Abstract
Co-generation plants have become mainstream energy production facilities at the demand side owing to their high efficiency and flexibility in operation. During the transition to more integrated energy supply, trading of energy mix will become an important issue, where a retailer is expected to play a more active role. This paper discusses the design of retailer's optimal contract with asymmetric information. Bilateral relationship between retailer and consumers can be described as an information game and is characterized by package contracts based on publicly observable information only. First, a mathematical model for the optimal contract design problem involving two coupled energy markets is established. Then, an equivalent reduced model is obtained by several certified lemmas and theorems. Consumer behaviors behind each reduction step are revealed. Thereafter, the market equilibrium is characterized with a proof of existence, revealing the impact of asymmetric information on the retailer's strategy. An illustrative example with locational marginal price based heat-power market is presented. Case studies confirm the theoretical analysis and show that our model can promote retailer's profit. The impact of several factors, such as the probability and reservation utility level, has been tested, providing fundamental insights into strategic behavior in multi-energy market under asymmetric information.

Abstract
The role of digital technologies for fostering sustainability and efficiency in forest-based supply chains is well acknowledged and motivated several studies in the scope of precision forestry. Sensor technologies can collect relevant data in forest-based supply chains, comprising all activities from within forests and the production of the woody raw material to its transformation into marketable forest-based products. Advanced planning systems can help to support decisions of the various entities in the supply chain, e.g., forest owners, harvest companies, haulage companies, and forest product processing industry. Such tools can help to deal with the complex interdependencies between different entities, often with opposing objectives and actions-which may increase efficiency of forest-based supply chains. This paper analyzes contemporary literature dealing with digital technologies in forest-based supply chains and summarizes the state-of-the-art digital technologies for real-time data collection on forests, product flows, and forest operations, as well as planning systems and other decision support systems in use by supply chain actors. Higher sustainability and efficiency of forest-based supply chains require a seamless information flow to foster integrated planning of the activities over the supply chainthereby facilitating seamless data exchange between the supply chain entities and foster new forms of collaboration. Therefore, this paper deals with data exchange and multi-entity collaboration aspects in combination with interoperability challenges related with the integration among multiple process data collection tools and advanced planning systems. Finally, this interdisciplinary review leads to the discussion of relevant guidelines that can guide future research and integration projects in this domain.

Abstract
This paper describes the implementation of a simulated bioinspired 3D model, which was moved through segmented gestures using fractional calculation segmentation methods. It was observed that for the increase in the detection of such gestures from this segmentation an improvement in the recognition and standardization of gesture images using the FODPSO method would be obtained. We used the AlexNet neural network for training and recognition of the processed gestures, which resulted in a simulated 3D model of a spider moved by gestures recognized through a webcam, which had an accuracy of approximately 98% recognition through the neural network.

Abstract

Abstract
Smart Grid technologies enable the intelligent integration and management of distributed energy resources. Also, the advanced communication and control capabilities in smart grids facilitate the active participation of aggregators at different levels in the available electricity markets. The portfolio optimization problem consists in finding the optimal bid allocation in the different available markets. In this scenario, the aggregator should be able to provide a solution within a timeframe. Therefore, the application of metaheuristic approaches is justified, since they have proven to be an effective tool to provide near-optimal solutions in acceptable execution times. Among the vast variety of metaheuristics available in the literature, Differential Evolution (DE) is arguably one of the most popular and successful evolutionary algorithms due to its simplicity and effectiveness. In this paper, the use of DE is analyzed for solving the portfolio optimization problem in electricity markets. Moreover, the performance of DE is compared with another powerful metaheuristic, the Particle Swarm Optimization (PSO), showing that despite both algorithms provide good results for the problem, DE overcomes PSO in terms of quality of the solutions.

Abstract
a Rural areas present vicissitudes and specific characteristics that need to be properly addressed towards guarantying and defining a sustainable and adjusted mobility to its population demand. The Mobility as a Service (MaaS) - a key component of any future mobility system -will play an important role in enhancing social inclusion in rural areas. Creating the opportunity to integrate various transport modes and functionalities, this system will allow the access to the information, in a personalized way. As pointed in the pilot cases presented, using a case studies methodology approach, the MaaS can integrate various transport modes, allowing the rural population to increase their quality of life. This survey also contributes to leverage the implementation of a MaaS pilot in the Alto Minho Region (within the scope of the Smob Project).