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Glycogen synthase kinase-3 (GSK-3), a key role in the pathogenesis of Alzheimer's disease (AD), has been linked with the formation of β-amyloid (Aβ), tubulin-associated unit (tau) protein phosphorylation and apoptosis. Moreover, the excessive presence of elements such as copper (Cu) can promote Aβ aggregation and increase the risk of AD. Combined with the role of GSK-3 and metal elements in AD, a metal-chelating imine GSK-3 inhibitor N-(4-{[(2-amino-5-phenylpyridin-3-ylidene)imino]methyl}pyridin-2-yl)cyclopropanecarboxamide (PIMPC) was designed and synthesized. In our study, Aβ/Cu

Recently, lithium–sulfur batteries have attracted considerable attention due to their high theoretical specific capacity (1673 mA h g−1) and high energy density (2800 W h kg−1), which is regarded as the most promising next-generation energy used for portable electronic devices, vehicles, and energy storage systems. However, there are still some problems that persist for the practical applications of lithium–sulfur batteries; in particular, the problems caused by lithium dendrite growth can seriously hinder the real-world applications and development of lithium–sulfur batteries. In this paper, we summarize the strategies of lithium anode improvement formulated in recent years, and we introduce them in sufficient progressive order on the basis of three aspects: anode surface modification, anode modification, and anode structure design. Nevertheless, the growth of lithium dendrites is still a formidable problem, and we have to continue devoting time and energy toward addressing this issue.

Purpose The purpose of this paper is to verify the feasibility of lunar capture braking through three methods based on particle swarm optimization (PSO) and compare the advantages and disadvantages of the three strategies by analyzing the results of the simulation. Design/methodology/approach The paper proposes three methods to verify capture braking based on PSO. The constraints of the method are the final lunar orbit eccentricity and the height of the final orbit around the Moon. At the same time, fuel consumption is used as a performance indicator. Then, the PSO algorithm is used to optimize the track of the capture process and simulate the entire capture braking process. Findings The three proposed braking strategies under the framework of PSO algorithm are very effective for solving the problem of lunar capture braking. The simulation results show that the orbit in the opposite direction of the trajectory has the most serious attenuation at perilune, and it should consume the least amount of fuel in theoretical analysis. The methods based on the fixed thrust direction braking and thrust uniform rotation braking can better ensure the final perilune control accuracy and fuel consumption. As for practice, the fixed thrust direction braking method is better realized among the three strategies. Research limitations/implications The process of lunar capture is a complicated process, involving effective coordination between multiple subsystems. In this article, the main focus is on the correctness of the algorithm, and a simplified dynamic model is adopted. At the same time, because the capture time is short, the lunar curvature can be omitted. Furthermore, to better compare the pros and cons of different braking modes, some influence factors and perturbative forces are not considered, such as the Earth’s flatness, light pressure and system noise and errors. Practical implications This paper presents three braking strategies that can satisfy all the constraints well and optimize the fuel consumption to make the lunar capture more effective. The results of comparative analysis demonstrate that the three strategies have their own superiority, and the fixed thrust direction braking is beneficial to engineering realization and has certain engineering practicability, which can also provide reference for lunar exploration orbit design. Originality/value The proposed capture braking strategies based on PSO enable effective capture of the lunar module. During the lunar exploration, the capture braking phase determines whether the mission will be successful or not, and it is essential to control fuel consumption on the premise of accuracy. The three methods in this paper can be used to provide a study reference for the optimization of lunar capture braking.

This paper aims to address attitude stabilization control of an underactuated post-capture combination and achieve test validation based on the magnetism–buoyancy hybrid micro-gravity experiment system (MBHMES). Using a precise reduced model, a cascade control law is proposed to solve the issue theoretically. First, an advanced quaternion-based kinematic control law is proposed to stabilize the attitude of the non-symmetric post-capture combination. This control law can overcome the singularity brought about by the small initial attitude under the consideration of uncontrolled angular velocity. Then, considering the existence of multiple disturbances introduced by the fluid flow and electromagnetic force, an effective adaptive dynamic controller is proposed to meet the attitude requirement and reduce the negative effect of the multiple disturbances. For test demonstrations, a scenario of a base body capturing the target with robotics, to achieve attitude stabilization expectation, is described. Simulation results demonstrate the performance of the cascade control laws and test data show the effectiveness of the proposed method.

The problem of propellant-efficient station-keeping using a hybrid sail in the Earth–Moon system is investigated in this paper. To achieve high-precision station-keeping and minimize propellant consumption, the problem is addressed from perspectives of reference orbits design and control strategy design. A high-fidelity model of a hybrid sail, which consists of a solar electric propulsion (SEP) system and a solar sail covered by reflectivity control devices (RCDs), is exploited for reference orbits design in the Earth–Moon system using numerical methods. These hybrid-sail perturbed halo and Lyapunov orbits are parameterized by the sail’s reflectivity and are inherent unstable. An orbit-attitude control strategy is proposed for station-keeping which is composed of three parts: a nonlinear disturbance observer (NDO)-based optimal periodic orbital controller, SEP acceleration optimization, and a NDO-based robust backstepping attitude controller. In particular, RCDs are used in both orbital control and attitude control. Numerical results show that the proposed control strategy can guarantee high-precision station-keeping and effective reduction in propellant consumption.

In this paper, motion planning and coordination is investigated for a space robot composed of a floating pedestal and manipulator. In some cases, such as a manipulator grasping a higher quality target, the dynamic coupling can occur leading to under-actuation of the floating pedestal (that is, the required control force of the pedestal exceeds the thrust limit). As a result, the desired operation may not be achieved due to large control error. Therefore, we propose an innovative planning method, termed dynamic scaling planning method, to avoid pedestal under-actuation and guarantee accuracy of manipulator operations. Furthermore, to validate the proposed method, an experimental model of a space robot operating in a magnetic-liquid hybrid suspension microgravity simulation environment was developed. Results of the experimental simulations demonstrate that the proposed method can effectively avoid under-actuation of the pedestal. Moreover, the end-effector of the manipulator follows a desired path to successfully reach its target location.

With the increasing frequency of space activities, non-cooperative targets such as space debris have brought great hidden dangers to spacecraft operation. How to estimate their state has gradually become the main demand. This paper introduces a new method for estimating the angular velocity value as well as the axis of rotation of non-cooperative targets based on deep neural networks. The proposed algorithm has three parts: (1) use of the convolutional neural network (CNN) YOLO model, which is trained to identify the non-cooperative targets in the images taken by the camera, (2) extracting ORB features in the detected pixel regions of the non-cooperative target and using simultaneous localization and mapping (SLAM) to calculate the rotation matrix and translation matrix of the non-cooperative target relative to the camera, and (3) using the angular velocity value calculated by the Rodrigues equation to estimate the time of loop closure in SLAM. In order to calculate the axis of rotation, the plane fitting and spatial arc fitting are used. Combined with ground test, the experimental results indicate the error of the measured speed value of this algorithm is 0.0081rad/s, and the maximum error of the rotation axis is 5.12° which show the correctness of the algorithm and the potential of online application.

In this work, we demonstrate a “three birds one stone” strategy for preparing 1D N-doped porous carbon nanotubes embedded with core–shell Co@CoOx nanoparticles (Co@CoOx/NCNTs) from bimetallic ZnO@Zn/Co-ZIF nanowires. The ZnO nanowires played three roles: (i) ZnO acted as a template for 1D metal–organic framework (MOF) growth, (ii) in situ evaporation of Zn during pyrolysis prevented the aggregation of the carbon framework and benefited the formation of hierarchical pores, and (iii) the excess oxygen species released from ZnO in situ reacted with metallic cobalt nanoparticles during pyrolysis, leading to the configuration of a Co@CoOx core–shell structure. The as-prepared 1D Co@CoOx/NCNTs exhibited excellent oxygen reduction reaction performance, including a high kinetic current (4.6 times better compared to 20 wt% Pt/C at 0.7 V), a low Tafel slope of 80 mV dec−1, outstanding stability, and strong tolerance to CH3OH crossover. The assembled Zn–air batteries with Co@CoOx/NCNTs yielded high open-circuit voltage (1.52 V), superior stability (over 100 h of operation), and unprecedented rate performance that ranged from 1 to 500 mA cm−2, while existing batteries have never achieved a galvanostatic discharge current density larger than 300 mA cm−2. Such exceptional rate capability was ascribed to the formation of a uniform interconnected nanotube network, facilitated electron transport, and an enlarged electrochemically accessible surface area in the unique 1D porous tubular structure.

A novel strategy for the fabrication of hollow Co and N-codoped carbon nanopolyhedra (H-CoNC) from metal-organic framework (MOF) using in situ evaporation of ZnO nanosphere templates is proposed. The excess Zn supply during the pyrolysis process is found beneficial in terms of high nitrogen (≈9.75 at%), relatively homogenous CoN bonding, and the electrochemically accessible hierarchical porous system. Compared with other reported "solid" CoNC of identical surface areas, the newly developed H-CoNC shows enhanced kinetic current in 0.1 m KOH electrolyte and elevated oxygen reduction reaction (ORR) performance in 6 m KOH. The latter exceeds results obtained with the benchmark 20 wt% Pt/C, which is related to the strong confinement of O2 molecules in the H-CoNC hierarchical porous system. Furthermore, the H-CoNC displays great tolerance toward the methanol crossover and KSCN poisoning. Finally, the assembled Zn-air batteries with H-CoNC yield a record open circuit potential (1.59 V vs Zn, stabilized at 1.52 V), high power density (331.0 mW cm-2 ), and promising rate performance. This work provides a new guideline for the design of MOF-derived carbon materials, as well as novel insights into spatial confinement effect toward the ORR activity.

In network measurement, one-way delay is an important network performance indicators, during the measurement, to synchronize the time of different nodes has a great influence on the results of measurement, especially in the large-scale network measurement. This paper propose a time synchronization stability comparison method based on NTP after research the time synchronization technology. In the one-way delay measurement, in order to eliminate measurement errors caused by the frequency difference between nodes, this paper propose a one-way delay corrective algorithm based on forward and reverse delay measurement after research existing time corrective algorithm. Finally, the measurement platform deployed in Planetlab and measure one-way delay. The measurement select more stable nodes based on NTP stability comparison algorithm, and correct one-way delay measurement results through clock corrective algorithm mentioned above. Experiments show that the results of corrective measurement algorithm are more accurate.