日本血吸虫抗体电化学免疫传感器研究

该文研制了一种高灵敏的基于辣根过氧化物酶(HRP)放大的电化学免疫传感器用于日本血吸虫抗体的检测.实验采用夹心法的模式,在电极表面固定了日本血吸虫抗原(SjAg),用以捕获血清中的日本血吸虫抗体(SjAb),然后再与辣根过氧化物酶(HRP)标记的羊抗兔IgG二抗形成免疫复合物.用计时安培法检测HRP酶催化H2O2还原对苯二酚底物产牛的电流,其大小与日本血吸虫抗体(SjAb)浓度在一定范围内成正比.对免疫反应的实验条件如电极表面固定抗原的浓度,HRP酶标二抗的浓度进行了优化.此外,还考察了其它蛋白质对测定结果的影响.结果表明,该方法操作简单,灵敏度高,线性范围宽,检测下限低.     

Molecular Verification of Rule-Based Systems Based on DNA Computation

Various graphic techniques have been developed to analyze structural errors in rule-based systems that utilize inference (propositional) logic rules. Four typical errors in rule-based systems are: redundancy (numerous rule sets resulting in the same conclusion); circularity (a rule leading back to itself); incompleteness (deadends or a rule set conclusion leading to unreachable goals); and inconsistency (rules conflicting with each other). This study presents a new DNA-based computing algorithm mainly based upon Adleman's DNA operations. It can be used to detect such errors. There are three phases to this molecular solution: rule-to-DNA transformation design, solution space generation, and rule verification. We first encode individual rules using relatively short DNA strands, and then generate all possible rule paths by the directed joining of such short strands to form longer strands. We then conduct the verification algorithm to detect errors. The potential of applying this proposed DNA computation algorithm to rule verification is promising given the operational time complexity of O(n*q), in which n denotes the number of fact clauses in the rule base and q is the number of rules with longest inference chain.     

Recursive support vector machines for dimensionality reduction.

The usual dimensionality reduction technique in supervised learning is mainly based on linear discriminant analysis (LDA), but it suffers from singularity or undersampled problems. On the other hand, a regular support vector machine (SVM) separates the data only in terms of one single direction of maximum margin, and the classification accuracy may be not good enough. In this letter, a recursive SVM (RSVM) is presented, in which several orthogonal directions that best separate the data with the maximum margin are obtained. Theoretical analysis shows that a completely orthogonal basis can be derived in feature subspace spanned by the training samples and the margin is decreasing along the recursive components in linearly separable cases. As a result, a new dimensionality reduction technique based on multilevel maximum margin components and then a classifier with high accuracy are achieved. Experiments in synthetic and several real data sets show that RSVM using multilevel maximum margin features can do efficient dimensionality reduction and outperform regular SVM in binary classification problems.     

Single-Item Dynamic Lot-Sizing Models With Bounded Inventory and Outsourcing

This paper addresses a real-life lot-sizing problem which can be considered a single-item dynamic lot-sizing problem with bounded inventory. The particularity is that the demand of a period can be entirely or partially outsourced with an outsourcing cost. The goal is to minimize the total cost of production, setup, inventory holding, and outsourcing. The cost functions are linear but time-varying. We assume that the unit production cost is constant or nonincreasing over time. The problem is shown to be solvable in a strongly polynomial time with a dynamic-programming approach. The proposed algorithm can solve problems of sizes of up to 400 periods in less than 2 ms on a 1.4-GHz Pentium IV processor.     

Effects of shear rate and small periodic corrugation on the slip velocity in microscopic domain

We obtain analytically the slip velocity (up to the second order) of shear-thinning fluids inside the periodically corrugated microtube by using the verified fluid model and boundary perturbation method. Our results show that, even the slip length being zero, there is a slip velocity which is proportional to the small amplitude of periodic corrugation, the (referenced) shear rate, the applied forcing, and the orientation or the angle. Our results could be applied to the flow control in microfluidics as well as biofluidics.     

小型飞行器综合测试系统方案设计

针对小型飞行器系统各部件在研制和生产中的测试要求,提出了小型飞行器综合测试系统的方案设计;方案设计中详细介绍了系统组成,并对方案中涉及的航空电子分系统、发动机分系统、无线电数据链分系统的测试内容及测试方法进行了分析说明;根据测试方法和测试内容,给出了综合测试系统的硬件设计原理和软件设计流程;运用该设计方案进行了综合测试设备发动机分系统测试的研制工作,并投入试运行,结果表明该方案设计合理可行,可推广应用于该领域或其它领域的测控系统的研制中。     

Secretome analysis of novel IgE-binding proteins from Penicillium citrinum

The Penicillium genus of fungi is a frequently reported cause of allergic reactions. However, only a limited number of allergens have been reported. In Penicillium spp., many allergens show higher IgE-binding activity in culture filtrate extracts than in cellular extracts. In order to investigate the IgE-reactive profile of mold-sensitized patients, secreted IgE-reactive proteins from Penicillium citrinum were identified by 2-DE, serum immunoblotting, and nanoLC-MS/MS. Among the IgE-reactive spots, one known allergen, Pen c 13, and four novel allergens were identified. The cDNAs coding for Pen c 32 and Pen c 30 were cloned using designed primers based on nanoLC-MS/MS analysis. The amino acid sequences of Pen c 32 and Pen c 30 were, respectively, found to have extensive similarity with those of pectate lyases and catalases from various fungi. Native Pen c 30 was shown to have catalase activity and to bind to serum IgE from 48% of mold-allergic patients and induced immediate type skin reactions in a sensitized patient. Here, we present a proteome approach which resulted in the identification of four novel secreted allergens. These novel allergens might be useful in allergy diagnosis and in the treatment of mold-allergic disorders.     

An improved closed-loop stability related measure forfinite-precision digital controller realizations

The pole-sensitivity approach is employed to investigate the stability issue of the discrete-time control system, where a digital controller implemented with finite word length (FWL), is used. A stability related measure is derived, which is more accurate in estimating the closed-loop stability robustness of an FWL implemented controller than some existing measures for the pole-sensitivity analysis. This improved stability measure thus provides a better criterion to find the optimal realizations for a generic controller structure that includes output-feedback and observer-based controllers. A numerical example is used to verify the theoretical analysis and to illustrate the design procedure     

The relationship of the bayes risk to certain separability measures in normal classification

For the problem of classifying an element (e.g., an unknown pattern) into one of two given categories where the associated observables are distributed according to one of two known multivariate normal populations having a common covariance matrix, it is shown that the minimum Bayes risk is a strict monotonic function of certain separability or statistical distance measures regardless of the a priori probabilities and the assigned loss function. However, for the associated conditional expected losses, strict monotonicity holds, if and only if a certain condition dependent on these probabilities and the given loss function is satisfied. These results remain valid for classification problems in which the observable can be transformed by a one-to-one differentiable mapping to normality.     

Regularized orthogonal linear discriminant analysis

In this paper the regularized orthogonal linear discriminant analysis (ROLDA) is studied. The major issue of the regularized linear discriminant analysis is to choose an appropriate regularization parameter. In existing regularized linear discriminant analysis methods, they all select the “best” regularization parameter from a given parameter candidate set by using cross-validation for classification. An obvious limitation of such regularized linear discriminant analysis methods is that it is not clear how to choose an appropriate candidate set. Therefore, up to now, there is no concrete mathematical theory available in selecting an appropriate regularization parameter in practical applications of the regularized linear discriminant analysis. The present work is to fill this gap. Here we derive the mathematical relationship between orthogonal linear discriminant analysis and the regularized orthogonal linear discriminant analysis first, and then by means of this relationship we find a mathematical criterion for selecting the regularization parameter in ROLDA and consequently we develop a new regularized orthogonal linear discriminant analysis method, in which no candidate set of regularization parameter is needed. The effectiveness of our proposed regularized orthogonal linear discriminant analysis is illustrated by some real-world data sets.