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The general epidemic process (GEP), also known as susceptible-infected-recovered model, provides a minimal model of how an epidemic spreads within a population of susceptible individuals who acquire permanent immunization upon recovery. This model exhibits a second-order absorbing state phase transition, commonly studied assuming immobile healthy individuals. We investigate the impact of mobility on the scaling properties of disease spreading near the extinction threshold by introducing two generalizations of GEP, where the mobility of susceptible and recovered individuals is examined independently. In both cases, including mobility violates GEP's rapidity reversal symmetry and alters the number of absorbing states. The critical dynamics of the models are analyzed through a perturbative renormalization group (RG) approach and large-scale stochastic simulations using a Gillespie algorithm. The RG analysis predicts both models to belong to the same novel universality class describing the critical dynamics of epidemic spreading when the infected individuals interact with a diffusive species and gain immunization upon recovery. At the associated RG fixed point, the immobile species decouples from the dynamics of the infected species, dominated by the coupling with the diffusive species. Numerical simulations in two dimensions affirm our RG results by identifying the same set of critical exponents for both models. Violation of the rapidity reversal symmetry is confirmed by breaking the associated hyperscaling relation. Our study underscores the significance of mobility in shaping population spreading dynamics near the extinction threshold. [ABSTRACT FROM AUTHOR]

Forward–backward doubly stochastic differential equations (FBDSDEs) serve as a probabilistic interpretation of stochastic partial differential equations (SPDEs) with diverse applications. Coupled FBDSDEs encounter numerous challenges in numerical approximation compared to forward–backward stochastic differential equations (FBSDEs) and decoupled FBDSDEs, including ensuring the measurability of the numerical solutions, accounting for the mutual influences between forward and backward processes, and considering the relationship with respect to SPDEs rather than PDEs. This paper introduces, for the first time, a numerical method for solving multi-dimensional coupled FBDSDEs. By integrating an optimal control-based approach with deep neural networks, it effectively addresses the coupling-related challenges between forward and backward equations. Computational examples of coupled FBDSDEs with explicit solutions demonstrate that the proposed deep learning-based numerical algorithm achieves commendable performance in terms of both accuracy and efficiency. [ABSTRACT FROM AUTHOR]

The low-harmonic (LOH) voltage of the DC link of three-phase voltage source converter (VSC) requires a large aluminum electrolytic capacitor for suppression under nonlinear AC current. Consequently, this work proposes an active decoupling control method combining DC-link LOH voltage closed loop and LOH current feedforward based on a DC–DC converter. This methodology effectively transfers the DC-link LOH voltage to the smaller-sized decoupling capacitor in the DC–DC converter, thereby reducing the number of capacitors required to stabilize of the VSC DC-link voltage. This work first investigates the relationship between the DC-link LOH voltage and the VSC nonlinear current. Second, a mathematical model for the decoupling capacitor voltage is derived, indicating that its voltage form is complex under nonlinear AC current, making direct voltage control arduous. Subsequently, the principle and design process of the proposed active decoupling control strategy are analyzed in detail. A dedicated fast-response filter structure is also utilized to extract the feedback LOH voltage and feedforward LOH current in the DC link. Meanwhile, a simple control strategy for the DC component of the decoupling capacitor voltage is proposed to improve the utilization of the decoupling capacitor. Finally, the effectiveness and correctness of the method are experimentally verified. [ABSTRACT FROM AUTHOR]

Aiming at the coupling problem of target detection with few shot intensification, a few shot target detection algorithm based on decoupling is proposed focusing on high-value air targets as the research object. Firstly, a gradient adjustment layer is introduced into the regional candidate network to strengthen the regional candidate network and alleviate the task coupling problem. Secondly, the target detection head is disassembled into two branches, classification and regression, and a parameter free average attention module is added at the front end to alleviate the feature coupling problem. The proposed algorithm improves the detection performance of few shot target detection and enhances the detection ability of new classes. The experimental results show that the proposed algorithm performs best in the 1, 2, 3, 5 and 10 shot experiments, with average accuracy of 32. 5%, 35. 6%, 39. 6%, 41. 2% and 57. 4%, respectively. Compared with the two-stage fine- tuning method, the detection performance of the proposed algorithm is greatly improved, which solves the problem of the deliine of network detection ability under the coupling contradiction of few shot intensification, and improves the detection accuracy of few shot high-value air targets. [ABSTRACT FROM AUTHOR]

Remote Sensing Image Object Detection (RSIOD) faces the challenges of multi-scale objects, dense overlap of objects and uneven data distribution in practical applications. In order to solve these problems, this paper proposes a YOLO-ACPHD RSIOD algorithm. The algorithm adopts Adaptive Condition Awareness Technology (ACAT), which can dynamically adjust the parameters of the convolution kernel, so as to adapt to the objects of different scales and positions. Compared with the traditional fixed convolution kernel, this dynamic adjustment can better adapt to the diversity of scale, direction and shape of the object, thus improving the accuracy and robustness of Object Detection (OD). In addition, a High-Dimensional Decoupling Technology (HDDT) is used to reduce the amount of calculation to 1/N by performing deep convolution on the input data and then performing spatial convolution on each channel. When dealing with large-scale Remote Sensing Image (RSI) data, this reduction in computation can significantly improve the efficiency of the algorithm and accelerate the speed of OD, so as to better adapt to the needs of practical application scenarios. Through the experimental verification of the RSOD RSI data set, the YOLO-ACPHD model in this paper shows very satisfactory performance. The F1 value reaches 0.99, the Precision value reaches 1, the Precision-Recall value reaches 0.994, the Recall value reaches 1, and the mAP value reaches 99.36 % , which indicates that the model shows the highest level in the accuracy and comprehensiveness of OD. [ABSTRACT FROM AUTHOR]

The cross-line operation (CO) of trains in urban rail transit is an effective method to efficiently satisfy transfer passenger travel demand as well as relieve the pressure of transfer stations. The primary problem of CO is designing train services to satisfy travel demand with an uneven spatial distribution of passengers. This study constructs a nonlinear integer programming model with a novel train operation scheme, i.e., virtual coupling (VC) technology, which allows the coupling/decoupling of trains on different lines at both ends of each operation zone. This scheme makes the train capacity equitably distributed in each operation zone, thereby balancing train capacity utilization over the whole CO system. Regarding the nonlinear characteristics of the proposed model, an adaptive simulated annealing genetic algorithm (ASA-GA) was designed to quickly generate high-quality solutions. Based on real-world data from the Beijing Changping Line and Line 13, the effectiveness of the proposed model and algorithm were verified. The computation results show that in comparison to a single grouping train composition scheme without CO, a VC scheme with CO would reduce operation costs by 46.8%, with 80.6% savings of train capacity equity. Furthermore, the average passenger residence time would be reduced by 25.9%. [ABSTRACT FROM AUTHOR]

In this paper, we study a kind of optimal control problem for forward-backward stochastic differential equations (FBSDEs for short) of McKean–Vlasov type via the dynamic programming principle (DPP for short) motivated by studying the infinite dimensional Hamilton–Jacobi–Bellman (HJB for short) equation derived from the decoupling field of the FBSDEs posed by Carmona and Delarue (2015) [28]. At the beginning, the value function is defined by the solution to the controlled BSDE alluded to earlier. On one hand, we can prove the value function is deterministic function with respect to the initial random variable; On the other hand, we can show that the value function is law-invariant , i.e., depending on only via its distribution by virtue of BSDE property. Afterward, utilizing the notion of differentiability with respect to probability measures introduced by P.L. Lions [50] , we are able to establish a DPP for the value function in the Wasserstein space of probability measures based on the application of BSDE approach, particularly, employing the notion of stochastic backward semigroups associated with stochastic optimal control problems and Itô formula along a flow property of the conditional law of the controlled forward state process. We prove that the value function is the unique viscosity solutions of the associated generalized HJB equations in some separable Hilbert space. Finally, as an application, we formulate an optimal control problem for linear stochastic differential equations with quadratic cost functionals of McKean-Vlasov type under nonlinear expectation, g -expectation introduced by Peng [43] and derive the optimal feedback control explicitly by means of several groups of Riccati equations. [ABSTRACT FROM AUTHOR]

In this paper, a state-space method for double-beam systems with variable cross sections is developed, making it possible to calculate the transverse vibration of the double-beams accurately and effectively. Due to the variability in the double-beam cross sections with the viscoelastic interlayer in between, the governing equations of vibration for the systems become highly coupled partial differential equations, making the problem difficult to solve. A basic double-beam system is introduced to modify the original governing equations to two inhomogeneous differential equations. Given the separation of variables, several mode-shape coefficients and a state variable are defined to construct the state-space equations. The coupling terms and variables are transferred into the constant coefficient matrix of the state-space equations, decoupling them. Numerical procedures are presented to solve the state-space equations to obtain homogenous and inhomogeneous solutions, including the natural frequencies and mode shapes in free vibration and the dynamic responses in forced vibration, respectively. The method has substantial advantages in decoupling high-order partial differential equations and can be further extended to solve complex structural systems. Numerical results also demonstrate that the method is accurate and efficient. Finally, an engineering application with a rail-bridge with a floating slab track is discussed in detail with the method. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new method based on a library of chemical reactions for constructing a system of ordinary differential equations from stochastic simulations arising from an agent-based model. The advantage of this approach is that this library respects any coupling between systems components, whereas the SINDy algorithm (introduced by Brunton et al.) treats the individual components as decoupled from one another. Another advantage of our approach is that we can use a non-negative least squares algorithm to find the non-negative rate constants in a very robust, stable and simple manner. We illustrate our ideas on an agent-based model of tumour growth on a 2D lattice. [ABSTRACT FROM AUTHOR]

The discrepancy in data distribution between training and testing scenarios, as well as the inductive bias of convolutional neural networks towards image styles, reduces the model's generalization ability. Many unsupervised domain generalization methods based on feature decoupling suffer from an initial neglect of explicit decoupling of content and style features, resulting in content features that still contain considerable redundant information, thereby restricting improvements in generalization capability. To tackle this problem, this paper optimizes the learning process of domain‐invariant (content) features into an information compression issue, minimizing redundancy in content features. Furthermore, to enhance decoupled learning, this paper introduces innovative cross‐domain loss functions and image reconstruction modules that explicitly decouple and merge content and style across different domains. Extensive experiments demonstrate the method's significant enhancements over recent cutting‐edge approaches. [ABSTRACT FROM AUTHOR]

Various problems on reducing a system of linear differential equations to several independent lower-order subsystems are overviewed. The construction of auxiliary square matrices for which similarity transformation is applied is substantiated. This allows the results obtained for the problem of reducing two square matrices to be transferred to different classes of problems: obtaining the maximum possible number of blocks, proof of the uniqueness of the obtained decoupling, revealing the hidden symmetry of the system under study, detecting the loosely coupled subsystems, and creating efficient computational decoupling algorithms. [ABSTRACT FROM AUTHOR]

As a typical nonlinear control method, backstepping control can decouple the mathematical model of permanent magnet synchronous motors. In addition, permanent magnet synchronous motor control systems based on the backstepping method can enhance the control performance of the control system to a certain extent. Furthermore, the design step is easy and simple to implement in engineering practice. However, the long-term wear and tear, aging, high temperature caused by changes in the basic parameters of motor and external load sudden changes as well as other factors will bring interference to the control system, leading to reduced-control accuracy and control performance degradation. To solve this problem, this paper suggests a control strategy combining backstepping control and fuzzy control based on backstepping control. It sets the load adaptive law and utilizes fuzzy control to make online real-time adjustments to the control parameters in the backstepping control. This is done to improve the immunity of interference and stability of the control system in response to the changes in the parameters of the body of the motor and sudden changes of the load. The effectiveness and feasibility of this system is verified by MATLAB simulation and experimental results, which provides a feasible solution for permanent magnet synchronous motor immunity and high-precision control occasions. [ABSTRACT FROM AUTHOR]

The Telecom Infra Project Open Optical & Packet Transport (TIP OOPT) carries out activities aimed at decoupling hardware and software and accelerating innovation in optical and IP networks. This article focuses on the TIP Phoenix Project, in which operators are working together to present common use cases and specifications to encourage the entry of new vendors and reduce costs. The background of the project, efforts to date, and contribution of the NTT Group are explained. [ABSTRACT FROM AUTHOR]

Dynamical decoupling (DD) is a promising technique for mitigating errors in near-term quantum devices. However, its effectiveness depends on both hardware characteristics and algorithm implementation details. This paper explores the synergistic effects of dynamical decoupling and optimized circuit design in maximizing the performance and robustness of algorithms on near-term quantum devices. By utilizing eight IBM quantum devices, we analyze how hardware features and algorithm design impact the effectiveness of DD for error mitigation. Our analysis takes into account factors such as circuit fidelity, scheduling duration, and hardware-native gate set. We also examine the influence of algorithmic implementation details, including specific gate decompositions, DD sequences, and optimization levels. The results reveal an inverse relationship between the effectiveness of DD and the inherent performance of the algorithm. Furthermore, we emphasize the importance of gate directionality and circuit symmetry in improving performance. This study offers valuable insights for optimizing DD protocols and circuit designs, highlighting the significance of a holistic approach that leverages both hardware features and algorithm design for the high-quality and reliable execution of near-term quantum algorithms. [ABSTRACT FROM AUTHOR]

This article investigates the finite horizon linear quadratic gaussian (LQG) control problem for networked control systems with two‐way Markovian packet dropouts and input delay, where packet dropouts occur from the sensor to the estimator and from the controller to the actuator, and delay occurs from the controller to the actuator. The novelty of this work lies in providing a complete solution for the optimal control problem subject to two‐way Markovian packet dropouts and input delay. The contributions of this article are as follows: first, by applying the maximum principle to the discrete‐time linear systems and the quadratic cost function involving input delay and Markovian packet dropouts, a solution to the forward and backward stochastic difference equations (FBSDEs) is derived. Second, a sufficient and necessary condition for the optimal control problem is obtained by decoupling the coupled Riccati equations. Finally, the explicit solution of the optimal controller is presented based on the complete square method. Numerical examples are provided to demonstrate the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for the construction of bulk–surface splitting schemes for semilinear parabolic partial differential equations with dynamic boundary conditions. The proposed construction is based on a reformulation of the system as a partial differential–algebraic equation and the inclusion of certain delay terms for the decoupling. To obtain a fully discrete scheme, the splitting approach is combined with finite elements in space and a backward differentiation formula in time. Within this paper, we focus on the second-order case, resulting in a |$3$| -step scheme. We prove second-order convergence under the assumption of a weak CFL-type condition and confirm the theoretical findings by numerical experiments. Moreover, we illustrate the potential for higher-order splitting schemes numerically. [ABSTRACT FROM AUTHOR]

In this paper, we prove Strichartz estimates for many body Schrödinger equations in the periodic setting, specifically on tori 핋 d {\mathbb{T}^{d}} , where d ≥ 3 {d\geq 3} . The results hold for both rational and irrational tori, and for small interacting potentials in a certain sense. Our work is based on the standard Strichartz estimate for Schrödinger operators on periodic domains, as developed in [J. Bourgain and C. Demeter, The proof of the l 2 l^{2} decoupling conjecture, Ann. of Math. (2) 182 2015, 1, 351–389]. As a comparison, this result can be regarded as a periodic analogue of [Y. Hong, Strichartz estimates for N-body Schrödinger operators with small potential interactions, Discrete Contin. Dyn. Syst. 37 2017, 10, 5355–5365] though we do not use the same perturbation method. We also note that the perturbation method fails due to the derivative loss property of the periodic Strichartz estimate. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions in the building sector is crucial to achieving carbon peak and carbon neutrality goals. Identifying the influencing factors of carbon emissions from building operations at the city level and predicting carbon peaks is of great significance for developing locally adapted policies. This article examines the spatial and temporal trends of carbon emissions at the building operation stage in the Yangtze River Delta (YRD) region over the last 15 years. This article analyzes the driving factors at a city level using the GDIM method and evaluates the decoupling status of income growth and carbon emissions with the GDIMbased decoupling model. The peak time and peak value of operational carbon emissions in the YRD region are predicted through a combination of scenario analysis and the Monte Carlo method. The research shows that: (1) the total carbon emissions from the building operational stage in the YRD region increased by 163.63%, of residents' disposable income and energy consumption contributed the most. (2) In terms of decoupling relationship between carbon emissions and income growth, rural residential buildings (RR) outperform urban residential buildings (UR) and public buildings (PB). (3) According to the dynamic simulation, the operational carbon emission in the YRD region is expected to peak at 498.18-504.83 Mt MtCO2 between 2030 and 2035. (4) The peak of PBs and URs in Nanjing, Suzhou and some third- and fourth-tier cities, and RRs in eastern and central cities in the YRD will occur at the latest, necessitating close monitoring. These findings can serve as a basis for developing scientific and reasonable building emission reduction policies in a multilevel governance context. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low accuracy and slow detection rate of existing target detection algorithms for PCB defect detection, and too many parameters of algorithm model leading to the inability to deploy on mobile terminals, a PCB defect detection algorithm based on MSD-YOLOv5 is proposed. Firstly, to ensure both detection accuracy and speed while reducing the model's size,we combine the lightweight MobileNet-v3 network with the CSPDarknet53 network. Further,the attention mechanism is introduced to highlight the important feature channels and weaken the less useful ones, so as to improve the feature extraction ability of the network. Finally, the coupling detection head is replaced with a decoupling detection head, and the defect location information and category information on the PCB are extracted and learned respectively, which solves the problem of highly coupling of different information feature distributions and enhances the generalization ability of the model. We conduct experiments on a publicly available PCB defect dataset from Peking University using this algorithm. The results show that the proposed method reduces the parameters of YOLOv5 model by 46% and improves the detection accuracy by 3.34%. [ABSTRACT FROM AUTHOR]

One of the main concerns in designing control structures for Voltage Source Inverters (VSI) is ensuring the generation of sinusoidal currents that comply with international power quality standards. In this context, the present study investigates the evaluation of multivariable control techniques characterized by their Deadbeat nature, within coordinates dq. One of these techniques incorporates a virtual emulation of the current loop filter behavior. The application of these controllers is demonstrated in the context of a three-phase VSI connected to the electrical grid. These controllers not only show their effectiveness in decoupling control loops but also have greater stability without the presence of phase delays. With a specific emphasis on developing and fine-tuning multivariable Deadbeat controllers using dq coordinates, the study leverages three distinct models to analyze the stability and evaluate the performance of the control strategy. The synthesis of system models and consequently of controllers was made possible by the α β and dq coordinate conversion method, developed in this study. This tool holds significant potential not only in synthesis but also in system analysis. The simulated solar setup uses a 5.1 kW photovoltaic system with second-generation modules. It includes an internal current loop, an external energy loop, and a multi-level VSI controlled by Space Vector Pulse Width Modulation (SVPWM). This complex combination of elements serves as the context for the tested control strategies, undergoing thorough testing and evaluation. [ABSTRACT FROM AUTHOR]

We investigate a fully discrete modular grad-div (MGD) stabilization algorithm for solving the incompressible micropolar Navier-Stokes equations (IMNSE) model, which couples the incompressible Navier-Stokes equations and the angular momentum equation together. The mixed finite element (FE) method is applied for the spatial discretization. The time discretization is based on the BDF2 implicit scheme for the linear terms and the two-step linearly extrapolated scheme for the convective terms. The considered algorithm constitutes two steps, which involve a post-processing step for linear velocity. First, we decouple the fully coupled IMNSE model into two smaller subphysics problems at each time step (one is for the linear velocity and pressure, the other is for the angular velocity), which reduces the size of the linear systems to be solved and allows for parallel computing of the two sub-physics problems. Then, in the post-processing step, we only need to solve a symmetrical positive determined grad-div system of linear velocity at each time step, which does not increase the computational complexity by much. However, the post-processing step can improve the solution quality of linear velocity. Moreover, we obtain unconditional stability, and error estimates of the linear velocity and angular velocity. Finally, several numerical experiments involving threedimensional and two-dimensional settings are used to validate the theoretical findings and demonstrate the benefits of the modular grad-div (MGD) stabilization algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a multi-frequency MIMO antenna for 5G and Wi-Fi 6E is presented. The antenna uses a cosine-shape monopole and split-ring resonator (SRR) structure for tri-band radiation, and frequency band expansion is achieved through SRR, folded split-ring resonators (FSRR) and Archimedean spiral metasurfaces for decoupling, with which a combination of surface wave and space wave decoupling is achieved. The Archimedean spiral metasurface unit can achieve space wave decoupling in the tri-band. By adopting the method of combining space wave decoupling and surface wave decoupling, the miniature antenna is achieved. The measured results closely align with the simulated results. Specifically, maintaining a reflection coefficient of −10 dB, the measured results indicate an increase in isolation of 3.5 dB, 36.47 dB, and 6.42 dB for the frequency bands of 3.45–3.55 GHz, 5.7–5.9 GHz, and 6.75–7 GHz, respectively. Additionally, the MIMO antenna demonstrates an average efficiency of approximately 89%, with an average envelope correlation coefficient (ECC) of 0.0025. Furthermore, the antenna's peak gain increases by 4.3 dB at 3.5 GHz, 3.8 dB at 5.8 GHz, and 1.9 dB at 6.9 GHz upon integrating the metasurface. The proposed method and structure are anticipated to contribute significantly to decoupling in multi-frequency MIMO antennas. [ABSTRACT FROM AUTHOR]

The present paper is concerned with exploiting an iterative decoupling algorithm to address the problem of third-order tensor deblurring. The regularized deblurring problem, which is mathematically given by the sum of a fidelity term and a regularization term, is decoupled into an observation fidelity and a denoiser model steps. One basic advantage of the iterative decoupling algorithm is that the deblurring problem is supervised by the efficiency of the denoiser model. Thus, we consider a patch-based weighted low-rank tensor with sparsity prior. Numerical tests to image deblurring are given to demonstrate the efficiency of the proposed decoupling based algorithm. [ABSTRACT FROM AUTHOR]

This paper focuses on investigating a second-order time parallel decoupled algorithm for the mixed Stokes/Darcy model. The main objective of this algorithm is to deal with the issue of low computational efficiency in solving the coupling problem directly. Our scheme not only reduces the computation scale through the decoupling method, but also realizes the parallelism in the time direction through parareal method. Furthermore, we implement a second-order spectral deferred correction method to improve accuracy. For some small time step size, we prove the stability and convergence results of the time parallel decoupled algorithm. Finally, we provide three numerical tests to demonstrate the reliability and computational efficiency of our algorithm. [ABSTRACT FROM AUTHOR]

Coupled multi-physics problems are encountered in countless applications and pose significant numerical challenges. In a broad sense, one can categorise the numerical solution strategies for coupled problems into two classes: monolithic approaches and sequential (also known as split, decoupled, partitioned or segregated) approaches. The monolithic approaches treat the entire problem as one, whereas the sequential approaches are iterative decoupling techniques where the different sub-problems are treated separately. Although the monolithic approaches often offer the most robust solution strategies, they tend to require ad-hoc preconditioners and numerical implementations. Sequential methods, on the other hand, offer the possibility to add and remove equations from the model flexibly and rely on existing black-box solvers for each specific equation. Furthermore, when problems are non-linear, inner iterations need to be performed even in monolithic solvers, making the sequential approaches an even more viable alternative. The cost of running inner iterations to recover the multi-physics coupling could, however, easily become prohibitive. Moreover, the sequential approaches might not converge at all. In this work, we present a general formulation of splitting schemes for continuous operators with arbitrary implicit/explicit splitting, like in standard iterative methods for linear systems. By introducing a generic relaxation operator, we find the conditions for the convergence of the iterative schemes. We show how the relaxation operator can be thought of as a preconditioner and constructed based on an approximate Schur complement. We propose a Schur-based Partial Jacobi relaxation operator to stabilise the coupling and show its effectiveness. Although we mainly focus on scalar-scalar linear problems, most results are easily extended to non-linear and higher-dimensional problems. The schemes presented are not explicitly dependent on any particular discretisation methodologies. Numerical tests (1D and 2D) for two PDE systems, namely the Dual-Porosity model and a Quad-Laplacian operator, are carried out to investigate the practical implications of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper highlights the design of a controller established on estimated states for one-sided Lipschitz (OSL) nonlinear systems subject to output and input delays. The controller has been devised by involving Luenberger-like estimated states. The stability of the time-delayed nonlinear system is reckoned by assuming a Lyapunov functional for delayed dynamics and for which a delay-range dependent criterion is posed with a delay ranging between known upper and lower bounds. The time derivative of the functional is further exploited with linear matrix inequality (LMI) procedures, and employing Wirtinger's inequality for the integral terms instead of the traditional and more conservative Jensen's condition. Moreover, a sufficient and necessary solution is derived for the proposed design by involving the tedious decoupling technique to attain controller and observer gain simultaneously. The proposed methodology validates the observer error stability between observers and states asymptotically. The solution of matrix inequalities was obtained by employing cone-complementary linearization techniques to solve the tiresome constraints through simulation tools by convex optimization. Additionally, a novel scheme of an observer-based controller for the linear counterpart is also derived for one-sided Lipschitz nonlinear systems with multiple delays. Finally, the effectualness of the presented observer-based controller under input and output delays for one-sided Lipschitz nonlinear systems is validated by considering a numerical simulation of mobile systems in Cartesian coordinates. [ABSTRACT FROM AUTHOR]

Some efficient temporal first-, second- and higher-order numerical schemes are constructed for the coupled nonlinear Schrödinger-Boussinesq (CNSB) equations based on discretizing the Hamiltonian formula by an exponential method in a compact representation, discrete gradient method and composition method. The schemes are fully decoupling of the three solution components, which is distinct from the partially decoupled scheme in the literature, and their compact representation reduces the storage requirement and operation count. Rigorous analyses are carried out to show the exact preservation of the discrete energy for the proposed schemes. Numerical experiments verify the theoretical results and confirm the satisfactory solution accuracy and excellent efficiency of the present schemes. [ABSTRACT FROM AUTHOR]

The decoupling of control and forwarding layers brings Software-Defined Networking (SDN) the network programmability and global control capability, but it also poses SDN security risks. The adversaries can use the forwarding and control decoupling character of SDN to forge legitimate traffic, launching saturation attacks targeted at SDN switches. These attacks can cause the overflow of switch flow tables, thus making the switch cannot forward benign network traffic. How to effectively detect saturation attack is a research hotspot. There are only a few graph-based saturation attack detection methods. Meanwhile, the current graph generation methods may take useless or misleading information to the attack detection, thus decreasing the attack detection accuracy. To solve the above problems, this paper proposes TITAN, a bidirecTional forwardIng graph-based saturaTion Attack detectioN method. TITAN defines flow forwarding rules and topology information, and designs flow statistical features. Based on these definitions, TITAN generates nodes of the bi-forwarding graph based on the flow statistics features and edges of the bi-forwarding graph based on the network traffic routing paths. In this way, each traffic flow in the network is transformed into a bi-directional forwarding graph. Then TITAN feeds the above bidirectional forwarding graph into a Graph Convolutional Network (GCN) to detect whether the flow is a saturation attack flow. The experimental results show that TITAN can effectively detect saturation attacks in SDNs with a detection accuracy of more than 97%. [ABSTRACT FROM AUTHOR]

In this work, a polarization rotating surface is designed, analyzed, and applied to the decoupling of ultra-wideband antennas. A method of using dual-size combined rings is proposed to expand the operating bandwidth to 4.8 to 18.2 GHz, and the polarization conversion rate within the entire bandwidth is higher than 99%. Based on the principle of polarization mismatch, placing the polarization rotating surface between ultra-wideband antennas for decoupling can reduce the coupling between antennas by an average of 20 dB within the operating bandwidth. Simulation and experimental results consistently prove its excellent decoupling capabilities and ultra-wide operating bandwidth. [ABSTRACT FROM AUTHOR]

New energy and multiple loads, such as distributed wind-solar storage and charging, are connected to the distribution network through power electronic converters, which increases the harmonic content in the distribution network and causes operational safety risks. In this paper, the mathematical model of harmonic current and harmonic power content in a distribution network is constructed by an equivalent circuit and vector diagram. The distributed power flow controller is proposed for harmonic control of the distribution network. The mathematical expressions of the harmonic current and harmonic power based on a distributed power flow controller are constructed, and the control strategy of the distributed power flow controller for harmonic control is proposed. The simulation results show that the proposed method can effectively suppress the fifth and seventh harmonics of the distribution network. [ABSTRACT FROM AUTHOR]

In this paper, we intend to utilize the generalized scalar auxiliary variable (GSAV) approach proposed in recent paper (Ju et al., SIAM J. Numer. Anal., 60 (2022), 1905–1931) for the nonlocal coupled sine-Gordon equation to construct a class of fully decoupled, linear, and second-order accurate energy-preserving scheme. The unconditional unique solvability and discrete energy conservation law of the proposed scheme are rigorously discussed, and the unconditional convergence is then proved by the mathematical induction. Particularly, the convergence analysis covers the proposed scheme in multiple dimensions due to the corresponding nonlinear terms satisfy the global Lipschitz continuity straightforwardly. Finally, time evolution of dynamical behavior of the governing equation with different nonlocal parameters are observed, and ample numerical comparisons demonstrate that the proposed scheme manifests high efficiency in long-time computations. [ABSTRACT FROM AUTHOR]

Analysis of cylinders under axisymmetric loading is of great interest as it finds many practical application. In this work, an attempt has been made to solve this problem through variational principle. The variational statement results in a set of coupled partial governing equation and associated boundary conditions. The solution has been derived after systematic decoupling of governing equation, application of separation of variables and use of Frobenius method. The resulting solution as demonstrated is capable of satisfying all the boundary conditions in an exact sense. The accuracy and efficiency of the presented solution have been validated for problems available in the literature and against three-dimensional finite element simulations for isotropic homogeneous material. It is observed that the present solution not only has excellent agreement with three-dimensional finite element analysis but also is generic in nature. [ABSTRACT FROM AUTHOR]

Recently, a signal sorting algorithm based on the congruence transform has been proposed, which is effective in dealing with the staggered Pulse Repetition Interval (PRI) signals. It can effectively sort the staggered PRI signals and obtain the sub-PRI sequence directly without sub-PRI ranking, and it is less affected by interfered pulses and pulse loss. Nevertheless, we find that the algorithm causes pseudo-peaks in the remainder histogram when sorting signals such as sliding PRI, sinusoidal PRI, etc. (collectively referred to as periodic PRI signal in this paper) and pseudo-peaks will cause errors in signal sorting. To solve the issue of pseudo-peaks when sorting periodic PRI signals, an improved sorting algorithm based on congruence transform is proposed. According to the analysis of the congruence characteristics of the periodic PRI signal, a novel method is proposed to identify pseudo-peaks based on the histogram peak amplitude and symmetric difference set. The signal sorting algorithm based on congruence transform is improved to achieve a good sorting effect on periodic PRI signals. Simulation experiments demonstrate that the novel algorithm can effectively sort periodic PRI signals and improve Precall, Pd, and Pf by 6.9%, 5.1%, and 3.2%, respectively, compared to the typical similar algorithms. [ABSTRACT FROM AUTHOR]

In this work, we introduce a collision model specifically tailored for the simulation of inextensible textiles. The model considers friction, contacts, and inextensibility constraints all at the same time without any decoupling. Self-collisions are modeled in a natural way that allows considering the thickness of cloth without introducing unwanted oscillations. The discretization of the equations of motion leads naturally to a sequence of quadratic problems with inequality and equality constraints. In order to solve these problems efficiently, we develop a novel active-set algorithm that takes into account past active constraints to accelerate the resolution of unresolved contacts. We put to a test the developed collision procedure with diverse scenarios involving static and dynamic friction, sharp objects, and complex-topology folding sequences. Finally, we perform an experimental validation of the collision model by comparing simulations with recordings of real textiles as given by a Motion Capture System. The results are very accurate, having errors around 1 cm for DIN A2 textiles (42 x 59.4 cm) even in difficult scenarios involving fast and strong hits with a rigid object. In this work, we present a novel collision model for inextensible textiles and validate it experimentally through a comparison with real textiles as recorded by a Motion Capture System. In the figure we can see four frames comparing the recorded hitting with a stick of a DIN A2 (42 x 59.4 cm) polyester sheet (left) with its inextensible simulation (right); its average error being 1.44 cm. The recordings are obtained by attaching 20 reflective markers of diameter 3 mm and weight of 0.013 g to the real textile and following their trajectory. On the bottom, we show a full plot of the mean absolute error of the position of each marker with respect to its simulation and with yellow lines we highlight the moments in which the object is in contact with the cloth. Notice that the biggest errors appear not during the hits but just after because of aerodynamic effects. The above simulations, with a 7 × 9 mesh, are two times faster than real-time. Our custom active-set solver is three times faster than a standard interior-point method using the same mesh resolution. • We develop a cloth collision model which results in a coupled resolution of friction, inextensibility, and contact forces. • Self-collisions are modeled in a way that allows considering cloth's thickness without introducing unwanted oscillations. • An active-set solver for the system's integration is developed, which can start from any non-necessarily feasible point. • An empirical validation is performed, with scenarios involving high-friction surfaces and strong hits with a stick. [ABSTRACT FROM AUTHOR]

Summary: We are considering the problem of designing observers for heat partial differential equations (PDEs) that are subject to sensor delay and parameter uncertainty. In order to get finite‐dimensional observers, described by ordinary differential equations (ODE), we develop a design method based on the modal decomposition approach. The approach is extended so that both parameter uncertainty and sensor delay effects are compensated for. To cope more effectively with sensor delay, an output predictor is designed and the online provided output predictions are substituted to the future output values in the observer. To compensate for parameter uncertainty, we design a parameter estimator providing online parameter estimates, which are substituted to the unknown parameters in the observer. The parameter estimator design is made decoupled from the observer gain design by using an appropriate decoupling transformation. Using an analysis of the small‐gain‐theorem type, the whole (state and parameter) estimation error system is shown to be exponentially stable, under well‐defined conditions on the observer dimension, the sensor delay, and signal persistent excitation (PE). [ABSTRACT FROM AUTHOR]

By virtue of stochastic decoupling, the quantum evolution of a harmonic oscillator is converted into two virtual contributions dictated by either a stochastic creation operator or a stochastic annihilation operator. Two approaches are provided to resolve these virtual two evolution operators. One is based on the coherent-state representation and the other deals with the momentum representation after separating out the position and momentum factors. The quantum propagator of the harmonic oscillator is obtained by taking the random average of the combined virtual propagators. The main mathematical exercise of the whole procedure is the calculation of the Gaussian integral. [ABSTRACT FROM AUTHOR]

The metalized film capacitors (MFC) in converter valves are subjected to high-frequency currents under the action of power electronic switching, which will cause large differences in currents among capacitor elements inside MFC and seriously affect the stability of MFC. In this paper, experiments were conducted to measure the current waveforms among 90 elements under impulse, short-circuit discharge and sine waves at different frequencies. The equivalent circuit topology was simplified by using decoupling and controlled source equivalence, and parameters were extracted by electromagnetic calculations combined with experiments. Finally, an equivalent circuit model was established and the current distribution among elements was calculated. Influenced by the reactance of the parasitic inductor and the capacitor element, the frequency range can be divided into 3 regions based on the current distribution characteristics: in the high frequency range (>100 kHz), the current is mainly concentrated on several capacitor elements near the connection terminals. In the middle frequency range (about 10 kHz–100 kHz), the current oscillates between elements and the inductor, resulting in a wavy distribution of current amplitude, strongly influenced by frequency. In the low frequency range (<10 kHz), the current distribution varies very little among 90 elements. These results can support the study of performance evolution, fault analysis and design optimization in MFC. [ABSTRACT FROM AUTHOR]

For the nonlinear parameter‐varying (NPV) model of unmanned surface vehicle with the consideration of the velocities on yaw and surge as well as wave disturbances, a robust H∞$$ {H}_{\infty } $$ control method is proposed based on extended homogeneous polynomial Lyapunov function (EHPLF) to regulate heading for the superior performance on the rapidity, accuracy, and robustness. First, a NPV model of heading error is established to design a general form of a state feedback controller with a robust H∞$$ {H}_{\infty } $$ performance. Second, a Lyapunov matrix with full states and varying parameter is constructed to derive the robust H∞$$ {H}_{\infty } $$ global exponential stability conditions by Euler's homogeneity relation for the NPV system, known as the EHPLF stability conditions. Third, since the EHPLF stability conditions consist of a set of nonlinear coupled inequalities that cannot be directly solved by sum of squares (SOS) toolboxes, they are decoupled with matrix transformations to obtain the EHPLF‐SOS stability conditions, which is solved for the parameters of the state feedback controller. Finally, the simulation results indicate that EHPLF method exhibits a superior performance on dynamic, steady‐state, and robustness. [ABSTRACT FROM AUTHOR]

This paper is focused on the numerical approximations of the incompressible magneto-hydrodynamic equations. Our interest is to develop a novel decoupled, linear and unconditional energy stable fully-discrete scheme, which is achieved by the interior penalty discontinuous Galerkin (DG) method for spatial discretization, the stabilizing strategy and implicit-explicit (IMEX) scheme used to handle the nonlinear coupling terms, and a rotational pressure-correction method for the Navier-Stokes equations. We prove the unique solvability, unconditional energy stability and optimal error estimates of the proposed scheme rigorously. We further present several numerical examples to demonstrate the accuracy, stability, and efficiency of the proposed scheme numerically. [ABSTRACT FROM AUTHOR]

In this article, we propose a fully decoupled first-order time discrete scheme for the unsteady thermally coupled magnetohydrodynamics (MHD) equations with variable density, which is a large nonlinear strongly coupled system consisting of incompressible Navier-Stokes equations with variable density, heat equation and Maxwell equations. The proposed scheme is highly efficient because only the linearised subproblems need to be solved at the discrete level. Furthermore, unconditional stability analysis is established which is a vital issue in the field of multiphysics. We also construct and implement a fully discrete scheme based on conforming finite elements in space. Several 2D/3D numerical tests are conducted to confirm the efficiency and accuracy of the developed scheme with large density differences. [ABSTRACT FROM AUTHOR]

We prove an (l², L6) decoupling inequality for the parabola with constant (log R)c. In the appendix, we present an application to the sixth-order correlation of the integer solutions to x² + y² = m. [ABSTRACT FROM AUTHOR]

Purpose: Fault diagnosis for wind turbines can effectively reduce the impact of failures, ensuring the safe and reliable operation of machinery equipment significantly and avoiding significant maintenance costs. However, the features of composite faults in wind turbines are coupled under the influence of multiple vibration sources. Particularly, slight fault signals are generally covered by noise and strong fault signals, making them difficult to identify effectively Methods: An early composite fault diagnosis algorithm named Continuous Spectral Kurtosis Deconvolution (CSKD) is proposed in this paper by analyzing the phenomenon of multiple spectral kurtosis maxima in the fast kurtosis graph under the composite fault condition. According to the maximum spectral kurtosis in the fast kurtosis graph and its corresponding frequency and frequency resolution, a band-pass FIR filter model is established for deconvolution processing to obtain significant fault signals. The obtained fault signals are removed by the narrow-band band-stop filter to achieve the purpose of significantly decoupling the composite fault. Results: The proposed algorithm is verified by a typical model simulation and engineering application, with the composite fault of the inner and outer rings of the large-scale wind turbine bearing. Results show that the proposed algorithm can realize the decoupling of large-scale rotating machinery composite fault signals and extract slighter signal features in the early composite faults effectively. Conclusion: Results show that the proposed algorithm is able to provide a solution for composite fault diagnosis of wind turbines. The method can be extended to further consider more complex and practical cases. [ABSTRACT FROM AUTHOR]

We report better-than-classical success probabilities for a complete Grover quantum search algorithm on the largest scale demonstrated to date, of up to five qubits, using two different IBM platforms. This is enabled by error suppression via robust dynamical decoupling. Further improvements arise after the use of measurement error mitigation, but the latter is insufficient by itself for achieving better-than-classical performance. For two qubits, we demonstrate a 99.5% success probability via the use of the [[4, 2, 2]] quantum error-detection (QED) code. This constitutes a demonstration of quantum algorithmic breakeven via QED. Along the way, we introduce algorithmic error tomography (AET), a method that provides a holistic view of the errors accumulated throughout an entire quantum algorithm, filtered via the errors detected by the QED code used to encode the circuit. We demonstrate that AET provides a stringent test of an error model based on a combination of amplitude damping, dephasing, and depolarization. [ABSTRACT FROM AUTHOR]

Lighter-than-air (LTA) aerial vehicles such as airships and aerostats can be found in various strategic and commercial applications, primarily due to their capability to hover and stealth. The mathematical model of these vehicles helps in understanding their complex dynamics and designing and developing proper stabilisation systems for them. Stability derivatives have been used for developing mathematical models for heavier-than-air aerial vehicles since their introduction. This paper presents a methodology to develop a mathematical model of an aerostat based on stability derivatives. One of the major contributions of this study is the estimation of aerostat's added mass terms expressed as longitudinal stability derivatives due to acceleration of the longitudinal motion variables. A longitudinally decoupled linear mathematical model of a single-tethered aerostat using stability derivatives is investigated in this study. A computational fluid dynamics (CFD)-based analysis of the 3D model of the vehicle is used to obtain the stability derivatives. The methodology presented considers the aerostat and tether models separately before coupling them to create the full model. The stability derivative analysis is carried out using ANSYS Fluent, and the coupled tethered aerostat model is investigated using MATLAB 2020. The negative pitch angle of the aerostat is caused by the selection of the pitching centre as the aerostat centre of volume instead of the tether confluence point. The tension force on the tether, which is proportional to the wind velocity, and aerostat velocity components are found to be stabilised within 200–400 s. [ABSTRACT FROM AUTHOR]

The design of multivariable process control systems is specially complicated when there are strong interactions between the different control loops, and even more with multiple time delays. This paper proposes an iterative design method of centralized proportional-integral-derivative (PID) controllers for stable linear systems. The methodology is based on the linear parameterization of equivalent loop transfer functions (ELTFs) for centralized control. These functions capture the dynamics of the other loops and, from a prior design, allow solving the design problem at each iteration with linear programming that shapes the Nyquist plot of the ELTFs in the frequency domain, which also avoids the need for approximations. Two optimizations are proposed: (I) maximizing integral gains by fulfilling linear robustness margins in each ELTF and (II) maximizing linear robustness margins by fulfilling minimum bandwidths in each loop. In both optimizations, static decoupling and decoupling at a frequency close to the bandwidth of each loop are included as constraints, which improves the decoupling performance and the procedure convergence. The effectiveness of the method is verified in three simulation examples (square and non-square) and a lab experimental process. The proposed designs achieve a similar or better response when compared to that achieved by other authors. [ABSTRACT FROM AUTHOR]

The traditional structural performance may be seriously degraded due to applied indeterministic cases. A novel framework for robust topology optimization of truss-like continuum considering uncertain loads is presented. The robust optimization formula is constructed as minimizing the weighted sum of expectancy and standard variance of structural compliance with volume constraints. In this framework, both the magnitude and direction of applied loads are uncertain and independent. Truss-like continuum provides the topology optimal structure theoretically. Based on the classic truss-like optimization method, the statistical moments of compliance are accurately evaluated utilizing a bivariate cloud model tool. An effective strategy based on linear decoupling is reported to largely reduce the total number of finite element analysis. The optimization is achieved with gradient-based mathematic programming. Several numerical examples demonstrate a better structural robust performance obtained by the proposed algorithm than the traditional one. [ABSTRACT FROM AUTHOR]

We introduce a notion of residual diffeomorphism covariance in quantum Kantowski–Sachs (KS) describing the interior of a Schwarzschild black hole. We solve for the family of Hamiltonian constraint operators satisfying the associated covariance condition, as well as parity invariance, preservation of the Bohr Hilbert space of the Loop Quantum KS and a correct (naïve) classical limit. We further explore the imposition of minimality for the number of terms and compare the solution with those of other Hamiltonian constraints proposed for the Loop Quantum KS in the literature. In particular, we discuss a lapse that was recently commonly chosen due to the resulting decoupling of the evolution of the two degrees of freedom and the exact solubility of the model. We show that such a choice of lapse can indeed be quantized as an operator that is densely defined on the Bohr Hilbert space and that any such operator must include an infinite number of shift operators. [ABSTRACT FROM AUTHOR]

The non-decoupling effects of heavy scalars and vector fields play an important role in the indirect search for Beyond the Standard Model (BSM) physics at the LHC. By exploiting some new differential equations for the 1-PI amplitudes, we show that such non-decoupling effects are absent for quite a general class of effective field theories involving dimension six two-derivative and dimension eight four-derivative operators, once the resummation in certain BSM couplings is taken into account and some particular regimes of the relevant couplings are considered. [ABSTRACT FROM AUTHOR]

We construct new three-family N = 1 supersymmetric Pati–Salam models from intersecting D6-branes with original gauge group U (4) C × USp (2) L × U (2) R on a Type IIA T 6 / (Z 2 × Z 2) orientifold. We find that replacing a U (2) with a USp (2) group severely restricts the number of three-generation supersymmetric models such that there are only five inequivalent models. Exchanging the left and right sectors, we obtain five dual models with gauge group U (4) C × U (2) L × USp (2) R . These ten models have different gauge coupling relations at string scale. The highest wrapping number is 4, and one of the models contains no filler O6-planes. Moreover, we discuss in detail the particle spectra, the composite particles through strong coupling dynamics, and the exotic particle decouplings. Also, we study how to realize the string-scale gauge coupling relations in some models. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the dynamic positioning control of large ships in rough sea and to meet the need for fixed-point operations, this paper proposes a dynamic positioning controller that can effectively achieve large ships' fixed-point control during Level 9 sea states (wind force Beaufort No. 10). To achieve a better control effect, a large ship's forward motion is decoupled to establish a mathematical model of the headwind stationary state. Meanwhile, the closed-loop gain shaping algorithm is combined with the exact feedback linearization algorithm to design the speed controller and the course-keeping controller. This effectively solves the problem of strong external interferences impacting the control system in rough seas and guarantees the comprehensive index of robustness performance. In this paper, three large ships—the "Mariner", "Taian kou", and "Galaxy"—are selected as the research objects for simulation research and the final fixing error is less than 10 m. It is proven that the method is safe, feasible, practical, and effective, and provides technical support for the design and development of intelligent marine equipment for use in rough seas. [ABSTRACT FROM AUTHOR]