Effects of two types of noise and switching on the asymptotic dynamics of an epidemic model

This paper mainly investigates dynamics behavior of HIV （human immunodeficiency virus） infectious disease model with switching parameters, and combined bounded noise and Gaussian white noise. This model is different from existing HIV models. Based on stochastic Ito lemma and Razumikhin-type approach, some threshold conditions are established to guarantee the disease eradication or persistence. Results show that the smaller amplitude of bounded noise and R0 〈 1 can cause the disease to die out; the disease becomes persistent if R0 〉 1. Moreover, it is found that larger noise intensity suppresses the prevalence of the disease even if R0 〉 1. Some numerical examples are given to verify the obtained results.

The Modified Multiple Model Switching Tuning Control Application in AVC

In the complex mechanical vibration environment, the dominant frequency of the system varies remarkably and swiftly under various running conditions, which also characterizes uncertainty and time-variation. It is very impending and important to suppress or isolate the detrimental vibrations related to the above memtoned system with active vibration control (AVC) technology. This paper presented the improved linear quadratic gaussian (LQG) control scheme with a specified filter to realize broadband disturbance/noise attenuation and assure intensive suppression of vibration at the key vibration frequency, then applies and modifies the multiple model switching tuning (MMST) control method by disturbance observation to track the variation of dominant vibration component timely. The effectiveness and superiority of the presented control method were demonstrated by numerical simulation and AVC experiment on a flexible cantilever beam under sweeping excitation.

Nonlinear adaptive switching control for a class of non-affine nonlinear systems

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.

Small-signal modeling of GaN HEMT switch with a new intrinsic elements extraction method

A novel and accurate method is proposed to extract the intrinsic elements of the GaN high-electron-mobility transistor（HEMT） switch.The new extraction method is verified by comparing the simulated S-parameters with the measured data over the 5-40 GHz frequency range.The percentage errors E（ij） within 3.83% show the great agreement between the simulated S-parameters and the measured data.

Observation evidence for the entropy switch model of substorm onset

The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observational evidence for this model by using Time History of Events and Macroscale Interactions during Substorms(THEMIS) data. We examined two events, one with and the other without a streamer before substorm onset. In contrast to the stable magnetosphere, where the total magnetic field strength is a decreasing function and entropy is an increasing function of the downtail distance, in both events the total magnetic field strength and entropy were reversed before substorm onset. After onset, the total magnetic field strength, entropy, and other plasma quantities fluctuated. In addition, a statistical study was performed. By confining the events with THEMIS satellites located in the downtail region between ~8 and ~12 Earth radii, and 3 hours before and after midnight, we found the occurrence rate of the total magnetic field strength reversal to be 69% and the occurrence rate of entropy reversal to be 77% of the total 205 events.

Are vulnerable farmers more easily influenced?Heterogeneous effects of Internet use on the adoption of integrated pest management

The Internet is believed to bring more technological dividends to vulnerable farmers during the green agriculture transformation.However,this is different from the theory of skill-biased technological change,which emphasizes that individuals with higher levels of human capital and more technological endowments benefit more.This study investigates the effects of Internet use on farmers'adoption of integrated pest management(IPM),theoretically and empirically,based on a dataset containing 1015 farmers in China's Shandong Province.By exploring the perspective of rational inattention,the reasons for the heterogeneity of the effects across farmers with different endowments,i.e.,education and land size,are analyzed.The potential endogeneity issues are addressed using the endogenous switching probit model.The results reveal that:(1)although Internet use significantly positively affects farmers'adoption of IPM,vulnerable farmers do not benefit more from it.Considerable selection bias leads to an overestimation of technological dividends for vulnerable farmers;(2)different sources of technology information lead to the difference in the degree of farmers'rational inattention toward Internet information,which plays a crucial role in the heterogeneous effect of Internet use;and(3)excessive dependence on strong-tie social network information sources entraps vulnerable farmers in information cocoons,hindering their ability to reap the benefits of Internet use fully.Therefore,it is essential to promote services geared towards elderly-oriented Internet agricultural technology information and encourage farmers with strong Internet utilization skills to share technology information with other farmers actively.

Bell State Preparation Based on Switching Between Quantum System Models

For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between two control channels under one model. Proper control Hamiltonians are selected for the two system models, a switching strategy between the two models is designed, and the stability of the whole switching system is proved in theory. For a given target Bell state, the effectiveness of the proposed switching control strategy between different models is illustrated through simulation experiments.

To jump or not to jump:momentum of jumps in crude oil price volatility prediction

A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predictive ability of the jump component is persistent when forecasting the oil futures market volatility.Specifically,we propose a strategy that allows the predictive model to switch between a benchmark model without jumps and an alternative model with a jump component according to their recent past forecasting performance.The volatility data are based on the intraday prices of West Texas Intermediate.Our results indicate that this simple strategy significantly outperforms the individual models and a series of competing strategies such as forecast combinations and shrinkage methods.A mean–variance investor who targets a constant Sharpe ratio can realize the highest economic gains using the MoJ-based volatility forecasts.Our findings survive a wide variety of robustness tests,including different jump measures,alternative volatility measures,various financial markets,and extensive model specifications.

A Markov Copula Model with Regime Switching and Its Application

Regime switching,which is described by a Markov chain,is introduced in a Markov copula model.We prove that the marginals（X,H^i）,i = 1,2,3 of the Markov copula model（X,H） are still Markov processes and have martingale property.In this proposed model,a pricing formula of credit default swap（CDS） with bilateral counterparty risk is derived.

Modeling,Control,and Protection of Modular Multilevel Converter-based Multi-terminal HVDC Systems:A Review

Multi-terminal direct current(MTDC)grids provide the possibility of meshed interconnections between regional power systems and various renewable energy resources to boost supply reliability and economy.The modular multilevel converter(MMC)has become the basic building block for MTDC and DC grids due to its salient features,i.e.,modularity and scalability.Therefore,the MMC-based MTDC systems should be pervasively embedded into the present power system to improve system performance.However,several technical challenges hamper their practical applications and deployment,including modeling,control,and protection of the MMC-MTDC grids.This paper presents a comprehensive investigation and reference in modeling,control,and protection of the MMC-MTDC grids.A general overview of state-of-the-art modeling techniques of the MMC along with their performance in simulation analysis for MTDC applications is provided.A review of control strategies of the MMC-MTDC grids which provide AC system support is presented.State-of-the art protection techniques of the MMCMTDC systems are also investigated.Finally,the associated research challenges and trends are highlighted.

Performance prediction of switched reluctance generator with time average and small signal models

This paper presents the complete mathematical model and predicts the performance of switched reluctance generator with time average and small signal models. The complete mathematical model is developed in three stages. First, a switching model is developed based on quasi-linear inductance profile. Next, based on the switching behaviour, a time average model is obtained to measure the difference between the excitation and generation time in each switching cycle. Finally, to track control voltage and current wave shapes, a small signal model is designed. The effectiveness of the complete multilevel model combining electrical machine, power converter, load and control with programming language is demonstrated through simulations. A PI controller is used for controlling the voltage of the generator. The results presented show that the controller exhibits accurate tracking control of load voltage under different operating conditions. This demonstrates that the proposed model is able to perform an accurate control of the generated output voltage even in transient situations. The simulation is performed to choose the control parameters and study the performance of switched reluctance generator prior to its actual implementation. Initial experimental results are presented using NI-Data acquisition card to control the output power according to load requirements.

Global Disturbance Rejection of Switched Nonlinear Systems with Switched Internal Model

This paper investigates the problem of global disturbance rejection for a class of switched nonlinear systems where the solvability of the disturbance rejection problem for subsystems is not assumed. The disturbances are assumed to be sinusoidal with completely unknown frequencies, phases and amplitudes. First, as an extension of the classic concept of internal model for non-switched systems, a switched internal model is proposed. Second, in order to solve the problem under study, an adaptive control method is established on the basis of the multiple Lyapunov functions method. Also,adaptive state-feedback controllers of subsystems are designed and incorporated with a switching law to asymptotically reject the unknown disturbances. Finally, an example is provided to demonstrate the effectiveness of the proposed design method.

A Piecewise Switched Linear Approach for Traffic Flow Modeling

Traffic modeling is a key step in several intelligent transportation systems（ITS） applications. This paper regards the traffic modeling through the enhancement of the cell transmission model. It considers the traffic flow as a hybrid dynamic system and proposes a piecewise switched linear traffic model. The latter allows an accurate modeling of the traffic flow in a given section by considering its geometry. On the other hand, the piecewise switched linear traffic model handles more than one congestion wave and has the advantage to be modular. The measurements at upstream and downstream boundaries are also used in this model in order to decouple the traffic flow dynamics of successive road portions. Finally, real magnetic sensor data, provided by the performance measurement system on a portion of the Californian SR60-E highway are used to validate the proposed model.

Small-signal switch model of GaN HEMTs for MMIC applications

Gallium nitride （GaN） high electron mobility transistor （HEMT） with symmetrical structure as a control device is discussed in this paper. The equivalent circuit model is proposed on the basis of physical and electrical properties of the GaN HEMT device. A transistor with 0.5 μm gate length and 6 x 125 gm gate width is fabricated to verify the model, which can be treated as a single pole single throw （SPST） switch due to the ON state and OFF state. The measurement results show a lzood agreement with the simulation results, which demonstrates the effectiveness of the proposed model.

Switched forced SEIRDV compartmental models to monitor COVID-19 spread and immunization in Italy

This paper presents a new hybrid compartmental model for studying the COVID-19 epidemic evolution in Italy since the beginning of the vaccination campaign started on 2020/12/27 and shows forecasts of the epidemic evolution in Italy in the first six months.The proposed compartmental model subdivides the population into six compartments and extends the SEIRD model proposed in[E.L.Piccolomini and F.Zama,PLOS ONE,15(8):1e17,082020]by adding the vaccinated population and framing the global model as a hybridswitched dynamical system.Aiming to represent the quantities that characterize the epidemic behaviour from an accurate fit to the observed data,we partition the observation time interval into sub-intervals.The model parameters change according to a switching rule depending on the data behaviour and the infection rate continuity condition.In particular,we study the representation of the infection rate both as linear and exponential piecewise continuous functions.We choose the length of sub-intervals balancing the data fit with the model complexity through the Bayesian Information Criterion.We tested the model on italian data and on local data from Emilia-Romagna region.The calibration of the model shows an excellent representation of the epidemic behaviour in both cases.Thirty days forecasts have proven to well reproduce the infection spread,better for regional than for national data.Both models produce accurate predictions of infected,but the exponential-based one perform better in most of the cases.Finally,we discuss different possible forecast scenarios obtained by simulating an increased vaccination rate.

Liquidity of China’s government bond market: Measures and driving forces

We construct a daily liquidity index of China’s government bond market using transaction data from the national interbank market during 2001–2020.The index is a composite of popular price-based and quantity-based metrics of liquidity.The composite indices,ob-tained by averaging across different metrics and by applying the principal component analysis,respectively,both point to a better liquidity condition after 2010.Market liquidity swings appear to be highly correlated with domestic funding liquidity and financial mar-ket volatility,but display fewer correlations with global macrofinan-cial indicators.Our findings suggest that the further deepening of the government bond market would support domestic financial stability and monetary operations down the road.

Refined analysis and prediction of natural gas consumption in China

In view of the abrupt and phased features of natural gas consumption,this paper attempts to predict natural gas consumption in China with a refined forecasting approach.First,we establish a Markov switching(MS)model to identify the phase characteristics after eliminating change points in the natural gas consumption sequence,using the product partition model(PPM).The results show that there are"rapid growth"and"slow growth"regimes in the development process of natural gas consumption in China.Second,the Bayesian model average(BMA)method is employed to determine the core determinants of natural gas consumption under sub-regimes,and it is determined that there are significant differences in the influencing factors under different regimes and periods.Third,this paper establishes the BMA model of the"rapid growth"regime after predicting the state of future natural gas consumption in China.We find that,compared to some other models,the BMA model that fully recognizes the regime without considering change points has the best predictive performance.Finally,the results of static and dynamic scenario analyses show that natural gas consumption continues to rise in 2019 and has obvious seasonal charac-teristics,while possible ultra-rapid growth of consumption in the future provides a new requirement for the supply of natural gas.

Understanding the impact of sustainable land-scape management practices on farm productivity under intensifying tropical cyclones: Evidence from Southern Malawi

Southern Malawi is continuously affected by tropical cyclone-related floods(TCRFs),which have negative consequences on households'livelihoods,thereby displacing most households to neighbouring communities of Mozambique.The TCRFs have further threatened national,regional,community,and household food security agenda,which is already constrained by poverty,poor agricultural practices,low use of improved varieties,unaffordable inorganic fertilizers,and fragmenting landholding sizes.Accordingly,households have indigenously engineered resilience-based Sustainable Landscape Management(SLM)practices,like intercropping,agroforestry,cover cropping,and soil and water conservation practices,against the adverse effects of TCRFs on-farm productivity.Hence,this study examines the effect of TCRFs and SLM adoption on-farm productivity.While using rigorous endogenous switching regression econometric tools,the study finds TCRFs reducing farm productivity by 27 percent.After SLM adoption,the study observes farm productivity enhancement by 29-126 percent when households adopt at least one SLM practices under varying degrees of TCRFs.Despite the highlighted advantages of SLM adoption,female farmers are less likely to adopt SLM practices because they do not have access to productive resources.Hence,the study proposes the need of gender targeted extension services,accompanied by some seed capital for SLM adoption.Besides,there is need to sensitize farmers on the complementarities between inorganic fertilizer and SLM practices.Lastly,future studies should assess the effect of sustained SLM adoption or dis-adoption and input intensification on farm productivity.