Surface treatment of titanium dioxide nanopowder using rotary electrode dielectric barrier discharge reactor

Titanium dioxide (TiO2) nanopowder (P-25;Degussa AG) was treated using dielectric barrier discharge (DBD) in a rotary electrode DBD (RE-DBD) reactor.Its electrical and optical characteristics were investigated during RE-DBD generation.The treated TiO2 nanopowder properties and structures were analyzed using x-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR).After RE-DBD treatment,XRD measurements indicated that the anatase peak theta positions shifted from 25.3° to 25.1°,which can be attributed to the substitution of new functional groups in the TiO2 lattice.The FTIR results show that hydroxyl groups (OH) at 3400 cm-1 increased considerably.The mechanism used to modify the TiO2 nanopowder surface by air DBD treatment was confirmed from optical emission spectrum measurements.Reactive species,such as OH radical,ozone and atomic oxygen can play key roles in hydroxyl formation on the TiO2 nanopowder surface.     

Pectic Galactan Polysaccharide-Based Gene Delivery System for Targeting Neuroinflammation

Treating neuroinflammation-related injuries and disorders through manipulation of neuroinflammation functions is being heralded as a new therapeutic strategy. In this study, a novel pectic galactan (PG) polysaccharide based gene therapy approach is developed for targeting reactive gliosis in neuroinflammation. Galectin-3 (Gal-3) is a cell protein with a high affinity to β-galactoside sugars and is highly expressed in reactive gliosis. Since PG carries galactans, it can target reactive gliosis via specific carbohydrate interaction between galactan and Gal-3 on the cell membrane, and therefore can be utilized as a carrier for delivering genes to these cells. The carrier is synthesized by modifying quaternary ammonium groups on the PG. The resulting quaternized PG (QPG) is found to form complexes with plasmid DNA with a mean diameter of 100 nm and have the characteristics required for targeted gene therapy. The complexes efficiently condense large amounts of plasmid per particle and successfully bind to Gal-3. The in vivo study shows that the complexes are biocompatible and safe for administration and can selectively transfect reactive glial cells of an induced cortical lesion. The results confirm that this PG-based delivery system is a promising platform for targeting Gal-3 overexpressing neuroinflammation cells for treating neuroinflammation-related injuries and neurodegenerative diseases.     

基于PMU的电力系统监控体系结构优化设计

文中提出了一种利用有限数量的相量测量单元(PMU)和相量数据集中器(PDC)设计最优监控结构的方法。通过在大量的设定值场景下,使电力系统可观测性曲线的期望值最大化,同时使通信基础设施成本最小化,最终确定PMU和PDC的最佳位置。提出了一种非线性动态扩展卡尔曼滤波(EFK)状态观测器。这种状态观测器可以将暂态行为转换为由代数微分方程描述的广域电力系统,而无需非线性反演技术。最后以IEEE-5电力系统为例,说明了该方法的有效性。     

建筑工业化发展的多群体演化博弈与仿真研究

新型建筑工业化具有高质量、低消耗、可循环发展等特征，其推广已上升到国家战略层面。利用演化博弈方法，建立“政府-开发商-银行” 的三方动态演化博弈模型，进行各博弈主体策略的演化稳定性分析，并针对初始状态、奖惩力度、借贷风险和开发成本等对演化结果的影响进行动态仿真。在此基础上， 考虑开发商群体的网络拓扑特征对演化真实性的影响，引入复杂网络理论， 以无标度网络为载体描述开发商个体的连接偏好和决策机制，构建政府监管下的建筑工业化扩散模型，并通过仿真深入研究相关因素对扩散深度的影响作用，最后结合仿真结果给出相应对策建议。     

基于NR-Transformer的集群作业运行时间预测

高性能集群的作业调度通常使用作业调度系统来实现，准确填写作业运行时间能在很大程度上提升作业调度效率。现有的研究通常使用机器学习的预测方式，在预测精度和实用性上还存在一定的提升空间。为了进一步提高集群作业运行时间预测的准确率，考虑先对集群作业日志进行聚类，将作业类别信息添加到作业特征中，再使用基于注意力机制的NR-Transformer网络对作业日志数据建模和预测。在数据处理上，根据与预测目标的相关性、特征的完整性和数据的有效性，从历史日志数据集中筛选出7维特征，并按作业运行时间的长度将其划分为多个作业集，再对各作业集分别进行训练和预测。实验结果表明，相比于传统机器学习和BP神经网络，时序神经网络结构有更好的预测性能，其中NR-Transformer在各作业集上都有较好的性能。     

超宽带大功率合成器设计北大核心CSCD

在80 MHz~1 GHz频段,单个功率管输出功率能达到100 W以上,为研制输出功率400 W的功率放大器,文中设计了四路功率合成器。该合成器需要实现功率容量大、工作频带宽、体积小的设计目标。在功率容量方面,文中采用悬置带状线结构,其功率容量远远大于微带线结构;在工作频带方面,采用切比雪夫九节阻抗变换器,将工作带宽拓宽为80 MHz~1 GHz;在体积方面,文中合成器的功率合成部分采用Y型节级联实现四路功率合成,阻抗变换部分采用切比雪夫阻抗变换器进行阻抗变换,该结构相较于磁环巴伦功率合成器,不但具有损耗小、平坦度高的优点,而且通过将阻抗变换器设计成曲折的形状,进一步缩小了合成器体积。仿真与实测结果显示该合成器在80 MHz~1 GHz范围内还具有较高的平坦度,合成效率可达90%以上。     

智能电网中D2D网络的通信资源管理优化方案

当前在智能电网的应用中,各种智能终端的使用,使得移动数据流量空前增长,电力互联方式在面临海量数据传输的需求时,由于资源受限,信道间会产生一定的干扰,从而影响通信质量。为了解决通信资源管理这一问题,与常见的移动边缘计算(MEC)方法不同,文中提出了一种网络资源分配方法,优化链路选择和子信道分配,以实现能量效率的最大化。仿真结果表明,与没有卸载和部分优化的方法相比,此方法在能效方面有了很大的提高。     

An optimal configuration for hybrid SOFC,gas turbine,and Proton Exchange Membrane Electrolyzer using a developed Aquila Optimizer

In this research, a technical, economic and environmental analysis has been proposed to a Hybrid Solid Oxide Fuel Cell (SOFC) system-based hybrid system including biomass, gas turbine, and Proton Exchange Membrane Electrolyzer. A multi-objective optimization technique has been utilized to improve the overall product cost and the exergy effectiveness based on a developed version of Aquila Optimizer (DAO). The main idea of using the developed version is to improve the accuracy and the precision of the original Aquila optimizer. The system is then authenticated in terms of energy/exergy effectiveness, and energy-economic efficiency. The achievements indicate that employing the optimization algorithm for different configurations provided satisfying results for the system.     

碳中和背景下配电网差异化节能降耗潜力评估分

为了提高配电网差异化节能降耗效果，解决现有潜力评估方法存在的应用性能差的问题，提出碳中和背景下配电网差异化节能降耗潜力优化评估方法。根据配电网的空间结构，构建相应的等值电路模型。在该模型下，从设备损耗和运行附加损耗2个方面计算配电网的损耗量。根据损耗量计算结果，确定配电网差异化碳中和节能降耗方式。从静态和动态2个角度设置潜力评估指标，通过指标数据处理、指标权重求解等步骤，得出配电网差异化节能降耗潜力的综合量化评估结果。将设计潜力评估方法应用到配电网的差异化节能降耗改造工作中，能够有效降低配电网的实际线损量、降低区域损耗费用，并具有较高的应用价值。