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.     

Lower down both ohmic and cathode polarization resistances of solid oxide fuel cell via hydrothermal modified gadolinia doped ceria barrier layer

Hydrothermal reaction in Cerium and Gadolinium solution as an optimization method is developed and first reported for the densification of gadolinia doped ceria, the barrier layer between Zirconia electrolyte and (La,Sr)(Co,Fe)O_3-δ cathode. This method is based on the hydrothermal reaction for nano particles in-situly grown on porous surface, to improve barrier layer density, alongside the sintering of cathode at 1075 °C. As a result, the ohmic resistance is prominently decreased by ～16.4 % at 750 °C for electrolyte supported symmetrical cell. Whereas, the cathode polarization resistance is decreased by as much as a factor of ～3 from 0.3702 Ω·cm² to 0.1325 Ω·cm² at 750 °C and $p_{O_2}=0.21atm$. Furthermore, the anode supported cell exhibits higher open circuit voltage, smaller area specific resistance, elevated performance output and less degradation. And this modified barrier layer shows reduced Sr migration in 300 h operation at 750 °C. The hydrothermal reaction is demonstrated to prepare denser and sintering-active barrier layer with faster oxygen ion transfer and better interface connection, with large-scale application prospects and cost-competitiveness.     

Water vapor volatilization and oxidation induced surface cracking of environmental barrier coating systems: A numerical approach

A numerical model is developed for surface crack propagation in brittle ceramic coatings, aiming at the intrinsic failure of rare-earth silicate environmental barrier coating systems (EBCs) under combustion conditions in advanced gas turbines. The main features of progressive degradation of EBCs in such conditions are captured, including selective silica vaporization in the top coat due to exposure to water vapor, diffusion path-dependent bond coat oxidation, as well as crack propagation during cyclic thermal loading. In light of these features, user-defined subroutines are implemented in finite element analysis, where surface crack growth is simulated by node separation. Numerical results are validated by existing experimental data, in terms of monosilicate layer thickening, thermal oxide growth, and fracture behaviors. The experimentally observed quasi-linear oxidation in the early stage is also elucidated. Furthermore, it is suggested that surface crack undergoes rapid propagation in the late stage of extended thermal cycling in water vapor and leads to catastrophic failure, driven by both thermal mismatch and oxide growth stresses. The latter is identified as the dominant mechanism of penetration. Based on detailed analyses of failure mechanisms, the optimization strategy of EBCs composition is proposed, balancing the trade-off between mechanical compliance and erosion resistance.     

High-roubustness keystroke recognition method based on acoustic spatial gradient

For the fluctuation of CFCC caused by environmental noise is the main reason for the low accuracy of keystroke detection,the spatial characteristics of adjacent between CFCC were studied,and the spatial gradient structure of CFCC based on points was established.On this basis,the effect of CFCC spatial gradient on keystroke content recognition and the selection of precise neighborhood points were studied on training and testing.Finally,a high-robustness keystroke recognition algorithm based on acoustic signals was constructed.Extensive experiments in different environments demonstrate that the proposed CFCC spatial gradient sound feature achieves great performance and the recognition accuracy is 96.15%.     

A Dynamic Programming Framework for Large-Scale Online Clustering on Graphs

Neural Processing Letters - As a fundamental technique for data analysis, graph clustering grouping graph data into clusters has attracted great attentions in recent years. In this paper, we...     

阿尔泰金莲花提取物抑制变异链球菌乳酸脱氢酶活性及抗氧化活性研究

采用微量稀释法测定了阿尔泰金莲花提取物对变异链球菌的最小抑菌浓度(MIC)和最小杀菌浓度(MBC),研究了阿尔泰金莲花提取物对变异链球菌的抑制作用,考察了阿尔泰金莲花提取物对变异链球菌产酸及乳酸脱氢酶(LDH)活性的影响,并通过测定阿尔泰金莲花提取物、牡荆素、荭草苷、抗坏血酸(VC)对DPPH自由基、ABTS自由基和·O~-_2的清除率来评价阿尔泰金莲花提取物的抗氧化活性。结果表明,阿尔泰金莲花提取物的MIC为12.5 mg·mL~(-1),MBC为25 mg·mL~(-1);阿尔泰金莲花提取物浓度越大,对变异链球菌的抑制作用就越强;当阿尔泰金莲花提取物浓度在1/8MIC～MIC范围内时,随着阿尔泰金莲花提取物浓度的增大,培养18 h后菌悬液的ΔpH值越小,LDH活性也越低,与空白对照组相比有显著性差异(P0.05);阿尔泰金莲花提取物对DPPH自由基、ABTS自由基和·O~-_2均具有一定的清除作用,且在一定浓度范围内存在量效关系。初步探讨其抑菌作用机制可能是,通过抑制LDH活性从而抑制变异链球菌产酸,影响其代谢及生长。