ALBERT

Description: Tungsten oxide (WO3) is widely used as a functional material for “smart windows” due to its excellent electrochromic properties, however it is difficult to overcome the conflict between its optical modulation and cyclic stability. In this work, WO3 thin films with different crystal structures were prepared by DC reactive magnetron sputtering method. The effects of substrate temperature on the structure, composition, and electrochromic properties of WO3 films were investigated. The results show that the crystallinity of the WO3 film increases with increasing deposition temperature, indicating that temperature plays an important role in controlling the structure of the WO3 film. For WO3 thin films formed at a substrate temperature of 573 K, the film is in an amorphous state to a crystalline transition state. From X-ray diffraction (XRD) analysis, the thin film showed a weak WO3 crystallization peak, which was in the composite structure of amorphous and nanocrystalline. Which has the best electrochromic properties, with modulation amplitude of 73.1% and bleached state with a coloration efficiency of 42.9 cm2/C at a wavelength of 550 nm. Even after 1500 cycles, the optical modulation still contains 65.4%, delivering the best cyclic stability.

Description: Predictive current control (PCC) applied on permanent magnet synchronous motors (PMSMs) has been developed into mainly three methods: the conventional finite-control-set PCC, the double voltage vectors PCC, and deadbeat PCC. However, each approach has its particular calculation way for voltage vectors selection and respective execution duration. This paper, based on the deadbeat idea, presents a unified predictive current control scheme of PMSMs. Under this scheme, the prior three classes are able to be clearly unified into one frame with lower calculation effort. Furthermore, to cope with problem of parameter mismatch in dq-axis current predictive model, a integrated identification method is proposed. Firstly, data selectors are designed to reject abnormal data of sampling signals, and then the interval-varying multi-innovation least squares algorithm is combined with forgetting factor (V-FF-MILS) to approximate the error terms caused by electromagnetic parameters error. The estimated results are online fed to the model of PMSM to enhance its accuracy. Finally, the processor in loop (PIL) simulation results verify that the proposed integrated scheme has advantages in current control of PMSMs with large-scale parameter uncertainty.

Description: This study was conducted to investigate the impacts of dietary energy and protein on rumen bacterial composition and ruminal metabolites. A total of 12 ruminal samples were collected from Shaanbei white cashmere goats which were divided into two groups, including high-energy and high-protein (Group H; crude protein, CP: 9.37% in dry matter; metabolic energy, ME: 9.24 MJ/kg) and control (Group C; CP: 8.73%; ME: 8.60 MJ/kg) groups. Thereby, 16S rRNA gene sequencing and a quantitative polymerase chain reaction were performed to identify the rumen bacterial community. Metabolomics analysis was done to investigate the rumen metabolites and the related metabolic pathways in Groups C and H. The high-energy and high-protein diets increased the relative abundance of phylum Bacteroidetes and genera Prevotella_1 and Succiniclasticum, while decreasing the number of Proteobacteria (p 〈 0.05). The dominant differential metabolites were amino acids, peptides, and analogs. Tyrosine metabolism played an important role among the nine main metabolic pathways. Correlation analysis revealed that both Prevotella_1 (r = 0.608, p 〈 0.05) and Ruminococcus_2 (r = 0.613, p 〈 0.05) showed a positive correlation with catechol. Our findings revealed that the diets with high energy and protein levels in Group H significantly altered the composition of ruminal bacteria and metabolites, which can help to improve the dietary energy and protein use efficiency in goats.

Description: Village committees, as grassroots spontaneously formed by rural collective members in China’s hierarchy system, play an irreplaceable role in the management of rural public affairs. Based on the filed survey dataset taken from three pilot counties/districts in Sichuan province, we explored the significant role that village committees played in farmers’ withdrawal from rural homesteads (WRH). Our empirical results, according to binary logistic regression (BLR) modelling, indicated that the WRH was significantly affected by the triple roles of village committees, among which information intermediary was the most effective followed by the trust builder and then the coordinated manager. Firstly, village committees’ involvement facilitated the WRH by improving policy transparency and decreasing information cost. Secondly, the depth of village committees’ participation (i.e., being involved in multiple phases) positively affected the WRH given its signification of the participation of farmers. Whereas the breadth of participation (i.e., considering various demands of different participants) negatively affected the process of WRH by reducing the decision-making efficiency. Thirdly, farmers’ trust in institutions played a positive role in the WRH, but their confidence in village cadres had limited impact. We therefore argue that promising village committees should act as “all-round stewards” in the decision-making of rural households, which not only includes the transmit of information between those above and those below, but also needs to actively strive for farmers’ trust by letting their voice heard. Based on our empirical findings, this paper finally proposed some policy suggestions, such as strengthening mutual communication, empowerment of rural grassroots, encouraging farmers’ participation and improving formal institutions.

Description: In order to meet the maneuverability requirements of spacesuits for future manned planetary exploration, the concept of an active spacesuit based on the joint-assisted exoskeleton technology is presented. First, by studying the kinematic characteristics of the operator wearing the simulated spacesuit in different gravity environments, we developed a prototype of the upper limb exoskeleton. Then, the resistance moment of the simulated spacesuit was roughly obtained to match the operator’s motion range, being utilized to design the resistance moment model. Considering the unknown resistance moment effects in the active spacesuit and the uncertainties of the exoskeleton’s dynamics model, an adaptive neural network control with fuzzy compensation was developed to drive the upper limb exoskeleton’s tracking desired trajectories. Experimental studies were carried out using an upper limb exoskeleton to illustrate that the proposed method has excellent trajectory tracking performance and good adaptive ability to the gravity environment changes.

Description: With the advent of very-high-resolution remote sensing images, semantic change detection (SCD) based on deep learning has become a research hotspot in recent years. SCD aims to observe the change in the Earth’s land surface and plays a vital role in monitoring the ecological environment, land use and land cover. Existing research mainly focus on single-task semantic change detection; the problem they face is that existing methods are incapable of identifying which change type has occurred in each multi-temporal image. In addition, few methods use the binary change region to help train a deep SCD-based network. Hence, we propose a dual-task semantic change detection network (GCF-SCD-Net) by using the generative change field (GCF) module to locate and segment the change region; what is more, the proposed network is end-to-end trainable. In the meantime, because of the influence of the imbalance label, we propose a separable loss function to alleviate the over-fitting problem. Extensive experiments are conducted in this work to validate the performance of our method. Finally, our work achieves a 69.9% mIoU and 17.9 Sek on the SECOND dataset. Compared with traditional networks, GCF-SCD-Net achieves the best results and promising performances.