Photocatalytic degradation of 2,2‐bis(4‐hydroxy‐3‐methylphenyl) propane (BPP) based on molecular recognition interaction

BACKGROUND: Endocrine disruptors in the aquatic environment and their potential adverse effects are currently issues of concern. One of these endocrine disruptors is 2,2‐bis(4‐hydroxy‐3‐methylphenyl)propane (BPP). In this work the molecular recognition interaction of BPP with β‐cyclodextrin (β‐CD) was studied using IR spectroscopy and steady state fluorescence spectroscopy, and the photocatalytic degradation behaviour of BPP based on molecular recognition interaction was investigated in a TiO₂/UV–visible (λ_max = 365 nm) system. This might provide a new method for the treatment of some organic pollutants in wastewater. RESULTS: β‐CD reacts with BPP to form a 1:1 inclusion complex, the formation constant of which is 4.94 × 10³ L mol^?1. The photodegradation rate constant of BPP after molecular recognition by β‐CD showed a 1.42‐fold increase in the TiO₂/UV–visible (λ_max = 365 nm) system. The photodegradation of BPP depended on the concentration of β‐CD, the pH value, the gaseous medium and the initial concentration of BPP. The photodegradation efficiency of BPP with molecular recognition was higher than that without molecular recognition. After 100 min of irradiation the mineralisation efficiency of BPP after molecular recognition by β‐CD reached 94.8%, whereas the mineralisation efficiency of BPP before molecular recognition by β‐CD was only 40.6%. CONCLUSION: The photocatalytic degradation of BPP after molecular recognition by β‐CD can be enhanced in the TiO₂/UV‐visible (λ_max = 365 nm) system. This enhancement is dependent on the enhancement of the adsorption of BPP, the moderate inclusion depth of BPP in the β‐CD cavity and the increase in the frontier electron density of BPP after molecular recognition. Copyright © 2008 Society of Chemical Industry     

深基坑工程安全评价的尖点突变模型

为评价深基坑工程失稳的突变特征,采用突变理论建立了深基坑工程尖点突变安全评价模型.根据工程安全监控理论,引入突变理论,以基坑水平变形为例,考虑深基坑土体的流变特性,建立了基于时效影响因子的深基坑工程尖点突变安全评价模型.实例分析表明,尖点突变安全评价模型克服了采用常规设置监控值评价时参数选择困难,并能反映基坑失稳突变性的特点,可以量化评价基坑安全程度,正确评价安全状态,具有适应性强、精度高的优点.     

基于MVC的振动噪声数据库系统的设计与实现

预期的研究成果是拥有自主知识产权的振动噪声数据库.通过建立这样一个数据信息规模较大、可用性强、开放式的振动噪声数据库,为振动噪声试验工作提供坚实的基础.对系统进行了概要的介绍,提出了一套基于J2EE框架平台的系统解决方案.整个系统采用了MVC设计模式,还采用了Struts、Spring、Hibernate等多种技术,使得系统成为以网络为系统平台,基于B/S结构、具有结构清晰,具有良好的可扩展性、可维护性以及重用性的主题数据库应用系统.     

支持多速率自适应的IEEE 802.11网络性能分析

针对基于自动速率回退(ARF)算法的多速率IEEE 802.11网络,给出了ARF算法分析的一种离散时间Markov链模型.模型的建立,考虑了节点在发送过程中,通过Basic与RTS/CTS模式的选择,对是否因为信道传输误码导致的失败进行的区分.利用算法模型,分析了节点在以随机概率选择不同发送模式的方式下,其采用各个传输速率的稳态概率分布,并在此基础上结合协议退避机制的研究,给出了多速率网络系统吞吐量性能的计算方法.通过大量的仿真实验,验证了模型分析方法具有很好的准确性,并讨论了算法以及MAC协议参数设置对网络性能的影响.     

Synthesis and characterization of layered perovskite-type organic-inorganic hybrids (R-NH3)2(CH3NH3)Pb2I7

Layered organic-inorganic hybrids containing bilayer perovsikte (R-NH3)2(CH3NH3)Pb2I7 (where R=C12H25,C6H5C2H4) were synthesized by reactions in solution. The influences of the solvents and the reactant ratio on the structures of the products were investigated. The structures and the properties of the hybrids were characterized using X-ray diffraction (XRD) and ultraviolet and visible (UV) adsorption spectra. For comparing with the bilayer perovskite hybrids in structure and band gap magnitude, the hybrids containing monolayer perovskite (R-NH3)2PbI4 were also synthesized and characterized. The results demonstrate that the thickness of inorganic layer has obvious effect on the tunneling magnitude of the band gap but the organic part can be micro actuator of band gap.     

取水口泥沙淤积问题及反向闸门的开发

在电厂及水厂等取水工程中，泥砂淤积往往是困扰工程取水质量和处理成本的老大难问题。乌江流域涪陵段某取水泵站采用高位取水方案，提高了取水质量，并结合水力抽砂装置和反冲冼系统很好地解决了井池及整个进水管路泥砂淤积问题。在实施技术改造的过程中，还开发了反向止水钢闸门。     

基于三角不等式原理的TTSAS聚类加速算法

顺序聚类算法是一种非常直接和快速的算法，并且不需要提前确定聚类个数。但是当处理海量数据时，时间效率仍然有待提高。TTSAS算法是两个阈值的顺序聚类算法，在此基础上，该文应用三角不等式原理提出了TI_TTSAS算法，该算法避免了冗余的距离计算，实验结果证明，相对于TTSAS算法，TI_TTSAS在速度上有很大程度的提高，数据规模越大，改进效果越明显。并且聚类效果保持了TTSAS算法的准确性。     

Analysis of the critical heat flux in round vertical tubes under low pressure and flow oscillation conditions. Applications of artificial neural network

Artificial neural networks (ANNs) for predicting critical heat flux (CHF) under low pressure and oscillation conditions have been trained successfully for either natural circulation or forced circulation (FC) in the present study. The input parameters of the ANN are pressure, mean mass flow rate, relative amplitude, inlet subcooling, oscillation period and the ratio of the heated length to the diameter of the tube, L/D. The output is a nondimensionalized factor F, which expresses the relative CHF under oscillation conditions. Based on the trained ANN, the influences of principal parameters on F for FC were analyzed. The parametric trends of the CHF under oscillation obtained by the trained ANN are as follows: the effects of pressure below 500 kPa are complex due to the influence of other parameters. F will increase with increasing mean mass flow rate under any conditions, and will decrease generally with an increase in relative amplitude. F will decrease initially and then increase with increasing inlet subcooling. The influence curves of mean mass flow rate on F will be almost the same when the period is shorter than 5.0 s or longer than 15 s. The influence of L/D will be negligible if L/D>200. It is found that the minimum number of neurons in the hidden layer is a product of the number of neurons in the input layer and in the output layer.     

iButton技术在安防系统中的应用

本文介绍了一种新型的智能化信息载体iButton以及iButton在安防系统上的应用举例，着重介绍了其硬件、软件设计及工作原理。