <em>GT_list : </em>List containing the GT file names which constitute the training, evaluation and test sets. The images and transcriptions can be downloaded from their original repositories.</p> <p>b) <em>Training :</em> Contains the training and testing results (evaluation and prediction files) presented in the original paper for the two training phases: Regular (Textualis and Cursiva separated training) and Quartiles (mixed training by quartiles).</p> <p>c) <em>Useful_scripts :</em> Scripts to produce the HTR metrics (CER, WER, SER) and plot the model's accuracy.</p> <p>d) <em>Best_model :</em> Contains the best multilingual and multi-script model.</p>
Data Hospital Beds, Physicians, Nurses and Expenditure for 20 Latin American Countries from 1960 to 2022
<p>Long-term quantitative series for 20 Latin American countries, spanning from 1960 to 2020, on the number of hospital beds, physicians, nurses and healthcare expenditure.</p> <p>Matus-Lopez, M. and Fernández Pérez, P. 2023. "Transformations in Latin American Healthcare: A Retrospective Analysis of Hospital Beds, Medical Doctors, and Nurses from 1960 to 2022". <em>Journal of Evolutionary Studies in Business</em>.</p> <p>The information was extracted from official reports and cross-country databases. Official reports were available in digital format in the Institutional Repository for Information Sharing (IRIS) of Pan American Health Organization (PAHO). They were summary of four-year reports on Health Conditions in the Americas (PAHO 1962, 1966, 1970, 1974, 1978, 1982, 1986, 1990, 1994, 1998, 2002a), annual reports of Basic Indicators (PAHO 2002b, 2007, 2008, 2010, 2013), Health in South America (PAHO 2012) and Core Indicators (PAHO 2016). Databases were Open Data Portal of the Pan American Health Organization (PLISA) (PAHO 2023), Core Indicator Database provided directly by PAHO (PAHO 2022), Data Portal of National Health Workforce Accounts of the World Health Organization (NHWA) (WHO 2022), and the Global Health Expenditure Database of the World Health Organization (GHED) (WHO 2023).</p> <p>Serie 1. Hospital Beds per 1,000 inhabitants</p> <p>Serie 2. Physicians per 10,000 inhabitants</p> <p>Serie 3. Nurses per 10,000 inhabitants</p> <p>Serie 4. Government spending on health, per capita. Constant US dollars of 2020</p> <p>Cite as:</p> <p> </p> <p> </p>
Study of a Novel Tetravalent Dengue Vaccine in Healthy Children and Adolescents Aged 9 to 16 Years in Latin America
ClinicalTrials.gov study NCT01374516. IPD Sharing: YES. Countries: 5. Publications: 15.
Immunogenicity and Safety of Sanofi Pasteur's CYD Dengue Vaccine in Healthy Children and Adolescents in Latin America
ClinicalTrials.gov study NCT00993447. IPD Sharing: YES. Countries: 4. Publications: 2.
Scaling Up Science-based Mental Health Interventions in Latin America
ClinicalTrials.gov study NCT03392883. IPD Sharing: YES. Countries: 1. Publications: 1.
Test Data from a Study on Latin Vocabulary Acquisition with Beginners (Textbook)
<p>The dataset contains test results from an intervention study with beginners in the 5th grade of a high school in Berlin. In total, 103 students participated in four groups (= classes). The intervention materials and tests are published as well.</p> <p>A key question of the still ongoing research project is: How can vocabulary competence in a historical language such as Latin be acquired and deepened by using corpus-based, i.e. context-based, methods? This question is based on a broad understanding of vocabulary that refers back to theories of the mental lexicon.</p>
The Marginal Latin (LaM) readings of 2 Samuel - all the cases collected
<p>Collected textual cases for my SBL 2020 paper "The Marginal Latin (LaM) readings of 2 Samuel".</p>
An Artificial Eye for Palaeography. Applying Deep Machine Learning for the Study of Medieval Latin Scripts
<p>The project “Digital Forensics for Historical Documents” (at Huygens ING, Amsterdam) attempts to create a digital tool, based on a deep learning system, in which the unique characteristics of one medieval script sample will be matched with similar script samples by making use of digitized manuscript collections available in the world wide web.</p> <p>Project website and contact: <a href="https://www.youtube.com/redirect?q=https%3A%2F%2Fen.huygens.knaw.nl%2Fprojecten%2Fdigital-forensics-for-historical-documents%2F&v=WYtseNK-1Dc&event=video_description&redir_token=QUFFLUhqbDM0WDRJRjN0V3QzOXV6d0ZNbDB2TVYzV1hUQXxBQ3Jtc0ttLVJHMEE1RlRkZjJVV3poYnpQOHZseTFzZHVqWHRGR2k2eWpVWTJSSldtV2p4aFhKbFRIQTFjVHQ5YnM0Mkd4ajBzOTNtdE1yOVJLVktqWlhqWUgzZXc3YmNQMS1nNGFpZ3p2amNOTFNqTDVUSTdtZw%3D%3D">https://en.huygens.knaw.nl/projecten/...</a> </p> <p>Presented as a Lightning Talk for the Schoenberg Symposium 2020</p>
KD040-002016 - Cross Slab - Latin
Pre-1200 cross-slab. A recumbent, tapering granite slab (dims. L 1.7m; Wth 0.28-0.41m; T 0.18m) with a Latin cross carved in relief, but slightly off-centre, with a central, diamond-shaped boss (diam. 0.15m). Located west of the South High Cross in St James' Graveyard. Survey: [@Dh_Age](https://www.digitalheritageage.com/) Funded: Kildare County Council Community Heritage Grant 2017 Source: Objaverse 1.0 / Sketchfab
Paphos, Cyprus. Tomb slab, Latin church in the Chrysopolitissa complex.
<p>Paphos, Cyprus. Tomb slab, Latin church in the Chrysopolitissa complex, made from an antique pillar, split in half; dated 1312. As documented in 1974.</p>
Education- and age-specific fertility rates for 50 African and Latin American countries between 1970 and 2020
<p><strong>Version 2</strong></p> <p>Education- and age-specific fertility rates for 50 African and Latin American countries between 1970 and 2020 as published in<strong> <a href="https://www.demographic-research.org/articles/volume/49/31/">Durowaa-Boateng et. al (2023</a></strong><a href="10.4054/DemRes.2023.49.31">)</a>. </p> <p>The data and figures can be accessed and downloaded from <strong><a href="https://populationafrica.org/">https://populationafrica.org/</a>.</strong></p> <p> </p> <p><strong>Education- and age-specific fertility rates for 50 African and Latin American countries between 1970 and 2020</strong>.</p> <p>The fertility rates are consistent with the United Nation's World Population Prospects (UN WPP) 2022 fertility rates.</p> <p>The Bayesian model developed to reconstruct the fertility rates using Demographic and Health Surveys and the UN WPP is published in a <a href="https://pure.iiasa.ac.at/id/eprint/18890/">working paper</a>.</p> <p><strong>Abstract:</strong></p> <p>Consistent and reliable time series of education- and age-specific fertility rates for the past are difficult to obtain in developing countries, although they are needed to evaluate the impact of women’s education on fertility along periods and cohorts. In this paper, we propose a Bayesian framework to reconstruct age-specific fertility rates by level of education using prior information from the birth history module of the Demographic and Health Surveys (DHS) and the UN World Population Prospects. In our case study regions, we reconstruct age- and education-specific fertility rates which are consistent with the UN age specific fertility rates by four levels of education for 50 African and Latin American countries from 1970 to 2020 in five-year steps. Our results show that the Bayesian approach allows for estimating reliable education- and age-specific fertility rates using multiple rounds of the DHS surveys. The time series obtained confirm the main findings of the literature on fertility trends, and age and education specific differentials.</p> <p><strong>Funding:</strong></p> <p>These data sets are part of the <a href="https://www.oeaw.ac.at/vid/research/research-projects/bayesedu">BayesEdu Project </a>at Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna) funded from the “Innovation Fund Research, Science and Society” by the Austrian Academy of Sciences (ÖAW).</p> <p><strong>Variables:</strong></p> <p>Country: Country names</p> <p>Education: Four education levels, No Education, Primary Education, Secondary Education and Higher Education.</p> <p>Age group: Five-year age groups between 15-19 and 45-49. </p> <p>Year: Five-year periods between 1970 and 2020.</p> <p>Median: Median education and age-specific fertility rate estimate </p> <p>Upper_CI: 95% Upper Credible Interval</p> <p>Lower_CI: 95% Lower Credible Interval</p> <p> </p> <p><strong>List of countries:</strong></p> <table> <tbody> <tr> <td> <p>Angola</p> </td> </tr> <tr> <td> <p>Benin</p> </td> </tr> <tr> <td> <p>Brazil</p> </td> </tr> <tr> <td> <p>Burkina Faso</p> </td> </tr> <tr> <td> <p>Burundi</p> </td> </tr> <tr> <td> <p>Cameroon</p> </td> </tr> <tr> <td> <p>Central African Republic</p> </td> </tr> <tr> <td> <p>Chad</p> </td> </tr> <tr> <td> <p>Colombia</p> </td> </tr> <tr> <td> <p>Comoros</p> </td> </tr> <tr> <td> <p>Congo</p> </td> </tr> <tr> <td> <p>Côte D'Ivoire</p> </td> </tr> <tr> <td> <p>DR Congo</p> </td> </tr> <tr> <td> <p>Ecuador</p> </td> </tr> <tr> <td> <p>Egypt</p> </td> </tr> <tr> <td> <p>Eswatini</p> </td> </tr> <tr> <td> <p>Ethiopia</p> </td> </tr> <tr> <td> <p>Gabon</p> </td> </tr> <tr> <td> <p>Gambia</p> </td> </tr> <tr> <td> <p>Ghana</p> </td> </tr> <tr> <td> <p>Guatemala</p> </td> </tr> <tr> <td> <p>Guinea</p> </td> </tr> <tr> <td> <p>Honduras</p> </td> </tr> <tr> <td> <p>Kenya</p> </td> </tr> <tr> <td> <p>Lesotho</p> </td> </tr> <tr> <td> <p>Liberia</p> </td> </tr> <tr> <td> <p>Madagascar</p> </td> </tr> <tr> <td> <p>Malawi</p> </td> </tr> <tr> <td> <p>Mali</p> </td> </tr> <tr> <td> <p>Mexico</p> </td> </tr> <tr> <td> <p>Morocco</p> </td> </tr> <tr> <td> <p>Mozambique</p> </td> </tr> <tr> <td> <p>Namibia</p> </td> </tr> <tr> <td> <p>Nicaragua</p> </td> </tr> <tr> <td> <p>Niger</p> </td> </tr> <tr> <td> <p>Nigeria</p> </td> </tr> <tr> <td> <p>Paraguay</p> </td> </tr> <tr> <td> <p>Peru</p> </td> </tr> <tr> <td> <p>Rwanda</p> </td> </tr> <tr> <td> <p>Sao Tome and Principe</p> </td> </tr> <tr> <td> <p>Senegal</p> </td> </tr> <tr> <td> <p>Sierra Leone</p> </td> </tr> <tr> <td> <p>South Africa</p> </td> </tr> <tr> <td> <p>Sudan</p> </td> </tr> <tr> <td> <p>Tanzania</p> </td> </tr> <tr> <td> <p>Togo</p> </td> </tr> <tr> <td> <p>Tunisia</p> </td> </tr> <tr> <td> <p>Uganda</p> </td> </tr> <tr> <td> <p>Zambia</p> </td> </tr> <tr> <td> <p>Zimbabwe</p> </td> </tr> </tbody> </table>
Water ethics and substantive democracy. Lessons from the Latin American Water Tribunal.
<p>Presentation made at Panel 5, the Educational, Ethical, and Preservationist Water Question, The Youth and the Climatic Struggle, First International Forum of the Federal University of Pernambuco (UFPE), in Preparation for the 2025 UNCOP30, 21-24 November 2023 Recife, Pernambuco, Brazil.</p>
Abbeyville - TN004-022001 - Latin Inscription
Lackeen Castle is an important site in Irish history. An O'Kennedy stronghold (Smyth 1985, 118) of sixteenth-century date which belonged to Brian Ua Cinneide Fionn, Chieftain of Ormond who died in 1588 (Harbison 1970, 230). Described in the Civil Survey (1654-6) as an 'old ruined castle & bawne of Leackeene the walls onely standing an orchard and garden' (Simington 1934, vol. 2, 315). Donogh Kenedy is listed as proprietor in 1640 (ibid.) The Stowe Missal was held at this site at one time. An Irish illuminated manuscript written mainly in Latin with some Gaelic in the late eighth or early ninth century, probably after 792. In the mid-11th century it was annotated and some pages rewritten at Lorrha Monastery in County Tipperary, Ireland. Also known as the Lorrha Missal. This medieval grafithi appears to show the name of Dermot Kenneddy, who returned to the site after being expelled by the English. The carving inlcudes Kennedys name and the date 1651 or 7. Discovered by David Broderick Source: Objaverse 1.0 / Sketchfab
Latin Cross Cathedral
This is for my final project at Sripathum University in summer semester. I hope you guys like it Source: Objaverse 1.0 / Sketchfab
In search for Old Greek readings: The Old Latin manuscript Palimpsestus Vindobonensis (La115) in 2 Samuel - the collation file for SBL 2021
<p>Collected cases for my SBL 2021 paper "In search for Old Greek readings: The Old Latin manuscript Palimpsestus Vindobonensis (La115) in 2 Samuel"</p>
Dataset for the paper "Ground-truth Free Evaluation of HTR on Old French and Latin Medieval Literary Manuscripts"
<p>This dataset was used in the context of the article <em>Ground-truth Free Evaluation of HTR on Old French and Latin Medieval Literary Manuscripts</em>, at the Computational Humanities Research 2022 conference.</p> <p>Predictions.zip contains the XML ALTO for the HTR and Segmentation prediction of around 10 pages of 1900 manuscripts from the Bibliothèque nationale de France.</p> <p>Varying ground truth contains the original training material for training a classifier for CER classification (see the article).</p> <p>The ManuscriptsIIIF.csv contains metadata about the manuscripts.</p> <p>This work was funded by the DIM MAP under the CREMMALab funding.</p>
Latin MS 182
Bede's Historia ecclesiastica gentis Anglorum, with the Continuo Bedae and two miracle stories, formerly owned by - and possibly produced at - the Benedictine Abbey of (Mönchen-)Gladbach, Germany in the twelfth century. Ancient binding, parchment over wooden boards, carefully restored. The 12th century script is in double columns of 31 lines, a very fine upright minuscule. Some coloured initials. Creator: Bede, the Venerable, Saint, 673-735 https://www.digitalcollections.manchester.ac.uk/view/MS-LATIN-00182/1 Source: Objaverse 1.0 / Sketchfab
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.