Psychometric Qualities of the Dimensional Assessment of Personality Pathology – Short Form for Adolescents

A growing body of research recognizes the occurrence and validity of personality pathology during adolescence as well as its relevance as a developmental precursor of adult personality pathology.The present study recognizes the need for a comprehensive and concise instrument to assess the dimensions of personality pathology in adolescents. Therefore, the psychometric qualities of an abbreviated version of the Dimensional Assessment of Personality Pathology - Basic Questionnaire for Adolescents (DAPP-BQ-A), which has been denoted as the DAPP - Short Form for Adolescents (DAPP-SF-A), were examined.The factorial structure, internal consistency, test-retest reliability, discriminative validity, and classification accuracy of the DAPP-SF-A scales were examined in three samples: 1596 non-referred adolescents; 166 adolescents referred to inpatient and outpatient mental health services; and 58 referred and general population adolescents.Despite a reduction in the number of items by 50% (from 290 to 144 items), the promising psychometric qualities established for the DAPP-BQ-A were replicated for the DAPP-SF-A.The results of this study are promising regarding the qualities of the DAPP-SF-A and its utility in both clinical and research settings. In addition, the equivalence of the instruments for adolescents and (young) adults enables the investigation of developmental trajectories across different life stages

Decoupling Graphene from SiC(0001) via Oxidation

When epitaxial graphene layers are formed on SiC(0001), the first carbon layer (known as the "buffer layer"), while relatively easy to synthesize, does not have the desirable electrical properties of graphene. The conductivity is poor due to a disruption of the graphene pi-bands by covalent bonding to the SiC substrate. Here we show that it is possible to restore the graphene pi-bands by inserting a thin oxide layer between the buffer layer and SiC substrate using a low temperature, CMOS-compatible process that does not damage the graphene layer

Associations of specific and multiple types of childhood abuse and neglect with personality pathology among adolescents referred for mental health services

The present study investigated the unique association between five types of childhood abuse and neglect and 18 lower-order dimensions of personality pathology, and using latent classes analysis (LCA) explored patterns of childhood abuse or neglect experiences. Further differences across latent classes on personality pathology traits, personality disorder symptom count and a diagnosis of personality disorder were examined. Participants were 178 adolescents and young adults (12–22 years; M = 16.02, 65.7% girls; 83% Axis I/II disorder) from the Netherlands referred for mental health services. Emotional abuse was uniquely associated with 11 personality pathology traits; sexual and physical were associated with three and four traits, respectively. LCA yielded three classes, namely, severe maltreatment (class 1), low-moderate emotional maltreatment and sexual abuse (class 2), and least maltreatment (class 3). After controlling for age, gender, presence of any Axis I disorder, multivariate analysis of covariance indicated that classes with more types of maltreatment experiences and higher severity (classes 1 and 2) endorsed more personality pathology traits, personality disorder symptom counts and a diagnosis of a personality disorder than the least maltreatment class. Findings have theoretical and clinical implications entailing the identification of patterns of maltreatment types and related personality pathology traits among youth

Associations of specific and multiple types of childhood abuse and neglect with personality pathology among adolescents referred for mental health services

The present study investigated the unique association between five types of childhood abuse and neglect and 18 lower-order dimensions of personality pathology, and using latent classes analysis (LCA) explored patterns of childhood abuse or neglect experiences. Further differences across latent classes on personality pathology traits, personality disorder symptom count and a diagnosis of personality disorder were examined. Participants were 178 adolescents and young adults (12–22 years; M = 16.02, 65.7% girls; 83% Axis I/II disorder) from the Netherlands referred for mental health services. Emotional abuse was uniquely associated with 11 personality pathology traits; sexual and physical were associated with three and four traits, respectively. LCA yielded three classes, namely, severe maltreatment (class 1), low-moderate emotional maltreatment and sexual abuse (class 2), and least maltreatment (class 3). After controlling for age, gender, presence of any Axis I disorder, multivariate analysis of covariance indicated that classes with more types of maltreatment experiences and higher severity (classes 1 and 2) endorsed more personality pathology traits, personality disorder symptom counts and a diagnosis of a personality disorder than the least maltreatment class. Findings have theoretical and clinical implications entailing the identification of patterns of maltreatment types and related personality pathology traits among youth

Node-Oriented Workflow (NOW): A Command Template Workflow Management Tool for High Throughput Data Analysis Pipelines

Next generation sequencing (NGS) systems produce vast quantities of data that require substantial computational resources for typical analysis tasks. In addition, data that are generated by different NGS systems are not homogeneous. Moreover, there are an overwhelming number of tools available for performing typical tasks. Managing NGS workflows involves writing custom scripts that quickly grow in complexity, often resulting in unwieldy workflows that underutilize typical high performance compute resources, and increase the demands of the staff managing these workflows. We present Node-Oriented Workflow (NOW), a dynamic command template workflow engine for high performance distributed computing (HPC) systems. Our system provides a simple-to-use browser-based front end for designing and managing complex workflows. Workflows are configured using a simple browser interface, and are managed by the integrated job engine, which initializes nodes, monitors node status, and processes results of individual jobs across nodes in an HPC configuration. We reduce excessive messaging across nodes by placing the burden on nodes to start tasks in a workflow when dependencies are met, i.e., node oriented workflow. Our system was designed for NGS processing in the clinical research setting, emphasizing user simplicity, tool scalability, minimization of redundancy in workflows, while maximizing throughput in an HPC environment. Furthermore, NOW is not restricted to NGS pipeline management, but can used to manage any computational pipeline