Abstract
In the context of interspecies play involving humans, we find limitations when it comes to understanding most species. One reason for this may be the fact that we tend to anthropomorphize the other to be able to empathize with it. In light of this, how can we infer communication signs of other species so we are able to connect with the nonhuman world? We look for answers to this question by adopting a phenomenological approach that allows us to decentre from the anthropocentric perspective. We highlight animal studies, especially those that extend to them the notion of play, and the studies on interspecies playful interaction conducted in the context of animal- computer interaction. In addition, we propose considering empathy as an interspecies dialogical bridge with nonhumans. Finally, we argue about an expansion of the field of interaction design as an approach to the connection with the nonhuman world.

Abstract
Algorithmic problem solving is a way of approaching and solving problems by using the advances that have been made in the principles of correct-by-construction algorithm design. The approach has been taught at first-year undergraduate level since September 2003 and, since then, a substantial amount of learning materials have been developed. However, the existing materials are distributed in a conventional and static way (e.g. as a textbook and as several documents in PDF format available online), not leveraging the capabilities provided by modern collaborative and open-source platforms. In this paper, we propose the creation of an online, open-source repository of interactive learning materials on algorithmic problem solving. We show how the existing framework Mathigon can be used to support such a repository. By being open and hosted on a platform such as GitHub, the repository enables collaboration and anyone can create and submit new material. Furthermore, by making the material interactive, we hope to encourage engagement with and a better understanding of the materials.

Abstract
The development of small-scale power generation units based on biomass gasification is an effective mean to meet the growth interest of deployment of local power generation exploiting endogenous renewable energy sources. However, significant research and development activities are required towards the deployment of cost-effective solutions suitable to be used in several applications and with different biomass feedstock. For this purpose, a flexible experimental setup is required to be developed. This paper proposes a critical review of the current state of the art of the available technologies suitable for small-scale power generation using biomass gasification. The main guidelines to develop cost-effective solutions are identified and the conceptual framework of the experimental setup is proposed. Also, the operational specifications are presented.

Abstract
Current approaches for risk management in energy market participation mostly refer to portfolio optimization for long-term planning, and stochastic approaches to deal with uncertainties related to renewable energy generation and market prices variation. Risk assessment and management as integrated part of actual market negotiation strategies is lacking from the current literature. This paper addresses this gap by proposing a novel model for decision support of players' strategic participation in electricity market negotiations, which considers risk management as a core component of the decision-making process. The proposed approach addresses the adaptation of players' behaviour according to the participation risk, by combining the two most commonly used approaches of forecasting in a company's scope: the internal data analysis, and the external, or sectorial, data analysis. The internal data analysis considers the evaluation of the company's evolution in terms of market power and profitability, while the sectorial analysis addresses the assessment of the competing entities in the market sector using a K-Means-based clustering approach. By balancing these two components, the proposed model enables a dynamic adaptation to the market context, using as reference the expected prices from competitor players, and the market price prediction by means of Artificial Neural Networks (ANN). Results under realistic electricity market simulations using real data from the Iberian electricity market operator show that the proposed approach is able to outperform most state-of-the-art market participation strategies, reaching a higher accumulated profit, by adapting players' actions according to the participation risk.

Abstract
Engaging the residential consumers and providing the best tariffs for their randomized behavior is one of the major barriers to demand response (DR) implementation. Additionally, DR offers submitted by aggregators or retailers are not consumer-specific, which turns it even more difficult for the engagement of consumers in these programs. In order to address this issue, this paper describes a methodology based on causal inference between dynamic DR tariffs and observed residential electricity consumption (resolution of 30 minutes) to estimate consumers' consumption elasticity. Ultimately, the aim of this approach is to aid aggregators and retailers to better tune DR offers to consumer needs and so to enlarge the response rate to their DR programs.

Abstract
Viscosity measurements of a solution are crucial for many processes involving fluid flows. The current optical fiber viscometers are complex and, in some cases, provide indirect measurements of viscosity through other non-optical effects. We developed a miniaturized optical fiber probe capable of providing an optical interferometric measurement of the viscosity of small volumes of a liquid viscous medium (less than 50 pL). The probe consists of an air cavity with a small access hole for fluids, which resulted from a simple post-processing of a hollow capillary tube. The structure behaves as a two-wave interferometer, where the intensity of the signal is sensible to the position of the air-fluid interface inside the cavity. The fluid displacement over time is obtained by monitoring the signal intensity variations, at 1550 nm, during the process of removing the sensing head from a fluid solution. Multiple sucrose solutions with viscosities ranging from 2.01 to 16.1 mPa.s were used for calibration. The viscosity of the solution is measured through the fluid evacuation velocity in the first 300 ms of resolved oscillations during the evacuation process. Reproducibility measurements, the influence of temperature, and the access hole dimensions are also addressed. The application to biological fluids is important to be considered in future studies.