Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

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.

Image Ratio Features for Facial Expression Recognition Application

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e. g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Hydrogen-Bonding Recognition-Induced Color Change of Gold Nanoparticles for Visual Detection of Melamine in Raw Milk and Infant Formula

The color change induced by triple hydrogen-bonding recognition between melamine and a cyanuric acid derivative grafted on the surface of gold nanoparticles can be used for reliable detection of melamine. Since such a color change can be readily seen by the naked eye, the method enables on-site and real-time detection of melamine in raw milk and infant formula even at a concentration as low as 2.5 ppb without the aid of any advanced instruments.

Colorimetric recognition of the coralyne-poly(dA) interaction using unmodified gold nanoparticle probes, and further detection of coralyne based upon this recognition system

Among the functional nucleic acids studied, adenine-rich nucleic acids have attracted attention due to their critical roles in many biological processes and self-assembly-based nanomaterials, especially deoxyribonucleic acids (abbreviated as poly(dA)). Therefore the ligands binding to poly(dA) might serve as potential therapeutic agents. Coralyne, a kind of planar alkaloid, has been firstly found that it could bind strongly to poly(dA). This work herein reports an approach for visual sensing of the coralyne-poly(dA) interaction. This method was based on the coralyne inducing poly(dA) into the homo-adenine DNA duplex and the difference in electrostatic affinity between single-stranded DNA and double-stranded DNA with gold nanoparticles (GNPs). Furthermore, we applied the recognition process of the interaction between coralyne and poly(dA) into specific coralyne detection with the assistance of certain software (such as Photoshop). A linear response from 0 to 728 nM was obtained for coralyne, and a detection limit of 91 nM was achieved.

Optimal specificity and function for flexible biomolecular recognition

Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.

Adaptive recognition of small molecules by nucleic acid aptamers through a label-free approach

We report a novel label-free method for the investigation of the adaptive recognition of small molecules by nucleic acid aptamers using capillary electrophoresis analysis. Cocaine and argininamide were chosen as model molecules, and the two corresponding DNA aptamers were used. These single-strand DNAs folded into their specific secondary structures, which were mainly responsible for the binding of the target molecules with high affinity and specificity. For molecular recognition, the nucleic acid structures then underwent additional conformational changes, while keeping the target molecules stabilized by intermolecular hydrogen bonds. The intrinsic chemical and physical properties of the target molecules enabled them to act as indicators for adaptive binding. Thus any labeling or modification of the aptamers or target molecules were made obsolete. This label-free method for aptamer-based molecular recognition was also successfully applied to biological fluids and therefore indicates that this approach is a promising tool for bioanalysis.

SERS opens a new way in aptasensor for protein recognition with high sensitivity and selectivity

SERS aptasensors for protein recognition based on Au nanoparticles labeled with aptamers and Raman reporters have been developed, which opens a new way for protein recognition of high sensitivity and selectivity.

CE with electrochemical detection for investigation of label-free recognition of amino acid amides by guanine-rich DNA aptamers

In this work, we report a simple and effective investigation into adaptive interactions between guanine-rich DNA aptamers and amino acid amides by CE with electrochemical (EC) detection. Argininamide (Arm) and tyrosinamide (Tym) were chosen as model molecules. On a copper electrode, Arm generated a good EC signal in 60 mM NaOH at 0.7 V (vs Ag/ AgCl), while Tym. was detected well on a platinum electrode at 1. 3 V in 20 mM phosphate of pH 7.0. Based on their EC properties, the ligands themselves were used as indicators for the adaptive interactions investigated by CE-EC, making any step of labeling and/or modification of aptamers with indicators exempted. Hydrophilic ionic liquid was used as an additive in running buffer of CE to improve the sensitivity of Arm detection, whereas the additive was not used for Tym. detection due to its negative effect. Two guanine-rich DNA aptamers were used for molecular recognition of Arm and Tym. When the aptamers were incubated with ligands, they bound the model molecules with high affinity and specificity, reflected by obvious decreases in the signals of ligands but no changes in those of the control molecules. However, the ligands were hardly affected by the control ssDNAs after incubation. The results revealed the specific recognition of Arm and Tym. by the aptamers.

Aptamer-based label-free method for hemin recognition and DNA assay by capillary electrophoresis with chemiluminescence detection

An aptamer-based label-free approach to hemin recognition and DNA assay using capillary electrophoresis with chemiluminescence detection is introduced here. Two guanine-rich DNA aptamers were used as the recognition element and target DNA, respectively. In the presence of potassium ions, the two aptamers folded into the G-quartet structures, binding hemin with high specificity and affinity. Based on the G-quartet-hemin interactions, the ligand molecule was specifically recognized with a K (d)approximate to 73 nM, and the target DNA could be detected at 0.1 mu M. In phosphate buffer of pH 11.0, hemin catalyzed the H2O2-mediated oxidation of luminol to generate strong chemiluminescence signal; thus the target molecule itself served as an indicator for the molecule-aptamer interaction, which made the labeling and/or modification of aptamers or target molecules unnecessary. This label-free method for molecular recognition and DNA detection is therefore simple, easy, and effective.

Exploring the mechanism of flexible biomolecular recognition with single molecule dynamics

Combining a single-molecule study of protein binding with a coarse grained molecular dynamics model including solvent (water molecules) effects, we find that biomolecular recognition is determined by flexibilities in addition to structures. Our single-molecule study shows that binding of CBD (a fragment of Wiskott-Aldrich syndrome protein) to Cdc42 involves bound and loosely bound states, which can be quantitatively explained in our model as a result of binding with large conformational changes. Our model identified certain key residues for binding consistent with mutational experiments. Our study reveals the role of flexibility and a new scenario of dimeric binding between the monomers: first bind and then fold.

Optimal specificity and function for flexible biomolecular recognition

Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.

Energetic basis of molecular recognition in a DNA aptamer

The thermal stability and ligand binding properties of the L-argininamide-binding DNA aptamer (5'-GATCGAAACGTAGCGCCTTCGATC3') were studied by spectroscopic and calorimetric methods. Differential calorimetric studies showed that the uncomplexed aptamer melted in a two-state reaction with a melting temperature T-m = 50.2 +/- 0.2 degrees C and a folding enthalpy Delta H degrees(fold) = -49.0 +/- 2.1 kcal mol(-1). These values agree with values of T-m = 49.6 degrees C and Delta H degrees(fold) = -51.2 kcal mol(-1) predicted for a simple hairpin structure. Melting of the uncomplexed aptamer was dependent upon salt concentration, but independent of strand concentration. The T of aptamer melting was found to increase as L-argininamide concentrations increased. Analysis of circular dichroism titration data using a single-site binding model resulted in the determination of a binding free energy Delta G degrees(bind) = -5.1 kcal mol(-1). Isothermal titration calorimetry studies revealed an exothermic binding reaction with Delta H degrees(bind) = -8.7 kcal mol(-1). Combination of enthalpy and free energy produce ail unfavorable entropy of -T Delta S degrees = +3.6 kcal mol(-1). A molar heat capacity change of -116 cal mol(-1) K-1 was determined from calorimetric measurements at four temperatures over the range of 15-40 degrees C. Molecular dynamics simulations were used to explore the structures of the unligated and ligated aptamer structures.