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This paper is a computational bifurcation analysis of a non-linear partial differential equation (PDE) characterizing equilibrium configurations in Micro electromechanical Systems (MEMS). MEMS are engineering systems that utilize electrostatic forces to actuate elastic surfaces. The potential equilibrium states of MEMS are described by solutions of a singularly perturbed elliptic nonlinear PDE. We develop a numerical method which couples a finite element approximation with mesh refinement to a pseudo arc-length continuation algorithm to numerically obtain bifurcation diagrams in the physically relevant two dimensional scenario. Several geometries, including a unit disk, square, and annulus, are studied to understand the behavior of the system over a range of domains and parameter regimes. We find that solution multiplicity, and importantly the potential for bistability in the system, depends sensitively on the parameters. In the annulus domain, symmetry breaking bifurcations are located and asymmetric solution branches are tracked. This work significantly extends the envelope for numerical characterization of equilibrium states in microscopic electrostatic contact problems relating to MEMS. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, an improved multiobjective particle swarm optimization (PSO) algorithm is proposed to optimize a three-phase, 12-slot, 19-pole, yokeless axial-field flux-switching permanent magnet (YASA-AFFSPM) motor. Design/methodology/approach: Based on the structural characteristics of the YASA-AFFSPM, a mathematical model is established to calculate the main size of the YASA-AFFSPM motor. The split ratio, stator axial length, sandwiching pole angle, rotor pole angle, PM arc and number of conductors per slot are selected as optimization variables. Also, the efficiency, power factor, cogging torque and average torque are considered as the optimization objectives. The objectives are optimized by combining the improved multiobjective PSO algorithm with electromagnetic calculation. Findings: Based on the proposed algorithm, the investigated motor is optimized. The on-load efficiency, power factor and average torque of the motor performance have increased by 0.87%, 3.13% and 10.39%, respectively. Moreover, the cogging torque and slot fill factor have undergone decreases of 8.57% and 3.34%, respectively. Finally, the effectiveness of the algorithm is verified using experiment results. Originality/value: So far, no comprehensive report has been observed on the optimization of the YASA-AFFSPM motor using evolutionary algorithms and the study of the effect of the motor parameters. Therefore, in this paper, the authors decided to investigate the effect of YASA-AFFSPM motor parameters and improve motor performance with the improved PSO method. [ABSTRACT FROM AUTHOR]

In this paper, we develop a new meshless numerical procedure for simulating the combustion model. To that end, we employ a local meshless collocation method according to the moving Taylor polynomial (MTP) approximation. The space derivative is approximated by using the local approach and then the Crank–Nicolson algorithm is utilized to approximate the time derivative. The stability and convergence of the time-discrete formulation are discussed, analytically and numerically. The Broyden method is applied to solve this nonlinear system. Since the size of the physical domain is large, we employ the non-overlapping domain decomposition method (DDM) to obtain a faster numerical algorithm. The local meshless approaches are efficient numerical techniques to simulate models in the fluid flow. The obtained results show that the proposed numerical formulation has efficient results for solving this mathematical model. [ABSTRACT FROM AUTHOR]

Purpose: Most projects are facing delays, and accelerating the pace of project progress is a necessity. Project managers are responsible for completing the project on time with minimum cost and with maximum quality. This study provides a trade-off between time, cost, and quality objectives to optimize project scheduling. Design/methodology/approach: The current paper presents a new resource-constrained multi-mode time–cost–quality trade-off project scheduling model with lags under finish-to-start relations. To be more realistic, crashing and overlapping techniques are utilized. To handle uncertainty, which is a source of project complexity, interval-valued fuzzy sets are adopted on several parameters. In addition, a new hybrid solution approach is developed to cope with interval-valued fuzzy mathematical model that is based on different alpha-levels and compensatory methods. To find the compatible solution among conflicting objectives, an arithmetical average method is provided as a compensatory approach. Findings: The interval-valued fuzzy sets approach proposed in this paper is denoted to be scalable, efficient, generalizable and practical in project environments. The results demonstrated that the crashing and overlapping techniques improve time–cost–quality trade-off project scheduling model. Also, interval-valued fuzzy sets can properly manage expressions of the uncertainty of projects which are realistic and practical. The proposed mathematical model is validated by solving a medium-sized dataset an adopted case study. In addition, with a sensitivity analysis approach, the solutions are compared and the model performance is confirmed. Originality/value: This paper introduces a new continuous-based, resource-constrained, and multi-mode model with crashing and overlapping techniques simultaneously. In addition, a new hybrid compensatory solution approach is extended based on different alpha-levels to handle interval-valued fuzzy multi-objective mathematical model of project scheduling with influential uncertain parameters. [ABSTRACT FROM AUTHOR]

To compute the similarity of scientific papers, text-based similarity measures, link-based similarity measures, and hybrid methods can be applied. The text-based and link-based similarity measures take into account only a single aspect of scientific papers, content or citations, respectively. The hybrid methods consider both content and citations; however, they do not carefully consider the relation between the content of a pair of papers involved in a citation relationship. In this paper, we propose a novel method, SimCC (similarity based on content and citations), that considers both aspects, content and citations, to compute the similarity of scientific papers. Unlike previous methods, SimCC effectively reflects both content and authority of scientific papers simultaneously in similarity computation by applying a new RA (relevance and authority) weighting scheme. Also, we propose an RA+R weighting scheme to consider the recency of papers and an RA+E weighting scheme to take into account the author expertise of papers in similarity computation. The effectiveness of our proposed method is demonstrated by extensive experiments on a real-world dataset of scientific papers. The results show that our method achieves more than 100% improvement in accuracy in comparison with previous methods. [ABSTRACT FROM AUTHOR]

This paper presents a performance analysis of a system for electrochemical impedance spectroscopy (EIS). The system, composed by an analog front-end (AFE) and a custom microcontroller (MCU) board, performs the impulse response (IR) measurement of linear and time-invariant (LTI) systems with pseudo-random excitation signals. As a novelty, a specific AFE for the interfacing of two-terminal resistive and capacitive sensors is covered in detail. The paper proposes, for the first time, a mathematical model to predict the impact of the main noise sources in the measured IR. Thanks to the proposed approach, the AFE and the system’s parameters can be properly designed in order to reduce the error, thus, minimizing the energy-per-error figure of merit (FOM) as well. The AFE is realized as discrete-components circuit and it has been included in a custom MCU-based measurement system as an expansion module. The predicted results from the mathematical model, in terms of noise power, SNR, and measurement error are validated through system-level simulation and experimental measurements. The system performs the IR measurement with 1023 points, showing root-mean-square (RMS) measurement errors of 1% and 1.4% for the tested ADC sampling frequencies of 62.5 kHz and 125 kHz, respectively. These lead to excellent FOM values of 128.9 mJ $\cdot $ %2 and 252.6 mJ $\cdot $ %2 that outstand the state of the art. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach to above- $f_{max}$ power detection, using harmonic injection locking of a cross-coupled oscillator and the resulting change in oscillation amplitude. The paper starts with the development of a theoretical framework for this receiver. Two previous methodologies are combined: analyzing an injection-locked oscillator as an active device in a positive feedback loop with a frequency selective network; and the more recently proposed way of modeling non-linearities by using inter-harmonic translation coefficients. Using this framework, a compact equation for the expected voltage response of the receiver is derived. Finally, the design of a receiver consisting of a 200 GHz cross-coupled oscillator with a 600 GHz folded dipole antenna as its tank inductor is discussed. A Noise Equivalent Power (NEP) of 2.3 pW/ $\sqrt {\text {Hz}}$ is achieved with the proposed receiver. [ABSTRACT FROM AUTHOR]

• The paper is the first batch that tries to inquiry the GPS of the PDIMNNs. Furthermore, unlike the previous literature [11,21,35] , the nonlinear substitution that converts the PDs system to a constant delays system is not used. Because the subsequent pro-cessing of the converted system is complicated, this paper directly performs on the original PDs system. • The paper employs the non-reduced-order method, which r-efrains the double-dimensional problem after reduced-order [3–5,23,24]. In practical applications, the method is more ponderable and si-gnificative for second-order scheme under controller. • In the paper, devise both the feedback controller and the adaptive controller for the first time to achieve the GPS of the PD-IMNNs. The advantages of the two types of controllers are compar-ed through numerical examples and simulations. The mathematical model is closer to reality, and selecting the appropriate controller in application can further reduce control expenses. This article probes into the global polynomial stabilization (GPS) of proportional delayed inertial memristive neural networks (PDIMNNs). Here, ruling out the reduced-order way, discuss the GPS of PDIMNNs under the second-order scheme directly. Firstly, a feedback controller is designed to make the system self-stabilizing. By designing suitable Lyapunov functional with adjustable parameters and combining with inequality techniques, two algebraic criteria are obtained to realize the GPS of the PDIMNNs. Owing to the conservatism caused by the ineluctable inequality scaling, it is worth noting that the controller gains are greater than the actual requirements. To further save control expenses, employing an adaptive controller to make the system stabilized. Finally, three numerical examples which sustain the usability of the obtained theoretical conclusions are shown. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to review previous research studies on mathematical models for entropy generation in the magnetohydrodynamics (MHD) flow of nanofluids. In addition, the influence of various parameters on the velocity profiles, temperature profiles and entropy generation was studied. Furthermore, the numerical methods used to solve the model equations were summarized. The underlying purpose was to understand the research gap and develop a research agenda. Design/methodology/approach: This paper reviews 141 journal articles published between 2010 and 2022 on topics related to mathematical models used to assess the impacts of various parameters on the entropy generation, heat transfer and velocity of the MHD flow of nanofluids. Findings: This review clarifies the application of entropy generation mathematical models, identifies areas for future research and provides necessary information for future research in the development of efficient thermodynamic systems. It is hoped that this review paper can provide a basis for further research on the irreversibility of nanofluids flowing through different channels in the development of efficient thermodynamic systems. Originality/value: Entropy generation analysis and minimization constitute effective approaches for improving the performance of thermodynamic systems. A comprehensive review of the effects of various parameters on entropy generation was performed in this study. [ABSTRACT FROM AUTHOR]

In this paper, aiming to systematically derive single-inductor multi-input multi-output (SI-MIMO) converters having favorable merits of high-density and low-cost, a basic model is firstly extracted from the working principle. Theoretically, by enumerating all possible connections of the basic model and one-by-one manually judging their effectiveness according to working criterions, multiple viable SI-MIMO topologies can be obtained, but with heavy workload. To simplify the topology derivation process, this paper also proposes a computer-aided method to replace the manual effort. By modelling the basic model and working criterions with graph theory, MATLAB codes can be developed to automatically screen out the effective topologies. With the proposed method, 8 three-port, 28 four-port and 115 five-port converters with single inductor are conveniently obtained, including both the existing and new topologies. Moreover, by configuring ports and switches in each derived topology, multiple specific converters can be further expanded. These converters can provide more options for practical engineering applications, and a new topology is also introduced and experimentally verified in the paper. [ABSTRACT FROM AUTHOR]

In this paper, we formulate a new system of nonlinear ordinary differential equations to study the unemployment problem in a context of financial crisis. We first prove the existence of a unique positive equilibrium. Then, using an appropriate Lyapunov function under some specified conditions, we prove the global stability of the unique positive equilibrium. We also propose and compare two control strategies with the objective to improve, at the lowest cost, the employment rate. Our results suggest that, in order to reduce the unemployment rate, it is better for a government to assist unemployed people in building their own business which will allow them to further create new vacancies than to assist self-employed individuals to create new vacancies. Numerical simulations are presented to substantiate the theoretical results. • We propose a new model to study the unemployment problem in financial crisis context. • We prove the global asymptotic stability of the unique equilibrium. • We propose two control strategies to improve, at lowest cost, the employment rate. • We perform numerical simulations to illustrate the theoretical results obtained. [ABSTRACT FROM AUTHOR]

The parabolic trough solar collector (PTSC) is a medium-temperature solar system that operates in the temperature range of 60–400 ºC. This technology is utilized dominantly for heat and power generation. Recently, numerous theoretical and numerical investigations have been carried out to evaluate and enhance the performance of PTSCs. This review paper provides fundamentals of PTSC systems, mathematical models, discretization methods, and turbulence models utilized for the simulation of PTSCs. Challenges in the field and future directions are presented to provide a perspective for researchers to achieve more accurate numerical results with lower computational costs. [ABSTRACT FROM AUTHOR]

Specific to the double saturation constraints of input and output in multimotor network systems, an anti-windup control framework with distributed total-amount optimal coordination is constructed, and a new saturated super-twisting sliding mode control strategy is designed in this paper. First, a mathematical model of direct torque and flux control of a multipermanent magnet synchronous motor is established. Next, the consistency of the total amount and output saturation are taken as the constraint conditions. Considering the lowest total energy consumption, the optimal multi-axis total-amount coordinated allocation algorithm is designed on the basis of the Karush-Kuhn-Tucker (KKT) condition. Then, the input saturation is introduced into the dynamic integral part of the super-twisting algorithm. A new saturated super-twisting sliding mode tracking control algorithm is designed, and the barrier Lyapunov function is used to prove the input constraint. Finally, the Matlab/Simulink simulation and RT-LAB semi-physical experiments verify that the anti-windup control strategy of distributed total-amount optimal coordination can effectively solve the double saturation constraints of input and output. [ABSTRACT FROM AUTHOR]

In this paper, a three tier mathematical model describing the interactions between susceptible population, Covid-19 infected, diabetic population and Covid-19 infected, non diabetic population is proposed. Basic properties of such a dynamic model, namely, non negativity, boundedness of solutions, existence of disease-free and disease equilibria are studied and sufficient conditions are obtained. Basic reproduction number for the system is derived. Sufficient conditions on functionals and parameters of the system are obtained for the local as well as global stability of equilibria, thus, establishing the conditions for eventual prevalence of disease free or disease environment, as the case may be. The stability aspects are discussed in the context of basic reproduction number and vice versa. An important contribution of this article is that a novel technique is presented to estimate some key, influencing parameters of the system so that a pre-specified, assumed equilibrium state is approached eventually. This enables the society to prepare itself with the help of these key, influencing parameters so estimated. Several examples are provided to illustrate the results established and simulations are provided to visualize the examples. [ABSTRACT FROM AUTHOR]

In this paper, a Takenaka-Malmquist (TM) basis function based equivalent data-model is established by an adaptive rational decomposition for the finite-time interval trajectory tracking control and real-time control of a class of nonlinear systems in the frequency domain. This data model can adaptively learn and match the control process of nonlinear systems. As a result, the proposed trajectory tracking as well as real-time control method can reflect the feature of adaptive learning in order-by-order decomposition, and the feasibility of the proposed method is guaranteed by the convergence of adaptive decomposition by TM basis function under the maximum selection principle (MSP) in Hardy space $H^{2}(\mathbb {D})$. Compared with the traditional model-free control method, this data learning model which matches the control process has obvious advantages in the system model expression and control accuracy. Simulation results at the end of this paper show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the distributed optimal containment control problem for multiple nonholonomic mobile robots (NHMRs) differential game is studied via reinforcement learning. An approximation-based optimal control strategy is developed to ensure the optimal performance index and avoid the potential collision among agents. Firstly, the collision avoidance problem considered in this paper is addressed by exploiting a consensus-like interconnection on a directed graph and an error transformation function. Then, on the basis of the optimal backstepping technique, a single critic neural network is adopted to obtain the solution of the coupled Hamilton-Jacobi (HJ) equation, in which an improved learning mechanism is constructed to relax the requirement on initial control conditions. In addition, based on the Lyapunov stability theory, it is proved that all signals in the closed-loop optimal control are uniformly ultimately bounded. Finally, the proposed control protocol is applied to NHMRs system, which verifies that the solution of the coupled HJ equation solves the containment problem of differential game. [ABSTRACT FROM AUTHOR]

Purpose: One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day pairings can be generated in a single model. The flexibility in generating parings causes that the proposed model leads to better solutions compared to existing models. Another advantage of the model is minimizing the risk of COVID-19 by limitation of daily flights as well as elapsed time minimization. As airports are among high risk places in COVID-19 pandemic, minimization of infection risk is considered in this model for the first time. Genetic algorithm is used as the solution approach, and its efficiency is compared to GAMS in small and medium-size problems. Design/methodology/approach: One of the most complex issues in airlines is crew scheduling problem which is divided into two subproblems: crew pairing problem (CPP) and crew rostering problem (CRP). Generating crew pairings is a tremendous and exhausting task as millions of pairings may be generated for an airline. Moreover, crew cost has the largest share in total cost of airlines after fuel cost. As a result, crew scheduling with the aim of cost minimization is one of the most important issues in airlines. In this paper, a new bi-objective mixed integer programming model is proposed to generate pairings in such a way that deadhead cost, crew cost and the risk of COVID-19 are minimized. Findings: The proposed model is applied for domestic flights of Iran Air airline. The results of the study indicate that genetic algorithm solutions have only 0.414 and 0.380 gap on average to optimum values of the first and the second objective functions, respectively. Due to the flexibility of the proposed model, it improves solutions resulted from existing models with fixed-duty pairings. Crew cost is decreased by 12.82, 24.72, 4.05 and 14.86% compared to one-duty to four-duty models. In detail, crew salary is improved by 12.85, 24.64, 4.07 and 14.91% and deadhead cost is decreased by 11.87, 26.98, 3.27, and 13.35% compared to one-duty to four-duty models, respectively. Originality/value: The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal. [ABSTRACT FROM AUTHOR]

In this paper, based on sampled-data control method, we address the stabilization problem for a general class of linear continuous-time fractional systems whose solution contains the Mittag-Leffler function that does not obey the basic exponentiation identity. By considering the infinite memory and hereditary characteristics of fractional-order calculus, we propose a sampled-data controller that guarantees the resulting closed-loop system to be asymptotically stable. Simulation examples are presented to demonstrate the effectiveness of the proposed controller and verify the established results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a scheme to design the reconfigurable filtering power divider with arbitrary operating channels based on external quality factor ($Q_{\mathbf {e}}$) control. By using an input feeding line, ${n}$ resonators, and $m$ output feeding lines, the $n^{\mathbf {th}}$ -order $m$ -way filtering power divider topology can be obtained with a simple configuration. A coupled-line output feeding structure loading with multiple PIN diodes is proposed to adjust the output $Q_{\mathbf {e}}$ values. Design theories for obtaining the desired $Q_{\mathbf {e}}$ values are provided. Then, the filtering power divider can be fully reconfigured in the states with one to $m$ operating channels. Good input matching can be achieved without using an additional reconfigurable impedance matching network in all these states, resulting in a size and loss reduction. For verification, a 2nd-order 4-way reconfigurable filtering power divider is designed, fabricated, and measured. As compared to the reported reconfigurable power dividers, the proposed design shows the merits of fully reconfigurable operating channels, favorable filtering responses, low insertion losses, high isolation, and a simple structure. [ABSTRACT FROM AUTHOR]

This paper presents a novel static digital pre-distortion (DPD) method for a current-steering digital-to-analog converter (CS-DAC). The proposed method utilizes the knowledge of the current cell array architecture to calculate the static mismatch currents of the cells. The mismatch values are stored in memory and added to the original input code to generate the new pre-distorted input word. The converter corrects the static error with its own current cells without incorporating an additional calibration DAC (CALDAC) or programmable current sources. This results in a reduction in area, power and simulation run times because of the simpler circuit design. An Overflow-Cell-Selection (OCS) is introduced as a novel solution to further enhance the static linearity of the converter. It also can be implemented as a software solution for already existing DAC designs which do not have an integrated DPD and lab/measurement equipment (e.g., arbitrary wave generator (AWG)). This poses as a strong differentiation factor compared to other state-of-the-art static DPD methods. The evaluation of the proposed DPD is done via simulations in MATLAB and on- chip measurements with a 14-bit CS-DAC in 16 nm. Single tone measurements show a performance gain of the total harmonic distortion (THD) of 12 dB. [ABSTRACT FROM AUTHOR]

Diffusion-driven instabilities with pattern formation may occur in a network of identical, regularly-spaced, and resistively-coupled cells if and only if the uncoupled cell is poised on a locally-active and stable operating point in the Edge of Chaos domain. This manuscript presents the simplest ever-reported two-cell neural network, combining together only 7 two-terminal components, namely 2 batteries, 3 resistors, and 2 volatile NbOx memristive threshold switches from NaMLab, and subject to diffusion-driven instabilities with the concurrent emergence of Turing patterns. Very remarkably, this is the first time an homogeneous cellular medium, with no other dynamic element than 2 locally-active memristors, hence the attribute all-memristor coined to address it in this paper, is found to support complex phenomena. The destabilization of the homogeneous solution occurs in this second-order two-cell array if and only if the uncoupled cell circuit parameters are chosen from the Edge of Chaos domain. A deep circuit- and system-theoretic investigation, including linearization analysis and phase portrait investigation, provides a comprehensive picture for the local and global dynamics of the bio-inspired network, revealing how a theory-assisted approach may guide circuit design with inherently non-linear memristive devices. [ABSTRACT FROM AUTHOR]

The integral nonlinearity of digital-to-analog converters manifests itself as adjacent-channel power in RF transmitters. This paper derives compact equations relating these two quantities and verifies the results by simulations. Both current-steering and switched-mode architectures are analyzed. [ABSTRACT FROM AUTHOR]

Recent studies on integrated circuits interconnections are mainly concentrated on the analysis of crosstalk and delay, by taking the trade-off between accuracy, speed, and complexity into consideration. The new idea of this paper is to apply the convex optimization method to analyze crosstalk and delay of the lossy coupled interconnections in identical and non-identical forms. For this purpose, a simple and comprehensive model is proposed to cover the functional and dynamic crosstalk in a computationally-effective way. More specifically, various case studies are determined to analyze the transient response of the coupled transmission lines with arbitrary excitation sources in the presence of both capacitive and inductive coupling characteristics. To validate the model, the numerical and Advanced Design System (ADS) simulation results are compared to indicate the desired accuracy. The calculated crosstalk percentage error of the proposed model with respect to ADS and HSPICE are less than 1.03% and 1.19%, respectively. In addition, the computational speed of the proposed method is about twice higher than ADS and HSPICE. The proposed model is extendible to handle ${N}$ coupled lines, making it appropriate to model complex integrated circuit interconnections. [ABSTRACT FROM AUTHOR]

Purpose: To design a pulse power water treatment system, it is necessary to design a reactor optimally. One of the most essential types of reactors used in water treatment is the dielectric barrier discharge (DBD) reactor. The purpose of this paper is to model the electric field in the two types of planar and coaxial reactors to have an accurate analytical formula for using in the optimal design according to the required electric field of the treatment. Design/methodology/approach: The method proposed in this paper focuses on the voltage of different areas in the reactor and different boundary conditions to obtain the surface charge density. In this regard, parameters of the dielectric and treated material, as well as the reactor dimension, have been affected in the equations. To confirm the analytical results, the finite element method simulation has been performed, and it shows the accuracy of this method. Findings: The exact analytical equation of the electric field is found within the discharge zone of the planar and coaxial DBD reactors. These equations can predict the values of different parameters of the reactor required to purify the material before each design and it does not even require simulation. Originality/value: The electric field formula presented in this paper can allow the manufacturers of pulse power water treatment systems to optimize their design easily, cost-effectively and in less time. Also, the formulas provided are completely general and remain effective for all materials. [ABSTRACT FROM AUTHOR]

This paper presents an implementation for a baseband massive multiple-input multiple-output (MIMO) application-specific instruction set processor (ASIP). The ASIP is geared with vector processing capabilities in the form of single instruction multiple data (SIMD), and furthermore exploits instruction level parallelism by employing a very large instruction word (VLIW) architecture. Additionally, a systolic array is built into the pipeline which is tuned to speed up matrix calculations. A parallel memory subsystem and stand-alone accelerators are integrated into the ASIP architecture in order to meet the processing requirement. The processor is synthesized in 22 nm FD-SOI technology running at a clock frequency of 800 MHz. The system achieves a maximum detection throughput of 0.75 Gb/s/mm2 for a $128\times 8$ massive MIMO system. [ABSTRACT FROM AUTHOR]

Eight-switch three-phase post-fault inverter (ESTPI) is widely used as the reconfigured topology of three-phase three-level neutral point clamped DC/AC inverter when open-circuit fault occurs. A key technical challenge for the ESTPI is the post-fault controller design. The existing post-fault control approaches for the ESTPI suffer from the difficulty in trading off the current tracking performance, neutral point voltage (NPV) balancing and common mode voltage (CMV) levels. To solve this problem, this paper proposes an improved predictive current control algorithm. The proposed algorithm contributes to achieve accurate output current tracking while greatly reducing the CMV with a balanced NPV. Simulation and experimental results are presented to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Efficient simulation of switched-mode power conversion circuits is necessary for the analysis and optimization of power electronics. This paper introduces the extended impedance method (EIM) to the simulation and analysis of general switched-mode power converter circuits. By using the EIM method, the conventional impedance concept can be extended to involve more linear time-variant (LTV) and nonlinear devices, such as MOSFET switches and diodes, which are commonly used in switched-mode power conversion circuits. EIM models a circuit network from the component level in the frequency domain, rather than from the system-level constitutive differential equation in the time domain. Compared with the conventional averaging method, EIM can reveal more high-frequency features of a switched-mode converter circuit, in particular, those around the switching instants. A buck converter is taken as a representative example to validate the EIM based analysis. Both the simulation and experimental results prove that EIM provides precise numerical results, which match the real waveform, as the commercial simulators, e.g. PSpice and ADS, do. Moreover, it largely reduces the computational complexity towards more efficient and more flexible steady-state analysis of switched-mode power electronics. [ABSTRACT FROM AUTHOR]

This paper presents a rigorous transfer function analysis of the power supply rejection ratio (PSRR) of low-dropout (LDO) regulators and the LDO with the feed-forward ripple cancellation (FFRC) scheme. Four main noise sources of conventional LDOs are first clarified. An efficient and accurate model is proposed to facilitate the analysis, and the transfer function, along with the poles and zeros, is derived based on the simplified model. Software simulation results and numerical plots are both demonstrated and compared to verify the analytical results, with respect to two specific design examples. The widely-used FFRC scheme for PSRR enhancement is also reinvestigated based on the proposed model. With the inclusion of the FFRC circuit, the new transfer function with new poles and zeros is presented. The working principles of the FFRC scheme are illustrated and the optimal FFRC case is clarified. The proposed model and the derived transfer function match well with the simulation results and the measurement results in prior works. The proposed model and the analytical results serve as the theoretical foundation of the design of high-PSRR LDOs. The recommended simulation methodology could be helpful during the circuit design phase. [ABSTRACT FROM AUTHOR]

Oil palm cultivation stands as a crucial industry in Indonesia, significantly contributing to the nation's economy by generating employment opportunities and fostering social welfare for communities residing near plantations. Despite its economic importance, oil palm plantations face various challenges, with one prominent issue being the infestation of nettle caterpillar pests. These pests cause leaf skeletonization, resulting in a staggering 36% reduction in oil palm productivity over a two-year period. This paper explores diverse strategies for pest management in oil palm plantations, encompassing biological control through the stimulation of natural predators, mechanical control involving the collection and incineration of cocoons, and chemical control through pesticide application. The research introduces a predator–prey mathematical model for oil palm plantation pests, where the leaf area serves as the primary food source for caterpillars, acting as prey. Through dynamic model analysis, four equilibrium points are identified, with interconnected conditions dictating their existence and stability. These conditions are visually represented in a bifurcation plane, providing concise information. The study further includes bifurcation diagrams of equilibrium points to elucidate the influence of each parameter on pests, predators, and the leaf area of oil palm plants. Additionally, sensitivity analysis of the stable interior equilibrium point is conducted to understand the impact of individual parameters. The paper extends its investigation to optimal control strategies, evaluating six scenarios categorized into two population conditions: with predators and without predators. Within each population condition, three control strategies are considered—chemical control only, mechanical control only, and a combination of chemical and mechanical control. Simulation results from the optimal control study reveal that the presence of natural predators emerges as a pivotal strategy in effectively managing nettle caterpillars. Notably, the control of resistant pests through pupa incineration has a substantial impact on reducing the caterpillar population in subsequent life cycles. • In current study, the MELP-S-B predator-prey model is proposed for managing nettle caterpillar pests in oil palm plantations involving the control measures. • The inclusion of prey populations, specifically oil palm leaves, in this predator-prey model constitutes the most fundamental novelty of this study. • The main objective of this research is to determine the dynamics of pests in plantations and avoid economic losses due to pests in oil palm plantations. • In-depth analysis of system dynamics around four equilibrium points conducted. Sensitivity analysis is carried out to measure the influence of parameters at the interior point. • Optimal control study conducted to manage pest abundance in oil palm plantations under varying predator presence. Numerical simulations of six strategies, blending mechanical and chemical measures, offer insights into effective pest control combinations. [ABSTRACT FROM AUTHOR]

The main results of this paper are concentrated on the nonlinear model predictive control (MPC) tracking optimization based on high-order fully actuated (HOFA) system approaches. The proposed HOFA MPC strategy makes full use of full-actuation property to eliminate the nonlinear dynamics of the system, and then the nonlinear optimization problem is equivalently transformed into a series of easy-solve linear convex optimization problems. Different from general nonlinear MPC methods and the current optimal control of the HOFA system approach, an analytical controller with smooth and less energy is obtained by the moving horizon optimization. And it is proven that the proposed controller can stabilize the corresponding tracking error closed-loop system. Finally, not limited to FA systems, as examples, a nonlinear numerical under-actuated model in the mathematical sense and a benchmark nonlinear under-actuated mechanical system are transformed into corresponding equivalent HOFA systems, the simulation results are given to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

For a physical problem described by a parameterized mathematical model, different configurations of the problem require computing the solution over a range of parameters in order to study the phenomenon when parameters change. In other words, it is a process of looking for a continuum of solutions of the equation, relative to these parameters, in order to find the ones that fit the experimental data. However, solving a direct problem for each parametric configuration will generate a cascade of direct problems, which will cost a huge amount of time, especially when we deal with non-linear equations. Therefore, the parametric solution is a suitable alternative strategy to compute the solution of the equation. In this paper, we will use the Proper Generalized Decomposition (PGD) method to solve non-linear diffusion equations and produce parametric solutions. To treat the non-linear functions, we will not use the Discrete Empirical Interpolation Methods (DEIM), which has proven their utility, but the non-linear terms will be replaced by their Taylor series expansion up to an order m. This will produce a new model, which we call here the " developed equation " and therefore the PGD is applied on. Polynomial equations appear for each tensor element computation. While space and time tensor elements' equations are to be solved using Finite Elements Methods (FEM) and Borel–Padé–Laplace (BPL) integrator respectively, Newton solver is used for tensors relative to the parameters' equations. Here, rational polynomial functions arise for parametric tensor elements, which are known to extrapolate solutions. Numerical simulations are done for a non-linear diffusion equation with exponential diffusion coefficient as first trial, and with a magnetic diffusion coefficient as a second one. • Dealing with non-linearity, within PGD, using a Taylor series expansion. • Elaboration of a developed equation to be used for computing parametric solution. • Rising of rational polynomials after solving parametric equations by Newton methods. • Small local and global errors of the parametric solution with reference ones. • Extrapolation of the parametric solution using rational polynomials. [ABSTRACT FROM AUTHOR]

In undergraduate mathematics classes, the most common discrete version of logistic growth is defined by the difference equation p n + 1 = k (L − p n) p n . While this is a natural analog of the logistic differential equation, and while in many cases it produces results similar to those of the continuous model, it can also give rise to chaotic behavior. This paper derives in a natural way an alternative discrete logistic model, defined by the Verhulst difference equation, with several noteworthy properties. For example the Verhulst equation has closed form solutions given by continuous logistic curves and never leads to chaotic behavior. Our development of the Verhulst equation also provides a beautiful example of the formulation-application-refinement cycle of mathematical modeling. For these and other reasons, the Verhulst equation deserves a place in the undergraduate curriculum alongside the more familiar logistic difference equation given above. [ABSTRACT FROM AUTHOR]

Multipliers are essential in implementing nonlinear neuron models, but they take huge implementation costs. Many multiplierless fitting schemes have been proposed to simplify the implementation of nonlinearities in neuron models. To optimize these schemes, this paper presents a nullcline-characteristics- based piecewise linear (NC-PWL) fitting scheme for multiplierless implementations of Hindmarsh-Rose (HR) neuron model. This NC-PWL fitting scheme uses as few line segments as possible to approximate the critical nonlinearity characteristics of the local nullclines. A NC-PWL HR neuron model that reproduces diverse firing patterns of the original one is successfully established. Using off-the-shelf low-cost components, an analog multiplierless circuit is designed for this fitting model and welded on print circuit board (PCB). Meanwhile, by logical shift method, a digital multiplierless circuit with low resource consumption is developed for this fitting model on field-programmable gate array (FPGA) platform. Experimental results of the analog and digital multiplierless hardware implementations verify the numerical simulations and show the simplicity and feasibility of the presented fitting scheme. [ABSTRACT FROM AUTHOR]

The analysis of injection-locked clock multipliers (ILCMs) using bang-bang phase detectors (BBPDs) is challenging due to the nonlinear BBPD and the multi-rate injected oscillator. This paper presents an explicit analysis of digital ILCMs using BBPDs and proposed an intuitive approach to optimizing parameters with given noise sources. A time-domain analysis in the single-clock domain is presented to solve the closed-form expression of jitter in the ILCM. The proposed approach exhibits good consistency with simulations, for various design parameters and noise cases. With the predicted input-referred jitter, the equivalent BBPD gain is resolved to derive the frequency-domain noise transfer functions in concise forms. To achieve the desired performance with given specifications, recommended design procedures are summarized based on the proposed analysis and verified by simulations. [ABSTRACT FROM AUTHOR]

This paper focuses on establishing an adaptive boundary observer for fully coupled reaction-diffusions partial differential equations (PDEs) containing unknown parameters. Firstly, the state error system is transformed into an intermediate system by finite dimensional backstepping-like transformation, and then we convert the intermediate system to a target system by infinite dimensional backstepping transformation. Secondly, a least-squares type parameter adaptive law is given. Thirdly, exploiting an ad hoc persistent excitation condition, the exponentially convergent of the observer will be established by applying Lyapunov functional. Finally, we use simulation analysis for Chemical Tubular Reactor model to demonstrate the validity of the results. [ABSTRACT FROM AUTHOR]

In this paper, a class of flexible riser systems modeled by partial differential equations (PDEs) with the backlash is considered. The backlash is formulated as the addition of a linear input and a interference-like term, then an new auxiliary item is introduced to compensate for the impact of this backlash. In addition, the constraint problem for the position and the velocity is also taken into consideration. To solve this constrain problem, the logarithmic barrier Lyapunov function is employed. For the flexible riser system, two kinds of adaptive controllers are proposed under the following two cases. One controller is designed when only the parameter of backlash is unknown. On the basis of this result, the other controller is presented when some system parameters cannot be measured through actual measurement. Then, combing the theory of Lyapunov stability, the two controllers can guarantee the boundedness of all signals in the closed-loop flexible riser system. Further, both the position and the velocity satisfy their corresponding constraint condition. Finally, the simulation example verifies that the proposed control method is effective. [ABSTRACT FROM AUTHOR]

In this paper, a low complexity moving average nested generalized memory polynomial model (MAN-GMP) is proposed for digital predistortion (DPD) of broadband power amplifiers (PAs). As the signal bandwidth increases drastically, the strong nonlinear distortions, especially those induced by the memory effect, are generated from the highly efficient PAs. To compensate for the strong memory effect, a moving average nested envelope memory polynomial (MAN-EMP) model is derived from an accuracy-enhanced GMP model, which offers reduced complexity while suffering from degraded modeling accuracy. The MAN-GMP model is further proposed to improve the modeling accuracy by connecting several memory branches of the MAN-EMP model in parallel. An iterative algorithm is designed to extract the model coefficients efficiently through only one or two iterations. Experimental measurements are carried out on two sub-7 GHz broadband GaN Doherty PAs with up to 200 MHz bandwidth OFDM signals to benchmark the proposed MAN-GMP model against the GMP, the parallel-LUT-MP-EMP (PLUME), the augmented complexity-reduced GMP (ACR-GMP), the generalized twin-nonlinear two-box (GTNTB), and the enhanced Wiener models. The experimental results show that the MAN-GMP model can effectively compensate for the nonlinear distortion of broadband PAs with significant complexity reduction. [ABSTRACT FROM AUTHOR]

This paper deals with nonlinear control of a single-phase half-bridge interleaved buck shunt active power filter (HBIB-SAPF) with a nonlinear load. The control objective for the system is twofold: performing power factor correction by compensating for harmonics and reactive current consumed by the nonlinear load from one hand and tightly regulating the HBIB converter DC capacitor voltage. Both objectives are accomplished using a two-loop nonlinear controller. The inner loop acts on the switching devices so that the active filter current tracks its reference with the aim of ensuring a unity power factor. This loop is tackled using backstepping technique and Lyapunov approach. The outer loop is responsible for regulating the DC capacitor voltage to its desired value, using a PI controller with a pre-filter. The stability analysis of the closed-loop system is formally performed by using the averaging theory. The validity of the designed nonlinear controller is checked by simulations in Matlab/SimpowerSystem showing its robustness and accuracy under various operating conditions. [ABSTRACT FROM AUTHOR]

This paper presents an extensive study of linear and logistic regression algorithms implemented with 1T1R memristor crossbars arrays. Using a sophisticated simulation platform that wraps circuit-level simulations of 1T1R crossbars and physics-based models of RRAM (memristors), we elucidate the impact of device variability on algorithm accuracy, convergence rate and precision. Moreover, a smart pulsing strategy is proposed for practical implementation of synaptic weight updates that can accelerate training in real crossbar architectures. Stochastic multi-variable linear regression shows robustness to memristor variability in terms of prediction accuracy but reveals impact on convergence rate and precision. Similarly, the stochastic logistic regression crossbar implementation reveals immunity to memristor variability as determined by negligible effects on image classification accuracy but indicates an impact on training performance manifested as reduced convergence rate and degraded precision. [ABSTRACT FROM AUTHOR]

Second order memristors are two terminal devices that present a conductance depending on two orders of variables, namely the geometric parameters and the internal temperature. They have shown to be able to mimic some specific features of neuron synapses, specifically Spike-Timing-Dependent-Plasticity (STDP), and consequently to be good candidates for neuromorphic computing. In particular, memristor crossbar structures appear to be suitable for implementing locally competitive algorithms and for tackling classification problems by exploiting temporal learning techniques. On the other hand, neuromorphic studies and experiments have revealed the existence of different kinds of plasticity and have shown the effect of calcium concentration on synaptic changes. Computational studies have investigated the behavior of spiking networks in the context of supervised, unsupervised, and reinforcement learning. In this paper, we first derive a simplified, almost analytical, model of a second-order memristor, only involving two variables, the mem-conductance, and the temperature, directly attributable to the synaptic efficacy and to the calcium concentration. Then we study in detail the response of a single memristive synapse to the most relevant plasticity models, including cycles of spike pairs, triplets, and quadruplets at different frequencies. Finally, we accurately characterize memristor spiking networks as discrete nonlinear dynamic systems, with mem-conductances as state variables and pre and postsynaptic spikes as inputs and outputs, respectively. The result shows that the model developed in this manuscript can explain and accurately reproduce a significant portion of observed synaptic behaviors, including those not captured by classical spike pair-based STDP models. Furthermore, under such an approach, the global dynamic behavior of memristor networks and the related learning mechanisms can be deeply analyzed by employing advanced nonlinear dynamic techniques. [ABSTRACT FROM AUTHOR]

The dynamics of modern hybrid power systems are characterized by behaviors at different timescales, typically separated by several orders of magnitude. In this paper we apply the envelope-following method to hybrid power systems simulations, in which single-phase and three-phase representations of a power system co-occur. This simulation method is well suited for handling coexisting behaviors occurring at different timescales. Compared to the simulation approaches present in the literature, the envelope-following method does not need to continuously switch between two separate simulation engines, but rather automatically handles instantaneous variations in the dynamics of the system, such as faults or topology changes. Additionally, given the vast penetration of power electronic components in modern electricity networks, employing the envelope-following method allows using a vast array of numerical algorithms that have been developed over the years to simulate electrical and electronic circuits. The proposed approach is validated by means of power systems case studies of increasing complexity. [ABSTRACT FROM AUTHOR]

A random sampling-and-averaging (RSA) technique based on stochastic Monte Carlo methods is described in this paper for enhancing the accuracy of single-photon arrival-time measurements down to sub-picosecond ranges in emerging quantum applications. The theoretical variances of both synchronous and asynchronous RSA techniques are presented in the mathematical formats and experimentally verified by the Monte Carlo simulations. Meanwhile, the methodology of converting the mathematical models into an almost all-digital low-power integrated-circuit is elaborated by a circuit-level example with the instruction of setting circuit parameters. Along with the superior measurement resolution, scalable dynamic ranges, high linearity, high noise immunity, and low power/area consumption, the primary limitation of the RSA techniques has also been addressed for the forthcoming conversion-rate enhancement techniques. [ABSTRACT FROM AUTHOR]

This paper presents the design of tunable CMOS pseudo-resistors aimed at achieving large and predictable resistance values. Instrumental to the proposed pseudo-resistor is the design of current sources of extremely low currents and transistors operating in subthreshold. The effects of the leakage currents of reverse-biased pn-junctions on the pseudo-resistor resistance are also evaluated. The proposed pseudo-resistor circuit was validated while in use as part of a filter integrated in a 180 nm CMOS process. Pseudo-resistors with resistances between 180 $\text{G}\Omega $ and 700 $\text{G}\Omega $ were employed to obtain low-frequency poles of a band-pass filter adjustable from 0.6 Hz to 2 Hz. [ABSTRACT FROM AUTHOR]

The paper presents a study of issues related to the identification of a non-linear mathematical model describing dynamics of the temporomandibular joint (TMJ) disc. Based on the tests of real disks, a non-linear model was built and verified, and then numerical simulations were carried out, the purpose of which was to analyze the behavior of the model for various excitation conditions. They include, among others, plotting a multi-colored map of distribution of the largest Lyapunov exponent based on which the areas of occurrence of periodic and chaotic motion zones are identified. Bifurcation diagrams of steady states for sample sections of the Lyapunov map and phase flows of periodic and chaotic solutions are generated. For the same sections, numerical simulations are performed to identify coexisting solutions. These studies are carried out using diagrams showing the number of coexisting solutions and their periodicity. The research presented in the paper shows a very good match between the results of computer simulations and the data recorded in the laboratory experiment. Due to the very strong damping occurring in the system, the chaotic attractors resemble quasi-periodic solutions with their geometric shape. Strong damping also significantly affects multiple solutions, which are relatively rare in the analyzed model. Most of the chaotic responses and multiple solutions occur in the range of low amplitude values of the dynamic load affecting the tissues of the articular disc. The obtained results of numerical experiments clearly indicate that in the range of low frequency values of the external load acting on the system, single periodic solutions with a periodicity of 1 T dominate. With the increase of the load amplitude, the area of occurrence of such solutions increases. [Display omitted] • A novel non-linear mathematical model of the TMJ disk has been proposed. • The model was very well adjusted to the results of experimental studies. • The behavior of the model for chaotic and periodic motion zones was tested. • The presence of coexisting solutions was confirmed. [ABSTRACT FROM AUTHOR]

This paper presents a circuit-theoretic analysis of a NbO2-Mott memristor fabricated at Hewlett-Packard Labs. It investigates mechanisms behind the origin of complexity based on local activity, which characterizes the behavior of this outstanding nanodevice. We propose an accurate, particularly simplified version of a recently introduced physical model suitable for large-scale circuit simulations. Following the concept of local activity, we then conduct a small-signal circuit-theoretic derivation of the impedance and associated small-signal equivalent circuit elements to analyze device stability and frequency response. Finally, our analysis reveals locally active operating regions, as well as regions where the device dynamics are positioned on the edge of chaos. The latter regions are crucial for designing bio-inspired computing systems. [ABSTRACT FROM AUTHOR]

Memristors are widely used to construct multi-scroll/wing chaotic systems with complex dynamics. However, the generation of a multi-scroll/wing attractor is typically not induced by the memristor but depends on other nonlinear functions in the system, which does not take advantage of the unique features of the memristor for chaos-based applications. To address this issue, the present paper introduces a memristor coupling (MC) method to construct a novel memristive Sprott A system (MSAS) through coupling a flux-controlled memristor with multi-piecewise linear memductance into the chaotic Sprott A system. From theoretical analysis and numerical simulations, the MSAS is shown to be able to generate any number of multi-type hidden attractors, including multi-one-scroll, multi-double-scroll and multi-double-wing hidden attractors. In addition, it has two kinds of multistabilities, that is, heterogeneous multistability and homogeneous multistability. Based on these unique properties, different numbers of coexisting heterogeneous hidden attractors and coexisting homogeneous hidden attractors are derived respectively by switching the memristor initial states. These interesting dynamical properties are comprehensively investigated using nonlinear analysis tools. Furthermore, hardware experiments are implemented to demonstrate the feasibility of the MSAS and the effectiveness of the MC method. Finally, a new pseudo-random number generator (PRNG) is proposed to explore the practical applications of the MSAS. Performance evaluation results verify the high-quality randomness of the designed PRNG. [ABSTRACT FROM AUTHOR]

Recently, integrating ferroelectric materials with nanotransistors such as carbon nanotube field-effect transistors (CNTFETs) has opened new doors for demonstrating a new generation of ultra-miniature circuits and systems. Utilizing the negative differential resistance effect in negative capacitance CNTFETs (NC-CNTFETs) has spurred the efforts for designing ultra-compact ternary circuits and systems similar to their binary structures. This paper presents an ultra-efficient ternary image edge detection hardware using NC-CNTFET technology. The proposed hardware is endowed with a noise reduction circuitry to mitigate the noise effects. Using four $1\times 3$ kernels and concatenating the image pixels, the proposed ternary hardware has been designed using only 50 transistors. The proposed ternary hardware at the circuit level shows, on average, 74% improvements regarding power delay-product (PDP) compared to the CNTFET-based counterparts. Our comprehensive simulations indicate that the proposed NC-CNTFET-based hardware shows a 40% improvement in data loss, 2.2 times improvement in performance ratio, and 1.14 times improvement in Pratt’s figure-of-merit, respectively, compared to the related designs. Our results accentuate that the proposed NC-CNTFET-based ternary hardware is a breakthrough achievement in demonstrating ultra-efficient and noise-immune ternary image processing circuits beyond the conventional binary counterparts. [ABSTRACT FROM AUTHOR]

• In this article, we present a three-phased framework to aid the multi-criteria decision analysis of portfolios in an online and interactive fashion. • This approach is based on the idea of enriching a classical mathematical technique (e.g. goal programming, ?-constraint, or compromise programming) by incorporating some concepts based on fuzzy relations taken from the European School of MCDA (Multi-Criteria Decision Analysis). • Experimental evidence on synthetic and real-world instances shows that our model computes quickly enough to be interactive and it is even capable of improving high quality solutions. • The contribution of this paper is in providing a guideline to build compromise programming models that follow the principles of ELECTRE III to prevent incomparability during the analysis. It aids the DM in identifying strictly preferred solutions. • In practical terms, the chief contribution of this approach is the level of confidence that the DM can feel in the final prescription. This paper introduces an interactive approach to support multi-criteria decision analysis of project portfolios. In high-scale strategic decision domains, scientific studies suggest that the Decision Maker (DM) can find help by using many-objective optimisation methods, which are supposed to provide values in the decision variables that generate high-quality solutions. Even so, DMs usually wish to explore the possibility of reaching some levels of benefits in some objectives. Consequently, they should repeatedly run the optimisation method. However, this approach cannot perform well – in an interactive way – for large instances under the presence of many objective functions. We present a mathematical model that is based on compromise programming and fuzzy outranking to aid DMs in analysing multi-criteria project portfolios on the fly. This approach allows relaxing the problem of rapidly optimising portfolios while preserving the beneficial properties of the DM's preferences expressed by outranking relations. Our model supports the decision analysis on two instance benchmarks: for the first one, a better compromise solution was generated 84% of the runs; for the second one, this ranged from 93% to 97%. Our model was also applied to a real-world problem involving social projects, obtaining satisfactory results. [ABSTRACT FROM AUTHOR]

Purpose of this paper is the presentation of a novel Machine Learning (ML) technique for nanoscopic study of thin nanoplates. The second-order strain gradient theory is used to derive the governing equations and account for size effects. The ML framework is based on Physics-Informed Neural Networks (PINNs), a new concept of Artificial Neural Networks (ANNs) enriched with the mathematical model of the problem. Training of PINNs is performed using a highly efficient learning algorithm, known as Extreme Learning Machine (ELM). Two applications of this ANNs-based method are illustrated: solution of the Partial Differential Equations (PDEs) modeling the flexural response of thin nanoplates (direct problem), and identification of the length scale parameter of the nanoplate mathematical model with the aid of measurement data (inverse problem). Comparison with analytical and Finite Element (FE) solutions demonstrate the accuracy and efficiency of this ML framework as meshfree solver of high-order PDEs. The stability and reliability of the present method are verified through parameter studies on hyperparameters, network architectures, data noise and training initializations. The results presented give evidence of the effectiveness and robustness of this new ML approach for solving both direct and inverse nanoplate problems. [ABSTRACT FROM AUTHOR]

This paper concentrates on dynamics and stability analysis of two predators–one prey mathematical model with competition between predators and fading memory in one predator. The investigation of the constructed model shows that there exist five equilibria, e.g. trivial extinction state of all populations, extinction of both predators state, extinction of first or second predator state and coexisting state. Investigating the eigenvalues of characteristic polynomial, conditions for the local stability around each equilibrium are also determined depending on the parameter space. Analytical formulations are complemented with numerical simulations, where time simulations and single parameter numerical continuation of each variable are performed with respect to model parameters and multiple sub-and super-critical Hopf bifurcations, period doubling bifurcation and transcritical bifurcation are detected for different values of memory related parameter. Our results show that fading memory and competition between predators have substantial impact on the existence and dynamics of all three populations and may shed lights on further understanding of interacting species in ecology. • A model comprising one prey and two competitive predators with fading memory is constructed. • Fading memory and competition between predators have a large impact on the dynamics. • Fading memory in one predator may affect the existence and nature of various bifurcations. [ABSTRACT FROM AUTHOR]