金针菇多糖对微冻大黄鱼及其鱼片品质变化的影响

为研究金针菇多糖（polysaccharide from Flammulina velutipes，FVP）对微冻大黄鱼及鱼片在贮藏期间肌原纤维蛋白性质的变化及水分分布的影响，实验分别选用0.03、0.06、0.09 g/L FVP浸渍处理大黄鱼和鱼片，以无菌水处理为对照组，分析微冻贮藏期间样品的感官指标得分、总挥发性盐基氮含量、总巯基含量、Ca2＋-ATPase活性、蛋白流变学性质以及水分迁移变化规律。结果表明：FVP可有效抑制整鱼总挥发性盐基氮含量上升和感官得分的下降；减缓整鱼及鱼片在微冻过程中总巯基含量、Ca2＋-ATPase活性下降和水分流失；此外FVP还能够延缓大黄鱼因腐败而出现的蛋白凝胶能力减弱。在本实验选取的多糖浓度范围内，0.09 g/L FVP处理组保鲜效果较强。该研究结果可为FVP用于水产品贮运保鲜提供理论参考。     

Techno-economical evaluations of decarbonized hydrogen production based on direct biogas conversion using thermo-chemical looping cycles

Hydrogen production by biogas conversion represent a promising solution for reduction of fossil CO₂ emissions. In this work, a detailed techno-economic analysis was performed for decarbonized hydrogen production based on biogas conversion using calcium and chemical looping cycles. All evaluated concepts generate 100,000 Nm³/h high purity hydrogen. As reference cases, the biogas steam reforming design without decarbonization and with CO₂ capture by gas-liquid chemical absorption were also considered. The results show that iron-based chemical looping design has higher energy efficiency compared with the gas-liquid absorption case by 2.3 net percentage points as well as a superior carbon capture rate (99% vs. 65%). The calcium looping case shows a lower efficiency than chemical scrubbing, with about 2.5 net percentage points, but the carbon capture rate is higher (95% vs. 65%). The hydrogen production cost increases with decarbonization, the calcium looping shows the most favourable situation (37.14 €/MWh) compared to the non-capture steam reforming case (33 €/MWh) and MDEA and iron looping cases (about 42 €/MWh). The calcium looping case has the lowest CO₂ avoidance cost (10 €/t) followed by iron looping (20 €/t) and MDEA (31 €/t) cases.     

Effects of feed composition,protein denaturation and storage of milk serum protein/lactose powders on lactosylation

During whey powder production, the feed is subjected to several heat treatments which can cause lactosylation of proteins. In this study, lactosylation of whey proteins was evaluated in spray-dried powders before and after storage by varying the native protein fraction as well as the serum protein/lactose ratio in the powders. The lactosylation of native α-lactalbumin and β-lactoglobulin in the powders before storage was not affected to a large extent by the protein denaturation or if the feed had been heat treated in a high or low lactose environment. After storage (relative humidity of 23.5%, 30 °C, 25 days), the kinetic of lactosylation tended to increase with increasing native protein fraction and bulk protein content in the powders. An explanation could be that proteins dissolved in the lactose glassy structure might have a lower reactivity, while proteins present in the protein glassy structure with dissolved lactose may display higher lactosylation reactivity.     

High energy storage properties of lead-free Mn-doped (1-x)AgNbO3-xBi0.5Na0.5TiO3 antiferroelectric ceramics

In this work, 0.2 wt.% Mn-doped (1-x)AgNbO₃-xBi_0.5Na_0.5TiO₃ (x = 0.00–0.04) ceramics were synthesized via solid state reaction method in flowing oxygen. The evolution of microstructure, phase transition and energy storage properties were investigated to evaluate the potential as high energy storage capacitors. Relaxor ferroelectric Bi_0.5Na_0.5TiO₃ was introduced to stabilize the antiferroelectric state through modulating the M₁-M₂ phase transition. Enhanced energy storage performance was achieved for the 3 mol% Bi_0.5Na_0.5TiO₃ doped AgNbO₃ ceramic with high recoverable energy density of 3.4 J/cm³ and energy efficiency of 62% under an applied field of 220 kV/cm. The improved energy storage performance can be attributed to the stabilized antiferroelectricity and decreased electrical hysteresis ΔE. In addition, the ceramics also displayed excellent thermal stability with low energy density variation (<6%) over a wide temperature range of 20−80 °C. These results indicate that Mn-doped (1-x)AgNbO₃-xBi_0.5Na_0.5TiO₃ ceramics are highly efficient lead-free antiferroelectric materials for potential application in high energy storage capacitors.     

Coil‐Type Asymmetric Supercapacitor Electrical Cables

Cable‐shaped supercapacitors (SCs) have recently aroused significant attention due to their attractive properties such as small size, lightweight, and bendability. Current cable‐shaped SCs have symmetric device configuration. However, if an asymmetric design is used in cable‐shaped supercapacitors, they would become more attractive due to broader cell operation voltages, which results in higher energy densities. Here, a novel coil‐type asymmetric supercapacitor electrical cable (CASEC) is reported with enhanced cell operation voltage and extraordinary mechanical‐electrochemical stability. The CASECs show excellent charge–discharge profiles, extraordinary rate capability (95.4%), high energy density (0.85 mWh cm⁻³), remarkable flexibility and bendability, and superior bending cycle stability (≈93.0% after 4000 cycles at different bending states). In addition, the CASECs not only exhibit the capability to store energy but also to transmit electricity simultaneously and independently. The integrated electrical conduction and storage capability of CASECS offer many potential applications in solar energy storage and electronic gadgets.     

飞机撞击下高温气冷堆乏燃料厂房损伤研究

本文针对典型高温气冷堆乏燃料厂房在双发商用飞机撞击载荷下的响应及结构完整性开展研究，并探讨结构特性对撞击损伤的影响。对乏燃料厂房及飞机分别建立有限元模型，通过弹体-目标相互作用分析模拟了飞机撞击过程，综合IAEA与NRC的评价准则对乏燃料厂房在飞机撞击下的损伤程度进行评估。数值结果表明：厂房上对应于机身及发动机的撞击位置发生可接受的局部损伤；乏燃料贮存井墙体对于提高构筑物抗飞机撞击能力有重要作用。此外，构筑物外形对损伤有很大影响，圆柱形壳体的抗飞机撞击能力显著强于方形厂房，是核电厂厂房设计的优化方向之一。     

基于深度信念网络的列车故障音频诊断方法

铁路在交通运输行业有着举足轻重的地位，一旦列车发生故障将会导致严重的生命财产损失。由于列车发生故障的概率相对较低，因此难以捕获列车的故障样本。针对上述问题，提出了一种无监督学习的列车故障识别方法，通过检测列车音频信号来识别列车故障。该方法基于深度信念网络(DBN)，利用小波包分解提取检测信号的特征向量并将其作为DBN的输入，待网络充分训练后，由训练好的DBN识别当前列车的运行状况。现场监测实验结果表明，该方法能够在无监督的条件下有效识别列车故障，保障了列车的运行安全。     

基于深度学习的秀丽隐杆线虫显微图像分割方法

利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。     

Remarkably enhanced energy storage properties of lead-free Ba0.53Sr0.47TiO3 thin films capacitors by optimizing bottom electrode thickness

The lead-free Ba_0.53Sr_0.47TiO₃ (BST) thin films buffered with La_0.67Sr_0.33MnO₃ (LSMO) bottom electrode of different thicknesses were fabricated by pulsed laser deposition method on a (001) SrTiO₃ substrate. It was found that the roughness of electrode decreases and substrate stress relaxes gradually with the increase of LSMO thickness, which is beneficial for weakening local high electric field and achieving higher E_b. Therefore, the recoverable energy density (W_rec) of BST films can be greatly improved up to 67.3 %, that is, from 30.6 J/cm³ for the LSMO thickness of 30 nm up to 51.2 J/cm³ for the LSMO thickness of 140 nm after optimizing the LSMO thickness. Furthermore, the thin film capacitor with a 140 nm LSMO bottom electrode shows an outstanding thermal stability from 20 °C to 160 °C and superior fatigue resistance after 10⁸ electrical cycles with only a slightly decrease of W_rec below 1.6 % and 3.7 %, respectively. Our work demonstrates that optimizing bottom electrodes thickness is a promising way for enhancing energy storage properties of thin-film capacitors.