97,436 research outputs found
Joshua Davis: Author of Spare Parts
No full textCitation: K-State First (2016). Joshua Davis: Author of Spare Parts [Flier]. Manhattan, Kansas: K-State First.Flyer advertising Joshua Davis's author talk at Kansas State University
Steven Johnson Author Talk Poster
No full textK-State Book NetworkA poster advertising an author talk by Steven Johnson at Kansas State University on September 3, 2014. Steven Johnson's book "The Ghost Map" was the 2014-2015 common book
Sentiment analysis data and word embeddings for Erzya, Komi-Zyrian, Moksha and Udmurt
No full textThe aligned sentiment annotated data is in setiment_eval_data.json, vectors.zip has the word embeddings in a textual Gensim format, code.zip has the code and models.zip the sentiment analysis model.
Please cite the following paper:
Alnajjar, K., Hämäläinen, M., & Rueter, J, (2023) Sentiment Analysis Using Aligned Word Embeddings for Uralic Languages. In Proceedings of the Second Workshop on Resources and Representations for Under-resourced Languages and Domains (RESOURCEFUL-2023
Dialectal Finnish Generators
No full textHämäläinen, M., Partanen, N., Alnajjar, K., Rueter J. & Poibeau T. (2020). Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity. In Proceedings of the 11th International Conference on Computational Creativity
OpenNMT-tf models for generating dialectal Finnish from standard Finnish. The input should be a chunk of 3 words, split into characters and separated by an underscore (koira juoksee kovaa should be k o i r a _ j u o k s e e _ k o v a a). The flag model also expects a dialect name to be appended to the input (Kainuu k o i r a _ j u o k s e e _ k o v a a).
Take a look at the README.md for more information
Neural models for morphological generation, analysis and lemmatization in 22 languages
No full textMorphological models for generation, lemmatization and analysis in 22 languages. The models are trained in OpenNMT-py https://github.com/OpenNMT/OpenNMT-py. Feed one word at a time, split into characters (kissa -> k i s s a)
Supported languages: German (deu), Kven (fkv), Komi-Zyrian (kpv), Mokhsa (mdf), Mansi (mns), Erzya (myv), Norwegian Bokmål (nob), Russian (rus), South Sami (sma), Lule Sami (smj), Skolt Sami (sms), Võro (vro), Finnish (fin), Komi-Permyak (koi), Latvian (lav), Eastern Mari (mhr), Western Mari (mrj), Namonuito (nmt), Olonets-Karelian (olo), Pite Sami (sje), Northern Sami (sme), Inari Sami (smn) and Udmurt (udm)
Cite:
Hämäläinen, M., Partanen, N., Rueter, J., & Alnajjar, K. (2021). Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangered. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Enterotoxigenic Escherichia coli Flagellin Inhibits TNF-Induced NF-κB Activation in Intestinal Epithelial Cells
No full textCitation: Wang, G.; Geisbrecht, B.V.; Rueter, C.; Hardwidge, P.R. Enterotoxigenic Escherichia coli Flagellin Inhibits TNF-Induced NF-κB Activation in Intestinal Epithelial Cells. Pathogens 2017, 6, 18.Enterotoxigenic Escherichia coli (ETEC) causes childhood diarrhea in developing countries. ETEC strains produce the heat-labile enterotoxin (LT) and/or heat-stable enterotoxins (ST) and encode a diverse set of colonization factors used for adherence to intestinal epithelial cells. We previously found that ETEC secretes a heat-stable protein we designated as ETEC Secreted Factor (ESF) that inhibits the extent of NF-κB activation normally induced by tumor necrosis factor alpha (TNF). Here we fractionated ETEC supernatants using fast protein liquid chromatography (FPLC) and determined that ETEC flagellin was necessary and sufficient to protect IκBα from degradation in response to TNF stimulation. These data suggest a potentially novel mechanism by which ETEC may evade the host innate immune response by down-regulating NF-κB-dependent host responses
47 Serial NTproBNP measurements for the prediction of 30-day-mortality in patients with decompensated heart failure and cardiogenic shock
No full textAppropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Expanding “Communities and Collections” in the K-State Research Exchange (K-REx) to benefit the K-State Community and Beyond
No full textKansas State University has used its institutional repository, the K-State Research Exchange (K-REx), to store and share its first year experience program, K-State First, and notably its common reading program, K-State First Book. We have done so with the aim that the accessibility and preservation of these documents ensures program stability, promotes engagement with first year programming, and provides the ability to foster growth,educational opportunities, and community building outside of K-State. Moving away from research concentrated repositories and taking a more holistic approach to scholarship, especially when realizing the pedagogical significance of collaborative campus programming, institutions can showcase, discover, preserve, and grow programs that shape campus communities and engagement.
This session will provide an overview of K-REx and spotlight the digital archive of the university’s first year experience program and common reading program, K-State First Book. We will discuss the benefits and challenges to expanding the purview of your repositories. We talkthrough the types of materials we decide to host in our repository and why we share what we do. We will also provide recommendations on new ways to evaluate what belongs in institutional repositories and how this diversity can benefit your program, your institution, the community, and others
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