The Drinking Expectancy Questionnaire for Men who have Sex with Men (DEQ-MSM): A measure of substance-related beliefs

Introduction and Aims. Alcohol expectancies are associated with drinking behaviour and post-drinking use thoughts, feelings and behaviours. The expectancies held by specific cultural or sub-cultural groups have rarely been investigated. This research maps expectancies specific to gay and other men who have sex with men (MSM) and their relationship with substance use. This study describes the specific development of a measure of such beliefs for alcohol, the Drinking Expectancy Questionnaire for Men who have Sex with Men (DEQ-MSM). Design and Methods. Items selected through a focus group and interviews were piloted on 220 self-identified gay or other MSM via an online questionnaire. Results. Factor analysis revealed three distinct substance reinforcement domains ('Cognitive impairment', 'Sexual activity' and 'Social and emotional facilitation'). These factors were associated with consumption patterns of alcohol, and in a crucial test of discriminant validity were not associated with the consumption of cannabis or stimulants. Similarities and differences with existing measures will also be discussed. Discussion and Conclusions. The DEQ-MSM represents a reliable and valid measure of outcome expectancies, related to alcohol use among MSM, and represents an important advance as no known existing alcohol expectancy measure, to date, has been developed and/or normed for use among this group. Future applications of the DEQ-MSM in health promotion, clinical settings and research may contribute to reducing harm associated with alcohol use among MSM, including the development of alcohol use among young gay men.

The rules of autogeddon : sex death and law in J G Ballard’s Crash

It was reported that the manuscript of Crash was returned to the publisher with a note reading ‘The author is beyond psychiatric help’. Ballard took the lay diagnosis as proof of complete artistic success. Crash conflates the Freudian tropes of libido and thanatos, overlaying these onto the twentieth century erotic icon, the car. Beyond mere incompetent adolescent copulatory fumblings in the back seat of the parental sedan or the clichéd phallic locomotor of the mid-life Ferrari, Ballard engages the full potentialities of the automobile as the locus and sine qua non of a perverse, though functional erotic. ‘Autoeroticism’ is transformed into automotive, traumatic or surgical paraphilia, driving Helmut Newton’s insipid photo-essays of BDSM and orthopædics into an entirely new dimension, dancing precisely where (but more crucially, because) the ‘body is bruised to pleasure soul’. The serendipity of quotidian accidental collisions is supplanted, in pursuit of the fetishised object, by contrived (though not simulated) recreations of iconographic celebrity deaths. Penetration remains as a guiding trope of sexuality, but it is confounded by a perversity of focus. Such an obsessive pursuit of this autoerotic-as-reality necessitates the rejection of the law of human sexual regulation, requiring the re-interpretation of what constitutes sex itself by looking beyond or through conventional sexuality into Ballard’s paraphiliac and nightmarish consensual Other. This Other allows for (if not demands) the tangled wreckage of a sportscar to function as a transformative sexual agent, creating, of woman, a being of ‘free and perverse sexuality, releasing within its dying chromium and leaking engine-parts, all the deviant possibilities of her sex’.

Sparse temporal representations for facial expression recognition

In automatic facial expression recognition, an increasing number of techniques had been proposed for in the literature that exploits the temporal nature of facial expressions. As all facial expressions are known to evolve over time, it is crucially important for a classifier to be capable of modelling their dynamics. We establish that the method of sparse representation (SR) classifiers proves to be a suitable candidate for this purpose, and subsequently propose a framework for expression dynamics to be efficiently incorporated into its current formulation. We additionally show that for the SR method to be applied effectively, then a certain threshold on image dimensionality must be enforced (unlike in facial recognition problems). Thirdly, we determined that recognition rates may be significantly influenced by the size of the projection matrix \Phi. To demonstrate these, a battery of experiments had been conducted on the CK+ dataset for the recognition of the seven prototypic expressions - anger, contempt, disgust, fear, happiness, sadness and surprise - and comparisons have been made between the proposed temporal-SR against the static-SR framework and state-of-the-art support vector machine.

i-vector based speaker recognition on short utterances

Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provide a comparison of Joint Factor Analysis (JFA) and i-vector based systems including various compensation techniques; Within-Class Covariance Normalization (WCCN), LDA, Scatter Difference Nuisance Attribute Projection (SDNAP) and Gaussian Probabilistic Linear Discriminant Analysis (GPLDA). Speaker verification performance for utterances with as little as 2 sec of data taken from the NIST Speaker Recognition Evaluations are presented to provide a clearer picture of the current performance characteristics of these techniques in short utterance conditions.

3D ellipsoid fitting for multi-view gait recognition

Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

Gait energy volumes and frontal gait recognition using depth images

Gait energy images (GEIs) and its variants form the basis of many recent appearance-based gait recognition systems. The GEI combines good recognition performance with a simple implementation, though it suffers problems inherent to appearance-based approaches, such as being highly view dependent. In this paper, we extend the concept of the GEI to 3D, to create what we call the gait energy volume, or GEV. A basic GEV implementation is tested on the CMU MoBo database, showing improvements over both the GEI baseline and a fused multi-view GEI approach. We also demonstrate the efficacy of this approach on partial volume reconstructions created from frontal depth images, which can be more practically acquired, for example, in biometric portals implemented with stereo cameras, or other depth acquisition systems. Experiments on frontal depth images are evaluated on an in-house developed database captured using the Microsoft Kinect, and demonstrate the validity of the proposed approach.

Compressive sensing for gait recognition

Compressive Sensing (CS) is a popular signal processing technique, that can exactly reconstruct a signal given a small number of random projections of the original signal, provided that the signal is sufficiently sparse. We demonstrate the applicability of CS in the field of gait recognition as a very effective dimensionality reduction technique, using the gait energy image (GEI) as the feature extraction process. We compare the CS based approach to the principal component analysis (PCA) and show that the proposed method outperforms this baseline, particularly under situations where there are appearance changes in the subject. Applying CS to the gait features also avoids the need to train the models, by using a generalised random projection.

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Automated recognition of drunk driving on highways from video sequences

A new method for the detection of abnormal vehicle trajectories is proposed. It couples optical flow extraction of vehicle velocities with a neural network classifier. Abnormal trajectories are indicative of drunk or sleepy drivers. A single feature of the vehicle, eg., a tail light, is isolated and the optical flow computed only around this feature rather than at each pixel in the image.

Spatial Sciences Student Awards Recognition : News from School of Urban Development, QUT

Summary of Spatial Sciences (Surveying) Student Prize Ceremony were recently held at The Old Government House - QUT Cultural Precinct. This short industry article briefly outlines the 15 student award descriptions and some photos of 2011 recipients and thanks industry sponsors.

Modulation of the Chlamydia trachomatis In vitro transcriptome response by the sex hormones estradiol and progesterone

BACKGROUND:Chlamydia trachomatis is a major cause of sexually transmitted disease in humans. Previous studies in both humans and animal models of chlamydial genital tract infection have suggested that the hormonal status of the genital tract epithelium at the time of exposure can influence the outcome of the chlamydial infection. We performed a whole genome transcriptional profiling study of C. trachomatis infection in ECC-1 cells under progesterone or estradiol treatment.RESULTS:Both hormone treatments caused a significant shift in the sub-set of genes expressed (25% of the transcriptome altered by more than 2-fold). Overall, estradiol treatment resulted in the down-regulation of 151 genes, including those associated with lipid and nucleotide metabolism. Of particular interest was the up-regulation in estradiol-supplemented cultures of six genes (omcB, trpB, cydA, cydB, pyk and yggV), which suggest a stress response similar to that reported previously in other models of chlamydial persistence. We also observed morphological changes consistent with a persistence response. By comparison, progesterone supplementation resulted in a general up-regulation of an energy utilising response.CONCLUSION:Our data shows for the first time, that the treatment of chlamydial host cells with key reproductive hormones such as progesterone and estradiol, results in significantly altered chlamydial gene expression profiles. It is likely that these chlamydial expression patterns are survival responses, evolved by the pathogen to enable it to overcome the host's innate immune response. The induction of chlamydial persistence is probably a key component of this survival response.

Towards condition-invariant sequence-based route recognition

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountainbiking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Substance-related expectancies among men who have sex with men : development of psychometric tools to predict unprotected sexual activity

Significant research has demonstrated direct and indirect associations between substance use and sexual behaviour. Substance use is related to sexual risk-taking and HIV seroconversion among some substance-using MSM. It remains unclear what factors mediate or underlie this relationship, and which substances are associated with greater harm. Substance-related expectancies are hypothesised as potential mechanisms. A conceptual model based on social-cognitive theory was tested, which explores the role of demographic factors, substance use, substance-related expectancies and novelty-seeking personality characteristics in predicting unprotected anal intercourse (UAI) while under the influence, across four commonly used substance types. Phase 1, a qualitative study (N = 20), explored how MSM perceive the effects of substance use on their thoughts, feelings and behaviours, including sexual behaviours. Information was attained through discussion and interviews, resulting in the establishment of key themes. Results indicated MSM experience a wide range of reinforcing aspects associated with substance use. General and specific effects were evident across substance types, and were associated with sexual behaviour and sexual risk-taking. Phase 2 consisted of developing a comprehensive profile of substance-related expectancies for MSM (SEP-MSM) regarding alcohol, cannabis, amyl nitrite and stimulants that possessed sound psychometric properties and was appropriate for use among this group. A cross-sectional questionnaire with 249 participants recruited through gay community networks was used to validate these measures, and involved online data collection, participants rating expectancy items and subsequent factor analysis. Results indicated expectancies can be reliably assessed, and predicted substance use patterns. Phase 3 examined demographic factors, substance use, substance-related expectancies, and novelty-seeking traits among another community sample of MSM (N = 277) throughout Australia, in predicting UAI while under the influence. Using a cross-sectional design, participants were recruited through gay community networks and completed online questionnaires. The SEP-MSM, and associated substance use, predicted UAI. This research extends social-cognitive theory regarding sexual behaviour, and advances understanding of the role of expectancies associated with substance use and sexual risk-taking. Future applications of the SEP-MSM in health promotion, prevention, clinical interventions and research are likely to contribute to reducing harm associated with substance-using MSM (e.g., HIV transmission).