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The advantages of a filtering material with an orthotropic structure (FMTS) consisting of a package of woven meshes are described. Information is given on the first stage of FMTS modeling, which includes the choice of parameters and factors of the experiment and the compilation of a planning matrix to establish the relationship between technological characteristics and properties of FMTS. When constructing a stochastic mathematical model at this stage, two factors were chosen to describe the properties of the material – qualitative (mesh type), specified by the sigma constraint method, and quantitative (package thickness). The constructed matrix of experiment planning is given. The natural and coded values of FMTS samples were determined.

The current methods of computer modeling of cost models created at the development stage of a building construction project are presented in the paper. The paper considers the world and Russian experience on the use of automation technologies in order to accelerate the formation of cost models for capital construction objects. The current approach to model formation is visualized, indicating the necessary components of the process.

1. Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management. 2. Greater sage-grouse Centrocercus urophasianus, hereafter 'sage-grouse' populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize the use of available information. 3. Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by >35 500 independent telemetry locations from >1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes. 4. We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of the following: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. 5. Synthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.

An actual task is to design the modeling and visualizing components of the Industry 4.0 production division activity. The Industry 4.0 production division as a part of smart factory functions automatically with special cyber and physical systems (CPS). The smart factory projection is done as a program of the industrial economy sector prioritized development. To project a production division they use the systems of automatic projection (CAD) installed in an instrument designer PC. Smart factory CAD components are CPS graphical models means, which includes the production division graphical models and the models of product being manufactured. All graphical models have the full information similarity to the physical devices. There are components and description schemes of their interaction to create CAD software to project automatic productions.

We are delighted to introduce you the publication of all reviewed papers which is the result of fruitful cooperation among the Technical University of Košice, University of Žilina, Alexander Dubček University of Trenčín, Slovak University of Technology in Bratislava, Kazimierz Wielki University in Bydgoszcz, Poznań University of Technology, Rzeszow University of Technology, Czestochowa University of Technology, Calisia University - Kalisz, Poland, AGH University of Science and Technology, Warsaw University of Technology, Regional technological institute, Jan Evangelista Purkyně University in Ústí nad Labem, Institute of Technology and Business in České Budějovice. The 26th International Slovak-Polish Scientific Conference on Machine Modelling and Simulations continues in the Slovak Republic and was held from 13th to 15th of September 2021 in Hotel Alexander, Bardejovské Kúpele, Slovak Republic. The international conference was established in 1996 and is held annually every year. List of Organizing Committee, Organizing Committee, Scientific Committee are available in this pdf.

We discuss the method of modelling design on horizontal box from five aspects: function, modelling, material, process and color. It is pointed out that in order to adapt to the market, it is necessary to design new products with a sense of the times.

Based on the principles of didactics, the role of student activity and independence in the learning process is shown. The approaches are determined and the place of simulation modeling in the development and design of systems is shown. Examples of modeling systems are given. Special attention is paid to the principle of controlled independent work of the student.

The maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr−1, 65% of the range of a recent model inter-comparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.

Background The dynamics of phosphorus (P) in the environment is important for regulating nutrient cycles in natural and managed ecosystems and an integral part in assessing biological resilience against environmental change. Organic P (Po) compounds play key roles in biological and ecosystems function in the terrestrial environment being critical to cell function, growth and reproduction. Scope We asked a group of experts to consider the global issues associated with Po in the terrestrial environment, methodological strengths and weaknesses, benefits to be gained from understanding the Po cycle, and to set priorities for Po research. Conclusions We identified seven key opportunities for Po research including: the need for integrated, quality controlled and functionally based methodologies; assessment of stoichiometry with other elements in organic matter; understanding the dynamics of Po in natural and managed systems; the role of microorganisms in controlling Po cycles; the implications of nanoparticles in the environment and the need for better modelling and communication of the research. Each priority is discussed and a statement of intent for the Po research community is made that highlights there are key contributions to be made toward understanding biogeochemical cycles, dynamics and function of natural ecosystems and the management of agricultural systems.

Structural thinking, defined as the identification of relationships among the elements of a system and their use to understand its functioning, is relevant in both scientific modelling and Mathematics Education. Due to the lack of explicit models to describe this type of thinking, this study aims to characterize the structural thinking present in Galois' first memoir, “Memoir on the Conditions for the Solvability of Equations by Radicals”. This treatise is significant for introducing the mathematical notion of group and the study of algebraic structures. Based on documentary analysis, the treatise and its historical context were examined, leading to the identification of three key characteristics of structural thinking: the study of structure–behavior relationships, isomorphism as a modelling mechanism, and the development of a macrostructural view.