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1,773
datasets available to search
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1,773 results for “mines”
Fig. 68–74. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 68–74. O. vimmeri Černý: 68, 69 — male head; 70 — phallus, lateral view; 71 — same, ventral view; 72 — female head; 73 — egg guide, left blade; 74 — spermatheca. Scale bar 0.1 mm.
Fig. 57–60. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 57–60. O. simplex (Loew): 57, 58 — male head; 59 — phallus, ventral view (without basifallus); 60 — same, lateral view (without basifallus). Scale bar 0.1 mm.
Fig. 38–43. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 38–43. O. orbiculata (Hendel): 38, 39 — male head; 40 — phallus, lateral view; 41 — female head; 42 — egg guide, left blade; 43 — spermatheca. Scale bar 0.1 mm.
Fig. 25–31. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 25–31. O. longilingua (Hendel): 25, 26 — male head; 27 — phallus, lateral view; 28 — same, ventral view; 29 — female head; 30 — egg guide, left blade; 31 — spermatheca. Scale bar 0.1 mm.
Fig. 18–24. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 18–24. O. cunctata (Hendel): 18, 19 — male head; 20 — phallus, ventral view; 21 — same, lateral view; 22 — female head; 23 — egg guide, left blade; 24 — spermatheca. Scale bar 0.1 mm.
Fig. 5–11. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 5–11. O. aeneonitens (Strobl): 5, 6 — male head; 7 — phallus, ventral view; 8 — same, lateral view; 9 — female head; 10 — egg guide, left blade; 11 — spermatheca. Scale bar 0.1 mm.
Fig. 61–67. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 61–67. O. vanyushai sp. n., holotype: 61, 62 — male head; 63 — phallus, lateral view; 64 — same, ventral view; paratype: 65 — female head; 66 — egg guide, left blade; 67 — spermatheca. Scale bar 0.1 mm.
Fig. 1–4. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 1–4. O. adunca sp. n., holotype: 1, 2 — male head; 3 — phallus, ventral view; 4 — same, lateral view. Scale bar 0.1 mm.
Fig. 50–56. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 50–56. O. pulicaria (Meigen): 50, 51 — male head; 52 — phallus, dorsal view; 53 — same, lateral view; 54 — same, ventral view; 55 — egg guide, left blade; 56 — spermatheca. Scale bar 0.1 mm.
Fig. 44–49. O in Mining Flies Of The Genus Ophiomyia (Diptera, Agromyzidae) Of Eastern Ukraine And Adjacent Territories: Review Of The Species Without A Fasciculus
Fig. 44–49. O. pinguis (Fallén): 44, 45 — male head; 46 — phallus, lateral view; 47 — same, ventral view; 48 — egg guide, left blade; 49 — spermatheca. Scale bar 0.1 mm.
Datasets for the publication "Sedimentation Kinetics of Hydrous Ferric Oxides in Ferruginous, Circumneutral Mine Water"
<p>This file contains datasets that were generated during laboratory-based column sedimentation experiments. The article was published in Environmental Science & Technology (accepted April 8, 2022).</p>
Dataset: Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training
<p>This repository contains supplementary materials for the following journal paper:</p> <p>Valdemar Švábenský, Jan Vykopal, Pavel Čeleda, Lydia Kraus.<br> <em>Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training.</em><br> In Springer Education and Information Technologies. 2022.<br> <a href="https://doi.org/10.1007/s10639-022-11093-6">https://doi.org/10.1007/s10639-022-11093-6</a></p> <p>Preprint available at: <a href="https://arxiv.org/abs/2307.08582">https://arxiv.org/abs/2307.08582</a></p> <ul> </ul> <p><strong>How to cite</strong></p> <p>If you use or build upon the materials, please use the BibTeX entry below to cite the original paper (not only this web link).</p> <pre><code>@article{Svabensky2022applications, author = {\v{S}v\'{a}bensk\'{y}, Valdemar and Vykopal, Jan and \v{C}eleda, Pavel and Kraus, Lydia}, title = {{Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training}}, journal = {Education and Information Technologies}, publisher = {Springer}, volume = {27}, year = {2022}, issn = {1360-2357}, url = {https://doi.org/10.1007/s10639-022-11093-6}, doi = {10.1007/s10639-022-11093-6}, }</code></pre> <p><strong>Attached content</strong></p> <p>The files included in the ZIP archive are:</p> <ul> <li>`All-discovered-papers.bib` -- a BibTeX export of the Mendeley database of all considered papers discovered by the automated search.</li> <li>`Candidate-papers-reviewer1.bib` -- a BibTeX export of the Mendeley database of the candidate papers suggested by the first investigator.</li> <li>`Candidate-papers-reviewer2.bib` -- a BibTeX export of the Mendeley database of the candidate papers suggested by the second investigator.</li> <li>`Selected-papers.bib` -- a BibTeX export of the Mendeley database of the 35 papers selected for the literature review.</li> <li>`Selected-papers.xlsx` -- an Excel spreadsheet with the extracted information about the selected papers.</li> <li>`Selected-papers.csv` -- a CSV equivalent of the Excel spreadsheet.</li> </ul>
Dataset and Puppet Issues Mining
<p>Mining Puppet and Dataset</p>
Genome Mining for Data Carpentry lesson
<p>Data for Software Carpentry Genome Mining lesson. These data are part of the study<em> "Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial pan-genome" </em>(Hervé Tettelin et al 2005)</p>
Classification of unstructured text in types of violence against women using text mining and Machine learning techniques
<p>These are the data used for the development of the investigation.</p> <p>This file was extracted from our mongoDB database. The data set contains real news of violence against women, which were organized with their date, the title and the body of the news.</p>
A topic modelling application for violence against the women through text mining techniques
<p>This research was focused on a social problem that affects worldwide. Violence Against Women (VAW) and girls occurs in many forms with different levels of aggressiveness. There is a wide amount of data on the internet about real cases of VAW that can be gathered for further study. Many researchers have done studies on structured data sets which facilitates their manipulation and understanding. But in this work digital news (data source large non-structured text) was used.</p> <p>These are the data used for the development of the investigation.This file was extracted from our mongoDB database. The data set contains real news of violence against women, which were organized with their date, the title and the body of the news.</p>
Mining minerals and critical raw materials from bittern: Understanding metal ions fate in saltwork ponds
<p>Seawater represents a potential resource for raw materials extraction. Although NaCl is the most representative mineral<br> extracted other valuable compounds such as Mg, Li, Sr, Rb and B and elements at trace level (Cs, Co, In, Sc, Ga and<br> Ge) are also contained in this “liquid mine”. Most of them are considered as Critical Raw Materials by the European<br> Union. Solar saltworks, providing concentration factors of up-to 20 to 40, offer a perfect platform for the development<br> of minerals and metal recovery schemes taking benefit of the concentration and purification achieved along the evaporation<br> saltwork ponds.<br> However, the geochemistry of these elements in this environment has not been yet thoroughly evaluated. Their knowledge<br> could enable the deployment of technologies capable to achieve the recovery of valuable minerals. The high ionic<br> strengths expected (0.5–7 mol/kg) and the chemical complexity of the solutions imply that only numerical geochemical<br> codes, as PHREEQC, and the use of Pitzer model to estimate the activity coefficients of the different species in solution<br> can be adopted to provide valuable description of the systems.<br> In the present work, for the first time, PHREEQC Pitzer code database was extended to include the target minor and<br> trace elements using Trapani saltworks (Sicily, Italy) as a case study system. The model was able to predict: i) the purity<br> in halite and the major impurities contained, mainly Ca,Mgand sulphate species; ii) the fate of minor components as B,<br> Sr, Cs, Co, Ge and Ga along the evaporation ponds. The results obtained pose a fundamental step in critical raw materials<br> mining from seawater brine, for process intensification and combination with desalination.</p>
An Empirical Evaluation of Unsupervised Event Log Abstraction Techniques in Process Mining
<p>This upload contains the event logs, generated by L-Sim, on which the experiments of the related paper were performed.</p><p>The related paper is accepted in the journal Information Systems.</p>
Historical Mine Register & Place Gazetteer: Schwaz / Rottenburg / Rattenberg, Tyrol; 17th Century
<p>The data of the historical registers is based on the historical document “Bergbeschau Schwaz/Rottenburg/Rattenberg” of the 17<sup>th</sup> century (approx. 1666). The document is currently stored by the Salinenarchiv Bad Ischl) using the Identifier XXD6.The document contains 6 coloured maps of the mining areas in the mining district of Schwaz (Falkenstein, Ringenwechsel, Mehren/Merach, Reichental, Palleiten) as well as the mining district of Rattenberg (Groß-, Kleinkogel, Geyer). Furthermore, it contains detailed mine descriptions and localisations of the mines in the maps.</p> <p>Historical Mine Register: Sorting is done by mining area, main pit / mine and associated mine sections. The historical writings of the mines and mine sections are summarized in separate columns (alternate writing). Mines written in capital letters symbolize latin characters within the historical document. All mines received an Identifier and URIs which lead to a Knowledge Graph (graph_Link). In a separate column the mines also received a standard spelling (mine_name_standard). The mentioned mines were compared to two geological maps created by Herwig Pirkl (1961). Mines that could be also be georeferenced by comparison also received a geo_link to OpenStreetMap as well as HIK (‘Historische Kartenwerke Tirol’). Finally, the historical mines of the “Bergbeschau” are also linked to the Knowledge Graph TMMMT (DOI: 10.5281/zenodo.6276586) of the UIBK Project „Text Mining Medieval Mining Texts“, whenever possible.</p> <p>The historical place gazetteer is in alphabetical order by place_standard. The historical writings of the place names are summarized in a separate column (alternate writing). Places written in capital letters symbolize latin characters within the historical document. All places received an Identifier and URIs which lead to a Knowledge Graph (graph_Link). In a separate column the places received their current standard spelling (place_standard). Places that could be also be georeferenced also received coordinates as well as a geo_link to OpenStreetMap. Finally, the historical places of the “Bergbeschau” are also linked to the Knowledge Graph TMMMT (DOI: 10.5281/zenodo.6276586) of the UIBK Project „Text Mining Medieval Mining Texts“, whenever possible.</p>
Text-fig. 4. Porechye open pit coal mine. a: photography of the Lipovtsy Formation section; b: stratigraphic column, 1 – sandstone, 2 – conglomerate, 3 – coal, 4 – tuff dated by U-Th-Pb geochronology, 5 – siltstone, 6 – mudstone, 7 – palynological samples with angiosperm pollen, 8 – dispersed angiosperm cuticles. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 4. Porechye open pit coal mine. a: photography of the Lipovtsy Formation section; b: stratigraphic column, 1 – sandstone, 2 – conglomerate, 3 – coal, 4 – tuff dated by U-Th-Pb geochronology, 5 – siltstone, 6 – mudstone, 7 – palynological samples with angiosperm pollen, 8 – dispersed angiosperm cuticles.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.