Hypersausage neural networks and its application in face recognition

In this paper, we firstly give the nature of 'hypersausages', study its structure and training of the network, then discuss the nature of it by way of experimenting with ORL face database, and finally, verify its unsurpassable advantages compared with other means.

Single-molecule dynamics reveals cooperative binding-folding in protein recognition

The study of associations between two biomolecules is the key to understanding molecular function and recognition. Molecular function is often thought to be determined by underlying structures. Here, combining a single-molecule study of protein binding with an energy-landscape-inspired microscopic model, we found strong evidence that biomolecular recognition is determined by flexibilities in addition to structures. Our model is based on coarse-grained molecular dynamics on the residue level with the energy function biased toward the native binding structure ( the Go model). With our model, the underlying free-energy landscape of the binding can be explored. There are two distinct conformational states at the free-energy minimum, one with partial folding of CBD itself and significant interface binding of CBD to Cdc42, and the other with native folding of CBD itself and native interface binding of CBD to Cdc42. This shows that the binding process proceeds with a significant interface binding of CBD with Cdc42 first, without a complete folding of CBD itself, and that binding and folding are then coupled to reach the native binding state.

An ancient C-type lectin in Chlamys farreri (CfLec-2) that mediate pathogen recognition and cellular adhesion

C-type lectins are a superfamily of Ca2+ dependent carbohydrate-recognition proteins which play significant diverse roles in nonself-recognition and clearance of invaders. In the present study, a C-type lectin (CfLec-2) from Zhikong scallop Chlamys farreri was selected to investigate its functions in innate immunity. The mRNA expression of CfLec-2 in hemocytes was significantly up-regulated (P < 0.01) after scallops were stimulated by LPS. PGN or beta-glucan, and reached the highest expression level at 12h post-stimulation, which was 72.5-, 23.6- or 43.8-fold compared with blank group, respectively. The recombinant Cflec-2 (designated as rCfLec-2) could bind LPS, PGN, mannan and zymosan in vitro, but it could not bind beta-glucan. Immunofluorescence assay with polyclonal antibody specific for Cflec-2 revealed that CfLec-2 was mainly located in the mantle, kidney and gonad. Furthermore, rCfLec-2 could bind to the surface of scallop hemocytes, and then initiated cellular adhesion and recruited hemocytes to enhance their encapsulation in vitro, and this process could be specifically blocked by anti-rCfLec-2 serum. These results collectively suggested that CfLec-2 from the primitive deuterostome C. farreri could perform two distinct immune functions, pathogen recognition and cellular adhesion synchronously, while these functions were performed by collectins and selectins in vertebrates, respectively. The synchronous functions of pathogen recognition and cellular adhesion performed by CfLec-2 tempted us to suspect that CfLec-2 was an ancient form of C-type lectin, and apparently the differentiation of these two functions mediated by C-type lectins occurred after mollusk in phylogeny. (C) 2010 Elsevier Ltd. All rights reserved.

Pattern Recognition With Weighted Complex Networks

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.

The application of DBF neural networks for object recognition

On the basis of DBF nets proposed by Wang Shoujue, the model and properties of DBF neural network were discussed in this paper. When applied in pattern recognition, the algorithm and implement on hardware were presented respectively. We did experiments on recognition of omnidirectionally oriented rigid objects on the same level, using direction basis function neural networks, which acts by the method of covering the high dimensional geometrical distribution of the sample set in the feature space. Many animal and vehicle models (even with rather similar shapes) were recognized omnidirectionally thousands of times. For total 8800 tests, the correct recognition rate is 98.75%, the error rate and the rejection rate are 0.5% and 1.25% respectively. (C) 2003 Elsevier Inc. All rights reserved.

Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

crossmodal error correction of continuous handwriting recognition by speech

In recognition-based user interface, users’ satisfaction is determined not only by recognition accuracy but also by effort to correct recognition errors. In this paper, we introduce a crossmodal error correction technique, which allows users to correct errors of Chinese handwriting recognition by speech. The focus of the paper is a multimodal fusion algorithm supporting the crossmodal error correction. By fusing handwriting and speech recognition, the algorithm can correct errors in both character extraction and recognition of handwriting. The experimental result indicates that the algorithm is effective and efficient. Moreover, the evaluation also shows the correction technique can help users to correct errors in handwriting recognition more efficiently than the other two error correction techniques.

Footwear for Gender Recognition

Conventionally, biometrics resources, such as face, gait silhouette, footprint, and pressure, have been utilized in gender recognition systems. However, the acquisition and processing time of these biometrics data makes the analysis difficult. This letter demonstrates for the first time how effective the footwear appearance is for gender recognition as a biometrics resource. A footwear database is also established with reprehensive shoes (footwears). Preliminary experimental results suggest that footwear appearance is a promising resource for gender recognition. Moreover, it also has the potential to be used jointly with other developed biometrics resources to boost performance.

Thia-michael addition reactions in water using 3-[Bis(alkylthio) methylene]pentane-2,4-diones as odorless and efficient thiol equivalents

3-[Bis(ethylthio)methylene]pentane-2,4-dione (1a) and 3-[bis(benzylthio)methylene]pentane-2,4-dione (1b) have been investigated as non-thiolic and odorless thiol equivalents in thia-Michael addition reactions. In the presence of aqueous p-dodecyl benzenesulfonic acid (DBSA), compound (1) was cleaved and the generated thiols underwent facile conjugate addition to alpha,beta-unsaturated ketones 2 in-situ, affording the corresponding beta-keto sulfides (3) in good yields.

Genome-wide survey of putative serine/threonine protein kinases in cyanobacteria

Background: Serine/threonine kinases (STKs) have been found in an increasing number of prokaryotes, showing important roles in signal transduction that supplement the well known role of two-component system. Cyanobacteria are photoautotrophic prokaryotes able to grow in a wide range of ecological environments, and their signal transduction systems are important in adaptation to the environment. Sequence information from several cyanobacterial genomes offers a unique opportunity to conduct a comprehensive comparative analysis of this kinase family. In this study, we extracted information regarding Ser/Thr kinases from 21 species of sequenced cyanobacteria and investigated their diversity, conservation, domain structure, and evolution. Results: 286 putative STK homologues were identified. STKs are absent in four Prochlorococcus strains and one marine Synechococcus strain and abundant in filamentous nitrogen-fixing cyanobacteria. Motifs and invariant amino acids typical in eukaryotic STKs were conserved well in these proteins, and six more cyanobacteria- or bacteria-specific conserved residues were found. These STK proteins were classified into three major families according to their domain structures. Fourteen types and a total of 131 additional domains were identified, some of which are reported to participate in the recognition of signals or substrates. Cyanobacterial STKs show rather complicated phylogenetic relationships that correspond poorly with phylogenies based on 16S rRNA and those based on additional domains. Conclusion: The number of STK genes in different cyanobacteria is the result of the genome size, ecophysiology, and physiological properties of the organism. Similar conserved motifs and amino acids indicate that cyanobacterial STKs make use of a similar catalytic mechanism as eukaryotic STKs. Gene gain-and-loss is significant during STK evolution, along with domain shuffling and insertion. This study has established an overall framework of sequence-structure-function interactions for the STK gene family, which may facilitate further studies of the role of STKs in various organisms.

Genome-wide survey of putative serine/threonine protein kinases in cyanobacteria

Background: Serine/threonine kinases (STKs) have been found in an increasing number of prokaryotes, showing important roles in signal transduction that supplement the well known role of two-component system. Cyanobacteria are photoautotrophic prokaryotes able to grow in a wide range of ecological environments, and their signal transduction systems are important in adaptation to the environment. Sequence information from several cyanobacterial genomes offers a unique opportunity to conduct a comprehensive comparative analysis of this kinase family. In this study, we extracted information regarding Ser/Thr kinases from 21 species of sequenced cyanobacteria and investigated their diversity, conservation, domain structure, and evolution. Results: 286 putative STK homologues were identified. STKs are absent in four Prochlorococcus strains and one marine Synechococcus strain and abundant in filamentous nitrogen-fixing cyanobacteria. Motifs and invariant amino acids typical in eukaryotic STKs were conserved well in these proteins, and six more cyanobacteria- or bacteria-specific conserved residues were found. These STK proteins were classified into three major families according to their domain structures. Fourteen types and a total of 131 additional domains were identified, some of which are reported to participate in the recognition of signals or substrates. Cyanobacterial STKs show rather complicated phylogenetic relationships that correspond poorly with phylogenies based on 16S rRNA and those based on additional domains. Conclusion: The number of STK genes in different cyanobacteria is the result of the genome size, ecophysiology, and physiological properties of the organism. Similar conserved motifs and amino acids indicate that cyanobacterial STKs make use of a similar catalytic mechanism as eukaryotic STKs. Gene gain-and-loss is significant during STK evolution, along with domain shuffling and insertion. This study has established an overall framework of sequence-structure-function interactions for the STK gene family, which may facilitate further studies of the role of STKs in various organisms.

Screening of genes expressed in vivo after infection by Vibrio anguillarum M3

Aims: Genes uniquely expressed in vivo may contribute to the overall pathogenicity of an organism and are likely to serve as potential targets for the development of new vaccine. This study aims to screen the genes expressed in vivo after Vibrio anguillarum infection by in vivo-induced antigen technology (IVIAT). Methods and Results: The convalescent-phase sera were obtained from turbot (Scophthalmus maximus) survived after infection by the virulent V. anguillarum M3. The pooled sera were thoroughly adsorbed with M3 cells and Escherichia coli BL21 (DE3) cells. A genomic expression library of M3 was constructed and screened for the identification of immunogenic proteins by colony immunoblot analysis with the adsorbed sera. After three rounds of screening, 19 putative in vivo-induced (ivi) genes were obtained. These ivi genes were catalogued into four functional groups: regulator/signalling, metabolism, biological process and hypothetical proteins. Three ivi genes were insertion-mutated, and the growth and 50% lethal dose (LD50) of these mutants were evaluated. Conclusions: The identification of ivi genes in V. anguillarum M3 sheds light on understanding the bacterial pathogenesis and provides novel targets for the development of new vaccines and diagnostic reagents. Significance and Impact of the Study: To the best of our knowledge, this is the first report describing in vivo-expressed genes of V. anguillarum using IVIAT. The screened ivi genes in this study could be new virulent factors and targets for the development of vaccine, which may have implications for the development of diagnostic regents.

Screening of genes expressed in vivo after infection by Vibrio anguillarum M3

Aims: Genes uniquely expressed in vivo may contribute to the overall pathogenicity of an organism and are likely to serve as potential targets for the development of new vaccine. This study aims to screen the genes expressed in vivo after Vibrio anguillarum infection by in vivo-induced antigen technology (IVIAT). Methods and Results: The convalescent-phase sera were obtained from turbot (Scophthalmus maximus) survived after infection by the virulent V. anguillarum M3. The pooled sera were thoroughly adsorbed with M3 cells and Escherichia coli BL21 (DE3) cells. A genomic expression library of M3 was constructed and screened for the identification of immunogenic proteins by colony immunoblot analysis with the adsorbed sera. After three rounds of screening, 19 putative in vivo-induced (ivi) genes were obtained. These ivi genes were catalogued into four functional groups: regulator/signalling, metabolism, biological process and hypothetical proteins. Three ivi genes were insertion-mutated, and the growth and 50% lethal dose (LD50) of these mutants were evaluated. Conclusions: The identification of ivi genes in V. anguillarum M3 sheds light on understanding the bacterial pathogenesis and provides novel targets for the development of new vaccines and diagnostic reagents. Significance and Impact of the Study: To the best of our knowledge, this is the first report describing in vivo-expressed genes of V. anguillarum using IVIAT. The screened ivi genes in this study could be new virulent factors and targets for the development of vaccine, which may have implications for the development of diagnostic regents.