Nouns in the Conceptual Framework "Node of Knowledge"

The "Node of Knowledge" method is one of the elements of the conceptual framework "Node of Knowledge (NOK)". It enables knowledge representation in graphical and formalized (textual) form and makes it possible to store formalized records of natural language sentences in a relational database. To enable correct transformation of all words from natural language sentences to formalized records, it is necessary to design a metamodel of a language, i.e. to analyse all word types of each particular natural language and define rules for transformation of sentences in natural language into formalized records. This paper analyses nouns in Croatian and English language. It presents rules for transformation of nouns and noun phrase structures into formalized records, with examples in both languages. The system is preliminary tested with a small set of sentences (used as input knowledge) and questions. Testing results are presented and discussed

mBLIP: Efficient Bootstrapping of Multilingual Vision-LLMs

Modular vision-language models (Vision-LLMs) align pretrained image encoders with (pretrained) large language models (LLMs), representing a computationally much more efficient alternative to end-to-end training of large vision-language models from scratch, which is prohibitively expensive for most. Vision-LLMs instead post-hoc condition LLMs to `understand' the output of an image encoder. With the abundance of readily available high-quality English image-text data as well as monolingual English LLMs, the research focus has been on English-only Vision-LLMs. Multilingual vision-language models are still predominantly obtained via expensive end-to-end pretraining, resulting in comparatively smaller models, trained on limited multilingual image data supplemented with text-only multilingual corpora. In this work, we present mBLIP, the first multilingual Vision-LLM, which we obtain in a computationally efficient manner -- on consumer hardware using only a few million training examples -- by leveraging a pretrained multilingual LLM. To this end, we \textit{re-align} an image encoder previously tuned to an English LLM to a new, multilingual LLM -- for this, we leverage multilingual data from a mix of vision-and-language tasks, which we obtain by machine-translating high-quality English data to 95 languages. On the IGLUE benchmark, mBLIP yields results competitive with state-of-the-art models. Moreover, in image captioning on XM3600, mBLIP (zero-shot) even outperforms PaLI-X (a model with 55B parameters). Compared to these very large multilingual vision-language models trained from scratch, we obtain mBLIP by training orders of magnitude fewer parameters on magnitudes less data. We release our model and code at \url{https://github.com/gregor-ge/mBLIP}

Cadmium exposure in adults across Europe: Results from the HBM4EU Aligned Studies survey 2014-2020

ReviewThe objectives of the study were to estimate the current exposure to cadmium (Cd) in Europe, potential differences between the countries and geographic regions, determinants of exposure and to derive European exposure levels. The basis for this work was provided by the European Human Biomonitoring Initiative (HBM4EU) which established a framework for alignment of national or regional HBM studies. For the purpose of Cd exposure assessment, studies from 9 European countries (Iceland, Denmark, Poland, Czech Republic, Croatia, Portugal, Germany, France, Luxembourg) were included and urine of 20–39 years old adults sampled in the years 2014–2021 (n = 2510). The measurements in urine were quality assured by the HBM4EU quality assurance/quality control scheme, study participants' questionnaire data were post-harmonized. Spatially resolved external data, namely Cd concentrations in soil, agricultural areas, phosphate fertilizer application, traffic density and point source Cd release were collected for the respective statistical territorial unit (NUTS). There were no distinct geographic patterns observed in Cd levels in urine, although the data revealed some differences between the specific study sites. The levels of exposure were otherwise similar between two time periods within the last decade (DEMOCOPHES - 2011–2012 vs. HBM4EU Aligned Studies, 2014–2020). The age-dependent alert values for Cd in urine were exceeded by 16% of the study participants. Exceedances in the different studies and locations ranged from 1.4% up to 42%. The studies with largest extent of exceedance were from France and Poland. Association analysis with individual food consumption data available from participants’ questionnaires showed an important contribution of vegetarian diet to the overall exposure, with 35% higher levels in vegetarians as opposed to non-vegetarians. For comparison, increase in Cd levels due to smoking was 25%. Using NUTS2-level external data, positive associations between HBM data and percentage of cropland and consumption of Cd-containing mineral phosphate fertilizer were revealed, which indicates a significant contribution of mineral phosphate fertilizers to human Cd exposure through diet. In addition to diet, traffic and point source release were identified as significant sources of exposure in the study population. The findings of the study support the recommendation by EFSA to reduce Cd exposure as also the estimated mean dietary exposure of adults in the EU is close or slightly exceeding the tolerable weekly intake. It also indicates that regulations are not protecting the population sufficiently.The HBM4EU project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 733032. Co-funding for the HBM4EU Aligned Studies has been provided by the national programs: Sant´e Publique France and the French ministries of Health and the Environment (ESTEBAN, France); MEYS (No. LM2018121), and Cetocoen Plus project (CZ.02.1.01/0.0/ 0.0/15_003/0000469) (CELSPAC:YA, Czech Republic); the Ministry of Science and Higher Education of Poland (contract no.3764/H2020/ 2017/2) (POALES, Poland); Public Health Fund (Diet_HBM, Iceland); Croatian Institute of Public Health (HBM survey in Croatia); National Institute of Health Dr Ricardo Jorge (INSEF_ExpoQuim, Portugal); German Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) (ESB, Germany); Luxembourg Institute of Health (LIH), the Laboratoire national de sant´e (human biomonitoring part), the Ministry of Higher Education and Research of Luxembourg and the Ministry of Health of Luxembourg (Oriscav-Lux2, Luxembourg); Candy Foundation (Nos. 2017–224 and 2020–344), Absalon Foundation (No. F-23653-01), The Danish Environmental Protection Agency (Miljøstyrelsen: MST-621-00012 Center on Endocrine Disrupters), The Research council of Capital Region of Denmark (No. E− 22717-11), Research council of Rigshospitalet (Nos. E− 22717-12, E− 22717-07, E− 22717-08), Aase og Ejnar Danielsens Fond (No. 10–001874), International Research and Research Training Centre for Male Reproduction and Child Health (EDMaRC, No. 1500321/1604357) (CPHMINIPUB (parents) and DYMS, Denmark). J.Kl. and L.A. thank the CETOCOEN EXCELLENCE project No. CZ.02.1.01/0.0/0.0/17_043/ 0009632 financed by MEYS for supportive background, and supported from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 857560.info:eu-repo/semantics/publishedVersio