Abstract
Wind energy sources have created new challenges in power system scheduling to follow the network load. Gas fired units with high ramping could better deal with inherent uncertainties of wind power compared to other power generation sources. The natural gas system constraints affect the flexibility of natural gas- fired power plants in the electrical market. In this paper, three solutions have been proposed to cover the challenges of gas system constraints and the uncertainty of wind power: 1) using information-gap decision theory (IGDT) based robust approach to address the uncertainty caused by the intrinsic nature of wind power, 2) Integration of compressed air energy storage (CAES), and demand response (DR) in day-ahead scheduling and 3) considering flexible ramping products in order to ensure reliable operations, there must be enough ramp to eliminate the variability of wind power in real-time dispatch stage. This paper proposes an IGDT-based robust security constrained unit commitment (SCUC) model for coordinated electricity and natural gas systems with the integration of wind power and emerging flexible resources while taking the flexible ramping products into account. Numerical tests demonstrate the effect of emerging flexible resources on a reduction of system operation cost and the uncertainty of predicted wind power.

Abstract
The growing needs in exploring ocean resources have been pushing the length and complexity of autonomous underwater vehicle (AUV) missions, leading to more stringent energy requirements. A promising approach to reduce the energy consumption of AUVs is to use variable buoyancy systems (VBSs) as a replacement or complement to thruster action, since VBSs only require energy consumption during limited periods of time to control the vehicle's floatation. This paper presents the development of an electrohydraulic VBS to be included in an existing AUV for shallow depths of up to 100 m. The device's preliminary mechanical design is presented, and a mathematical model of the device's power consumption is developed, based on data provided by the manufacturer. Taking a standard mission profile as an example, a comparison between the energy consumed using thrusters and the designed VBS is presented and compared.

Abstract
When we look around us, we see people of all ages using all kinds of technology, more specifically, devices like cellphones are used by younglings, adults and older people. There is no escaping it. Consequently, we decided to analyse how technologies affect the lives of these men and women, focusing on an older age group, mainly because of the lack of studies that focus on people over 65. If most of them are able to speak, focus, and learn, how many of them have given in to the new waves of evolution that have feasted on the world for the past few years? That is exactly what we are trying to find out: How older people react to new technology (more specifically to information and communication technologies or ICT), how often and how they use it. For this study, we decided to focus on the littoral north of Portugal, given that the author-group’s members live along the coast line. A survey was performed (with 56 valid responses) as were eight interviews. Regarding the view that the older people we have interviewed have of millennials, most of our respondents show some concern. Notably, they see the Internet as an addiction of the younger elements in society, contributing to them getting into trouble, losing interest in school, meeting up with strangers and only being concerned with being popular on social media. As concerns ICT usage by elders, the psychological component of the “I can’t" does not help them.

Abstract
This paper addresses the participation of an aggregator of small prosumersin the energy and tertiary reserve markets. A two-stage stochastic optimization model is proposed to exploit the load and generation flexibility of the prosumers. The aim is to define energy and tertiary reserve bids to minimize the net cost of the aggregator buying and selling energy in the day-ahead and real-time markets, as well as to maximize the revenue of selling tertiary reserve during the real-time stage. Scenario-based stochastic programming is used to deal with the uncertainties of photovoltaic power generation, electricity demand, outdoor temperature, end-users' behavior, and preferences. A case study of 1000 small prosumers from MIBEL is used to compare the proposed strategy to two other strategies. The numerical results show that the proposed strategy reduces the bidding net cost of the aggregator by 48% when compared to an inflexible strategy typically used by retailers.

Abstract
Minimally invasive medical devices can greatly benefit from Narrow Band Imaging (NBI) diagnostic capabilities, as different wavelengths allow penetration of distinct layers of the gastrointestinal tract mucosa, improving diagnostic accuracy and targeting different pathologies. An important performance parameter is the light intensity at a given power consumption of the medical device. A method to increase the illumination intensity in the NBI diagnostic technique was developed and applied to minimally invasive medical devices (e.g., endoscopic capsules), without increasing the size and power consumption of such instruments. Endoscopic capsules are generally equipped with light-emitting diodes (LEDs) operating in the RGB (red, green, and blue) visible light spectrum. A polydimethylsiloxane (PDMS) mu-lens was designed for a maximum light intensity at the target area of interest when placed on top of the LEDs. The PDMS mu-lens was fabricated using a low-cost hanging droplet method. Experiments reveal an increased illumination intensity by a factor of 1.21 for both the blue and green LEDs and 1.18 for the red LED. These promising results can increase the resolution of NBI in endoscopic capsules, which can contribute to early gastric lesions diagnosis.

Abstract
Retailers need demand forecasts at different levels of aggregation in order to support a variety of decisions along the supply chain. To ensure aligned decision-making across the hierarchy, it is essential that forecasts at the most disaggregated level add up to forecasts at the aggregate levels above. It is not clear if these aggregate forecasts should be generated independently or by using an hierarchical forecasting method that ensures coherent decision-making at the different levels but does not guarantee, at least, the same accuracy. To give guidelines on this issue, our empirical study investigates the relative performance of independent and reconciled forecasting approaches, using real data from a Portuguese retailer. We consider two alternative forecasting model families for generating the base forecasts; namely, state space models and ARIMA. Appropriate models from both families are chosen for each time-series by minimising the bias-corrected Akaike information criteria. The results show significant improvements in forecast accuracy, providing valuable information to support management decisions. It is clear that reconciled forecasts using the Minimum Trace Shrinkage estimator (MinT-Shrink) generally improve on the accuracy of the ARIMA base forecasts for all levels and for the complete hierarchy, across all forecast horizons. The accuracy gains generally increase with the horizon, varying between 1.7% and 3.7% for the complete hierarchy. It is also evident that the gains in forecast accuracy are more substantial at the higher levels of aggregation, which means that the information about the individual dynamics of the series, which was lost due to aggregation, is brought back again from the lower levels of aggregation to the higher levels by the reconciliation process, substantially improving the forecast accuracy over the base forecasts.