Oles Honchar Dnipro National University (Ukrainian: Дніпровський національний університет імені Олеся Гончара) is an establishments of higher education in Ukraine. It was founded in 1918. The first four faculties were history and linguistics, law, medicine and physics and mathematics. Nowadays the university has level IV accreditation, with 20 faculties and 1,300 professors, 850 of them PhDs. The university has about 22,000 Ukrainian students and offers 87 majors. It has about 3,000 international students from 20 countries. It has strong ties with one of the largest world's rocket space centres, Yuzhnoye Design Bureau, and other industrial and scientific organizations in the Donetsk-Pridneprovsk area with population of more than 15 million people. Being a big educational and research center, DNU provides training at all qualifications levels: Master's degree, Specialist's degree, Bachelor's degree. It prepares researchers and university teachers at the post-graduate and doctor of science courses. Second higher education can be obtained. According to a decision of the Intersectorial Accreditation Collegiums and to the order of the Ministry of Sciences and Education of Ukraine Dnipropetrovsk National University has been accredited as a higher institution of the 4-th level accreditation. According to the UNESCO poll DNU takes the 6th place of all Ukrainian higher education institutes due to its academic and research indexes. DNU has 63 agreements with higher education institutes and research centers from many countries of Europe, Asia, the US, Canada. DNU has joined the work of the TEMPUS Program in Ukraine. The first project on reforming the economy was won in 1993. Since then DNU has won 14 projects (including three more Tempus projects in 2009) for terms of 1 to 3 years in sectors of science and education such as economics, management, university managements, social informatics and international economics. The library has 2,600,000 volumes and computer library rooms. Since 2007, DNU has been taking part in the Erasmus Mundus Project “External Cooperation Window”. In the plan there is a paragraph about development of close relations with EU universities, and strengthening of exchange programmes. Participation should raising the skills of DNU teachers and improving the style of teaching. The project can give the possibility of progress in implementation of Bologna standards, including ECTS and quality assurance.
The present study aimed to assess the early functional responses of plant communities to extreme anthropogenic disturbances caused by war. To this end, the case of the Kakhovka Dam destruction in June 2023 was examined. The functional structure of plant communities in the first year following the event on Khortytsia Island in the lower Dnipro floodplain (southern Ukraine) was analysed. The research identified 146 species of vascular plants and employed multivariate analysis, utilising functional diversity indices and principal component analysis. Hemeroby and naturalness indices were incorporated to distinguish between anthropogenic and natural influences. The study’s results revealed the presence of five distinct axes of variation in functional community structure. Disturbed areas exhibited increased functional redundancy and evenness, driven by ruderal species dominance and loss of ecological dominants. The phenomenon of functional richness and specialisation exhibited a response to variations in moisture levels, while alterations in functional identity reflected shifts in pollination strategies. The findings indicated a close association between hemeroby and functional redundancy and evenness alterations. The spatial patterns observed across the island reflect a complex interaction between human impacts and natural moisture gradients. This study is among the first to document rapid, trait-based vegetation responses to wartime ecosystem disruption. The study emphasises the efficacy of functional diversity and hemeroby as mechanisms for assessing ecological stability in conflict-affected regions.
Microreview describes recent (2013–2025) advances in the synthesis of imidazolidines using 1,3-dipolar (Huisgen) cycloaddition of N-benzyl-1-methoxy-N-[(trimethylsilyl)methyl]methanamine or its analogs to an imine double bond.
Catastrophic disturbances pose significant challenges to remote sensing because landscapes can change rapidly, while access for field validation is limited, making it difficult to consistently track the spatiotemporal dynamics of discrete land-surface types. Building on the metaphor of the “ecosystem as an organism” and the individualistic perspective on ecosystems, each surface type is treated as a spectrally coherent entity whose identity must remain comparable over time despite changing conditions. To achieve this comparability, a Procrustes-based framework is introduced to align multi-index feature spaces from different dates to a common archetype, enabling cross-date classification within a commensurable coordinate system. Since Procrustes alignment requires a stable reference, the concept of core pixels (centroid-typical samples in feature space) is extended to spatially grounded anchor pixels that are invariant in both spectral and geographic space, thereby representing the persistent “organismal” structure of the landscape. Regression-based evaluation indicates that the Procrustes–anchor workflow improves classification fidelity and produces a clearer, more interpretable transition matrix of type changes, facilitating the separation of systematic transient dynamics from noisy reassignments. The resulting discrete habitat maps are independently validated using field geobotanical vegetation types, providing an ecological basis for the classified surface-type dynamics under catastrophic conditions.
Remote sensing enables the analysis of landscape dynamics; however, catastrophic disturbances create new surface conditions that are not adequately captured by retrospectively defined land-cover classes. This study addresses the challenge of temporally matching unsupervised classifications to monitor post-catastrophic floodplain dynamics on Khortytsia Island following the destruction of the Kakhovka Reservoir. Multi-temporal Sentinel-2 Level-2A data from 2022 to 2025 were processed using spectral indices, standardised within a common predictor space, and classified through unsupervised clustering. Cluster solutions from individual dates were then matched based on spectral similarity and spatial continuity, with their temporal interpretation guided by concepts of landscape memory and landscape perception. Higher-order spatiotemporal units were subsequently derived through contextual superclustering. The analysis identified 16 clusters across the study period, with 4 to 12 clusters represented on individual dates. Their temporal coordination enabled the distinction of higher-order units exhibiting contrasting dynamics, including directional trend, seasonal, and mixed types. The proposed framework facilitates the identification of newly formed surface states, their temporal coordination, and their integration into a hierarchical spatiotemporal model of post-catastrophic landscape change.
