A dense and compact laser cladding layer with solid metallurgical bonding significantly improved corrosion resistance of Mg alloy for engineering applications

Although Mg alloy attracts great attention for engineering applications because of high specific strength and low density, low corrosion resistance limits its extensive use. In this study, Mg–Al–Zn–Mn alloy was treated via a laser cladding process to generate a dense and compact laser cladding layer with solid metallurgical bonding on the substrate for improving corrosion resistance, effectively hindering the corrosion pervasion into Mg alloy. The corrosion current density declined from 103 μA/cm² for Mg alloy to 13 μA/cm² for the laser cladding layer in NaCl aqueous solution. Moreover, the laser cladding layer was slightly corroded in comparison with Mg alloy in NaCl aqueous solution. Besides, the microhardness of the cladding layer reached a mean value of 170.5 HV, 3.1 times of Mg alloy (56.8 HV) due to the in situ formation of hardening intermetallic phases. Wear resistance of laser cladding layer was also obviously improved. These results demonstrated that the laser cladding layer obviously enhanced anticorrosion property of Mg alloy for engineering applications.     

Aptamer-Functionalized Nanoparticles in Targeted Delivery and Cancer Therapy

Using nanoparticles to carry and delivery anticancer drugs holds much promise in cancer therapy, but nanoparticles per se are lacking specificity. Active targeting, that is, using specific ligands to functionalize nanoparticles, is attracting much attention in recent years. Aptamers, with their several favorable features like high specificity and affinity, small size, very low immunogenicity, relatively low cost for production, and easiness to store, are one of the best candidates for the specific ligands of nanoparticle functionalization. This review discusses the benefits and challenges of using aptamers to functionalize nanoparticles for active targeting and especially presents nearly all of the published works that address the topic of using aptamers to functionalize nanoparticles for targeted drug delivery and cancer therapy.     

A Flexi-PEGDA Upconversion Implant for Wireless Brain Photodynamic Therapy

Near-infrared (NIR) activatable upconversion nanoparticles (UCNPs) enable wireless-based phototherapies by converting deep-tissue-penetrating NIR to visible light. UCNPs are therefore ideal as wireless transducers for photodynamic therapy (PDT) of deep-sited tumors. However, the retention of unsequestered UCNPs in tissue with minimal options for removal limits their clinical translation. To address this shortcoming, biocompatible UCNPs implants are developed to deliver upconversion photonic properties in a flexible, optical guide design. To enhance its translatability, the UCNPs implant is constructed with an FDA-approved poly(ethylene glycol) diacrylate (PEGDA) core clad with fluorinated ethylene propylene (FEP). The emission spectrum of the UCNPs implant can be tuned to overlap with the absorption spectra of the clinically relevant photosensitizer, 5-aminolevulinic acid (5-ALA). The UCNPs implant can wirelessly transmit upconverted visible light till 8 cm in length and in a bendable manner even when implanted underneath the skin or scalp. With this system, it is demonstrated that NIR-based chronic PDT is achievable in an untethered and noninvasive manner in a mouse xenograft glioblastoma multiforme (GBM) model. It is postulated that such encapsulated UCNPs implants represent a translational shift for wireless deep-tissue phototherapy by enabling sequestration of UCNPs without compromising wireless deep-tissue light delivery.     

基于CFD方法的铅铋冷却燃料棒束的热工水力特性分析

铅铋冷却快堆作为第4代反应堆候选之一具有安全性高等特点，研究其在正常工况下的热工水力特性具有重要意义。本文基于商用计算流体力学（CFD）软件STAR-CCM+，使用流固耦合的方法对带有绕丝结构的19棒束铅铋组件进行数值分析，探究了质量流量、功率等边界条件对组件内部流动传热特性的影响。模拟计算结果表明：CFD方法在子通道中心温度和壁面温度预测上与实验结果取得了较好的一致。同时，绕丝结构的存在使得子通道之间存在周期性的横向交混，并使得棒束表面温度呈现震荡。随质量流量的增加，子通道间横向交混增大。功率变化对通道间的横向交混速度的影响较小，冷却剂温度的横向分布无明显差异。     

光伏用电致发光缺陷检测仪空间分辨率的量化评估

针对光伏用电致发光缺陷检测仪空间分辨率目视判定重复性、准确性差,并且难以量化等问题,提出一套基于卷积神经网络模型的空间分辨率量化评估方法。参照相关标准JJF(闽)1088-2018,采取不同的拍摄条件拍摄并切割出空间分辨率线对图像,对图像进行人工分类。设计卷积神经网络结构,采用卷积层、池化层和全连接层结构,并使用已分类完成的空间分辨率线对图像对模型进行训练。最终使用测试集对模型进行评估,结果表明,模型在测试集上的判别正确率达到99.2%。该方法满足使用要求,可取代目视判别,提高了光伏用电致发光缺陷检测仪空间分辨率判定的准确性与重复性,并为其量化提出了新的解决思路。由于太阳电池片用光致发光缺陷检测仪与光伏用电致发光缺陷检测仪的成像方式类似,该方法可兼容太阳电池片光致发光检测仪的性能评估。     

影响高空探测质量的原因分析及措施

高空气象探测系统具有较高的探测精度和自动化程度。文章通过对高空探测中影响探测的重放球、迟放球原因的分析,结合工作实践,总结了雷达、计算机、基测箱、探空仪等在运行过程中出现的问题,并提出具体的解决方法,实践证明运行效果显著,为业务人员提供参考。     

基于深度学习的安全缺陷报告预测方法实证研究

软件安全问题的发生在大多数情况下会造成非常严重的后果，及早发现安全问题，是预防安全事故的关键手段之一.安全缺陷报告预测可以辅助开发人员及早发现被测软件中潜藏的安全缺陷，从而尽早得以修复.然而，由于安全缺陷在实际项目中的数量较少，而且特征复杂（即安全缺陷类型繁多，不同类型安全缺陷特征差异性较大），这使得手工提取特征相对困难，并随后造成传统机器学习分类算法在安全缺陷报告预测性能方面存在一定的瓶颈.针对该问题，提出基于深度学习的安全缺陷报告预测方法，采用深度文本挖掘模型TextCNN和TextRNN构建安全缺陷报告预测模型；针对安全缺陷报告文本特征，使用skip-grams方式构建词嵌入矩阵，并借助注意力机制对TextRNN模型进行优化.所构建的模型在5个不同规模的安全缺陷报告数据集上展开了大规模实证研究，实证结果表明：深度学习模型在80%的实验案例中都要优于传统机器学习分类算法，性能指标F1-score平均可提升0.258，在最好的情况下甚至可以提升0.535.除此之外，针对安全缺陷报告数据集存在的类不均衡问题，对不同采样方法进行了实证研究，并对结果进行了分析.     

Recycling photovoltaic silicon waste for fabricating porous mullite ceramics by low-temperature reaction sintering

In this study, porous mullite ceramics with coral-like structures were fabricated at a low temperature of 900 °C by using photovoltaic silicon waste (PSW) as the silicon source directly. The effects of additive content and sintering temperature on the mullitization reaction of green bodies were studied. The results showed that ammonium molybdate tetrahydrate molybdenum (H₂₄Mo₇N₆O₂₄·4H₂O) as an additive could reduce the reaction temperature for mullitization from 1100 °C to 900 °C. The research on the influence of catalyst on material properties showed that porous mullite ceramics with a flexural strength of 52.83 MPa, a 41.78 % porosity, a sintering expansion rate of 0.49 % and an average pore size of 0.23 μm could be fabricated by introducing 7.5 % H₂₄Mo₇N₆O₂₄·4H₂O at the sintering temperature of 1000 °C. This study develops an environment-friendly recycling method of PSW and provides a new idea for the low-cost preparation of porous mullite ceramics with high purity.     

Opportunities and Challenges in Tunneling Nanotubes Research: How Far from Clinical Application?

Tunneling nanotubes (TNTs) are recognized long membrane nanotubes connecting distance cells. In the last decade, growing evidence has shown that these subcellular structures mediate the specific transfer of cellular materials, pathogens, and electrical signals between cells. As intercellular bridges, they play a unique role in embryonic development, collective cell migration, injured cell recovery, cancer treatment resistance, and pathogen propagation. Although TNTs have been considered as potential drug targets for treatment, there is still a long way to go to translate the research findings into clinical practice. Herein, we emphasize the heterogeneous nature of TNTs by systemically summarizing the current knowledge on their morphology, structure, and biogenesis in different types of cells. Furthermore, we address the communication efficiency and biological outcomes of TNT-dependent transport related to diseases. Finally, we discuss the opportunities and challenges of TNTs as an exciting therapeutic approach by focusing on the development of efficient and safe drugs targeting TNTs.