Man vs. Machine:Extracting Character Networks from Human and Machine Translations

Most of the work on Character Networks to date is limited to monolingual texts. Conversely, in this paper we apply and analyze Character Networks on both source texts (English novels) and their Finnish translations (both human- and machine-translated). We assume that this analysis could provide some insights on changes in translations that could modify the character networks, as well as the narrative. The results show that the character networks of translations differ from originals in case of long novels, and the differences may also vary depending on the novel and translator's strategy

Dr. Livingstone, I presume? Polishing of foreign character identification in literary texts

Character identification is a key element for many narrative-related tasks. To implement it, the baseform of the name of the character (or lemma) needs to be identified, so different appearances of the same character in the narrative could be aligned. In this paper we tackle this problem in translated texts (English–Finnish translation direction), where the challenge regarding lemmatizing foreign names in an agglutinative language appears. To solve this problem, we present and compare several methods. The results show that the method based on a search for the shortest version of the name proves to be the easiest, best performing (83.4% F1), and most resource-independent.</p

New optical tools for non-invasive imaging and quantification of glucose and nicotinamide riboside in living cells and animals

Glucose is one of the most important metabolites that plays a key role in living organisms, as it is the primary energy source. Glucose metabolism is also an integral part in the pathogenesis of diabetes and cancer. Despite this tremendous impact of glucose, there are no tools for imaging of glucose uptake non-invasively and in a real-time manner working in both living cells and animals without utilization of hazardous radiation and suitable for convenient preclinical use. The first part of this thesis is describing the development of a probe for imaging glucose uptake based on a highly sensitive and versatile bioluminescence technique. We set a goal to design a probe, which should be reliable, robust, easy to use and simply represent the glucose uptake in both living cells and animals. In addition the synthesis of the probe should be straightforward and high-yielding. This part of the thesis is composed of two projects utilizing different approaches to the probe design and probeâs mechanism of action. The first project was based on the Staudinger Ligation for imaging of glucose uptake by modifying the glucose molecule with an azide moiety and using luciferin caged with a reactive phosphine as a counter-partner for the assay. The second project describes the development of a cleavable disulfide glucose-conjugate probe. For the first project we aimed to synthesize a library of glucose pro bioluminescent probes, validate them in a cell-free and cell-based assay and identify the hit compound. Then we proved the GLUT-specificity of the uptake of our hit compound in living cells and animals. The robust and reproducible assay method for measurement of glucose uptake was established. The probe was applied for imaging of antidiabetic drugsâ influence on glucose uptake. We have also demonstrated its superior properties over 2-NBDG that is currently the most used probe in preclinical research. However, the probe utilized in the second project namely cleavable disulfide glucose conjugate probe was not so sensitive as glucose-azide. Nevertheless, we showed a successful application of this probe for imaging of glucose uptake in living cells and animals. The second part of this thesis describes the design and evaluation of the bioluminescent probe for imaging of nicotinamide riboside (NR) uptake. NR is a recently discovered NAD+ precursor that is naturally present in cow's milk. Despite its importance in modern research and a high potential as a new medicine for treatment of various types of diseases, including diabetes, there are no tools to visualize NR uptake in preclinical research. Also, there is a lack of knowledge on where and how NR can be absorbed in mammals. Here we established the Staudinger Ligation-based approach to develop an imaging tool for NR uptake. After the successful synthesis of azido-nicotinamide riboside molecule, we demonstrated its specificity and utility for imaging in living cells and animals. Findings described in this part cover not only the imaging of NR uptake, but also the possibility of existence of specific NR transporter in mammalian cells, which has not been discovered and described yet

Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

Most of the work on Character Networks to date is limited to monolingual texts. Conversely, in this paper we apply and analyze Character Networks on both source texts (English novels) and their Finnish translations (both human- and machine-translated). We assume that this analysis could provide some insights on changes in translations that could modify the character networks, as well as the narrative. The results show that the character networks of translations differ from originals in case of long novels, and the differences may also vary depending on the novel and translator’s strategy.</p

Creating a parallel Finnish—Easy Finnish dataset from news articles

Modern natural language processing tasks such as text simplification or summarization are typically formulated as monolingual machine translation tasks. This requires appropriate datasets to train, tune, and evaluate the models. This paper describes the creation of a parallel Finnish–Easy Finnish dataset from the Yle News archives. The dataset contains 1919 manually verified pairs of articles, each containing an article in Easy Finnish (selkosuomi) and a corresponding article from Standard Finnish news. Standard Finnish texts total 687555 words, and Easy Finnish texts have 106733 words. This new aligned resource was created automatically based on the Yle News archives from the Language Bank of Finland (Kielipankki) and manually checked by a human expert. The dataset is available for download from Kielipankki. This resource will allow for more effective Easy Language research and for creating applications for automatic simplification and/or summarization of Finnish texts.Peer reviewe

Man vs. Machine: Extracting Character Networks from Human and Machine Translations

Most of the work on Character Networks to date is limited to monolingual texts. Conversely, in this paper we apply and analyze Character Networks on both source texts (English novels) and their Finnish translations (both human- and machine-translated). We assume that this analysis could provide some insights on changes in translations that could modify the character networks, as well as the narrative. The results show that the character networks of translations differ from originals in case of long novels, and the differences may also vary depending on the novel and translator's strategy