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July 2, 2026
Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.
July 2, 2026
HSE Develops App for Assessing Phonological Processing in Children
Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.
July 1, 2026
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.

 

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Soundness Correction of Data Petri Nets

IEEE Access. 2025. Vol. 13. P. 149142–149157.
Suvorov N. M., Lomazova I. A.

A process model is called sound if it always terminates properly and each model activity can occur in a process instance. Conducting soundness verification right after process design enables the detection and elimination of design errors in a process to be implemented. The process of eliminating such errors is called soundness repair. In many repair scenarios, the resulting model should retain only the correct behavior of the source model, especially if a model is created manually. In this paper, we consider this type of soundness repair applied to data-aware process models represented as data Petri nets (DPNs). We investigate the capabilities to repair soundness of DPNs by restricting the transition guards and disprove some earlier statements regarding it. We propose a new repair algorithm that follows this approach, with a key distinction that it does not require an input DPN to have a sound control flow. The algorithm is implemented, and the results of its preliminary evaluation justify its practical applicability in realistic application domains.

Research target: Computer Science
Language: English
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Keywords: бездефектностьИсправление моделей процессовData Petri netsData-aware soundnessdata-aware processessoundness repairсеть Петри с даннымимодели процессов с данными
Publication based on the results of:
New methods in the study of formal computation models, computer systems and related theoretical computer science problems (2025)
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