Data with abnormal trend pattern in a manufacturing process

The data represents a trend in a deteriorating process caused by gradually increasing material variability and deteriorations of operator skills or loosening fixtures.

Data with abnormal cyclic pattern in a manufacturing process

The data represents a cyclic pattern in process variable presented in a control chart due to periodic rotation of operators, seasonal or environmental changes.

Data with abnormal systematic pattern in a manufacturing process

The data represents a systematic pattern in process variable presented in a control chart due to measurement gauge rotation and power fluctuations in manufacturing processes.

Association between abnormal psychosocial situations in childhood, generalised anxiety disorder and oppositional defiant disorder

Objective: Psychosocial stressors are important in the pathogenesis of most mental disorders. However, little is known about the way psychosocial stressors uniquely combine to create risk for different expressions of child and adolescent psychopathology. The purpose of this study was to determine whether core dimensions of stressful psychosocial situations are differentially associated with childhood generalized anxiety disorder and oppositional defi ant disorder.

Method: A case-control design conducted in Trondheim (Norway) from 2002 to 2004 comparing exposure to ICD-10-defi ned abnormal psychosocial situations (Z-codes) among 21 children with oppositional defi ant disorder (ODD) and 22 children with generalized anxiety disorder (GAD) recruited from a university outpatient clinic with 42 non-patient school controls.

Results: Multigroup discriminant analysis extracted two signifi cant dimensions within the psychosocial variables assessed. Function 1 was characterized by overprotection, parental pressures and acute life events and was associated with GAD. Function 2 was characterized by parental abuse/hostility and interpersonal stress and was associated with ODD. Both dimensions were able to correctly classify 89.7% of the cases, compared to 35.9% by chance.

Conclusions: The results indicate that specifi c psychosocial dimensions are differentially related to childhood GAD and ODD. This may be useful in targeting at-risk populations for preventive intervention as well as informing more accurate alignment of psychosocial resources for treatment.

Area-level socioeconomic status and incidence of abnormal glucose metabolism : the Australian diabetes, obesity and lifestyle (AusDiab) study

OBJECTIVE--To examine the role of area-level socioeconomic status (SES) on the development of abnormal glucose metabolism (AGM) using national, population-based data.

RESEARCH DESIGN AND METHODS--The Australian Diabetes, Obesity and Lifestyle (AusDiab) study is a national, population-based, longitudinal study of adults aged [greater than or equal to] 25 years. A sample of 4,572 people provided complete baseline (1999 to 2000) and 5-year follow-up (2004 to 2005) data relevant for these analyses. Incident AGM was assessed using fasting plasma glucose and 2-h plasma glucose from oral glucose tolerance tests, and demographic, socioeconomic, and behavioral data were collected by interview and questionnaire. Area SES was defined using the Index of Relative Socioeconomic Disadvantage. Generalized linear mixed models were used to examine the relationship between area SES and incident AGM, with adjustment for covariates and correction for cluster design effects.

RESULTS--Area SES predicted the development of AGM, after adjustment for age, sex, and individual SES. People living in areas with the most disadvantage were significantly more likely to develop AGM, compared with those living in the least deprived areas (odds ratio 1.53; 95% CI 1.07-2.18). Health behaviors (in particular, physical activity) and central adiposity appeared to partially mediate this relationship.

CONCLUSIONS--Our findings suggest that characteristics of the physical, social, and economic aspects of local areas influence diabetes risk. Future research should focus on identifying the aspects of local environment that are associated with diabetes risk and how they might be modified.

Relationship between Clinical Macular Changes and Retinal Function in Age-Related Macular Degeneration

Purpose

The value of impulsivity to define subgroups of addicted individuals differing in personality dysfunction, craving, psychosocial adjustment, and wellbeing: A latent class analysis

High impulsivity is common to substance and gambling addictions. Despite these commonalities, there is still substantial heterogeneity on impulsivity levels within these diagnostic groups, and variations in impulsive levels predict higher severity of symptoms and poorer outcomes. We addressed the question of whether impulsivity scores can yield empirically driven subgroups of addicted individuals that will exhibit different clinical presentations and outcomes. We applied latent class analysis (LCA) to trait (UPPS-P impulsive behavior scale) and cognitive impulsivity (Stroop and d2 tests) scores in three predominantly male addiction diagnostic groups: Cocaine with Personality Disorders, Cocaine Non-comorbid, and Gambling and analyzed the usefulness of the resulting subgroups to differentiate personality beliefs and relevant outcomes: Craving, psychosocial adjustment, and quality of life. In accordance with impulsivity scores, the three addiction diagnostic groups are best represented as two separate classes: Class 1 characterized by greater trait impulsivity and poorer cognitive impulsivity performance and Class 2 characterized by lower trait impulsivity and better cognitive impulsivity performance. The two empirically derived classes showed significant differences on personality features and outcome variables (Class 1 exhibited greater personality dysfunction and worse clinical outcomes), whereas conventional diagnostic groups showed non-significant differences on most of these measures. Trait and cognitive impulsivity scores differentiate subgroups of addicted individuals with more versus less severe personality features and clinical outcomes.

Is body dysmorphic disorder associated with abnormal bodily self-awareness? A study using the rubber hand illusion.

Evidence from past research suggests that behaviours and characteristics related to body dissatisfaction may be associated with greater instability of perceptual body image, possibly due to problems in the integration of body-related multisensory information. We investigated whether people with body dysmorphic disorder (BDD), a condition characterised by body image disturbances, demonstrated enhanced susceptibility to the rubber hand illusion (RHI), which arises as a result of multisensory integration processes when a rubber hand and the participant's hidden real hand are stimulated in synchrony. Overall, differences in RHI experience between the BDD group and healthy and schizophrenia control groups (n = 17 in each) were not significant. RHI strength, however, was positively associated with body dissatisfaction and related tendencies. For the healthy control group, proprioceptive drift towards the rubber hand was observed following synchronous but not asynchronous stimulation, a typical pattern when inducing the RHI. Similar drifts in proprioceptive awareness occurred for the BDD group irrespective of whether stimulation was synchronous or not. These results are discussed in terms of possible abnormalities in visual processing and multisensory integration among people with BDD.

Abnormal mitochondrial L-arginine transport contributes to the pathogenesis of heart failure and rexoygenation injury

Impaired mitochondrial function is fundamental feature of heart failure (HF) and myocardial ischemia. In addition to the effects of heightened oxidative stress, altered nitric oxide (NO) metabolism, generated by a mitochondrial NO synthase, has also been proposed to impact upon mitochondrial function. However, the mechanism responsible for arginine transport into mitochondria and the effect of HF on such a process is unknown. We therefore aimed to characterize mitochondrial L-arginine transport and to investigate the hypothesis that impaired mitochondrial L-arginine transport plays a key role in the pathogenesis of heart failure and myocardial injury.

Developmental antecedents of abnormal eating attitudes and behaviors in adolescence

Objective This study capitalizes on developmental data from an Australian population-based birth cohort to identify developmental markers of abnormal eating attitudes and behaviors in adolescence. The aims were twofold: (1) to develop a comprehensive path model identifying infant and childhood developmental correlates of Abnormal Eating Attitudes and Behaviors in adolescence, and (2) to explore potential gender differences.

Nonparametric discovery of learning patterns and autism subgroups from therapeutic data

Autism Spectrum Disorder (ASD) is growing at a staggering rate, but, little is known about the cause of this condition. Inferring learning patterns from therapeutic performance data, and subsequently clustering ASD children into subgroups, is important to understand this domain, and more importantly to inform evidence-based intervention. However, this data-driven task was difficult in the past due to insufficiency of data to perform reliable analysis. For the first time, using data from a recent application for early intervention in autism (TOBY Play pad), whose download count is now exceeding 4500, we present in this paper the automatic discovery of learning patterns across 32 skills in sensory, imitation and language. We use unsupervised learning methods for this task, but a notorious problem with existing methods is the correct specification of number of patterns in advance, which in our case is even more difficult due to complexity of the data. To this end, we appeal to recent Bayesian nonparametric methods, in particular the use of Bayesian Nonparametric Factor Analysis. This model uses Indian Buffet Process (IBP) as prior on a binary matrix of infinite columns to allocate groups of intervention skills to children. The optimal number of learning patterns as well as subgroup assignments are inferred automatically from data. Our experimental results follow an exploratory approach, present different newly discovered learning patterns. To provide quantitative results, we also report the clustering evaluation against K-means and Nonnegative matrix factorization (NMF). In addition to the novelty of this new problem, we were able to demonstrate the suitability of Bayesian nonparametric models over parametric rivals.