491. |
492. |
493. Poročilo o preskusu št.: LVG 2024-157 : vzorec št. 2024/00650Nikica Ogris, Patricija Podkrajšek, Zina Devetak, Špela Hočevar, Barbara Piškur, 2024, expertise, arbitration decision Keywords: varstvo gozdov, morfološke analize, Pseudocercospora pini-densiflorae, rdeči bor, bolezen iglic Published in DiRROS: 23.10.2024; Views: 135; Downloads: 0 This document has many files! More... |
494. Poročilo o preskusu št.: LVG 2024-156 : vzorec št. 2024/00627Barbara Piškur, Patricija Podkrajšek, Zina Devetak, Nikica Ogris, 2024, expertise, arbitration decision Keywords: varstvo gozdov, morfološke analize, Pseudocercospora pini-densiflorae, rdeči bor, bolezen iglic Published in DiRROS: 23.10.2024; Views: 125; Downloads: 0 This document has many files! More... |
495. |
496. Poročilo o preskusu št.: LVG 2024-153 : vzorec št. 2024/00608Barbara Piškur, Zina Devetak, Patricija Podkrajšek, Špela Hočevar, Nikica Ogris, 2024, expertise, arbitration decision Keywords: varstvo gozdov, morfološke analize, Pseudocercospora pini-densiflorae, rdeči bor, bolezen iglic Published in DiRROS: 23.10.2024; Views: 138; Downloads: 0 This document has many files! More... |
497. Knots and $\theta$-curves identification in polymeric chains and native proteins using neural networksFernando Bruno da Silva, Boštjan Gabrovšek, Marta Korpacz, Kamil Luczkiewicz, Szymon Niewieczerzal, Maciej Sikora, Joanna I. Sulkowska, 2024, original scientific article Abstract: Entanglement in proteins is a fascinating structural motif that is neither easy to detect via traditional methods nor fully understood. Recent advancements in AI-driven models have predicted that millions of proteins could potentially have a nontrivial topology. Herein, we have shown that long short-term memory (LSTM)-based neural networks (NN) architecture can be applied to detect, classify, and predict entanglement not only in closed polymeric chains but also in polymers and protein-like structures with open knots, actual protein configurations, and also $\theta$-curves motifs. The analysis revealed that the LSTM model can predict classes (up to the $6_1$ knot) accurately for closed knots and open polymeric chains, resembling real proteins. In the case of open knots formed by protein-like structures, the model displays robust prediction capabilities with an accuracy of 99%. Moreover, the LSTM model with proper features, tested on hundreds of thousands of knotted and unknotted protein structures with different architectures predicted by AlphaFold 2, can distinguish between the trivial and nontrivial topology of the native state of the protein with an accuracy of 93%. Keywords: machine learning, topology, protein databases, entanglements, open knots, closed knots Published in DiRROS: 23.10.2024; Views: 134; Downloads: 399 Full text (3,61 MB) This document has many files! More... |
498. Kakovost peletov na slovenskem trgu v letu 2024Darja Stare, Peter Prislan, Matjaž Dremelj, Amina Gačo Jež, 2023, treatise, preliminary study, study Keywords: gozdarstvo, lesna biomasa, trg lesnih goriv, peleti, kakovost Published in DiRROS: 23.10.2024; Views: 134; Downloads: 66 Full text (1,50 MB) This document has many files! More... |
499. Poročilo o preskusu št.: LVG 2024-152 : vzorec št. 2024/00809Nikica Ogris, Patricija Podkrajšek, Špela Hočevar, Barbara Piškur, 2024, expertise, arbitration decision Keywords: varstvo gozdov, morfološke analize, program preiskav, Fusarium circinatum, borov smolasti rak, PCR v realnem času Published in DiRROS: 23.10.2024; Views: 139; Downloads: 2 This document has many files! More... |
500. Discovery of novel and known viruses associated with toxigenic and non-toxigenic bloom forming diatoms from the Northern Adriatic SeaTimotej Turk Dermastia, Denis Kutnjak, Ion Gutiérrez-Aguirre, Corina P. D. Brussaard, Katarina Bačnik, 2024, original scientific article Abstract: Algal blooms impact trophic interactions, community structure and element fluxes. Despite playing an important role in the demise of phytoplankton blooms, only few viruses infecting diatoms have been cultured. Pseudo-nitzschia is a widespread diatom genus that commonly blooms in coastal waters and contains toxin-producing species. This study describes the characterization of a novel virus infecting the toxigenic species Pseudo-nitzschia galaxiae isolated from the northern Adriatic Sea. The ssRNA virus PnGalRNAV has 29.5 nm ± 1.2 nm icosahedral virions and a genome size of 8.8 kb. It belongs to the picorna-like Marnaviridae family and shows high specificity for P. galaxiae infecting two genetically and morphologically distinct strains. We found two genetically distinct types of this virus and screening of the global virome database revealed matching sequences from the Mediterranean region and China, suggesting its global distribution. Another virus of similar shape and size infecting Pseudo-nitzschia calliantha was found, but its genome could not be determined. In addition, we have obtained and characterized a new virus that infects Chaetoceros tenuissimus. The replicase protein of this virus is very similar to the previously described ChTenDNAV type-II virus, but it has a unique genome and infection pattern. Our study is an important contribution to the collective diatom virus culture collection and will allow further investigation into how these viruses control diatom bloom termination, carbon export and toxin release in the case of Pseudo-nitzschia. Keywords: algal blooms, diatoms, virus, PnGalRNAV, genome, Adriatic Sea, marine virology, phytoplankton ecology, marine biology Published in DiRROS: 23.10.2024; Views: 173; Downloads: 883 Full text (8,37 MB) This document has many files! More... |