Zbierka úloh z matematickej analýzy III.

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Adriana Zeleňáková - Jozef Bednarčík

Peer-reviewed Proceedings of the Scientific Conference NANOVIR

The main objective of the scientific conference NANOVIR was the presentation of scientific results obtained during the implementation of the NANOVIR project – Nanoparticles for solving diagnostic and therapeutic problems with COVID-19, co-financed by the European Regional Development Fund within the Operational Programme Integrated Infrastructure 2014 – 2020, ITMS: 313011AUW7.

The project was carried out from January 1, 2021, to June 30, 2023, and was supported with a sum of EUR 1,916,004.79. Three co-investigating organizations participated in the project: Pavol Jozef Šafárik University in Košice as the main investigator, the University of Veterinary Medicine and Pharmacy in Košice as partner no. 1, and the Institute of Experimental Physics of the Slovak Academy of Sciences as partner no. 2.

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Gabriela Andrejková - Ľubomír Antoni

Machine learning addresses the issues of how computer programs recognize complex patterns and make decisions based on data. In these university textbooks, we focus on theoretical knowledge in the field of machine learning in which we present the creation of concepts for objects, the preparation of concepts, hypotheses and the process of learning from examples. We describe Boolean formulas and their representations, probabilistic learning, linear and logistic regression, linear modeling and classification. Clustering and the Bayesian approach to machine learning conclude this publication.

University textbooks are intended for students of master's degree programs in computer science.

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Jana Shepa (ed.)

The book of abstracts from the second year of the international conference Spring electrochemical meeting is composed of contributions from the participants of this student conference.

The conference consisted of one invited lecture and ten competing student lectures. The message of this meeting is to create a dialogue between students of electrochemistry and the mutual exchange of knowledge. All contributions are professionally processed and inspiring.

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Vladislav Kolarčik

Flow cytometry is a diagnostic and research technique that enables rapid analysis of cells, nuclei and organelles of plants and other organisms. In plant biology, it is most often used for DNA content analysis in a wide range of applications. It is the method of first choice and its importance is even increasing compared to competing technologies. It is unrivaled in speed, accuracy, repeatability and low cost. Flow cytometry has become a standard tool in laboratories focused on biological-ecological plant research.

This textbook provides information on the historical development of flow cytometry and its establishment in the analysis of the plant genome. It describes the procedure of sample analysis to determine the nuclear DNA content and presents the basic applications, such as determination of genome size, ploidy level and reproduction modes of plants and determination of endopolyploidy level in plant tissues. These college textbooks are intended for students, teachers and anyone interested in the use of flow cytometry in scientific work with plant cells.

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