Abstract
Customers' response is an important topic in direct marketing. This study proposes a data mining response model supported by random forests to support the definition of target customers for banking campaigns. Class imbalance is a typical problem in telemarketing that can affect the performance of the data mining techniques. This study also contributes to the literature by exploring the use of class imbalance methods in the banking context. The performance of an undersampling method (the EasyEnsemble algorithm) is compared with that of an oversampling method (the Synthetic Minority Oversampling Technique) in order to determine the most appropriate specification. The importance of the attribute features included in the response model is also explored. In particular, discriminative performance was enhanced by the inclusion of demographic information, contact details and socio-economic features. Random forests, supported by an undersampling algorithm, presented very high prediction performance, outperforming the other techniques explored.

Abstract
Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs) is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

Abstract
Image quality assessment has been a topic of intense research over the last decades. Although its application to other disciplines is growing tremendously, its use in retinal imaging is still immature and some fundamental challenges remain unsolved. Thus, we present a research methodology for the objective assessment of the quality in retinal images. The methodology can be used as a preliminary step in any computer-aided system, and is composed of four main steps: the location of the region-of-interest, the extraction of relevant image properties and their analysis by feature selection, and the final binary classification into two classes (good and poor quality). The experimental results demonstrate the adequacy of the proposed methodology in this context, being able to objectively assess the quality of retinal images with an accuracy over 99%.

Abstract
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 study focuses on the concepts and developments necessary in order to make possible that residential clients can participate in a market environment with their electrical flexibility, also considering distribution system operator (DSO) needs when gird is under stress caused by any technical constraint. Moreover, than the concept behind it is necessary to consider several developments: (i) a low layer where residential assets will live in customer’s houses; (ii) a high-level layers where market tools and DSO management tools will live; (iii) an intermediate layer, which bridge the gap between the low layer and high layer. 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. © 2017 Institution of Engineering and Technology. All rights reserved.

Abstract
Objectives: Fluid overload (FO) is frequently present in peritoneal dialysis (PD) patients and is associated with markers of malnutrition, inflammation, and atherosclerosis/calcification (MIAC) syndrome. We examined the relationships in stable PD patients between phase angle (PhA) and the spectrum of uremic vasculopathy including vascular calcification and arterial stiffness and between PhA and changes in serum fetuin-A levels. Methods: Sixty-one stable adult PD patients were evaluated in a cross-sectional study (ST1). Phase angle was measured by multifrequency bioimpedance analysis (InbodyS10, Biospace, Korea) at 50 kHz. Augmentation index (AI), a surrogate marker of arterial stiffness, was assessed by digital pulse amplitude tonometry (Endo PAT, Itamar Medical, Caesarea, Israel). Vascular calcification was assessed by simplified calcification score (SCS). Serum fetuin-A levels were measured by ELISA (Thermo scientific; Waltham, MA, USA). Serum albumin was used as a nutritional marker, and serum C-reactive protein (CRP) was used as an inflammatory marker. The same assessments were carried out longitudinally (ST2) in the first 33 patients who completed 1 year of evaluation in ST1. Results: In ST1, patients with PhA < 6(omicron) had higher CRP levels, AI, and SCS and lower serum albumin and fetuin-A levels, in comparison with patients with PhA >= 6(omicron). In addition, PhA was a predictor of both AI (beta = -0.351, p = 0.023) and SCS >= 3 (EXP (B) = 0.243, p = 0.005). In ST2, the increase of PhA over time was associated with decreases in both AI (r = -0.378, p = 0.042) and CRP levels (r= -0.426, p = 0.021), as well as with the increase in serum fetuin-A levels (r = 0.411, p = 0.030). Conclusions: Phase angle predicts both arterial stiffness and vascular calcification in stable PD patients.

Abstract
The problem of electromagnetic wave propagation in time varying media is very old, but in recent years it has been revisited at a more fundamental level leading to the introduction of several new concepts, such as Time Refraction. These concepts explore the symmetries between space and time and can be transposed to different fields by establishing powerful analogies between effects in Electrodynamics, Optics and problems in Quantum Cosmology and in what is sometimes called Analogue Gravity. We examine the alteration of the ordinary (spatial) Fresnel laws of refraction at the interface between two media when the optical properties of one of the media varies in time.