A novel invariant and sequence comparison for DNA

We consider numerical characterization of DNA primary sequence based on the positions of bases (a, t, c, g) and the pairs of bases X, Y in DNA (X, Y=a, t, c, g). This leads to a representation of DNA by a numerical sequence. Then, we extract a novel invariant (molecular connectivity index) from the derived numerical sequences. The suitable invariant can offer a characterization of DNA primary sequence. Finally, we provide an illustration of its utility by making a comparison between ten DNA sequences belonging to beta-globin gene in different species. The evolutionary relationships of ten species we have revealed in this contribution accord with phylogenetic tree properly.

Amplification of antigen-antibody interactions based on biotin labeled protein-streptavidin network complex using impedance spectroscopy

Antibody was covalently immobilized by amine coupling method to gold surfaces modified with a self-assembled monolayer of thioctic acid. The electrochemical measurements of cyclic voltammetry and impedance spectroscopy showed that the hexacyanoferrate redox reactions on the gold surface were blocked due to the procedures of self-assembly of thioctic acid and antibody immobilization. The binding of a specific antigen to antibody recognition layer could be detected by measurements of the impedance change. A new amplification strategy was introduced for improving the sensitivity of impedance measurements using biotin labeled protein- streptavidin network complex. This amplification strategy is based on the construction of a molecular complex between streptavidin and biotin labeled protein. This complex can be formed in a cross-linking network of molecules so that the amplification of response signal will be realized due to the big molecular size of complex. The results show that this amplification strategy causes dramatic improvement of the detection sensitivity of hIgG and has good correlation for detection of hIgG in the range of 2-10 mug/ml. (C) 2001 Elsevier Science B.V. All rights reserved.

Molecular cloning, characterization and expression analysis of a putative C-type lectin (Fclectin) gene in Chinese shrimp Fenneropenaeus chinensis

Lectin is regarded as a potential molecule involved in immune recognition and phagocytosis through opsonization in crustacean. Knowledge on lectin at molecular level would help us to understand its regulation mechanism in crustacean immune system. A novel C-type lectin gene (Fclectin) was cloned from hemocytes of Chinese shrimp Fenneropenaeus chinensis by 3' and 5' rapid amplification of cDNA ends (RACE) PCR. The full-length cDNA consists of 1482 bp with an 861 bp open reading frame, encoding 287 amino acids. The deduced amino acid sequence contains a putative signal peptide of 19 amino acids. It also contains two carbohydrate recognition domains/C-type lectin-like domains (CRD1 and CRD2), which share 78% identity with each other. CRD1 and CRD2 showed 34% and 30% identity with that of mannose-binding lectin from Japanese lamprey (Lethenteron japonicum), respectively. Both CRD1 and CRD2 of Fclectin have I I amino acids residues, which are relatively invariant in animals' C-type lectin CRDs. Five residues at Ca2+ binding site I are conserved in Fclectin. The potential Ca2+/carbohydrate-binding (site 2) motif QPD, E, NP (Gln-Pro-Asp, Glu, Asn-Pro) presented in the two CRDs of Fclectin may support its ability to bind galactose-type sugars. It could be deduced that Fclectin is a member of C-type lectin superfamily. Transcripts of Fclectin were found only in hemocytes by Northern blotting and RNA in situ hybridization. The variation of mRNA transcription level in hemocytes during artificial infection with bacteria and white spot syndrome virus (WSSV) was quantitated by capillary electrophoresis after RT-PCR. An exploration of mRNA expression variation after LPS stimulation was carried out in primarily cultured hemocytes in vitro. Expression profiles of Fclectin gene were greatly modified after bacteria, LPS or WSSV challenge. The above-stated data can provide us clues to understand the probable role of C-type lectin in innate immunity of shrimp and would be helpful to shrimp disease control. (c) 2006 Elsevier Ltd. All rights reserved.

AiC1qDC-1, a novel gC1q-domain-containing protein from bay scallop Argopecten irradians with fungi agglutinating activity

The globular C1q-domain-containing (C1qDC) proteins are a family of versatile pattern recognition receptors via their globular C1q (gC1q) domain to bind various ligands including several PAMPs on pathogens. In this study, a new gC1q-domain-containing protein (AiC1qDC-1) gene was cloned from Argopecten irradians by rapid amplification of cDNA ends (RACE) approaches and expressed sequence tag (EST) analysis. The full-length cDNA of AiC1qDC-1 was composed of 733 bp, encoding a signal peptide of 19 residues and a typical gC1q domain of 137 residues containing all eight invariant amino acids in human C1qDC proteins and seven aromatic residues essential for effective packing of the hydrophobic core of AiC1qDC-1. The gC1q domain of AiC1qDC-1, which possessed the typical 10-stranded beta-sandwich fold with a jelly-roll topology common to all C1q family members, showed high homology not only to those of Cl qDC proteins in mollusk but also to those of C1qDC proteins in human. The AiC1qDC-1 transcripts were mainly detected in the tissue of hepatopancreas and also marginally detectable in adductor, heart, mantle, gill and hemocytes by fluorescent quantitative real-time PCR. In the microbial challenge experiment, there was a significant up-regulation in the relative expression level of AiC1qDC-1 in hepatopancreas and hemocytes of the scallops challenged by fungi Pichia pastoris GS115, Gram-positive bacteria Micrococcus luteus and Gram-negative bacteria Listonella anguillarum. The recombinant AiC1qDC-1 (rAiC1qDC-1) protein displayed no obvious agglutination against M. luteus and L. anguillarum, but it aggregated P. pastoris remarkably. This agglutination could be inhibited by D-mannose and PGN but not by LPS, glucan or D-galactose. These results indicated that AiC1qDC-1 functioned as a pattern recognition receptor in the immune defense of scallops against pathogens and provided clues for illuminating the evolution of the complement classical pathway. (C) 2010 Elsevier Ltd. All rights reserved.

Sensitive and Rapid Detection of Genetic Modified Soybean (Roundup Ready) by Loop-Mediated Isothermal Amplification

Using the LAMP method, a highly specific and sensitive detection system for genetically modified soybean (Roundup Ready) was designed. In this detection system, a set of four primers was designed by targeting the exogenous 35S epsps gene. Target DNA was amplified and visualized on agarose gel within 45 min under isothermal conditions at 65 degrees C. Without gel electrophoresis, the LAMP amplicon was visualized directly in the reaction tube by the addition of SYBR Green I for naked-eye inspection. The detection sensitivity of LAMP was 10-fold higher than the nested PCR established in our laboratory. Moreover, the LAMP method was much quicker, taking only 70 min, as compared with 300 min for nested PCR to complete the analysis of the GM soybean. Compared with traditional PCR approaches, the LAMP procedure is faster and more sensitive, and there is no need for a special PCR machine or electrophoresis equipment. Hence, this method can be a very useful tool for GMO detection and is particularly convenient for fast screening.

Object Recognition By Alignment Using Invariant Projections of Planar Surfaces

In order to recognize an object in an image, we must determine the best transformation from object model to the image. In this paper, we show that for features from coplanar surfaces which undergo linear transformations in space, there exist projections invariant to the surface motions up to rotations in the image field. To use this property, we propose a new alignment approach to object recognition based on centroid alignment of corresponding feature groups. This method uses only a single pair of 2D model and data. Experimental results show the robustness of the proposed method against perturbations of feature positions.

Pose-Invariant Face Recognition Using Real and Virtual Views

The problem of automatic face recognition is to visually identify a person in an input image. This task is performed by matching the input face against the faces of known people in a database of faces. Most existing work in face recognition has limited the scope of the problem, however, by dealing primarily with frontal views, neutral expressions, and fixed lighting conditions. To help generalize existing face recognition systems, we look at the problem of recognizing faces under a range of viewpoints. In particular, we consider two cases of this problem: (i) many example views are available of each person, and (ii) only one view is available per person, perhaps a driver's license or passport photograph. Ideally, we would like to address these two cases using a simple view-based approach, where a person is represented in the database by using a number of views on the viewing sphere. While the view-based approach is consistent with case (i), for case (ii) we need to augment the single real view of each person with synthetic views from other viewpoints, views we call 'virtual views'. Virtual views are generated using prior knowledge of face rotation, knowledge that is 'learned' from images of prototype faces. This prior knowledge is used to effectively rotate in depth the single real view available of each person. In this thesis, I present the view-based face recognizer, techniques for synthesizing virtual views, and experimental results using real and virtual views in the recognizer.

Evaluation of TFTP DDoS Amplification Attack.

Web threats are becoming a major issue for both governments and companies. Generally, web threats increased as much as 600% during last year (WebSense, 2013). This appears to be a significant issue, since many major businesses seem to provide these services. Denial of Service (DoS) attacks are one of the most significant web threats and generally their aim is to waste the resources of the target machine (Mirkovic & Reiher, 2004). Dis-tributed Denial of Service (DDoS) attacks are typically executed from many sources and can result in large traf-fic flows. During last year 11% of DDoS attacks were over 60 Gbps (Prolexic, 2013a). The DDoS attacks are usually performed from the large botnets, which are networks of remotely controlled computers. There is an increasing effort by governments and companies to shut down the botnets (Dittrich, 2012), which has lead the attackers to look for alternative DDoS attack methods. One of the techniques to which attackers are returning to is DDoS amplification attacks. Amplification attacks use intermediate devices called amplifiers in order to amplify the attacker's traffic. This work outlines an evaluation tool and evaluates an amplification attack based on the Trivial File Transfer Proto-col (TFTP). This attack could have amplification factor of approximately 60, which rates highly alongside other researched amplification attacks. This could be a substantial issue globally, due to the fact this protocol is used in approximately 599,600 publicly open TFTP servers. Mitigation methods to this threat have also been consid-ered and a variety of countermeasures are proposed. Effects of this attack on both amplifier and target were analysed based on the proposed metrics. While it has been reported that the breaching of TFTP would be possible (Schultz, 2013), this paper provides a complete methodology for the setup of the attack, and its verification.

An Invariant Representation for Matching Trajectories across Uncalibrated Video Streams

We introduce a view-point invariant representation of moving object trajectories that can be used in video database applications. It is assumed that trajectories lie on a surface that can be locally approximated with a plane. Raw trajectory data is first locally approximated with a cubic spline via least squares fitting. For each sampled point of the obtained curve, a projective invariant feature is computed using a small number of points in its neighborhood. The resulting sequence of invariant features computed along the entire trajectory forms the view invariant descriptor of the trajectory itself. Time parametrization has been exploited to compute cross ratios without ambiguity due to point ordering. Similarity between descriptors of different trajectories is measured with a distance that takes into account the statistical properties of the cross ratio, and its symmetry with respect to the point at infinity. In experiments, an overall correct classification rate of about 95% has been obtained on a dataset of 58 trajectories of players in soccer video, and an overall correct classification rate of about 80% has been obtained on matching partial segments of trajectories collected from two overlapping views of outdoor scenes with moving people and cars.

View-Invariant Object Category Learning, Recognition, and Search: How Spatial and Object Attention Are Coordinated Using Surface-Based Attentional Shrouds

Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624)

Variable Rate Working Memories for Phonetic Categorization and Invariant Speech Perception

Speech can be understood at widely varying production rates. A working memory is described for short-term storage of temporal lists of input items. The working memory is a cooperative-competitive neural network that automatically adjusts its integration rate, or gain, to generate a short-term memory code for a list that is independent of item presentation rate. Such an invariant working memory model is used to simulate data of Repp (1980) concerning the changes of phonetic category boundaries as a function of their presentation rate. Thus the variability of categorical boundaries can be traced to the temporal in variance of the working memory code.

A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).

Orientational Harmonic Model for Rotation, Translation, and Scale Invariant Pattern Representation in Biological Vision

An extension to the orientational harmonic model is presented as a rotation, translation, and scale invariant representation of geometrical form in biological vision.

Orientational Harmonic Model for Rotation, Translation, and Scale Invariant Pattern Representation in Biological Vision

The proposed model, called the combinatorial and competitive spatio-temporal memory or CCSTM, provides an elegant solution to the general problem of having to store and recall spatio-temporal patterns in which states or sequences of states can recur in various contexts. For example, fig. 1 shows two state sequences that have a common subsequence, C and D. The CCSTM assumes that any state has a distributed representation as a collection of features. Each feature has an associated competitive module (CM) containing K cells. On any given occurrence of a particular feature, A, exactly one of the cells in CMA will be chosen to represent it. It is the particular set of cells active on the previous time step that determines which cells are chosen to represent instances of their associated features on the current time step. If we assume that typically S features are active in any state then any state has K^S different neural representations. This huge space of possible neural representations of any state is what underlies the model's ability to store and recall numerous context-sensitive state sequences. The purpose of this paper is simply to describe this mechanism.