Abstract
Industrial Internet and Industrial Internet of Things are emerging concepts that concern the use of Internet technologies on industrial environments. The main objective of such architectural visions is allowing a tight and seamless integration between all the functional units and layers that compose industrial processes, from the lowest levels (e.g. field level devices such as sensors and actuators) to the higher layers, including management, logistics and maintenance. This kind of architecture promises, among other advantages, improving efficiency and flexibility, reduce installation and maintenance costs and reduce unplanned downtime. However, industrial processes often encompass functionalities like closed-loop control of physical processes that are highly critical and have strict timeliness requirements. These requirements are not satisfied by normal Ethernet-based systems. Standards such as IEEE AVB and TSN are addressing this problem, enhancing the real-time properties of Ethernet. However, considering the information presently available, such standards still present some limitations and inefficiencies. This paper reports the extension of HaRTES, an Ethernet-based real-time architecture originally developed for use at the lower layers of industrial scenarios, with MAC Bridge standard functionalities, to make it capable of being integrated on Industrial Internet of Things frameworks. The paper also presents preliminary results obtained with a prototype realization of the extended HaRTES switch.

Abstract

Abstract
This paper presents a framework for management of flexible energy loads in the context of the Internet of Things and the Smart Grid. The framework takes place in the European project Arrowhead, and aims at taking advantage of the flexibility (in time and power) of energy production and consumption offered by sets of devices, appliances or buildings, to help at solving the issue of fluctuating energy production of renewable energies. The underlying concepts are explained, the actors involved in the framework, their incentives and interactions are detailed, and a technical overview is provided. An implementation of the framework is presented, as well as the expected results of the pilots.

Abstract
The reuse of treated wastewater, in particular for irrigation, is an increasingly common practice, encouraged by governments and official entities worldwide. Irrigation with wastewater may have implications at two different levels: alter the physicochemical and microbiological properties of the soil and/or introduce and contribute to the accumulation of chemical and biological contaminants in soil. The first may affect soil productivity and fertility; the second may pose serious risks to the human and environmental health. The sustainable wastewater reuse in agriculture should prevent both types of effects, requiring a holistic and integrated risk assessment. In this article we critically review possible effects of irrigation with treated wastewater, with special emphasis on soil microbiota. The maintenance of a rich and diversified autochthonous soil microbiota and the use of treated wastewater with minimal levels of potential soil contaminants are proposed as sine qua non conditions to achieve a sustainable wastewater reuse for irrigation.

Abstract
The variable and uncertain nature of the leading renewable energy resources, such as wind power generation, imposes the development of a sophisticated balance mechanism between supply and demand to maintain the consistency of a power system. In this study, a two stage stochastic programming model is proposed to procure the required load-following reserves from both generation and demand side resources under high wind power penetration. Besides, a novel load model is introduced to procure flexible reserves from industrial clients. Load following reserves from load serving entities (LSE) are also taken into account as well as network constraints, load shedding and wind spillage. The proposed methodology is applied to an illustrative test system, as well as to a 24-node system.

Abstract
Common breast cancer treatment techniques, such as radiation therapy or the surgical removal of the axillary lymphatic nodes, result in several impairments in women's upper-body function. These impairments include restricted shoulder mobility and arm swelling. As a consequence, several daily life activities are affected, which contribute to a decreased quality of life (QOL). Therefore, it is of extreme importance to assess the functional restrictions caused by cancer treatment, in order to evaluate the quality of procedures and to avoid further complications. Although the research in this field is still very limited and the methods currently available suffer from a lack of objectivity, this highlights the relevance of the pioneer work presented in this paper, which aims to develop an effective method for the evaluation of the upper-body function, suitable for breast cancer patients. For this purpose, the use of both depth and skeleton data, provided by the Microsoft Kinect, is investigated to extract features of the upper-limbs motion. Supervised classification algorithms are used to construct a predictive model of classification, and very promising results are obtained, with high classification accuracy.