The Network Structure of Childhood Psychopathology in International Adoptees

International adoptees are at an increased risk of emotional and behavioral problems, especially those who are adopted at an older age. We took a new approach in our study of the network structure and predictability of emotional and behavioral problems in internationally adopted children in Finland. Our sample was from the on-going adoption study and comprised 778 internationally adopted children (387 boys and 391 girls, mean age 10.5 (SD 3.4) years). Networks were estimated using Gaussian graphical models and lasso regularization for all the children, and separately for those who were adopted at different ages. The results showed that anxiety/depressive symptoms, social problems, and aggressiveness were the most central symptom domains. Somatic symptoms were the least central and had the weakest effect on the other domains. Similarly, aggressiveness, social problems, and attention problems were high in terms of predictability (73-65%), whereas internalizing problems were relatively low (28-56%). There were clear but local age-group differences in network structure, symptom centrality, and predictability. According to our findings, network models provide important additional information about the centrality and predictability of specific symptom domains, and thus may facilitate targeted interventions among international adoptees.Peer reviewe

Selected Papers from the ICCoptS 9 (Cairo 2008)

Les actes du neuvième congrès d'études coptes (Le Caire, 2008) n'ont jamais paru. Beaucoup d'auteurs ont publié ailleurs leurs contributions. Avec deux collègues, nous avons proposés de consacrer un numéro spécial du Journal of Coptic Studies pour publier une sélection de 14 communications communications restées inédites.info:eu-repo/semantics/publishe

Senatus - Implementation and Performance Evaluation

Traffic anomaly detection in backbone networks has received increased at-tention from the research community over the last years. A variety of tech-niques and implementations has been proposed in this area, some which hasbecome commercial products. However, studies have revealed that theseproducts are hardly used, mainly because of high false-positive rates andthe fact that manual inspection of alarms is a time consuming task for thenetwork administrator.Senatus is a recently proposed technique for combined anomaly detectionand root-cause analysis, originally proposed by Atef Abdelkefi. In this the-sis, we provide a complete high-performance implementation of Senatus,including a web Dashboard with overview of anomalies and the possibil-ity for manual fine-tuning of parameters. Furthermore, we have verifiedSenatus performance by comparing Senatus with a implementation of awell-known histogram-based anomaly detection technique.Our results show that Senatus performs very well for detection scans, andthat it matches the histogram-based anomaly detector for Denial of Service-attacks