Associating Facial Expressions and Upper-Body Gestures with Learning Tasks for Enhancing Intelligent Tutoring Systems

Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of learner’s nonverbal behaviors involving hand-over-face gestures, head and eye movements and emotions via facial expressions during learning. The proposed computer vision-based behavior monitoring method uses a low-cost webcam and can easily be integrated with modern tutoring technologies. We investigate these behaviors in-depth over time in a classroom session of 40 minutes involving reading and problem-solving exercises. The exercises in the sessions are divided into three categories: an easy, medium and difficult topic within the context of undergraduate computer science. We found that there is a significant increase in head and eye movements as time progresses, as well as with the increase of difficulty level. We demonstrated that there is a considerable occurrence of hand-over-face gestures (on average 21.35%) during the 40 minutes session and is unexplored in the education domain. We propose a novel deep learning approach for automatic detection of hand-over-face gestures in images with a classification accuracy of 86.87%. There is a prominent increase in hand-over-face gestures when the difficulty level of the given exercise increases. The hand-over-face gestures occur more frequently during problem-solving (easy 23.79%, medium 19.84% and difficult 30.46%) exercises in comparison to reading (easy 16.20%, medium 20.06% and difficult 20.18%)

Peer victimization and its impact on adolescent brain development and psychopathology

Chronic peer victimization has long-term impacts on mental health; however, the biological mediators of this adverse relationship are unknown. We sought to determine whether adolescent brain development is involved in mediating the effect of peer victimization on psychopathology. We included participants (n = 682) from the longitudinal IMAGEN study with both peer victimization and neuroimaging data. Latent profile analysis identified groups of adolescents with different experiential patterns of victimization. We then associated the victimization trajectories and brain volume changes with depression, generalized anxiety, and hyperactivity symptoms at age 19. Repeated measures ANOVA revealed time-by-victimization interactions on left putamen volume (F = 4.38, p = 0.037). Changes in left putamen volume were negatively associated with generalized anxiety (t = -2.32, p = 0.020). Notably, peer victimization was indirectly associated with generalized anxiety via decreases in putamen volume (95% CI = 0.004-0.109). This was also true for the left caudate (95% CI = 0.002-0.099). These data suggest that the experience of chronic peer victimization during adolescence might induce psychopathology-relevant deviations from normative brain development. Early peer victimization interventions could prevent such pathological changes.</p

Comparative genomic and phylogeographic analysis of Mycobacterium leprae

Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae, an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6 x coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38 x coverage) and NHDP63 (46 x coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy

Genistein induces adipogenesis but inhibits leptin induction in human synovial fibroblasts

It was shown recently that synovial fibroblast transformation into adipocytes reduced the expression of interleukin-6 (IL-6) and IL-8. However, the synovial fibroblast adipogenesis was inhibited in inflammatory conditions induced by the tumor necrosis factor-alpha (TNF-alpha). Furthermore, adipogenesis is often accompanied by leptin production, a proinflammatory adipokine in rheumatic diseases. In this study, we tested the phytohormone genistein for adipogenic and anti-inflammatory properties on human synovial fibroblasts. Results showed that genistein was able to transform synovial fibroblasts into adipocytes that expressed perilipin-A and produced adiponectin, but not leptin. Furthermore, genistein enhanced glucocorticoid-mediated synovial fibroblast adipogenesis and, in parallel, downregulated glucocorticoid-induced leptin and leptin receptor. Endogenous and TNF-alpha-induced expressions of IL-6, IL-8, p38, p65 and C/EBP-beta were also downregulated by genistein, showing its anti-inflammatory properties. Peroxisome proliferator- activated receptor-gamma (PPAR-gamma) agonist, rosiglitazone, had a synergic effect on genistein-induced whereas the non-active tyrosine kinase inhibitor, daidzein, had a significantly inferior adipogenic activity than genistein. The Janus kinase-2 tyrosine kinase inhibitor, AG 490, mimicked the anti-leptin effect of genistein. These results showed that genistein-induced adipogenesis involves PPAR-gamma induction and tyrosine kinase inhibition. In conclusion, genistein, alone or coupled with glucocorticoids, have both adipogenic and anti-inflammatory effects on synovial fibroblasts

Neurobehavioral Markers of Resilience to Depression Amongst Adolescent Exposed to Child Abuse

Childhood maltreatment is strongly associated with depression, which is characterized by reduced reactivity to reward. Identifying factors that mitigate risk for depression in maltreated children is important for understanding etiological links between maltreatment and depression as well as improving early intervention and prevention. We examine whether high reward reactivity at behavioral and neurobiological levels is a marker of resilience to depressive symptomology in adolescence following childhood maltreatment. A sample of 59 adolescents (21 with a history of maltreatment; Mean Age = 16.95 years, SD = 1.44) completed an fMRI task involving passive viewing of emotional stimuli. BOLD signal changes to positive relative to neutral images were extracted in basal ganglia regions of interest. Participants also completed a behavioral reward-processing task outside the scanner. Depression symptoms were assessed at the time of the MRI and again 2 years later. Greater reward reactivity across behavioral and neurobiological measures moderated the association of maltreatment with baseline depression. Specifically, faster reaction time (RT) to cues paired with monetary reward relative to those unpaired with reward and greater BOLD signal in the left pallidum was associated with lower depression symptoms in maltreated youth. Longitudinally, greater BOLD signal in the left putamen moderated change in depression scores over time, such that higher levels of reward response were associated with lower increases in depression over time among maltreated youths. Reactivity to monetary reward and positive social images, at both behavioral and neurobiological levels, is a potential marker of resilience to depression among adolescents exposed to maltreatment. These findings add to a growing body of work highlighting individual differences in reactivity to reward as a core neurodevelopmental mechanism in the etiology of depression. (PsycINFO Database Recor

What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: recency, accumulation, or sensitive periods?

Copyright © Cambridge University Press 2018Â. Background Although childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity exposure, including its developmental timing or duration, influence subsequent mental health outcomes. This study compared three models from life course theory (recency, accumulation, sensitive period) to determine which one(s) best explained this relationship.Methods Prospective data came from the Avon Longitudinal Study of Parents and Children (n = 7476). Four adversities commonly linked to psychopathology (caregiver physical/emotional abuse; sexual/physical abuse; financial stress; parent legal problems) were measured repeatedly from birth to age 8. Using a statistical modeling approach grounded in least angle regression, we determined the theoretical model(s) explaining the most variability (r2) in psychopathology symptoms measured at age 8 using the Strengths and Difficulties Questionnaire and evaluated the magnitude of each association.Results Recency was the best fitting theoretical model for the effect of physical/sexual abuse (girls r2 = 2.35%; boys r2 = 1.68%). Both recency (girls r2 = 1.55%) and accumulation (boys r2 = 1.71%) were the best fitting models for caregiver physical/emotional abuse. Sensitive period models were chosen alone (parent legal problems in boys r2 = 0.29%) and with accumulation (financial stress in girls r2 = 3.08%) more rarely. Substantial effect sizes were observed (standardized mean differences = 0.22-1.18).Conclusions Child psychopathology symptoms are primarily explained by recency and accumulation models. Evidence for sensitive periods did not emerge strongly in these data. These findings underscore the need to measure the characteristics of adversity, which can aid in understanding disease mechanisms and determining how best to reduce the consequences of exposure to adversity