A Mediterranean element of the vegetation: Junco maritimi-Cladietum marisci – a new association for Ukraine

Cladium mariscus (L.) Pohl (Cyperaceae) is a rare species in Europe considered by several authors to be a relict of the early Holocene period. It is listed in the Red Data Book of Ukraine, Annexes of the Habitat Directive and the Bern Convention. Communities with domination of this species are included in the Green Data Book of Ukraine. Substantial differences in major ecological factors for Cladium mariscus communities in the western (carbonate bogs) and the southern (marshes and floating swamps of the northern Black Sea) regions of Ukraine were shown. The author carried out comparisons of relevés characterizing different communities with Cladium mariscus within Europe. Based on the results of TWINSPAN analysis, four associations were identified, confirmed by floristic indices and ecological data: Cladietum marisci Allorge 1921, Soncho maritimi-Cladietum marisci (Br.-Bl. & O. de Bolòs 1957) Cirujano 1980, Dorycnio recti-Cladietum marisci Gradstein & Smittenberg 1977 and Junco maritimi-Cladietum marisci (Br.-Bl. & O. de Bolòs 1957) Géhu & Biondi 1988. Thus, in addition to the association Cladietum marisci, a new one was indicated for Ukraine, Junco maritimi-Cladietum marisci

Vegetation mapping of the Dzharylhach Island (Ukraine)

Dzharylhach Island – the largest one in the Black Sea and it is part of the “Dzharylhatskyi” National Nature Park, which located in the southern part of Ukraine. A 1:10000 scale vegetation map of Dzharylhach Island has been developed. The main unit for mapping is a complex of associations. In total 28 of such complexes were identified. The map shows the territorial differentiation of vegetation. It has also been used to reconstruct the island vegetation changes over the past 80 and 20 years. A comparison of cartographic materials revealed that the predominant processes in vegetation cover are halophytization and xerophytization of communities. The most distributed types of communities on the island are aquatic – Zosteretea), halophytic – Festuco-Puccinellietea and psammophytic – Festucetea vaginatae. Due to specific hydrological and soil conditions, the northern spit and shores of the island represent natural vegetation types only

Broken bar fault diagnosis for induction machines under load variation condition using discrete Wavelet transform

The paper presents a new approach for detection of broken rotor bar fault in squirrel cage induction motors operating under varying load conditions. A mathematical model used in the presented method was developed using winding function approach to provide indication references for induction motor parameters under load variation. The model shows a strong relationship between broken rotor bar fault and stator current. The method is based on analysis of stator current using discrete wavelet transform. To verify the proposed method a squirrel cage induction motor with 1, 2 and 3 broken bars at no-load, half- and full-load conditions was investigated. Obtained experimental results confirmed the validity of the proposed approach

Ukrainian Plant Trait Database: UkrTrait v. 1.0

Background Considering the growing demand for plant trait data and taking into account the lack of trait data from Eastern Europe, especially from its steppic region, we launched a new Ukrainian Plant Trait Database (UkrTrait v. 1.0) aiming at collecting all the available plant trait data from Ukraine. To facilitate further use of this database, we linked the trait terminology to the TRY Plant Trait Database, Thesaurus of Plant Characteristics (TOP) and Plant Trait Ontology (TO). For taxa names, we provide the crosswalks between the Ukrainian checklist and international sources, i.e. GBIF Backbone Taxonomy, World Checklist of Vascular Plants (World Checklist of Vascular Plants (World Checklist of Vascular Plants (WCVP), World Flora Online (WFO) and Euro+Med PlantBase. We aim to integrate our data into the relevant global (TRY Plant Trait Database) and pan-European (FloraVeg.EU) databases. The current version of the database is freely available at the Zenodo repository and will be updated in the future. New information Until now, plant traits for the Ukrainian flora were scattered across literature, often focusing on single species and written mainly in Ukrainian. Additionally, many traits were in grey literature or remained non-digitised, which rendered them inaccessible to the global scientific community. Addressing this gap, our Ukrainian Plant Trait Database (UkrTrait v. 1.0) represents a significant step forward. We compiled and digitised plant traits from local Ukrainian literature sources. Furthermore, we performed our own field and laboratory measurements of various plant traits that were not previously available in literature. In the current version of the UkrTrait, we focus on vascular plant species that are absent from the other European trait databases, with emphasis on species that are representative for the steppe vegetation. Traits assembled from literature include life span (annuals, biennials, perennials), plant height, flowering period (flowering months), life form (by Raunkiaer), plant growth form and others. Our own measured traits include seed mass, seed shape, leaf area, leaf nitrogen concentration and leaf phosphorus concentration. The current version, i.e. UkrTrait v. 1.0, comprises digitised literature data of 287,948 records of 75 traits for 6,198 taxa and our own trait measurements of 2,390 records of 12 traits for 388 taxa

Rapid functional but slow species diversity recovery of steppe vegetation on former arable fields in southern Ukraine

Questions: European steppes are among the most threatened ecosystems in the Palaearctic region, mainly because of conversion to arable land. Abandonment may allow for the passive recovery of steppes. We made use of an exceptional old-field succession chronosequence of nearly 100 years to answer the following questions: (a) Are the plant species composition, species richness and functional characteristics typical of virgin grass steppes able to self-restore during ca. 100 years after abandonment? (b) Do the rates of recovery of the above vegetation characteristics differ over the studied chronosequence? (c) Do topsoil carbon and nitrogen content change over the succession chronosequence, leading to concentrations similar to that of virgin steppes? Location: Southern Ukraine. Methods: We sampled vegetation and soil in a virgin grass steppe and in old fields abandoned for 6, 15, 31, 50 and ca. 97 years. We subjected the composition data to multivariate analysis. To test whether species richness, functional and soil characteristics of the old fields diverge from those of the virgin steppe, we used one-way analysis of variance with Tukey's honestly significant difference (HSD) statistic to create 90% confidence intervals. Results: The vegetation composition of the three most recently abandoned old fields differed significantly from that of the virgin steppe. The species richness of vascular plants was lower in old fields than in the virgin steppe. The share of steppe habitat specialists was similar to the virgin steppe only in the field abandoned for ca. 97 years. Functional characteristics were significantly different from the virgin steppe only in the most recently abandoned old field. Contents of Corg and Ntot in fields abandoned for ≤50 years were lower compared with the virgin steppe. Conclusions: The functional characteristics of steppe vegetation seem to recover much faster than its biodiversity. However, based on our results, 100 years can be enough time for the spontaneous re-establishment of typical steppe vegetation

Evaluating the effectiveness of hierarchical management systems

This paper demonstrates a possibilities of using brute force methods for evaluating the effectiveness of hierarchical management systems. Proposed model of hierarchy provides finding the optimal distribution of load between the executive elements at a predetermined structure. A simple hierarchical structure has been used as an example to investigate the functionality of the model and its software implementation

Молодые люди и Интернет: субъективные факторы выбора стратегий онлайн-поведения

Introduction. Technologies and digital communication play a crucial role in everyday life. With the increasing number of people spending a significant amount of time online, the study of subjective factors influencing online behavior strategies becomes highly relevant. The novelty of this research lies in identifying online behavior strategies among young individuals and examining the factor structures of young people with different online behavior strategies. This article presents the results of studying the personality traits of students with various online behavior strategies. Methods. Various methods were employed, including theoretical analysis and summarization of research findings on this issue; psychodiagnostic research methods; mathematical and statistical analysis (descriptive statistics, Mann-Whitney U-test, cluster analysis, factor analysis). In the study, 177 students aged 17 to 21 participated. Two groups were distinguished in order to differentiate students based on their online behavior strategies: students with an entertainment-oriented Internet behavior (n = 124) and students with a productive-oriented Internet behavior (n = 53). Results. The following results were obtained: among contemporary youth who are active in the online environment, two strategies of online behavior are identified - entertainment-oriented online behavior strategy and productive-oriented strategy. The choice of behavior strategy is related to the respondents\u27 personality traits. Significant differences were found between the groups of students with different online behavior strategies in terms of adaptability, self-acceptance, and autonomy. Discussion. The authors examine the personality traits of youth with different online behavior strategies. In conclusion, it is concluded that the factor structures of students with different online behavior strategies differ.Введение. Технологии и цифровая коммуникация играют важнейшую роль в повседневной жизни. В связи с растущим числом людей, проводящих значительное количество времени в сети Интернет, набирает актуальность изучение субъективных факторов выбора стратегий онлайн-поведения. Новизна исследования заключается в выделении стратегий онлайн-поведения молодежи и изучении факторных структур молодых людей с разными стратегиями поведения в Интернет-среде. В статье представлены результаты исследования личностных особенностей студентов с разными стратегиями поведения в Интернет-среде. Методы. Использованы такие методы, как теоретический анализ и обобщение результатов исследования по данной проблеме; психодиагностические методы исследования; математико-статистический анализ (описательная статистика, U-критерий Манна-Уитни, кластерный анализ, факторный анализ).  В исследовании принимали участие 177 студентов в возрасте от 17 до 21 года. С целью дифференциации студентов по стратегиям поведения были выделены две группы: студенты с развлекательной направленностью поведения в Интернете (n = 124) и студенты с продуктивной направленностью поведения в Интернете (n = 53). Результаты. Были получены следующие результаты: у современной молодежи, проявляющих активность в Интернет-среде, выделяется две стратегии онлайн-поведения: стратегия с развлекательной направленностью онлайн-поведения и стратегия с продуктивной направленностью; причем выбор стратегии поведения связан с личностными особенностями респондентов. Обнаружены значимые различия между группами студентов с разными стратегиями поведения в Интернете по адаптивности, самопринятию и автономности. Обсуждение результатов. Авторы рассматривают личностные особенности молодежи с разными стратегиями онлайн-поведения. В заключение делается вывод, что факторные структуры студентов с разными стратегиями онлайн-поведения различаются

Ukrainian Plant Trait Database: UkrTrait v. 1.0

Considering the growing demand for plant trait data and taking into account the lack of trait data from Eastern Europe, especially from its steppic region, we launched a new Ukrainian Plant Trait Database (UkrTrait v. 1.0) aiming at collecting all the available plant trait data from Ukraine.To facilitate further use of this database, we linked the trait terminology to the TRY Plant Trait Database, Thesaurus of Plant Characteristics (TOP) and Plant Trait Ontology (TO). For taxa names, we provide the crosswalks between the Ukrainian checklist and international sources, i.e. GBIF Backbone Taxonomy, World Checklist of Vascular Plants (World Checklist of Vascular Plants (World Checklist of Vascular Plants (WCVP), World Flora Online (WFO) and Euro+Med PlantBase. We aim to integrate our data into the relevant global (TRY Plant Trait Database) and pan-European (FloraVeg.EU) databases. The current version of the database is freely available at the Zenodo repository and will be updated in the future.Until now, plant traits for the Ukrainian flora were scattered across literature, often focusing on single species and written mainly in Ukrainian. Additionally, many traits were in grey literature or remained non-digitised, which rendered them inaccessible to the global scientific community. Addressing this gap, our Ukrainian Plant Trait Database (UkrTrait v. 1.0) represents a significant step forward. We compiled and digitised plant traits from local Ukrainian literature sources. Furthermore, we performed our own field and laboratory measurements of various plant traits that were not previously available in literature. In the current version of the UkrTrait, we focus on vascular plant species that are absent from the other European trait databases, with emphasis on species that are representative for the steppe vegetation. Traits assembled from literature include life span (annuals, biennials, perennials), plant height, flowering period (flowering months), life form (by Raunkiaer), plant growth form and others. Our own measured traits include seed mass, seed shape, leaf area, leaf nitrogen concentration and leaf phosphorus concentration. The current version, i.e. UkrTrait v. 1.0, comprises digitised literature data of 287,948 records of 75 traits for 6,198 taxa and our own trait measurements of 2,390 records of 12 traits for 388 taxa