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Product service system (PSS) is an effective approach to achieve win–win situation between service providers and consumers, and the design of PSS is the first step of its application. However, on the one hand, PSS is relatively an abstract concept, and what exactly should be considered when designing a PSS still require further exploration; on the other hand, the fast development of information and web technologies bring both opportunities and challenges for PSS design. For example, how to efficiently design the smart & connected products that support remote monitoring and control of service operation, how to build the dynamic service activity flow model that can be intuitively and visually read by human engineers and also can be conveniently deployed on computers, and how to realise edge–cloud collaboration between service providers and consumers. In this regard, a service requirement-oriented four-step generic PSS design method is established, including service mode selection and structured service order generation → smart & connected service product configuration → dynamic event-state knowledge graph-based service activity flow and service resource network configuration → industrial internet-based edge–cloud collaborative service delivering. Finally, a real design case of carbon block grinding and polishing PSS is used for verification. ABBREVIATIONS: AS: assembly service; C: controlling targets or objectives; I: input; M: enabling methods or mechanisms; MRO: maintenance, repair, and operation; MS: maintenance service; O: output; OEE: overall equipment effectiveness; PSS: product service system; PV: processing volume; RxEy-Sz: the relation from Event y to the State z of Service activity x; RxSz-Ey: the relation from the State z of Service activity x to Event y; StateAiCurrent: the current state of Service activity i; StateAiFuturek: the kth possible future state of Service activity i; StateAiHistoryj: the jth historical state of service activity i; StateEy: the state of Event y; Tq: the qth time point in the time line. [ABSTRACT FROM AUTHOR]

Trends over the past two decades indicate that much of the performance gains of commercial optimization solvers is due to improvements in x86 hardware. To continue making progress, it is critical to consider alternative/specialized massively parallel computing architectures. In this work, we detail the development of an open-source source code transformation approach built using Symbolics.jl to construct McCormick-based relaxations of functions that enables their effective parallelized evaluation. We then apply this approach in a novel parallelized branch-and-bound routine that offloads lower- and upper-bounding problems to a GPU. The effectiveness of this new approach is demonstrated on three nonconvex problems of interest, where it yields convergence time improvements of 22–118x compared to an equivalent serial CPU implementation and in two cases outperforms vanilla branch-and-bound versions of existing state-of-the-art solvers that use tighter bounding techniques. This work exemplifies how deterministic global optimizers using alternative hardware architectures can compete with—or eventually outclass—even the most powerful serial CPU implementations, and to the best of the authors' knowledge, represents the first successful demonstration of deterministic global optimization using a GPU. [ABSTRACT FROM AUTHOR]

This scoping review aimed to synthesise methodological steps taken by researchers in the development of formal, dynamical systems models of health psychology theories. We searched MEDLINE, PsycINFO, the ACM Digital Library and IEEE Xplore in July 2023. We included studies of any design providing that they reported on the development or refinement of a formal, dynamical systems model unfolding at the within-person level, with no restrictions on population or setting. A narrative synthesis with frequency analyses was conducted. A total of 17 modelling projects reported across 29 studies were included. Formal modelling efforts have largely been concentrated to a small number of interdisciplinary teams in the United States (79.3%). The models aimed to better understand dynamic processes (69.0%) or inform the development of adaptive interventions (31.0%). Models typically aimed to formalise the Social Cognitive Theory (31.0%) or the Self-Regulation Theory (17.2%) and varied in complexity (range: 3–30 model components). Only 3.4% of studies reported involving stakeholders in the modelling process and 10.3% drew on Open Science practices. We conclude by proposing an initial set of expert-derived ‘best practice’ recommendations. Formal, dynamical systems modelling is poised to help health psychologists develop and refine theories, ultimately leading to more potent interventions. [ABSTRACT FROM AUTHOR]

Many PID (Proportional plus Integral plus Derivative) controller tuning methods are proposed in the control literature based on different closed-loop specifications. Also, tuning techniques, based on the maximum sensitivity specification, have been proposed in the literature. In this paper, a novel PID controller design method, based on maximum sensitivity, has been proposed. In this work, the PID controller is viewed as a gain and dynamic part and tuned separately. The PID controller dynamic part is tuned using one of the existing popular tuning methods. The tuned dynamic part is cascaded with the process. After that, the PID controller gain is tuned for the maximum sensitivity specification. The maximum sensitivity versus controller gain graph can be generated. The user can choose the controller gain for the desired maximum sensitivity specification. The popular Ziegler & Nichols and IMC (Internal Model Control) methods tune the dynamic part of the system in this work. These proposed techniques can achieve the desired maximum sensitivity by tuning the controller gain in the subsequent stage. Many illustrative instances are considered to display the applicability and the proposed technique’s simplicity. [ABSTRACT FROM AUTHOR]

AbstractOver the course of his career, Reuben Baron challenged traditional psychological perspectives in his endeavor to study the rich phenomena that comprise our lives. He pioneered a connection between ecological and social psychology through his application of a dynamical systems approach to the social world. As a result, social psychologists were provided with an alternative framework that accounted for more nuance in exchanges among individuals and groups. In this article, we revisit Baron’s proposition that interdependencies such as exchange and communal relationships overlay the local and global dynamics of social development. We highlight two special topics of burgeoning interest within intergroup relations research that we propose may benefit from a more comprehensive integration of the dynamical systems implications for exchange and development. Specifically, we demonstrate how insights from the dynamical systems approach may stand to further enrich research and theory on intergroup friendships (i.e. close relationships between individuals who hold different salient social identities) and prejudice confrontations (i.e. behavioral responses that communicate displeasure with an expression of prejudice). In doing so, we provide a framework for how further work may explicitly draw from dynamical systems perspectives to better understand real-world processes that shape intergroup relations. [ABSTRACT FROM AUTHOR]

The consolidation of Building Information Modelling (BIM) on construction sites and the preparation of the Internet-of-Things (IoT) in urban city planning are on-going processes. Therefore, the operation of modern total stations in dynamic urban scenarios becomes inevitable and often reveals the limitations of state-of-the-art approaches. This paper discusses augmentation strategies for the automatic operation of total stations. Additional internal sensor information and external facility information can be used to increase the resilience of the systems and enable them to adapt to changing circumstances. This is demonstrated by the examples of a changing prism orientation due to vandalism, local refraction effects due to air-conditioning and dynamic obstructions due to traffic. [ABSTRACT FROM AUTHOR]

This paper is devoted to studying the topological entropy of shrinking target problem in nonautonomous dynamical systems (NDSs). After providing the shrinking target problem of the topological version in NDSs, we obtain a general formula for computing the topological entropy of it. More precisely, we show that the entropy distribution principle still holds in NDSs and apply it to estimate the lower bound of the formula. In addition to the specification property, the concept of control non-decreasing property about the Bowen metric proposed by us is taken as a supplementary condition. Furthermore, we get the connection about the topological entropy between the shrinking target problem and the whole system. This extends the result of Ma et al. [Discrete Contin. Dyn. Syst. 39(5) (2019), pp. 2455–2471], corresponding to the case when the maps are the same as the more general case of different maps. [ABSTRACT FROM AUTHOR]

In this work we provide detailed estimates of maximal principal angles between subspaces and we analyse their smoothness for smoothly varying subspaces. This leads to a new definition of angular values for linear dynamical systems in continuous time. We derive some of their properties complementary to the theory of angular values developed in Beyn, et al. [Angular values of nonautonomous and random linear dynamical systems: Part I – fundamentals, SIAM J. Appl. Dyn. Syst. 21(2) (2022), pp. 1245–1286; Angular values of nonautonomous linear dynamical systems: Part II – reduction theory and algorithm, SIAM J. Appl. Dyn. Syst. 22(1) (2023), pp. 162–198] for discrete time systems. The estimates are further employed to establish upper semicontinuity of angular values for some parametric model examples of discrete and continuous type. [ABSTRACT FROM AUTHOR]

One of the fundamental results of ergodic optimization asserts that for any dynamical system on a compact metric space with the specification property and for a generic continuous function f every invariant probability measure that maximizes the space average of f must have zero entropy. We establish the analogical result in the context of constrained ergodic optimization, which is introduced by [Garibaldi and Lopes, Functions for relative maximization, Dyn. Syst. 22(4) (2007), pp. 511-528]. [ABSTRACT FROM AUTHOR]

Repulsion systems under the discrete dynamical systems perspective are considered. The goal is to study the nonlinear dynamics of an arrangement of individual or cells under various types of repulsion laws. Repulsion is a natural mechanism, so we consider the following laws: global, open, cyclic and bounded repulsion. A first scenario under consideration is when particles are freely located on an Euclidean space and the second scenario where they are restricted to remain in a bounded set. We consider those two scenarios under the previous types of repulsion. The analysis culminates in a unification of two mechanisms: attraction and repulsion via a specific social behaviour problem. [ABSTRACT FROM AUTHOR]

Digital twin represents the core technology to realize the dynamic monitoring of complex industrial systems. However, the human body, as the most complex system in the physical world, digital twin is rarely applied in it. In this study, we successfully demonstrated a digital twin in the human biomedical application by proposing a dynamic monitoring system of the upper limb force. In this system, the real upper limb drives the motion of the virtual one in real-time and dynamically updates the force. Meanwhile, the virtual upper limb feeds back the monitoring-results of the force to the controller of the real upper limb via immersive virtual reality interaction. Experimental results of the typical motions of the upper limb revealed that the proposed system functioned interactively in real-time in a non-invasive manner, while ensuring the accurate solving of the muscle force. In conclusion, our digital twin-driven system is of great importance for rehabilitation medicine, biomechanical scientific research and physical training, promoting the application of the digital twin in the human biomedical field. [ABSTRACT FROM AUTHOR]

We will denote by $ \mathcal {M} $ M the space of Borel probabilities on the symbolic space $ \Omega =\{1,2\cdots,m\}^\mathbb {N} $ Ω={1,2⋯,m}N. $ \mathcal {M} $ M is equipped Monge–Kantorovich metric. We consider here the push-forward map $ \mathfrak {T}:\mathcal {M} \to \mathcal {M} $ T:M→M as a dynamical system. The space of Borel probabilities on $ \mathcal {M} $ M is denoted by $ \mathfrak {M} $ M. Given a continuous function $ A: \mathcal {M}\to \mathbb {R} $ A:M→R, an a priori probability $ \Pi _0 $ Π0 on $ \mathcal {M} $ M, and a certain convolution operation acting on pairs of probabilities on $ \mathcal {M} $ M, we define an associated Level-2 IFS Ruelle operator. We show the existence of an eigenfunction and an eigenprobability $ \hat {\Pi }\in \mathfrak {M} $ Π^∈M for such an operator. Under a normalization condition for A, we show the existence of some $ \mathfrak {T} $ T-invariant probabilities $ \hat {\Pi }\in \mathfrak {M}. $ Π^∈M. We are able to define the variational entropy of such $ \hat {\Pi } $ Π^ and a related maximization pressure problem associated to A. In some particular examples, we show how to get eigenprobabilities solutions on $ \mathfrak {M} $ M for the Level-2 Thermodynamic Formalism problem from eigenprobabilities on $ \mathcal {M} $ M for the classical (Level-1) Thermodynamic Formalism; this shows that our approach is a natural generalization of the classic case. [ABSTRACT FROM AUTHOR]

AbstractObjectiveMethods and MeasuresResultsConclusionsAssessing the progression of COVID stress syndrome (CSS) and understanding how cognitive and emotional factors play a role in the dynamic system is critical for prevention and intervention during the COVID-19 pandemic. We investigated the dynamic relationship between self-reported COVID stress syndrome, cognitive factors, and emotional factors through time-series network analysis.Participants were 188 university students involved in an experience sampling method study that lasted 14 days, three times a day, during the COVID-19 pandemic period following a shift in pandemic prevention and control policy.CSS symptoms are usually present simultaneously, and xenophobia is the most central node of the network. There is a complex mutual predictive relationship between CSS symptoms, in which traumatic stress symptoms are crucial in developing and maintaining the CSS symptom network. Negative affect was associated with CSS symptoms at the same time, and subjective health cognition was a significant predictor of CSS symptoms the next time.Traumatic stress symptoms are essential nodes in the CSS symptom network, and negative emotions and subjective health influence the occurrence and development of CSS symptoms. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive cooperative formation controller is developed to force a swarm of nonholonomic mobile robots with limited sensing ranges to move along the desired reference trajectory in a predetermined formation, while maintaining communication connectivity among the initial user-specified connected robots and guaranteeing no collision between the robots. Both kinematic models and dynamic systems with parametric uncertainties are discussed. The presence of parametric uncertainties is handled by adaptive control technique. A novel artificial potential function, which is based on a 4 times differential pseudo bump function, is constructed to achieve collision avoidance and connectivity maintenance. The control design is based on a fusion of potential function, adaptive backstepping technique, and Lyapunov synthesis. The cooperative formation controller is proven to be stable and can guarantee that there is no collision between any robots and the initial connectivity of the communication network can be always maintained. The proposed formation control approach is decentralized in the sense that the control action on each robot depends only on information from its neighbours and the desired trajectory of the group. Comparative simulation and experiment studies are performed to show the effectiveness of the proposed formation controller. [ABSTRACT FROM AUTHOR]

This work examines how system mapping, an established exploratory and analytic technique grounded in complex dynamic systems theory, can operate as a heuristic to increase learners' language awareness (LA) and develop their L2 writing proficiency. Accordingly, this study addresses repeated calls in the instructed SLA literature for effective research methods that directly serve learners at the point of enquiry. That is, although related research often foregrounds learners and pedagogy rather than theoretical abstraction, questions remain about how participants benefit at the time data are collected. To explore this concern, this work engaged system mapping through a LA pedagogy and followed two intact university classes (one using system mapping, and one not: N = 30) over one semester. Comparative quantitative and qualitative analyses of learners' narrative reflections and academic essay writing highlighted that system mapping facilitates the raising of -learners' LA in service of developing their writing. This work demonstrates how system mapping capitalizes on learning theories that support image-schematic interventions and underscores how system mapping engages with and advances LA pedagogy in service of researchers, instructors, and students alike. PLAIN LANGUAGE SUMMARY: Studies on second language (L2) learning often focus on theory or fine-tuning teaching practice. However, the research tools employed (e.g. classroom observations or fill-in-the-blank tasks) sometimes offer little benefit for student participants. Accordingly, researchers have repeatedly called for new exploratory techniques that help students improve their L2 while they are being investigated. To address this concern, the present study explores the potential of system mapping—a research tool typically reserved for investigating how L2 learning unfolds—as a teaching instrument. This work examines the following questions: Can system mapping increase learners' awareness of the different ways language works as a communicative tool? If so, will increasing learners' awareness result in students becoming stronger writers? To answer these questions, this study followed two university classes for one semester (one that used system mapping as a teaching tool and one that did not). To explore differences between the two groups, writing assignments from both classes were collected in the first and last week of the semester, and language awareness measures were collected three times during the term. The dataset was compared across the two groups using statistical and non-statistical analyses. The findings show that system mapping helps students better understand how language works, and that such insights translate positively onto students' writing. Collectively, these findings demonstrate that system mapping can (1) raise students' language awareness in service of L2 writing and (2) act as an effective tool for learners, instructors, and researchers alike. [ABSTRACT FROM AUTHOR]

The effect of the hydraulic anti-kink system on the longitudinal-yaw stability and small radius curve passing safety of the four-module single-type tram is studied. Firstly, the dynamics model of the anti-kink system is established based on the working principle of the anti-kink system, and the dynamic response of the system is analysed. Secondly, the influence of the anti-kink system on the longitudinal-yaw stability is analysed based on the longitudinal-yaw dynamics model of the four-module single-type tram. Finally, a virtual prototype of the anti-kink system and the four-module single-type low-floor tram with independent rotating wheels is established to test the longitudinal-yaw stability of the vehicle, and the curve passing safety. The results show that: the double-hinged device increases the longitudinal-yaw instability of the vehicle and is more likely to produce jackknifing phenomenon, so the stiffness of the anti-kink system should be set as much as possible to prevent the jackknifing phenomenon and ensure the safe operation of the train. By reducing the stiffness of the anti-kink system properly, the wheel-rail force during curve passing can be reduced, and thus improving vehicle safety. [ABSTRACT FROM AUTHOR]

Bifurcations of nonlinear and supernonlinear ion-acoustic waves (IAWs) are studied in an electron-ion plasmas with generalized (r, q)-distributed electrons. The IAWs are examined under the Zakharov–Kuznetsov (ZK) and modified ZK equations using the reductive perturbation technique. Transforming both the ZK and mZK equations into their corresponding dynamical systems, all possible phase spaces and potential energy functions are analyzed. The nonlinear periodic and solitary wave solutions are obtained under the ZK and mZK equations. A newly discovered supernonlinear wave, in particular, supernonlinear periodic wave under the modified ZK equation in electron-ion magnetized plasma with (r, q)-distributed electrons is reported for the first time in the literature. Nonlinear and supernonlinear wave solutions are shown under the influence of physical parameters. The proposed study contributes to new wave motions in slow solar wind streams and astrophysical plasmas. [ABSTRACT FROM AUTHOR]

Practical combustors in furnaces, industrial heaters, and gas turbine engines face a sudden loss of flame due to rich blowout (RBO) at an extremely rich fuel-air mixture or lean blowout (LBO) at an extremely lean fuel-air mixture. Thus, the stability limits of the combustion regime are governed by RBO and LBO. In the present study, we focus on the dynamics of swirl-stabilized premixed combustion near lower and higher flammability limits, where the possibilities of LBO and RBO, respectively, are observed. Near RBO and LBO, we employ metrics from statistics and dynamical systems theory to characterize the transition in flame dynamics. We observe that the range of frequencies obtained using Fourier Transform near RBO and LBO is alike. The emergence of dominantly low-frequency oscillation near those blowout limits is investigated using Hilbert Transform. The mean frequency of the combustion system gradually reduces near both blowout limits due to behavioral oscillations prominently observed. The scaling property of flame oscillation is examined using the Hurst exponent, and we observe a decreasing trend of the parameter as combustion approaches both LBO and RBO. Therefore, for the gradual reduction of the Hurst exponent near both flammability limits, we can use the parameter as a precursor for both RBO and LBO. [ABSTRACT FROM AUTHOR]

The aim of the present study was to compare the coordination patterns and levels of coordination variability of healthy and injured runners with iliotibial band syndrome (ITBS). Sixty runners divided into four groups (15 healthy males, 15 healthy females, 15 males with ITBS and 15 females with ITBS) ran at a steady and freely chosen pace on an over-ground track, and their coordination patterns of the lower limbs were calculated during 10 running stances using the vector coding technique. Both male and female runners with ITBS showed a greater dominance of the pelvis segment and the anti—phase patterns in the frontal plane thigh—pelvis coupling (p = 0.001, η2 = 0.36). In addition, injured female runners showed a greater hip adduction dominance, whereas injured males presented a greater anti—phase pattern in the transverse plane—frontal plane hip coupling (p = 0.003, η2 = 0.08). The levels of coordination variability during running stance did not change between ITBS injured and healthy runners in any of the couplings. Currently injured runners with ITBS appeared to present altered coordination patterns on the hip couplings that were partly dependent on gender but did not lead to changes in the coordination variability levels. [ABSTRACT FROM AUTHOR]

In this paper, we focus on studying the Mixed-Effects State-Space (MESS) models previously introduced by Liu et al. [Liu D, Lu T, Niu X-F, et al. Mixed-effects state-space models for analysis of longitudinal dynamic systems. Biometrics. 2011;67(2):476–485]. We propose an estimation method by combining the auxiliary particle learning and smoothing approach with the Expectation Maximization (EM) algorithm. First, we describe the technical details of the algorithm steps. Then, we evaluate their effectiveness and goodness of fit through a simulation study. Our method requires expressing the posterior distribution for the random effects using a sufficient statistic that can be updated recursively, thus enabling its application to various model formulations including non-Gaussian and nonlinear cases. Finally, we demonstrate the usefulness of our method and its capability to handle the missing data problem through an application to a real dataset. [ABSTRACT FROM AUTHOR]

AbstractCurrent study presents state of the art approach to risk and reliability assessment for multivariate nonlinear dynamic systems. Specifically, novel hypersurface Gaidai risks evaluation methodology has been presented for evaluating offshore structural risks. Advocated approach being particularly suitable for offshore engineering multidimensional dynamic systems, possessing large number of critical components, that have either been physically observed/measured, or numerically modeled over a representative timelapse. Advocated Gaidai hypersurface structural risks evaluation methodology is applicable for a wide range of engineering and industrial systems. This study demonstrates that given in situ environmental conditions, it is well possible to assess accurately risks of system’s failures, damages or hazards, caused by excessive structural dynamics. Multivariate dynamic systems, possessing nonlinear cross-correlations between critical system’s components often present design challenges, when utilizing classic structural risks evaluation approaches, as those are mostly only univariate or bivariate. Dynamic offshore Jacket hot spot stresses have been utilized as an example in this reliability investigation. Modeling system’s excessive dynamics is challenging because of the non-stationarity of the system and the intricacy of fluid-structural dynamic interactions, arising from in situ wave-induced loads, influencing Jacket’s structural dynamics. Nonlinearities greatly affect structural dynamics, e.g., 2nd, 3rd, higher order effects within fluid-structural interactions. Methodology presented in this work offers a straightforward, effective, yet precise means of assessing the risks of failure or hazard for multivariate, non-stationary, non-linear dynamic offshore systems. For bivariate case, verification note has been added. [ABSTRACT FROM AUTHOR]

AbstractIdentifying modal parameters for the different vibrational conditions for any structure or machine is very important for its structural health monitoring. Researchers have proposed different methodologies to determine that structure’s excitation or natural frequency. In the initial design phase, researchers have to rely on building the FE model and then analyze its natural and excitation frequencies. However, for the complex structure, it is difficult to handle a huge dataset of the vibrational information of the mesh for multi-frequency excitations and it becomes computationally expensive to analyze the system’s performance. This work presents the data-driven technique called Dynamic Mode Decomposition (DMD) which addresses this problem by discovering the system’s dynamics using system’s high-dimensional spatiotemporal data. The present work studies the FE vibration of fixed-fixed beams with single and multi-frequency harmonic forcing functions with and without noise for real-time scenarios. Here, DMD is applied to the sequential spatiotemporal data of displacement of the vibrating beams, and dominant frequencies and corresponding mode shapes are identified to predict the actual time dynamics of the system under different conditions in simulation and experimental conditions. This study also involves the failure of the DMD to capture the periodic oscillation (standing wave) in the beam and proposes the application of the Hankel matrix (time-delay coordinate) to capture the actual dynamical parameters of the system. The resulting predicted frequencies match the actual excitation frequencies, and the accuracy is improved with a number of stackings of the given time series data through the Hankel matrix at different rank truncations. [ABSTRACT FROM AUTHOR]

Dynamic systems theory and complexity theory (DST/CT) is a framework explaining how complex systems change and adapt over time. In psychotherapy, DST/CT can be used to understand how a person's mental and emotional state changes during therapy incorporating higher levels of complexity. This study aimed to systematically review the variability of DST/CT methods applied in psychotherapy research. A primary studies search was conducted in the EBSCO and Web of Knowledge databases, extracting information about the analyzed DST/CT phenomena, employed mathematical methods to investigate these phenomena, descriptions of specified dynamic models, psychotherapy phenomena, and other information regarding studies with empirical data (e.g., measurement granularity). After screening 38,216 abstracts and 4,194 full texts, N = 41 studies published from 1990 to 2021 were identified. The employed methods typically included measures of dynamic complexity or chaoticity. Computational and simulation studies most often employed first-order ordinary differential equations and typically focused on describing the time evolution of client-therapist dyadic influences. Eligible studies with empirical data were usually based on case studies and focused on data with high time intensity of within-session dynamics. This review provides a descriptive synthesis of the current state of the proliferation of DST/CT methods in the psychotherapy research field. [ABSTRACT FROM AUTHOR]

We re-consider Schelling's (1971) bounded neighborhood model as put into the form of a dynamical system by Haw and Hogan (2018). The aim is to determine how tolerance can prevent (or lead to) segregation. In the case of a single neighborhood, we explain the occurring bifurcation set, thereby correcting a scaling error. In the case of two neighborhoods, we correct a major error and derive a dynamical system that does satisfy the modeling assumptions made by Haw and Hogan (2020), staying as close as possible to their construction. We find that stable integration is then only possible if the populations in the two neighborhoods have the option to be in neither neighborhood. In the absence of direct movement between the neighborhoods, the problem is furthermore equivalent to independent single neighborhood problems. [ABSTRACT FROM AUTHOR]

This article proposes a novel hybrid technique of order abatement for large-scale models that combines the Mihailov stability method (MSM) and the stability equation method (SEM). In this approach, the denominator coefficients of the higher-order system (HOS) are estimated using the MSM, while the numerator coefficients are computed using the SEM. The suggested approach is based on the MSM, which guarantees the stability of the estimated model if the actual model is stable. The MSM also makes sure that important factors of the original plant, such as dominant poles and stability, are retained in the reduced order system (ROS). The suggested approach is compared to several current conventional reduction methods using error indicators, and the smallest performance error indices values reflect the supremacy of the method. The transfer function (TF) of the ROS is then used to design controllers by employing the moment matching technique. When the controller designed with the approximated model is applied to the real HOS, it indicates that the response of the closed-loop system of the real model entirely overlaps with the response of the reference plant. To further demonstrate the efficiency of the proposed schemes, time-domain specifications are produced and time responses are plotted. [ABSTRACT FROM AUTHOR]

Subsistence farmers in elephant rangelands suffer food insecurity, economic losses and emotional stress from crop damage by elephants, resulting in reduced local support toward elephant conservation. To foster human-elephant co-existence in a dynamic social-ecological system, we explored the validity of Classification Tree (CT) analysis application to identify human-elephant hotspots in an effort to target approaches to reduce human-elephant conflicts. The CT analysis revealed that the most important factors affecting occurrence of crop damage were crop types, field sizes and distance to nearest road and river. From CT generated thresholds, we propose establishment of multi-criteria-based risk zones, as an alternative approach, to quickly identify and prioritize future human-elephant conflict (HEC) hotspots for improved agrarian livelihood and elephant conservation outcomes. We also explained the limitations of CT models. This study contributes to the existing theory and body of work on elephant habitat use at the human-elephant interface. [ABSTRACT FROM AUTHOR]

Autonomous sailing is seen as one of the possible solutions to cope with the decrease in qualified personnel and to minimise the risk to humans and ships in challenging conditions. Autonomy is not limited to sailing a vessel safely through the seas, but it also includes docking the vessel. A feeder vessel distributes cargo and spends a relative large percentage of its time on (un)docking. Automating this part of the operation is expected to help save on resources. The objective of this work is to automatically approach a dock with an underactuated vessel. It comprises of both the design of a time-dependent trajectory, and a controller that can track this trajectory. The solution is tailored for our 71 m long feeder vessel designed for the eu-h2020 Moses project. The focus is on approaching the dock from cruising speed until the speed of the vessel is near-zero. The result of the study is a high-fidelity time simulation that shows the behaviour of the vessel in combination with the control system when it approaches a dock. The simulations show that the ship can approach the dock with coupled azimuthing thrusters to a speed when the bow thrusters become effective. The vessel then becomes fully actuated and can safely dock with its dynamical positioning system. [ABSTRACT FROM AUTHOR]

The water-lubricated hydrodynamic spiral grooved bearings have been utilized to support the high-speed motorized spindle. However, the viscous damping effect of water is much weaker than that of the oil, so the dynamic behavior and the stability of the motorized spindle with the water-lubricated spiral grooved bearings need to be studied thoroughly. This paper established an improved rotor-bearing dynamic model for the motorized spindle by incorporating both the distributed effect of journal bearing and the tilting effect of thrust bearing into a turbulent thermohydrodynamic lubrication model. An experimental setup for the motorized spindle was developed to measure the spindle dynamic behaviors and verify the established dynamic model. The critical speeds, the transient dynamics, and the stability of the motorized spindle are studied theoretically and experimentally. The results show that the motorized spindle with the water-lubricated spiral grooved bearings can operate at high speeds with a satisfactory supporting stiffness and exhibits an excellent operational stability. [ABSTRACT FROM AUTHOR]

Objectives: The relationship between task constraints and player behaviors is of interest to coaches tasked with designing practice to optimize learning. This study aims to compare the skill involvements and cooperative team behavior of teams of youth soccer players engaged in a goal exaggeration and/or a prescriptive coach instruction condition compared to a free-play control condition. Methods: Twenty male soccer players aged 12–15 participated in small-sided games under four conditions: free-play, goal exaggeration, prescriptive coach instruction, and combination over four weeks. Using video footage, teams’ collective skill involvements (shot, pass, dribble) and passing network characteristics (closeness, density, and betweenness) were measured for each game. Results: A Friedmans rank test identified that playing conditions resulted in significant differences in attempted dribbles (p < .001), goals scored (p < .001), network density (p = .001), closeness (p < .001) and betweenness (p = .002). Teams attempted to dribble the most in the free-play and goal-exaggeration conditions, and the most goals were scored in the goal-exaggeration and combination conditions. Additionally, teams exhibited more well-connected passing networks (i.e. higher density, higher closeness, and lower betweenness values) in the combination condition and higher network density in the explicit instruction condition. Conclusions: The results of this study indicate that coach instruction may be more associated with cooperative team behavior, whereas free-play or manipulating task constraints in the absence of instruction may be associated with players attempting more individual actions. [ABSTRACT FROM AUTHOR]

AbstractAccurate simulation of the cutting forces in the milling process is extremely complicated because of variations in cutting process parameters, including the change in modal characteristics of the workpiece along the machining path and the high-temperature gradient around the cutting zone, especially for the modeling of milling forces in flexible thin-walled workpieces. Therefore, proposing effective methods for prediction and control of cutting forces is highly important to ensure the high performance and stability of the cutting process as well as the quality of the machined surface. In this article, a novel method is presented for rapid prediction of cutting force signals based on the combination of the multi-variable time series analysis, the Imperialist Competitive Algorithm (ICA) and Multi-View Embedding (MVE) algorithm. A state-space model of the dynamic system is presented in order to quickly predict the instantaneous dynamic characteristics of the cutting process. The maximum error between the amplitude of experimental and predicted force signals (peak-to-peak) in stable and unstable cutting conditions is less than 8% and 17%, respectively. Therefore, it is illustrated that the presented method has remarkable computational accuracy and convergence speed for predicting the future of the cutting forces under both stable and unstable conditions. [ABSTRACT FROM AUTHOR]

The axle box bearing serves as a critical rotational component for high-speed trains. Thus, it is of great significance to obtain accurate loading conditions for axle box bearings for its reliability design. In this study, a bearing-vehicle coupled system dynamic model, consisting of an equivalent bearing model characterized by the time-varying stiffness in the bearing, a nonlinear high-speed train dynamic model, and a slab track model, is developed. The validity of the proposed coupled dynamic model is demonstrated by comparing the simulated results with those obtained in a field test and the literature, respectively. Subsequently, the influence of long- and short-wavelength irregularities on the dynamic responses of bearings is investigated using the proposed coupled model in terms of dynamic loads of the axle box bearing. The results obtained by the proposed model are further compared with those calculated using a traditional vehicle dynamic model that represents the bearing as a revolute joint, so as to illustrate the advantages of the proposed model. The results suggest that the loading responses of the bearing calculated by the two models exhibit differences, which are simultaneously related to the structural damping of the bearing and the mode frequency change of the system. [ABSTRACT FROM AUTHOR]

We study the existence and uniqueness of solutions to the inverse quasi-variational inequality problem. Motivated by the dynamical approach to solving optimization problems such as variational inequality, monotone inclusion, and inverse variational problems, we consider a dynamical system associated with the inverse quasi-variational inequality problem, and establish the existence and uniqueness of a solution to the proposed system. We prove that every trajectory of the proposed dynamical system converges to the unique solution of the inverse quasi-variational inequality problem and that the system is globally asymptotically stable at its equilibrium point. We also prove that if the function which governs the inverse quasi-variational inequality problem is strongly monotone and Lipschitz continuous, then the dynamical system is globally exponentially stable at its equilibrium point. We discretize the dynamical system and show that the sequence generated by the discretization of the system converges strongly to the unique solution of the inverse quasi-variational inequality problem under certain assumptions on the parameters involved. Finally, we provide numerical examples to support and illustrate our theoretical results. [ABSTRACT FROM AUTHOR]

In this research article, the dynamics of optical solitons in cascaded system with spatio-temporal dispersion is discussed. The Kerr medium is considered for this investigation. Two versatile integration tools have been used to extricate different traveling wave solutions. Rapid convergent approximation method has been employed to extract bright, singular and periodic solitons whereas polynomial function solutions are obtained by unified method. The constraints on the parameters for the validity of these solutions are also provided. Galilean transformation is prosecuted to construct the planer dynamical system of the said model. Runge–Kutta fourth-order technique is used to extract the non-linear periodic waves of the considered problem and consequences are depicted through different portraits. Further, by employing an extrinsic periodic force, chaotic and quasiperiodic pattern of discussed model is analyzed for different values of the parameters. While chaotic and quasiperiodic behaviors are observed for some values of parameters of considered system by keeping the force and frequency of the perturbed dynamical system fixed. Sensitive anatomy is carried out for diverse initial value problems. It is investigated that the chaotic and quasiperiodic pattern is present in the perturbed dynamical system. [ABSTRACT FROM AUTHOR]

Principal curves are natural generalizations of principal lines arising as first principal components in the Principal Component Analysis. They can be characterized—from a stochastic point of view—as so-called self-consistent curves based on the conditional expectation and—from the variational-calculus point of view—as saddle points of the expected difference of a random variable and its projection onto some curve, where the current curve acts as argument of the energy functional. Beyond that, Duchamp and Stützle (1993, 1996) showed that planar curves can be computed as solutions of a system of ordinary differential equations. The aim of this paper is to generalize this characterization of principal curves to R d with d ≥ 3. Having derived such a dynamical system, we provide several examples for principal curves related to uniform distribution on certain domains in R 3. [ABSTRACT FROM AUTHOR]

We develop the theory of kernel sections of non-autonomous dynamical systems. Under some sufficient conditions, we establish some abstract results on the asymptotically autonomous stability of kernel sections, which suggests that the time-section of a kernel section is asymptotically stable to a global attractor of the autonomous dynamical system. A lattice plate equation with nonlinear damping and non-autonomous forcing is considered as an application. It is shown that the time-section of kernel sections of the non-autonomous lattice plate equations are nonempty, uniformly compact, pullback attracting, and asymptotically stable to a global attractor of the autonomous lattice plate equations. [ABSTRACT FROM AUTHOR]

In this paper, we study some Krasnoselskii-Mann type dynamical systems in solving fixed point problems. The first one can be regarded as a continuous version of the Krasnoselskii-Mann iterations. We prove that the solution of this dynamical system converges weakly to a fixed point of the involving mapping. Next, we focus our attention on a regularized Krasnoselskii-Mann type dynamical system. Besides proving existence and uniqueness of strong global solutions, we show that the generated trajectories converge strongly to a unique solution of a variational inequality over the fixed point set. Also, we provide a convergence rate analysis for the regularized dynamical system. [ABSTRACT FROM AUTHOR]

This paper is devoted to the stochastic travelling wave solutions of a three-species competitive–cooperative system with multiplicative noise. The existence of the travelling wave solutions can be proved by constructing upper/lower-solution and stochastic dynamical systems theory. Moreover, under the more restricted assumption on the coefficients of system, and applying Feynman–Kac formula and upper/lower solution technique, the upper/lower bounds of the asymptotic wave speed can be provided. [ABSTRACT FROM AUTHOR]

Process control is widely discussed in the manufacturing process, especially in semiconductor manufacturing. Due to unavoidable disturbances in manufacturing, different process controllers are proposed to realize variation reduction. Since Reinforcement Learning (RL) has shown great advantages in learning actions from interactions with a dynamic system, we introduce RL methods for process control and propose a new controller called RL-based controller. Considering the fact that most existing run-to-run (R2R) controllers mainly rely on a linear model assumption for the process input–output relationship, we first discuss theoretical properties of RL-based controllers based on the linear model assumption. Then the performance of RL-based controllers and traditional R2R controllers (e.g., Exponentially Weighted Moving Average (EWMA), double EWMA, adaptive EWMA, and general harmonic rule controllers) are compared for linear processes. Furthermore, we find that the RL-based controllers have potential advantages to deal with other complicated nonlinear processes. The intensive numerical studies validate the advantages of the proposed RL-based controllers. [ABSTRACT FROM AUTHOR]

Let $ (X, f) $ (X , f) be a dynamical system, i.e. X is a compact metric space and f is a continuous self-map on X and let $ K(X) $ K (X) , $ M(X) $ M (X) and $ \mathbb {F}(X) $ F (X) be the sets of all non-empty compact subsets of X, Borel probability measures on X and upper semi-continuous fuzzy sets on X, respectively. Then $ K(X) $ K (X) , $ M(X) $ M (X) and $ \mathbb {F}(X) $ F (X) are metric spaces under Hausdorff metric, prohorov metric and level-wise metric, respectively. Therefore, $ (X, f) $ (X , f) naturally induces three new systems $ (K(X), \bar {f}) $ (K (X) , f ¯) , $ (M(X), \hat {f}) $ (M (X) , f ^) and $ (\mathbb {F}(X), \tilde {f}) $ (F (X) , f ~). In this article, we investigate the connection of $ (r,s) $ (r , s) -sensitivity, $ (r,s) $ (r , s) -asymptotic sensitivity, $ (r,s) $ (r , s) -Li-Yorke sensitivity and Δ-transitivity of $ (X, f) $ (X , f) and its induced systems $ (K(X),\bar {f}) $ (K (X) , f ¯) , $ (M(X),\hat {f}) $ (M (X) , f ^) and $ (\mathbb {F}(X),\tilde {f}) $ (F (X) , f ~) and we obtain some desired results. For instance, we prove that $ (K(X),\bar {f}) $ (K (X) , f ¯) is $ (r,s) $ (r , s) -sensitive ⇔ $ (\mathbb {F}^{1}(X),\widetilde {f_{g}}) $ (F 1 (X) , f g ~) is $ (r,s) $ (r , s) -sensitive for each $ g\in D_{m}(I) $ g ∈ D m (I) satisfying $ g^{-1}(1)=\{1\} $ g − 1 (1) = { 1 } ; $ (X,f) $ (X , f) is Δ-transitive ⇔ $ (K(X),\bar {f}) $ (K (X) , f ¯) is Δ-transitive ⇔ $ (M(X),\hat {f}) $ (M (X) , f ^) is Δ-transitive $ \Leftrightarrow \,(\mathbb {F}^{1}(X),\tilde {f}) $ ⇔ (F 1 (X) , f ~) is Δ-transitive. [ABSTRACT FROM AUTHOR]

Partially stable systems involve dynamical systems whose motion lie in a subspace of the state space resulting in system stability with respect to part of the system's states. In this paper, we develop partial stability theorems for nonlinear continuous-time and discrete-time dissipative feedback systems. Specifically, by invoking additional structural constraints on the forward loop and feedback loop system storage functions, we develop feedback interconnection partial stability results for dissipative nonlinear dynamical systems. Our results provide extensions of the positivity and small gain theorems for guaranteeing partial stability of feedback interconnected systems. [ABSTRACT FROM AUTHOR]

Aiming at the nonlinear vibration problem caused by the dynamic misalignment of rolling bearings in the rotating machinery, a rotor dynamic model with bearing dynamic misalignment is established, and the effects of the dynamic misalignment of single and two bearings and the phase relationship of two dynamic misalignment bearings on the rotor vibration characteristics are researched. The effects of bearing clearance, raceway curvature radius, the ball number and radial load on the nonlinear vibration response of the dynamic misalignment bearing-unbalance rotor system are further analyzed. The results show that the dynamic misalignment of the bearing can excite the vibration at twice the rotor frequency, raise the resonance speed and enhance the hardening-type nonlinearity characteristics of the rotor. The influence of dynamic misalignment under two bearings with out-of-phase on rotor resonance is greater than that of the in-phase. The stability of the system can be improved by decreasing the bearing clearance and increasing the curvature radius coefficient. The vibration caused by bearing dynamic misalignment can be reduced by selecting the bearing with more balls and appropriately increasing the bearing load. [ABSTRACT FROM AUTHOR]

We study the metric mean dimension of Φ-irregular set $ I_{\Phi }(f) $ I Φ (f) in dynamical systems with the shadowing property. In particular, we prove that for dynamical systems with the shadowing property containing a chain recurrent class Y, the values of topological entropy together with the values of lower and upper metric mean dimension of the set $ I_{\Phi }(f)\cap B(Y,\varepsilon)\cap CR(f) $ I Φ (f) ∩ B (Y , ε) ∩ CR (f) are bounded from below by the respective values for class Y. [ABSTRACT FROM AUTHOR]

In this study, control and fault detection are examined for Takagi–Sugeno (T–S) fuzzy continuous-time systems with conic-type nonlinearity. In a conic-type dynamic system, Takagi–Sugeno fuzzy models are applied. A conic-type non-linearity must lie in an n-dimensional hyper-sphere with an uncertain centre to satisfy the restrictive condition. A combined error system of estimation and control error is obtained by combining the observations and the controller. Our main goal is to design an observer and controller for fault detection that minimizes the impact of unknown inputs and faults on the system in terms of the $ H_{\infty } $ H ∞ performance. The Lyapunov function is used to construct the residual signal using an observer and a controller. Using Linear Matrix Inequalities (LMIs), we can express the performance conditions for $ H_{\infty } $ H ∞ . The scheme's effectiveness is demonstrated with numerical examples. [ABSTRACT FROM AUTHOR]

In the following article, we construct an interaction model of general language change. This contributes in particular to quantitative studies on reversible language change initiated by G. Altmann by adding explanatory character in tracing global features of general language change back to the individual interaction of speakers. Although the corresponding coupled differential equations are (presumably) non-integrable, we use methods from the theory of dynamical systems to deduce the long-term behaviour (depending on four interaction parameters) of the model for any given initial constellation of speakers. Subsequent numerical analysis of real data on language change is used to justify the relevance of the constructed model for the practicing quantitative linguist. We show how data-fitting methods can be used to determine the four interaction parameters and predict from them the long-term behaviour of the system, i.e. if complete language change or reversible language change will take place. [ABSTRACT FROM AUTHOR]

This paper proposes a user-biometric-based image encryption using chaotic dynamical systems, SHA-256 hash function, and zigzag transformation. Three chaotic systems, namely, the Henon map, logistic map, and Lorenz system, are used to apply the chaotic properties to the encryption system. The hash value of the user biometric image is used to generate the initial value of the Henon map. The initial values for the logistic map and Lorenz system are generated from the hash value of the plain image. SHA-256 hash algorithm generates the hash values of the biometric and plain images. The plain image is scrambled using the two-dimensional chaotic values generated by the Henon map first. Next, the first scrambled image's pixels are XORed with the one-dimensional chaotic values generated from the logistic map and produce the second scrambled image. Finally, take the second scrambled image's pixels, and XOR them with the three-dimensional chaotic values generated from the Lorenz system and create the final encrypted image. The robustness and flexibility of the encryption system are analyzed using various security and performance analyses. The experiment results are compared with the existing algorithms to prove the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Network sequence has been commonly used for describing the longitudinal pattern of a dynamic system. Proper online monitoring of a network sequence is thus important for detecting temporal structural changes of the system. To this end, there have been some discussions in the statistical process control (SPC) literature to first extract some features from the observed networks and then apply an SPC chart to monitor the extracted features sequentially over time. However, the features used in many existing methods are insensitive to some important network structural changes, and the control charts used cannot accommodate the complex structure of the extracted features properly. In this paper, we suggest using four specific features to describe the structure of an observed network, and their combination can reflect most network structural changes that we are interested in detecting in various applications. After the four features are extracted from the observed networks, we suggest using a multivariate nonparametric control chart to monitor the extracted features online. Numerical studies show that our proposed network monitoring method is more reliable and effective than some representative existing methods in various cases considered. [ABSTRACT FROM AUTHOR]

This article is concerned with the stability and stabilisation of switched time-delay systems (STDSs) with exponential uncertainty. Based on the Hurwitz convex combination and the energy attenuation principle, an improved state-dependent switching strategy is proposed, which switches to the next modes to obey the minimum energy. This approach fully considers the system dynamic of subsystems, which is more general. Considering the complex switching and delay dynamics, a mode-dependent Lyapunov–Krasovskii functional (LKF) that contains a triple integral term is constructed. The generalised free-matrix-based integral inequality (GFMBII) is used to estimate the integral terms in the derivative of the LKF, and an improved delay-dependent stability criterion is established in the form of linear matrix inequalities (LMIs). Further, to guarantee the stability of the STDSs with a large time-varying delay, a controller that considers the time delay and the exponential uncertainty is designed. Under this controller, a less conservative delay-dependent robust stabilisation criterion for STDSs with exponential uncertainty is established. The validity of the proposed methods is validated by two numerical examples and an application in river pollution control. [ABSTRACT FROM AUTHOR]

In the present study, the stability limit of the MILD regime of combustion has been studied in a reverse flow combustor using syngas (20% H2, 20% CO, 60% N2) as fuel. Pressure oscillations obtained from the combustor are analyzed using regular approaches from the dynamical systems theory as the oxidizer preheat temperature varies from 772 K to 424 K. Stable MILD combustion is obtained at preheat temperatures ≥724 K; at lower preheat temperatures combustion becomes unstable, leading to high amplitude periodic oscillations. Permutation spectrum test and recurrence plot of the MILD condition unravels the deterministic nature of the pressure oscillations. The correlation dimension confirms that the system has high-dimensional chaotic characteristics. At temperatures <724 K, the correlation dimension becomes close to 1 as the system transitions to combustion instability. In these conditions, the permutation spectrum test shows close to zero standard deviation in all ordinal indices, the phase-space shows doughnut-shaped structures, and recurrence plot consists of long diagonal lines, all confirming the periodic nature of the system. The dominating frequency during combustion instability is attributed to the second axisymmetric mode of the combustor. Finally, three recurrence quantification criteria, namely, Recurrence Rate, Determinism, and Laminarity, and K-value obtained from 0 to 1 test, are tested as indicators for the onset of combustion instability. Determinism and K-value are recommended for capturing the transition in the underlying dynamics. [ABSTRACT FROM AUTHOR]

Due to high utility of the sandwich structures in the vast spectrum of applications, this research focuses on the practical solution to protect them from damaging consequences of thermal shocks through parametric assessment of its time-variant thermoelastic performance. To this end, current research proposes a novel approach by taking the advantage of coupling the exactitude of the analytical solutions with the agility of the machine-learning methods to predict the accurate results by lower computational efforts. Case study of this research is a sandwich sector plate with functionally-graded carbon-nanotubes reinforced (FG-CNTR) nanocomposite face-layers exposed to the thermal shock loading. As another novelty, this study considers a radial-variant elastic substrate as a mechanism of resistance against the destructive consequences of thermal shock loading. As all machine-learning based regressors require the set of datapoints, this study employs harmonic format of the differential quadrature approach (HDQA) to find the system's response toward thermal shock in the background of general elasticity theory at definite design- points. Laplace transform integrated with the extended model of Dubner and Abate's scheme to translate the time-variant response of the system from time to Laplace domain and vice versa. Validity of the solution used in this survey is confirmed through comparing its outcomes with those of the published articles. As a valuable finding, it is strongly suggested to enhance the system's thermal shock resistance by using the substrates which their reaction's dependency to the radial coordinate is expressed by higher-order polynomial estimator functions. [ABSTRACT FROM AUTHOR]

This article analyzes the forced and free vibrations of bi-directional functionally graded (BDFG) porous nanobeams under moving loads by considering the thickness effect based on the nonlocal strain gradient theory (NSGT). It is assumed that the material properties of the system are graded across the transverse and axial directions according to power and exponential laws, respectively. Various porosity models, including even, uneven, and asymmetric porosity distribution patterns, are considered to model the porosity effects. The dynamic equation of the system is derived by implementing the physical neutral surface concept. Analytical and numerical approaches are adopted to acquire the vibration response of the system. Mathematical closed-form expressions are provided for various dynamic phenomena, such as two types of cancelation, two types of resonance, maximum resonance, cancelation disappearance, and resonance disappearance. In addition, for the first time in this article, it is demonstrated that BDFG porous nanobeams under moving loads are prone to experience the double cancelation phenomenon. Several comparison studies with published data are conducted to validate the results. Also, comprehensive parametric studies are carried out to elucidate the impacts of system parameters such as thickness power index, axial gradient parameter, scale parameter ratio, axial force, porosity coefficient, and porosity distribution pattern on the dynamic magnification factor, critical load speed, and maximum free-response. The outcomes established that by considering the thickness effect, the stiffening behavior of the system is amplified depending on the slenderness ratio. Also, it is concluded that, among the considered porous models, the critical load speed for the system with an even porosity distribution is more dependent on the thickness power index. [ABSTRACT FROM AUTHOR]