Component-based Adaptation Methods for Service-Oriented Peer-to-Peer Software Architectures

Service-oriented peer-to-peer architectures aim at supporting application scenarios of dispersed collaborating groups in which the participating users are capable of providing and consuming local resources in terms of peer services. From a conceptual perspective, service-oriented peer-to-peer architectures adopt relevant concepts of two well-established state-of-the-art software architectural styles, namely service-oriented architectures (also known as SOA) and peer-to-peer architectures (P2P). One major argumentation of this thesis is that the adoption of end-user adaptability (or tailorability) concepts is of major importance for the successful deployment of service-oriented peer-to-peer architectures that support user collaboration. Since tailorability concepts have so far not been analyzed for both peer-to-peer and service-oriented architectures, no relevant models exist that could serve as a tailorability model for service-oriented peer-to-peer architectures. In order to master the adaptation of peer services, as well as peer service compositions within service-oriented peer-to-peer architectures, this dissertation proposes the adoption of component-oriented development methods. These so-called component-based adaptation methods enable service providers to adapt their provided services during runtime. Here, a model for analyzing existing dependencies on subscribed ser-vice consumers ensures that a service provider is able to adapt his peer services without violating any dependencies. In doing so, an adaptation policy that can be pre-arranged within a peer group regulates the procedures of how to cope with existing dependencies in the scope of a group. The same methods also serve as a way to handle exceptional cases, in particular the failure of a dependent service provider peer and, hence, a service that is part of a local service composition. In this, the hosting runtime environment is responsible for detecting exceptions and for initiating the process of exception resolution. During the resolution phase, a user can be actively involved at selected decision points in order to resolve the occurred exception in unpredictable contexts. An exception could also be the reason for the violation of an integrity constraint that serves as a contract between various peers that interact within a given collaboration. The notion of integrity constraints and the model of handling the constraint violation aim at improving the reliability of target-oriented peer collaborations. This dissertation is composed of three major parts that each makes a significant contribution to the state of the art. First of all, a formal architectural style (SOP2PA) is introduced to define the fundamental elements that are necessary to build service-oriented peer-to-peer architectures, as well as their relationships, constraints, and operational semantics. This architectural style also formalizes the above-mentioned adaptation methods, the exception handling model that embraces these methods, the analysis model for managing consumer dependencies, as well as the integrity constraints model. Subsequently, on this formal basis, a concrete (specific) service-oriented peer-to-peer architecture (DEEVOLVE) is conceptualized that serves as the default implementation of that style. Here, the notions described above are materialized based on state-of-the-art software engineering methods and models. Finally, the third contribution of this work outlines an application scenario stemming from the area of construction informatics, in which the default implementation DEEVOLVE is deployed in order to support dispersed planning activities of structural engineers

Support of Collaborative Structural Design Processes through the Integration of Peer-to-Peer and Multiagent Architectures

Structural engineering projects are increasingly organized in networked cooperations due to a permanently enlarged competition pressure and a high degree of complexity while performing the concurrent design activities. Software that intends to support such collaborative structural design processes implicates enormous requirements. In the course of our common research work, we analyzed the pros and cons of the application of both the peer-to-peer (University of Bonn) and multiagent architecture style (University of Bochum) within the field of collaborative structural design. In this paper, we join the benefits of both architecture styles in an integrated conceptual approach. We demonstrate the surplus value of the integrated multiagent–peer-to-peer approach by means of an example scenario in which several structural engineers are co-operatively designing the basic structural elements of an arched bridge, applying heterogeneous CAD systems

Support of Collaborative Structural Design Processes through the Integration of Peer-to-Peer and Multiagent Architectures

Structural engineering projects are increasingly organized in networked cooperations due to a permanently enlarged competition pressure and a high degree of complexity while performing the concurrent design activities. Software that intends to support such collaborative structural design processes implicates enormous requirements. In the course of our common research work, we analyzed the pros and cons of the application of both the peer-to-peer (University of Bonn) and multiagent architecture style (University of Bochum) within the field of collaborative structural design. In this paper, we join the benefits of both architecture styles in an integrated conceptual approach. We demonstrate the surplus value of the integrated multiagent–peer-to-peer approach by means of an example scenario in which several structural engineers are co-operatively designing the basic structural elements of an arched bridge, applying heterogeneous CAD systems

Holistic Support for the Collaborative Planning of Fire Protection Concepts in Building Design

Der Bauplanungsprozess ist durch ein hohes Maß an Kooperation zwischen Planungsbeteiligten verschiedener Fachrichtungen gekennzeichnet. Hierbei werden zum einen Planungen auf der Basis von Planungsinformationen anderer Planungsbeteiligter detailliert, zum anderen geben Planungen einzelner auch wichtige Rahmenbedingungen für die Gesamtplanung vor. Der vorliegende Beitrag beschreibt einen Ansatz zur ganzheitlichen Unterstützungen verteilter Planungen am Beispiel des baulichen Brandschutzes. Der Antrag trägt hierbei der verteilten und parallelen Planung Rechnung, wie sie heute bei der Planung großer und mittlerer Bauwerke angewendet wird. Die Verteiltheit wird nicht nur für die Planungsbeteiligten modelliert, sondern auch die einzelnen Planungsinformationen liegen im gemeinsamen Kooperationsverbund verteilt vor. Der Fokus dieses Beitrags liegt auf der Wahrnehmung von Planungsänderungen und Ereignissen während der Planung und die Verarbeitung dieser Informationen um eine durchgängige Planung zu gewährleisten. Dies wird zum einen durch das CoBE Awarenessmodell erreicht, mit dem Ereignisse erkannt und dem Informationsverbund zur Verfügung gestellt werden können. Zum anderen werden die Ereignisbehandlung und die darauf folgende fachgerechte Informationsverarbeitung mit Hilfe eines Multi-Agentensystems beschrieben

Gene set enrichment analysis and expression pattern exploration implicate an involvement of neurodevelopmental processes in bipolar disorder

Background Bipolar disorder (BD) is a common and highly heritable disorder of mood. Genome-wide association studies (GWAS) have identified several independent susceptibility loci. In order to extract more biological information from GWAS data, multi-locus approaches represent powerful tools since they utilize knowledge about biological processes to integrate functional sets of genes at strongly to moderately associated loci. Methods We conducted gene set enrichment analyses (GSEA) using 2.3 million single-nucleotide polymorphisms, 397 Reactome pathways and 24,025 patients with BD and controls. RNA expression of implicated individual genes and gene sets were examined in post-mortem brains across lifespan. Results Two pathways showed a significant enrichment after correction for multiple comparisons in the GSEA: GRB2 events in ERBB2 signaling, for which 6 of 21 genes were BD associated (P = 0.0377), and NCAM signaling for neurite out-growth, for which 11 out of 62 genes were BD associated (P = 0.0451). Most pathway genes showed peaks of RNA co-expression during fetal development and infancy and mapped to neocortical areas and parts of the limbic system. Limitations Pathway associations were technically reproduced by two methods, although they were not formally replicated in independent samples. Gene expression was explored in controls but not in patients. Conclusions Pathway analysis in large GWAS data of BD and follow-up of gene expression patterns in healthy brains provide support for an involvement of neurodevelopmental processes in the etiology of this neuropsychiatric disease. Future studies are required to further evaluate the relevance of the implicated genes on pathway functioning and clinical aspects of BD

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Gene set enrichment analysis and expression pattern exploration implicate an involvement of neurodevelopmental processes in bipolar disorder

Bipolar disorder (BD) is a common and highly heritable disorder of mood. Genome-wide association studies (GWAS) have identified several independent susceptibility loci. In order to extract more biological information from GWAS data, multi-locus approaches represent powerful tools since they utilize knowledge about biological processes to integrate functional sets of genes at strongly to moderately associated loci.We conducted gene set enrichment analyses (GSEA) using 2.3 million single-nucleotide polymorphisms, 397 Reactome pathways and 24,025 patients with BD and controls. RNA expression of implicated individual genes and gene sets were examined in post-mortem brains across lifespan.Two pathways showed a significant enrichment after correction for multiple comparisons in the GSEA: GRB2 events in ERBB2 signaling, for which 6 of 21 genes were BD associated (PFDR = 0.0377), and NCAM signaling for neurite out-growth, for which 11 out of 62 genes were BD associated (PFDR = 0.0451). Most pathway genes showed peaks of RNA co-expression during fetal development and infancy and mapped to neocortical areas and parts of the limbic system.Pathway associations were technically reproduced by two methods, although they were not formally replicated in independent samples. Gene expression was explored in controls but not in patients.Pathway analysis in large GWAS data of BD and follow-up of gene expression patterns in healthy brains provide support for an involvement of neurodevelopmental processes in the etiology of this neuropsychiatric disease. Future studies are required to further evaluate the relevance of the implicated genes on pathway functioning and clinical aspects of BD

Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Background: Alzheimer's disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits. Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer's Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework. Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR=0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR=0.022, opposite direction of effect). Conclusions: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP

The genetics of the mood disorder spectrum:genome-wide association analyses of over 185,000 cases and 439,000 controls

Background Mood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders. Methods To clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; non-overlapping N = 609,424). Results Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell-types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment – positive in bipolar disorder but negative in major depressive disorder. Conclusions The mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum