Dynamical Systems Theory Research Articles

Simulation Study on the Policy of Coordinated Development of Agriculture and Agricultural Product Logistics in Sichuan Province

This paper utilises the system dynamics theory to develop a simulation model of the agricultural and agricultural product logistics system in Sichuan Province. The coordinated development policy of the agricultural and agricultural product logistics in Sichuan Province is analysed through simulation by adjusting the proportions of investment in the logistics industry, logistics information technology, and agricultural financial input. The study suggests that enhancing investments in logistics industry and logistics information technology leads to an accelerated development in the agricultural product logistics sector, ultimately promoting coordination between the agricultural economy and agricultural product logistics. Moreover, lowering agricultural financial input can lead to more rational allocation and utilization of resources, hence further advancing the coordinated growth of agriculture and agricultural product logistics.

Improving the construction accuracy of precast components in prefabricated buildings by analyzing relevant factors from the perspective of supply chain: a system dynamics model

ABSTRACT The construction accuracy of precast components in prefabricated buildings has received sufficient attention in the context of the high-quality development of the construction industry. However, various unknown factors in the production, transportation, and installation stages lead to significant deviations in construction, and have not been systematically identified and dynamically analyzed in previous studies. This study aims to improve the construction accuracy of precast components by unlocking the causal relationships among these factors and revealing top-sensitive factors among them. Thus, based on the theory of system dynamics (SD), an SD model is established from the perspective of a supply chain consisting of the production, transportation, and installation stages. The 14 factors and their causal relationships involved in the SD model are identified through literature review and expert consultation methods. The sensitivity analysis method based on dynamic simulation is adopted to analyze the data output from the SD model. Finally, a real prefabricated building project is used for demonstrating and validating this SD model. The significant findings indicate that the installation stage is the most critical stage affecting the construction accuracy of precast components, and the precision of cast-in-situ structure is the most sensitive factor. The formwork system of cast-in-situ structure and construction personnel quality are the root causes of the precision of cast-in-situ structure. The suggestions corresponding to these findings are made. These findings and suggestions can facilitate general contractors in allocating relevant resources to more critical factors for efficiently improving the construction accuracy of precast components.

Fluctuations in auxin levels depend upon synchronicity of cell divisions in a one-dimensional model of auxin transport.

Auxin is a well-studied plant hormone, the spatial distribution of which remains incompletely understood. Here, we investigate the effects of cell growth and divisions on the dynamics of auxin patterning, using a combination of mathematical modelling and experimental observations. In contrast to most prior work, models are not designed or tuned with the aim to produce a specific auxin pattern. Instead, we use well-established techniques from dynamical systems theory to uncover and classify ranges of auxin patterns as exhaustively as possible as parameters are varied. Previous work using these techniques has shown how a multitude of stable auxin patterns may coexist, each attainable from a specific ensemble of initial conditions. When a key parameter spans a range of values, these steady patterns form a geometric curve with successive folds, often nicknamed a snaking diagram. As we introduce growth and cell division into a one-dimensional model of auxin distribution, we observe new behaviour which can be explained in terms of this diagram. Cell growth changes the shape of the snaking diagram, and this corresponds in turn to deformations in the patterns of auxin distribution. As divisions occur this can lead to abrupt creation or annihilation of auxin peaks. We term this phenomenon 'snake-jumping'. Under rhythmic cell divisions, we show how this can lead to stable oscillations of auxin. We also show that this requires a high level of synchronisation between cell divisions. Using 18 hour time-lapse imaging of the auxin reporter DII:Venus in roots of Arabidopsis thaliana, we show auxin fluctuates greatly, both in terms of amplitude and periodicity, consistent with the snake-jumping events observed with non-synchronised cell divisions. Periodic signals downstream of the auxin signalling pathway have previously been recorded in plant roots. The present work shows that auxin alone is unlikely to play the role of a pacemaker in this context.

An Examination of Improvement in Swallowing and Speech Production on the Quality of Life Among Children with Cerebral Palsy in Mombasa County, Kenya

The purpose of this research was to examine if an improvement in swallowing and speech production can increase the quality of life among children with Cerebral Palsy (CP). Dynamic Systems Theory by Smith and Thelen (1995) was adopted. Case study design was adopted for the study which allowed a researcher to look into a single subject in depth. Piloting was done at the Association for the Physically Disabled of Kenya (APDK), Mombasa County. Purposive sampling was employed to sample children between 3-8 years of age with Cerebral Palsy. Modified speech assessment tools and a list of the evidence-based swallowing exercises were used to collect data. Data analysis was carried out using both qualitative and quantitative methods. Data was analyzed using Statistical Package for Social Sciences (SPSS, version 24.0) and descriptive statistics of frequencies and percentages were used to summarize the demographic information. Analysis of Covariance (ANCOVA) for the pre-treatment and post treatment engaging swallowing exercises was computed at .05 alpha level. Tables and graphs were used to present the data. A p-value < 0.05 was considered statistically significant if there were differences in the mean ranks of the responses. Findings revealed that before treatment through swallowing exercises, an average of one child with CP could communicate through speech and was able to feed variety of food without problems. However, after the administration of swallowing exercise during the eighth week, an average of children with CP across all the groups were able to communicate through speech and feed a variety of food without help The use of tongue extension, tongue retraction , tongue tip up, elevating tongue towards palate, opening of the jaw, circular movement of the jaw and lip press on tongue depressor had the highest mean rank implying that they had better effects on speech and vocal quality among children with CP under the study. The study concludes that apart from enhancing speech production, swallowing exercises positively impacted on quality of life among children with CP. The study recommends the government should create awareness regarding the need to promote speech therapy courses and medical education to increase the number of available speech therapists. Keywords: improvement in swallowing exercise; speech production; quality of life; children with Cerebral Palsy

Motivational Dynamics of Intermediate Chinese Learners in a COVID-Induced Remote IPA-Informed CSL Curriculum: A Case Study From a CDST Lens

Abstract Grounded in a complex and dynamic systems theory (CDST) perspective of L2 learning motivation, this year-long longitudinal study examines evolving motivational dynamics of two intermediate Chinese as a Second Language (CSL) learners at a Sino-US joint-venture university in China during the COVID-19 pandemic. Adopting Higgins’ framework of motivation, this case study focuses on the interplay of learner motivation for value, control, and truth effectiveness and contextual factors in shaping the contrastive motivational trajectories of two CSL learners who displayed discrepancy in the improvement of Mandarin oral proficiency. In particular, the two contextual factors of interest are an Integrated Performance Assessment (IPA) -informed CSL curriculum and COVID-induced remote online learning. We focus on how learners co-adapted with the “here-and-now” manifestations of these contextual factors and how their motivational dynamics and learning behaviors evolved based on multiple interrelated layers of the temporal-spatial context. The findings show that CSL learners’ motivational dynamics were shaped by multiple overlapping and interrelated motivations related to value, control, and truth effectiveness, which emerged out of the contingencies and affordances in the learning context. The learner-context co-adaptations play a significant role in directing relevant motivational dimensions and thereby shaping the overall identity of the whole system. This empirical study contributes to CSL and L2 motivational studies by exploring the applicability of a CDST approach and a global motivational framework to study intermediate CSL learners’ motivational dynamics and how they individually co-adapted with an innovative curricular design and the perturbance during the COVID-19 online teaching and learning process. The paper reflects on the effectiveness and applicability of IPA in an intermediate-level CSL curriculum from a motivational perspective and offers insights into understanding and promoting the complex learner motivation during COVID-19 for language educators.

Modeling car dependency and policies towards sustainable mobility: A system dynamics approach

Despite decades of research on urban transportation, few researchers apply a holistic understanding of the urban transport mechanism. To address this gap, in this paper we employed a two-stage modeling approach using a system dynamics method and theory of path dependence. First, an exploratory model presents the structure, including feedback loops and underlying mechanisms of the evolution of car dependency. The model explores loop dominance, and implicit goals determine whether it is a car-dependent or transit-oriented and active modes-based transport system. Car dependence arises from the dominance of road-based feedback loops for commuters to achieve their transportation goals. Second, a revised policy structure reveals that shifting the loop dominance towards transit-oriented and active modes-based transportation system is possible when commuters achieve their goals through transit and active infrastructure-based feedback loops. The scale and timing of policy leverages determine the thresholds for the loop dominance shift.

Social indexicality and L2 speech development

The propensity to see language as a construction that provides social cues has great implications for both societal structure and human psychological processes, including first and second language development and attrition. In this regard, social indexicality, for instance, has been shown to play a crucial role in L2 speech development. Even though some branches of linguistics embrace social indexicality in their machinery and predictions (e.g., sociolinguistics, sociophonetics), the addition of social variables in the area of Second Language Acquisition (SLA) and in Psycholinguistics might be seen as recent and limited. Considering that psycholinguistics should start including social indexicality when addressing language learning, this theoretical research article aims at exploring and drawing attention to the relationship between psycholinguistics and sociolinguistics with regard to L2 speech development. In order to do so, it provides an outline of the research agenda of L2 speech development as situated in psycholinguistics. It then discusses the role of social indexicality in bilingual development. Finally, the article advocates the Complex Dynamic Systems Theory (CDST) as a fruitful paradigm to anchor such an interface, since it includes both cognitive and social aspects in its core.

Language Transfer of English Majors in L3 German Learning from the Perspective of Dynamic Systems Theory

As the cultures of the worlds peoples interact and merge, language is an important vehicle for their development and will inevitably influence and intermingle with each other. English and German belong to the same language family, and both languages have commonalities and similarities in phonology, vocabulary and grammar. Based on this, from the perspective of dynamic systems theory, this paper focuses on the positive and negative transfer of L2 (English) knowledge in the acquisition of L3 (German) vocabulary and investigates the difficulties of trilingual learning of English majors in Guangzhou, China by means of questionnaires and interviews. The contents of the questionnaire included the different trilingual categories chosen by English majors and the influence of second language in the trilingual learning process. Through the questionnaire survey, the author found that second language had a significant transfer effect on third language acquisition in phonetics and vocabulary. Through the classification of trilingual and the analysis of transfer categories, it is expected to effectively improve the learning effect of German and strengthen the understanding of English majors on trilingual acquisition.

Analysis of the joint trading of local green power certificates, carbon emissions rights, and electricity considering demand flexibility

Establishing synergy among distinct yet associated markets through market orientation is crucial because it can facilitate a clean and low-carbon energy transition. However, researchers have not yet developed a quantitative analytical dynamic model for studying market participants in the context of the joint electricity-carbon-green power certificates market. Moreover, the solution algorithm merits further exploration. This article proposes an analytical method for evaluating the joint trading of local green power certificates, carbon emission rights, and electricity, while taking into account the demand flexibility. First, a framework for the joint trading of local green power certificates, carbon emission rights, and electricity is designed. Second, market participants, such as traditional thermal power plants, renewable energy power plants, and load aggregators, are modelled via system dynamics theory. On this basis, a deep distributed reinforcement learning algorithm is applied to solve the problem. Finally, the effectiveness of the proposed theoretical approach is verified through real-life simulations, and the sensitivity of the key factors influencing joint trading is also analysed.

Dynamics of the FitzHugh-Nagumo equation with numerical methods

In this paper, our research focuses on investigating the behavior of the FitzHugh-Nagumo (FHN) equation dynamics, a mathematical model that describes the spiking behavior of neurons. We begin by presenting the mathematical formulation of the FHN equation as a system of two coupled ordinary differential equations. We then apply methods from the theory of dynamical systems to analyze the behavior of the system, including stability analysis and phase-plane analysis. We also discuss the bifurcations that occur in the system as its parameters are varied. In addition, we present numerical methods for solving the FHN equation, including explicit and implicit methods. We compare the accuracy and efficiency of these methods and discuss their suitability for different types of problems.Our results show that the FHN equation exhibits a rich range of dynamical behaviors, including periodic and chaotic solutions, bistability, and hysteresis.Additionally, FHN equation can be used to simulate the behavior of networks of excitable cells, such as neural circuits or cardiac tissue,and FHN models can also be used to study the effects of drugs or other interventions on the behavior of excitable cells. The numerical methods we present provide a powerful tool for studying the FHN equation and its variants, allowing us to explore the parameter space and predict the behavior of the system under different conditions.

Differentiability of the Largest Lyapunov Exponent for Non-Planar Open Billiards

This paper investigates the behaviour of open billiard systems in high-dimensional spaces. Specifically, we estimate the largest Lyapunov exponent, which quantifies the rate of divergence between nearby trajectories in a dynamical system. This exponent is shown to be continuous and differentiable with respect to a small perturbation parameter. A theoretical analysis forms the basis of the investigation. Our findings contribute to the field of dynamical systems theory and have significant implications for the stability of open billiard systems, which are used to model physical phenomena. The results provide a deeper comprehension of the behaviour of open billiard systems in high-dimensional spaces and emphasise the importance of taking small perturbations into consideration when analysing these systems.

A discourse dynamics analysis of academic voice construction: Disciplinary variation, trajectories, and dynamic interaction patterns

The discourse dynamics approach is a novel approach proposed within Complex Dynamic Systems Theory to explore the developmental and interactional characteristics of a complex system as manifested in discourse over time. This approach has been attested to be advantageous for identifying the evolutionary dynamics of language practices and social events. The current study adopts this approach to investigate the diachronic changes and dynamic interaction patterns of different categories of voice markers across four disciplines in 1970–2020. Using published research articles sampled with two-year intervals, the analysis revealed non-linear trajectories and dynamically changing interaction patterns of different categories of voice markers, as well as disciplinary variation in the use, trajectories, and interaction patterns of such expressions. Our findings demonstrate the value of understanding academic voice construction from a diachronic perspective through the discourse dynamics approach and can be useful for informing academic writing pedagogy aimed at helping novice academic writers understand discipline-specific practices of academic voice construction.

Robust learning of parsimonious deep neural networks

We propose a simultaneous learning and pruning algorithm capable of identifying and eliminating irrelevant structures in a neural network during the early stages of training. Simultaneous learning and pruning presents serious challenges such as premature pruning of units that can lead to poor performance. Our method is capable of overcoming such challenges and is robust, i.e., it gives consistent pruning levels and prediction accuracy regardless of weight initialization or the size of the starting network. Thus, it allows for substantial computational cost savings during training, besides that of inference, and it can enable the training of very deep networks when transfer learning to obtain fully trained deep networks that can be pruned after training is not possible. Our approach is based on variational inference principles using Gaussian scale mixture priors on the neural network weights. The variational posterior distribution of Bernoulli random variables multiplying the units/filters is learned, similarly to adaptive dropout. We construct a novel hyper-prior distribution over the prior parameters to impose properties crucial for their optimal selection and the overall robustness of our algorithm. It is shown in the context of our algorithm that the parameters of the posterior distributions practically converge to either 0 or 1, establishing a deterministic final network. Convergence is proved analytically based on dynamical systems theory and from the theoretical results, practical pruning conditions are established. The proposed algorithm is evaluated on the MNIST, CIFAR-10 and ImageNet data sets and the commonly used fully connected, convolutional and residual architectures LeNet, VGG16 and ResNet. The simulations show that our method typically achieves better pruning levels while maintaining test-accuracy on par with state-of the-art methods for structured pruning in a manner robust with respect to network initialization and initial size.

Nonlinear time series analysis of coastal temperatures and El Niño–Southern Oscillation events in the eastern South Pacific

Abstract. We carry out a nonlinear time series analysis motivated by dynamical systems theory to investigate the links between temperatures on the eastern South Pacific coast, influenced by the Humboldt Current System, and El Niño–Southern Oscillation (ENSO) events. To this aim, we use a set of 16 oceanic and atmospheric temperature time series from Chilean coastal stations distributed between 18 and 45∘ S. The spectral analysis indicates periodicities that can be related to both internal and external forcing, involving not only ENSO, but also the Pacific Decadal Oscillation, the Southern Annual Mode, the Quasi-Biennial Oscillation and the lunar nodal cycle. The asymptotic neural network test for chaos based on the largest global Lyapunov exponent indicates that the temperature dynamics along the Chilean coast is not chaotic. We use local Lyapunov exponents to characterize the short-term stability of the series. Using a cross-entropy test, we find that two stations in northern Chile, one oceanic (Iquique) and one atmospheric (Arica), present a significant positive cross-dependence between local Lyapunov exponents and ENSO. Iquique is the station that presents the greater number of regional characteristics and correlates with ENSO differently from the rest. The unique large-scale study area, combined with time series from hitherto unused sources (Chilean naval records), reveals the nonlinear dynamics of climate variability in Chile.

Government resource allocation practices toward carbon neutrality in China: A hybrid system approach

Government resource allocation practices for achieving carbon neutrality need to be guided by dynamic system theory to identify potential dynamics in China. In particular, dynamic system theory addresses the complex interrelationships and identifies the changes in dynamics to support the decision-making process in pursuing carbon neutrality among international trade, transportation, industrial demand and dynamic control. However, carbon neutrality involves various activities to better understand the complex activity interrelationships. The data are collected from four major databases including 30 Chinese provinces/cities covering a six-year period with the accumulated frequency in the Baidu Index. This study proposes a hybrid system approach to dynamic resource analysis. The results showed that carbon intensity control dynamics impose a greater influence on the other dynamics toward carbon neutrality. Many provinces can achieve carbon neutrality by regulating the electronics and telecommunications equipment industry.

Heteroclinic networks for brain dynamics.

Heteroclinic networks are a mathematical concept in dynamic systems theory that is suited to describe metastable states and switching events in brain dynamics. The framework is sensitive to external input and, at the same time, reproducible and robust against perturbations. Solutions of the corresponding differential equations are spatiotemporal patterns that are supposed to encode information both in space and time coordinates. We focus on the concept of winnerless competition as realized in generalized Lotka-Volterra equations and report on results for binding and chunking dynamics, synchronization on spatial grids, and entrainment to heteroclinic motion. We summarize proposals of how to design heteroclinic networks as desired in view of reproducing experimental observations from neuronal networks and discuss the subtle role of noise. The review is on a phenomenological level with possible applications to brain dynamics, while we refer to the literature for a rigorous mathematical treatment. We conclude with promising perspectives for future research.

Wave solutions of the time-space fractional complex Ginzburg-Landau equation with Kerr law nonlinearity

In this paper, the bifurcation theory of dynamical system is applied to investigate the time-space fractional complex Ginzburg-Landau equation with Kerr law nonlinearity. We mainly consider the case of $\alpha\neq 2\beta$ which is not discussed in previous work. By overcoming some difficulties aroused by the singular traveling wave system, such as bifurcation analysis of nonanalytic vector field, tracking orbits near the full degenerate equilibrium and calculation of complicated elliptic integrals, we give a total of 20 explicit exact traveling wave solutions of the time-space fractional complex Ginzburg-Landau equation and classify them into 11 categories. Some new traveling wave solutions of this equation are obtained including the compactons and the bounded solutions corresponding to some bounded manifolds.

Textiles as a Type of Decorative and Applied Arts: Constructing a Definition

The article is devoted to the construction of the concept of “textile as a type of decorative and applied arts” in Russian art history. An accurate and fully formulated definition helps to build a coherent scientific theory. The need to develop a theory of textiles is long overdue, due to its significant role in the life of society. The difficulties of definitions of textiles as an object of research are related to its interdisciplinary nature and the need to take into account all qualitative characteristics. In the course of the work we analyzed groups of domestic and translated bibliographic sources: reference editions, works of theorists and historians of decorative and applied arts and art textiles. It has been revealed that domestic publications have not yet formulated a universal concept of textile, which would reflect its essential qualities. The methodological argumentation, with the help of which definitions are constructed, has not yet been applied to textiles as a type of decorative and applied arts. In order to form a universal concept, we propose to turn to the proven methodological tools of the method of two-level triadic decoding of categories of the theory of dynamic information systems, which has already shown its heuristics in different fields of knowledge. Identification, comprehension and structuring of fundamental aspects of textile as a kind of decorative and applied arts in the course of consistent application of this method allowed us to formulate the following definition: textile as a kind of decorative and applied arts in the format of dynamic information system is an object or a set of objects of a certain purpose (utilitarian, symbolic, decorative), made of fiber (natural, artificial, synthetic) by means of technology (manual, industrial). The full definition of the category expands and deepens the formal-logical definition that existed earlier in the scientific literature. The present study allowed not only to construct a conceptual apparatus, but also to identify the main categories of the definition, to designate the elements and subsystems of the phenomenon for a more detailed study and formation of the theory of textiles.

The Josephson junction as a quantum engine

We treat the Cooper pairs in the superconducting electrodes of a Josephson junction (JJ) as an open system, coupled via Andreev scattering to external baths of electrons. The disequilibrium between the baths generates the direct-current bias applied to the JJ. In the weak-coupling limit we obtain a Markovian master equation that provides a simple dynamical description consistent with the main features of the JJ, including the form of the current–voltage characteristic, its hysteresis, and the appearance under periodic voltage driving of discrete Shapiro steps. For small dissipation, our model also exhibits a self-oscillation of the JJ’s electrical dipole with frequency around mean voltage V. This self-oscillation, associated with ‘hidden attractors’ of the nonlinear equations of motion, explains the observed production of monochromatic radiation with frequency Ω and its harmonics. We argue that this picture of the JJ as a quantum engine resolves open questions about the Josephson effect as an irreversible process and could open new perspectives in quantum thermodynamics and in the theory of dynamical systems.

CONTROLLING CHAOS IN 3D POROUS MEDIA IN THE PRESENCE OF ORIENTATION EFFECT

The influence of orientation on the control of chaotic behaviors of the system in a porous medium is studied in this article based on the theory of dynamical systems. A three-dimensional system model is obtained using the spectral method. The results showed that chaos can be suppressed in the case of a low or moderate Prandtl number by choosing appropriate tilt angles.