Explainable machine learning for predicting shellfish toxicity in the Adriatic Sea using long-term monitoring data of HABs

Autor: Marzidovšek, Martin, Francé, Janja, Podpečan, Vid, Vadnjal, Stanka, Dolenc, Jožica, Mozetič, Patricija

In this study, explainable machine learning techniques are applied to predict the toxicity of mussels in the Gulf of Trieste (Adriatic Sea) caused by harmful algal blooms. By analysing a newly created 28-year dataset containing records of toxic phyto

Externí odkaz: http://arxiv.org/abs/2405.04372

Author Correction: The interaction of β-arrestin1 with talin1 driven by endothelin A receptor as a feature of α5β1 integrin activation in high-grade serous ovarian cancer

Autor: Ilenia Masi, Flavia Ottavi, Danila Del Rio, Valentina Caprara, Cristina Vastarelli, Sara Maria Giannitelli, Giulia Fianco, Pamela Mozetic, Marianna Buttarelli, Gabriella Ferrandina, Giovanni Scambia, Daniela Gallo, Alberto Rainer, Anna Bagnato, Francesca Spadaro, Laura Rosanò

Publikováno v: Cell Death and Disease, Vol 15, Iss 10, Pp 1-2 (2024)

Externí odkaz: https://doaj.org/article/ba001aab394040888c1bd6841fb5cc6b

Retweet communities reveal the main sources of hate speech

Autor: Evkoski, Bojan, Pelicon, Andraz, Mozetic, Igor, Ljubesic, Nikola, Novak, Petra Kralj

Publikováno v: B. Evkoski, A. Pelicon, I. Mozeti\v{c}, N. Ljube\v{s}i\'c, P. Kralj Novak. Retweet communities reveal the main sources of hate speech, PLoS ONE 17(3): e0265602, 2022

We address a challenging problem of identifying main sources of hate speech on Twitter. On one hand, we carefully annotate a large set of tweets for hate speech, and deploy advanced deep learning to produce high quality hate speech classification mod

Externí odkaz: http://arxiv.org/abs/2105.14898

Community evolution in retweet networks

Autor: Evkoski, Bojan, Mozetic, Igor, Ljubesic, Nikola, Novak, Petra Kralj

Publikováno v: PLoS ONE 16(9): e0256175, 2021

Communities in social networks often reflect close social ties between their members and their evolution through time. We propose an approach that tracks two aspects of community evolution in retweet networks: flow of the members in, out and between

Externí odkaz: http://arxiv.org/abs/2105.06214

Cross-lingual Transfer of Sentiment Classifiers

Autor: Robnik-Sikonja, Marko, Reba, Kristjan, Mozetic, Igor

Word embeddings represent words in a numeric space so that semantic relations between words are represented as distances and directions in the vector space. Cross-lingual word embeddings transform vector spaces of different languages so that similar

Externí odkaz: http://arxiv.org/abs/2005.07456