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2,863 results for “Challenge”
CrowdAI / OpenSNP - height prediction challenge - dataset
<p>OpenSNP data used in the CrowdAI challenge, https://www.crowdai.org/challenges/opensnp-height-prediction</p> <p>It contains both training set and test set with individuals' height (including what was kept secret during the challenge)</p> <p>It contains both the subset and the full set</p>
Challenge Image 3
<p>3eme image pour la semaine Innovation & Recherche</p>
Challenge Image 1
<p>1ere image pour la semaine Innvoation & Recherche</p>
Challenge Image 2
<p>2eme image pour la semaine Innovation & Recherche</p>
Billion Triple Challenge (BTC) 2019 Dataset
<p>The Billion Triple Challenge (BTC) 2019 Dataset is the result of a large-scale RDF crawl (accepting RDF/XML, Turtle and N-Triples) conducted from 2018/12/12 until 2019/01/11 using <a href="https://github.com/ldspider/ldspider">LDspider</a>. The data are stored as quads where the fourth element encodes the location of the Web document from which the associated triple was parsed. The dataset contains 2,155,856,033 quads, collected from 2,641,253 RDF documents on 394 pay-level domains. Merging the data into one RDF graph results in 256,059,356 unique triples. These data (as quads or triples) contain 38,156 unique predicates and instances of 120,037 unique classes.</p> <p>If you would like to use this dataset as part of a research work, we would ask you to please consider citing our paper:</p> <blockquote> <p>José-Miguel Herrera, Aidan Hogan and Tobias Käfer. "<a href="http://aidanhogan.com/docs/btc2019.pdf">BTC-2019: The 2019 Billion Triple Challenge Dataset </a>". In the Proceedings of the 18th International Semantic Web Conference (ISWC), Auckland, New Zealand, October 26–30, 2019 (Resources track).</p> </blockquote> <p>The dataset is published in three main parts:</p> <ol> <li><strong>Quads</strong>:<strong> (*nq.gz)</strong>: contains the quads retrieved during the crawl (N-Quads, GZipped). These data are divided into individual files for each of the top 100 pay-level-domains by number of quads contributed (btc2019-[<em>domain</em>]_000XX.nq.gz). While most domains have one file, larger domains are further split into parts (000XX) with approximately 150,000,000 quads each. Finally, quads from the 294 domains not in the top 100 are merged into one file: btc2019-other_00001.nq.gz.</li> <li><strong>Triples</strong>:<strong> (btc2019-triples.nt.gz)</strong>: contains the unique triples resulting from taking all quads, dropping the fourth element (indicating the location of the source document) and computing the unique triples.</li> <li><strong>VoID (void.nt)</strong>: contains a <a href="https://www.w3.org/TR/void/">VoID</a> file offering statistics about the dataset.</li> </ol> <p>For parsing the files, we recommend a streaming parser, such as <a href="http://librdf.org/raptor/rapper.html">Raptor</a>, <a href="http://docs.rdf4j.org/programming/#_parsing_and_writing_rdf_with_rio">RDF4j/Rio</a>, or <a href="https://github.com/nxparser/nxparser">NxParser</a>.</p> <p>The data are sourced from 2,641,253 RDF documents. The <strong>top-10 pay-level-domains in terms of documents</strong> contributed are:</p> <ol> <li><em>dbpedia.org</em> 162,117 documents (6.14%)</li> <li><em>loc.gov</em> 150,091 documents (5.68%)</li> <li><em>bnf.fr</em> 146,186 documents (5.53%)</li> <li><em>sudoc.fr</em> 144,877 documents (5.49%)</li> <li><em>theses.fr</em> 141,228 documents (5.35%)</li> <li><em>wikidata.org</em> 141,207 documents (5.35%)</li> <li><em>linkeddata.es</em> 130,459 documents (4.94%)</li> <li><em>getty.edu</em> 130,398 documents (4.94%)</li> <li><em>fao.org</em> 92,838 documents (3.51%)</li> <li><em>ontobee.org</em> 92,812 documents (3.51%)</li> </ol> <p>The data contain 2,155,856,033 quads. The <strong>top-10 pay-level-domains in terms of quads</strong> contributed are:</p> <ol> <li><em>wikidata.org</em> 2,006,338,975 quads (93.06%)</li> <li><em>dbpedia.org</em> 36,686,161 quads (1.70%)</li> <li><em>idref.fr</em> 22,013,225 quads (1.02%)</li> <li><em>bnf.fr</em> 12,618,155 quads (0.59%)</li> <li><em>getty.edu</em> 7,453,134 quads (0.35%)</li> <li><em>sudoc.fr</em> 7,176,301 quads (0.33%)</li> <li><em>loc.gov</em> 6,725,390 quads (0.31%)</li> <li><em>linkeddata.es</em> 6,485,114 quads (0.30%)</li> <li><em>theses.fr</em> 4,820,874 quads (0.22%)</li> <li><em>ontologycentral.com</em> 4,633,947 quads (0.21%)</li> </ol> <p>The data contain 256,059,356 unique triples. The <strong>top-10 pay-level-domains in terms of unique triples</strong> contributed are:</p> <ol> <li><em>wikidata.org</em> 133,535,555 triples (52.15%)</li> <li><em>dbpedia.org</em> 32,981,420 triples (12.88%)</li> <li><em>idref.fr</em> 16,820,681 triples (6.57%)</li> <li><em>bnf.fr</em> 11,769,268 triples (4.60%)</li> <li><em>getty.edu</em> 6,571,525 triples (2.57%)</li> <li><em>linkeddata.es</em> 5,898,762 triples (2.30%)</li> <li><em>loc.gov</em> 5,362,064 triples (2.09%)</li> <li><em>sudoc.fr</em> 4,972,647 triples (1.94%)</li> <li><em>ontologycentral.com</em> 4,471,962 triples (1.75%)</li> <li><em>theses.fr</em> 4,095,897 triples (1.60%)</li> </ol> <p>If you wish to download all N-Quads files, the following may be useful to copy and paste in Unix:</p> <pre><code>wget https://zenodo.org/record/2634588/files/btc2019-acropolis.org.uk_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-aksw.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-babelnet.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-bbc.co.uk_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-berkeleybop.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-bibliotheken.nl_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-bl.uk_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-bne.es_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-bnf.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-camera.it_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-cervantesvirtual.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-chemspider.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-cnr.it_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-comicmeta.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-crossref.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-cvut.cz_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-d-nb.info_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-datacite.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-dbpedia.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-dbtune.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-drugbank.ca_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ebi.ac.uk_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ebu.ch_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ebusiness-unibw.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-edamontology.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-europa.eu_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-fao.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-gbv.de_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-geonames.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-geospecies.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-geovocab.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-gesis.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-getty.edu_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-github.io_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-githubusercontent.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-glottolog.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-iconclass.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-idref.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-iflastandards.info_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ign.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-iptc.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-kanzaki.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-kasei.us_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-kit.edu_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-kjernsmo.net_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-korrekt.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-kulturarvsdata.se_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-kulturnav.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-l3s.de_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-lehigh.edu_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-lexvo.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-linkeddata.es_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-linkedopendata.gr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-linkedresearch.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-loc.gov_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-lu.se_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-mcu.es_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-medra.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-myexperiment.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ndl.go.jp_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-nih.gov_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-nobelprize.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-okfn.gr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ontobee.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ontologycentral.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-openei.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-openlibrary.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-orcid.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-ordnancesurvey.co.uk_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-oszk.hu_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-other_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-persee.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-pokepedia.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-princeton.edu_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-productontology.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-rdaregistry.info_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-rdvocab.info_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-reegle.info_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-rhiaro.co.uk_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-schema.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-sf.net_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-simia.net_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-sti2.at_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-stoa.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-sudoc.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-taxonconcept.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-theses.fr_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-timbl.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-uba.de_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-unesco.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-uni-mannheim.de_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-uniprot.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-unitn.it_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-verborgh.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-w3.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wals.info_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-walsh.name_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00002.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00003.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00004.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00005.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00006.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00007.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00008.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00009.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00010.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00011.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00012.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00013.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-wikidata.org_00014.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-worldcat.org_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-xmlns.com_00001.nq.gz wget https://zenodo.org/record/2634588/files/btc2019-zbw.eu_00001.nq.gz</code></pre> <p>To merge these files into one (again on Unix):</p> <pre><code>cat *.nq.gz > btc2019-quads.nq.gz_bak mv btc2019-quads.nq.gz_bak btc2019-quads.nq.gz</code></pre> <p> </p> <p><strong>Links to previous BTC datasets:</strong></p> <ul> <li><a href="http://km.aifb.kit.edu/projects/btc-2014/">BTC 2014 </a></li> <li><a href="http://km.aifb.kit.edu/projects/btc-2012/">BTC 2012</a></li> <li><a href="http://km.aifb.kit.edu/projects/btc-2011/">BTC 2011</a></li> <li><a href="http://km.aifb.kit.edu/projects/btc-2010/">BTC 2010</a></li> <li><a href="http://km.aifb.kit.edu/projects/btc-2009/">BTC 2009</a></li> <li>BTC 2008 (no link available)</li> </ul>
Supplementary material 1 from: Ramírez-Albores JE, Badano EI, Flores J, Flores-Flores JL, Yáñez-Espinosa L (2019) Scientific literature on invasive alien species in a megadiverse country: advances and challenges in Mexico. NeoBiota 48: 113-127. https://doi.org/10.3897/neobiota.48.36201
: Data type: species data
Exoplanet imaging data challenge
<p>Datasets for the Exoplanet imaging data challenge (<a href="https://exoplanet-imaging-challenge.github.io/">https://exoplanet-imaging-challenge.github.io</a>). </p>
Energy consumption and weather data collected continuously during a period of 29 months at Challenger building (France).
<p>The dataset consists of energy consumption and weather data collected continuously during a period of 29 months at Challenger building (France).</p> <p>Energy consumption data at 10 minutes intervals include:</p> <ul> <li>Heating and cooling electrical consumption (indoor and outdoor comfort units) for the 8 zones in the South Triangle (kWh)</li> <li>Lighting consumption for the 8 zones in the South Triangle (kWh)</li> <li>Plug load consumption for the 8 zones in the South Triangle (kWh)</li> <li>Sanitary consumption for the 8 zones in the South Triangle (kWh)</li> <li>Blinds consumption for the 8 zones in the South Triangle (kWh)</li> <li>Air handling unit consumption for the South Triangle (kWh)</li> <li>Total electrical consumption for the South Triangle (kWh)</li> <li>Thermal energy consumption for VRF (Variable refrigerant flow) units of the South Triangle (kWh)</li> </ul> <p>Weather data include:</p> <ul> <li>Daily degree days (°C)</li> <li>Hourly humidity (%)</li> <li>Daily rain precipitation (mm)</li> <li>Hourly direct and global radiation (J/cm2)</li> <li>Daily sunshine hours (hrs)</li> <li>Hourly temperature (°C)</li> </ul> <p>The data set contains<br> - Timeseries as CSV files<br> - Timeseries metadata (description, unit, type,...) as JSON file</p> <p>The data have been made available from the BMS database, thanks to the BEMServer open-source platform - <a href="http://www.bemserver.org">www.bemserver.org</a>, developed in the HIT2GAP project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement n. 680708 - <a href="http://www.hit2gap.eu">www.hit2gap.eu</a>.</p>
FIGURE 1. Monophyes princeps Haeckel, 1888b. Plate XXVIII, figs. 13 & 14 in A review of the siphonophore species mentioned in Haeckel's (1888 b) Challenger Monograph
FIGURE 1. Monophyes princeps Haeckel, 1888b. Plate XXVIII, figs. 13 & 14.
Figure 3 in Towards a global synthesis of Collembola knowledge - challenges and potential solutions
Figure 3. Local species richness depends on landscape age? Data from three forested regions in Russia with similar vegetation but different glaciation history: Primorsky Krai (no glaciation in the Pleistocene, solid lines), Caucasus (partial glaciation, dashed lines) and East European Plain (post-glacial landscape, dotted lines). Each line represents a distinct sampling locality with 81 cores of 8 cm2 collected from an area of 100 m2. Data from (Kuznetsova et al. 2019a, 2019b).
Figure 2 in Towards a global synthesis of Collembola knowledge - challenges and potential solutions
Figure 2. Communication of taxonomic knowledge on Collembola should include open online databases. Large image and genetic collections will allow semi-automated processes of species description and identification to be established. Green shaded boxes list components that need to be included in future common practices.
Fig. 2 in Detection and quantification of house mouse Eimeria at the species level - Challenges and solutions for the assessment of coccidia in wildlife
Fig. 2. Phylogenetic trees based on 18S rRNA and COI sequences. Sequences of 18S A) and COI B) were used to infer the molecular identification of wild-derived isolates of Eimeria. In both phylogenies, our isolates clustered in three groups one close to E. falciformis (red), other close to E. ferrisi (green) and finally one to E. vermiformis (yellow). Numbers in the branches represent the Bayesian posterior probability and the non-parametric bootstrap value. In bold are indicate the reference sequences for each species. CE and IL make reference to sequence derived from cecum or ileum tissue DNA, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Broad tapeworms (Diphyllobothriidae), parasites of wildlife and humans: Recent progress and future challenges
Fig. 3. Distribution of two genera of diphyllobothriid tapeworms from wildlife and man. A – Dibothriocephalus spp., B – Spirometra spp. Based on available literature data by countries except for some large countries where occurrence was estimated based on data available (Russia, China, etc.).
Fig. 1 in Broad tapeworms (Diphyllobothriidae), parasites of wildlife and humans: Recent progress and future challenges
Fig. 1. Microphotographs of diphyllobothriid tapeworms. A – Adenocephalus pacificus from Callorhinus ursinus, St. Paul Island, Alaska; fixed with hot water by T. Kuzmina. B – Dibothriocephalus latus spontaneously shed from experimentally infected man; fixed by R. Kuchta. C – Pyramicocephalus phocarum from Erignathus barbatus, Saint Lawrence Island, Alaska; fixed after relaxation by R. Rausch (MSBP 16648). D – Dibothriocephalus alasensis from Canis familiaris, Chevak, Alaska, 28 June 1958; fixed after relaxation by R. Rausch; type series (MSBP 17496). E – Dibothriocephalus dalliae from C. familiaris experimentally infected with plerocercoids from Dallia pectoralis, Gene Lake, Alaska, 12 March 1958; fixed after relaxation by R. Rausch; type series (MSBP 17092). F – Plicobothrium globicephalae from Orcinus orca, Newfoundland, Canada; inset: detail of the scolex; 'cold' (= in room temperature) fixation, museum sample (CMNPA 1999-0009). G – Diphyllobothrium cordatum (larger), Diphyllobothrium lanceolatum and Diphyllobothrium schistochilos (smaller) from E. barbatus; Greenland, 5 May 1916, "Crocker Land Expedition"; 'cold' fixation (SNM). H – Diphyllobothrium cordatum from E. barbatus, Greenland; 24 July 1890; decomposed material; museum sample (SNM). I – Diphyllobothrium scotium from Hydrurga leptonyx, Antarctica; type material (NMS Z.1921.1.43.1501). J – Diphyllobothrium hians from Monachus monachus; captured in Austria; collected by K.M. Diesing; type material (NMW 2684). K – Spirometra decipiens from Puma concolor, Brazil; collected by J. Natterer; type material (NMW 2682). Acronyms of museum collections: CMNPA – Canadian Museum of Nature, Parasitology Collection, Ottawa, Ontario, Canada; MSBP – Museum of Southwestern Biology, Division of Parasitology, University of New Mexico, Albuquerque, New Mexico, U.S.A.; NMS – National Museum of Scotland, Edinburgh, Scotland, U.K.; NMW – Das Naturhistorische Museum Wien, Vienna, Austria; SNM – Swedish Museum of Natural History, Stockholm, Sweden.
Datasets of "FraSSD: a framework to help teachers in the challenge of developing hard and soft skills in Software Engineering students"
<p>Hard and soft skills are essential for software professionals to perform their daily activities successfully, considering the specificities of the area, which requires a combination of different skills during the software development cycle. Thus, professionals must develop such skills from undergraduate onwards. In this context, although there are related works in the literature, no results were found that were aimed at supporting teachers in developing students' soft skills in the classroom through active education methodologies, focusing on student motivation. Therefore, to provide a model to help teachers in the challenge of contemplating hard and soft skills in a more meaningful teaching-learning process for students enrolled in Software Engineering subjects, this paper presents a framework based on the active methodologies PBL - Project Based Learning and role-play. Emphasis was placed on the six main soft skills required of software engineers: communication, teamwork, organization, leadership, learning, and creativity. To complement the motivational elements, the framework, called FraSSD – Framework for Soft Skills Development, uses some gamification elements, namely competition, scoring, and scoreboard. Finally, the activities established for students are based on Bloom's Taxonomy, which provides progressive knowledge development. As a proof of concept, FraSSD was applied in two Software Engineering classes, and a self-evaluation was conducted on the part of the students before and after the development of the project proposed by the framework, in which students evaluated their level of development in each of the six soft skills worked on during the course. The results were compared through statistical testing, showing an increase in the level of development of soft skills worked on, emphasizing organization, creativity, and teamwork in Class 1 and teamwork, creativity, and leadership in Class 2. Furthermore, a phenomenological analysis of an open question in the self-evaluation enabled FraSSD's positive points to be observed, as well as suggestions for improvements. From the teachers' point of view who applied the framework, although they suggested some modifications, they considered the FraSSD model easy to implement, which helped motivate students as opposed to traditional teaching methods.</p>
Fig. 1 in Taeniid cestodes in Tibetan foxes (Vulpes Ferrilata) detected by copro-PCR: Applications and challenges
Fig. 1. Phylogram of Taenia species, which were found in China, especially in Tibetan Plateau, using the maximum likelihood method generated from partial cox1 (a) and nad1 (b) gene haplotypes. Isolates from Shiqu County were marked with ▴. Sequences from the referential T. polyacantha larva sample collected in Xinyuan County, Xinjiang Autonomous Region, China, shared the same haplotypes with published sequences from Finland marked with ☆. To each sequence, its accession number and geographic region were presented following the taeniid species name and haplotype number. Scale bar was represented in substitutions per nucleotide, and bootstrap values (with 1000 replicates) were marked at the nodes of branches.
Fig. 4 in Intraspecific Variability of Melasis buprestoides (Linnaeus, 1761) Challenges the Validity of Melasis fermini Sánchez-Ruiz and Rosa, 2003 (Coleoptera: Eucnemidae)
Fig. 4. Length (a) and width (b) measurements of antennomere 9 of Melasis.
MASTERING THE ENGLISH LANGUAGE: OVERCOMING COMMON CHALLENGES
Open the record for dataset details and reuse information.
Challenges in analysis of code review comments. Various BERTopic parameters and impact on coherence.
Open the record for dataset details and reuse information.
Pesticide impacts on insect pollinators: current knowledge and future research challenges. ARIMA analysis
<p>FAOSTAT sourced Data on crop production, area and productivity</p>
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