Domain-Specific Modeling and Code Generation for Cross-Platform Multi-Device Mobile Apps

Nowadays, mobile devices constitute the most common computing device. This new computing model has brought intense competition among hardware and software providers who are continuously introducing increasingly powerful mobile devices and innovative OSs into the market. In consequence, cross-platform and multi-device development has become a priority for software companies that want to reach the widest possible audience. However, developing an application for several platforms implies high costs and technical complexity. Currently, there are several frameworks that allow cross-platform application development. However, these approaches still require manual programming. My research proposes to face the challenge of the mobile revolution by exploiting abstraction, modeling and code generation, in the spirit of the modern paradigm of Model Driven Engineering

Improving NDT with Automatic Test Case Generation

The model-driven development defi nes the software development process as a set of iterations to create models and a set of transformations to obtain new models. From this point of view, this paper presents the enhancement of a model- driven approach, called navigational development techniques (NDT), by means of new models and transformations in order to generate test cases. It also states some conclusions from the research work and practical cases in which this approach was used.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Implementation of a Physical Activity Group at a Community Mental Health Center: A Pilot Quality Improvement Project to Reduce Depressive Symptoms in Adolescents with Major Depressive Disorder

Major Depressive Disorder is a debilitating illness that affects millions of Americans, including adolescents. The majority of adolescents with Major Depressive Disorder (MDD) do not receive treatment. There may be a variety of reasons for this including stigma, access to care, and potential adverse reactions. People suffering from MDD are known to be at high risk for suicide. Lack of treatments adds the risk of suicide for adolescents with MDD. Identifying and implementing treatment options that are more acceptable and accessible are of the utmost importance. Although there is limited research regarding exercise/physical activity, depressive symptoms, and adolescents with MDD, there are two promising studies by Hughes, Barnes, Barnes, DeFina, Nakonezny, & Graham (2013) and Finazzi, Mesquita, Lopes, Fu, & Oliveira (2009). Currently, there is a physical activity program at Lakes Region Mental Health for adult patients. Unfortunately, adolescents do not have access to a similar group. This Doctorate of Nursing Practice (DNP) Quality Improvement (QI) Project piloted an eight-week physical activity group for adolescents with MDD to determine the impact physical activity had on depressive symptoms. The PHQ-9 for Adolescents Depression Screening Tool was given to participants before joining the physical exercise group and upon completion of the physical activity group. Pre-intervention and post-intervention results of the PHQ-9 for Adolescents Depression Screening were compared and analyzed. In addition, a survey was administered at week four and upon completion of the physical activity group to gather qualitative data. The results of this Pilot DNP QI project indicate there was a decrease in the PHQ-9 for Adolescents for two out of the three participants. The qualitative data demonstrated improvement in depressive symptoms, self-esteem and social interaction for all three participants. These results are promising and support the need for a physical activity group for adolescents with MDD at Lakes Region Mental Health Center

Phenomenology and Dimensional Approaches to Psychiatric Research and Classification

Contemporary psychiatry finds itself in the midst of a crisis of classification. The developments begun in the 1980s—with the third edition of the Diagnostic and Statistical Manual of Mental Disorders —successfully increased inter-rater reliability. However, these developments have done little to increase the predictive validity of our categories of disorder. A diagnosis based on DSM categories and criteria often fails to accurately anticipate course of illness or treatment response. In addition, there is little evidence that the DSM categories link up with genetic findings, and even less evidence that they..