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Fast steering mirrors (FSMs), actuated by piezoelectric ceramics, play pivotal roles in satellite laser communication, distinguished by their high bandwidth and fast responsiveness, thereby facilitating the precise pointing and robust tracking of laser beams. However, the dynamic performance of FSMs is notably impaired by the hysteresis nonlinearity inherent in piezoelectric ceramics. Under dynamic conditions, rate-dependent hysteresis models and Hammerstein models are predominantly employed to characterize hysteresis nonlinearity. By combining the advantages of these two models, a hysteresis model termed modified Hammerstein-like (MHL) model is proposed. This model integrates an input time delay, a rate-dependent hysteresis term, and a linear dynamic term in a cascaded structure, effectively capturing the dynamic characteristics of hysteresis systems across a broad frequency range. Additionally, a composite control strategy is tailored for the MHL model which consists of a feedforward compensator based on a rate-dependent hysteresis inverse model and a proportional–integral (PI) controller for closed-loop regulation. Experimental results demonstrate the effectiveness of the proposed modeling and composite control methods.

Fast steering mirrors (FSMs), driven by piezoelectric ceramics, are usually used as actuators for high-precision beam control. A FSM generally contains four ceramics that are distributed in a crisscross pattern. The cooperative movement of the two ceramics along one radial direction generates the deflection of the FSM in the same orientation. Unlike the hysteresis nonlinearity of a single piezoelectric ceramic, which is symmetric or asymmetric, the FSM exhibits complex hysteresis characteristics. In this paper, a systematic way of modeling the hysteresis nonlinearity of FSMs is proposed using a Madelung’s rules based symmetric hysteresis operator with a cascaded neural network. The hysteresis operator provides a basic hysteresis motion for the FSM. The neural network modifies the basic hysteresis motion to accurately describe the hysteresis nonlinearity of FSMs. The wiping-out and congruency properties of the proposed method are also analyzed. Moreover, the inverse hysteresis model is constructed to reduce the hysteresis nonlinearity of FSMs. The effectiveness of the presented model is validated by experimental results.

Low-temperature (including room-temperature) gas sensors are crucial for energy-efficient and safe detection applications. In this study, we report the synthesis of In2O3-sensitized NiO nanoparticles (NPs) for NO2 detection. The NiO/In2O3 hybrid materials were obtained by pyrolysis of Ni/In bimetallic metal–organic framework (MOF) nanosheets (NSs) fabricated through ultrasonic synthesis and cation exchange. Gas sensing tests revealed that the In2O3 sensitization significantly enhances the NO2 sensing performance of NiO, enabling a response of 1.5 at room temperature (RT) and an optimal response at 100 °C. The NiO/In2O3 sensor demonstrates enhanced selectivity toward NO2, an ultra-low detection limit (41 ppb), and long-term stability. This study presents an effective MOF-derived route for developing high-performance low-power gas sensors.

The configuration of adjustable capacity transformers will be affected by photovoltaic (PV) penetration. In this paper, we propose a method for optimizing the configuration of adjustable capacity transformers by analyzing the parameters and topology of the low-voltage distribution network, which considers both the operational safety of the grid and economic objectives under optimal power flow (OPF) distribution. We construct the objectives and constraints of the OPF-solving model in different PV penetration scenarios for two types of node topologies and utilize second-order cone (SOC) relaxation to solve the results of OPF distribution. In order to calculate the long-term power loss and comprehensively assess the transformer replacement cost, we analyze the low-voltage side load curves of the adjustable capacity transformers based on the OPF solutions. We design an optimization scheme for the capacity configuration of transformers under different PV penetration rates. Simulation results show that the proposed scheme can effectively reduce power loss and transformer operating costs.

Photocatalytic hydrogen production could sustainably and efficiently convert solar energy. However, a low light utilization ratio limits the wide application. Herein, a Moiré-like structure was constructed in the TiO2 body to improve the light absorption by multiple reflections and suitable light dispersion and diffraction based on similar wavelength and nick. Furthermore, the Moiré-like structure slightly reduces the band gap and accelerates the separation of the photogenerated electrons and holes, and the mass transfer was enhanced by the regular nano-channels and Bernoulli phenomenon. After calcination at 500 °C (M-T500), compared with pure TiO2, M-T500 achieved a 20% increase in RhB degradation efficiency and a double increase in hydrogen production rate, thus providing a novel design for catalysts and a high catalytic strategy. Moreover, the nearly 100% recovery rate supported environmental protection and sustainable development.

Active power outputs of a wind farm connected to a weak power grid greatly affect the stability of grid-connected voltage source converter (VSC) systems. This paper studies the impact of active power outputs and control parameters on the subsynchronous oscillation characteristics of full-converter wind farms connected weak power grids. Eigenvalue and participation factor analysis was performed to identify the dominant oscillation modes of the system under consideration. The impact of active power output and control parameters on the damping characteristics of subsynchronous oscillation is analysed with the eigenvalue method. The analysis shows that when the phase-locked loop (PLL) proportional gain is high, the subsynchronous oscillation damping characteristics are worsened as the active power output increases. On the contrary, when the PLL proportional gain is small, the subsynchronous oscillation damping characteristics are improved as the active power output increases. By adjusting the control parameters in the PLL and DC link voltage controllers, system stability can be improved. Time-domain results verify the analysis and the findings.

Low-temperature (including room-temperature) gas sensors are crucial for energy-efficient and safe detection applications. In this study, we report the synthesis of In[sub.2]O[sub.3]-sensitized NiO nanoparticles (NPs) for NO[sub.2] detection. The NiO/In[sub.2]O[sub.3] hybrid materials were obtained by pyrolysis of Ni/In bimetallic metal–organic framework (MOF) nanosheets (NSs) fabricated through ultrasonic synthesis and cation exchange. Gas sensing tests revealed that the In[sub.2]O[sub.3] sensitization significantly enhances the NO[sub.2] sensing performance of NiO, enabling a response of 1.5 at room temperature (RT) and an optimal response at 100 °C. The NiO/In[sub.2]O[sub.3] sensor demonstrates enhanced selectivity toward NO[sub.2], an ultra-low detection limit (41 ppb), and long-term stability. This study presents an effective MOF-derived route for developing high-performance low-power gas sensors.

Photocatalytic hydrogen production could sustainably and efficiently convert solar energy. However, a low light utilization ratio limits the wide application. Herein, a Moiré-like structure was constructed in the TiO[sub.2] body to improve the light absorption by multiple reflections and suitable light dispersion and diffraction based on similar wavelength and nick. Furthermore, the Moiré-like structure slightly reduces the band gap and accelerates the separation of the photogenerated electrons and holes, and the mass transfer was enhanced by the regular nano-channels and Bernoulli phenomenon. After calcination at 500 °C (M-T500), compared with pure TiO[sub.2], M-T500 achieved a 20% increase in RhB degradation efficiency and a double increase in hydrogen production rate, thus providing a novel design for catalysts and a high catalytic strategy. Moreover, the nearly 100% recovery rate supported environmental protection and sustainable development.

Here we report a human intellectual disability disease locus on chromosome 14q31.3 corresponding to mutation of the ZC3H14 gene that encodes a conserved polyadenosine RNA binding protein. We identify ZC3H14 mRNA transcripts in the human central nervous system, and we find that rodent ZC3H14 protein is expressed in hippocampal neurons and colocalizes with poly(A) RNA in neuronal cell bodies. A Drosophila melanogaster model of this disease created by mutation of the gene encoding the ZC3H14 ortholog dNab2, which also binds polyadenosine RNA, reveals that dNab2 is essential for development and required in neurons for normal locomotion and flight. Biochemical and genetic data indicate that dNab2 restricts bulk poly(A) tail length in vivo, suggesting that this function may underlie its role in development and disease. These studies reveal a conserved requirement for ZC3H14/dNab2 in the metazoan nervous system and identify a poly(A) RNA binding protein associated with a human brain disorder.

Two types of tailored activated carbons (BC-41-OG and BC-41-MnN) with favorable physicochemical characteristics were employed as adsorbents to study effects of synthetic small organic molecular (phenolics) on fulvic acid (FA) removal. The adsorption of FA on activated carbon was greatly declined due to competitive adsorption as a result of oxidation coupling of phenolics. However, the physicochemical characteristics of novel activated carbons (surface metal oxides and mesoporosity) can play an important role in alleviating this effect. The adsorption of FA onto F400 fluctuated a lot due to a relatively lower mesoporosity and surface basicity. Kinetic study was also conducted to determine the effects of oxidative coupling on adsorption kinetics of FA. The results demonstrated that presence of phenolics caused more significant effect on FA adsorption kinetics as compared to humic acid (HA).