Abstract
Despite the recent popularity achieved by the modern X-band SAR sensors, mainly due to their high spatial resolutions which enable the detection of deformation components impossible so far, such as thermal expansion, SAR C-band sensors continue to be of great utility and with a great future in the deformation monitoring field, namely for critical structure monitoring, such as dams. The new ESA missions (Sentinel-1A and 1B) and the extension of the Canadian Radarsat mission corroborate this finding. In this paper the possibility of using spacebome SAR sensors for dam monitoring is addressed in terms of feasibility and applications. The presented results show the potential of C-band sensors for the particular case of dam monitoring and can be handful to recognize the applicability of new Sentinel-1 data (since 2014) for continuous monitoring of dam deformations. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
In this paper a cone tapered surface plasmon resonance (SPR) based chemical fiber sensor is fabricated and demonstrated for the detection of low water content in ethanol. Here the 11nm thickness of Aluminum (Al) is used to coat tip of probe to generate Plasmon wave. The output power has been found to increase linearly with water content in the range 1-10% due to the increase in refractive index (RI) of ethanolabove which, as the percentage of water increases in step of 20% it shows abrupt decrease in RI hence decrease in the output power. The compact size of sensor and its low cost fabrication makes it useful for many applications in the field of chemical and biochemical sensing. © 2016 Author(s).

Abstract
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stakeholders. Having reliable electricity consumption forecasts can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study regarding the forecast of electricity consumption using a methodology based on Hybrid neural Fuzzy Inference System (HyFIS). The proposed approach considers two distinct strategies, namely one strategy using only the electricity consumption as the input of the method, and the second strategy uses a combination of the electricity consumption and the environmental temperature as the input. A case study considering the forecasting of the consumption of an office building using the proposed methodologies is also presented. Results show that the second strategy is able to achieve better results, hence concluding that HyFIS is an appropriate approach to incorporate different sources of information. In this way, the environmental temperature can help the HyFIS method to achieve a more reliable forecast of the electricity consumption. © 2016 IEEE.

Abstract
Knowledge builds on itself. Scientific progress is achieved through piecewise advances, and is based on the enlightenment of prior evidence and discoveries. Accessing prior information has been a tremendously complex venture for centuries, and restricted to the privileged few. Technological progress and namely, the advent of Internet have opened a world of possibilities, including the instant sharing and diffusion of information. Reaping the full benefits of technological advances has however been prevented by the prerogatives of the publishing industry, which have been increasingly challenged over the last two decades. Major historical milestones include the creation of ArXiv.org, an online repository of electronic preprints in 1991; the launch of SciELO in Brazil in 1997 and its extension to 14 countries; the foundation of PLOS by the Public Library of Science, established as an alternative to traditional publishing and nowadays known as PLOS ONE, which is by far the world’s largest series of journals with over 30,000 papers published in 2015; the Budapest Declaration on Open Access in 2002; the campaign Access2Research and the US Fair Access to Science and Technology Research Act, a foundational piece in the establishment of Open Access in the USA; and the initiative of the European Commission to require all research publications funded under Horizon2020 to be openly accessible, free of charge.  All these initiatives converged towards the same aim: fostering free and unrestricted access to publications, so as to ensure the widespread and rapid diffusion of research findings within, across and outside scientific communities. (...)

Abstract
This study analyses how drivers of PSS enable supplier companies to adoption integrated solutions in B2B relationships. Two case studies were performed in two large supplier companies that operate in different segments, which represents a significant Brazilian market share. The findings show that this adopted PSS strategies enable the two companies to operate their customer's systems and to price their offerings according to the established performance. The strategies adopted by the companies provide a more rigorous knowledge about the products and services, attention to promoting the buyers' support over the life cycle and promote the relationships with buyers. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
In this paper, a novel real-time rolling horizon optimization framework for the optimal operation of a smart household is presented. A home energy management system (HEMS) model based on mixed-integer linear programming (MILP) is developed in order to minimize the energy procurement cost considering that the household is enrolled in a dynamic pricing tariff scheme. Several assets such as a photovoltaic (PV) installation, an electric vehicle (EV) and controllable appliances are considered. Additionally, the energy from the PV and the EV can be used either to satisfy the household demand or can be sold back to the grid. The uncertainty of the PV production is estimated using time-series models and performing forecasts on a rolling basis. Also, appropriate distribution is used in order to model the uncertainty related to the EV. Besides, several parameters can be updated in real-time in order to reflect changes in demand and consider the end-user's preferences. The optimization algorithm is executed on a regular basis in order to improve the results against uncertainty.