Abstract
This paper deals with integrating energy storage systems (ESS) into existing electricity markets. We explain why ESS increase flexibility of power systems and energy markets and why more flexible systems and markets are desirable, particularly in a context of high integration of variable renewable energy sources (RES). The Dutch electricity markets are introduced as the case studies. As opposing to the existing literature, we focus on implementation of a dual technology ESS, which we believe is more beneficial than a single ESS. To show this, we introduce an optimal control model, in which the goal is to maximize the revenues of the dual technology energy storage system applied into two different energy markets, assuming the selling and buying electricity prices are exogenous. Subsequently, we introduce our model, using a simple strategy and present its results, showing the impact of the devices nominal rating on the potential revenues.

Abstract
Collections of time-series data appear in a wide variety of contexts. To gain insight into the underlying phenomenon (that the data represents), one must analyze the time-series data. Analysis can quickly become challenging for very large data (~terabytes or more) sets, and it may be infeasible to scan the entire data-set on each query due to time limits or resource constraints. To avoid this problem, one might pre-compute partial results by scanning the data-set (usually as the data arrives). However, for complex queries, where the value of a new data record depends on all of the data previously seen, this might be infeasible because incorporating a large amount of historical data into a query requires a large amount of storage. We present an approach to performing complex queries over very large data-sets in a manner that is (i) practical, meaning that a query does not require a scan of the entire data-set, and (ii) fixed-cost, meaning that the amount of storage required only depends on the time-range spanned by the entire data-set (and not the size of the data-set itself). We evaluate our approach with three different data-sets: (i) a 4-year commercial analytics data-set from a production content-delivery platform with over 15 million mobile users, (ii) an 18-year data-set from the Linux-kernel commit-history, and (iii) an 8-day data-set from Common Crawl HTTP logs. Our evaluation demonstrates the feasibility and practicality of our approach for a diverse set of complex queries on a diverse set of very large data-sets. © 2015 IEEE.

Abstract
Accurate prediction of the functional effect of genetic variation is critical for clinical genome interpretation.We systematically characterized the transcriptome effects of protein-truncating variants, a class of variants expected to have profound effects on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitated tissue-specific and positional effects on nonsense-mediated transcript decay and present an improved predictive model for this decay. We directly measured the effect of variants both proximal and distal to splice junctions. Furthermore, we found that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.

Abstract
Objective To identify dietary availability and its time trends in elderly Portuguese households. Design A set of four cross-sectional studies based on the Household Budget Surveys was used. The dietary data were described using the daily per capita availability of food and beverages, energy and selected nutrients (macronutrients, different lipid fractions and simple sugars). Differences between elderly household types and time trends were studied. Setting Portuguese Household Budget Survey data from 1989/1990, 1994/1995, 2000/2001 and 2005/2006. Subjects Households with members aged 65 years were selected and categorized as solitary elderly female, solitary elderly male or couple (composed of one elderly female and one elderly male). Results While cereals, fats/oils, potatoes and sugar/sugar products decreased, an increase occurred in milk/milk products, fruits, bottled water, fruit/vegetable juices and soft drinks (P<005). The highest values for foods and beverages were mostly found in couples, while the lowest ones were from solitary males. Exceptions were observed for cereals, eggs, milk/milk products, vegetables, fruits and non-alcoholic beverages, higher in solitary females; and for sugar/sugar products and alcoholic beverages, higher in solitary males. Over time, total energy and carbohydrates decreased while proteins and saturated fatty acids increased (P<0001). Lipids increased in solitary males and couples (P<005). Simple sugars increased in solitary males but decreased in solitary females and couples (P<005). Conclusions The increases in fruits and vegetables in solitary females accord with a healthier food pattern, but overall imbalances in the macronutrient profile for all elderly households may imply a decreasing diet quality.

Abstract
This paper presents a method for the automatic analysis of macroarray (dot blot) images. The system developed receives as input a dot blot image, corrects it for grid rotation, identifies the visible markers and provides an evaluation of the status of each marker (ON/OFF). Two experiments were carried out to evaluate the detection and classification stages. A total of 222 test images were produced from 6 original dot blot images, with various rotations, translations, contrast and noise level. Over 7500 markers were identified automatically and compared to manual reference. The RMS error in positioning the molecular marker center was between 1.1 and 3.8 pixels and the marker radius error less than 4%. The automatic classification of markers (ON/OFF) was compared to the classification by 3 human experts, using 10 test images. The overall accuracy evaluated on 5118 markers was 94.0%. For those markers that had the same evaluation by all 3 experts, the classification accuracies were 96.6% (ON) and 95.9% (OFF).

Abstract
This paper presents a domain-specific querying language for model-driven spreadsheets. We briefly show the design of the language and present in detail its implementation, from the denormalization of data and translation of our user-friendly query language to a more efficient query, to the execution of the query using Google. To validate our work, we executed an empirical study, comparing QuerySheet with an alternative spreadsheet querying tool, which produced positive results.