Dynamic Subsystem Research Articles

Parents' perception of children's behaviors, self-compassion, and parenting stress: Actor-partner interdependence model.

This study explores how self-compassion mediates the relations between parents' perceptions of children's behaviors and parenting stress, as well as interactions between parents. We conducted a longitudinal actor-partner interdependence mediation model and assessed parents' perceptions of children's behaviors, self-compassion, and parenting stress. A total of 656 pairs of parents (fathers' Mage = 34.96 years, SDage = 5.62; mothers' Mage = 33.13 years, SDage = 5.77) participated in the study. Results revealed that parents' perceptions of children's problem behavior affected their own parenting stress through their self-compassion. Additionally, parents' perceptions of children's prosocial behavior directly influenced their own parenting stress and also affected it through self-compassion in both parents. Parents' perceptions of children's problem behavior directly influenced their partner's parenting stress and also indirectly through their own self-compassion. Similarly, parents' perceptions of children's prosocial behavior affected their partner's parenting stress via self-compassion in both parents. The findings highlighted the importance of parents recognizing and valuing their children's positive behaviors, thereby fostering a constructive "child effect" that improved the dynamics of the parental subsystem. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exact Hidden Markovian Dynamics in Quantum Circuits.

Characterizing nonequilibrium dynamics in quantum many-body systems is a challenging frontier of physics. In this Letter, we systematically construct solvable nonintegrable quantum circuits that exhibit exact hidden Markovian subsystem dynamics. This feature thus enables accurately calculating local observables for arbitrary evolution time. Utilizing the influence matrix method, we show that the influence of the time-evolved global system on a finite subsystem can be analytically described by sequential, time-local quantum channels acting on the subsystem with an ancilla of finite Hilbert space dimension. The realization of exact hidden Markovian property is facilitated by a solvable condition on the underlying two-site gates in the quantum circuit. We further present several concrete examples with varying local Hilbert space dimensions to demonstrate our approach.

Теоретические основы построения систем управления современными предприятиями

Timely research and analysis of enterprise management systems, their competent decomposition into component parts in order to implement corrective actions to improve the final efficiency of the management process as a whole, are relevant areas of theoretical and practical scientific research. As a result of the study of existing approaches to the concept of a management system, its substantive characteristics as an anthropogenic system and directions for study, analysis and improvement at specific enterprises have been clarified. The importance of such properties of the management system in modern conditions is substantiated as: integrity, manifested in the presence of its own pattern of development and influence on the characteristics of the controlling and controlled subsystems; synergy, providing qualitatively new properties, and dynamic equilibrium, compensating for the effects of the internal and external environment on the functioning of the enterprise. As the main directions of the decomposition of the management system, the following are highlighted: functional areas of management – production subsystem, financial subsystem, personnel subsystem, etc.; management functions – planning, organization, motivation, control, etc.; object and subject of management; dynamic and static subsystems, where the static subsystem (structure, resources, controls) sets the framework for management activities, and the dynamic subsystem (management process carried out using management functions) transfers the system from one stable state to another to compensate for the effects exerted by the external and internal environment.

Study abroad experiences in homestay: where complexity, dynamicity, and individuality stay

Abstract Informed by Complex Dynamic Systems Theory, this study examines the nature of homestay as a situated language learning site, with an eye toward the development of American student guests and Chinese host families’ homestay experiences within the larger context of the study abroad (SA) program and local community. Drawing on data collected from host families and student guests, this study discovers benefits, conflicts, and co-adaptations in homestay; the evolution of host families’ dispositions toward homestay; student guests’ proficiency gains and interactions with hosts and locals; and contextual factors that influence the proficiency gains and interactions. The findings reveal that homestay is a dynamic, self-evolving subsystem, which constantly interacts with other dynamic subsystems, such as the SA program and local community, within the complex social ecosystem of the entire SA environment. This study also provides suggestions for the design and management of the homestay component in the SA program and future research.

The Coupling Coordination Degree and Its Driving Factors for Water–Energy–Food Resources in the Yellow River Irrigation Area of Shandong Province

Water resources, energy, and food are essential for the development of society, and they are strongly interdependent. The coupling and coordination relationships of the water–energy–food (WEF) system are important for regional resource security and high-quality development. The Yellow River Irrigation Area in Shandong Province, China, is a grain production base and has a substantial impact on national food security. To examine the water, energy, and food subsystem dynamics in this area, an evaluation system for the WEF system was established. A comprehensive weighting method based on game theory was employed to determine index weights. TOPSIS was used to assess the development level of the WEF system. A coupling coordination degree model was used to analyze the evolution of the coupling coordination degree of the WEF system from 2000 to 2020, and a GWR model was constructed to explore the spatial heterogeneity of its driving factors. The findings indicated that the development level of the WEF system in the study area was moderate, with a gradual upward trend. The coupling coordination degree fluctuated between 0.62 and 0.739. The GWR model revealed that temperature had an overall negative effect on the coupling coordination degree, with the greatest impact on the central irrigation area; the slope and NDVI had a negative effect, with increasing intensity from the southwest to the northeast; and rainfall had an overall positive effect, with the greatest impact on the irrigation area near the estuary in the northeast. Overall, the building area ratio had a negative effect on the coupling coordination degree, with exceptions in some areas. These research outcomes provide theoretical support for sustainable agricultural development in the Yellow River irrigation areas of Shandong Province and methodological reference data for studying collaborative resource utilization in irrigation regions.

Modeling the Influence of Internal Factors on Vehicular Mobility Performance

Traffic mobility is significantly influenced by road conditions and the internal factors governing vehicular performance. Internal factors play a crucial role in vehicular mobility, influencing vehicles operate and performance. While existing vehicular mobility models primarily address external factors, external factors such as governor, engine, gear train and differential unit remain underexplored. This study formulates a comprehensive model to address this gap, focusing on the internal components that affect vehicular mobility. The proposed model employs both analytical and numerical methods to derive transfer functions for these subsystems using Matrix Laboratory (MATLAB), aiming to capture the dynamic behavior of vehicles under various conditions. The model was evaluated by examining vehicle transaction times across different road surface qualities, measured by the International Roughness Index (IRI) values of 3.5, 3.0, and 2.0, and tractive forces ranging from 4500 N to 17750 N, with applied pedal forces of 50 N, 100 N, 150 N and 200 N. Results indicated that higher tractive forces lead to reduced transaction times, with IRI values of 3.5 m/km showing a decrease from 122.0 seconds to 31.0 seconds as tractive forces increased from 4500 N to 17750 N. Similarly, for IRI values of 2.0 m/km, the transaction times reduced from 67.5 seconds to 7.5 seconds under the same conditions. The analysis further demonstrated that increased applied pedal forces correspond to higher tractive forces, thereby enhancing vehicular mobility and performance. These findings highlight the critical role of internal factors in optimizing vehicular mobility and performance, suggesting that internal subsystem dynamics should be integrated into future mobility models for more accurate and comprehensive assessments.

Adaptive optimal concurrent control for detumbling space non-cooperative target via multipoint repeated contact

Space debris generally exhibits complex tumbling motions, and its direct capture may cause damage to space manipulator and base spacecraft. Current detumbling strategies typically require continuous contact collisions with the target and do not take into account actuator limitations. Thus, this paper presents an adaptive optimal concurrent control of space free-floating multi-fingered robot (SFMR) for multipoint repeated contact detumbling of non-cooperative targets. Firstly, the multipoint repeated intermittent contact model between the SFMR and the target is established. Further, an optimal admittance control that considers manipulator actuator limits and target motion bounds is formulated to generate a compliant detumbling trajectory. Through transforming the state and input inequality constraints into extended dynamical subsystems and saturation functions, respectively, the optimal control problem (OCP) is transformed into a readily solvable equality constraint problem. Moreover, an enhanced nonsingular terminal sliding mode (ENTSM) control with radial basis function neural network (RBFNN) compensation is presented in the presence of lumped uncertainties and external disturbances, which achieves rapid finite-time convergence and low-chattering. The simulation results show that the proposed method can reduce the velocity of the space target effectively without causing base spacecraft interference while achieving accurate trajectory tracking.

The role of thermal and squeezed photons in the entanglement dynamics of the double Jaynes–Cummings model

The effects of squeezed photons and thermal photons on the entanglement dynamics of atom-atom, atom-field and field-field subsystems are studied for the double Jaynes–Cummings model. For this purpose, squeezed coherent states and Glauber-Lachs states of radiation are chosen as field states. For the atomic states, we choose one of the Bell state as pure state and a Werner-type state as mixed state. Werner-type state is used to understand the effects of mixedness on entanglement. To measure the entanglement between the two atoms, Wootters’ concurrence is used; whereas for the atom-field and field-field subsystems, negativity is chosen. The squeezed photons and thermal photons create, destroy and transfer entanglement within various subsystems. Also, the addition of squeezed photons and thermal photons either lengthens or shortens the duration of entanglement sudden deaths (ESD) associated with atom-atom, atom-field and field-field entanglement dynamics in a complementary way. The effects of Ising-type interaction, detuning and Kerr-nonlinearity on the entanglement dynamics are studied. Each of these interactions removes the ESDs associated with various subsystems. We show that new entanglements are created in this atom-field system by introducing Ising-type interaction between the two atoms. With proper choice of the parameters corresponding to Ising-type interaction, detuning and Kerr-nonliearity, entanglement can be transferred among various subsystems.

A Novel Tire and Road Testing Bench for Modern Automotive Needs

The automotive industry is currently transforming, primarily due to the rise of electric and hybrid vehicle technologies and the need to reduce vehicle mass and energy losses to decrease consumption, pollution, and raw material usage. Additionally, road surface manufacturers emphasize improving pavement durability and reducing rolling noise. This necessitates precise load condition definitions and drives the need for reliable wheel testing benches. Many current benches use abrasive-coated rollers or synthetic tapes, but devices capable of testing on actual road surfaces are rare. In this work, a novel device for testing tire-pavement interaction is proposed. The system features a cart moving along a closed-track platform, ensuring test repeatability and enabling structural durability tests on uneven surfaces with installed obstacles. The cart is equipped with a cantilever arm capable of supporting either a testing wheel with customizable dimensions and kinematic parameters or a tire integrated with a complete suspension system, moving along a customizable pavement surface. The system includes actuators and sensors for applying vertical loads and adjusting the alignment of the testing wheel (slip angle, camber angle, etc.), allowing the characterization of tire behavior such as wear, fatigue, rolling noise, and rolling resistance. Multibody simulations were performed to evaluate the bench’s feasibility in terms of kinematics, power requirements, and structural loads. Results confirmed how this novel test bench represents a promising advancement in tire testing capabilities, enabling comprehensive studies on tire performance, noise reduction, and the structural dynamics of vehicle subsystems.

Reduced-order modeling of modular, position-dependent systems with translating interfaces

Many complex mechatronic systems consist of multiple interconnected dynamical subsystems, which are designed, developed, analyzed, and manufactured by multiple independent teams. To support such a design approach, a modular model framework is needed to reduce computational complexity and, at the same time, enable multiple teams to develop and analyze the subsystems in parallel. In such a modular framework, the subsystem models are typically interconnected by means of a static interconnection structure. However, many complex dynamical systems exhibit position-dependent behavior (e.g., induced by translating interfaces) which cannot be captured by such static interconnection models. In this paper, a modular model framework is proposed, which allows to construct an interconnected system model, which captures the position-dependent behavior of systems with translating interfaces, such as linear guide rails, through a position-dependent interconnection structure. Additionally, this framework allows to apply model reduction on subsystem level, enabling a more effective reduction approach, tailored to the specific requirements of each subsystem. Furthermore, we show the effectiveness of this framework on an industrial wire bonder. Here, we show that including a position-dependent model of the interconnection structure (1) enables to accurately model the dynamics of a system over the operating range of the system and, (2) modular model reduction methods can be used to obtain a computationally efficient interconnected system model with guaranteed accuracy specifications.

Understanding long-term human ecodynamics through the lens of ecosystem collapse

Most research on long-term human ecodynamics examines changes in the size and structure of human populations, often in relation to climate change. Here we offer an alternative perspective that draws on recent progress in conservation science, examining the causes and consequences of ecosystem collapse. We identify human actions that can cause abrupt transformation of ecosystems, in relation to key mechanisms and underlying theory. Such ecosystem collapse can in turn affect human societies by altering flows of ecosystem benefits to people. In this way, human ecodynamics can be understood by separately analysing the dynamics of social and ecological sub-systems, which are reciprocally linked. Ecosystem collapse represents a perturbation of these sub-systems, and provides insights into the mechanisms underlying their respective dynamics. We illustrate this approach through four case studies, which examine the spread of agriculture during the Holocene. Four key knowledge gaps emerge through consideration of these case studies: the linkages between social and ecological sub-systems, and how these change over time; the presence of feedbacks between these sub-systems; the relationships between local- and regional-scale collapse; and the relationships with ecological recovery. Increased research on ecosystem collapse could help clarify the relative influence of environmental degradation on societal dynamics, while providing insights into resilience and sustainability. Given the outstanding societal importance of ecosystem collapse, such research could also strengthen the relevance of historical sciences to the contemporary world.

Влияние динамических характеристик процесса резания на шероховатость поверхности детали при токарной обработке

Introduction. The formation of the surface of a part when processing it on a metal-cutting machine is based on properly selected cutting modes. Complex methods of ensuring the specified quality of the part surface also take into account the tool geometry, its condition, and include corrections for tool deviation from the trajectory set by the CNC system under the influence of kinematic disturbances and spindle wavering. Subject. The paper analyzes the relationship between cutting modes and dynamic characteristics of the turning process, and its mapping into surface roughness. The aim of the work is to evaluate the influence of technological cutting modes taking into account the vibration activity of the tool on the roughness of the machined surface by means of simulation modeling. Method and methodology. Mathematical simulation of the dynamics of the cutting process is given, on the basis of which a digital simulation model is built. A methodology of using the simulation model for determining optimal cutting modes and predicting surface roughness taking into account tool vibrations is proposed. By means of experiments and analysis of the frequency characteristics of tool vibrations, the created model is validated, parameters of the cutting forces model subsystem and dynamic tool subsystem are specified, and geometrical topologies of the part surface are constructed. The calculated cutting forces are compared with experimental forces, and similar patterns and levels of characteristics are observed. An assessment of the optimality of the selected cutting modes is proposed based on the analysis of the tool vibration spectrum relative to the workpiece and the results of the numerical model simulation. Results and Discussion. A comparison of the results of digital modeling of the geometrical surface of the workpiece and the real surface obtained during the field experiment is given. It is shown that the roughness of the real surface obtained by machining with constant cutting modes varies relative to the surface roughness of the simulation model within the limits of not more than 0.066 µm.

General framework for quantifying dissipation pathways in open quantum systems. II. Numerical validation and the role of non-Markovianity.

In the previous paper [C. W. Kim and I. Franco, J. Chem. Phys. 160, 214111-1-214111-13 (2024)], we developed a theory called MQME-D, which allows us to decompose the overall energy dissipation process in open quantum system dynamics into contributions by individual components of the bath when the subsystem dynamics is governed by a Markovian quantum master equation (MQME). Here, we contrast the predictions of MQME-D against the numerically exact results obtained by combining hierarchical equations of motion (HEOM) with a recently reported protocol for monitoring the statistics of the bath. Overall, MQME-D accurately captures the contributions of specific bath components to the overall dissipation while greatly reducing the computational cost compared to exact computations using HEOM. The computations show that MQME-D exhibits errors originating from its inherent Markov approximation. We demonstrate that its accuracy can be significantly increased by incorporating non-Markovianity by exploiting time scale separations (TSS) in different components of the bath. Our work demonstrates that MQME-D combined with TSS can be reliably used to understand how energy is dissipated in realistic open quantum system dynamics.

Parameter learning of multi‐input multi‐output Hammerstein system with measurement noises utilizing combined signals

SummaryIn this article, the parameter learning scheme for the multi‐input multi‐output (MIMO) Hammerstein nonlinear systems under measurement noises is studied, which is derived by exploiting the correlation analysis and data filtering technique. The coupled MIMO Hammerstein system presented involves a static nonlinear subsystem modeled by neural fuzzy model (NFM), and a dynamic linear subsystem established by autoregressive moving average with extra input (ARMAX) model. To learn the unknown parameter of the MIMO Hammerstein system, the combined signals are designed to realize that identification of the nonlinear subsystem is separated from that of linear subsystem. First, the correlation properties of separable signals in a nonlinear system are analyzed, then the parameters of the linear subsystem are estimated utilizing correlation analysis, which can deal with the issue of unmeasured intermediate variable in the Hammerstein system. Second, the data filtering technique is introduced to derive the data filtering‐based recursive least squares technique for learning the nonlinear subsystem parameter, which can reduce the impact of the moving average noise and improve the precision of parameter estimation. Finally, the effectiveness and feasibility of the proposed identification scheme is proved by numerical simulation and nonlinear pH process.

Stability analysis of stochastic nonlinear switched systems with time‐delay and its application

AbstractThis paper studies the stability of stochastic nonlinear time‐delay systems with arbitrary switching and its application. A novel Krasovskii‐type stability theorem is introduced for stochastic nonlinear systems featuring arbitrary switching and time‐delay. Unlike previous results, this stability result removes the restriction that the infinitesimal generator of Lyapunov–Krasovskii functional (i.e., ) must be negative definite and allows to be indefinite. As an application, the tracking control is studied for a class of stochastic switched systems with inverse dynamics and time‐delay. The assumption condition imposed on the inverse dynamic subsystem is weaker compared with most of existing findings. Finally, we illustrate the feasibility and effectiveness of proposed control strategy by two simulation examples.

Dynamic modelling of supplemental cooling systems with vapor compression refrigeration units in civil aircrafts

Newly developed airliners have adopted supplemental cooling systems (SCS) to provide for non-cabin cooling requirements. In the present study, dynamic component models for compressor and phase change heat exchangers were developed with dynamic decoupling and explicit solution methods, and pressure zone separation and solution methods are developed based to obtain dynamic pressures as key values. A dynamic VCRU subsystem model is established, and the result under single-unit startup condition shows pressure deviations less than 0.16 %, with a simulation time ratio of 5.65 %, exhibiting good overall performance at both precision and speed. A dynamic SCS system model is developed, and the simulation of a 9000 s flight took 1973.3 s to complete. Result in the cruise phase shows the condensation and evaporation temperatures are in the ranges of 28.39–31.33 °C and −17.93 to −10.71 °C, respectively, meeting their respective designed ranges of 30 ± 5 °C and −15 ± 5 °C. These results reflects good consistency of the model with actual system characteristics. Control optimization is conducted based on the developed model to eliminate temperature fluctuation. The optimization reduced the maximum temperature deviation from 0.4004 K to 0.0019 K after system starting process, proving the feasibility of control method optimization based on the developed dynamic simulation model.

Design and analysis of an adaptive radiation resilient RRAM subsystem for processing systems in satellites

Among the numerous benefits that novel RRAM devices offer over conventional memory technologies is an inherent resilience to the effects of radiation. Hence, they appear suitable for use as a memory subsystem in a computer architecture for satellites. In addition to memory devices resistant to radiation, the concept of applying protective measures dynamically promises a system with low susceptibility to errors during radiation events, while also ensuring efficient performance in the absence of radiation events. This paper presents the first RRAM-based memory subsystem for satellites with a dynamic response to radiation events. We integrate this subsystem into a computing platform that employs the same dynamic principles for its processing system and implements modules for timely detection and even prediction of radiation events. To determine which protection mechanism is optimal, we examine various approaches and simulate the probability of errors in memory. Additionally, we are studying the impact on the overall system by investigating different software algorithms and their radiation robustness requirements using a fault injection simulation. Finally, we propose a potential implementation of the dynamic RRAM-based memory subsystem that includes different levels of protection and can be used for real applications in satellites.

Approximations of Symbolic Substitution Systems in One Dimension

AbstractPeriodic approximations of quasicrystals are a powerful tool in analyzing spectra of Schrödinger operators arising from quasicrystals, given the known theory for periodic crystals. Namely, we seek periodic operators whose spectra approximate the spectrum of the limiting operator (of the quasicrystal). This naturally leads to study the convergence of the underlying dynamical systems. We treat dynamical systems which are based on one‐dimensional substitutions. We first find natural candidates of dynamical subsystems to approximate the substitution dynamical system. Subsequently, we offer a characterization of their convergence and provide estimates for the rate of convergence. We apply the proposed theory to some guiding examples.

Efficacité des psychothérapies sur les symptômes dissociatifs en population adulte : une revue de la littérature PRISMA

IntroductionDissociation is a psychological process in reaction to threat which can be found in many psychiatric conditions. Dissociative symptoms can become very disabling, whether in daily life or in care. Nevertheless, few studies seem to have examined the efficacy of psychotherapy on the latter and its relevance as a therapeutic target. MethodA systematic review of the literature (PRISMA) on the efficacy of psychotherapy on dissociative symptoms in adults with mental disorders was conducted. Effectiveness was considered in terms of reduction in dissociative symptomatology. The search was conducted on Scopus, PubMed and PsycInfo. Overall, 50 full-text articles were evaluated. ResultsFourteen studies were included in the review. In all, 711 adult subjects with post-traumatic stress disorder, borderline personality disorder or dissociative disorder were included. Overall, this systematic review reports a reduction in dissociative symptoms associated with a variety of psychotherapeutic interventions, without allowing any conclusions to be drawn on the superiority of one psychotherapy over another. DiscussionThe conclusions of this work highlight three possible therapeutic orientations for reducing dissociative symptoms: (i) by reintegrating the dynamic subsystems, (ii) by treating the cognitive processes underlying dissociation, and (iii) by acting on the processes identified as common to the effectiveness of psychotherapy.

Controlling quantum many-body systems using reduced-order modeling

Quantum many-body control is among the most challenging problems in quantum science due to its outstanding computational complexity in a general case. We propose an efficient approach to a class of many-body quantum control problems, where time-dependent controls are applied to a sufficiently small subsystem. The method employs a tensor-network scheme to construct a reduced-order model of a subsystem's non-Markovian dynamics. The resulting reduced-order model serves as a digital twin of the original subsystem. Such twins allow significantly more efficient dynamics simulation, which enables the use of a gradient-based optimization toolbox in the control parameter space. This approach to building control protocols takes advantage of non-Markovian dynamics of subsystems by design. We validate the proposed method by solving control problems for quantum spin chains. In particular, the approach automatically identifies control sequences for exciting and guiding quasiparticles to recover and transmit quantum information across the system. In addition, we find generalized spin-echo sequences for a system in a many-body localized phase enabling significant revivals. We expect our approach can be useful for ongoing experiments with noisy intermediate-scale quantum devices. Published by the American Physical Society 2024