An exonuclease-assisted amplification electrochemical aptasensor of thrombin coupling “signal on/off” strategy

In this work, a dual-signaling electrochemical aptasensor based on exonuclease-catalyzed target recycling was developed for thrombin detection. The proposed aptasensor coupled “signal-on” and “signal-off” strategies. As to the construction of the aptasensor, ferrocene (Fc) labeled thrombin binding aptamer (TBA) could perfectly hybridize with the methylene blue (MB) modified thiolated capture DNA to form double-stranded structure, hence emerged two different electrochemical signals. In the presence of thrombin, TBA could form a G-quadruplex structure with thrombin, leading to the dissociation of TBA from the duplex DNA and capture DNA formed hairpin structure. Exonuclease could selectively digest single-stranded TBA in G-quadruplex structure and released thrombin to realize target recycling. As a consequence, the electrochemical signal of MB enhanced significantly, which realized “signal on” strategy, meanwhile, the deoxidization peak current of Fc decreased distinctly, which realized “signal off” strategy. The employment of exonuclease and superposition of two signals significantly improved the sensitivity of the aptasensor. In this way, an aptasensor with high sensitivity, good stability and selectivity for quantitative detection of thrombin was constructed, which exhibited a good linear range from 5 pM to 50 nM with a detection limit of 0.9 pM (defined as S/N = 3). In addition, this design strategy could be applied to the detection of other proteins and small molecules.     

The primary target model of energetic ions penetration in thin botanic samples

The ion transmission spectra of very low current MeV H⁺ ions through two kinds of botanic samples, kidney bean slices and onion endocuticle, were carried out. The experimental spectra confirmed the botanic sample is inhomogeneous in mass density. A target model with local density approximation was suggested to describe the penetration of the energetic ions in such kind of materials. From the fitting of proton transmission spectra of two-energies, this target model was verified primarily. Including the influence of surface roughness and irradiation damage, this target model could be improved to predict the profile of penetration depth and range distribution of the energetic ions in the botanic samples.     

一种基于知识模型的红外目标检测方法

针对电厂冷却塔这类具有特殊建筑规范的典型目标,在分析目标红外特性与形状特性的基础上,提出了一种基于知识模型的红外目标检测方法.首先根据冷却塔目标的红外特性,提取图像的亮度、方向和局部熵特征,采用视觉注意模型提取红外图像中的显著区域,作为待检测目标的感兴趣区域;在此基础上,根据冷却塔目标的形状特性建立双曲线形状模型,在感兴趣区内进行结构特征边缘提取和形状模型拟合,构建相关判定准则检测出目标.在一组机载前视红外图像上的实验结果表明,该方法可以达到98.67％的查全率和93.97％的查准率,具有较好的目标检测效果.由于本文方法不需要基准图的参与,降低了对数据保障的要求,因此具有较大的实用性.     

Manufacturing performance measurement and target setting: A data envelopment analysis approach

Manufacturing decision makers have to deal with a large number of reports and metrics for evaluating the performance of manufacturing systems. Since the metrics provide different and at times conflicting assessments, it is hard for the manufacturing decision makers to track and improve overall manufacturing system performance. This research presents a data envelopment analysis (DEA) based approach for performance measurement and target setting of manufacturing systems. The approach is applied to two different manufacturing environments. The performance peer groups identified using DEA are utilized to set performance targets and to guide performance improvement efforts. The DEA scores are checked against past process modifications that led to identified performance changes. Limitations of the DEA based approach are presented when considering measures that are influenced by factors outside of the control of the manufacturing decision makers. The potential of a DEA based generic performance measurement approach for manufacturing systems is provided.     

Rapid analysis of multicomponent pesticide mixture by GC-MS with the aid of chemometric resolution

Applications of hyphenated chromatographic techniques, especially GC-MS technique, have been reported in chemical, biological, environmental, agricultural and medical analysis. The complexity of the samples in these fields is still an obstacle for the technique to be practical and the overlapping of the multicomponent signals induces chemometric methods widely employed. In this work, taking the rapid analysis of pesticide mixture as an example, a chemometric approach was proposed for resolution of multicomponent overlapping GC-MS signal. In the method, a mass spectral library of pesticides was organized at first, then target factor analysis (TFA) was employed for testing the existence of a specific pesticide in the multicomponent overlapping GC-MS signal, and finally the chromatographic information of the pesticide was extracted by a non-negative immune algorithm (IA). A GC-MS signal of a 40-component pesticide mixture eluted within 9 min was analyzed by the method. It was found that the mass spectra and chromatographic profiles of almost all the pesticides can be obtained.     

Gas chromatography coupled to high-resolution time-of-flight mass spectrometry to analyze trace-level organic compounds in the environment, food safety and toxicology

Gas chromatography coupled to high-resolution time-of flight mass spectrometry (GC-HR-TOF-MS) is a powerful analytical technique with excellent capabilities due to its high sensitivity in full-spectrum-acquisition mode together with its resolving power and accurate-mass measurements. These features make this technique very attractive in qualitative analysis, especially for wide-scope screening of a large number of organic contaminants and residues at trace levels.Full-spectrum MS allows data processing, in principle, of an unlimited number of compounds in samples, as no analyte-specific information is required before the injection. Also, as all data remain available, retrospective analysis is always possible without the need to reinject the sample - an important advantage of full-spectrum MS techniques. Despite these advantages, GC-HR-TOF-MS has rarely been applied, so we expect promising results in different applied fields in the years ahead.We discuss in detail the characteristics and the potential of GC-HR-TOF-MS. We describe different analytical strategies from wide-scope target screening to investigation of unknowns in biology, the environment and food safety. Recent instrumental developments (e.g., high-speed analog-to-digital converter or soft ionization sources) and advances in software for processing the huge amount of data available open up new prospects, making GC-TOF-MS one of the most promising techniques to investigate the presence of organic compounds in different fields.     

Multiwavelength Spectrophotometric Determination of Acid Dissociation Constants. Deconvolution of Binary Mixtures of Ionizable Compounds

ABSTRACT

A spectral deconvolution method based on target factor analysis has been developed to determine pK_a values of binary mixtures of monoprotic and/or diprotic ionizable compounds. The technique makes use of the approach of Frans and Harris, which has been implemented previously for mixtures of monoprotic compounds (Anal. Chem. 1985, 57, 1718-1721), to extract the unknown pK_a values. The method has been illustrated by using the multiwavelength spectrophotometrictitation data of binary mixtures of: I. benzoic acid and phenol, 2. benzoic acid and nicotinic acid, 3. p-aminosalicylic acid and phthalic acid. It was demonstrated that the pK_a values as determined in this study are in good agreement with the literature.     

多层防御模式下武器目标分配决策的群体智能优化算法

武器目标分配(WTA)是军事运筹学中经典的NP完全问题,迄今为止未找到求精确解的多项式时间算法.针对武器数量、布防空间、运行维护成本以及人力资源等多约束下的多层防御WTA问题,采用粒子群优化(PSO)和蚁群优化(ACO)两种群体智能算法求解.给出了PSO和ACO算法实现方案,通过一个算例评估两个算法的性能.结果表明,两种算法都能给出高质量的近似最优解,对求解WTA问题是有效的.PSO在解的质量、算法鲁棒性和计算效率方面均优于ACO.     

Incorporating performance measures with target levels in data envelopment analysis

Data envelopment analysis (DEA) is a technique for evaluating relative efficiencies of peer decision making units (DMUs) which have multiple performance measures. These performance measures have to be classified as either inputs or outputs in DEA. DEA assumes that higher output levels and/or lower input levels indicate better performance. This study is motivated by the fact that there are performance measures (or factors) that cannot be classified as an input or output, because they have target levels with which all DMUs strive to achieve in order to attain the best practice, and any deviations from the target levels are not desirable and may indicate inefficiency. We show how such performance measures with target levels can be incorporated in DEA. We formulate a new production possibility set by extending the standard DEA production possibility set under variable returns-to-scale assumption based on a set of axiomatic properties postulated to suit the case of targeted factors. We develop three efficiency measures by extending the standard radial, slacks-based, and Nerlove–Luenberger measures. We illustrate the proposed model and efficiency measures by applying them to the efficiency evaluation of 36 US universities.     

Volatility Targeting Using Delayed Diffusions

ABSTRACT

A target volatility strategy (TVS) is a risky asset-riskless bond dynamic portfolio allocation which makes use of the risky asset historical volatility as an allocation rule with the aim of maintaining the instantaneous volatility of the investment constant at a target level. In a market with stochastic volatility, we consider a diffusion model for the value of a target volatility fund (TVF) which employs a system of stochastic delayed differential equations (SDDEs) involving the asset realized variance. First we prove that under some technical assumptions, contingent claim valuation on a TVF is approximately of Black-Scholes type, which is consistent with and supports the standing market practice. In second place, we develop a computational framework using recent results on Markovian approximations of SDDEs systems, which we then implement in the Heston variance model using an ad hoc Euler scheme. Our framework allows for efficient numerical valuation of derivatives on TVFs, whose typical purpose is the assessment of the guarantee costs of such funds for insurers.