Switching Model Research Articles

Molecularly Imprinted Polymers for Highly Specific Bioorthogonal Catalysis Inside Cells.

Transition metal catalysts (TMCs) mediated bioorthogonal catalysis expand the chemical possibilities within cells. Developing synthetic TMCs tools that emulate the efficiency and specificity of natural metalloenzymes is a rewarding yet challenging endeavor. Here, we highlight the potential of molecularly imprinted enzyme mimics (MIEs) containing a Cu center and specific substrate binding domain, for conducing dimethylpropargyloxycarbonyl (DmProc) cleavage reactions within cells. Our studies reveal that the Cu-MIEs act as highly specific guides, precisely catalyzing target substrates, even in glutathione (GSH)-rich cellular environments. By adapting templates similar to the target substrates, we evolved Cu-MIEs activity to a high level and provided a method to broaden its scope to other unique substrates. This system was applied to a thyroid hormone (T3)-responsive gene switch model, inducing firefly luciferase expression by T3 in cells. This approach verifies that MIEs effectively rescue DmProc-bearing T3 prodrugs and seamlessly integrating themself into cellular biocatalytic networks.

Evasion Maneuver and Timing Strategy for UAVs Under Direct Force Control

Given the capabilities of modern high-performance missiles, efficient evasion maneuver strategies are crucial for enhancing UAV survivability. This paper addresses the integration of evasion strategies and maneuver timing for targeted UAVs. First, a three-dimensional engagement scenario is modeled using the relative motion mechanism. Subsequently, a fundamental evasion strategy focusing on large roll maneuvers and two-phase acceleration is developed. With the initiation timing of direct force control designated as the control variable, the formulation of a constrained optimization problem to maximize miss distance is fully articulated. While preserving the high fidelity of the established switching model, the feasible timing intervals and the optimal timing are determined through numerical optimization. Finally, simulation experiments are conducted focusing on omnidirectional attacks from the upper hemisphere. The results demonstrate that by implementing specific evasion maneuvers at optimal timing, the target successfully escapes the effective range of the proximity fuse, thus confirming the feasibility of the proposed evasion maneuver and timing strategy.

Theoretical and Numerical Modeling of Optical Switching of Epitaxial Nanostructures Based on Iron-Garnet Films

The paper presents a theoretical analysis of magnetization switching in a gadolinium ferrite garnet film due to the demagnetizing effect of a femtosecond laser pulse. Using the Lagrange formalism for a two-sublattice ferrimagnet, the effective Lagrangian, thermodynamic potential, and Rayleigh dissipative function are obtained. The phase diagram of the ferrite film is analyzed, and the main states of the system are identified. Magnetization switching diagrams and trajectories of the order parameter dynamics of the magnet are constructed. The ranges of magnetic fields, temperatures, and demagnetization values for the most efficient magnetization switching are analyzed.

Small-Signal Stability Analysis and Voltage Control Parameter Design for DC Microgrids

Small-signal instability issues will occur in the DC microgrid when the high-frequency oscillation peaks of the voltage closed-loop transfer function are not effectively suppressed. To ensure the small-signal stability of DC microgrids, the concept of a small-signal stability domain for voltage control parameters is proposed. Based on the voltage closed-loop transfer function, a small-signal-stability-domain-solving algorithm is proposed. With this stability domain, the impact of voltage-proportional coefficient and voltage-integral coefficient on oscillation frequency (or damping factor) is quantitatively analyzed. In addition, the influence of current control parameters on the small-signal stability boundary is also analyzed. With the introduction of this stability domain, a design method for voltage control parameters has been proposed. The voltage control parameters, which are quantitatively designed by this method, are able to maintain the small-signal stability of the system. Finally, based on the RT-BOX hardware-in-the-loop experimental platform, a switching model for a typical DC microgrid is established. Additionally, the effectiveness of the proposed algorithm and designed control parameters is verified by multiple sets of experimental results.

Dynamic output feedback robust MPC hybrid fault-tolerant control for discrete uncertain systems: a switching control strategy

To guarantee the control performance of the discrete system under unmeasurable state and partial actuator failure, a robust dynamic output feedback predictive fault-tolerant control method derived from switching strategy is developed. A new iterative error switching model is established, which both ensures tracking performance and lays the foundation for the development of the next switching controller. Based on this model, output feedback switching fault-tolerant controller is developed. Compared with conventional fault-tolerant control methods, the designed controller can be used under the case of unmeasurable states, and it is more fault tolerant and less conservative. According to the Lyapunov stability theory, the robust stability analysis is carried out under normal and fault conditions, respectively. Then, depending on the findings of the stability analysis, sufficient conditions to guarantee the stability of the closed-loop normal and faulty system are derived. Finally, the suggested method's efficacy is confirmed using the injection moulding process as an example.

Signatures of substorm onset in thermodynamic model of geomagnetic tail

Earlier, an entropy switch model (ESM) for substorm onset as a result of the development of localized inner magnetospheric interchange-ballooning instability, was suggested. Shown observations testify that the substorm onset is accompanied by the reversal and strong fluctuations in key magnetospheric parameters such as total magnetic field strength, plasma pressure, entropy, and some others. Independently, similar behavior was attributed to a thermodynamic theory, where the onset of a substorm is regarded as a consequence of global energy development in the geomagnetic tail. In the latter, the geomagnetic tail is taken as an open thermodynamic system with an infinite number of conserved energy links (CEL) to the external space environment, and the shaping of the substorm profile is ultimately controlled by the system properties of the tail. A comparison between the signatures of substorm onset in the ESM and CEL models is conducted, and correspondence between experimental data and theoretical results is discussed.

Investigation of ferro-resistive switching mechanisms in TiN/Hf0.5Zr0.5O2/WOx/W ferroelectric tunnel junctions with the interface layer effect

This study presents an in-depth analysis of ferro-resistive switching (FRS) behaviors in a TiN/Hf0.5Zr0.5O2(HZO)/WOx/W ferroelectric tunnel junction (FTJ) device, with a particular focus on the role of the tungsten oxide (WOx) interface layer (IL). Structural examinations confirm the presence of the WOx IL, which significantly influences the FRS properties of the device. Electrical measurements indicate the devices exhibit stable and reproducible FRS characteristics with an ON/OFF ratio of 9.7, predominantly attributed to the tunneling electro-resistance (TER) effect driven by the ferroelectric polarization. Comprehensive numerical simulations, incorporating the nucleation-limited switching model and Simmons tunneling mechanism, provide detailed insights into how the WOx IL and the trapped charges at the HZO/WOx interface affect polarization switching mechanisms and the electronic potential barrier profile. These findings underscore the importance of interface effects in HfO2-based FTJs and advance the understanding of the TER mechanism in multilayer ferroelectric systems.

Carbon Taxation and Electricity Price Dynamics: Empirical Evidence from the Australian Market

AbstractIn this paper, we study the change of Australian electricity price dynamics that was observed before, during and after the two-year period in which a Carbon Pricing Mechanism was in force. We fit a two-states Markov Switching Model, representing a high- and a low-volatility state of the world. To avoid the interference due to periodic patterns, a deseasonalization process accounting for short- and long-term seasonality is carried out prior to the study of volatility. Estimation results highlight that, during the period when the carbon tax applies, the volatility level is lower for both the states of the world. Furthermore, the persistence in the low-volatility state is increased in the presence of the carbon tax. This conclusion is particularly relevant for macroeconomic and investment considerations because the increased uncertainty in electricity prices can significantly influence firms’ investment decisions and shape inflation expectations.

Switching costs in transient technology use: Panel evidence from Kenyan maize production

AbstractThe idea of switching costs and how they affect agricultural technology adoption has received little attention in the literature. We employ a dynamic switching model to show that switching costs generally discourage the adoption of new technologies by farmers, but the extent of the effect depends on the level of switching costs, as well as farmer perceptions and foresight. We provide an empirical strategy to identify switching costs and estimate their effects on adoption under different farmers’ perceptions about adoption uncertainty. An application to hybrid seed adoption in Kenya confirms the existence of switching costs. The correlated‐random‐effects probit results suggest there is heterogeneity in dominant farmer types across agro‐ecological zones in Kenya. Area‐specific policies are suggested to promote technology adoption in different environments.

Satellite-derived bathymetry using Sentinel-2 in mesotidal coasts

Coastal zones are strategic environments of high socioeconomic, political, and ecological value, with over half of the world’s population residing within 200 km of the coast. This proximity highlights their vulnerability to extreme events, which are exacerbated by global changes, leading to significant coastal impacts such as erosion, flooding, and ecosystem services deterioration. Consequently, efficient and operational methodologies for continuous monitoring are urgently needed to face these challenges. Bathymetric data are essential for understanding coastal dynamics, yet traditional data collection methods are often constrained by logistical challenges and high costs. Spaceborne remote sensing techniques offer significant advantages over traditional ground-based methods, particularly in terms of cost-effectiveness and operational efficiency. Over the last half-century, different Satellite-derived bathymetry (SDB) methodologies have been developed; however, challenges still persist. In this research, we applied a robust SDB methodology to three different study sites: Cíes Islands, Baiona Bay, and Vao beach within the Ría de Vigo, Galicia (NW Spain). These areas offer diverse and complex mesotidal environments to test for the very first time the methodology's efficacy. SDB was retrieved with a median absolute error (MedAE) ranging from 0.35 m to 1.55 m for depths up to 14 m. Results with different data source were evaluated, obtaining MedAE for nautical charts ranging from 0.46 m to 1.55 m. The precision between the data sources were quite close. In addition, multi-image composite was generated using images coinciding with both low tide (LT) and high tide (HT) conditions across the three zones. The lowest MedAE values were consistently obtained in images classified as LT (0.46 m) corresponding to Vao area. The results highlight the potential of nautical charts as a reliable source of calibration data for SDB, confirm the effectiveness of multi-image and switching models to correct artifacts and turbidity, considering tidal effects, improving single image approaches, and leverage visible bands for precise depth retrieval under varying conditions.

Adaptive Risk Parity Strategies for Managing Portfolio Risk in Volatile Markets

This paper presents a novel model for Adaptive Risk Parity Portfolio Construction, designed to dynamically adjust portfolio weights based on changing market conditions and economic regimes. Traditional portfolio strategies, such as Modern Portfolio Theory (MPT), often rely on static assumptions that can lead to suboptimal performance in volatile markets. In contrast, the adaptive risk parity approach aims to equalize risk contributions across asset classes while responding to fluctuations in economic indicators, such as GDP growth and inflation rates. By employing techniques such as Markov switching models and machine learning for regime identification, the proposed model allows for real-time adjustments to asset allocations. The back-testing results demonstrate that the adaptive risk parity portfolio outperforms static risk parity and traditional mean-variance optimized portfolios in terms of risk-adjusted returns and drawdown management. This research contributes to the field of portfolio management by providing a framework that enhances resilience and adaptability in investment strategies.

Salp Swarm Algorithm-Based Kalman Filter for Seamless Multi-Source Fusion Positioning with Global Positioning System/Inertial Navigation System/Smartphones

With the rapid development of high-precision positioning service applications, there is a growing demand for accurate and seamless positioning services in indoor and outdoor (I/O) scenarios. To address the problem of low localization accuracy in the I/O transition area and the difficulty of achieving fast and accurate I/O switching, a Kalman filter based on the salp swarm algorithm (SSA) for seamless multi-source fusion positioning of global positioning system/inertial navigation system/smartphones (GPS/INS/smartphones) is proposed. First, an Android smartphone was used to collect sensor measurement data, such as light, magnetometer, and satellite signal-to-noise ratios in different environments; then, the change rules of the data were analyzed, and an I/O detection algorithm based on the SSA was used to identify the locations of users. Second, the proposed I/O detection service was used as an automatic switching mechanism, and a seamless indoor–outdoor localization scheme based on improved Kalman filtering with K-L divergence is proposed. The experimental results showed that the SSA-based I/O switching model was able to accurately recognize environmental differences, and the average accuracy of judgment reached 97.04%. The localization method achieved accurate and continuous seamless navigation and improved the average localization accuracy by 53.79% compared with a traditional GPS/INS system.

Forecasts of the mortality risk of COVID-19 using the Markov-switching autoregressive model: a case study of Nigeria (2020–2022)

The global pandemic due to SARS-Cov-2 ravaged the world and killed more than 6 million people globally within two years. Studies predicting future occurrences are essential to effectively combat the virus. This study modeled daily fatality rate in Nigeria from March 23, 2020 to March 19, 2022 and forecast future occurrences using Markov switching model (MSM). MSM estimates segmented fatality rates into three states of low-, medium- and high-risks. Further, estimates revealed that as at 19th March, 2022, Nigeria remained at the low-risk regime in which 1 (95%CI: 0, 1) person, on the average, died of coronavirus daily; however, the most probable scenario in the nearest future was the medium-risk state in which an average of 4 (95%CI: 2, 5) persons would die daily with 48.7% probability. The study concluded that Nigerian COVID mortality risks followed a switching pattern which fluctuated within low-, medium- and high-risks; however, the medium-risk state was most likely in the future. Our results indicated that the quarantine measures adopted by the governments yielded positive results. It also underscored the need for governments and individuals to intensify efforts to ensure that the country remained at the low-risk zone till the virus would be eventually eradicated.

Pricing a Defaultable Zero-Coupon Bond under Imperfect Information and Regime Switching

We propose a pricing formula for a defaultable zero-coupon bond with imperfect information under a regime switching model using a structural form of credit risk modelling. This paper provides explicit representations of risky debt under regime switching with a constant interest rate and risky debt under regime switching with a regime switching interest rate. While the value of the firm’s equity is observed continuously, we assume that the total value of the firm is only observed at discrete times, such as the dates of the release of the firm’s annual reports, or quarterly reports. This uncertainty about the true value of the firm results in credit spreads that do not approach zero as the debt approaches maturity, which is a problem with many structural models. The firm’s value is typically decomposed into its equity and debt; however, we consider the asset–to–equity ratio, an accounting ratio used to examine a firm’s financial well-being. The parameters in our model are regime switching, where the regime can be thought of as the state of the economy. A Markov chain with a constant transition rate matrix produces the regime switching.

Bayesian sparse vector autoregressive switching models with application to human gesture phase segmentation

Bayesian sparse vector autoregressive switching models with application to human gesture phase segmentation

A Modified Algorithm for the L/C-based Switch Model of Power Converters in Real-Time Simulation Based on FPGA

A Modified Algorithm for the L/C-based Switch Model of Power Converters in Real-Time Simulation Based on FPGA

Operator-Based Triboelectric Nanogenerator Power Management and Output Voltage Control.

In this paper, an operator-based voltage control method for TENGs is investigated, achieving output voltage tracking without compensators and uncertainty suppression using robust right coprime factorization. Initially, a comprehensive simulation-capable circuit model for TENGs is developed, integrating their open-circuit voltage and variable capacitance characteristics. This model is implemented to simulate the behavior of TENGs with a rectifier bridge and capacitive load. To address the high-voltage, low-current pulsating nature of TENG outputs, a storage capacitor switching model is designed to effectively transfer the pulsating energy. This switching model is directly connected to a buck converter and operates under a unified control strategy. A complete TENG power management system was established based on this model, incorporating an operator theory-based control strategy. This strategy ensures steady output voltage under varying load conditions without using compensators, thereby reducing disturbances. Simulation results validate the feasibility of the proposed TENG system and the efficacy of the control strategy, providing a robust framework for optimizing TENG energy harvesting and management systems with significant potential for practical applications.

Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching

Phase-field modeling offers a powerful tool for investigating the electrical control of the domain structure in ferroelectrics. However, its broad application is constrained by demanding computational requirements, limiting its utility in inverse design scenarios. Here, we introduce a machine-learning surrogate to accelerate 3D phase-field modeling of tip-induced electrical switching. By dynamically handling the boundary conditions, the surrogate achieves accurate reproduction of switching trajectories under various tip locations and applied voltages. With stable predictions throughout entire morphological evolution pathways and a relative error inferior to 10% compared to direct solvers, the model efficiently emulates intricate switching sequences. By successfully replicating the boundary conditions, the presented framework strides towards a holistic surrogate for the ferroelectric phase field. With up to 2500-fold speed-ups over classical methods, our approach opens the path for the tractable design of the domain structure and the resolution of realistic inverse problems.

Circular RNA circ_0002984 Facilitates the Proliferation and Migration of Ox-LDL-Induced Vascular Smooth Muscle Cells via the Let-7a-5p/KLF5 Pathway.

Circular RNAs (circRNAs) play an important role in the progression of atherosclerosis (AS). This study aimed to explore the exact role and mechanism of circ_0002984 in oxidized low-density lipoprotein (ox-LDL)-mediated human vascular smooth muscle cells (HVSMCs). The model of smooth muscle cell phenotype switching was constructed by treating HVSMCs with ox-LDL. The levels of circ_0002984, let-7a-5p, and kruppel-like factor 5 (KLF5) were measured by quantitative real-time PCR or western blot assay. Cell proliferation, migration, and apoptosis were detected by Cell Counting Kit-8 (CCK-8), EdU staining, wound healing assay, transwell assay, and flow cytometry. The expression of cleaved-caspase-3 and KLF5 was examined by western blot. The relationship between let-7a-5p and circ_0002984 or KLF5 was verified by dual-luciferase reporter assay or RIP assay. The results showed thatcirc_0002984 and KLF5 were up-regulated, while let-7a-5p was down-regulated in AS patients and ox-LDL-disposed HVSMCs. Silence of circ_0002984 suppressed proliferation and migration, and promoted apoptosis in ox-LDL-stimulated HVSMCs. Moreover, circ_0002984 sponged let-7a-5p to regulate the proliferation, migration, and apoptosis in ox-LDL-resulted HVSMCs. In addition, KLF5 was a target of let-7a-5p and its overexpression reversed the effect of let-7a-5p on the proliferation, migration, and apoptosis in ox-LDL-treated HVSMCs. Also, circ_0002984 positively regulated KLF5 expression by absorbing let-7a-5p. The promotion effect of circ_0002984 on the proliferation and migration of ox-LDL-treated HVSMCs was reversed by KLF5 silencing. Taken together,depletion of circ_0002984 inhibited the proliferation and migration of ox-LDL-stimulated HVSMCs, which might be achieved by modulating the let-7a-5p/KLF5 axis.

Dual-layer control strategy based on economic characterization of lifetime state and frequency regulation limit partition of hybrid energy storage

Compared with a single type of energy storage, hybrid energy storage system (HESS) has a better performance in improving the frequency safety of the grid. However, the combination of hybrid energy storage with different resource characteristics and thermal power units will significantly increase the difficulty of coordinated control. In view of the life decay of battery energy storage system (BESS) and the insufficient frequency regulation capability of the system, this paper proposes a dual-layer control strategy based on the economic characterization of hybrid energy storage life state and the frequency regulation limit partition. Real-time state of charge (SOC) is used to establish dynamic equilibrium quotation and energy storage performance characterization as the upper-layer model. Meanwhile, the optimal life evaluation of energy storage is proposed, and the charging and discharging switching model of energy storage is constructed to limit the frequent switching of energy storage and extend its life. The lower-layer model constructs the limit standard of frequency regulation of flywheel energy storage system (FESS), introduces multi-objective constraints, proposes a hybrid energy storage operation scheme suitable for the whole scene, and uses “two rules” as the evaluation index to evaluate the frequency regulation effect of the proposed frequency regulation control model from the regulation rate, accuracy and response time. Finally, taking the actual data of a local thermal power unit as an example, the validity and economy of the frequency regulation effect of the proposed model are verified.