温度对变压器绝缘缺陷影响规律的分析及验证

本文中作者研究了温度对油浸式变压器绝缘纸老化水平的影响,开展了频域介电谱测试得出不同的试验温度下绝缘纸的电导率频域谱.推导了温度、电导率和相对介电常数之间的作用情况,并进行实例验证.     

VO2/GaAs异质结的制备及其光电特性研究

采用直流磁控溅射和后退火氧化工艺在p型GaAs单晶衬底上成功制备了n-VO_2/pGaAs异质结,研究了不同退火温度和退火时间对VO_2/GaAs异质结性能的影响,并分析其结晶取向、化学组分、膜层质量以及光电特性。结果表明,在退火时间2 h和退火温度693 K下能得到相变性能最佳的VO_2薄膜,相变前后电阻变化约2个数量级。VO_2/GaAs异质结在308 K、318 K和328 K温度下具有较好的整流特性,对应温度下的阈值跳变电压分别为6.9 V、6.6 V和6.2 V,该结果为基于VO_2相变特性的异质结光电器件的设计与应用提供了可行性。     

基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

Inhibitory effects of curcumin and piperine on fluorescent advanced glycation end products formation in a bovine serum albumin–fructose model

This study investigated the inhibitory effects of curcumin and piperine on fluorescent advanced glycation end products (fAGEs) formation in a bovine serum albumin (BSA)–fructose model. Model systems of BSA and fructose were prepared, and curcumin or piperine was added. fAGEs and BSA oxidation product (dityrosine, kynurenine and N'-formylkynurenine) contents were determined. The results showed that fAGEs content decreased with increasing concentration of curcumin and piperine (P < 0.05). Addition of curcumin and piperine at 160 µg mL⁻¹ could inhibit fluorescent AGEs by 100% and 93% respectively. Dityrosine and N'-formylkynurenine contents decreased as curcumin and piperine concentration increased (P < 0.05). Furthermore, the result of principal component analysis indicated that curcumin and piperine markedly impeded BSA oxidation, resulting in a lower level of fAGEs in model systems. Therefore, adding curcumin and piperine may facilitate reduced fAGEs levels in BSA–fructose model.     

智慧标识网络服务机理研究进展及安全性分析

随着互联网规模的不断扩大以及应用场景的多元化,传统网络无法很好地满足新业务的动态多样化需求,因此国内外对未来网络展开了深入研究.本文首先介绍了未来互联网体系架构的研究现状.其次,介绍了具备"三层、两域"特征的智慧标识网络(Smart Identifier NETwork,SINET)体系架构,然后重点阐述了SINET服务机理在服务的命名与解析、路由机制、服务缓存、移动性、传输控制机制、可扩展性、绿色节能等关键技术方面取得的研究进展,并进一步详细分析了SINET服务机理的安全性.最后总结了SINET面临的挑战,对SINET服务机理在大规模场景部署中可能存在的问题做出讨论.     

Eco-friendly and degradable red phosphorus nanoparticles for rapid microbial sterilization under visible light

Pathogens pose a serious challenge to environmental sanitation and a threat to public health.The frequent use of chemicals for sterilization in recent years has not only caused secondary damage to the environment but also increased pathogen resistance to drugs,which further threatens public health.To address this issue,the use of non-chemical antibacterial means has become a new trend for environmental disinfection.In this study,we developed red phosphorus nanoparticles(RPNPs),a safe and degradable photosensitive material with good photocatalytic and photothermal properties.The red phosphorus nanoparticles were prepared using a template method and ultrasonication.Under the irradiation of simulated sunlight for 20 min,the RPNPs exhibited an efficiency of 99.98%in killing Staphylococcus aureus due to their excellent photocatalytic and photothermal abilities.Transmission electron microscopy and ultraviolet–visible spectroscopy revealed that the RPNPs exhibited degradability within eight weeks.Both the RPNPs and their degradation products were nontoxic to fibroblast cells.Therefore,such RPNPs are expected to be used as a new type of low-cost,efficient,degradable,biocompatible,and eco-friendly photosensitive material for environmental disinfection.     

基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

Optical design of the Lyman alpha based beam emission spectroscopy(LAB)diagnostic on the HL-2A tokamak

In this article, we present the optical design of a novel diagnostic on the HL-2 A tokamak, i.e. the20-channel edge Lyman-alpha beam emission spectroscopy, which is a promising solution for edge density turbulence research on tokamaks, as it offers the possibility of density fluctuation measurement with a 3.3 mm spatial resolution while maintains a high temporal resolution of1 μs. The optical path, including the reflective collection optics, the high-dispersion spectrometer, and the linear detector array, is carefully optimized to obtain a good image quality and a high throughput. The maximum root mean square radius of the collection optics is 64 μm.The detected photon flux is estimated to be about 10~(11) photons/s/channel.     

基于跨临界CO2热泵的茶叶生产能源系统负荷削减潜力

乡村产业中的化石能源设备逐渐被电能技术替代，引起了乡村负荷波动增大、部分时段产生集中高负荷的问题。为了解决以上问题，将低品位清洁能源应用至乡村的茶叶生产中，针对烘茶全过程的工艺要求提出了跨临界CO₂热泵烘茶技术；并以某茶叶生产乡村为对象，对其代表台区的全年日用电量及产茶日负荷进行了分析，得出采用CO₂热泵烘茶后其负荷得到大幅度削减，整体可降低至原负荷的39.6%~46.8%，峰值负荷与平时负荷的比值由原本的13.6降至5.4~6.2。跨临界CO₂热泵应用至农产品生产中可有效缓解乡村供电压力。