Thermal stability and hot-stage Raman spectroscopic study of Ca-montmorillonite modified with different surfactants : a comparative study

Three long chain cationic surfactants were intercalated into Ca-montmorillonite through ion exchangeand the obtained organoclays were characterized by X-ray diffraction (XRD), high resolution thermo-gravimetric analysis (TG) and Raman spectroscopy. The intercalation of surfactants not only changes thesurface properties of clay from hydrophilic to hydrophobic but also greatly increases the basal spacing ofthe interlayers based on XRD analysis. The thermal stability of organoclays intercalated with three sur-factants (TTAB, DTAB and CTAB) and the different arrangements of the surfactant molecules intercalatedinto Ca-montmorillonite were determined by TG-DTG analysis. A Raman spectroscopic study on the Ca-montmorillonite modified by three surfactants prepared at different concentrations provided the detailedconformational ordering of different intercalated long-chain surfactants under different conditions. Thewavenumber of the antisymmetric stretching mode is more sensitive than that of the symmetric stretch-ing mode to the mobility of the tail of the amine chain. At room temperature, the conformational orderingis more easily affected by the packing density in the lateral model. With the increase of the temperature,the positions of both the antisymmetric and symmetric stretching bands shift to higher wavenumbers,which indicates a decrease of conformational ordering. This study offers new insights into the struc-ture and properties of Ca-montmorillonite modified with different long chain surfactants. Moreover, theexperimental results confirm the potential applications of organic Ca-montmorillonites for the removalof organic impurities from aqueous media.

Inside the pleasure dome : cultural tourism on Australia’s Gold Coast

In 2018 the City of the Gold Coast in south-east Queensland, Australia, will host the next Commonwealth Games. The City is made up a 57 km stretch of coastline and hinterland divided by a major highway. The famous surfing beaches are framed by high-rise development while the hinterland is marketed as a green, unspoilt environment. The winning bid for the Games, and discussion about future infrastructure and marketing of the region’s attributes, has focussed attention on the way City residents and policy makers think about their region in broad terms. Whereas in the past tourism marketing has been directed towards the pleasures of sun and surf by day and bright lights by night, various regional tourist stakeholders are beginning to reorient their programs. This paper considers some of the competing aims of the various stakeholders in this region and the interaction of existing ‘cultures’ with new technology and the demands of permanent residents, using data from a case study of e-literary trails developed in Brisbane, the capital city of Queensland. The importance of tourist imaginaries as a basis for using rich accounts of the past for future planning is emphasized.

Physical activity and health-related quality of life among physiotherapists : a cross sectional survey in an Australian hospital and health service

Background Physiotherapists are a professional group with a high rate of attrition and at high risk of musculoskeletal disorders. The purpose of this investigation was to examine the physical activity levels and health-related quality of life of physiotherapists working in metropolitan clinical settings in an Australian hospital and health service. It was hypothesized that practicing physiotherapists would report excellent health-related quality of life and would already be physically active. Such a finding would add weight to a claim that general physical activity conditioning strategies may not be useful for preventing musculoskeletal disorders among active healthy physiotherapists, but rather, future investigations should focus on the development and evaluation of role specific conditioning strategies. Methods A questionnaire was completed by 44 physiotherapists from three inpatient units and three ambulatory clinics (63.7% response rate). Physical activity levels were reported using the Active Australia Survey. Health-related quality of life was examined using the EQ-5D instrument. Physical activity and EQ-5D data were examined using conventional descriptive statistics; with domain responses for the EQ-5D presented in a frequency histogram. Results The majority of physiotherapists in this sample were younger than 30 years of age (n = 25, 56.8%) consistent with the presence of a high attrition rate. Almost all respondents exceeded minimum recommended physical activity guidelines (n = 40, 90.9%). Overall the respondents engaged in more vigorous physical activity (median = 180 minutes) and walking (median = 135 minutes) than moderate exercise (median = 35 minutes) each week. Thirty-seven (84.1%) participants reported no pain or discomfort impacting their health-related quality of life, with most (n = 35,79.5%) being in full health. Conclusions Physical-conditioning based interventions for the prevention of musculoskeletal disorders among practicing physiotherapists may be better targeted to role or task specific conditioning rather than general physical conditioning among this physically active population. It is plausible that an inherent attrition of physiotherapists may occur among those not as active or healthy as therapists who cope with the physical demands of clinical practice. Extrapolation of findings from this study may be limited due to the sample characteristics. However, this investigation addressed the study objectives and has provided a foundation for larger scale longitudinal investigations in this field.

Quality based frame selection for face clustering in news video

Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Capturing complex, non-linear team behaviours during competitive football performance

This study investigated changes in the complexity (magnitude and structure of variability) of the collective behaviours of association football teams during competitive performance. Raw positional data from an entire competitive match between two professional teams were obtained with the ProZone® tracking system. Five compound positional variables were used to investigate the collective patterns of performance of each team including: surface area, stretch index, team length, team width, and geometrical centre. Analyses involve the coefficient of variation (%CV) and approximate entropy (ApEn), as well as the linear association between both parameters. Collective measures successfully captured the idiosyncratic behaviours of each team and their variations across the six time periods of the match. Key events such as goals scored and game breaks (such as half time and full time) seemed to influence the collective patterns of performance. While ApEn values significantly decreased during each half, the %CV increased. Teams seem to become more regular and predictable, but with increased magnitudes of variation in their organisational shape over the natural course of a match.

Cell image classification using histograms, higher order statistics and adaboost

A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.

Real-time image classification for adaptive mission planning using an Autonomous Underwater Vehicle

Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

Mechanical tension as a driver of connective tissue growth in vitro

We propose the progressive mechanical expansion of cell-derived tissue analogues as a novel, growth-based approach to in vitro tissue engineering. The prevailing approach to producing tissue in vitro is to culture cells in an exogenous “scaffold” that provides a basic structure and mechanical support. This necessarily pre-defines the final size of the implantable material, and specific signals must be provided to stimulate appropriate cell growth, differentiation and matrix formation. In contrast, surgical skin expansion, driven by increments of stretch, produces increasing quantities of tissue without trauma or inflammation. This suggests that connective tissue cells have the innate ability to produce growth in response to elevated tension. We posit that this capacity is maintained in vitro, and that order-of-magnitude growth may be similarly attained in self-assembling cultures of cells and their own extracellular matrix. The hypothesis that growth of connective tissue analogues can be induced by mechanical expansion in vitro may be divided into three components: (1) tension stimulates cell proliferation and extracellular matrix synthesis; (2) the corresponding volume increase will relax the tension imparted by a fixed displacement; (3) the repeated application of static stretch will produce sustained growth and a tissue structure adapted to the tensile loading. Connective tissues exist in a state of residual tension, which is actively maintained by resident cells such as fibroblasts. Studies in vitro and in vivo have demonstrated that cellular survival, reproduction, and matrix synthesis and degradation are regulated by the mechanical environment. Order-of-magnitude increases in both bone and skin volume have been achieved clinically through staged expansion protocols, demonstrating that tension-driven growth can be sustained over prolonged periods. Furthermore, cell-derived tissue analogues have demonstrated mechanically advantageous structural adaptation in response to applied loading. Together, these data suggest that a program of incremental stretch constitutes an appealing way to replicate tissue growth in cell culture, by harnessing the constituent cells’ innate mechanical responsiveness. In addition to offering a platform to study the growth and structural adaptation of connective tissues, tension-driven growth presents a novel approach to in vitro tissue engineering. Because the supporting structure is secreted and organised by the cells themselves, growth is not restricted by a “scaffold” of fixed size. This also minimises potential adverse reactions to exogenous materials upon implantation. Most importantly, we posit that the growth induced by progressive stretch will allow substantial volumes of connective tissue to be produced from relatively small initial cell numbers.

Estimating hidden message length in binary image embedded by using boundary pixels steganography

In this paper, we propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Generalized azimuthal shear deformations in compressible isotropic elastic materials

In this article we study the azimuthal shear deformations in a compressible Isotropic elastic material. This class of deformations involves an azimuthal displacement as a function of the radial and axial coordinates. The equilibrium equations are formulated in terms of the Cauchy-Green strain tensors, which form an overdetermined system of partial differential equations for which solutions do not exist in general. By means of a Legendre transformation, necessary and sufficient conditions for the material to support this deformation are obtained explicitly, in the sense that every solution to the azimuthal equilibrium equation will satisfy the remaining two equations. Additionally, we show how these conditions are sufficient to support all currently known deformations that locally reduce to simple shear. These conditions are then expressed both in terms of the invariants of the Cauchy-Green strain and stretch tensors. Several classes of strain energy functions for which this deformation can be supported are studied. For certain boundary conditions, exact solutions to the equilibrium equations are obtained. © 2005 Society for Industrial and Applied Mathematics.

The complete mitochondrial genome of Spilonota lechriaspis Meyrick (Lepidoptera: Tortricidae)

We determined the nucleotide sequence of the mitochondrial genome (mtgenome) of Spilonota lechriaspis Meyrick (Lepidoptera: Tortricidae). The entire closed circular molecule is 15,368 bp and contains 37 genes with the typical gene complement and order for lepidopteran mtgenomes. All tRNAs except tRNASer(AGN) can be folded into the typical cloverleaf secondary structures. The protein-coding genes (PCGs) have typical mitochondrial start codons, with the exception of COI, which uses the unusual CGA one as is found in all other Lepidoptera sequenced to date. In addition, six of 13 PCGs harbor the incomplete termination codons, a single T. The A+T-rich region contains some conserved structures that are similar to those found in other lepidopteran mtgenomes, including a structure combining the motif 'ATAGA', a 19-bp poly(T) stretch and three microsatellite (AT)n elements which are part of larger 122+ bp macrorepeats. This is the first report of macrorepeats in a lepidopteran mtgenome.

Predicting movie ratings from audience behaviors

We propose a method of representing audience behavior through facial and body motions from a single video stream, and use these features to predict the rating for feature-length movies. This is a very challenging problem as: i) the movie viewing environment is dark and contains views of people at different scales and viewpoints; ii) the duration of feature-length movies is long (80-120 mins) so tracking people uninterrupted for this length of time is still an unsolved problem, and; iii) expressions and motions of audience members are subtle, short and sparse making labeling of activities unreliable. To circumvent these issues, we use an infrared illuminated test-bed to obtain a visually uniform input. We then utilize motion-history features which capture the subtle movements of a person within a pre-defined volume, and then form a group representation of the audience by a histogram of pair-wise correlations over a small-window of time. Using this group representation, we learn our movie rating classifier from crowd-sourced ratings collected by rottentomatoes.com and show our prediction capability on audiences from 30 movies across 250 subjects (> 50 hrs).