Nanostructured hydroxyapatite surfaces-mediated adsorption alters recognition of BMP receptor IA and bioactivity of bone morphogenetic protein-2

Highly efficient loading of bone morphogenetic protein-2 (BMP-2) onto carriers with desirable performance is still a major challenge in the field of bone regeneration. Till now, the nanoscaled surface-induced changes of the structure and bioactivity of BMP-2 remains poorly understood. Here, the effect of nanoscaled surface on the adsorption and bioactivity of BMP-2 was investigated with a series of hydroxyapatite surfaces (HAPs): HAP crystal-coated surface (HAP), HAP crystal-coated polished surface (HAP-Pol), and sintered HAP crystal-coated surface (HAP-Sin). The adsorption dynamics of recombinant human BMP-2 (rhBMP-2) and the accessibility of the binding epitopes of adsorbed rhBMP-2 for BMP receptors (BMPRs) were examined by a quartz crystal microbalance with dissipation. Moreover, the bioactivity of adsorbed rhBMP-2 and the BMP-induced Smad signaling were investigated with C2C12 model cells. A noticeably high mass-uptake of rhBMP-2 and enhanced recognition of BMPR-IA to adsorbed rhBMP-2 were found on the HAP-Pol surface. For the rhBMP-2-adsorbed HAPs, both ALP activity and Smad signaling increased in the order of HAP-Sin < HAP < HAP-Pol. Furthermore, hybrid molecular dynamics and steered molecular dynamics simulations validated that BMP-2 tightly anchored on the HAP-Pol surface with a relative loosened conformation, but the HAP-Sin surface induced a compact conformation of BMP-2. In conclusion, the nanostructured HAPs can modulate the way of adsorption of rhBMP-2, and thus the recognition of BMPR-IA and the bioactivity of rhBMP-2. These findings can provide insightful suggestions for the future design and fabrication of rhBMP-2-based scaffolds/implants.

Specific IgE recognition of pollen allergens from subtropic grasses in patients from the subtropics

Background Pollens of subtropical grasses, Bahia (Paspalum notatum), Johnson (Sorghum halepense), and Bermuda (Cynodon dactylon), are common causes of respiratory allergies in subtropical regions worldwide. Objective To evaluate IgE cross-reactivity of grass pollen (GP) found in subtropical and temperate areas. Methods Case and control serum samples from 83 individuals from the subtropical region of Queensland were tested for IgE reactivity with GP extracts by enzyme-linked immunosorbent assay. A randomly sampled subset of 21 serum samples from patients with subtropical GP allergy were examined by ImmunoCAP and cross-inhibition assays. Results Fifty-four patients with allergic rhinitis and GP allergy had higher IgE reactivity with P notatum and C dactylon than with a mixture of 5 temperate GPs. For 90% of 21 GP allergic serum samples, P notatum, S halepense, or C dactylon specific IgE concentrations were higher than temperate GP specific IgE, and GP specific IgE had higher correlations of subtropical GP (r = 0.771-0.950) than temperate GP (r = 0.317-0.677). In most patients (71%-100%), IgE with P notatum, S halepense, or C dactylon GPs was inhibited better by subtropical GP than temperate GP. When the temperate GP mixture achieved 50% inhibition of IgE with subtropical GP, there was a 39- to 67-fold difference in concentrations giving 50% inhibition and significant differences in maximum inhibition for S halepense and P notatum GP relative to temperate GP. Conclusion Patients living in a subtropical region had species specific IgE recognition of subtropical GP. Most GP allergic patients in Queensland would benefit from allergen specific immunotherapy with a standardized content of subtropical GP allergens.

Multiview gait biometrics for human identity recognition

We propose a novel multiview fusion scheme for recognizing human identity based on gait biometric data. The gait biometric data is acquired from video surveillance datasets from multiple cameras. Experiments on publicly available CASIA dataset show the potential of proposed scheme based on fusion towards development and implementation of automatic identity recognition systems.

What triggers problem recognition? An exploration on young Australian male problematic online gamers

Help-seeking is a complex decision-making process that first begins with problem recognition. However, little is understood about the conceptualisation of the helpseeking process and the triggers of problem recognition. This research proposes the use of the Critical Incident Technique (CIT) to examine and classify incidents that serve as key triggers of problem recognition among young Australian male problematic online gamers. The research provides a classification of five different types of triggers that will aid social marketers into developing effective early detection, prevention and treatment focused social marketing interventions.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

On robust face recognition via sparse coding: The good, the bad and the ugly

In the field of face recognition, sparse representation (SR) has received considerable attention during the past few years, with a focus on holistic descriptors in closed-set identification applications. The underlying assumption in such SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such an assumption is easily violated in the face verification scenario, where the task is to determine if two faces (where one or both have not been seen before) belong to the same person. In this study, the authors propose an alternative approach to SR-based face verification, where SR encoding is performed on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which then form an overall face descriptor. Owing to the deliberate loss of spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment and various image deformations. Within the proposed framework, they evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN) and an implicit probabilistic technique based on Gaussian mixture models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, on both the traditional closed-set identification task and the more applicable face verification task. The experiments also show that l1-minimisation-based encoding has a considerably higher computational cost when compared with SANN-based and probabilistic encoding, but leads to higher recognition rates.

Robust iris recognition using decision fusion and degradation modelling

This thesis investigates the use of fusion techniques and mathematical modelling to increase the robustness of iris recognition systems against iris image quality degradation, pupil size changes and partial occlusion. The proposed techniques improve recognition accuracy and enhance security. They can be further developed for better iris recognition in less constrained environments that do not require user cooperation. A framework to analyse the consistency of different regions of the iris is also developed. This can be applied to improve recognition systems using partial iris images, and cancelable biometric signatures or biometric based cryptography for privacy protection.

Conceptualising recognition of prior learning processes in the age of open learning

This chapter interrogates what recognition of prior learning (RPL) can and does mean in the higher education sector—a sector in the grip of the widening participation agenda and an open access age. The chapter discusses how open learning is making inroads into recognition processes and examines two studies in open learning recognition. A case study relating to e-portfolio-style RPL for entry into a Graduate Certificate in Policy and Governance at a metropolitan university in Queensland is described. In the first instance, candidates who do not possess a relevant Bachelor degree need to demonstrate skills in governmental policy work in order to be eligible to gain entry to a Graduate Certificate (at Australian Qualifications Framework Level 8) (Australian Qualifications Framework Council, 2013, p. 53). The chapter acknowledges the benefits and limitations of recognition in open learning and those of more traditional RPL, anticipating future developments in both (or their convergence).

Solvent effect in molecular recognition: Determining binding constants in different solvents following an extraction based protocol

Semi-rigid molecular tweezers 1, 3 and 4 bind picric acid with more than tenfold increment in tetrachloromethane as compared to chloroform.

Heterologous promoter recognition leading to high-level expression of cloned foreign genes in Bombyx mori cell lines and larvae

The baculovirus expression system using the Autographa californica nuclear polyhedrosis virus (AcNPV) has been extensively utilized for high-level expression of cloned foreign genes, driven by the strong viral promoters of polyhedrin (polh) and p10 encoding genes. A parallel system using Bombyx mori nuclear polyhedrosis virus (BmNPV) is much less exploited because the choice and variety of BmNPV-based transfer vectors are limited. Using a transient expression assay, we have demonstrated here that the heterologous promoters of the very late genes polh and p10 from AcNPV function as efficiently in BmN cells as the BmNPV promoters. The location of the cloned foreign gene with respect to the promoter sequences was critical for achieving the highest levels of expression, following the order +35 > +1 > -3 > -8 nucleotides (nt) with respect to the polh or p10 start codons. We have successfully generated recombinant BmNPV harboring AcNPV promoters by homeologous recombination between AcNPV-based transfer vectors and BmNPV genomic DNA. Infection of BmN cell lines with recombinant BmNPV showed a temporal expression pattern, reaching very high levels in 60-72 h post infection. The recombinant BmNPV harboring the firefly luciferase-encoding gene under the control of AcNPV polh or p10 promoters, on infection of the silkworm larvae led to the synthesis of large quantities of luciferase. Such larvae emanated significant luminiscence instantaneously on administration of the substrate luciferin resulting in 'glowing silkworms'. The virus-infected larvae continued to glow for several hours and revealed the most abundant distribution of virus in the fat bodies. In larval expression also, the highest levels were achieved when the reporter gene was located at +35 nt of the polh.

A fuzzy multistage evolutionary (FUME) clustering technique

n this paper, a multistage evolutionary scheme is proposed for clustering in a large data base, like speech data. This is achieved by clustering a small subset of the entire sample set in each stage and treating the cluster centroids so obtained as samples, together with another subset of samples not considered previously, as input data to the next stage. This is continued till the whole sample set is exhausted. The clustering is accomplished by constructing a fuzzy similarity matrix and using the fuzzy techniques proposed here. The technique is illustrated by an efficient scheme for voiced-unvoiced-silence classification of speech.

Speech Rhythm in an Interlanguage Perspective : Finnish Adolescents Speaking English

Speech rhythm is an essential part of speech processing. It is the outcome of the workings of a combination of linguistic and non-linguistic parameters, many of which also have other functions in speech. This study focusses on the acoustic and auditive realization of two linguistic parameters of rhythm: (1) sentence stress, and (2) speech rate and pausing. The aim was to find out how well Finnish comprehensive school pupils realize these two parameters in English and how native speakers of English react to Finnish pupils English rhythm. The material was elicited by means of a story-telling task and questionnaires. Three female and three male pupils representing different levels of oral skills in English were selected as the experimental group. The control group consisted of two female and two male native speakers of English. The stories were analysed acoustically and auditorily with respect to interstress intervals, weak forms, fundamental frequency, pausing, and speech as well as articulation rate. In addition, 52 native speakers of English were asked to rate the intelligibility of the Finnish pupils English with respect to speech rhythm and give their attitudes on what the pupils sounded like. Results showed that Finnish pupils can produce isochronous interstress intervals in English, but that too large a proportion of these intervals contain pauses. A closer analysis of the pauses revealed that Finnish pupils pause too frequently and in inappropriate places when they speak English. Frequent pausing was also found to cause slow speech rates. The findings of the fundamental frequency (F0) measurements indicate that Finnish pupils tend to make a slightly narrower F0 difference between stressed and unstressed syllables than the native speakers of English. Furthermore, Finnish pupils appear to know how to reduce the duration and quality of unstressed sounds, but they fail to do it frequently enough. Native listeners gave lower intelligibility and attitude scores to pupils with more anomalous speech rhythm. Finnish pupils rhythm anomalies seemed to derive from various learning- or learner-related factors rather than from the differences between English and Finnish. This study demonstrates that pausing may be a more important component of English speech rhythm than sentence stress as far as Finnish adolescents are concerned and that interlanguage development is affected by various factors and characterised by jumps or periods of stasis. Other theoretical, methodological and pedagogical implications of the results are also discussed.

A Fuzzy Approximation Scheme for Sequential Learning in Pattern Recognition

An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.

Fluorescent labelling of strychnine: A novel approach for recognition of strychnine binding sites on neuronal membrane

trychnine was coupled to fluorescein isothiocyanate to mark strychnine binding sites in spinal cord of rat. Specific binding of strychnine could be demonstrated in synaptosomal fraction. Addition of glycine to the strychninised membrane led to a decrease in fluorescence indicating same receptor loci.

Simplified algorithms based on Haar transforms for signal recognition in protective relays

This letter presents the development of simplified algorithms based on Haar functions for signal extraction in relaying signals. These algorithms, being computationally simple, are better suited for microprocessor-based power system protection relaying. They provide accurate estimates of the signal amplitude and phase.