Geometry vs appearance for discriminating between posed and spontaneous emotions

Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.

Application of higher order spectra to identify epileptic EEG

Epilepsy is characterized by the spontaneous and seemingly unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into this phenomenon. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, we made a comparative study of the performance of Gaussian mixture model (GMM) and Support Vector Machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Results show that the selected HOS based features achieve 93.11% classification accuracy compared to 88.78% with features derived from the power spectrum for a GMM classifier. The SVM classifier achieves an improvement from 86.89% with features based on the power spectrum to 92.56% with features based on the bispectrum.

Psychotic symptom and cannabis relapse in recent-onset sychosis

Background Cannabis use appears to exacerbate psychotic symptoms and increase risk of psychotic relapse. However, the relative contribution of cannabis use compared with other risk factors is unclear. The influence of psychotic symptoms on cannabis use has received little attention. Aims To examine the influence of cannabis use on psychotic symptom relapse and the influence of psychotic symptom severity on relapse in cannabis use in the 6 months following hospital admission. Method At baseline, 84 participants with recent-onset psychosis were assessed and 81 were followed up weekly for 6 months, using telephone and face-to-face interviews. Results A higher frequency of cannabis use was predictive of psychotic relapse, after controlling for medication adherence, other substance use and duration of untreated psychosis. An increase in psychotic symptoms was predictive of relapse to cannabis use, and medication adherence reduced cannabis relapse risk. Conclusions The relationship between cannabis use and psychosis may be bidirectional, highlighting the need for early intervention programmes to target cannabis use and psychotic symptom severity in this population.

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

Effects of Mobile Phone Distraction at the Onset of Amber Light: Analysis of Driving Simulator Data

Distraction whilst driving on an approach to a signalized intersection is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. This study examines the decisions of distracted drivers during the onset of amber lights. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of IOWA - National Advanced Driving Simulator. Explanatory variables include age, gender, cell phone use, distance to stop-line, and speed. An iterative combination of decision tree and logistic regression analyses are employed to identify main effects, non-linearities, and interactions effects. Results show that novice (16-17 years) and younger (18-25 years) drivers’ had heightened amber light running risk while distracted by cell phone, and speed and distance thresholds yielded significant interaction effects. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Solutions are needed to combat the use of mobile phones whilst driving.

Towards spontaneous facial expression recognition in real-world video

Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.

Quantitative studies of lower motor neuron degeneration in amyotrophic lateral sclerosis : Evidence for exponential decay of motor unit numbers and greatest rate of loss at the site of onset

Objective: To use our Bayesian method of motor unit number estimation (MUNE) to evaluate lower motor neuron degeneration in ALS. Methods: In subjects with ALS we performed serial MUNE studies. We examined the repeatability of the test and then determined whether the loss of MUs was fitted by an exponential or Weibull distribution. Results: The decline in motor unit (MU) numbers was well-fitted by an exponential decay curve. We calculated the half life of MUs in the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and/or extensor digitorum brevis (EDB) muscles. The mean half life of the MUs of ADM muscle was greater than those of the APB or EDB muscles. The half-life of MUs was less in the ADM muscle of subjects with upper limb than in those with lower limb onset. Conclusions: The rate of loss of lower motor neurons in ALS is exponential, the motor units of the APB decay more quickly than those of the ADM muscle and the rate of loss of motor units is greater at the site of onset of disease. Significance: This shows that the Bayesian MUNE method is useful in following the course and exploring the clinical features of ALS. 2012 International Federation of Clinical Neurophysiology.

Birth outcomes after spontaneous or assisted conception among infertile Australian women aged 28 to 36 years: A prospective, population-based study

Objective To examine the extent to which the odds of birth, pregnancy, or adverse birth outcomes are higher among women aged 28 to 36 years who use fertility treatment compared with untreated women. Design Prospective, population-based. Setting Not applicable. Patient(s) Participants in the ALSWH born in 1973 to 1978 who reported on their infertility and use of in vitro fertilization (IVF) or ovulation induction (OI). Intervention(s) Postal survey questionnaires administered as part of ALSWH. Main Outcome Measure(s) Among women treated with IVF or OI and untreated women, the odds of birth outcomes estimated by use of adjusted logistic regression modeling. Result(s) Among 7,280 women, 18.6% (n = 1,376) reported infertility. Half (53.0%) of the treated women gave birth compared with 43.8% of untreated women. Women with prior parity were less likely to use IVF compared with nulliparous women. Women using IVF or OI, respectively, were more likely to have given birth after treatment or be pregnant compared with untreated women. Women using IVF or OI were as likely to have ectopic pregnancies, stillbirths, or premature or low birthweight babies as untreated women. Conclusion(s) More than 40% of women aged 28–36 years reporting a history of infertility can achieve births without using treatment, indicating they are subfertile rather than infertile.

A novel DRD2 single-nucleotide polymorphism associated with schizophrenia predicts age of onset : HapMap tag-single-nucleotide polymorphism analysis

Background: Dopamine D2 receptor (DRD2) is thought to be critical in regulating the dopaminergic pathway in the brain which is known to be important in the aetiology of schizophrenia. It is therefore not surprising that most antipsychotic medication acts on the Dopamine D2 receptor. DRD2 is widely expressed in brain, levels are reduced in brains of schizophrenia patients and DRD2 polymorphisms have been associated with reduced brain expression. We have previously identified a genetic variant in DRD2, rs6277 to be strongly implicated in schizophrenia susceptibility. Methods: To identity new associations in the DRD2 gene with disease status and clinical severity, we genotyped seven single nucleotide polymorphisms (SNPs) in DRD2 using a multiplex mass spectrometry method. SNPs were chosen using a haplotype block-based gene-tagging approach so the entire DRD2 gene was represented. Results: One polymorphism rs2734839 was found to be significantly associated with schizophrenia as well as late onset age. Individuals carrying the genetic variation were more than twice as likely to have schizophrenia compared to controls. Conclusions: Our results suggest that DRD2 genetic variation is a good indicator for schizophrenia risk and may also be used as a predictor age of onset.

Spontaneous Volunteering During Natural Disasters

The recent spate of natural disasters across Australia has led to an outpouring of spontaneous volunteering, both formally through nonprofit and government agencies and informally through local community and online networks. Relatively little is understood about the motivations and characteristics of spontaneous volunteers. The aims of this project were to:  Examine the characteristics and motivations of spontaneous volunteers who respond to a crisis event;  Illuminate the effects of spontaneous volunteering on personal, social and civic networks;  Explicate the conditions under which sustained volunteering and other forms of civic engagement arise from spontaneous volunteering and;  Consider the practical implications of these findings for organisations involved in coordinating volunteers both with and beyond disaster events.

Factors associated with common mental disorders during the transition to adulthood : do emerging adults and ‘early starters’ differ? Findings from an Australian birth cohort study

Background: Despite increasing diversity in pathways to adulthood, choices available to young people are influenced by environmental, familial and individual factors, namely access to socioeconomic resources, family support and mental and physical health status. Young people from families with higher socioeconomic position (SEP) are more likely to pursue tertiary education and delay entry to adulthood, whereas those from low socioeconomic backgrounds are less likely to attain higher education or training, and more likely to partner and become parents early. The first group are commonly termed ‘emerging adults’ and the latter group ‘early starters’. Mental health disorders during this transition can seriously disrupt psychological, social and academic development as well as employment prospects. Depression, anxiety and most substance use disorders have early onset during adolescence and early adulthood with approximately three quarters of lifetime psychiatric disorders having emerged by 24 years of age. Aims: This thesis aimed to explore the relationships between mental health, sociodemographic factors and family functioning during the transition to adulthood. Four areas were investigated: 1) The key differences between emerging adults and ‘early starters’, were examined and focused on a series of social, economic, and demographic factors as well as DSM-IV diagnoses; 2) Methodological issues associated with the measurement of depression and anxiety in young adults were explored by comparing a quantitative measure of symptoms of anxiety and depression (Achenbach’s YSR and YASR internalising scales) with DSM-IV diagnosed depression and anxiety. 3) The association between family SEP and DSM-IV depression and anxiety was examined in relation to the different pathways to adulthood. 4) Finally, the association between pregnancy loss, abortion and miscarriage, and DSM-IV diagnoses of common psychiatric disorders was assessed in young women who reported early parenting, experiencing a pregnancy loss, or who had never been pregnant. Methods: Data were taken from the Mater University Study of Pregnancy (MUSP), a large birth cohort started in 1981 in Brisbane, Australia. 7223 mothers and their children were assessed five times, at 6 months, 5, 14 and 21 years after birth. Over 3700 young adults, aged 18 to 23 years, were interviewed at the 21-year phase. Respondents completed an extensive series of self-reported questionnaires and a computerised structured psychiatric interview. Three outcomes were assessed at the 21-year phase. Mental health disorders diagnosed by a computerised structured psychiatric interview (CIDI-Auto), the prevalence of DSM-IV depression, anxiety and substance use disorders within the previous 12-month, during the transition (between ages of 18 and 23 years) or lifetime were examined. The primary outcome “current stage in the transition to adulthood” was developed using a measure conceptually constructed from the literature. The measure was based on important demographic markers, and these defined four independent groups: emerging adults (single with no children and living with parents), and three categories of ‘early starter’, singles (with no children or partner, living independently), those with a partner (married or cohabitating but without children) and parents. Early pregnancy loss was assessed using a measure that also defined four independent groups and was based on pregnancy outcomes in the young women This categorised the young women into those who were never pregnant, women who gave birth to a live child, and women who reported some form of pregnancy loss, either an abortion or a spontaneous miscarriage. A series of analyses were undertaken to test the study aims. Potential confounding and mediating factors were prospectively measured between the child’s birth and the 21-year phase. Binomial and multinomial logistic regression was used to estimate the risk of relevant outcomes, and the associations were reported as odds ratios (OR) and 95% confidence intervals (95%CI). Key findings: The thesis makes a number of important contributions to our understanding of the transition to adulthood, particularly in relation to the mental health consequences associated with different pathways. Firstly, findings from the thesis clearly showed that young people who parented or partnered early fared worse across most of the economic and social factors as well as the common mental disorders when compared to emerging adults. That is, young people who became early parents were also more likely to experience recent anxiety (OR=2.0, 95%CI 1.5-2.8) and depression (OR=1.7, 95%CI 1.1-2.7) than were emerging adults after taking into account a range of confounding factors. Singles and those partnering early also had higher rates of lifetime anxiety and depression than emerging adults. Young people who partnered early, but were without children, had decreased odds of recent depression; this may be due to the protective effect of early marriage against depression. It was also found that young people who form families early had an increased risk of cigarette smoking (parents OR=3.7, 95%CI 2.9-4.8) compared to emerging adults, but not heavy alcohol (parents OR=0.4, 95%CI 0.3-0.6) or recent illicit drug use. The high rates of cigarette smoking and tobacco use disorders in ‘early starters’ were explained by common risk factors related to early adversity and lower SEP. Having a child and early marriage may well function as a ‘turning point’ for some young people, it is not clear whether this is due to a conscious decision to disengage from a previous ‘substance using’ lifestyle or simply that they no longer have the time to devote to such activities because of child caring. In relation to the methodological issues associated with assessing common mental disorders in young adults, it was found that although the Achenbach empirical internalising scales successfully predicted both later DSM-IV depression (YSR OR=2.3, 95%CI 1.7-3.1) and concurrently diagnosed depression (YASR OR=6.9, 95%CI 5.0- 9.5) and anxiety (YASR OR=5.1, 95%CI 3.8- 6.7), the scales discriminated poorly between young people with or without DSM-IV diagnosed mood disorder. Sensitivity values (the proportion of true positives) for the internalising scales were surprisingly low. Only a third of young people with current DSM-IV depression (range for each of the scales was between 34% to 42%) were correctly identified as cases by the YASR internalising scales, and only a quarter with current anxiety disorder (range of 23% to 31%) were correctly identified. Also, use of the DSM-oriented scales increased sensitivity only marginally (for depression between 2-8%, and anxiety between 2-6%) above the standard Achenbach scales. This is despite the fact that the DSM-oriented scales were originally developed to overcome the poor prediction of DSM-IV diagnoses by the Achenbach scales. The internalising scales, both standard and DSM-oriented, were much more effective at identifying young people with comorbid depression and anxiety, with OR’s 10.1 to 21.7 depending on the internalising scale used. SEP is an important predictor of both an early transition to adulthood and the experience of anxiety during that time Family income during adolescence was a strong predictor of early parenting and partnering before age 24 but not early independent living. Compared to families in the upper quintile, young people from families with low income were nearly twice as likely to live with a partner and four times more likely to become parents (OR ranged from 2.6 to 4.0). This association remained after adjusting for current employment and education level. Children raised in low income families were 30% more likely to have an anxiety disorder (OR=1.3, 95%CI 0.9-1.9), but not depression, as young adults when compared to children from wealthier families. Emerging adults and ‘early starters’ from low income families did not differ in their likelihood of having a later anxiety disorder. Young women reporting a pregnancy loss had nearly three times the odds of experiencing a lifetime illicit drug disorder (excluding cannabis) [abortion OR=3.6, 95%CI 2.0-6.7 and miscarriage OR=2.6, 95%CI 1.2-5.4]. Abortion was associated with alcohol use disorder (OR=2.1, 95%CI 1.3- 3.5) and 12-month depression (OR=1.9, 95%CI 1.1- 3.1). These finding suggest that the association identified by Fergusson et al between abortion and later psychiatric disorders in young women may be due to pregnancy loss and not to abortion, per se. Conclusion: Findings from this thesis support the view that young people who parent or partner early have a greater burden of depression and anxiety when compared to emerging adults. As well, young women experiencing pregnancy loss, from either abortion or miscarriage, are more likely to experience depression and anxiety than are those who give birth to a live infant or who have never been pregnant. Depression, anxiety and substance use disorders often go unrecognised and untreated in young people; this is especially true in young people from lower SEP. Early identification of these common mental health disorders is important, as depression and anxiety experienced during the transition to adulthood have been found to seriously disrupt an individual’s social, educational and economic prospects in later life.

What do we know about recovery interventions used in the management of delayed onset muscle soreness?

Since the pioneering work of Hough in 1902 (1) the term ‘delayed onset muscle soreness (DOMS)’ has dominated the field of athletic recovery. DOMS typically occurs after exercise induced muscle damage (EIMD), particularly if the exercise is unaccustomed or involves a large amount of eccentric (muscle lengthening) contractions. The symptoms of EIMD manifest as a temporary reduction in muscle force, disturbed proprioceptive acuity, increases in inflammatory markers both within the injured muscle and in the blood as well as increased muscle soreness, stiffness and swelling. The intensity of discomfort and soreness associated with DOMS increases within the first 24 hours, peaks between 24 and 72 hours, before subsiding and eventually disappearing 5-7 days after the exercise. Consequently, DOMS may interfere with athletic training or competition and several recovery interventions have been utilised by athletes and coaches in an attempt to offset the negative effects...

Hydraulic instability onset detection in Kaplan turbines by monitoring shaft vibrations

Design of hydraulic turbines has often to deal with hydraulic instability. It is well-known that Francis and Kaplan types present hydraulic instability in their design power range. Even if modern CFD tools may help to define these dangerous operating conditions and optimize runner design, hydraulic instabilities may fortuitously arise during the turbine life and should be timely detected in order to assure a long-lasting operating life. In a previous paper, the authors have considered the phenomenon of helical vortex rope, which happens at low flow rates when a swirling flow, in the draft tube conical inlet, occupies a large portion of the inlet. In this condition, a strong helical vortex rope appears. The vortex rope causes mechanical effects on the runner, on the whole turbine and on the draft tube, which may eventually produce severe damages on the turbine unit and whose most evident symptoms are vibrations. The authors have already shown that vibration analysis is suitable for detecting vortex rope onset, thanks to an experimental test campaign performed during the commissioning of a 23 MW Kaplan hydraulic turbine unit. In this paper, the authors propose a sophisticated data driven approach to detect vortex rope onset at different power load, based on the analysis of the vibration signals in the order domain and introducing the so-called "residual order spectrogram", i.e. an order-rotation representation of the vibration signal. Some experimental test runs are presented and the possibility to detect instability onset, especially in real-time, is discussed.

Spatial analysis of community-onset Staphylococcus aureus bacteremia in Queensland, Australia

OBJECTIVES To investigate and describe the relationship between indigenous Australian populations, residential aged care services, and community-onset Staphylococcus aureus bacteremia (SAB) among patients admitted to public hospitals in Queensland, Australia. DESIGN Ecological study. METHODS We used administrative healthcare data linked to microbiology results from patients with SAB admitted to Queensland public hospitals from 2005 through 2010 to identify community-onset infections. Data about indigenous Australian population and residential aged care services at the local government area level were obtained from the Queensland Office of Economic and Statistical Research. Associations between community-onset SAB and indigenous Australian population and residential aged care services were calculated using Poisson regression models in a Bayesian framework. Choropleth maps were used to describe the spatial patterns of SAB risk. RESULTS We observed a 21% increase in relative risk (RR) of bacteremia with methicillin-susceptible S. aureus (MSSA; RR, 1.21 [95% credible interval, 1.15-1.26]) and a 24% increase in RR with nonmultiresistant methicillin-resistant S. aureus (nmMRSA; RR, 1.24 [95% credible interval, 1.13-1.34]) with a 10% increase in the indigenous Australian population proportion. There was no significant association between RR of SAB and the number of residential aged care services. Areas with the highest RR for nmMRSA and MSSA bacteremia were identified in the northern and western regions of Queensland. CONCLUSIONS The RR of community-onset SAB varied spatially across Queensland. There was increased RR of community-onset SAB with nmMRSA and MSSA in areas of Queensland with increased indigenous population proportions. Additional research should be undertaken to understand other factors that increase the risk of infection due to this organism.