Search

A cell's fate involves transitions among its various states, each defined by a distinct gene expression profile governed by the topology of gene regulatory networks, which are affected by 3D genome organization. Here, we develop thermodynamic models to determine the fate of a malignant cell as governed by the tumor suppressor p53 signaling network, taking into account long-range chromatin interactions in the mean-field approximation. The tumor suppressor p53 responds to stress by selectively triggering one of the potential transcription programs that influence many layers of cell signaling. These range from p53 phosphorylation to modulation of its DNA binding affinity, phase separation phenomena, and internal connectivity among cell fate genes. We use the minimum free energy of the system as a fundamental property of biological networks that influences the connection between the gene network topology and the state of the cell. We constructed models based on network topology and equilibrium thermodynamics. Our modeling shows that the binding of phosphorylated p53 to promoters of target genes can have properties of a first order phase transition. We apply our model to cancer cell lines ranging from breast cancer (MCF-7), colon cancer (HCT116), and leukemia (K562), with each one characterized by a specific network topology that determines the cell fate. Our results clarify the biological relevance of these mechanisms and suggest that they represent flexible network designs for switching between developmental decisions. [ABSTRACT FROM AUTHOR]

In this era of Web World-3, usage of the Internet of Things (IoT) in power system networks has attained scalable altitude. By using this technology, data can be transferred and monitored from the far end. Further, the suggested corrective actions are also executed. However, recently, many cyber-attacks have been observed on the power system in which activities such as injection of false data, unwanted switching operations, formation of sub-system layers, and false indication of failure of cyber-physical components (CpC) are experienced. In the worst case, it leads to invite cascade tripping of the power system. Utmost care is taken for the selection of CpC for the power system. However, it is observed that the cyber attackers mostly take entry into the network using the CpC of the power system. Cyber attackers perform false switching operations and false data injection. This article suggests a cyber security concept to minimize the false switching operations and false data injection in the power system network. A hardware model is prepared and the working scheme is implemented using IoT technology. The hardware result suggests that the un-authentic attempt/cyber-attack has been identified and the alarm is generated. It also does not permit the un-authentic person to access the real-time data. A wide range of applicability of the suggested scheme has been verified by hardware results. In addition to this, the power factor correction algorithm also works satisfactorily in the hardware along with the cyber security constraints. In order to prove wide range of applicability of the suggested scheme, additional features such as controlling of multiple switching devices and interlock between CB and earthing switch has been successfully implemented in developed hardware. [ABSTRACT FROM AUTHOR]

In this study, a 13‐level switched‐capacitor inverter with triple voltage gain is proposed. The proposed structure generates 13‐level output voltage using only one DC source, eleven switches, and three capacitors. The capacitors have the capability of self‐balancing without the use of additional circuits or complex control methods. Additionally, the inrush current of the capacitors has been reduced using a soft charging method. The proposed structure has been compared with different 13‐level structures presented in recent studies in terms of various parameters such as the number of semiconductor devices, the number of DC sources, voltage gain, Maximum Blocking Voltage (MBV), and Total standing Voltage (TSV). Another advantage of the proposed structure is the non‐use of any diode and its cost‐effectiveness. In addition, the power losses of the proposed structure have been evaluated, and its efficiency has been calculated for various output powers. Finally, the performance of the proposed structure has been verified through simulation and laboratory implementation under both stable and various dynamic conditions. [ABSTRACT FROM AUTHOR]

In this manuscript, a direct current (DC) boost converter based on a switched-capacitor circuit with closed-loop control, tailored for applications with high-voltage gain, is introduced. The converter utilizes a network with switching capacitors to enhance voltage gain without relying on inductors, making it ideal for high-voltage scenarios. An active disturbance rejection control (ADRC)-based control scheme is used to maintain output voltage stability in the presence of disturbances. The proposed converter's functionality and performance are assessed through simulations and experimental tests under various load conditions. A loss analysis, considering the losses from switches and diodes, is provided to determine the net efficiency. The results from both simulations and experiments show that the proposed converter achieves a high-voltage gain, excellent load regulation, and rapid transient response, highlighting its potential for applications that require a high-voltage boosting operation. [ABSTRACT FROM AUTHOR]

In this paper, we consider the cooperative robust output regulation problem for a class of nonlinear multi-agent systems over jointly connected switching networks. First, by attaching each subsystem with an input driven filter, we obtain an extended system. Second, by integrating the distributed observer approach and the distributed internal model approach, we convert the cooperative output regulation problem of the original system into a distributed robust stabilisation problem of an augmented error system which is also a multi-agent system. Finally, we solve the original problem by stabilising the augmented error system via a distributed output feedback control law. [ABSTRACT FROM AUTHOR]

This paper investigates the design of a reduced‐order H∞$H_\infty$ filter for a specific class of switched complex network systems with time‐varying delays. To handle the nonlinear components of the complex network, a T‐S fuzzy model is employed to convert them into a set of linear components. To tackle the issue of heavy network load, a memory‐based adaptive trigger mechanism is proposed. In this study, a reduced‐order H∞$H_\infty$ state estimator is designed using the T‐S fuzzy model. To demonstrate the exponential stability of the error system, a suitable Lyapunov function is constructed based on the Lyapunov stability principle. The parameter matrix of the reduced‐order estimator is determined using the linear matrix inequality and convex linearization method. Additionally, a sufficient condition for the exponential stability of the error system at the suppression level is provided. Finally, the feasibility of the proposed scheme is validated through a simulation experiment. [ABSTRACT FROM AUTHOR]

State‐based games contain an additional state space by comparing with normal games. Correspondingly, the equilibrium of state‐based games is called recurrent state equilibrium (RSE). For state‐based games, the stochastic convergence to RSE is investigated in this paper. Firstly, the stochastic convergence of state‐based games is defined. Then, a kind of state‐based best‐response update rule is designed for state‐based games. Under this update rule, the state‐based games can be converted into the Markovian switching logical networks through the semi‐tensor product. Next, based on the results of Markovian switching logical networks and positive systems, the stochastic convergence of state‐based games is investigated and a verifiable criterion is derived. Finally, an example is presented to illustrate the validity of the obtained criterion. [ABSTRACT FROM AUTHOR]

Locomotion in mammals is directly controlled by the spinal neuronal network, operating under the control of supraspinal signals and somatosensory feedback that interact with each other. However, the functional architecture of the spinal locomotor network, its operation regimes, and the role of supraspinal and sensory feedback in different locomotor behaviors, including at different speeds, remain unclear. We developed a computational model of spinal locomotor circuits receiving supraspinal drives and limb sensory feedback that could reproduce multiple experimental data obtained in intact and spinal-transected cats during tied-belt and splitbelt treadmill locomotion. We provide evidence that the spinal locomotor network operates in different regimes depending on locomotor speed. In an intact system, at slow speeds (<0.4 m/s), the spinal network operates in a non-oscillating state-machine regime and requires sensory feedback or external inputs for phase transitions. Removing sensory feedback related to limb extension prevents locomotor oscillations at slow speeds. With increasing speed and supraspinal drives, the spinal network switches to a flexor-driven oscillatory regime and then to a classical half-center regime. Following spinal transection, the model predicts that the spinal network can only operate in the state-machine regime. Our results suggest that the spinal network operates in different regimes for slow exploratory and fast escape locomotor behaviors, making use of different control mechanisms. [ABSTRACT FROM AUTHOR]

The article presents the methodology of optimization of technology mapping of a multi-output function implemented in the form of sum of product (SOP) networks. The optimization is based on the concept of reducing the switching activity of combinational circuits. The aim of reducing network switching is to limit the consumption of dynamic power. Since dynamic power is one of the components of the total power consumed by digital systems, this leads to an optimization focused on the energy efficiency of digital systems. The basis of the proposed method is the technology mapping using a modified output graph describing the result of minimizing the multi-output function. The modified output graph, in terms of parameters associated with dynamic power, is defined as a switching graph. It was assumed that the key parameter associated with dynamic power is the switching activity of individual nodes of the logic network. The article presents elements of switching graph optimization which lead to the improvement of parameters associated with the dynamic power of the circuit. The essence of the proposed optimization methods is the appropriate movement of products and connections occurring in the logic network. Reducing the number of logic network vertices is also extremely important. The effectiveness of the proposed method was confirmed by the results of experiments performed on selected benchmarks. A significant reduction in the total value of switching activity was obtained for the optimized structures. [ABSTRACT FROM AUTHOR]

This article addresses the multiple symmetric task control issue of networked robot systems modeled by the Euler–Lagrange equation under a switching communication network topology. A distributed coordinated control protocol is presented with the aid of multiple virtual leaders. Based on the special structure of the network topology, some geometric convergence criteria under which the network can realize multiple symmetric consensus is given. Finally, two simulations conducted on seven two‐link revolute arms and eleven mass agents are proposed to illustrate our design, respectively. [ABSTRACT FROM AUTHOR]

The incorporation of molecular switches into polymer networks has been a powerful approach for the development of functional polymer materials that display macroscopic actuation and function enabled directly by molecular changes. However, such materials sometimes require harsh conditions to perform their functions, and the design of new molecular photoswitches that can function under physiological conditions is highly needed. Here, we report the design and synthesis of a spiropyridine-based photoswitchable hydrogel that exhibits light-driven actuation at physiological pH. Owing to its high pKa, spiropyridine maintains its ring-open protonated form at neutral pH, and the resulting hydrogel remains in a swollen state. Upon irradiation with visible light, the ring closure of spiropyridine leads to a decrease in the charge and a reduction in the volume of the hydrogel. The contracted gel could spontaneously recover to its expanding state in the dark, and this process is highly dynamic and reversible when the light is switched on and off. Furthermore, the hydrogel shows switchable fluorescence in response to visible light. Bending deformation is observed in the hydrogel thin films upon irradiation from one side. Importantly, the independence of this spiropyridine hydrogel from the acidic environment makes it biotolerant and shows excellent biocompatibility. This biocompatible spiropyridine hydrogel might have important biorelated applications in the future. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper is concerned with almost sure exponential synchronization of multilayer complex networks with Markovian switching via aperiodically intermittent discrete observation noise. First, Markovian switching and multilayer interaction factors are taken into account simultaneously, which make our system more general compared with the existing literature. Meanwhile, the network architecture may be undirected or directed, and consequently, the adjacency matrix is symmetrical and asymmetrical. Second, the control strategy is based on aperiodically intermittent discrete observation noise, where the average control rate is integrated to depict the distributions of work/rest intervals of the control strategy from an overall perspective. Third, different from the work about p th moment exponential synchronization of network systems, by utilizing M-matrix theory and various stochastic analysis techniques including the Itô formula, the Gronwall inequality, and the Borel-Cantelli lemma, some criteria on almost sure exponential synchronization of multilayer complex networks with Markovian switching have been constructed and the upper bound of the duration time has been also estimated. Finally, several numerical simulations are exhibited to validate the effectiveness and feasibility of our analytical findings. [ABSTRACT FROM AUTHOR]

In the video compression industry, video compression tailored to machine vision tasks has recently emerged as a critical area of focus. Given the unique characteristics of machine vision, the current practice of directly employing conventional codecs reveals inefficiency, which requires compressing unnecessary regions. In this paper, we propose a framework that more aptly encodes video regions distinguished by machine vision to enhance coding efficiency. For that, the proposed framework consists of deep learning-based adaptive switch networks that guide the efficient coding tool for video encoding. Through the experiments, it is demonstrated that the proposed framework has superiority over the latest standardization project, video coding for machine benchmark, which achieves a Bjontegaard delta (BD)-rate gain of 5.91% on average and reaches up to a 19.51% BD-rate gain. [ABSTRACT FROM AUTHOR]

In this paper, the minimal observability of switching Boolean networks (SBNs) is investigated. Firstly, applying the semi‐tensor product (STP) method of matrices, a parallel extension system is constructed, based on which a necessary and sufficient condition to detect the observability of the SBNs is given. Secondly, when an SBN is unobservable, the specific steps to obtain the required measurements to make the system observable are given using the set reachable method; however, the measurements given in this part are not necessarily the fewest. Then, a criterion for determining the minimum number of measurements is further proposed through a constructed indicator matrix. Lastly, the effectiveness of the new results is verified by an example. [ABSTRACT FROM AUTHOR]

Biological systems are robust and redundant. The redundancy can manifest as alternative metabolic pathways. Synthetic double lethals are pairs of reactions that, when deleted simultaneously, abrogate cell growth. However, removing one reaction allows the rerouting of metabolites through alternative pathways. Little is known about these hidden linkages between pathways. Understanding them in the context of pathogens is useful for therapeutic innovations. We propose a constraint-based optimisation approach to identify inter-dependencies between metabolic pathways. It minimises rerouting between two reaction deletions, corresponding to a synthetic lethal pair, and outputs the set of reactions vital for metabolic rewiring, known as the synthetic lethal cluster. We depict the results for different pathogens and show that the reactions span across metabolic modules, illustrating the complexity of metabolism. Finally, we demonstrate how the two classes of synthetic lethals play a role in metabolic networks and influence the different properties of a synthetic lethal cluster. [ABSTRACT FROM AUTHOR]

In response to the challenge of existing wireless communication anti-jamming methods in effectively handling unknown jamming, this paper proposes a multi-parameter control anti-jamming algorithm for wireless communication systems based on the Linear–Quadratic Regulator (LQR). First, the proposed algorithm models the wireless communication system as a linear switched system based on the modulation and coding scheme. Subsequently, a feedback controller design method based on the LQR is introduced. By utilizing the multiple Lyapunov function method combined with linear matrix inequalities, sufficient criteria for the asymptotic stability of the system under unknown jamming conditions are provided. Finally, theoretical analysis and simulation results indicate that the proposed algorithm can rapidly adjust modulation and coding schemes as well as transmission power in complex jamming environments, thereby maintaining bit error rate (BER) stability and enhancing the reliability of the communication system. [ABSTRACT FROM AUTHOR]

This paper is dedicated to studying the mean square exponential stability of switched stochastic time‐varying delay neural networks with asynchronous switching aperiodic intermittent control. By utilizing the Halanay‐type inequality and designing appropriate asynchronous switching aperiodic intermittent control, several novel stability criteria of switched stochastic delay neural networks with asynchronous aperiodic intermittent control are presented under the Lyapunov function method and Lyapunov functional method. Among them, asynchronous switching aperiodic intermittent controllers are more practical and flexible compared to state feedback controllers. Finally, we provide two examples to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This research paper primarily focuses on the synchronization of a specific class of multi‐weighted coupled neural networks (MWCNNs) with switching topology, employing two adaptive control methods. In complex environments and under the influence of communication disturbances, the topology structures of coupled neural networks with multiple weights inevitably undergo time‐varying changes. To address this, we propose a novel type of MWCNNs with switching topologies. To ensure synchronization within this network, we develop sufficient conditions based on Lyapunov functional and inequality techniques. These conditions guarantee the achievement of synchronization. Moreover, we address the synchronization problem by employing node‐based and edge‐based adaptive controllers. Finally, we provide a numerical example to demonstrate the effectiveness of the obtained results. This example serves as empirical evidence showcasing the successful application of the proposed synchronization approach in practical scenarios. [ABSTRACT FROM AUTHOR]

This study examines the problem of minimizing the amount and distribution of time delays or latencies experienced by data as they travel from one point to another within a software-defined network (SDN). For this purpose, a model is proposed that seeks to represent the minimization of the distances between network switches in proportion to the total nodes in a network. The highlights of this study are the proposal of two mixed-integer quadratic models from a fractional initial version. The first is obtained by transforming (from the original fractional model) the objective function into equivalent constraints. The second one is obtained by splitting each term of the fraction with an additional variable. The two developed models have a relationship between switches and controllers with quadratic terms. For this reason, an algorithm is proposed that can solve these problems in a shorter CPU time than the proposed models. In the development of this research work, we used real benchmarks and randomly generated networks, which were to be solved by all the proposed models. In addition, a few additional random networks that are larger in size were considered to better evaluate the performance of the proposed algorithm. All these instances are evaluated for different density scenarios. More precisely, we impose a constraint on the number of controllers for each network. All tests were performed using our models and the computational power of the Gurobi solver to find the optimal solutions for most of the instances. To the best of our knowledge, this work represents a novel mathematical representation of the latency density management problem in an SDN to measure the efficiency of the network. A detailed analysis of the test results shows that the effectiveness of the proposed models is closely related to the size of the studied networks. Furthermore, it can be noticed that the performance of the second model compared to the first one presents better behavior in terms of CPU times, the optimal solutions obtained, and the reduced Mipgaps obtained using the solver. These findings provide a deep understanding of how the models operate and how the optimization dynamics contribute to improving the efficiency and performance of SDNs. [ABSTRACT FROM AUTHOR]

Random variations in microelectronic circuit structures represent the source of entropy for physical unclonable functions (PUFs). In this paper, we investigate delay variations that occur through the routing network and switch matrices of a field-programmable gate array (FPGA). The delay variations are isolated from other components of the programmable logic, e.g., look-up tables (LUTs), flip-flops (FFs), etc., using a feature of Xilinx FPGAs called dynamic partial reconfiguration (DPR). A set of partial designs is created to fix the placement of a time-to-digital converter (TDC) and supporting infrastructure to enable the path delays through the target interconnect and switch matrices to be extracted by subtracting out common-mode delay components. Delay variations are analyzed in the different levels of routing resources available within FPGAs, i.e., local routing and across-chip routing. Data are collected from a set of Xilinx Zynq 7010 devices, and a statistical analysis of within-die variations in delay through a set of the randomly-generated and hand-crafted interconnects is presented. [ABSTRACT FROM AUTHOR]

Based on the adaptive control structure of neural networks, this paper proposes a novel output voltage control strategy for DC converters. The strategy regulates the inductor current to maintain a constant voltage by adjusting the duty cycle of four-switch buck—boost (FSBB) converters. A nonlinear average model for the FSBB converter, derived from its energy consumption, is introduced, and its effectiveness is demonstrated through simulations. The simulations confirm that the FSBB converter enables zero-voltage switching (ZVS) of the four switches across the entire operating voltage range. The comparative simulation results show that the proposed control strategy achieves faster voltage regulation while ensuring ZVS, leading to improved converter performance across the full power range. [ABSTRACT FROM AUTHOR]

A finite-time consensus protocol is presented in this paper for a network of connected heterogeneous agents with fixed and switching topology. In this study, two cases directed networks with fixed topology and directed networks with switching topology are examined. Convergence analysis for both the cases are presented. An independent tracking controller, which assures that an agent follows an ideal trajectory designed by sliding mode based consensus control, is devised. Agents stability are independent of the distributed consensus algorithm. Under the proposed control methodology, the measurement vectors of heterogeneous agents converge to the agreement value in a finite amount of time. The comparison results with the existing works show the proposed algorithm's improved performance in terms of convergence time in presence of disturbances. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • An optoelectronic spiking neuron is developed. • The gate-modulated PDVT-10 channel was combined with a volatile threshold switching memristor. • The device achieves optoelectronic performance through resistance-matching mechanism. • The neuron alters its spiking behavior in a manner resembling that of a retina. • The artificial neuron accurately replicates neuronal signal transmission in a biologically manner. The human perception and learning heavily rely on the visual system, where the retina plays a vital role in preprocessing visual information. Developing neuromorphic vision hardware is based on imitating the neurobiological functions of the retina. In this work, an optoelectronic neuron is developed by combining a gate-modulated PDVT-10 channel with a volatile threshold switching memristor, enabling the achievement of optoelectronic performance through a resistance-matching mechanism. The optoelectronic spiking neuron exhibits the ability to alter its spiking behavior in a manner resembling that of a retina. Incorporating electrical and optical modulation, the artificial neuron accurately replicates neuronal signal transmission in a biologically manner. Moreover, it demonstrates inhibition of neuronal firing during darkness and activation upon exposure to light. Finally, the evaluation of a perceptron spiking neural network utilizing these leaky integrate-and-fire neurons is conducted through simulation to assess its capability in classifying image recognition algorithms. This research offers a hopeful direction for the development of easily expandable and hierarchically structured spiking electronics, broadening the range of potential applications in biomimetic vision within the emerging field of neuromorphic hardware. [ABSTRACT FROM AUTHOR]

Network reconfiguration is a very economical technique that can improve electrical system performance. The development of semiconductor electrical equipment technology to meet human needs and work, known as nonlinear loads, has had a negative impact in the form of the spread of harmonic distortion which can accelerate the aging process and even damage equipment. In this paper, the effect of the optimization results of network reconfiguration techniques on the Sungguminasa 165-bus Executive Unit Service or Unit Layanan Pelanggan (ULP) electrical system is contaminated with harmonic distortion due to the use of nonlinear loads. This technique was optimized using the particle swarm optimization (PSO) method with a multi objective function in the form of minimizing %THDv and total losses with several limitations. Simulation results from the optimization process of several study cases are shown by activating the five tie switches from the network reconfiguration process on the Sungguminasa 165-bus ULP system which is able to improve power quality by reducing the average %THDv by 3.89% and total losses by 8.19%. [ABSTRACT FROM AUTHOR]

This paper proposes an extended DC‐DC converter with high voltage conversion ratio and soft‐switching ability. The proposed converter has active switched‐inductors, switched‐capacitors included in the conventional high gain converter and operates in continuous conduction mode (CCM). Simple auxiliary resonant elements are added on the primary leg of the converter to provide design freedom for soft‐switching operation. The significant merits of the proposed converter are lesser voltage and current stresses, high voltage gain with reduced component count and better efficiency. Additional feature of this converter is soft‐switching operation under different load conditions and duty ratios without considerably increasing stresses. The zero voltage switching (ZVS) turn‐on operation is obtained for all switching devices. Therefore, switching power losses are minimized greatly. This paper presents the description, principles of operation and steady state analysis in comparison with the existing high gain converters. The theoretical analysis is verified with a 350 W prototype operated at input is 20 V and output is 220 V. The overall efficiency achieved is 96.7%. The obtained results confirm ZVZCS operation at full load. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) speaks to the current and future state of the Internet. Numerous things (objects) related to the Internet generate a large amount of information that requires a ton of labor and prepare tasks to move to valuable data. In addition, for the association and control of this enormous information, the original ideas in the project and the executives of the IoT system need to expedite and improve its presentation. A software-defined networking (SDN) system is another worldview that has recently emerged to cover all the complexities in the traditional system architecture by summarizing all the controls and management functions from the basic devices (things in IoT). The open-flow protocol is used to make messages between switches and controllers. It is a correspondence conference, through which the controller integrates the path of the network pocket with switches. Therefore, data packets should be directed to the optimum path to improve system operation. The best or optimal path for packet routing in the SDN data plane is found using the Lion Optimization Algorithm (LOA), which is proposed in this study. Response times and packet loss rates can both be decreased by choosing the best route between the hosts. The suggested LOA outperforms current optimal path detection methods in terms of performance, delay, packet delivery rate, performance, and pocket loss rate, according to simulation findings. [ABSTRACT FROM AUTHOR]

This paper introduces an advanced observer-based control strategy designed for fractional multi-agent systems operating in hostile environments. We take into account the dynamic nature of the agents with nonlinear delayed dynamics and consider external disturbances affecting the system. The manuscript presents an improved observation-based control approach tailored for fractional-order multi-agent systems functioning in challenging conditions. We also establish various applicable conditions governing the creation of observers and disturbance compensation controllers using the fractional Razmikhin technique, signed graph theory, and matrix transformation. Furthermore, our investigation includes observation-based control on switching networks by employing a typical Lyapunov function approach. Finally, the effectiveness of the proposed strategy is demonstrated through the analysis of two simulation examples. [ABSTRACT FROM AUTHOR]

In this article, we study the leader‐following formation problem for high‐order nonlinear multi‐agent systems with an uncertain leader system over switching networks. We first divide the uncertain leader system into two types and then design adaptive distributed observers for them respectively. Then, based on our designed observers, we synthesize two adaptive distributed control laws respectively to solve our problem, forcing the errors between the states of the followers and that of the leader to the prescribed time‐varying desired formation vectors. Finally, our main result is illustrated by two examples. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic event‐triggered fixed‐time control scheme for the phase synchronization of Kuramoto networks with switching topology and stochastic coupling noise. To deal with the problems of switching topology and stochastic coupling noise, a multilayered control structure with a specially designed noise reduction layer is developed. The effectiveness is proved based on stochastic differential theory. To save communication resources and reduce control frequency, a dynamic event‐triggered mechanism is proposed. By introducing a dynamic variable into the triggering condition, the triggered instants are further reduced compared to the traditional static event‐triggered method. The synchronizing criteria and parameter conditions are established with stochastic Lyapunov stability theory. The analysis of Zeno behavior is also given. Finally, numerical simulation experiments are conducted to demonstrate the effectiveness of the proposed dynamic event‐triggered control scheme. [ABSTRACT FROM AUTHOR]

Vehicle ad hoc networks (VANETs) have garnered considerable attention for their potential to enhance road safety and facilitate advanced driver assistance systems. A fundamental aspect of VANET is the formation of stable clusters and cluster heads (CH) for improved network performance. Due to the dynamic nature of VANET and the different mobility of the vehicles, maintaining CH stability is significant. To address this issue, this study presents the network as connecting hypergraphs. The proposed approach uses an improved tensor-trace maximization-based spectral clustering algorithm (iTTM) and eigen heuristics to generate an optimal. The suggested clustering approach is followed by the CH selection based upon the four vehicle attributes: modularized link lifetime, connectivity level, relative speed, and consensus trust score. The multi-decision CRITIC approach will decide the CH in each cluster using those four attributes. These metrics have improved throughput and reduced packet delay to improve network performance. Simulation results, conducted in Delhi's Connaught Place using SUMO, demonstrate the proposed method's superiority in CH stability, throughput, and packet delay compared to existing algorithms. The state-of-the-art comparison is done on the criteria of CH stability, which comes out to be 84% in the proposed case and 82% in the previous work. The evaluation is done with recently published research on the CH rate of change and to validate the lower switching frequency in the network. The network is evaluated with different average speeds of the vehicles, and superior performance is noted in the proposed approach with the increase in lesser switching frequency with higher average speed than state-of-the-art. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for rapidly balancing lithium-ion batteries using a single DC–DC converter, enabling direct energy transfer between high- and low-voltage cells. Utilizing relays for cell pair selection ensures cost-effectiveness in the switch network. The control system integrates a battery-monitoring IC and an MCU to oversee cell voltage and ensure battery protection. A prototype circuit with twelve lithium-ion batteries demonstrates the method's efficacy, achieving a remarkable balancing time of 48 min during charging with a maximum efficiency of 89.85%. Comparative analysis with other methods underscores the superior performance of the proposed balancing circuit in terms of balancing time and implementation cost. Furthermore, this paper delves into hardware aspects of battery management systems (BMSs) for electric vehicles and stationary applications. It offers an overview of prevailing concepts in state-of-the-art systems, aiding readers in assessing considerations essential for BMS design in various applications. The discussion includes examples of battery packs sourced from commercially available electric vehicles. Subsequently, the manuscript addresses implementation aspects concerning the measurement of critical physical variables such as voltage, current, and temperature, alongside balancing strategies. [ABSTRACT FROM AUTHOR]

In the literature, three-stage switching networks have been considered for nodes in elastic optical networks, where switches with spectrum conversion capability are placed in the first and third stages (wavelength–space–wavelength—WSW) or only in the second stage (space–wavelength–space—SWS). This paper proposes three-stage switching networks where the switches with spectrum conversion functions are located only in the first stage (wavelength–space–space—WSS) or only in the third stage (space–space–wavelength—SSW). For these networks, the strict-sense non-blocking conditions are derived and proved, and the number of elements required for their construction is assessed. It turns out that the proposed networks can be constructed with 50% fewer tunable spectrum converters than in the WSW networks, and this reduction is even greater in the case of the SWS networks. [ABSTRACT FROM AUTHOR]

Sensor networks generate large volumes of data that require robust processing, storage, and analysis capabilities provided by data centers. Software-defined networking, as a new network technique for designing and building networks, provides new concepts and solutions for the current data center system construction. However, the software-defined networking (SDN) framework based on the OpenFlow protocol cannot support new protocols or actively add unknown protocols, since they cause the control plane protocol to become more bloated. It is difficult to solve the problem of network scalability because components are being continuously redesigned. Therefore, an optimized source routing technology is proposed in combination with the protocol-oblivious forwarding technology. Furthermore, a low-cost and extensible network switch is designed to realize the independent data forwarding mechanism that effectively reduces the amount of network control signaling. The experimental results show that the scheme can significantly reduce the scale of flow table items and improve the hardware forwarding rates as well as the flexibility of forwarding rules. Moreover, the design scheme has a good application prospect. [ABSTRACT FROM AUTHOR]

The microscopically structural switching of supramolecular networks endows programmable gel materials with dynamic hiding properties and functionalities. However, the reconstruction of supramolecular network will destroy the programming information imprinted on the original network structure, making it difficult to restore to the original state. Here, a novel intelligent programmable photonic gel composed of cellulose nanocrystals (CNC) and acrylamide is constructed. The mechanical properties and optical signals of gel can be switched reversibly on demand by reasonably designing the winding and compression between molecular structures. Under this conversion mechanism, the rigid "skeleton" constructed from the CNC chiral structure perfectly acts as the coding substrate. Importantly, even after multiple dynamic switching of the supramolecular network, the encoded information can be displayed completely and accurately on the CNC chiral structure in the stretched state. In addition, the 5D controllable conversion of stiffness, transparency, stretchability, color, and shape greatly improves the security and confidentiality of the encoded information inside the gel. This is a successful example of the application of CNC chiral structure in switchable supramolecular network materials. It is believed that the flexible variability and advanced camouflage give the intelligent gel the potential to be used in a wider range of practical scenarios. [ABSTRACT FROM AUTHOR]

In order to further solve the problem of weak attack defense existing in the traditional network architecture, improve the shortcomings of network architecture in processing capacity, hardware expansion, security protection and other aspects, and better cope with the security challenges under the new network architecture, this article aims to provide more secure computer information exchange and sharing services for enterprises. A network access layer security protection system based on zero trust architecture is constructed. At the same time, the zero-trust architecture evaluation algorithm based on fuzzy theory is used to construct the security protection model. System tests show that more than 100 hosts on the enterprise access layer network use switches that support SNMP, and the security protection system at the network access layer processes more than 1500 attacks. In addition, malicious IP address changes are effectively prevented and the security protection level is greatly improved. [ABSTRACT FROM AUTHOR]

Introduction: Gene regulatory networks (GRNs) are characterized by their dynamism, meaning that the regulatory interactions which constitute these networks evolve with time. Identifying when changes in the GRN architecture occur can inform our understanding of fundamental biological processes, such as disease manifestation, development, and evolution. However, it is usually not possible to know a priori when a change in the network architecture will occur. Furthermore, an architectural shift may alter the underlying noise characteristics, such as the process noise covariance. Methods: We develop a fully Bayesian hierarchical model to address the following: a) sudden changes in the network architecture; b) unknown process noise covariance which may change along with the network structure; and c) unknown measurement noise covariance. We exploit the use of conjugate priors to develop an analytically tractable inference scheme using Bayesian sequential Monte Carlo (SMC) with a local Gibbs sampler. Results: Our Bayesian learning algorithm effectively estimates time-varying gene expression levels and architectural model indicators under varying noise conditions. It accurately captures sudden changes in network architecture and accounts for time-evolving process and measurement noise characteristics. Our algorithm performs well even under high noise conditions. By incorporating conjugate priors, we achieve analytical tractability, enabling robust inference despite the inherent complexities of the system. Furthermore, our method outperforms the standard particle filter in all test scenarios. Discussion: The results underscore our method's efficacy in capturing architectural changes in GRNs. Its ability to adapt to a range of time-evolving noise conditions emphasizes its practical relevance for real-world biological data, where noise presents a significant challenge. Overall, our method provides a powerful tool for studying the dynamics of GRNs and has the potential to advance our understanding of fundamental biological processes. [ABSTRACT FROM AUTHOR]

Analyzing visual scenes and computing ensemble statistics, known as perceptual averaging, is crucial for the stable sensory experience of a cognitive agent. Despite the apparent simplicity of applying filters to scenes, the challenge arises from our brain's seamless transition between summarization and individuation across various reference frames (retinotopic, spatiotopic, and hemispheric). In this study, we explore the capability of a neural network to dynamically switch between individuation and summarization. Our chosen computational model, a fully connected on-center off-surround recurrent neural network previously employed for enumeration/individuation, demonstrates the potential to extract both summary statistics and achieve high individuation accuracy. Notably, our results show that the individuation accuracy can reach close to perfection within a presentation duration of 100 ms, but not so for summarization. We have also shown a spatially varying excitation version of the network that can explain quite a few interesting spatio-temporal patterns of perception. These findings not only highlight the feasibility of such a neural network but also provide insights into the temporal dynamics of ensemble perception. [ABSTRACT FROM AUTHOR]

This article presents a fault‐tolerant platooning control algorithm for a class of nonlinear homogeneous multi‐vehicle systems under unreliable network communication environment. The considered types of actuator failures in individual vehicle are loss‐in‐effectiveness, and bias faults. Suppose the communication network among vehicles is here described as a switching graph subject to intermittent communications. Unlike the existing results dealing with vehicle platoon under continuous communications, this article develops a hierarchical fault‐tolerant platooning control approach, under which, the multiple vehicle coordination platooning objective is ensured even in the cases of discontinuous communication faults and actuator failures. First, each following vehicle can estimate the desire reference information via cooperative adaptive virtual estimator even in intermittent communications. Second, the local fault‐tolerant controller with adaptive parameter update mechanism can guarantee the practical position and velocity of following vehicles asymptotically track the desire estimations. Finally, a simulation example of a team of autonomous vehicles is given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a new simultaneous framework of distribution network operation is proposed based on the scheduling of photovoltaic/wind/battery multi-microgrids with network reconfiguration considering self-healing. The objective function is considered to minimize the energy losses, and multi-microgrids cost and improve the reliability indices including minimization of energy not-supplied (ENS) and minimizing system average interruption duration (SAIDI) and system average interruption frequency (SAIFI) indices. The optimization variables are defined as the situation of the distribution network switches to find the network's optimal configuration with the installation location and size of renewable resources and battery energy storage during 24 hours. An improved beluga whale optimization (IBWO) based on a nonlinearly diminishing inertia weight (NDIW) approach is used to find the optimal variable set of the problem. The recommended methodology is implemented on 33-bus and real 59-bus distribution networks. The results demonstrated that by obtaining an optimal state of the network switches in the event of a fault, as well as the optimal scheduling of the two microgrids, the energy losses have decreased and the reliability indices have improved. The outcomes of the proposed methodology based on the hybrid multi-microgrid allocation and network reconfiguration are stated that the losses, ENS, SAIDI, and SAIFI are reduced by 66.39%, 54.00%, 50.24%, and 33.61%, respectively, for 33-bus network and are declined by 65.29%, 57.44%, 48.63%, and 62.33%, respectively, for the real 59-bus Ahvaz network in comparison with the base network. The obtained results illustrated that in the condition of the network line outage, by simultaneously implementing the reconfiguration with the change of network switches and the optimal allocation and scheduling of HMGs in the network, self-healing is provided to prevent a significant weakening of the network performance so that the resilience is improved in addition to minimizing the energy losses and the cost of HMG energy injection compared to the base network. The findings revealed that the objectives including losses, ENS, SAIFI, and SAIDI are increased by 78.29%, 33.00%, 83.33%, and 35.11%, respectively, due to outage of line 22 of the 33-bus network and these objectives are increased by 52.32%, 10.30%, 32.29%, and 79.66%, respectively, due to outage of line 12 of the 59-bus network compared with not considering the line outage. Moreover, the superior capability of the recommended NDIW-based IBWO has been confirmed in comparison with the well-known particle swarm optimizer (PSO) and ant lion optimizer (ALO) in solving the problem to achieve better objective value. [ABSTRACT FROM AUTHOR]

Circadian rhythms are generated by complex interactions among genes and proteins. Self-sustained ∼24 h oscillations require negative feedback loops and sufficiently strong nonlinearities that are the product of molecular and network switches. Here, we review common mechanisms to obtain switch-like behavior, including cooperativity, antagonistic enzymes, multisite phosphorylation, positive feedback, and sequestration. We discuss how network switches play a crucial role as essential components in cellular circadian clocks, serving as integral parts of transcription-translation feedback loops that form the basis of circadian rhythm generation. The design principles of network switches and circadian clocks are illustrated by representative mathematical models that include bistable systems and negative feedback loops combined with Hill functions. This work underscores the importance of negative feedback loops and network switches as essential design principles for biological oscillations, emphasizing how an understanding of theoretical concepts can provide insights into the mechanisms generating biological rhythms. [ABSTRACT FROM AUTHOR]

This article addresses the hostile-based bipartite containment control of nonlinear fractional multi-agent systems (FMASs) with input delays. Several fundamental algebraic criteria have been offered by the use of signed graph theory. To make the controller design more realistic, we assumed that the controller was under some disturbance. For the analysis of bipartite containment control, we used a fixed and switching signed network. The commonly used Lyapunov function approach and the Razumikhin technique were used. The use of these techniques can conquer the challenge brought on by switching, temporal delays, and fractional mathematics. To better elucidate the theoretical results, two examples are provided. [ABSTRACT FROM AUTHOR]

This study describes an array antenna that allows for reconfiguration of the three significant antenna properties, that is, radiation pattern, half‐power beamwidth (HPBW), and single and bi‐directional beam. A reconfigurable reflecting surface (RRS) has been designed and incorporated with the array antenna on the top and bottom. The RRS works to reflect or pass the incident electromagnetic wave. It enables us to reconfigure from single to multibeam radiation in the ±z direction. It also provides two levels of HPBW, that is, 49.6° and 95°. Eventually, the same three sets of antennae have been stacked and rotated with a 60° angle to achieve the radiation pattern reconfiguration in the entire azimuth plane. It conforms to reconfigure all three antenna properties in six directions at an equal interval of 60° angle. The achieved maximum gain in a narrow beam is 9.56 dBi. The proposed reconfigurable antenna array can be used in modern wireless communication applications. [ABSTRACT FROM AUTHOR]

Data traffic is rapidly growing due to e-commerce, digital communication, and the digital world. Optical networks must provide a better solution to enhance transmission and improve service with cost efficiency. Considerable investigations of the 64QAM (Quadrature Amplitude Modulation) model have been conducted on wireless and optical communication to improve transmission efficiency. The next generation 400Gb/s systems are now widely recognized to be commercially accessible. At the same time, optical communication networks need a superior method to provide the best Quality of Transmission with improved data transmission efficiency. This paper aims to improve the Quality of Transmission in Optical Communication Networks (OCN). Therefore, a simple and fast reconfigurable network model is essentially required. However, there is a problem primarily related to configuring the network parameters to improve the Quality of Transmission (QoT). Research has shown that deep learning algorithms can improve QoT. Recurrent Neural Networks and Long-Short-Term-Memory (RNN-LSTM) algorithms are employed to leverage the factors of QoT in OCN. The RNN model analyzes the physical network parameters, and LSTM analyzes the dynamic data parameters and data from OCN. The Gaussian processes and path computation elements are utilized to obtain a mean absolute Signal Noise Ratio error of merely 0.1dB as a better result by the Gaussian process. The proposed model can provide high flexibility in changing the network topologies, planning, and period with less complexity by including a dataset evolution, adjusting the parameters, and examining output. A real-time dataset is analyzed using RNN-LSTM, implemented in Python, and experimented with. The throughput, bandwidth, and modulation path following light paths are calculated in the experiment to estimate the QoT. The experimental results showed that the proposed RNN-LSTM model provides better QoT. From the comparison, the proposed model provides a better throughput of 1 to 2 Gbps and Under Provisioning Ratio of 0.5 Hz over the existing models. [ABSTRACT FROM AUTHOR]

The distributed adaptive fuzzy coordination control (DAFCC) method for the leader-following for non-affine nonlinear (NAN) multi-agent systems (MASs) with actuator failures (including partial failures and actuator bias failures) under the unreliable switching communication environments is proposed in this article. First, based on the neighborhood state information, a group of distributed reference observer (DRO) is constructed so that all followers can easily estimate the leader's information. Second, the implicit function theorem and the mean value theorem are utilized to convert the non-affine term into the corresponding affine term in order to solve the non-affine term in the NAN system. Third, to achieve global synchronization, we design an adaptive fuzzy coordination fault-tolerant controller with local estimation. Besides, the DAFCC method presented in this paper solves the cooperative control problem when switching undirected networks with intermittent communications. Finally, simulation is used to validate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]