General Structural Model Research Articles

Hopf bifurcation structure of a generic car-following model with multiple time delays

This paper establishes a general bifurcation structure of a car-following model with multiple time delays. By applying the Hopf theorem, analytical calculation and numerical simulation are carried out for some typical car-following models. Our results allow a discussion of the impact of multiple time delays and other model parameters on Hopf bifurcation in various existing car-following models with delays, from elementary car-following models such as the optimal velocity model, the full velocity difference model and the intelligent driver model, to Cooperative Adaptive Cruise Control car-following models. It is particularly interesting to observe that the multiple time delays cancel out the impact of each other on the traffic instability.

Twisted Trilayer Graphene: A Precisely Tunable Platform for Correlated Electrons.

We introduce twisted trilayer graphene (tTLG) with two independent twist angles as an ideal system for the precise tuning of the electronic interlayer coupling to maximize the effect of correlated behaviors. As established by experiment and theory in the related twisted bilayer graphene system, van Hove singularities (VHS) in the density of states can be used as a proxy of the tendency for correlated behaviors. To explore the evolution of VHS in the twist-angle phase space of tTLG, we present a general low-energy electronic structure model for any pair of twist angles. We show that the basis of the model has infinite dimensions even at a finite energy cutoff and that no Brillouin zone exists even in the continuum limit. Using this model, we demonstrate that the tTLG system exhibits a wide range of magic angles at which VHS merge and that the density of states has a sharp peak at the charge-neutrality point through two distinct mechanisms: the incommensurate perturbation of twisted bilayer graphene's flatbands or the equal hybridization between two bilayer moiré superlattices.

Development of the mathematical model for calculation of energy efficiency of mobile diesel compressor stations

The experience of development of domestic and foreign specialists in the sphere of energy loss reduction during gas cooling of mobile diesel compressor stations of the oil and gas industry is analyzed. The reason why the productivity of the compressors decreases after short period of operation, while the specific energy consump-tion increases. The disadvantages of existing cooling systems of compressed gas of mobile diesel compressor sta-tions are presented. Requirements for refrigerant coolants for compressor gas cooling systems are formulated. A reasonable choice of Freon R134a as a coolant for cooling of the compressed gas of the compressor stations is made. The structure and principle of operation of the system of high-efficiency reduction of temperature of the perspective system of cooling of compressed gas are presented. The tasks and basic assumptions of mathematical modeling of energy efficient scheme of gas cooling system are formulated. The purpose of this article is to investigate theoreti-cally the choice of coolant for a promising highly efficient system for cooling the compressed gas of mobile diesel compressor stations in the oil and gas industry. Inputs, outputs and general structure of mathematical model of multistage gas cooling of mobile diesel compressor stations are offered. The structure of the system of high-efficiency reduction of temperature of the perspective system of cooling of compressed gas and the principle of action are presented. The description and calculation formulas of the mathematical model of compressed gas cool-ing of mobile diesel compressor stations are given. When choosing a refrigerant with the condition of further use of the obtained energy, the main requirement was taken into account. The total specific energy costs for the opera-tion of the compressor installation according to the existing and perspective schemes and its energy efficiency indicators are determined.

Hybrid model approaches for compensating environmental influences in machine tools using integrated sensors

Abstract Uncontrolled environmental conditions often impact manufacturing processes and lead to product quality fluctuations. For machine tools, thermal influences are a major limitation to the volumetric performance. Climate controls for the shop floor, and machines, or thermally stable structural designs are economically not feasible, promoting control-based compensation as a possible solution. Since the relationship between disturbing quantities and effects are complex and specific to each machine, appropriate modelling is a critical requirement. The authors describe an approach for developing hybrid models, superposing white-box model knowledge, and machine learning. The overall effort can be optimized by combining and balancing different modelling methods, like designing the physical model part and training intelligent algorithms. A general model structure allows a continuous integration of different white-box and black-box model components. The authors integrate self-developed smart sensors into a demonstrator machine tool to test and validate the performance of the approach.

Obtaining and losing the bipolarity of the five-factor model through factor analysis.

The predominant model of general personality structure is arguably the 5-factor model (FFM), consisting of the 5 broad domains of neuroticism, extraversion, openness, agreeableness, and conscientiousness. A FFM of personality disorder (FFMPD) has proposed maladaptive variants at both poles of the FFM. The purpose of the current study was to identify a subset of FFMPD scales, using factor analysis, that illustrate the bipolarity present in the FFMPD, but equally important, to demonstrate that the presence of bipolarity is impaired by a number of concerns, including the impact of nondiametric scales and the occupation of interstitial space. All of the FFMPD scales were administered to 443 community participants recruited from Amazon Mechanical Turk. Bipolarity was evident in a series of factor analyses of subsets of FFMPD scales, with the exception of openness due to the presence of nondiametric scales. Scales identified in the current study can be used to provide an alternative measure of maladaptive personality structure, particularly if there is an interest in assessing for maladaptive variants at both poles, but an additional point of emphasis in the current study was also the fragility of this bipolar factor structure within factor analytic research. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Modern Solutions to Modeling and Optimization of the Steady State of Multi-Energy Systems

A complex solution of problem of creating mathematical models of multi-energy systems is possible using a unified approach. An approach that will ensure consistent construction of mathematical models and unification of computational algorithms. The paper presents the elements of the concept of energy circuits as a basis for unified modeling of systems of different physical nature. The existing and developed approaches to solving the problems of calculating the flow distribution in multi-energy systems are presented, based on the analysis of publications on this subject. The general structure of the mathematical model of the flow distribution in a multi-energy system and the set of optimization problems for steady-state operating conditions are described. A possible formulation of the optimization problem for the short-term operation of a multi-energy system is presented.

Analysis of personality disorder profiles obtained by five-factor personality model

Background/Aim. In spite of the growing body of evidence in the field of personality disorders, these disorders still retain the lowest diagnostic reliability of any major category of mental disorders. The aim of this study was to investigate the differences of personality profiles in patients diagnosed with personality disorder in comparison with the group of healthy control subjects, as well as to establish to what extent the five-factor personality model domains determine the specific clusters of personality disorders. Methods. The study group comprised 97 patients diagnosed as personality disorders (according to the Diagnostic and Statistical Manual of Mental Disorders ? DSM-IV criteria), aged between 18 and 65 years [mean = 35.78 years, standard deviation (SD) = 13.72 years], 67% were female. Control group included 58 healthy subjects (student population) aged between 20 to 35 years (mean = 22.48 years, SD = 2.56 years), 56% were female. The assessment was carried out by the new version of the NEO Personality Inventory-Revised (NEO-PIR), form S, and the Structured Clinical Interview (SCID II) for DSM-IV disorders. Results. The three clusters were found by the use of regression analysis: cluster A ? eccentrics (low scores in agreeableness), cluster B ? dramatics (high score in extroversion, low score in agreeableness, and cluster C ? anxious (low score in extroversion). The findings showed that the high level of neuroticism was a non-specific predictor of all three clusters, while dimension openness to experience had no predictive power for any of the three clusters. Conclusion. Our findings support the meta-analysis which suggests consistently high level of neuroticism and low level of agreeableness in most personality disorders. The study showed that it is possible to conceptualize personality disorders by using five-factor personality model of normal personality. Integrating the psychiatric classification with the dimensional model of general personality structure could enable the uncovering of essential parameters for setting the diagnosis.

Aptamers targeting protein-specific glycosylation in tumor biomarkers: general selection, characterization and structural modeling.

Detecting specific protein glycoforms is attracting particular attention due to its potential to improve the performance of current cancer biomarkers. Although natural receptors such as lectins and antibodies have served as powerful tools for the detection of protein-bound glycans, the development of effective receptors able to integrate in the recognition both the glycan and peptide moieties is still challenging. Here we report a method for selecting aptamers toward the glycosylation site of a protein. It allows identification of an aptamer that binds with nM affinity to prostate-specific antigen, discriminating it from proteins with a similar glycosylation pattern. We also computationally predict the structure of the selected aptamer and characterize its complex with the glycoprotein by docking and molecular dynamics calculations, further supporting the binary recognition event. This study opens a new route for the identification of aptamers for the binary recognition of glycoproteins, useful for diagnostic and therapeutic applications.

A highway Across the Atlantic? Trade and Welfare Effects of the EU-Mercosur Agreement

In this paper we analyze the EU-Mercosur agreement and predict its effects on trade and welfare using a general equilibrium structural gravity model. First, we estimate the increase in trade flows generated by trade agreements that are similar to the EU-Mercosur one, in a partial equilibrium setting. In a second step, the estimated increase in trade is mapped into reductions in bilateral trade costs and imputed to EU-Mercosur country pairs to compute the general equilibrium effects of the agreement in terms of trade creation, trade diversion, and welfare effects. Our results indicate that the EU-Mercosur agreement is likely to have a positive impact on trade and welfare of both regional blocs, although with substantial heterogeneity both between and within the two areas.

Формирование механизма управления промышленными предприятиями в условиях ограничительных мер

The article presents current problems faced by industrial enterprises related to the impact of the coronavirus epidemic. Difficulties arising from the production of industrial products, which are directly related to restrictive measures, are disclosed. The key directions of companies in the field of processing are defined, namely: creation of a corporate information management system, improvement of the cash management system, introduction of such mechanisms as” implementation of remote office “and” promotion of production automation. Currently, many manufacturing companies have urgent needs for remote collaborative task management, project management, workflow management, and other software. At the same time, they pay more attention to the practical application of BI, big data analysis, and artificial intelligence. The key advantages of processes for automation and intelligent modernization of fixed assets are identified. It is proved that integration of remote control, intelligent equipment and a high level of automation into production and management processes of industrial enterprises will contribute to development in the short and long term. The main task of the presented research is to determine the key features and relationships of the elements of the management mechanism of industrial enterprises among themselves. At the same time, it was possible to form a conceptual management model based on them. To do this, it is necessary to determine the role of the industrial enterprise management mechanism in the management system. The General structural model of the industrial enterprise management mechanism in the conditions of remote control of divisions is formed. The main goal of integrating the management mechanism of an industrial enterprise is to increase competitive advantages and increase profits

Корпоративна культура, соціальна відповідальність та лідерські вміння керівника як фактори результативності трансформації компетенцій органу публічного управління

Обґрунтовано практичну та теоретичну актуальність дослідження і використання впливу корпоративної культури, соціальної відповідальності та лідерських вмінь керівників на забезпечення результативності трансформації компетенцій органів публічного управління. Проаналізовано у площині публічного управління взаємозв’язок процесів розвитку корпоративної культури, соціальної відповідальності, лідерства та визначено їх вплив на забезпечення результативності реалізації органами публічного управління своїх компетенцій. Проаналізовано стилі лідерства та обґрунтовано доцільність ширшого застосування трансформаційного лідерства як найбільш спроможного забезпечити розвиток корпоративної культури та практики соціальної відповідальності органів публічного управління для ефективної реалізації їх компетенцій.

Investigation of Mixing in Tanks of a Special Geometry

Mixing is one of the most crucial processes in the chemical industry. Homogeneity is a requirement for all feedstocks and industrial products. The degree of mixing depends on the hydrodynamic properties of the fluid in the units. The Residence Time Distribution (RTD) was investigated in a tank of a special geometry. Mixing was investigated using various geometries of the tank by applying the Heaviside function in step-response experiments. After obtaining experimental results, the RTD function was calculated. The flow structure in the tank was approximated by fitting black-box transfer function models onto the RTD function of the system. Two general model structures were defined and their fitness compared. By evaluating the fitted models, a relationship was established between the flow structure in the tank and its geometry.

Neural Networks Based Prediction Model for Vessel Track Control

The problem of neural networks implementation for the construction of a predictive model for vessel track control was studied. It has been shown that the vessel track control problem may be considered as an approximation task, and neural networks may be implemented as universal approximating tools. The general structure of the prediction model, based on neural networks, has been developed. The model consists of several two-layered feedforward neural networks, which architectures satisfy the conditions of universal approximation properties. The analysis of the functions of the different neural networks in the prediction model has been performed. The network predicting WGS-84 geodetic latitude as a part of the predictive model has been constructed, trained and validated by using MATLAB software. The validation results show the good prediction precision of the net.

Systems featuring chain structures – a generalized Bond Graph modelling

ABSTRACTThe study presents power flow modelling for dynamic systems featuring chain structures. For this purpose, the Bond Graph method is particularly suitable. This tool describes engineering systems in different fields via domain-independent graphical representation using general dynamic modelling for any physical system. Even repetitive constructions called chains can be modelled. This paper aims for power flow based dynamical models of serial type chain structures. Further graphical systematization identifies four basic scalar segments which again correlate with four general vectorial total model structures. Examples and general algorithms, to obtain the scalar segment model and the vectorial overall model, support the proposed modeling. The main vectorial modelling element is identified as a relative coordinate transformation. The approach includes usage for open and closed chains plus rings of ring structures. It aims at universal usage independent of serial chain structure type, application domain or software tool. Moreover, it can be used beneficially in various non-physical fields.

Models of everywhere revisited: A technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and non-linearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment.

Державне сприяння розвитку освіти у сфері фізичної культури на регіональному рівні: проблема узгодженості державних політик

Обґрунтовано необхідність ефективного державного сприяння розвитку освіти у сфері фізичної культури як важливого фактора формування і розвитку фізичного, психічного, соціального та духовного здоров’я суспільства та його членів. Проаналізовано систему взаємовідносин між органами виконавчої влади, органами місцевого самоврядування, організаціями фізкультурно-спортивної спрямованості щодо розвитку освіти у сфері фізичної культури шляхом поліпшення її організаційного, нормативно-правового, кадрового, матеріально-технічного, фінансового, наукового, медичного, інформаційного забезпечення. Узагальнено концептуальні засади структурно-функціональної моделі узгодження державних політик щодо сприяння розвитку освіти у сфері фізичної культури.

The importance of variation in offspring body size for stability in cannibalistic populations

Animals exhibit remarkable intraspecific variation in phenotypic traits such as body size. Understanding how such trait variation affects population and ecosystem dynamics is critically important, because future environmental change and human impacts are expected to alter phenotypic trait distributions. In species with seasonal reproduction, offspring size variation within cohorts is ubiquitous, yet we know little about its implications for population stability. In addition, long‐term monitoring data indicate that changes in offspring size variation occur at ecologically relevant time scales. Here, we study the consequences of changing offspring size variation by developing and analysing an integral projection model (IPM). Our model accounts for size‐dependent cannibalism as well as additional density regulation occurring during the first year. The model is parameterized using literature values and long‐term monitoring data for pike Esox lucius, a common fish predator in temperate freshwater ecosystems, but the general model structure applies to a wide range of size‐structured organisms. Our analyses demonstrate that a wide size distribution of offspring promotes stable dynamics, whereas narrow distributions can be destabilizing because cannibalism increases the annual variation in mean offspring mortality. Our results indicate that the stabilizing effect of offspring size variation is likely an important property of size‐structured organisms with seasonal reproduction and cannibalistic behaviour. This work highlights the importance of intracohort trait variation and describes how variation in body size can shape the dynamics of animal populations.

Unsteady State Lightweight Iris Certification Based on Multi-Algorithm Parallel Integration

Aimed at the one-to-one certification problem of unsteady state iris at different shooting times, a multi-algorithm parallel integration general model structure is proposed in this paper. The iris in the lightweight constrained state affected by defocusing, deflection, and illumination is taken as the research object, the existing algorithms are combined into the model structure effectively, and a one-to-one certification algorithm for lightweight constrained state unsteady iris was designed based on multi-algorithm integration and maximum trusted decision. In this algorithm, a sufficient number of iris internal feature points from the unstable state texture were extracted as effective iris information through the image processing layer composed of various filtering processing algorithms, thereby eliminating defocused interference. In the feature recognition layer, iris deflection interference was excluded by the improved methods of Gabor and Hamming and Haar and BP for the stable features extracted by the image processing layer, and two certification results were obtained by means of parallel recognition. The correct number of certifications for an algorithm under a certain lighting condition were counted. The method with the most correct number was set as the maximum trusted method under this lighting condition, and the results of the maximum trusted method were taken as the final decision, thereby eliminating the effect of illumination. Experiments using the JLU and CASIA iris libraries under the prerequisites in this paper show that the correct recognition rate of the algorithm can reach a high level of 98% or more, indicating that the algorithm can effectively improve the accuracy of the one-to-one certification of lightweight constrained state unsteady iris. Compared with the latest architecture algorithms, such as CNN and deep learning, the proposed algorithm is more suitable for the prerequisites presented in this paper, which has good environmental inclusiveness and can better improve existing traditional algorithms’ effectiveness through the design of a parallel integration model structure.

The Five Factor Model of personality structure: an update.

The Five Factor Model of personality structure: an update.

A numerical method for a nonlinear structured population model with an indefinite growth rate coupled with the environment

AbstractA numerical method is developed for a general structured population model coupled with the environment dynamics over a bounded domain where the individual growth rate changes sign. Sign changes notably exhibit nonlocal dependence on the population density and environmental factors (e.g., resource availability and other habitat variables). This leads to a highly nonlinear PDE describing the time‐evolution of the population density coupled with a nonlinear‐nonlocal system of ODEs describing the environmental time‐dynamics. Stability of the finite‐difference numerical scheme and its convergence to the unique weak solution are proved. Numerical experiments are provided to demonstrate the performance of the finite difference scheme and to illustrate a range of biologically relevant potential applications.