Dynamical Theory Research Articles

INTELLIGENT INFORMATION TECHNOLOGIES TO SUPPORT DECISION-MAKING WHEN APPLYING THE CAD/CAM/CAE SYSTEM OF DESIGN AND USING ADDITIVE TECHNOLOGIES

The direction of research is the development of principles and methods for making scientifically based decisions in the design and additive manufacturing of bone substitutes based on apatite-biopolymer composites with functional properties depending on the nature of the localization of the cavity bone defect and its size. The relevance is due to the fact that the development of an intelligent decision-making support system based on neural network modeling, the development of methods for their training, tabagato-criterion optimization of design processes, will allow the creation of three-dimensional solid models of defects taking into account their spatial structure and bone substitutes for the synthesis of biomaterials with controlled composition, porosity and mechanical strength, which are optimal for a specific area of bone replacement, which will increase the effectiveness of treatment and prosthetics in orthopedics and traumatology. A set of methods for analyzing images of bone tissue, taking into account its spatial structure, which are obtained by sensors of different physical nature, with the use of neural network models, development of methods of their design, optimization, and training is proposed. A modification of the method of learning neural networks based on gradient descent, based on the application of the theory of nonlinear dynamics, is proposed. Corresponding theoretical provisions have been developed.

Backstepping synchronization control for four-dimensional chaotic system based on DNA strand displacement

Backstepping control is an important nonlinear control design method, which realizes the control of complex systems by constructing control law step by step, and has significant advantages for dealing with complex nonlinear systems. This article proposes a synchronization technique for four-dimensional chaotic systems using a combination of backstepping control method and DNA strand displacement technology. By relying on theoretical knowledge of DNA molecules, five basic chemical reaction modules such as trigger reaction, reference reaction, catalytic reaction, annihilation reaction and degradation reaction are given to construct a four-dimensional DNA chaotic system. On the basis of the relevant theory of chaotic dynamics, the constructed system is analyzed by Lyapunov exponent diagram and spectral entropy complexity algorithm, and the results come to the conclusion that the system reveals extremely complex and varied dynamic behaviors. Combining DNA strand displacement technology with backstepping control method, four controllers are developed to ensure that the trajectories of two homogeneous chaotic systems are synchronized. The numerical simulation results validate the feasibility and applicability of the proposed method. The method proposed in this paper may provide some references in the field of DNA molecular chaos synchronization control.

Effective model and electron correlations in trilayer nickelate superconductor La4Ni3O10.

Recently, signatures of superconductivity with critical temperature from 20 to 30 K have been reported in pressured trilayer nickelate La$_4$Ni$_3$O$_{10}$ through a pressure-induced structure transition. Here we explore the evolution of electronic structures and electronic correlations in different phases of La$_4$Ni$_3$O$_{10}$ under corresponding pressure regions, by using density functional theory (DFT) combined with dynamical mean-field theory (DMFT). Similar to bilayer superconductor La$_3$Ni$_2$O$_{7}$, the electronic bands in superconducting La$_4$Ni$_3$O$_{10}$ are dominated by Ni-3$d_{x^2-y^2}$ and 3$d_{z^2}$ orbits near the Fermi level, in contrast, the inner Ni-O plane in La$_4$Ni$_3$O$_{10}$ generates a doublet hole-pocket Fermi surfaces around the Brillouin-zone corner, meanwhile one branch of the Ni-$3d_{z^2}$ bands is pushed very close above the Fermi level, which can induce an electron pocket through small electron doping. The DFT+DMFT simulations suggest that the electronic correlations only give minor modification to the Fermi surfaces, meanwhile the Ni-$3d_{z^2}$ and 3$d_{x^2-y^2}$ states on outer Ni-O layers have considerable greater mass enhancements than on the inner layer. The sensitiveness of electronic structure under doping and unique layer dependence of correlation suggest a distinct superconducting mechanism with respect to bilayer La$_3$Ni$_2$O$_{7}$. Based on the DFT and DFT+DMFT simulations, we eventually derive a trilayer effective tight-binding model, which can produce rather precise electronic bands and Fermi surfaces, hence can serve as an appropriate model to further study the superconducting mechanism and paring symmetry in trilayer La$_4$Ni$_3$O$_{10}$.

Agribusiness Supply Chain Collaboration: Role of Innovation Capacity and Business Process Agility as Antecedents of Supply Chain Performance

This article examines the role of innovation capacity and business process agility (BPA) in the relationship between supply chain collaboration (SCC) and supply chain performance (SCP) of smallholder agro-based enterprises (SAEs). Based on the relational view and dynamic capability theories and the survey research design, the author used questionnaires to gather data from 226 SAEs who were sampled from agribusiness associations in four regions of Ghana via the quota sampling technique. Smart PLS-SEM 4.0 was used as the statistical method to analyze the data. The results showed that SCC has a significant and positive relationship with SCP, innovation capacity, and BPA. Innovation capacity significantly mediates the relationship between SCC and SCP. Furthermore, BPA fully mediates the relationship between SCC and innovation capacity, with innovation capacity also influencing SCP. This study integrates relational and capability-based views to propose a comprehensive theoretical model showing the inter-relational effect of SCC, BPA, and innovation capacity on SCP. The empirical findings widen the context of SCC literature to include SAEs from emerging economies in sub-Saharan Africa. The empirical findings enrich the understanding of how SAEs can manage their SCCs to develop and use specific capabilities that positively impact SCP. The uniqueness of this article rests in the proposed model and new empirical knowledge, which extends the scope of the relational and capability-based views and SCC literature to include innovation capacity, BPA, and SCP of SAEs in emerging markets.

Impact of innovation, entrepreneurial orientation and entrepreneurial leadership on supply chain resilience in handicraft industry: moderating role of supply chain orientation

PurposeThe study aims to explore dynamic capabilities such as innovation, entrepreneurial leadership, absorptive capability, and the dimension of entrepreneurial orientation in the handicraft sector to enhance supply chain resilience and innovation during unprecedented times. This study also used innovation as a mediating construct and supply chain orientation as a moderating construct.Design/methodology/approachWe gathered data from the handicraft sector in the Uttar Pradesh (UP) in India using a pretested questionnaire. We used variance-based partial least squares structural equation modelling (PLS-SEM) to test our research hypotheses.FindingsOur study indicates that to enhance innovation and improve supply chain resilience, firms should focus on developing dynamic capabilities such as entrepreneurial leadership, absorptive capacity, artificial intelligence (AI), innovativeness, risk-taking ability, and protectiveness. The study highlights the significant role of dynamic capabilities in the handicraft sector during times of crisis, enabling innovation and resilience to risk.Practical implicationsThe study highlights the significant role of dynamic capabilities in the handicraft sector during times of crisis, enabling innovation and resilience to risk.Originality/valueThis study provides significant insights into the current understanding of dynamic capability theory and supply chain orientation and expands upon the existing literature in this field. It comprehensively analyses the latest research and advances knowledge in this area.

A family of quantum von Neumann architecture

Abstract In this work, we develop universal quantum computing models that form a family of quantum von Neumann architectures, with modular units of memory, control, CPU, and internet, besides input and output. This family contains three generations characterized by dynamical quantum resource theory, and it also circumvents no-go theorems on quantum programming and control. Besides universality, such a family satisfies other desirable engineering requirements on system and algorithm design, such as modularity and programmability, hence serves as a unique approach to build universal quantum computers.

Food supply chain resilience through digital transformation: a mixed-method approach

PurposeThis study aims to explore the relationship between digital transformation and resilience development in the Australian food supply chain (FSC), and identify the contribution of digital technologies to it using the dynamic capabilities theory as theoretical lens.Design/methodology/approachFor that, a mixed-method approach was used. It combines both quantitative and qualitative data to identify trends and details of the phenomenon, yielding more robust findings. We firstly collected and analyzing quantitative data obtained from food industry practitioners and, then, qualitative data gathered through semi-structured interviews with experts.FindingsThe study findings suggest that the relationship between digital transformation and resilience varies among tiers of the FSC and that digital technologies adoption affects resilience development differently across tiers. This highlights the potential cost savings of developing strategies that jointly address digital transformation and resilience development, improving performance outcomes and determining the extent to which digital technologies enhance or inhibit certain aspects of resilience in the FSC.Originality/valueThe study frames the relationship between digital technologies and resilience within the dynamic capabilities theory and suggests that digitalization can enhance resilience by enabling organizations to sense, seize, and transform strategies. We also provide insights for managers to develop strategies that simultaneously enhance digitalization and resilience, resulting in improved performance during disruptive events.

‘Quantum of information’ functionality as a measure of subjectivity beyond the capabilities of deep learning

The potential of conscious artificial intelligence (AI), with its functional systems that surpass automation and rely on elements of understanding, is a beacon of hope in the AI revolution. The shift from automation to conscious AI, once replaced with machine understanding, offers a future where AI can comprehend without needing to experience, thereby revolutionizing the field of AI. In this context, the proposed Dynamic Organicity Theory of consciousness (DOT) stands out as a promising and novel approach for building artificial consciousness that is more like the brain with physiological nonlocality and diachronicity of self-referential causal closure. However, deep learning algorithms utilize "black box" techniques such as “dirty hooks” to make the algorithms operational by discovering arbitrary functions from a trained set of dirty data rather than prioritizing models of consciousness that accurately represent intentionality as intentions-in-action. The limitations of the “black box” approach in deep learning algorithms present a significant challenge as quantum information biology, or intrinsic information, is associated with subjective physicalism and cannot be predicted with Turing computation. This paper suggests that deep learning algorithms effectively decode labeled datasets but not dirty data due to unlearnable noise, and encoding intrinsic information is beyond the capabilities of deep learning. New models based on DOT are necessary to decode intrinsic information by understanding meaning and reducing uncertainty. The process of “encoding” entails functional interactions as evolving informational holons, forming informational channels in functionality space of time consciousness. The “quantum of information” functionality is the motivity of (negentropic) action as change in functionality through thermodynamic constraints that reduce informational redundancy (also referred to as intentionality) in informational pathways. It denotes a measure of epistemic subjectivity towards machine understanding beyond the capabilities of deep learning.

Bifurcation analysis of electron-acoustic waves in electron beam-plasma with suprathermal electrons

It has investigated the properties of nonlinear electron-acoustic waves propagating in a four-component collisionless, unmagnetized plasma. The system consists of cool inertial background electrons of temperature T c , the cool inertial electron beam of temperature T b , hot inertialess suprathermal electrons modeled by a κ-distribution of temperature T h , and ions. The nonlinear modified Korteweg-de Vries-Burgers (mKdV-Burgers) equation that characterizes the electron acoustic waves in such a plasma model is derived. The wave solutions of the resultant mKdV-Burgers equation are investigated using planar dynamical system bifurcation theory. The unperturbed hot, cool, and beam electron densities and the superthermal electron parameter are revealed to have a considerable influence on the nonlinear electron-acoustic traveling waves and the associated electric fields. The system evolves also monotonic shock waves when the dissipation term dominates over the dispersion term. The current model might be useful for understanding the generation of nonlinear electron-acoustic waves in a variety of astrophysical plasma settings, including the Earth's magnetosphere.

A Mechanistic Study of Enterprise Digital Intelligence Transformation, Innovation Resilience, and Firm Performance

Enterprise Digital Intelligence Transformation is based on the Digital Conversion of information and process service upgrading, further touching the enterprise’s core business, with the goal of building a new business model of Digital Intelligence Transformation at a higher level. Based on dynamic capability theory, this paper conducts an in-depth study on the mechanism of enterprise Digital Intelligence Transformation and firm performance. This paper selects manufacturing companies listed in China’s Shanghai and Shenzhen A-shares from 2013 to 2022 as the research sample, and analyzes and tests the sample data using empirical research methods in order to explore the actual impact of Digital Intelligence Transformation on firm performance, including the specific pathways of action and moderating effects. This study helps enterprises to positively face the megatrend of Digital Intelligence Transformation and upgrading and the challenges it brings, and to grasp the new opportunities in the digital era. This study finds that enterprises carry out digital empowerment transformation and development strategies, and implement information Digital Conversion, service upgrading, and Digital Intelligence Transformation to promote firm performance to different degrees. Enterprise innovation resilience has a mechanism effect between information digitalization conversion enterprise performance and process service upgrading enterprise performance. The higher the environmental uncertainty, the greater the positive contribution of information digitalization to firm performance. Digital Conversion is the base and service upgrading is the process. The current sample enterprises have limited years of data collection, and most of them have only carried out the strategic implementation of Digital Conversion or servitization, and have not reached the high-level stage of digital and intellectual transformation. Therefore, it is found that enterprise innovation resilience has not yet shown a significant role mechanism effect between digital–intelligent transformation and enterprise performance at present. And environmental uncertainty has not yet shown a significant moderating effect in the stage of Servitization Upgrading and digital–intelligent transformation. The marginal contributions of this paper are mainly reflected in the following: (1) This study introduces the dynamic capability theory to explore the role of Digital Intelligence Transformation (Digital Conversion + service upgrading) on enterprise performance. (2) This paper investigates the role of Digital Intelligence Transformation in influencing the performance of enterprises from the Digital Conversion and service upgrading phases, and enriches the relevant role and regulatory mechanisms. (3) This study provides new ideas and strategic suggestions on Digital Intelligence Transformation for enterprises with different factor intensities, at different stages of development, and in different regions.

Editorial Conclusion for the Special Issue “New Theory and Applications of Nonlinear Analysis, Fractional Calculus and Optimization”

Nonlinear analysis has widespread and significant applications in many areas at the core of many branches of pure and applied mathematics and modern science, including nonlinear ordinary and partial differential equations, critical point theory, functional analysis, fixed point theory, nonlinear optimization, fractional calculus, variational analysis, convex analysis, dynamical system theory, mathematical economics, data mining, signal processing, control theory, and many more [...]

Decision tree for adaptation after radical changes: linking dynamic capabilities, ambidexterity, and strategic alliances

AbstractWe developed a decision tree that integrates relevant organizational adaptation theories to respond to radical changes. The understanding of organizational adaptation often requires a combination of multiple theoretical lenses, especially considering today’s radical changes in technologies, markets, and regulations. However, the research streams on adaptation and change are often disconnected and we lack a unifying adaptation framework that might reveal the synergistic contribution of each theoretical perspective to the problem. To fill this important lacuna, we integrate four relevant scholarly perspectives on the topic: dynamic capabilities, ambidexterity, vertical alliances, and horizontal strategic alliances. Our main contribution is an integrative decision tree that unveils when and why each perspective is most appropriate to respond to radical changes. Our research also unpacks dynamic capabilities theory by suggesting when ambidexterity, vertical, and horizontal alliances are appropriate to integrate the upper-level theory of dynamic capabilities, and how they can overcome some of its limitations. The paper also clarifies that, in order to adapt ambidextrously after radical changes destroying core and/or complementary assets, companies need specific alliance strategies.

EEG entropy insights in the context of physiological aging and Alzheimer's and Parkinson's diseases: a comprehensive review.

In recent decades, entropy measures have gained prominence in neuroscience due to the nonlinear behaviour exhibited by neural systems. This rationale justifies the application of methods from the theory of nonlinear dynamics to cerebral activity, aiming to detect and quantify its variability more effectively. In the context of electroencephalogram (EEG) signals, entropy analysis offers valuable insights into the complexity and irregularity of electromagnetic brain activity. By moving beyond linear analyses, entropy measures provide a deeper understanding of neural dynamics, particularly pertinent in elucidating the mechanisms underlying brain aging and various acute/chronic-progressive neurological disorders. Indeed, various pathologies can disrupt nonlinear structuring in neural activity, which may remain undetected by linear methods such as power spectral analysis. Consequently, the utilization of nonlinear tools, including entropy analysis, becomes crucial for capturing these alterations. To establish the relevance of entropy analysis and its potential to discern between physiological and pathological conditions, this review discusses its diverse applications in studying healthy brain aging and neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). Various entropy parameters, such as approximate entropy (ApEn), sample entropy (SampEn), multiscale entropy (MSE), and permutation entropy (PermEn), are analysed within this context. By quantifying the complexity and irregularity of EEG signals, entropy analysis may serve as a valuable biomarker for early diagnosis, treatment monitoring, and disease management. Such insights offer clinicians crucial information for devising personalized treatment and rehabilitation plans tailored to individual patients.

Theory for and from agent-based modelling: Insights from a virtual special issue and a vision

The Virtual Special Issue "Agents for Theory" discusses theory development using agent-based models (ABMs). The six contributions focus on how the word "theory" is used in the ABM literature, how reviews of ABMs should be conducted to gain general insights, how even the conceptualisation of ABMs can help to transform heuristic theories into scientific ones, how the context-dependent choice of decision models can be better justified, how reusable building blocks (RBBs) of ABMs could support theory development, and how a modular framework of RBBs can be used to identify general solutions. Overall, theories of decision making that go into ABMs and theories of system dynamics that come out of ABMs are interrelated, so the micro-macro perspective and the attempt to identify and reproduce patterns at both levels simultaneously is a way forward. Theory development requires clearer communication using a common language, reference to patterns, and more detailed model analysis and testing.

Modeling the dissemination of privacy information in online social networks

AbstractDriven by the rapid development of information technology, online social networks (OSNs) have experienced a fast development in recent years, allowing increasingly more people to share and spread information over OSNs. The rapid rise of OSN platforms such as Facebook and Twitter is sufficient evidence of such development. As one type of information, privacy information can also be created and disseminated over an OSN, posing a severe threat to individual privacy. This article attempts to construct a model for disseminating privacy information in OSNs and to analyze the model by simulating the dissemination process of privacy information in OSNs. First, we establish network models that exhibit the main characteristics of OSNs. Second, by considering the factors related to social relationships, especially intimacy between users and the attention of users to the privacy subject, we derive the parameters for privacy information dissemination models in OSNs. Third, based on the theory of information dissemination dynamics, we construct a model for information dissemination that conforms to the properties of privacy information. We also present some experimental results based on the constructed model and analyze the characteristics of privacy information dissemination. Fourth, we study and verify the various properties of the model through a set of experiments. The proposed model provides the opportunity to better understand the dynamics of privacy information dissemination in OSNs and the effect of user behavior on dissemination.

Employees’ facilitative allowances on the performance of commercial state corporations in Kenya

This study examined the effect of employees’ facilitative allowances on the performance of commercial state corporations in Kenya. Despite their mandate, many commercial state corporations have consistently underperformed, raising concerns about their continued existence. Scholarly research on whether employees’ facilitative allowances structures and their implementation affect the performance of commercial state corporations in Kenya is lacking. The study draws on theories such as Resource-based theory, Principal Agency Theory, Dynamic capability theory, and Stakeholder Theory. A survey research design was employed, targeting 612 managers from 68 commercial state corporations in Kenya. The sample size of 242 managers was determined using the Yamane sampling formula. The research instrument demonstrated high reliability and validity. Inferential and descriptive statistical analyses were performed on the data collected, including multiple regression models and hierarchical regression for moderation analysis. The results revealed that employees’ facilitative allowances significantly and positively influenced the performance of commercial state corporations. These findings emphasise the importance of employee facilitative allowances in enhancing the performance of commercial state corporations. Recommendations include prioritising facilitative allowances and the implementation of remuneration policy guidelines for improved performance. Overall, this research offers significant insights into the influence of employees’ facilitative allowances on commercial state corporations’ performance in Kenya.

Digital platforms and SMEs’ performance: the moderating effect of intellectual capital and environmental dynamism

PurposeThis research aims to shed light on the linkage between digital platforms and small and medium-sized enterprises (SMEs) performance and consider the moderating effect of intellectual capital and environmental dynamism.Design/methodology/approachThis study applies a quantitative approach using a sample of primary data from 508 managers and directors of Vietnamese SMEs, using structural equation modeling (SEM).FindingsThe utilization of digital platforms by managers and directors has a positive impact on enhancing intellectual capital. However, under the influence of external environment changes, this trend may shift towards a negative direction. The ability to utilize digital platforms, whether directly or through information communication, positively affects the performance of businesses. Research has shown that the positive promotion of digital platform capability for intellectual capital factors such as human capital, organizational capital, and relational capital decreases when the external environment changes in the context of uncertain globalization.Originality/valueThis research focuses on SMEs operating in the technology and e-commerce sectors and it evidences that digital platforms are an effective baseline driver for promoting high-performing SMEs. By examining the connection between digital platform’s capability and IC and the significance of intellectual capital for SMEs’ performance, this study adds to the body of literature already available on the destructive regulatory potential of environmental dynamism. This study broadens the dynamic capabilities theory’s outcome audience and adds a new dimension to the impact of the digital platform’s capability (resource utilization) on the performance of SMEs.

Social Media for Conflict Escalation and De –Escalation: Two Sides of a Coin

Communication may be said to be "the conveying or shifting of information by speaking, writing or using some of the other media" (Oxford, 2021). Without communication, there will not be conflict. Conflict is a state when units of intercourse agents are in dissension. When two agreeing parties’ dissent, the conflict has happened. The term conflict is relative as its usage spans across different segments, sectors, institutions and areas of life. Conflict escalation refers to the spreading of minor disagreement between parties. Conflict de-escalation refers to the process of reducing the tension of any conflict, especially by not allowing it to be more destructive or going beyond the level it is. Social media is also part of the media type that is majorly centered on technological advancement. Examples of social media we have include Facebook, Twitter, Instagram, google chat room, Eskimi, telegram, WhatsApp, Part of the profitable components of social media is that. A varied group of people use social media to formulate trouble. They use the medium to starts conflict and also use it to escalate it. The research procedure embraced was exploratory research design. Secondary reference of data was used. However, the study examines Glasl's conflict escalation model to properly understands how minor disagreement escalate to large scale conflict. This paper base its theoretical argument on the theory called “The Role of Resource Mobilisation Theory in Social Movement. Another theory to look at is the C - Escalation and D - Escalation A theory of the time dynamics of conflict by Randall Collins. Authority to fashion a bill directing social media usage. The paper concluded that every authority to fashion a bill directing social media usage.

Enhanced Methods for Evaluating Water-inrush Risk from Underlying Aquifers: Incorporating Dynamic Weight Theory and Uncertainty Analysis Model

Enhanced Methods for Evaluating Water-inrush Risk from Underlying Aquifers: Incorporating Dynamic Weight Theory and Uncertainty Analysis Model

Optimal parameter estimation for uncertain structural systems under unknown random excitations

An optimal parameter estimation method for uncertain structural systems under unknown random excitations is proposed, which combines the Bayesian inference and stochastic dynamics using geometrically averaged likelihood and optimal response estimation. The general description of optimal parameter estimation problems for uncertain dynamic systems under only stochastic responses measured is presented. The posterior probability density conditional on measured responses is expressed by the likelihood function conditional on system parameters based on Bayes’ theorem. For finite time processes, the parameter estimation problem as the probability integral of conditional means is converted into the optimization problem expressed as maximizing the posterior probability density. A geometrically averaged likelihood function is defined and used for calculating the logarithmic posterior probability density. This estimation can avoid the numerical singularity of the likelihood function and reduce the effects of incomplete posterior probability density and inaccurate prior statistics of unknown random excitations, and then it will be more reasonable and effective. Furthermore, the differential equations for system response means and covariances are derived and solved based on stochastic dynamics theory. The means and covariances conditional on responses at the present instant are expressed by the previous statistics based on optimal response estimation. By combining two results, the analytical expressions of the averaged likelihood function and logarithmic posterior probability density are obtained which will be more reliable and accurate. The proposed optimal estimation method is verified by numerical results for a five-storey frame structure under base random excitation. The estimated results are not affected by the prior statistics errors of random excitation as a factor. For noisy observation, the Kalman filtering is incorporated in the estimation method and hence the estimation is more accurate and robust even for low signal noise ratios. The optimal estimation method has the potential for application to general uncertain systems.