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This article addresses the developments ongoing in SENSIBLE, an H2020 funded project focused on energy storage and energy management, which demonstration occurs in Évora-Portugal, Nottingham, UK and Nuremberg, Germany. Currently, the presented work focuses on the developments necessary to make possible islanding operation in low-voltage grids, where new assets like storage and new automation and protection schemes are necessary to guaranty safety and reliability of low-voltage grids. These developments are a result of the ongoing works under one of SENSIBLE use cases which demonstrations occurs in a small village in Évora district in Portugal.

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Electric Power Systems: Advanced Forecasting Techniques and Optimal Generation Scheduling helps readers develop their skills in modeling, simulating, and optimizing electric power systems. Carefully balancing theory and practice, it presents novel, cutting-edge developments in forecasting and scheduling. The focus is on understanding and solving pivotal problems in the management of electric power generation systems. Methods for Coping with Uncertainty and Risk in Electric Power Generation Outlining real-world problems, the book begins with an overview of electric power generation systems. Since the ability to cope with uncertainty and risk is crucial for power generating companies, the second part of the book examines the latest methods and models for self-scheduling, load forecasting, short-term electricity price forecasting, and wind power forecasting. Toward Optimal Coordination between Hydro, Thermal, and Wind Power Using case studies, the third part of the book investigates how to achieve the most favorable use of available energy sources. Chapters in this section discuss price-based scheduling for generating companies, optimal scheduling of a hydro producer, hydro-thermal coordination, unit commitment with wind generators, and optimal optimization of multigeneration systems. Written in a pedagogical style that will appeal to graduate students, the book also expands on research results that are useful for engineers and researchers. It presents the latest techniques in increasingly important areas of power system operations and planning. © 2012 by Taylor & Francis Group, LLC.

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Purpose - Hospital centres (HCs) are the result of a horizontal integration of two or more hospital units. The benefits of this integration have been presented in the literature. The purpose of this paper is to define the hospital performance dimensions most valued by HC internal stakeholders, and to evaluate if the importance given to each dimension is different when comparing professional groups. Design/methodology/approach - An in-depth HC case study using a quantitative survey based on the Parsons' social system action theory to achieve this goal was conducted which embraces the four major models of organizational performance. In the final version of the survey, 37 items were retained for analysis. An exploratory factor analysis was conducted for a final sample of 365 participants, through principal component analysis, with oblique rotation and the Kaiser criterion. Findings - Four factors were retained: "Human resources development and Internal Processes", "Attractiveness/Openness", "Public service mission" and "Interpersonal relationships". The means factor scores only reveal statistical differences between the attractiveness/openness factor and the remaining three factors. A shared view was found in this study among the three groups of internal stakeholders: physicians, caregivers and administrative staff. Originality/value - The results of this study suggest that the HC performance concept should be expanded and performance measurement frameworks with a greater scope should be used. Interpersonal relationships, the human resources development and the public service are considered important dimensions for the performance measurement of the HC. Additionally, a consensual view regarding the most valued performance dimension could contribute to a beneficial and healthy working environment and improvements in HC performance.

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Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches. 2017 © The Authors.

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Introduction: The establishment of prognostic models for Crohn's disease [CD] is highly desirable, as they have the potential to guide physicians in the decision-making process concerning therapeutic choices, thus improving patients' health and quality of life. Our aim was to derive models for disabling CD and reoperation based solely on clinical/demographic data. Methods: A multicentric and retrospectively enrolled cohort of CD patients, subject to early surgery or immunosuppression, was analysed in order to build Bayesian network models and risk matrices. The final results were validated internally and with a multicentric and prospectively enrolled cohort. Results: The derivation cohort included a total of 489 CD patients [64% with disabling disease and 18% who needed reoperation], while the validation cohort included 129 CD patients with similar outcome proportions. The Bayesian models achieved an area under the curve of 78% for disabling disease and 86% for reoperation. Age at diagnosis, perianal disease, disease aggressiveness and early therapeutic decisions were found to be significant factors, and were used to construct user-friendly matrices depicting the probability of each outcome in patients with various combinations of these factors. The matrices exhibit good performance for the most important criteria: disabling disease positive post-test odds = 8.00 [2.72-23.44] and reoperation negative post-test odds = 0.02 [0.00-0.11]. Conclusions: Clinical and demographical risk factors for disabling CD and reoperation were determined and their impact was quantified by means of risk matrices, which are applicable as bedside clinical tools that can help physicians during therapeutic decisions in early disease management.

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