The prevalence of cyber bullying in higher education in the UK

Empirical findings have demonstrated that cyber bullying in schools is a growing problem, but it is not clear whether the phenomenon exists in the higher education context in UK. An explorative study of two hundred and nineteen undergraduate and postgraduate students was conducted to examine cyber bullying in UK universities. It was found that close to 25% of students were cyber victims, while about 15% were cyber perpetrators during their studies. When sex was taken into account, no differences in victimization and/or perpetration were identified. Furthermore,possible associations between past experiences of school bullying and current higher education cyber bullying were investigated. The relationship between traditional school bullying and cyber bullying at university was found with cyber bullying or cyber victimization behaviour continuing in the higher education context. This concurs with current perpetrator/victim research findings within the school context (Smith et al., 2003). Data of students’ internet usage and online behaviour are also presented and implications for interventions in higher education are discussed

Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace

Affective computing has been largely limited in terms of available data resources. The need to collect and annotate diverse in-the-wild datasets has become apparent with the rise of deep learning models, as the default approach to address any computer vision task. Some in-the-wild databases have been recently proposed. However: i) their size is small, ii) they are not audiovisual, iii) only a small part is manually annotated, iv) they contain a small number of subjects, or v) they are not annotated for all main behavior tasks (valence-arousal estimation, action unit detection and basic expression classification). To address these, we substantially extend the largest available in-the-wild database (Aff-Wild) to study continuous emotions such as valence and arousal. Furthermore, we annotate parts of the database with basic expressions and action units. As a consequence, for the first time, this allows the joint study of all three types of behavior states. We call this database Aff-Wild2. We conduct extensive experiments with CNN and CNN-RNN architectures that use visual and audio modalities; these networks are trained on Aff-Wild2 and their performance is then evaluated on 10 publicly available emotion databases. We show that the networks achieve state-of-the-art performance for the emotion recognition tasks. Additionally, we adapt the ArcFace loss function in the emotion recognition context and use it for training two new networks on Aff-Wild2 and then re-train them in a variety of diverse expression recognition databases. The networks are shown to improve the existing state-of-the-art. The database, emotion recognition models and source code are available at http://ibug.doc.ic.ac.uk/resources/aff-wild2

Brainstem Auditory Evoked Potentials in Boys with Autism: Still Searching for the Hidden Truth

How to Cite This Article: Ververi A, Vargiami E, V Papadopoulou V, Tryfonas D, Zafeiriou DI. Brainstem Auditory Evoked Potentials inBoys with Autism: Still Searching for the Hidden Truth. Iran J Child Neurol. Spring 2015;9(2):21-28.Abstract Objective Brainstem auditory evoked potentials (BAEPs) have long been utilized in the investigation of auditory modulation and, more specifically, auditory brainstem functions in individuals with autism. Although most investigators have reported significant abnormalities, no single BAEPs pattern has yet been identified. The present study further delineates the BAEPs deficits among subjects with autism. Materials & Methods BAEPs were recorded in 43 male patients, aged 35–104 months, who underwent standard evaluations after receiving a diagnosis of autism. The control group consisted of 43 age-matched typically developing boys. The study took place in a tertiary neurodevelopmental center over a period of two years. Results The mean values of all absolute and/or interpeak latencies were longer in patients when compared to controls, albeit the differences were not significant for any of the parameters. Prolonged or shortened absolute/interpeak latencies (control group mean ± 2.5SD) were unilaterally or bilaterally identified in 33% of patients, compared to 9% of controls. The most frequent findings included prolongation of absolute latencies I, V and III, followed by shortening of interpeak latency I-V. In addition, abnormalities (either shortening or prolongation) of absolute latencies I and V, as well as interpeak latency I-V, were significantly more common among patients. Taken together, BAEPs in 23% of patients were indicative of a clinically abnormal response in 32% of patients. Conclusion As can be easily concluded, BAEPs abnormalities characterize only a subset of subjects with autism, who may be important to identify clinically. The latter individuals may benefit from targeted intervention to utilize brainstem plasticity