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Chemical reduction in oxides plays a crucial role in engineering the material properties through structural transformation and electron filling. Controlling the reduction at nanoscale forms a promising pathway to harvest functionalities, which however is of great challenge for conventional methods (e.g., thermal treatment and chemical reaction). Here, we demonstrate a convenient pathway to achieve nanoscale chemical reduction for vanadium dioxide through the electron-beam illumination. The electron beam induces both surface oxygen desorption through radiolytic process and positively charged background through secondary electrons, which contribute cooperatively to facilitate the vacancy migration from the surface toward the sample bulk. Consequently, the VO 2 transforms into a reduced V 2 O 3 phase, which is associated with a distinct insulator to metal transition at room temperature. Furthermore, this process shows an interesting facet-dependence with the pronounced transformation observed for the c-facet VO 2 as compared with the a-facet, which is attributed to the intrinsically different oxygen vacancy formation energy between these facets. Remarkably, we readily achieve a lateral resolution of tens nanometer for the controlled structural transformation with a commercial scanning electron microscope. This work provides a feasible strategy to manipulate the nanoscale chemical reduction in complex oxides for exploiting functionalities. The authors demonstrate a nanoscale chemical reduction for VO 2 into V 2 O 3 through electron-beam illumination, showcasing potential for nanoscale manipulation of oxygen ionic evolution for advanced harvesting functionalities.

The paper proposes four improved proportional topology optimization (IPTO) algorithms which are called IPTO_A, IPTO_B, IPTO_C, and IPTO_D, respectively. The purposes of this work are to solve the minimum compliance optimization problem, avoid the problems of numerical derivation and sensitivity calculation involved in the process of obtaining sensitivity information, and overcome the deficiencies in the original proportional topology optimization (PTO) algorithm. Inspired by the PTO algorithm and ant colony algorithm, combining the advantages of the filtering techniques, the new algorithms are designed by using the compliance proportion filter and the new density variable increment update scheme and modifying the update way of the density variable in the inner and main loops. To verify the effectiveness of the new algorithms, the minimum compliance optimization problem for the MBB beam is introduced and used here. The results show that the new algorithms (IPTO_A, IPTO_B, IPTO_C, and IPTO_D) have some advantages in terms of certain performance aspects and that IPTO_A is the best among the new algorithms in terms of overall performance. Furthermore, compared with PTO and Top88, IPTO_A has some advantages such as improving the objective value and the convergence speed, obtaining the optimized structure without redundancy, and suppressing gray-scale elements. Besides, IPTO_A also possesses the advantage of strong robustness over PTO.

In a satellite navigation system, high-precision prediction of satellite clock bias directly determines the accuracy of navigation, positioning, and time synchronization and is the key to realizing autonomous navigation. To further improve satellite clock bias prediction accuracy, we establish a satellite clock bias prediction model by using long short-term memory (LSTM) that can accurately express the nonlinear characteristics of the navigation satellite clock bias. Outliers in the original clock bias should be preprocessed before using the clock bias for prediction. By analyzing the working principle of the traditional median absolute deviations method, the ambiguity of the mathematical model of that method was improved. Experimental results show that the improved method is better than the traditional method at detecting gross errors. The single difference sequence of the preprocessed satellite clock bias was taken as the research object. First, a quadratic polynomial model was fit to the trend term of the single difference sequence. Second, based on the LSTM neural network model and the basic principles of supervised learning, a supervised learning LSTM network model (SL-LSTM) was proposed that models cyclic and random terms. Finally, the prediction function of the satellite clock bias was realized by extrapolating the model by adding a trend term. We adopt the GPS precision satellite clock bias of International GNSS Service data forecast experiments and apply wavelet neural network (WNN), autoregressive integrated moving average (ARIMA), and quadratic polynomial (QP) models to compare their prediction effects. The average prediction RMSE for 3 h, 6 h, 12 h, 1 d, and 3 d based on the SL-LSTM improved by approximately −21.80, −1.85, 8.57, 2.27, and 40.79%, respectively, compared with the results of the WNN. The average prediction RMSE based on the SL-LSTM improved by approximately 38.23, 65.48, 80.22, 85.18, and 94.51% compared with the ARIMA results. The average prediction RMSE based on the SL-LSTM improved by approximately 82.37, 75.88, 67.24, 45.71, and 58.22% compared with the QP results. Compared with the WNN, the SL-LSTM method has no obvious advantages in the prediction accuracy and stability in short-term prediction but achieves a better long-term prediction accuracy and stability. With an increased prediction duration, the SL-LSTM method is clearly better than the other three methods in terms of the prediction accuracy and stability. The results indicated that the quality of satellite clock bias prediction by the SL-LSTM method is better than that of the above three methods and is more suitable for the middle- and long-term prediction of satellite clock bias.

There are some drawbacks such as the propagation and spread of bacteria and viruses during the use of normal paper. Therefore, this work designed a starch styrene-acrylic antibacterial emulsion for improving the paper properties. The modified antimicrobial monomer was prepared by the subject-object recognition of β-cyclodextrin with hydrophobic modified titanium dioxide. The antibacterial performance of prepared emulsion was tested by Escherichia coli, Staphylococcus aureus. And the mechanical properties of the modified paper were measured according to the national standards. The results showed that the antibacterial emulsion has excellent comprehensive performance with the viscosity of 1750 mPa·s, the inhibition ring diameter of 11.82 mm, the good chemical stability and storage stability. Therefore, the proposed cationic starch styrene-acrylic antibacterial emulsion has promising applications in paper surface modification.

How circuit wiring is specified is a key question in developmental neurobiology. Previously, using the Drosophila motor system as a model, we found the classic temporal transcription factor Hunchback acts in NB7-1 neuronal stem cells to control the number of NB7-1 neuronal progeny form functional synapses on dorsal muscles (Meng et al., 2019). However, it is unknown to what extent control of motor neuron-to-muscle synaptic partnerships is a general feature of temporal transcription factors. Here, we perform additional temporal transcription factor manipulations—prolonging expression of Hunchback in NB3-1, as well as precociously expressing Pdm and Castor in NB7-1. We use confocal microscopy, calcium imaging, and electrophysiology to show that in every manipulation there are permanent alterations in neuromuscular synaptic partnerships. Our data show temporal transcription factors, as a group of molecules, are potent determinants of synaptic partner choice and therefore ultimately control circuit membership.

With the development trend of large-scale and flexible structures in engineering, the research on drag reduction of structures becomes more urgent. This paper presents a drag reduction design method for box girders based on the bionic method. Through the analysis of the Ostracion cubicus body shape, three features of the “fish mouth”, which were helpful for drag reduction were extracted. Then the bionic design model with the height of the box girder (D) as the design variable was obtained. By attaching lightweight materials to the windward side, the bionic shape of the structure can be realized without changing the loading characteristics of the original structure. Taking a box girder (rectangular cylinder, side ratio B/D = 0.6) as a prototype, the flow around two structures (rectangular cylinder and bionic attachment cylinder) was numerically simulated. The results show that the drag coefficient of the bionic attachment structure is reduced by 66.5%. The reduction of wind-load means that this method can save energy consumption of the equipment. Meanwhile, the aerodynamic parameter oscillation of the structure is weakened, which represents that the bionic attachment structure can effectively reduce the wind-induced vibration on the structure and improve the stability of the structure in the wind field.

Neuronal cell death and subsequent brain dysfunction are hallmarks of aging and neurodegeneration, but how the nearby healthy neurons (bystanders) respond to the death of their neighbors is not fully understood. In the Drosophila larval neuromuscular system, bystander motor neurons can structurally and functionally compensate for the loss of their neighbors by increasing their terminal bouton number and activity. We term this compensation as cross-neuron plasticity, and in this study, we demonstrate that the Drosophila engulfment receptor, Draper, and the associated kinase, Shark, are required for cross-neuron plasticity. Overexpression of the Draper-I isoform boosts cross-neuron plasticity, implying that the strength of plasticity correlates with Draper signaling. In addition, we find that functional cross-neuron plasticity can be induced at different developmental stages. Our work uncovers a role for Draper signaling in cross-neuron plasticity and provides insights into how healthy bystander neurons respond to the loss of their neighboring neurons. Neuronal death is a feature of development and neurodegeneration. Here, the authors report that ablation of Drosophila motor neurons triggers Draper-dependent signaling in glia to engage ‘cross-neuron plasticity’ in bystander neurons.

The paths axons travel to reach their targets and the subsequent synaptic connections they form are highly stereotyped. How cell surface proteins (CSPs) mediate these processes is not completely understood. The Drosophila neuromuscular junction (NMJ) is an ideal system to study how pathfinding and target specificity are accomplished, as the axon trajectories and innervation patterns are known and easily visualized. Dpr10 is a CSP required for synaptic partner choice in the neuromuscular and visual circuits and for axon pathfinding in olfactory neuron organization. In this study, we show that Dpr10 is also required for motor axon pathfinding. To uncover how Dpr10 mediates this process, we used immunoprecipitation followed by mass spectrometry to identify Dpr10 associated proteins. One of these, Nocte, is an unstructured, intracellular protein implicated in circadian rhythm entrainment. We mapped nocte expression in larvae and found it widely expressed in neurons, muscles, and glia. Cell-specific knockdown suggests nocte is required presynaptically to mediate motor axon pathfinding. Additionally, we found that nocte and dpr10 genetically interact to control NMJ assembly, suggesting that they function in the same molecular pathway. Overall, these data reveal novel roles for Dpr10 and its newly identified interactor, Nocte, in motor axon pathfinding and provide insight into how CSPs regulate circuit assembly.

Temperature stability is a critical factor affecting the performance of the most subsystems in the lithography system, due to the high precision and sensitivity of system components to temperature variations. The temperature control system of the lithography machine is characterized by its large inertial constant, time delay characteristics, as well as susceptibility to multiple disturbances. The temperature control system of the lithography machine chiefly requires response speed, high accuracy, and stable and constant temperature control. The contribution of this study is not only avoiding complex precision modeling processes based on real-time parameter estimation and neural network self-tuning but also improving the performance of temperature control in real time under external disturbances. A novel adaptive algorithm with a cascade structure based on generalized predictive control (GPC) and backpropagation (BP) neural network proportional-integral (PI) control is successfully proposed for high accuracy temperature control of lithography machine with a large inertial constant, time delay, and multiple disturbances. In this study, firstly, the liquid circulating temperature control system is developed based on heat exchanger and heater. Secondly, an adaptive controller composed of GPC and BP neural network PI control is successfully proposed. A BP neural network is employed to enable the parameters of the PI controller to adjust in real time, and the mathematical model parameters of the control system are identified in real time by the least square method. Also, the performance of the proposed controller is evaluated comparing with conventional PI controller and GPC controller in terms of robustness and quantitative study of error analysis. Finally, the temperature stability and robustness of the temperature control system controlled with the proposed adaptive GPC-PI algorithm has been investigated by the simulation results carried out in different working scenarios. The simulation results show that the steady-state error from the proposed algorithm is less than 0.01°C under the action of disturbance input. It can effectively counteract the influence of environmental interference and time-varying system parameters. The results of the simulation experiment indicate that the proposed adaptive GPC and PI control algorithm exhibits significant advantages in terms of control accuracy, anti-interference ability, and robustness compared to the conventional control method.