Enhanced properties for visible-light-driven photocatalysis of Ag nanoparticle modified Bi2MoO6 nanoplates

The visible light driven Bi₂MoO₆ photocatalyst doped with different contents of Ag nanoparticles was successfully synthesized by a combination of hydrothermal and sonochemical methods. The as-synthesized samples were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning and transmission electron microscopy (SEM and TEM) and UV–visible spectroscopy to investigate crystalline structure, morphology, composition and photocatalytic properties. XRD patterns and TEM images of the samples revealed pure phase orthorhombic Bi₂MoO₆ nanoplates without any detection of Ag dopant due to its low concentration and very tiny particle size. TEM images showed that Ag nanoparticles with the size of 10–15 nm were dispersed randomly on the surface of Bi₂MoO₆. The XPS analysis of Ag/Bi₂MoO₆ nanocomposites revealed the presence of additional metallic Ag. Photocatalytic activities of the Ag/Bi₂MoO₆ nanocomposites were evaluated by determining the degradation of rhodamine B (RhB) under visible light radiation. In this research, the 10 wt% Ag/Bi₂MoO₆ nanocomposites showed the best photocatalytic activity. The results suggest that the dispersion of Ag nanoparticles on the surface of Bi₂MoO₆ significantly enhances its photocatalytic activity.     

Optimised phase compositions and improved microwave dielectric properties based on calcium tin silicates

The Ca_(1+2y)Sn_(1-x)Si_(1+y)O_(5-2x+4y) low-permittivity microwave dielectric ceramics were prepared through solid-state reaction at 1350–1450 °C for 5 h. The relations between microwave dielectric properties and phase compositions for non-stoichiometric Ca_(1+2y)Sn_(1-x)Si_(1+y)O_(5-2x+4y) ceramics have been investigated. A single CaSnSiO₅ phase with abnormally positive temperature coefficient of resonant frequency (τ_f = + 62.5 ppm/°C) was synthesised at 1450 °C. This composition was an effective τ_f compensator of CaSiO₃ and Ca₃SnSi₂O₉ phases with typically negative τ_f value. The CaSiO₃ second phase was related to the Sn deficiency in the CaSn_(1-x)SiO_(5-2x) (0 < x < 1.0) composition, whereas the Ca₃SnSi₂O₉ second phase was obtained by controlling the Ca:Sn:Si ratios on the basis of the Ca_(1+2y)SnSi_(1+y)O_(5+4y) (0 < y < 1.0) composition. A promising low-permittivity millimetre-wave ceramic with most excellent microwave dielectric properties (ε_r = 10.2, Q×f = 81,000 GHz and τ_f = −4.8 ppm/°C) was produced from the Ca_(1+2y)SnSi_(1+y)O_(5+4y) (y = 0.4) ceramic.     

超宽带极窄脉冲设计与产生

超宽带(UWB)技术是以持续时间极短的脉冲作为传输载体进行数据通信的无线新技术。基于BJT雪崩特性,本文采用并行同时触发的工作方式,设计并产生了高重复速率的UWB脉冲电路发生器,极大地减少了时延,缩短了上升时间,提高了脉冲的幅度,并从等效电路法的观点分析计算了脉冲的特性参数,理论结果与实测结果具有较好的一致性。     

光通信技术讲座--(五):WDM系统光节点器件

介绍WDM系统光节点所用到的器件,如波长转换器、光分插复用器及其使用的光隔离器和光环形器.     

Optimizing random walk search algorithms in P2P networks

In this paper we develop a model for random walk-based search mechanisms in unstructured P2P networks. This model is used to obtain analytical expressions for the performance metrics of random walk search in terms of the popularity of the resource being searched for and the random walk parameters. We propose an equation-based adaptive search mechanism that uses an estimate of the popularity of a resource in order to choose the parameters of random walk such that a targeted performance level is achieved by the search. We also propose a low-overhead method for maintaining an estimate of popularity that utilizes feedback (or lack there-off) obtained from previous searches. Simulation results show that the performance of the equation-based adaptive search is significantly better than the non-adaptive random walk and other straight-forward adaptive mechanisms.     

光纤通信在军事上的应用

简述了光纤通信在军事通信中的地位与作用，较全面介绍了陆、海、空军各领域的应用情况，阐明了军事通信对光纤通信元器件的要求和核爆炸对光纤通信的影响。     

云计算的可信性

云计算是一种新兴的商业计算模型,同时又是一种能够动态伸缩的虚拟化资源。云计算的安全问题其实就是一种对可信的挑战。     

一种基于相关函数法铁磁谐振波形研究

对铁磁谐振波形进行了系统的分类分级,提出了一种基于Matlab的相关函数方法,并且利用大量数据进行对比,已经得到了效果验证,经过桂林市电力电容器责任有限公司认证,具有良好的实际效果。     

Data monitoring and sports injury prediction model based on embedded system and machine learning algorithm

Managing sports performance is very important in the sports industry. Performance, the executives, centers on boosting competitor execution and decreasing the danger of injury. Several factors contribute to these goals, including player health, emotional status, exercise load and physical intensity requirements. Generally speaking, injury prediction is an essential component of injury prevention, and successful identification of injury prediction is a primary indicator for effective prevention. The proposed Artificial Neural Network (ANN) objective is to develop and use early-doing ability and exercise load data to validate a hierarchical machine learning prediction system with accurate detection of player injuries. The physical and workload that requires detection of this early personalized damage can be avoided with specific help. The framework is used to test 21 soccer players’ sports information from various sources, including gathered and inside burden information, outside burden information, and review information. The entirety of this information is fused into the proposed framework to improve the exactness of harm expectation. This calculation distinguishes competitors in danger of injury, with their early intervention available.