框架技术与设计模式在网上购物系统中的应用

框架技术和设计模式是设计可复用面向对象软件的基础,是对在特定场景下解决一般设计问题的类和相互通信的对象的描述,两者的组合应用在实际的软件设计中能够发挥更大的威力.目前大多数网上购物系统是基于两层体系结构来进行设计开发,存在效率低下、可维护性差等问题,为改善这种状况,从网上购物系统的需求出发,通过引入框架技术与设计模式,构建了一个具有较强的可重用性和可扩展性的系统.     

聚(N-异丙基丙烯酰胺)水凝胶微控阀的制备与性能

以毛细管(0.5 mm内径)为反应器,通过自由基聚合的方法合成了聚(N-异丙基丙烯酰胺)(PNIPAAm)水凝胶.在自制的毛细管系统中分别测定了盐浓度、pH值、有机溶剂体积分数以及压力对PNIPAAm水凝胶的响应时间和相转变温度值的影响.结果表明:乙酸铵溶液浓度在0.05 mol/L以下、磷酸二氢钠溶液的pH值在3~11范围内、乙醇溶液的体积分数在5%以下和流体静压力低于1.96 kPa时,PNIPAAm水凝胶的响应时间及相转变温度值变化不大,该水凝胶可作为微流控系统中的微阀直接使用.     

基于嵌入式Linux的渔探系统

针对渔探仪发展的现状,提出了一种基于嵌入式Linux的渔探仪系统.该系统将图形用户界面构建在嵌入式Linux和嵌入式GUI库之上,具有视窗风格,界面美观,用户操作方便.GUI库的引入在很大程度上提高了开发效率.多进程的设计保证了系统的响应速度,同时通过软件结构和软件算法上的优化,提高了系统性能.     

甲基丙烯酸叔丁酯的原子转移自由基聚合

分别以对氯甲基苯乙烯和α-溴代丙酸乙酯为引发剂,联二吡啶和N,N,N′,N″,N″-五甲基二亚乙基三胺为配位剂,在氯化亚铜的催化作用下,使甲基丙烯酸叔丁酯(tBMA)进行本体聚合.用凝胶渗透色谱跟踪聚合物的相对分子质量变化,发现不同引发剂与配位剂对聚合反应速率有明显的影响.根据体系中的ln([cM0]/[cM])变化与聚合反应时间成线形的关系,证明tBMA的聚合过程在实验范围内符合原子转移自由基聚合(ATRP)反应规律.利用ATRP的反应特点,改变引发剂与单体tBMA的配比,可将聚甲基丙烯酸叔丁酯(PtBMA)的相对分子质量控制在所需范围内,并保持PtBMA的相对分子质量分布≤1.2;同时用核磁共振氢谱对产物的结构进行表征,结果表明所得聚合物PtBMA的结构明确.     

pH响应性聚乙二醇-co-聚丙烯酸交联微球的合成

在N,N′-亚甲基二丙烯酰胺(Bis)存在的条件下,以偶氮二异丁腈(AIBN)为引发剂,使苯乙烯单封端聚乙二醇(St-PEG)大分子单体与丙烯酸(AAc)在3-戊酮溶液中进行分散共聚反应,得到了聚乙二醇-co-聚丙烯酸(PEG-co-PAAc)交联微球.动态激光光散射测试结果表明,所得的交联微球具有良好的单分散性;同时发现,在共聚反应中St-PEG大分子单体、AAc和Bis溶液浓度对交联微球粒径有明显的影响;交联微球的Rh在pH为4.5附近突然增加,并在pH>7.0后保持不变,说明该PEG-co-PAAc交联微球具有明显的pH响应性.     

磷、铁营养盐的协同交互作用对赤潮隐藻(Crytomonas sp.)生长增殖的影响

通过设计磷、铁双因子六水平二重复的随机试验,初步探讨了协同交互作用对赤潮隐藻生长增殖的影响.结果表明,磷、铁交互作用(P×Fe)极显著,隐藻合适生长铁浓度范围为50 n mol/L~1μmol/L,隐藻生长的培养液最优组合为50μmol/L磷×50 nmol/L铁浓度和10μmol/L磷×1 000 nmol/L铁.     

Crystallization kinetics of （Ni0.75 Fe0.25）78-xNbxSi10B12 （ x = 0, 5 ） amorphous alloys

Amorphous ribbons of （Ni0.75 Fe0.25 ） 78- x Nbx Silo B12 （x = 0, 5 ） were prepared by a single roller melt-spinning technique in air atmosphere. The crystallization kinetics of the alloys were investigated by means of continuous heating, and the activation energies of the alloys were calculated using Kissinger plot method and Ozawa plot method on the basis of differential thermal analysis data.     

中国戏曲中的美——昆曲的艺术魅力及昆曲的传承与革新

以昆曲的艺术魅力为主线就昆曲的传承与革新问题提出几点思考。昆曲是我国一种古老的戏曲剧种,它的剧目丰富,曲调婉转,表演优美动人,是中国古典戏曲的代表。在“流行”已逐渐成为人们审美定势和思维习惯的现今社会,昆曲在中国传统文化轨道中将如何生存和健康地发展,是摆在戏曲界的一个问题。     

Liquid Flow in Shaped Fiber Bundle

By computation and comparison of the critical spreading coefficient parameter, it was found that shaped fiber bundle is better for wetting. Liquid-air interface tension of liquid arising the shaped fiber bundle body is considered as one critical factor besides liquid viscosity, inertia force and liquid-fiber interface tension. Experimental result simulation demonstrated that the liquid-air interface tension is correlated with the geometric size of the liquid arising in body, Φ0 （x） and which is affected by the cross sectional shape of fiber and the radius of single fiber. The shaped fiber bundle model is/ntroduced to/nvestigate liquid flow in fiber assembly. The model is generated based on a random function for stochastic forming of fibers in bundle and it is necessary to combine this fundamental model with physical explanation for investigation of liquid flow in fiber assembly.     

Combined Density-based and Constraint-based Algorithm for Clustering

We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm （CDC）. CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules.Due to the merged clusters around the center cluster, the clustering results show high accu racy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm （GCA）proposed in 2004. Experimental results show that CDC has better performance.