Site-directed mutagenesis of recombinant human beta 2-glycoprotein I identifies a cluster of lysine residues that are critical for phospholipid binding and anti-cardiolipin antibody activity

beta2-Glycoprotein I (beta2GPI) is a phospholipid-binding serum protein with anticoagulant properties. It plays a vital role in the binding of anti-cardiolipin Abs purified from patients with autoimmune disease when assayed in a cardiolipin (CL) ELISA. Based on a three-dimensional model of beta2GPI, electrostatic calculations, and earlier peptide studies, a highly positively charged amino acid sequence, Lys282-Asn-Lys-Glu-Lys-Lys287, located in the fifth domain of beta2GPI, has been predicted to be the phospholipid binding site. We tested this hypothesis by site-directed mutagenesis of residues in the predicted phospholipid binding site and by assessing the mutants for phospholipid binding and anti-beta2GPI activity. A single amino acid change from Lys286 to Glu significantly decreased the binding of beta2GPI to CL. Double and triple mutants 2k (from Lys286, 287 to Glu286, 287), 2ka (from Lys284, 287 to Glu284, 287), and 3k (from Lys284, 286, 287 to Glu284, 286, 287) possessed no binding of Ab to beta2GPI in a CL ELISA, as well as no inhibitory activity on the binding of iodinated native beta2GPI to CL. These results indicate that the residues Lys284, Lys286, and Lys287 in the fifth domain of beta2GPI are critical for its binding to anionic phospholipids and its subsequent capture for binding of anti-beta2GPI Abs.     

A robust estimation approach for uncertain systems with perturbed measurements

This paper deals with state estimation problem for uncertain continuous‐time systems. A numerical treatment is proposed for designing interval observers that ensures guaranteed upper and lower bounds on the estimated states. In order to take into account possible perturbations on the system and its outputs, a new type of interval observers is introduced. Such interval observers consist of two coupled general Luenberger‐type observers that involve dilatation functions. In addition, we provide an optimality criterion in order to find optimal interval observers that lead to tight interval error estimation. The proposed existence and optimality conditions are expressed in terms of linear programming. Also, some illustrative examples are given. Copyright © 2015 John Wiley & Sons, Ltd.     

Virtual-water content of agricultural production and food trade balance of Tunisia

This article is devoted to the assessment of Tunisian agricultural production and food trade balance water-equivalent. A linear regression model relating annual rainfall to crop yields is developed to estimate the agricultural production water-equivalent. Its implementation is based on national data for crop and animal production, leading to food demand water-equivalent quantification. Results highlight the relationship between agricultural and water policies and provide a picture of food security in the country in relation to local agricultural production, and to virtual water fluxes related to foodstuffs trade balance.     

An integrated semantic-based approach in concept based video retrieval

Multimedia content has been growing quickly and video retrieval is regarded as one of the most famous issues in multimedia research. In order to retrieve a desirable video, users express their needs in terms of queries. Queries can be on object, motion, texture, color, audio, etc. Low-level representations of video are different from the higher level concepts which a user associates with video. Therefore, query based on semantics is more realistic and tangible for end user. Comprehending the semantics of query has opened a new insight in video retrieval and bridging the semantic gap. However, the problem is that the video needs to be manually annotated in order to support queries expressed in terms of semantic concepts. Annotating semantic concepts which appear in video shots is a challenging and time-consuming task. Moreover, it is not possible to provide annotation for every concept in the real world. In this study, an integrated semantic-based approach for similarity computation is proposed with respect to enhance the retrieval effectiveness in concept-based video retrieval. The proposed method is based on the integration of knowledge-based and corpus-based semantic word similarity measures in order to retrieve video shots for concepts whose annotations are not available for the system. The TRECVID 2005 dataset is used for evaluation purpose, and the results of applying proposed method are then compared against the individual knowledge-based and corpus-based semantic word similarity measures which were utilized in previous studies in the same domain. The superiority of integrated similarity method is shown and evaluated in terms of Mean Average Precision (MAP).     

Application of the cross entropy method to the GLVQ algorithm

This paper discusses an alternative approach to parameter optimization of well-known prototype-based learning algorithms (minimizing an objective function via gradient search). The proposed approach considers a stochastic optimization called the cross entropy method (CE method). The CE method is used to tackle efficiently the initialization sensitiveness problem associated with the original generalized learning vector quantization (GLVQ) algorithm and its variants. Results presented in this paper indicate that the CE method can be successfully applied to this kind of problem on real-world data sets. As far as known by the authors, it is the first use of the CE method in prototype-based learning.     

信息处理用维语词汇标注标记集的确定

介绍了研究和制定信息处理用维语标注标记集的研究进展。讨论了研究与制订“维语标注标记集”必要性,说明了只靠语法角度提出的词汇一级“维语标注标记集”的有限性,论述国内外英语、汉语层次分析研究的最新成果,结合维语的本身特点研究维语语义分类体系迫切性,给出了“维语标注标记集”的工作思路、标记集制定的原则和语法语义词汇一级词性标记集的内容,比较了标记集两个版本的特点,展望了其发展。     

Evaluating Six Sigma failure rate for inverse Gaussian cycle times

Six Sigma is a quality philosophy and methodology that aims to achieve operational excellence and delighted customers. The cost of poor quality depends on the sigma quality level and its corresponding failure rate. Six Sigma provides a well-defined target of 3.4 defects per million. This failure rate is commonly evaluated under the assumption that the process is normally distributed and its specifications are two-sided. However, these assumptions may lead to implementation of quality-improvement strategies that are based on inaccurate evaluations of quality costs and profits. This paper defines the relationship between failure rate and sigma quality level for inverse Gaussian processes. The inverse Gaussian distribution has considerable applications in describing cycle times, product life, employee service times, and so on. We show that for these processes attaining Six Sigma target failure rate requires higher quality efforts than for normal processes. A generic model is presented to characterise cycle times in manufacturing systems. In this model, the asymptotic production is described by a drifted Brownian motion, and the cycle time is evaluated by using the first passage time theory of a Wiener process to a boundary. The proposed method estimates the right efforts required to reach Six Sigma goals.     

Region-based surveillance video retrieval with effective object representation

Retrieving the most relevant video frames that contain the object specified in a given query (query-by-region) remains a challenging task. Two common challenges of region-based retrieval approaches are to accurately extract or segment object(s) and select a proper matching strategy. This paper addresses these problems by proposing a retrieval approach that uses a new region-based matching technique equipped with an effective object representation method. In the first stage, the proposed approach selects the most informative instances of each object that appeared in the video by utilizing an adapted clustering algorithm over the extracted features. In the retrieval stage, the new matching technique returns the most relevant sequences of video by mapping a given region with those identified representative instances of objects based on their similarity scores. The proposed approach is evaluated on standard datasets and the results demonstrate a 31% improvement in the retrieval performance compared to other state-of-the-art methods.     

Visualization and clustering of categorical data with probabilistic self-organizing map

This paper introduces a self-organizing map dedicated to clustering, analysis and visualization of categorical data. Usually, when dealing with categorical data, topological maps use an encoding stage: categorical data are changed into numerical vectors and traditional numerical algorithms (SOM) are run. In the present paper, we propose a novel probabilistic formalism of Kohonen map dedicated to categorical data where neurons are represented by probability tables. We do not need to use any coding to encode variables. We evaluate the effectiveness of our model in four examples using real data. Our experiments show that our model provides a good quality of results when dealing with categorical data.