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.     

Fabrication of crescent-shaped ceramic microparticles based on single emulsion microfluidics

Ceramic microparticles have great potentials in various fields such as materials engineering, biotechnology, microelectromechanical systems, etc. Morphology of the microparticle performs an important role on their application. To date, it remains difficult to find an effective and controllable way for fabricating nonspherical ceramic microparticles with 3D features. This work demonstrates a method that combines UV light lithography and single emulsion opaque-droplet-templated microfluidic molding to prepare the crescent-shaped ceramic microparticles. By tailoring the intensity of UV light and flow rate of fluid, the shapes of microparticles are accordingly tuned. Therefore, varieties of crescent-shaped microparticles and their variations have been fabricated. After sintering, the crescent-shaped alumina ceramic microparticles were obtained. Benefitting from the light absorption and scattering behavior of most ceramic nanoparticles, this system can serve as a general platform to produce crescent-shaped microparticles made from different materials, and hold great potentials for applications in microrobotics, structural materials in MEMS, and biotechnology.     

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.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Ratiometric Detection of Glutathione Based on Disulfide Linkage Rupture between a FRET Coumarin Donor and a Rhodamine Acceptor

Abnormal levels of glutathione, a cellular antioxidant, can lead to a variety of diseases. We have constructed a near-infrared ratiometric fluorescent probe to detect glutathione concentrations in biological samples. The probe consists of a coumarin donor, which is connected through a disulfide-tethered linker to a rhodamine acceptor. Under the excitation of the coumarin donor at 405 nm, the probe shows weak visible fluorescence of the coumarin donor at 470 nm and strong near-infrared fluorescence of the rhodamine acceptor at 652 nm due to efficient Forster resonance energy transfer (FRET) from the donor to the acceptor. Glutathione breaks the disulfide bond through reduction, which results in a dramatic increase in coumarin fluorescence and a corresponding decrease in rhodamine fluorescence. The probe possesses excellent cell permeability, biocompatibility, and good ratiometric fluorescence responses to glutathione and cysteine with a self-calibration capability. The probe was utilized to ratiometrically visualize glutathione concentration alterations in HeLa cells and Drosophila melanogaster larvae.     

Effect of MoS2/PTFE coatings on performance of Si3N4/TiC ceramics in dry sliding against WC/Co

To enhance the tribological performance of Si₃N₄/TiC ceramics, MoS₂/PTFE composite coatings were deposited on the ceramic substrate through spraying method. The micrographs and basic properties of the MoS₂/PTFE coated samples were investigated. Dry sliding friction experiments against WC/Co ball were performed with the coated ceramics and traditional ones. These results showed that the composite coatings could significantly reduce the friction coefficient of ceramics, and protect the substrate from adhesion wear. The primary tribological mechanisms of the coated ceramics were abrasive wear, coating spalling and delamination, and the tribological property was transited from slight wear to serious wear with the increase of load because of the lower surface hardness and shear strength. The possible mechanisms for the effects of MoS₂/PTFE composite coatings on the friction performance of ceramics were discussed.     

一种商用车MT变速箱简易推式分离机构设计

为了提升大型载货车、专用车用变速箱分离机构分离性能,满足大离合器盘分离需求,设计出一种分离机构.该机构通过机械原理实现放大输入端推力来满足离合器摩擦片分离.该分离机构结构简单、成本低廉,值得推广.     

The surface carboxyl group of carbonaceous microspheres effects on the synthesis and structure of SiOC ceramics

In this study, C/SiOC and C/SiO₂ composites were prepared by using carbonaceous microspheres with different surface functional groups. Carbonaceous microspheres based on hydrothermal reaction of glucose contains hydroxyl group, while the surface carboxyl group increases after NaOH etching. The hydroxyl group increases the oxygen-enriched structural units of SiOC ceramics, and the C spheres are closely enwrapped in SiOC matrix after pyrolysis at 900 °C. However, the interfacial reaction of surface carboxyl with Si–OH results in the formation of cristobalite SiO₂, and C spheres are not only encased inside the SiOC matrix, but also dispersed outside of SiOC ceramics. After removal of C via calcination at 500 °C for 5 h, C/SiOC and C/SiO₂ composites are transformed into amorphous SiO₂ and cristobalite SiO₂, respectively. The thermogravimetric analysis indicates the oxidation resistance of SiOC is superior to that of C and SiO₂.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.