Modeling cross-language structural priming in sentence production

A central question in the psycholinguistic study of multilingualism is how syntax is shared across languages. We implement a model to investigate whether error-based implicit learning can provide an account of cross-language structural priming. The model is based on the Dual-path model of sentence-production (Chang, 2002). We implement our model using the Bilingual version of Dual-path (Tsoukala, Frank, & Broersma, 2017). We answer two main questions: (1) Can structural priming of active and passive constructions occur between English and Spanish in a bilingual version of the Dual- path model? (2) Does cross-language priming differ quantitatively from within-language priming in this model? Our results show that cross-language priming does occur in the model. This finding adds to the viability of implicit learning as an account of structural priming in general and cross-language structural priming specifically. Furthermore, we find that the within-language priming effect is somewhat stronger than the cross-language effect. In the context of mixed results from behavioral studies, we interpret the latter finding as an indication that the difference between cross-language and within- language priming is small and difficult to detect statistically

Simulating code-switching using a neural network model of bilingual sentence production

Code-switching is the alternation from one language to the other during bilingual speech. We present a novel method of researching this phenomenon using computational cognitive modeling. We trained a neural network of bilingual sentence production to simulate early balanced Spanish–English bilinguals, late speakers of English who have Spanish as a dominant native language, and late speakers of Spanish who have English as a dominant native language. The model produced code-switches even though it was not exposed to code-switched input. The simulations predicted how code-switching patterns differ between early balanced and late non-balanced bilinguals; the balanced bilingual simulation code-switches considerably more frequently, which is in line with what has been observed in human speech production. Additionally, we compared the patterns produced by the simulations with two corpora of spontaneous bilingual speech and identified noticeable commonalities and differences. To our knowledge, this is the first computational cognitive model simulating the code-switched production of non-balanced bilinguals and comparing the simulated production of balanced and non-balanced bilinguals with that of human bilinguals

Simulating Spanish-English code-switching: El modelo está generating code-switches

Multilingual speakers are able to switch from one language to the other (“code-switch”) be- tween or within sentences. Because the under- lying cognitive mechanisms are not well un- derstood, in this study we use computational cognitive modeling to shed light on the pro- cess of code-switching. We employed the Bilingual Dual-path model, a Recurrent Neu- ral Network of bilingual sentence production (Tsoukala et al., 2017) and simulated sentence production in simultaneous Spanish-English bilinguals. Our first goal was to investigate whether the model would code-switch with- out being exposed to code-switched training input. The model indeed produced code- switches even without any exposure to such input and the patterns of code-switches are in line with earlier linguistic work (Poplack, 1980). The second goal of this study was to investigate an auxiliary phrase asymmetry that exists in Spanish-English code-switched pro- duction. Using this cognitive model, we ex- amined a possible cause for this asymmetry. To our knowledge, this is the first computa- tional cognitive model that aims to simulate code-switched sentence production

SHORELINE EFFECTS OF 10-28 RUNWAY OF “MACEDONIA" AIRPORT EXTENSION INTO THE SEA LABORATORY STUDY

Προκειμένου να διερευνηθούν οι επιπτώσεις στις παρακείμενες ακτές από την επέκταση στη θάλασσα του διαδρόμου προσαπογειώσεων "10-28", του κρατικού διεθνή αερολιμένα Θεσσαλονίκης "Μακεδονία", ανατέθηκε από το Υ.ΠΕ.ΧΩ.Δ.Ε./Ε.Υ.Δ.Ε. Αεροδρομίων Βόρειας Ελλάδας, στο Εργαστήριο Λιμενικών Έργων του Εθνικού Μετσόβιου Πολυτεχνείου η έρευνα σε φυσικό προσομοίωμα. Κατά την πειραματική μελέτη της κυματικής διαταραχής στην περιοχή του αερολιμένα, παρατηρήθηκε μικρή αύξηση της κυματικής διαταραχής λόγω ανάκλασης των προσπιπτόντων κυματισμών στο μέτωπο του προβλεπόμενου έργου και προσωρινές ζώνες στασιμότητας ροής στις γωνίες του, ενώ δεν παρατηρήθηκε συστηματική και αξιοσημείωτη αλλοίωση της ακτογραμμής από την παρουσία του έργου. Οι κατασκευαστικές εργασίες (λιμενικά έργα) έχουν ξεκινήσει από το τέλος του 2006. Τα αποτελέσματα των πειραματικών μετρήσεων στο φυσικό προσομοίωμα επιβεβαιώνονται με την απόκριση του έργου στη φύση δεδομένου ότι δεν έχουν σημειωθεί μέχρι σήμερα αλλοιώσεις και διάβρωση της ακτογραμμής.Thessaloniki International Airport “Macedonia” had decided the extension of the existing Runway “10-28” by about 1 km west into the sea. In order to assure that no catastrophic erosion of the adjacent beaches will occur due to such a big construction into the sea, the Ministry of Environment, Physical Planning and Public Works assigned Laboratory of Harbour Works of National Technical University of Athens the experimental investigation of its coastal impacts. Wave perturbation, wave overtopping and beach response to the construction of the Runway were tested. The construction of the Runway in the sea has already started. The experimental results were confirmed by field observation

Detection of Fake Generated Scientific Abstracts

The widespread adoption of Large Language Models and publicly available ChatGPT has marked a significant turning point in the integration of Artificial Intelligence into people's everyday lives. The academic community has taken notice of these technological advancements and has expressed concerns regarding the difficulty of discriminating between what is real and what is artificially generated. Thus, researchers have been working on developing effective systems to identify machine-generated text. In this study, we utilize the GPT-3 model to generate scientific paper abstracts through Artificial Intelligence and explore various text representation methods when combined with Machine Learning models with the aim of identifying machine-written text. We analyze the models' performance and address several research questions that rise during the analysis of the results. By conducting this research, we shed light on the capabilities and limitations of Artificial Intelligence generated text

Green Production of Anionic Surfactant Obtained from Pea Protein

A pea protein isolate was hydrolyzed by a double enzyme treatment method in order to obtain short peptide sequences used as raw materials to produce lipopeptides-based surfactants. Pea protein hydrolysates were prepared using the combination of Alcalase and Flavourzyme. The influence of the process variables was studied to optimize the proteolytic degradation to high degrees of hydrolysis. The average peptide chain lengths were obtained at 3–5 amino acid units after a hydrolysis of 30 min with the mixture of enzymes. Then, N-acylation in water, in presence of acid chloride (C12 and C16), carried out with a conversion rate of amine functions of 90%, allowed to obtain anionic surfactant mixtures (lipopeptides and sodium fatty acids). These two steps were performed in water, in continuous and did not generate any waste. This process was therefore in line with green chemistry principles. The surface activities (CMC, foaming and emulsifying properties) of these mixtures were also studied. These formulations obtained from natural renewable resources and the reactions done under environmental respect, could replace petrochemical based surfactants for some applications

Frontal sinuses and human evolution

The frontal sinuses are cavities inside the frontal bone located at the junction between the face and the cranial vault and close to the brain. Despite a long history of study, understanding of their origin and variation through evolution is limited. This work compares most hominin species? holotypes and other key individuals with extant hominids. It provides a unique and valuable perspective of the variation in sinuses position, shape, and dimensions based on a simple and reproducible methodology. We also observed a covariation between the size and shape of the sinuses and the underlying frontal lobes in hominin species from at least the appearance of Homo erectus. Our results additionally undermine hypotheses stating that hominin frontal sinuses were directly affected by biomechanical constraints resulting from either chewing or adaptation to climate. Last, we demonstrate their substantial potential for discussions of the evolutionary relationships between hominin species. Variation in frontal sinus shape and dimensions has high potential for phylogenetic discussion when studying human evolution