Efficient Compliance Checking Using BPMN-Q and Temporal Logic

Abstract. Compliance rules describe regulations, policies and quality constraints business processes must adhere to. Given the large number of rules and their frequency of change, manual compliance checking can be-come a time-consuming task. Automated compliance checking of process activities and their ordering is an alternative whenever business pro-cesses and compliance rules are described in a formal way. This paper introduces an approach for automated compliance checking. Compliance rules are translated into temporal logic formulae that serve as input to model checkers which in turn verify whether a process model satisfies the requested compliance rule. To address the problem of state-space explo-sion we employ a set of reduction rules. The approach is prototypically realized and evaluated.

Neuroanatomical abnormalities in first-episode psychosis across independent samples: a multi-centre mega-analysis

Abstract Background Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be subtle and widespread. The vast majority of previous studies have used small samples, and therefore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in individuals with FEP that are expressed consistently across several independent samples. Methods Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons. Results FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease – gyrus rectus – was negatively correlated with the severity of positive and negative symptoms. Conclusions This study identified a consistent pattern of fronto-temporal, insular and occipital abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differences in anti-psychotic medication, scanning parameters and recruitment criteria

Neuroanatomical abnormalities in first-episode psychosis across independent samples: A multi-centre mega-analysis

Background Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be subtle and widespread. The vast majority of previous studies have used small samples, and therefore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in individuals with FEP that are expressed consistently across several independent samples. Methods Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons. Results FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease-gyrus rectus-was negatively correlated with the severity of positive and negative symptoms. Conclusions This study identified a consistent pattern of fronto-temporal, insular and occipital abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differences in anti-psychotic medication, scanning parameters and recruitment criteria

The Impact of Brand Quality on Shareholder Wealth

This study examines the impact of brand quality on three components of shareholder wealth: stock returns, systematic risk, and idiosyncratic risk. The study finds that brand quality enhances shareholder wealth insofar as unanticipated changes in brand quality are positively associated with stock returns and negatively related to changes in idiosyncratic risk. However, unanticipated changes in brand quality can also erode shareholder wealth because they have a positive association with changes in systematic risk. The study introduces a contingency theory view to the marketing-finance interface by analyzing the moderating role of two factors that are widely followed by investors. The results show an unanticipated increase (decrease) in current-period earnings enhances (depletes) the positive impact of unanticipated changes in brand quality on stock returns and mitigates (enhances) their deleterious effects on changes in systematic risk. Similarly, brand quality is more valuable for firms facing increasing competition (i.e., unanticipated decreases in industry concentration). The results are robust to endogeneity concerns and across alternative models. The authors conclude by discussing the nuanced implications of their findings for shareholder wealth, reporting brand quality to investors, and its use in employee evaluation

Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning

Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size and have limited clinical relevance. These concerns have prompted a paradigm shift toward highly powered (that is, big data) individual-level inferences, which are data driven, transdiagnostic and neurobiologically informed. Here we built and validated supervised neuroanatomical machine learning models for individual-level inferences, using a case–control design and the largest known neuroimaging database on youth anxiety disorders: the ENIGMA-Anxiety Consortium (N = 3,343; age = 10–25 years; global sites = 32). Modest, yet robust, brain-based classifications were achieved for specific anxiety disorders (panic disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status and symptom severity (area under the receiver operating characteristic curve, 0.59–0.63). Classifications were driven by neuroanatomical features (cortical thickness, cortical surface area and subcortical volumes) in fronto-striato-limbic and temporoparietal regions. This benchmark study within a large, heterogeneous and multisite sample of youth with anxiety disorders reveals that only modest classification performances can be realistically achieved with machine learning using neuroanatomical data.NWORubicon 019.201SG.022Advanced Behavioural Research MethodsHealth and Well-bein

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival