Applying model transformation and Event-B for specifying an industrial DSL

In this paper we describe our experience in applying the Event-B formalism for specifying the dynamic semantics of a real-life industrial DSL. The main objective of this work is to enable the industrial use of the broad spectrum of specification analysis tools that support Event-B. To leverage the usage of Event-B and its analysis techniques we developed model transformations, that allowed for automatic generation of Event-B specifications of the DSL programs. The model transformations implement a modular approach for specifying the semantics of the DSL and, therefore, improve scalability of the specifications and the reuse of their verification. Keywords: domain specific language, Event-B, model transformations, verification and validation, reuse, scalabilit

Constraint-based run-time state migration for live modeling

Live modeling enables modelers to incrementally update models as they are running and get immediate feedback about the impact of their changes. Changes introduced in a model may trigger inconsistencies between the model and its run-time state (e.g., deleting the current state in a statemachine); effectively requiring to migrate the run-time state to comply with the updated model. In this paper, we introduce an approach that enables to automatically migrate such runtime state based on declarative constraints defined by the language designer. We illustrate the approach using Nextep, a meta-modeling language for defining invariants and migration constraints on run-time state models. When a model changes, Nextep employs model finding techniques, backed by a solver, to automatically infer a new run-time model that satisfies the declared constraints. We apply Nextep to define migration strategies for two DSLs, and report on its expressiveness and performance

The Relationship Between Social Intelligence and Empathy of Older Preschool Children

В статье изложены результаты проведенного эмпирического исследования взаимосвязи социального интеллекта и эмпатии детей старшего дошкольного возраста, определены достоверные различия в уровне выраженности социального интеллекта и эмпатии у девочек и мальчиков старшего дошкольного возраста. В результате корреляционного анализа были выявлены взаимосвязи между социальным интеллектом и эмпатии у девочек и мальчиков старшего дошкольного возраста. Мы также пришли к выводу о необходимости разработки и реализации программы развития социального интеллекта и эмпатии детей старшего дошкольного возраста.The article presents the results of an empirical study of the relationship between social intelligence and empathy of older preschool children, identifies significant differences in the level of expression of social intelligence and empathy in girls and boys of older preschool age. The correlation analysis revealed the relationship between social intelligence and empathy in girls and boys of senior preschool age. We also came to the conclusion that it is necessary to develop and implement a program for the development of social intelligence and empathy of older preschool children

EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment

The global biogeography of tree leaf form and habit

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

Clinical features of post-COVID-19 period. Results of the international register “Dynamic analysis of comorbidities in SARS-CoV-2 survivors (AKTIV SARS-CoV-2)”. Data from 6-month follow-up

Aim. To study the clinical course specifics of coronavirus disease 2019 (COVID-19) and comorbid conditions in COVID-19 survivors 3, 6, 12 months after recovery in the Eurasian region according to the AKTIV register. Material and methods.The AKTIV register was created at the initiative of the Eurasian Association of Therapists. The AKTIV register is divided into 2 parts: AKTIV 1 and AKTIV 2. The AKTIV 1 register currently includes 6300 patients, while in AKTIV 2 — 2770. Patients diagnosed with COVID-19 receiving in- and outpatient treatment have been anonymously included on the registry. The following 7 countries participated in the register: Russian Federation, Republic of Armenia, Republic of Belarus, Republic of Kazakhstan, Kyrgyz Republic, Republic of Moldova, Republic of Uzbekistan. This closed multicenter register with two nonoverlapping branches (in- and outpatient branch) provides 6 visits: 3 in-person visits during the acute period and 3 telephone calls after 3, 6, 12 months. Subject recruitment lasted from June 29, 2020 to October 29, 2020. Register will end on October 29, 2022. A total of 9 fragmentary analyzes of the registry data are planned. This fragment of the study presents the results of the post-hospitalization period in COVID-19 survivors after 3 and 6 months. Results. According to the AKTIV register, patients after COVID-19 are characterized by long-term persistent symptoms and frequent seeking for unscheduled medical care, including rehospitalizations. The most common causes of unplanned medical care are uncontrolled hypertension (HTN) and chronic coronary artery disease (CAD) and/or decompensated type 2 diabetes (T2D). During 3- and 6-month follow-up after hospitalization, 5,6% and 6,4% of patients were diagnosed with other diseases, which were more often presented by HTN, T2D, and CAD. The mortality rate of patients in the post-hospitalization period was 1,9% in the first 3 months and 0,2% for 4-6 months. The highest mortality rate was observed in the first 3 months in the group of patients with class II-IV heart failure, as well as in patients with cardiovascular diseases and cancer. In the pattern of death causes in the post-hospitalization period, following cardiovascular causes prevailed (31,8%): acute coronary syndrome, stroke, acute heart failure. Conclusion. According to the AKTIV register, the health status of patients after COVID-19 in a serious challenge for healthcare system, which requires planning adequate health system capacity to provide care to patients with COVID-19 in both acute and post-hospitalization period

Positive feedbacks and alternative stable states in forest leaf types

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4–43% higher growth rates, 14–17% higher survival rates and 4–7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

BACterial Hosts for production of Bioactive phenolics from bERRY fruits (BacHBerry) was a 3-year project funded by the Seventh Framework Programme (FP7) of the European Union that ran between November 2013 and October 2016. The overall aim of the project was to establish a sustainable and economically-feasible strategy for the production of novel high-value phenolic compounds isolated from berry fruits using bacterial platforms. The project aimed at covering all stages of the discovery and pre-commercialization process, including berry collection, screening and characterization of their bioactive components, identification and functional characterization of the corresponding biosynthetic pathways, and construction of Gram-positive bacterial cell factories producing phenolic compounds. Further activities included optimization of polyphenol extraction methods from bacterial cultures, scale-up of production by fermentation up to pilot scale, as well as societal and economic analyses of the processes. This review article summarizes some of the key findings obtained throughout the duration of the project