Germination improves the functional properties of soybean and enhances soymilk quality

The effects of soybean variety and germination time on structural changes, antinutritional factor content, antioxidant activity of germinated soybean, and on the functional properties of soymilk were comprehensively investigated. The results showed that the antioxidant activity increased with increasing germination time. The content of antinutritional factors decreased with increasing germination time. Soybean varieties with the lowest tannin and trypsin inhibitor content were DN690 and HJ1. Lipoxygenase activity and phytic acid content showed no significant differences among soybean varieties. The content of α-helices and β-turns in soybean protein decreased with increasing germination time, while the content of β-sheets was increased. Soybean protein was progressively broken down into smaller molecular peptides during the germination process. The digestion and content of soluble protein in soymilk increased with germination. In summary, we show that germination is an effective, cheap, and green method that improves the functional properties of soybean and soymilk.     

Dilated and soft attention-guided convolutional neural network for breast cancer histology images classification

Breast cancer is one of the most common types of cancer in women, and histopathological imaging is considered the gold standard for its diagnosis. However, the great complexity of histopathological images and the considerable workload make this work extremely time-consuming, and the results may be affected by the subjectivity of the pathologist. Therefore, the development of an accurate, automated method for analysis of histopathological images is critical to this field. In this article, we propose a deep learning method guided by the attention mechanism for fast and effective classification of haematoxylin and eosin-stained breast biopsy images. First, this method takes advantage of DenseNet and uses the feature map's information. Second, we introduce dilated convolution to produce a larger receptive field. Finally, spatial attention and channel attention are used to guide the extraction of the most useful visual features. With the use of fivefold cross-validation, the best model obtained an accuracy of 96.47% on the BACH2018 dataset. We also evaluated our method on other datasets, and the experimental results demonstrated that our model has reliable performance. This study indicates that our histopathological image classifier with a soft attention-guided deep learning model for breast cancer shows significantly better results than the latest methods. It has great potential as an effective tool for automatic evaluation of digital histopathological microscopic images for computer-aided diagnosis.     

Preparation,structural and photocatalytic activity of Sn/Fe co-doped TiO2 nanoparticles by sol-gel method

Pure and Sn/Fe co-doped (0.2 at.% Sn and 0.6 at.% Fe, 0.6 at.% Sn and 0.2 at.% Fe, 1.0 at.% Sn and 1.0 at.% Fe) TiO₂ nanoparticles were synthesized via a sol-gel method and subsequently calcined at different temperatures. Furthermore, the particles were analyzed by TG-DSC, XRD, TEM, HRTEM, EDS, SAED and UV–Vis for investigating the influences of dopant and calcination temperature on the thermal effect, composition, morphology, energy band gap (E_g) and the degradation efficiency of methyl orange (MO) under various light irradiations respectively. Results indicated that Sn/Fe co-doping inhibited the crystallization transformation from anatase to rutile phase of TiO₂ and decreased the E_g. The increased calcination temperature and Sn/Fe co-doped effect brought about the abnormal grain growth of TiO₂ nanoparticles. 0.6 at.% Sn/0.2 at.% Fe and 1.0 at.% Sn/1.0 at.% Fe co-doped TiO₂ nanoparticles presented better photocatalytic performance than pure and 0.2 at.% Sn/0.6 at.% Fe co-doped TiO₂ nanoparticles under visible light irradiation mainly due to the decreased E_g. On the contrary, 0.2 at.% Sn and 0.6 at.% Fe co-doped TiO₂ nanoparticles calcined at 650 °C showed the most excellent photocatalytic performance under UV light irradiation, which was about twice as large as that of pure TiO₂ possibly due to the formed hybrid structure of anatase and rutile phase as well as the h⁺-mediated decomposition pathway.     

Fabrication of alumina ceramics with functional gradient structures by digital light processing 3D printing technology

Alumina ceramics with different unit numbers and gradient modes were prepared by digital light processing (DLP) 3D printing technology. The side length of each functional gradient structure was 10 mm, the porosity ratio was controlled to 70%, and the number of units were (1 × 1 × 1 unit) and (2 × 2 × 2 unit) respectively. The different gradient modes were named FCC, GFCC-1, GFCC-2 and GFCC-3. SEM, XRD, and other characterization methods proved that these gradient structures of alumina ceramics had only α-Al2O3 phase and good surface morphology. The mechanical properties and energy absorption properties of alumina ceramics with different functional gradient structures were studied by compression test. The results show that the gradient structure with 1 × 1 × 1 unit has better mechanical properties and energy absorption properties when the number of units is different. When the number of units is the same, GFCC-2 and GFCC-3 gradient structures have better compressive performance and energy absorption potential than FCC structures. The GFCC-2 gradient structure with 1 × 1 × 1 unit has a maximum compressive strength of 19.62 MPa and a maximum energy absorption value of 2.72 × 105 J/m3. The good performance of such functional gradient structures can provide new ideas for the design of lightweight and compressive energy absorption structures in the future.     

角行程阀门电液执行器传动结构的分析

介绍了角行程电液执行器的几种常见传动结构,分析了各种结构的力矩输出特性及与阀门配套的特点。     

Anisotropy Effects in the Shape-Memory Performance of Polymer Foams

Isotropic and anisotropic shape-memory polymer foams are prepared by supercritical carbon dioxide foaming from a multiblock copolymer (PDLCL) consisting of poly(ω-pentadecalactone) and poly(ε-caprolactone) segments. Analysis by micro-computed tomography reveals for the anisotropic PDLCL foam cells a high shape anisotropy ratio of R = 1.72 ± 0.62 with a corresponding Young's compression moduli ratio between longitudinal and transversal direction of 4.3. The experimental compression data in the linear elastic range can be well described by the anisotropic open foam model of Gibson and Ashby. A micro-morphological analysis for single pores using scanning electron microscopy images permits the correlation between the macroscopic stress-compression behavior and microscale structural changes.     

Dense and core-rim structured B4C-TiB2 ceramics with Mo-Co-WC additive

B₄C-TiB₂ ceramics (TiB₂ ranging 5~70 vol%) with Mo-Co-WC as the sintering additive were prepared by spark plasma sintering. In comparison with B₄C-TiB₂ without additive, the enhanced densification was evident in the sintered specimen with Mo-Co-WC additive. Core-rim structured grain was observed around TiB₂ grains. The interface of the rim between TiB₂ and B₄C phases demonstrated different feature: the inner borderline of the rim exhibited a smooth feature, whereas a sharp curved grain boundary was observed between the rim and the B₄C grain. The formation mechanism is discussed: the epitaxial growth of (Ti,Mo,W)B₂ rim around the TiB₂ core may occur as a result of the solid solution and dissolution-precipitation between TiB₂ phase and the sintering additive. It was revealed that the fracture toughness increased as the content of TiB₂ content increased, alongside the decreased hardness. B₄C-30 vol% TiB₂ specimen demonstrated the optimal combination of mechanical properties, reaching Vickers hardness of 24.3 GPa and fracture toughness of 3.33 MPa·m^1/2.     

Influence of Sr ions on the structure and dielectric properties of Cu/Nb Co-doped BaTiO3 ceramics

Sr-modified Cu/Nb co-doped BaTiO₃ ceramics were prepared using solid-state reactions and the structures and dielectric properties were studied. All the samples had single-phase perovskite structures with no detectable secondary phases. In the low-temperature range, the dielectric constant decreased as the Sr content increased in the high- and low-frequency ranges. Two dielectric constant plateaus accompanied by dielectric relaxation peaks were present in the loss curves, and the relaxation process deviated from the Arrhenius law at low temperatures. The dielectric constants of different plateaus were related to inhomogeneous structures such as grain interiors and grain boundaries. The polarization strength of the grain boundaries in the low-frequency range increased with the temperature and that of the grain interiors demonstrated paraelectric behaviour in high-temperature ranges. An analysis of the electric modulus spectra indicated a close relationship between the relaxation process and resistivity of the grains for high-frequency relaxation. The impedance spectra at high temperatures consist of three electrical responses, corresponding to the effects of grains, grain boundaries, and electrodes. The dielectric relaxation appeared in high temperature range was related to the electrical properties of the grain boundaries.     

Effect of lattice structure evolution and stacking fault energy on the properties of Cu–ZrO2/GNP nanocomposites

A hybrid nanocomposite comprising nanosized ZrO₂ and graphene nanoplatelet (GNP)-reinforced Cu matrix was synthesised via powder metallurgy. The influence of sintering temperature and GNP content on the electrical and mechanical behaviour of the Cu–ZrO₂/GNP nanocomposite was investigated. The ZrO₂ concentration was fixed at 10% for all the composites. Upon increasing the GNP concentration up to 0.5%, a significant improvement was observed in the compressive strength, microhardness, and electrical conductivity of the composite. Furthermore, the properties were significantly improved by increasing the sintering temperature from 900 to 1000 °C. The compressive strength, hardness, and electrical conductivity of Cu–10%ZrO₂/0.5%GNP were higher than those of the Cu–ZrO₂ nanocomposite by 60, 21, and 23.8%, respectively. This improvement in the mechanical properties is because of the decrease in the crystallite size and dislocation spacing, which increases the dislocation density, thereby increasing the impedance towards dislocation movement. The lower stacking fault energy of the hybrid nanocomposites enables easier electron transfer within and between the Cu grains, resulting in an improved electrical conductivity. The enhancement in strength and electrical conductivity were aided by the GNPs and ZrO₂ nanoparticles that were dispersed widely in the Cu matrix.