Integration of geographically distributed heterogeneous resources based on the DIRAC Interware Igor PelevanyukLaboratory of Information Technologies, JINR, Dubna, RussiaOnline seminar via WebexJuly 29 , 2020 The DIRAC Interware platform enables the integration of distributed heterogeneous computing resources and storage systems into a unified system. Since 2009, it has been developed as a versatile open-source tool. At present, the DIRAC-based unified environment, which includes both computing resources and data storage systems, is used to generate and reconstruct events of the MPD experiment, to study the SARS-CoV-2 virus within the Folding@Home project on available cloud resources and to integrate clouds of the JINR Member States’ organizations into a distributed platform. Development of a service for conducting radiobiological studies on the HybriLIT platform. Y.A.ButenkoLaboratory of Information Technologies, JINR, Dubna, RussiaJoint LIT-LRB workshopJune 18 , 2020 The report covers the development of the server part of an information system for analyzing behavioral and pathomorphological changes in the central nervous system in the study of the effects of ionizing radiation and other factors on biological objects. For data acquisition and storage, a client-server architecture of the application was elaborated and a database was designed. The given system provides a wide range of opportunities for users and takes into account the specifics of working with biological data. The system was built on the basis of the HybriLIT heterogeneous platform. Algorithms of computer vision for the analysis of behavioral responses of small laboratory animals. A.S. BulatovLaboratory of Information Technologies, JINR, Dubna, RussiaDubna State University, Dubna, RussiaJoint LIT-LRB workshopJune 18, 2020 The report considers the possibility of automating the evaluation of behavioral parameters of laboratory animals during the experiment using computer vision algorithms when analyzing the video recordings of the experiment. Specific algorithms that allow one to evaluate the track of a laboratory animal, as well as algorithms that automate the reading of the parameters of the experiment, such as the marking of the laboratory pool and the coordinates of the test site, are presented.