European University at Saint Petersburg

Near repeat victimization (NRV) is a well-documented phenomenon, yet little is known about how it operates not across cities as a whole but within homogeneous urban morphologies. This study analyzes spatial and temporal patterns of property crime incidents from 2023 across urban morphology belts in Almaty, Kazakhstan. We use both the Knox test and interpretable machine learning (XGBoost with SHAP values) to predict victimization risk across three urban built environments (multi-level apartments, low-income detached houses, and high-income detached houses) based on prior incidents within spatio-temporal windows. The results show that although we observe partial evidence of the “Law of Crime Concentration”, overall NRV effects appear weak in Almaty. The machine learning approach further indicates that close-proximity crimes do not change recurrence risk, whereas more distant events in space and time are linked to higher odds of reoccurrence. Instead of a conventional “near repeat,” we observe a form of “distant repeat” victimization. This pattern suggests a specific type of crime displacement, where the most attractive target is not the site of a prior offence, but one that draws less attention from law enforcement. In addition, the morphology clusters do not differ substantially from one another — the key divide is not between grid-like and organic layouts per se, but between the high-class detached areas in the foothills and the rest of the city. These findings underscore the need to evaluate NRV in non-Western contexts using diverse methodological approaches, with explicit consideration of the urban morphology in which crimes occur. • Near repeat victimization (NRV) is not observed in the non-Western context of Almaty, Kazakhstan. • A distant repeat pattern emerges, driven by effects from outer time-space belts. • The main NRV divide lies between high-class foothill areas and the rest of the city, not grid vs. organic layouts. • Interpretable machine learning (XGBoost + SHAP) yields more nuanced results than the Knox test. • The Law of Crime Concentration holds: 50% of crimes occur within 5% of urban space.

Coronary artery bypass grafting (CABG) is a vital intervention for severe coronary artery disease, yet it induces significant oxidative stress, contributing to postoperative complications and long-term cardiovascular risks. Aminothiols, including glutathione, homocysteine, cysteine, and cysteinylglycine, are key regulators of redox homeostasis, making them promising biomarkers for assessing oxidative stress in CABG patients. This narrative review explores their biochemical roles, measurement techniques, and associations with clinical outcomes. Glutathione mitigates reactive oxygen species (ROS) through the glutathione redox cycle, while elevated homocysteine promotes oxidative damage and inflammation, linked to complications like atrial fibrillation and acute kidney injury. Cysteine and cysteinylglycine further support redox balance, with their dysregulation reflecting perioperative stress. Studies demonstrate that altered aminothiol levels pre- and post-CABG correlate with adverse outcomes, including myocardial injury, graft restenosis, and major adverse cardiovascular events. Advanced analytical methods like high-performance liquid chromatography and liquid chromatography-mass spectrometry enable precise aminothiol quantification, although variability and lack of standardization pose challenges. Therapeutic interventions, such as N-acetylcysteine and folate supplementation, show potential to modulate aminothiol levels and reduce oxidative stress. Despite these insights, gaps in longitudinal data and assay standardization limit clinical adoption. Future research should focus on standardized protocols, large-scale studies, and metabolomics to integrate aminothiols into personalized medicine, enhancing risk stratification and therapeutic strategies for improved CABG outcomes. Overall, this narrative review synthesizes available data on aminothiols and oxidative stress in CABG, with the objective of identifying knowledge gaps and potential pathways for translational and clinical application.

This paper provides a scoping review of the literature published between 2023 and 2025 concerning the use of artificial intelligence (AI) to provide scaffolding in higher education. Adopting a Human-Computer Interaction perspective, this review treats AI as an active participant in educational interactions. The analysis identifies five distinct types of AI-driven support: analytically managed cues and prompts; cognitive assistants; didactically designed chatbots; AI-assisted educational assignment design; and algorithmically generated recommendations. The review concludes that the efficacy of such AI tools depends on their deep integration into the learning process and their ability to augment the cognitive engagement of students.

Abstract This article develops a set of quantitative indicators that allow for tracing the dynamics of Russia’s political regime along two dimensions: electoral evaporation, understood as a gradual diminishing in the level of competitiveness; and autocratic personalization, understood as the rise of the personalist traits of the regime. The values of the indicators offered in this article are derivable from the objective data, not from expert coding, which increases data reliability. The indicators are country-specific. This reduces the loss of information that is unavoidable in cross-national research. Electoral evaporation is measured on the basis of election results, while for measuring autocratic personalization, the article builds a composite index involving several indicators of personalist rule. The parallel tracing of these indicators’ values throughout the period under observation, 2004–2022, shows that the evaporation of the electoral component of the regime has occurred largely in parallel with the rise of its personalist component. At the same time, slow-downs in one of the components could be compensated by the accelerated increase of the other, to the effect that the authoritarian transformation of the regime continued to progress. There were also instances when the indicators’ values concurrently increased after periods of decline on both parameters.

The paper deals with one of the most debatable historiographical issues, that of comparability of the Russian Zemsky Sobors with their counterparts in the West. A review of a wide range of the current scholarly literature reveals some stereotypes in the perception of this problem. It is shown that Zemsky Sobors, in spite of some skeptical voices, do share some key common features with the representative institutions elsewhere in Europe and that they can be regarded as a variant of the monarchical model of the medieval representation. The undertaken comparative typological analysis casts some light on the origins of Zemsky Sobors in Russia as well as on the possible causes of their decline in the second half of the 17th century.

Recent advancements in artificial intelligence (AI) applications in medicine have been significant over the past 30 years. To monitor current research developments, it is crucial to examine the latest trends in AI adoption across various medical fields. This bibliometric analysis focuses on AI applications in cardiology. Unlike existing literature reviews, this study specifically examines journal articles published in the last decade, sourced from both Scopus and Web of Science databases, to illustrate the recent trends in AI within cardiology. The bibliometric analysis involves a statistical and quantitative evaluation of the literature on AI application in cardiovascular medicine over a defined period. A comprehensive global literature review is conducted to identify key research areas, authors, and their interrelationships through published works. The leading institutions and most influential authors in research on the role of AI in cardiology were located in the United States, the United Kingdom, and China. This study also provides researchers with an overview of the evolution of research in AI and cardiology. The main contribution of this study is to highlight the prominent authors, countries, journals, institutions, keywords, and trends in the development of AI in cardiology.

Abstract Background The Dokdo sea lion (Zalophus japonicus), commonly referred to as Gangchi in Korea also known as the Japanese sea lion, was endemic to the Northwest Pacific coast before becoming extinct in the 1950s. Little is known about its origins and speciation compared to other Otariidae species or how the rapid decline affected the species’ genetic diversity. Results To raise the Dokdo sea lion from this relative obscurity, we sequenced DNA from 16 Z. japonicus’ bone fragments, obtained from Dokdo and Ulleungdo islands in Korea. Our genome-wide SNP-based analyses establish Z. japonicus as the earliest diverged species within its genus, significantly redefining its evolutionary relationship with the California (Z. californianus) and Galapagos (Z. wollebaeki) sea lions. Our research further elucidates the phylogeny of Z. japonicus, shedding light on the complexity of the genetic isolation process within its genus that was prompted by the geographic isolation of the three populations of Zalophus ancestral stock. Conversely, the genetic signature of Dokdo sea lion genome can be modeled as an evolutionary pathway involving gene flow from Otariidae species with shared range. In addition, we discovered, population decline of the Z. japonicus started already over 1,000 years ago, however, Z. japonicus genome maintained a relatively high heterozygosity despite nearing extinction. Conclusions Our genome-scale analysis has eliminated ambiguity in the phylogeny of Z. japonicus and shed light on the evolutionary pathways underlying its speciation and the genetic diversity before its extinction. Broadly, this study highlights the importance of genome-scale analysis for the extinct marine megafauna to elucidate the complexity of their gene flow and subsequent genetic diversities among extant species. Furthermore, this study offers retrospective genomic insights into the extinction process of a carnivorous marine mammal, information that could aid conservation efforts towards extant Otariidae species.