State Of Subsystem Research Articles

Nonclassical coincidences of atomic and mechanical excitations

Hybrid systems hold promise to provide an advantage in future quantum technology. Operating such systems outside the classical regime is crucially important to fully realize their potential. We investigate a pulsed quantum nondemolition gate between a cloud of atoms and a mechanical oscillator in distant cavities and demonstrate that this gate is capable of producing nonclassical coincidences of excitations in the disparate subsystems interacting by light. The nonclassicality is justified by evaluation of excitations created simultaneously in both modes beyond any joint classical states of such subsystems. To test the result, we use a nonclassicality witness based on available homodyne tomography of the atomic and mechanical states. Using feasible parameters, we show that it is possible to turn the pulsed dynamics of the state-of-the-art systems into nonclassical coincidences, and illustrate it for the cases of the atom-light, optomechanical, and atom-mechanical hybrid interactions. These tests are necessary to open full investigation of quantum correlations in hybrid systems. Published by the American Physical Society 2024

Quantum–Classical Hybrid Dynamics: Coupling Mechanisms and Diffusive Approximation

In this paper we demonstrate that any Markovian master equation defining a completely positive evolution for a quantum–classical hybrid state can always be written in terms of four basic coupling mechanisms. Each of them is characterized by a different “backaction” on each subsystem. On this basis, for each case, we find the conditions under which a diffusive limit is approached, that is, the time evolution can be approximated in terms of the first and second derivatives of the hybrid state with respect to a classical coordinate. In this limit, the restricted class of evolutions that guaranty the positivity of the hybrid state at all times (quantum Fokker-Planck master equations) emerges when the coupling mechanisms lead to infinitesimal (non-finite) changes in both the quantum and classical subsystems. A broader class of diffusive evolutions is obtained when positivity is only granted after a transient time or alternatively is granted after imposing an initial finite width on the state of the classical subsystem. A set of representative examples support these results.

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

EFFICIENCY OF OPERATION OF THE FIRE SAFETY SUBSYSTEM OF THE HYDROGEN STORAGE AND SUPPLY SYSTEM

Hydrogen may become one of the most valuable energy carriers in the 21st century. A big step to this is the safe, compact, and cost-effective storage of hydrogen provided by hydrogen storage systems (HSS). One of the operating system elements of the hydrogen storage and supply system is its fire safety subsystem. The effectiveness of such a subsystem’s functioning depends on a conditional probability that this subsystem correctly recognises the actual state of the hydrogen storage and supply system. We carry out the formalisation of the operation of the fire safety subsystem of the hydrogen storage and supply system in the form of a graph of its states. The study considers three modes of operation of such a subsystem: control, testing, and self-control. We build a weight matrix of the fire safety subsystem states. Its elements include the intensity of transitions from one state to another, the recovery intensity, and the completeness of control and testing. The study shows that the roots of the system of Kolmogorov equations determine the efficiency of the functioning of the fire safety subsystem of the hydrogen storage and supply system. We represent this system of equations in matrix form, with the main matrix having a size of 8×7. Next, we obtain expressions for the roots of such a system of comparisons and construct an expression for the efficiency of the fire safety subsystem’s functioning of the hydrogen storage and supply system. This expression applies to all three modes of operation of such a fire safety subsystem. The considered typical modes of operation of the fire safety subsystem of the hydrogen storage and supply system are control mode, control mode with self-control, and control and testing mode. For each of these modes, we obtain expressions that describe their effectiveness. It is necessary to note that the magnitudes of recovery intensities, in contrast to transition intensities, can vary. We further provide an example of choosing the intensities of restoration of the subsystem during its control using the acceptance criterion for the probability of finding the subsystem in a state corresponding to the fire-hazardous state of the hydrogen storage and supply system. Keywords: fire safety, efficiency, hydrogen storage and supply system.

Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning

BackgroundThe prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretability in most machine learning and deep learning methods. Therefore, it is imperative to establish an interpretable model that receives various cell line and drug feature data to learn drug response mechanisms and achieve stable predictions between available datasets.ResultsThis study proposes a new and interpretable deep learning model, DrugGene, which integrates gene expression, gene mutation, gene copy number variation of cancer cells, and chemical characteristics of anticancer drugs to predict their sensitivity. This model comprises two different branches of neural networks, where the first involves a hierarchical structure of biological subsystems that uses the biological processes of human cells to form a visual neural network (VNN) and an interpretable deep neural network for human cancer cells. DrugGene receives genotype input from the cell line and detects changes in the subsystem states. We also employ a traditional artificial neural network (ANN) to capture the chemical structural features of drugs. DrugGene generates final drug response predictions by combining VNN and ANN and integrating their outputs into a fully connected layer. The experimental results using drug sensitivity data extracted from the Cancer Drug Sensitivity Genome Database and the Cancer Treatment Response Portal v2 reveal that the proposed model is better than existing prediction methods. Therefore, our model achieves higher accuracy, learns the reaction mechanisms between anticancer drugs and cell lines from various features, and interprets the model’s predicted results.ConclusionsOur method utilizes biological pathways to construct neural networks, which can use genotypes to monitor changes in the state of network subsystems, thereby interpreting the prediction results in the model and achieving satisfactory prediction accuracy. This will help explore new directions in cancer treatment. More available code resources can be downloaded for free from GitHub (https://github.com/pangweixiong/DrugGene).

Improvement of urban passenger ground transport structure based on coordinated development of subsystems

Introduction. The high importance of the urban passenger transport complex as a system determining the level of socio-economic development of the urban area is formulated. One of the systemic problems of the passenger transport complex of modern cities is the decentralization of planning and management processes, which determines the structural imbalance of key subsystems. The results of a literary review are presented, during which the works devoted to improving the efficiency of the transport process, the process of providing energy resources and the process of maintaining rolling stock in good condition are considered. The necessity of developing a methodology ensuring the coordination of the state and functioning of key subsystems of the transport complex is noted. The purpose of scientific work is defined, the list of solved tasks is defined.Materials and methods. The structural scheme of the urban passenger transport complex is given, a conceptual approach to solving the problem of coordinated optimization of its key subsystems is described. The following are defined: the target indicator, the objective function and its limitations that determine the optimization process being implemented. A brief description of methods for determining and mutual coordination of structural parameters of subsystems forming the material basis of the transport complex is given.Results. Theoretical provisions reflecting a conceptual approach to ensuring the efficiency of urban transport systems based on the coordinated development of subsystems, based on the magnitude of the proposed integrated efficiency indicator, are presented. Based on the data obtained from the results of analytical studies and field experiments, a calculation was made that made it possible to determine the structural parameters of the subsystems of the urban passenger transport system of one of the cities, ensuring the maximum value of the efficiency of transport activities provided by structural coordination of the subsystems that make up the material basis of the urban passenger transport system.Discussion. The solution of the tasks set is reflected, indicators reflecting the achievement of the research goal are indicated, confirmation of the hypothesis about the possibility of improving the efficiency of the urban passenger transport complex through the implementation of conditions ensuring the coordinated development and interaction of key subsystems is formulated.Conclusion. A generalizing conclusion about the solution of an important scientific, methodological and applied task – to increase the efficiency of the passenger transportation process along urban passenger transport routes based on ensuring the coordinated development of the subsystems that make up its material base is formulated.

Quantum entanglement: Principles and research progress in quantum information processing

Quantum entanglement is a peculiar phenomenon in quantum information science, characterized by nonclassical correlations between quantum states of subsystems in a quantum system. Since the proposal of the Einstein-Podolsky-Rosen (EPR) paradox by Einstein, Podolsky, and Rosen, quantum entanglement has sparked intense debates on local realism. Bells inequality experiment established the nonlocality of quantum mechanics. Currently, high-dimensional quantum entanglement of both deterministic and random states can be realized in systems such as photons and cold atoms. Technologies such as quantum teleportation, quantum teleportation, quantum computing, and others rely on quantum entanglement to achieve effects beyond classical limitations. Current research focuses on the implementation of macroscopic quantum entanglement and its significance in fundamental problems of quantum mechanics. Quantum entanglement opens up a new paradigm for information processing with broad application prospects. It is necessary to conduct in-depth research on the nature of quantum entanglement and its advantages in information processing. This paper reviews the theoretical foundations of quantum entanglement, methods of generation and detection, and research progress in its applications in the field of quantum information. It discusses the important applications of quantum entanglement in quantum communication, computing, and sensing and provides an outlook on the future development prospects of quantum entanglement technologies.

Robust decomposed system control for an electro‐mechanical linear actuator mechanism under input constraints

AbstractThis paper aims to develop a robust decomposed system control (RDSC) strategy under input constraints for an electro‐mechanical linear actuator (EMLA) facing model uncertainty and external disturbances. At first, a state‐space model of a complex multi‐stage gearbox EMLA system, driven by a permanent magnet synchronous motor (PMSM), is developed, and the non‐ideal characteristics of the ball screw are presented through the model. The result is a four‐order nonlinear strict‐feedback form (NSFF) system decomposed into three subsystems. As the paper's main result, a novel RDSC strategy with uniform exponential stability for controlling subsystem states is presented. This developed controller avoids the "explosion of complexity" problem associated with backstepping by treating the time derivative of the virtual control input as an uncertain system term. The proposed method, despite assuming load disturbances and input constraints with arbitrary bounds, offers a straightforward control approach for a broader range of applications. Further, the controller's performance is evaluated by simulating two distinct duty cycles, each representing different levels of demand on the actuator facing load disturbances near the rated motor performance.

Digital Twin Technologies for Autonomous Environmental Control and Life Support Systems

Environmental control and life support systems will require enhanced self-awareness and self-sufficiency as human spaceflights are designed to reach further destinations. These requirements have led to the development of autonomous technologies and systems to enable more Earth independence, while at the same time relying more heavily on the knowledge contained in their computational models (as opposed to the knowledge of ground control experts). For environmental control and life support systems, these consist of disparate models often tailored to specific subsystems and use cases, such as temperature control and CO2 removal. Therefore, there is a need for technologies supporting the integration of existing models. We propose to extend existing digital twin frameworks to integrate models and serve as a tool for answering onboard queries during operation. Toward this vision, we identify research directions for three types of technologies: i) streamlining the process of merging information models without redundancies by leveraging model-based systems engineering languages; ii) the calibration of simulation models that requires a better understanding of how to encode domain knowledge into a probabilistic representation of subsystem states and model parameters; and iii) automating the query understanding process and constructing a mapping between information and simulation models.

Policies addressing suspension and expulsion in state early care and education subsystems: A national census of policy alignment and integration

Exclusion from early care and education (ECE) programs creates employment challenges for families and disrupts learning for children, often differentially impacting children placed at-risk due to income, race, and disability. Federal policy guidance and changes in the Child Care and Development Fund (CCDF) Block Grant requirements are meant to influence states to create policies that will both regulate and prevent disciplinary exclusions, especially suspension and expulsion. We present a national census of states’ CCDF plans, center-based child care licensing regulations, and state pre-K policies addressing suspension and expulsion. Using content analysis methodology, we evaluate the presence of key policy components of suspension and expulsion prevention including data collection, parent/family involvement in the process of exclusions, accessing community resources, and the use of developmental information to inform the use of exclusionary discipline. Our results indicate that expulsion and suspension policies vary widely both across states, and within the same state's subsystems. The component found most frequently across all subsystems is an expulsion policy, with noticeable variation in specifying and defining suspension. Our findings also point to a great deal of variance in policy alignment, with pre-K including the most information on expulsion and suspension policies and prevention. As state-level policymakers seek to adopt policies that reduce exclusion in ECE, our findings point to a need to consider the importance of creating policies that protect children, especially those over exposed to exclusionary discipline, and then aligning those components within and across ECE subsystems to promote equitable access to ECE. This is particularly important for low-income families, Black children, children with disabilities, and boys.

Digital potential of the Russian agro-Industrial complex based on the results of technological innovations

The article analyzes the current state of innovation activity and the fundamental features of technological development in the agricultural sector of the economy, identifies barriers and prerequisites for the transition to digital transformation, and demonstrates the results of the introduction of domestic technological innovations. In the context of modern realities, innovations are becoming a fundamental component of the development of the national economy. The process of digitalization for the agro-industrial complex is due to the urgent need to increase the efficiency and sustainability of its functioning through radical transformations of managerial efficiency by technological processes and decision-making processes at all levels of the hierarchical ladder, based on innovative approaches to production and the subsequent application of information data on the state of controlled elements and subsystems and forecasting their potential adjustments, as well as economic conditions in the agricultural sector. The practice of a global scale and the experience of authoritative domestic agricultural producers illustrate that the use of modern technological solutions contributes to ensuring optimal soil, agrotechnical and organizational and territorial conditions, which make it possible throughout the full life cycle of agricultural products to contribute to an increase in yield and labor productivity, reduce material costs for fuels and lubricants (F&L), electricity, plant protection products (PPP), wages and other types of expenses, maintaining soil fertility and preserving the environment. Increasing and stimulating innovative and technological activity in the agro-industrial complex will also increase production volumes, increase the competitiveness of domestic agricultural products, eliminate the problem of import substitution and increase the level of profitability of agricultural enterprises.

Mechanisms of resilience in cities at different development phases: A system dynamics approach

Ecological degradation, environmental pollution, and lack of resources have brought challenges to sustainable urban development, whereas the concept of resilience provides a new normative and analytical tool to investigate urban responses to changes. To explore the mechanisms of resilience in cities at different development phases, this study employs a system dynamics approach to simulate and compare the evolutionary state of different resilient subsystems, including economic, social, ecological and infrastructure modules within cities. Then taking Beijing, Fuzhou, and Urumqi in China, three cities at different development stages as examples, the evolution of urban resilience systems from 2000 to 2035 is simulated under the socio-economic development scenario. The results show urban resilience in the three case study cities evolves in different trajectories with distinctive features showcasing different development phase. This study constructs a resilient city system dynamics model, which provides references for future quantitative resilience simulations and can be adapted and applied to resilience simulations of cities in different contexts. In addition, the case study provides distinct policy recommendations for resilience building in cities at various stages of development and points out key areas for resilience building in different cities.

Institutional support for the development of the Donbas: a retrospective analysis performed upon the inclusion of the region Into the Russian Federation

Subject. Institutional support for the development of the Donbas during the process of its adaptation to the social and economic system of the Russian Federation. The state and development prospects of institutional subsystems: business, public authority, financial, and non-commercial sectors. Purpose. To study the main parameters of the institutional subsystems in the Donbas and determine the problems and the vectors of institutional, social, and economic development of the region in the situation of an armed conflict running parallel to its integration with Russian institutes. Research methods. The theoretical basis of the study was the dialectical method, which allowed us to consider social, economic, and institutional systems of the Donbas in the context of integration of the region in Russian social environment. To determine the problems of social, economic, and institutional development of the region, the monographic method was used. It allowed us to review the existing approaches to the state and prospects of the economy and the supporting institutes during the period of integration into the Russian Federation. A retrospective analysis was a key practical research method. It helped to determine the dynamics of the main institutional subsystems of the region from the point of view of modernisation of the functions implemented by such institutes as business, public authority, financial, and non-commercial sector during the armed conflict of 2014-2021 and the special military operation. Results and discussion. After its inclusion into the Russian Federation, the institutional support of the development of the Donbas requires a fundamental transformation in order to adapt to new conditions. The transformation should involve a comprehensive transformation of the social and economic model of the region and its infrastructure, diversification, and modernisation of the development institutes. At the same time, it is necessary to take into account the weaknesses of the institutional system of the region. They include external threats caused by the armed conflict which started in 2014 and caused damage to the business institute; a dramatic reduction in the number of stimuli for the functioning of financial institutes, especially for the innovative and investment activities; underdevelopment of non-commercial organisations; and a high level of bureaucracy in public institutions. The new institutional model should be aimed at decreasing the vulnerability of the region to geopolitical and economic crises and its dependence on heavy industry and coal mining, while developing high-tech industries and innovations, and investing in education, healthcare, and the retraining of the labour force. It is therefore necessary to develop reasonable adaptation strategies and programmes, including appointing responsible executives to the governmental and municipal bodies and developing mechanisms for the financing of projects aimed at the economic growth and well-being of the population.

Energy state of the electronic subsystem of porous carbon material caused by laser irradiation

The changes in the electronic subsystem of a porous carbon material caused by its doping with Mn, Cr, and Fe and laser irradiation were studied by the method of electron paramagnetic resonance. It has been found that Mn doping leads to the appearance of several paramagnetic centers, and laser irradiation facilitates the redistribution of electrons between different states so that their mobility increases due to the transition from the g = 3.9 to the g = 6.0 state. The Mössbauer spectroscopy of porous Fe-doped carbon material indicates the presence of oxygen ligands for iron ions, in particular the formation of octa- and tetra-complexes with redistribution of electron density between iron and oxygen nuclei, and, accordingly, changes in the degree of covalence of the chemical bond from Fe3+ to Fe2+.

DESIGN THINKING IN THE VISUALIZATION OF ECONOMIC DEVELOPMENT PROJECTS IN THE AGRARIAN SPHERE: SCIENCE AND ART

The article represents an attempt to comprehend the possibilities of applying general methodological principles of design thinking in the process of planning and developing innovative economic development projects in the agricultural sector. The relations of design and visualization as the science and art processes in the economy are outlined. It is noted that smart agriculture uses advanced technologies such as sensors, devices, machines and information technology, robots, GPS technologies, which will allow farms to be more profitable, efficient, safe, and environmentally friendly. The authors claim that the goal of digitalization of agriculture is to achieve a significant increase in the efficiency and sustainability of its functioning through fundamental changes in the quality of management of both technological processes and decision-making processes at all levels of the hierarchy, based on modern production methods, and the further use of information about the state of controlled elements and subsystems, as well as states of the economic environment of agriculture. Based on a study of the use of visualization technologies within the framework of the philosophy of design thinking, it is shown that the introduction of digital technologies in the agro-industrial complex will dramatically increase labor productivity and reduce risks in agriculture. In modern conditions of intense competition, digitalization based on such projects will give the agricultural sector of any country (which is especially important for developing countries) great competitive advantages.

Prognostic and Health Management of Critical Aircraft Systems and Components: An Overview.

Prognostic and health management (PHM) plays a vital role in ensuring the safety and reliability of aircraft systems. The process entails the proactive surveillance and evaluation of the state and functional effectiveness of crucial subsystems. The principal aim of PHM is to predict the remaining useful life (RUL) of subsystems and proactively mitigate future breakdowns in order to minimize consequences. The achievement of this objective is helped by employing predictive modeling techniques and doing real-time data analysis. The incorporation of prognostic methodologies is of utmost importance in the execution of condition-based maintenance (CBM), a strategic approach that emphasizes the prioritization of repairing components that have experienced quantifiable damage. Multiple methodologies are employed to support the advancement of prognostics for aviation systems, encompassing physics-based modeling, data-driven techniques, and hybrid prognosis. These methodologies enable the prediction and mitigation of failures by identifying relevant health indicators. Despite the promising outcomes in the aviation sector pertaining to the implementation of PHM, there exists a deficiency in the research concerning the efficient integration of hybrid PHM applications. The primary aim of this paper is to provide a thorough analysis of the current state of research advancements in prognostics for aircraft systems, with a specific focus on prominent algorithms and their practical applications and challenges. The paper concludes by providing a detailed analysis of prospective directions for future research within the field.

Quantized H∞$$ {H}_{\infty } $$ output feedback control for uncertain impulsive switched systems via a hybrid control approach

SummaryThis article investigates the quantized dynamical output feedback (DOF) control problem for uncertain impulsive switched systems (ISSs) with multiple state impulsive jumps, where the static quantization strategy is applied to quantize the control input to improve the signal transmission capacity of ISSs. First, to correspond the abrupt changes for states of ISSs at switching moments, the controller states are also allowed to jump besides the system state jumps of ISSs, which increases the universality of the impulsive behavior in ISSs. Second, the multiple Lyapunov functions approach and the average dwell time switching strategy are applied to derive the sufficient conditions that guarantee the stability and weighted performance of the closed‐loop uncertain ISSs. The desired hybrid controllers comprising of DOF controllers for every subsystem and controller state update rules at switching instants can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example is provided to verify the effectiveness of the obtained results.

Device Health Status Assessment Under the Influence of Multiple Exception Modes

Equipment reliability is the key feature to ensure the equipment operation for a long time. It is difficult to determine the overall reliability of industrial equipment due to the different reliability states of different subsystems. A device abnormality identification method based on JS (Jenson's Shannon) divergence and a health status assessment technology based on FMECA (failure mode, effect and criticality analysis) are proposed. This method enables an accurate assessment of the current health status of the device. First, the historical operation data is preprocessed according to the characteristics of the equipment to improve the data quality. The JS divergence method is reused to extract the similarity between the key feature data distribution and the benchmark data distribution. Then, the FMECA report is established using the real running data of the device combined with expert experience. Gray theory was used to determine the degree of association between one-way health state membership vector and different health state rank vector. Finally, the health status level was comprehensively evaluated by the fuzzy membership method. Taking the mechanical arm component of a 100-ton crane as an example, the results show that this method can effectively evaluate the current health state of the equipment, and provide power for the abnormal advance disposal and auxiliary management decisions.

Two-stage multirate state feedback control designs for systems with slow and fast eigenvalue modes

Design of feedback control, for a system with slow and fast eigenvalue modes, using single sampling rate results in either information loss (for a larger sampling period) or increased computations (for a smaller sampling period). This paper contributes to designing multirate state feedback controllers for such systems. In this, it is shown that the feedback control for a linear time-invariant system, having slow and fast eigenvalue modes, can be successfully designed by multirate sampling of states in two stages. Multirate sampling refers to sampling slow- and fast-varying states at different rates, that is sampling slow states at a lower rate than the fast states. Here, two approaches for multirate sampling of states are presented, depending on the sampling sequence. In the first approach, fast subsystem states are sampled initially, and then, slow subsystem states are sampled, whereas in the second approach, slow subsystem states are sampled before sampling the fast subsystem states. As far as the two-stage design is concerned, the first stage of the design of feedback control is initiated just after sampling the first subsystem. Then, the left subsystem is sampled, and the second stage of the design of feedback control is accomplished. It is proved that the feedback controls derived with the multirate sampling of states stabilize the full-order system in both approaches. The design and implementation aspects of both approaches are compared. Finally, the applicability of the proposed control is demonstrated by simulating two examples. Simulations are also compared with other methods proposed in the literature.

Phase transitions in chiral ferromagnets with topological features of electronic structure (on the example of MnSi)

Magnetic and topological electronic (TEP) phase transitions in chiral ferromagnets with the Dzyaloshinskii-Moriya (DM) interaction are considered. We consider the example of a chiral helical ferromagnet MnSi with a large Berry curvature of the Fermi surface. It is shown that the state of the spin subsystem with a ferromagnetic short-range order and with Berry phases arises as a result of a first-order transition from a helicoidal ferromagnetic phase with increasing temperature. This state is characterized by left-handed vortex microstructures and manifests itself through the topological Hall effect. In the region of the paramagnetic short-range order, vortex microstructures of both signs of spin chirality arise, which leads to the experimentally observed pattern of partial chirality. With an increase in temperature, TEP appears in the chiral paramagnetic state due to that the chemical potential leaves the region of the electronic spectrum with Berry curvature. As a result, the local magnetization and chiral interaction of the DM disappear. A quantitative agreement has been obtained between the calculations of the temperature dependence of the spin magnetic susceptibility and experimental data.