Good dielectric performance and broadband dielectric polarization in Ag,Nb co-doped TiO2

Due to the demand of miniaturization and integration for ceramic capacitors in electronic components market, TiO₂-based ceramics with colossal permittivity has become a research hotspot in recent years. In this work, we report that Ag⁺/Nb⁵⁺ co-doped (Ag_1/4Nb_3/4)_xTi_1−xO₂ (ANTOx) ceramics with colossal permittivity over a wide frequency and temperature range were successfully prepared by a traditional solid–state method. Notably, compositions of ANTO0.005 and ANTO0.01 respectively exhibit both low dielectric loss (0.040 and 0.050 at 1 kHz), high dielectric permittivity (9.2 × 10³ and 1.6 × 10⁴ at 1 kHz), and good thermal stability, which satisfy the requirements for the temperature range of application of X9R and X8R ceramic capacitors, respectively. The origin of the dielectric behavior was attributed to five dielectric relaxation phenomena, i.e., localized carriers' hopping, electron–pinned defect–dipoles, interfacial polarization, and oxygen vacancies ionization and diffusion, as suggested by dielectric temperature spectra and valence state analysis via XPS; wherein, electron-pinned defect–dipoles and internal barrier layer capacitance are believed to be the main causes for the giant dielectric permittivity in ANTOx ceramics.     

润滑油中磨损颗粒在线监测传感器研究进展*

油液监测是判断设备健康状况和提供设备故障隐患预警的有效方法。综述了用于监测润滑油中磨损颗粒的最新各类在线传感器的基本原理,包括批量磁吸附式传感器、微流体电容传感器、金属扫描传感器、双层平面线圈传感器、超声波传感器和光学传感器等,并讨论各种传感方法的优缺点以及未来发展面临的挑战;指出了高通量、高灵敏度、能区别金属与非金属磨粒、可采集磨粒图像信息的集成式传感器是未来研究的重点,集成式、智能化、无线传输的传感器是未来研发方向。     

纳米药物非临床药代动力学的研究策略及关注要点

随着纳米技术的迅速发展，纳米药物的研发已成为目前药物创新的发展方向之一。纳米药物具有基于纳米结构的尺度效应，其药代动力学特征与普通药物相比存在明显差异，其药代动力学研究与普通药物相比也有其特殊性。本文着重探讨纳米药物的非临床药代动力学的研究策略及关注要点，包括受试物、体内/外试验、生物样本分析、数据评价分析等，期望为研发者提供参考。     

High-temperature oxidation behavior of monolithic Zr3[Al(Si)]4C6 and its composite incorporating 30vol% ZrB2-SiC: Providing a basis for broadening the service temperature

To provide a basis for the high-temperature oxidation of ultra-high temperature ceramics (UHTCs), the oxidation behavior of Zr₃[Al(Si)]₄C₆ and a novel Zr₃[Al(Si)]₄C₆-ZrB₂-SiC composite at 1500 °C were investigated for the first time. From the calculation results, the oxidation kinetics of the two specimens follow the oxidation dynamic parabolic law. Zr₃[Al(Si)]₄C₆ exhibited a thinner oxide scale and lower oxidation rate than those of the composite under the same conditions. The oxide scale of Zr₃[Al(Si)]₄C₆ exhibited a two-layer structure, while that of the composite exhibited a three-layer structure. Owing to the volatilization of B₂O₃ and the active oxidation of SiC, a porous oxide layer formed in the oxide scale of the composite, resulting in the degradation of its oxidation performance. Furthermore, the cracks and defects in the oxide scale of the composite indicate that the reliability of the oxide scale was poor. The results support the service temperature of the obtained ceramics.     

0–1膨胀几何分布的客观贝叶斯分析

在医疗卫生、金融证券等应用领域，经常会同时出现零观测值、一观测值较多的情况. 为更好地拟合这类数据，提出0–1膨胀几何分布模型并进行客观贝叶斯分析. 通过参数变换，得到Jeffreys先验和reference先验. 设计后验分布的抽样算法，设置不同的样本量和参数真值，采用数值模拟方法对不同客观先验下的估计效果进行评估.     

盾构隧道施工物料无人运输发展现状及关键技术

盾构隧道施工物料无人运输有助于提升运输效率、降低运输成本、减少运输安全事故率。与公路汽车无人驾驶、港口车辆无人驾驶、轨道交通无人驾驶等逐步成熟的无人驾驶技术不同，在隧道场景下实施施工物料无人运输存在运输物料种类繁多、运输调度困难、地下定位信号拒止、狭窄车道频繁会车、行车路面工况复杂、地上地下联动响应慢等诸多挑战。从实现盾构隧道施工物料无人运输的关键问题分析入手，综述当前盾构隧道施工物料运输方式、运输需求、无人运输发展现状及存在的挑战，提出盾构隧道施工物料无人运输的五大关键技术：多种类物料智能货控能效管理技术，无人化垂直装卸门机控制技术，多传感器融合同步定位与地图构建技术，隧道复杂环境路径规划与自主避障技术，隧-地一体化联动响应的高可靠性无线通信技术。     

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。     

基于堆叠稀疏去噪自动编码网络与多隐层反向传播神经网络的铣刀磨损预测模型

刀具磨损状态是机械加工过程中需考虑的重要因素之一.针对铣刀磨损的在线预测问题,建立了一种基于深度学习的铣刀磨损预测模型.首先,将采集到的铣刀切削时的振动信号进行小波去噪后,利用快速傅里叶变换和小波包分解等技术提取时域、频域及时频域上的特征参数,并根据相关性分析从中筛选出合格的特征参数合并为特征向量,以此作为堆叠稀疏去噪自动编码网络(SSDAE)的含噪样本.其次,利用特征后处理的方式对已经筛选出的特征参数进行单调不递减及平滑处理,并将其作为SSDAE的无噪样本来训练该网络.然后,将经过SSDAE降维后的特征向量作为多隐层反向传播神经网络(BPNN)的输入,以这些特征对应的实际铣刀的磨损量作为标签对该网络进行拟合训练.最后,对训练好的模型进行实验验证,通过测试数据集和人为加入噪声的测试数据集的对比,结果显示所提模型不仅具有较高的预测精度,还具有较高的鲁棒性.