用于腺苷检测的基于级联扩增核酸适体电化学传感界面的构建研究

该文报道了一种基于酶级联扩增的电化学核酸适体检测腺苷的新方法。当腺苷存在时,滚环扩增的引物通过E.coli DNA连接酶的作用与通过巯基组装在金电极上的固定探针连接。在pHi29 DNA聚合酶的作用下,滚环扩增反应进行并产生一条与环形探针完全互补的长的单链,然后将大量金纳米粒子标记的核酸探针与滚环扩增的产物杂交。该传感界面电化学行为的结果表明,通过酶级联扩增的方法提高了检测腺苷的阻抗响应灵敏度,且选择性和重现性良好。用于腺苷的检测时,其线性范围为2.0μmol/L~100μmol/L,最低检测浓度为2.0μmol/L,表明该传感界面的设计可作为一种通用方法而有望用于其它目标物的检测。     

《化学传感器:特性、性能和应用》简介

美国Nova科学出版公司自2009年起出版以评介化学各分支领域的进展和应用前景为重点的《化学研究与应用》(Chemical Research and Applications)系列丛书,涵盖了化学的各个分支领域。预计到2012年底共出版125卷。目前已列     

探析数据通信中的多路复用技术及其应用

现代社会科学技术飞速发展,各种技术之间相互依赖、相互促进.计算机和集成电路的出现为整个科技的发展提供了强有力的推进器,而大量计算机之间的交流需要依靠网络的连接,因此网络间的通信传输就显得尤为重要.本文就网络通信中的多路复用技术的主要方法及其应用领域作一简单的介绍.     

浅析网络异常流量分析检测研究与实现

伴随着互联网技术与网络业务的快速发展,网络规模逐渐扩大,网络运用开始逐步朝多元化、多样化以及复杂化的方向发展.现今,网络流量监测已经逐渐发展为计算机网络运用当中一个必不可少的内容与环节.文章将对网络异常流量加以说明,并对网络异常流量检测技术研究与实现进行分析与研究.     

对高校图书馆智能化管理的探究

随着现代信息的蔓延,学校素质教育的全面推进,学校图书馆的地位在不断提高,作用也会逐渐的凸现出来.图书馆是落实素质教育的一个重要阵地,把图书活动作为一个栽体,充分发挥图书馆现有的物质基础,大力开展全校师生的读书活动,形成爱书,读书的良好风尚,使图书馆成为师生最大、最亲近的学习课堂.由此,大力加强和广泛发展高校图书馆的建设,是一项非常重要而迫切的艰巨任务,也是高校图书馆顺应时代发展的必要,这样就要求正确面对管理,加强对图书馆智能化的探究.     

计算机内存的优化及管理浅析

信息总量、网络浏览人数以及人们对网络享受需求的增加,促使着信息制作水平的提高,制作水平的提高在给人们带来了更好的视觉和听觉享受的同时,也对计算机的硬件系统提出了巨大的考验.计算机内存作为计算机硬件系统的重要组成部分,能否对内存做好合理的划分,对计算机的体验具有重要的意义.     

Sampling average approximation method for a class of stochastic Nash equilibrium problems

We consider a class of stochastic Nash equilibrium problems (SNEP). Under some mild conditions, we reformulate the SNEP as a stochastic mixed complementarity problem (SMCP). We apply the well-known sample average approximation (SAA) method to solve the SMCP. We further introduce a semismooth Newton method to solve the SAA problems. The comprehensive convergence analysis is given as well. In addition, we demonstrate the proposed approach on a stochastic Nash equilibrium model in the wholesale gas–oil markets.     

Occlusion cues for image scene layering

To bring computer vision closer to human vision, we attempt to enable computer to understand the occlusion relationship in an image. In this paper, we propose five low dimensional region-based occlusion cues inspired by the human perception of occlusion. These cues are semantic cue, position cue, compactness cue, shared boundary cue and junction cue. We apply these cues to predict the region-wise occlusion relationship in an image and infer the layer sequence of the image scene. A preference function, trained with samples consisting of these cues, is defined to predict the occlusion relationship in an image. Then we put all the occlusion predictions into the layering algorithm to infer the layer sequence of the image scene.The experiments on rural, artificial and outdoor scene datasets show the effectiveness of our method for occlusion relationship prediction and image scene layering.     

Accelerating a Recurrent Neural Network to Finite-Time Convergence for Solving Time-Varying Sylvester Equation by Using a Sign-Bi-power Activation Function

Bartels–Stewart algorithm is an effective and widely used method with an O(n ³) time complexity for solving a static Sylvester equation. When applied to time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. Gradient-based recurrent neural network are able to solve the time-varying Sylvester equation in real time but there always exists an estimation error. In contrast, the recently proposed Zhang neural network has been proven to converge to the solution of the Sylvester equation ideally when time goes to infinity. However, this neural network with the suggested activation functions never converges to the desired value in finite time, which may limit its applications in realtime processing. To tackle this problem, a sign-bi-power activation function is proposed in this paper to accelerate Zhang neural network to finite-time convergence. The global convergence and finite-time convergence property are proven in theory. The upper bound of the convergence time is derived analytically. Simulations are performed to evaluate the performance of the neural network with the proposed activation function. In addition, the proposed strategy is applied to online calculating the pseudo-inverse of a matrix and nonlinear control of an inverted pendulum system. Both theoretical analysis and numerical simulations validate the effectiveness of proposed activation function.     

Treatment of biologically treated leachate by oxidation and coagulation

This work aims to investigate removal efficiency of oxidation and coagulation/flocculation processes, to provide an effective method for the treatment of biologically pre-treated leachate. Leachate containing 985 mg L(-1) COD was treated by using three treatment schemes, i.e. oxidation, coagulation/flocculation and the combined process of coagulation/flocculation followed by oxidation. The application of single oxidation resulted in the effective removal of COD and color up to 80.4 and 83.2%, respectively. However, residual COD values lower than 200 mg L(-1) could only be achieved under intensive experimental conditions (high dosage of Ca(ClO)(2) and prolonged oxidation time). Coagulation/flocculation yielded residual COD values higher than 200 mg L(-1) even at the optimum coagulation conditions. The combined treatment by coagulation/flocculation followed by oxidation yielded final COD lower than 100 mg L(-1) at the following conditions: pre-coagulation with 250 mg L(-1) PFS (poly-ferric sulfate) and over 30-min post-oxidation, or pre-coagulation with 300 mg L(-1) PFS and over 20-min post-oxidation. Hence, pre-coagulation with PFS followed by oxidation with Ca(ClO)(2) was recommended for advanced treatment of biologically treated leachate.