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The increasing penetration of DER with smart-inverter functionality is set to transform the electrical distribution network from a passive system, with fixed injection/consumption, to an active network with hundreds of distributed controllers dynamically modulating their operating setpoints as a function of system conditions. This transition is being achieved through standardization of functionality through grid codes and/or international standards. DER, however, are unique in that they are typically neither owned nor operated by distribution utilities and, therefore, represent a new emerging attack vector for cyber-physical attacks. Within this work we consider deep reinforcement learning as a tool to learn the optimal parameters for the control logic of a set of uncompromised DER units to actively mitigate the effects of a cyber-attack on a subset of network DER.

Aim: Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort., Methods and Results: In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes., Conclusion: This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.)

We present a study on how to predict new emerging trends in the biomedical domain based on textual data. We thereby propose a way of anticipating the transformation of arbitrary information into ground truth knowledge by predicting the inclusion of new terms into the MeSH ontology. We also discuss the preparation of a dataset for the evaluation of emerging trend prediction algorithms that is based on PubMed abstracts and related MeSH terms. The results suggest that early prediction of emerging trends is possible.

The Arabidopsis circadian system regulates the expression of up to 36% of the nuclear genome, including many genes that encode photosynthetic proteins. The expression of nuclear-encoded photosynthesis genes is also regulated by signals from the chloroplasts, a process known as retrograde signaling. We have identified CHLOROPLAST RNA BINDING (CRB), a putative RNA-binding protein, and have shown that it is important for the proper functioning of the chloroplast. crb plants are smaller and paler than wild-type plants, and have altered chloroplast morphology and photosynthetic performance. Surprisingly, mutations in CRB also affect the circadian system, altering the expression of both oscillator and output genes. In order to determine whether the changes in circadian gene expression are specific to mutations in the CRB gene, or are more generally caused by the malfunctioning of the chloroplast, we also examined the circadian system in mutations affecting STN7, GUN1, and GUN5, unrelated nuclear-encoded chloroplast proteins known to be involved in retrograde signaling. Our results provide evidence that the functional state of the chloroplast may be an important factor that affects the circadian system.

The five parameter double integral ∫ 0 ∞ d y exp ( - p 2 y 2 ) sin ( β y + θ ) times ∫ 0 y d x exp ( - x 2 ) cos ( ϵ β x + ϕ ) is evaluated in terms of Fourier transforms of exp(- x 2 )erfc( αx ). Some new expressions for these transforms are obtained.