Improving gelling properties of myofibrillar proteins incorporating with cellulose micro/nanofibres

The effects of cellulose microfibres (CMFs, Average size: 100 ± 5 μm) and cellulose nanofibres (CNFs, Average size: 60 ± 3 nm) on the properties of myofibrillar protein (MP) gels from duck breast meat were studied. The results demonstrated that CMFs and CNFs were mostly connected to MP by non-covalent bonds, the diffusion and cross-linking of MP molecules was promoted, and a denser and more complete gel network was formed. With the increases of CMFs and CNFs concentration (0–10%), the hardness was increased by 13.15% and 19.78% for CMFs10% and CNFs10% gels, respectively, and the elasticity was increased by 40% and 80%, respectively. At the same concentration (0–10%), the increase in gel hardness, viscoelasticity and immobilised water content was greater in the CNFs-MP group than in the CMFs-MP group. The CNFs-MP group had a tighter gel network, and CNFs had a better potential to improve the gelation performance of MP.     

Ensemble relation network with multi-level measure

Fine-grained few-shot learning is a difficult task in image classification. The reason is that the discriminative features of fine-grained images are often located in local areas of the image, while most of the existing few-shotlearning image classification methods only use top-level features and adopt a single measure. In that way, the localfeatures of the sample cannot be learned well. In response to this problem, ensemble relation network with multi-level measure (ERN-MM) is proposed in this paper. It adds the relation modules in the shallow feature space tocompare the similarity between the samples in the local features, and finally integrates the similarity scores from thefeature spaces to assign the label of the query samples. So the proposed method ERN-MM can use local details andglobal information of different grains. Experimental results on different fine-grained datasets show that the proposedmethod achieves good classification performance and also proves its rationality.     

Fabrication and joining mechanism of Nano-Cu/Si3N4 ceramic substrates

A novel method for fabricating a nano-Cu/Si₃N₄ ceramic substrate is proposed. The nano-Cu/Si₃N₄ ceramic substrate is first fabricated using spark plasma sintering (SPS) with the addition of nanoscale multilayer films (Ti/TiN/Ti/TiN/Ti) as transition layers. The microstructures of the nano-Cu metal layer and the interface between Cu and Si₃N₄ are investigated. The results show that a higher SPS temperature increases the grain size of the nano-Cu metal layer and affects the hardness. The microstructure of the transition layer evolves significantly after SPS. Ti in the transition layer can react with Si₃N₄ and with nano-Cu to form interfacial reaction layers of TiN and Ti–Cu, respectively; these ensure stronger bonding between nano-Cu and Si₃N₄. Higher SPS temperatures improve the diffusion ability of Ti and Cu, inducing the formation of Ti₃Cu₃O compounds in the nano-Cu metal layer and Ti₂Cu in the transition layer. This study provides an important strategy for designing and constructing a new type of ceramic substrate.     

SDN中基于KMOBPSO的高可靠性控制器部署算法

针对SDN中控制器系统的单节点故障问题,兼顾系统成本和系统时延,应用N+1冗余备份模型来提高SDN控制器部署的可靠性,并将其抽象为多目标优化问题.同时,提出了一种融合K-means聚类算法和遗传算子的多目标二进制粒子群算法——KMOBPSO算法,以求解SDN控制器高可靠性部署问题的解.仿真结果表明,所提算法具有求解精度高、分布均匀、沿Pareto前沿面覆盖广的特点,能够显著提高SDN中控制器部署的可靠性.     

Combating Biofilm Associated Infection In Vivo: Integration of Quorum Sensing Inhibition and Photodynamic Treatment based on Multidrug Delivered Hollow Carbon Nitride Sphere

Recently, quorum sensing (QS) inhibitors (QSIs) have been combined with antibiotics to enhance antibiofilm efficacy in vitro and in vivo. However, targeting QS signals alone is not enough to prevent bacterial infections. Drug resistance and recurrence of biofilms makes it difficult to eradicate. Herein, photodynamic therapy (PDT) is selected to unite QSIs and antibiotics. A synergistically antibiofilm system, which combines QSIs, antibiotics, and PDT based on hollow carbon nitride spheres (HCNSs) is envisaged. First, HCNS provides the multidrug delivering ability, enabling QSIs and antibiotics to be released in sequence. Subsequently, multistage releases sensitize bacteria effectively, potentiating the chemotherapeutic effects of the antibiotics. Finally, the integration of QSIs and PDT not only minimizes the possibility of drug resistance, but also overcomes the problem of limited mass and extension of PDT. Even after 48 h of incubation, the bacterial biofilm is obviously inhibited. And its biofilm disperse efficiency exceeds 48% (compared with QSI‐potentiated chemotherapy group) and 40% (compared with PDT group). Besides, the inhibition of the QS system influences phenotypes related to virulence factor production and surface hydrophobicity, which weaken biofilm invasion and formation. Eventually, this system is applied to disperse bacterial biofilm in vivo. Overall, PDT and QS modulation are devoted to eradicate drug resistance and recurrence of the biofilm.     

基于粒子群优化和支持向量机的花粉浓度预测模型

为了提高花粉浓度预报的准确率，解决现有花粉浓度预报准确率不高的问题，提出了一种基于粒子群优化（PSO）算法和支持向量机（SVM）的花粉浓度预报模型。首先，综合考虑气温、气温日较差、相对湿度、降水量、风力、日照时数等多种气象要素，选择与花粉浓度相关性较强的气象要素构成特征向量；其次，利用特征向量与花粉浓度数据建立SVM预测模型，并使用PSO算法找出最优参数；然后利用最优参数优化花粉浓度预测模型；最后，使用优化后的模型对花粉未来24 h浓度进行预测，并与未优化的SVM、多元线性回归法（MLR）、反向神经网络（BPNN）作对比。此外使用优化后的模型对某市南郊观象台和密云两个站点进行逐日花粉浓度预测。实验结果表明，相比其他预报方法，所提方法能有效提高花粉浓度未来24 h预测精度，并具有较高的泛化能力。     

High-rate capability of carbon-coated micron-sized hexagonal TT-Nb2O5 composites for lithium-ion battery

With excellent specific capacity, superior cycle stability, safety and strong practical, Nb₂O₅ has been considered as one of the prospective anode materials for lithium-ion batteries (LIBs). However, current study suggests that Nb₂O₅ electrode materials for LIBs still face the vital issues of low electrical conductivity and poor rate performance. Therefore, carbon-coated TT-Nb₂O₅ materials are designed and synthesized through solid state method in this work, which present high specific capacity (228 mA h g^?1 at 0.2C), satisfactory rate properties (107 mA h g^?1 at 20 C). The outstanding electrochemical property can not only give the credit to the pseudocapacitance effect of TT-Nb₂O₅, but also attribute to introduction of carbon. The homogeneous carbon-coated materials enhance the electrical conductivity, increase the electron transmission speed and alleviate particle crushing. This research not only offers a new method for preparing excellent electrode materials, but also provides a kind of excellent anode material with prospective application for LIBs.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.