Chemically Ordered Pt–Co–Cu/C as Excellent Electrochemical Catalyst for Oxygen Reduction Reaction

This paper reveals the ordered structure and composition effect to electrochemical catalytic activity towards oxygen reduction reaction (ORR) of ternary metallic Pt–Co–Cu/C catalysts. Bimetallic Pt-Co alloy nanoparticles (NPs) represent an emerging class of electrocatalysts for ORR, but practical applications, e.g. in fuel cells, have been hindered by low catalytic performances owning to crystal phase and atomic composition. Cu is introduced into Pt-Co/C lattices to form PtCoxCu1−x/C (x = 0.25, 0.5 and 0.75) ternary-face-centered tetragonal (fct) ordered ternary metallic NPs. The chemically ordered Pt–Co–Cu/C catalysts exhibit excellent performance of 1.31 A mg−1 Pt in mass activity and 0.59 A cm−2 Pt in specific activity which are significantly higher than Pt-Co/C and commercial Johnson Matthey (JM) Pt/C catalysts, because of the ordered crystal phase and composition control modified the Pt-Pt atoms distance and the surface electronic properties. The presence of Cu improves the surface electronic structure, as well as enhances the stability of catalysts

Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory

Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfully applied to the HRS imagery semantic segmentation task due to their hierarchical representation ability. However, the heavy dependency on a large number of training data with dense annotation and the sensitiveness to the variation of data distribution severely restrict the potential application of DCNNs for the semantic segmentation of HRS imagery. This study proposes a novel unsupervised domain adaptation semantic segmentation network (MemoryAdaptNet) for the semantic segmentation of HRS imagery. MemoryAdaptNet constructs an output space adversarial learning scheme to bridge the domain distribution discrepancy between source domain and target domain and to narrow the influence of domain shift. Specifically, we embed an invariant feature memory module to store invariant domain-level context information because the features obtained from adversarial learning only tend to represent the variant feature of current limited inputs. This module is integrated by a category attention-driven invariant domain-level context aggregation module to current pseudo invariant feature for further augmenting the pixel representations. An entropy-based pseudo label filtering strategy is used to update the memory module with high-confident pseudo invariant feature of current target images. Extensive experiments under three cross-domain tasks indicate that our proposed MemoryAdaptNet is remarkably superior to the state-of-the-art methods.Comment: 17 pages, 12 figures and 8 table

Molecular cloning and preliminary functional analysis of six RING-between-ring (RBR) genes in grass carp (Ctenopharyngodon idellus)

Ubiquitination is a post-translational modification of proteins that is widely present in eukaryotic cells. There is increasing evidence that ubiquitinated proteins play crucial roles in the immune response process. In mammals, RING-between-RING (RBR) proteins play a key role in regulating immune signaling as the important E3 ubiquitin ligases during ubiquitination. However, the function of RBR in fish is still unclear. In the present study, six RBR genes (RNF19A, RNF19B, RNF144AA, RNF144AB, RNF144B and RNF217) of grass carp (Ctenopharyngodon idellus) were cloned and characterized. Similar to mammals, all six members of RBR family contained RING, inbetween-ring (IBR) and transmembrane (TM) domains. These genes were constitutively expressed in all studied tissues, but the relative expression level differed. Following grass carp reovirus(GCRV) infection, the expression of six RBR genes in liver, gill, spleen and intestine significantly altered. Additionally, their expression in Ctenopharyngodon idellus kidney (CIK) cells was significantly increased after GCRV infection. And deficiency of RNF144B in CIK with small interference RNA (siRNA) up-regulated polyinosinic:polycytidylic acid poly(I:C))- induced inflammatory cytokines production, including 1FN-I, TNF-alpha, IL-6, and transcription factor IRF3, which demonstrated that RNF144B was a negative regulator of inflammatory cytokines. Our results suggested that the RBR might play a vital role in regulating immune signaling and laid the foundation for the further mechanism research of RBR in fishes

Biomass-derived carbons for sodium-ion batteries and sodium-ion capacitors

In the past decade, the rapid development of portable electronic devices, electric vehicles, and electrical devices has stimulated extensive interest in fundamental research and the commercialization of electrochemical energy-storage systems. Biomass-derived carbon has garnered significant research attention as an efficient, inexpensive, and eco-friendly active material for energy-storage systems. Therefore, high-performance carbonaceous materials, derived from renewable sources, have been utilized as electrode materials in sodium-ion batteries and sodium-ion capacitors. Herein, the charge-storage mechanism and utilization of biomass-derived carbon for sodium storage in batteries and capacitors are summarized. In particular, the structure–performance relationship of biomass-derived carbon for sodium storage in the form of batteries and capacitors is discussed. Despite the fact that further research is required to optimize the process and application of biomass-derived carbon in energy-storage devices, the current review demonstrates the potential of carbonaceous materials for next-generation sodium-related energy-storage applications.</p

Research on system of ultra-flat carrying robot based on improved PSO algorithm

Ultra-flat carrying robots (UCR) are used to carry soft targets for functional safety road tests of intelligent driving vehicles and should have superior control performance. For the sake of analyzing and upgrading the motion control performance of the ultra-flat carrying robot, this paper develops the mathematical model of its motion control system on the basis of the test data and the system identification method. Aiming at ameliorating the defects of the standard particle swarm optimization (PSO) algorithm, namely, low accuracy, being susceptible to being caught in a local optimum, and slow convergence when dealing with the parameter identification problems of complex systems, this paper proposes a refined PSO algorithm with inertia weight cosine adjustment and introduction of natural selection principle (IWCNS-PSO), and verifies the superiority of the algorithm by test functions. Based on the IWCNS-PSO algorithm, the identification of transfer functions in the motion control system of the ultra-flat carrying robot was completed. In comparison with the identification results of the standard PSO and linear decreasing inertia weight (LDIW)-PSO algorithms, it indicated that the IWCNS-PSO has the optimal performance, with the number of iterations it takes to reach convergence being only 95 and the fitness value being only 0.117. The interactive simulation model was constructed in MATLAB/Simulink, and the critical proportioning method and the IWCNS-PSO algorithm were employed respectively to complete the tuning and optimization of the Proportional-Integral (PI) controller parameters. The results of simulation indicated that the PI parameters optimized by the IWCNS-PSO algorithm reduce the adjustment time to 7.99 s and the overshoot to 13.41% of the system, and the system is significantly improved with regard to the control performance, which basically meets the performance requirements of speed, stability, and accuracy for the control system. In conclusion, the IWCNS-PSO algorithm presented in this paper represents an efficient system identification method, as well as a system optimization method