The challenges posed to humanity by climate change require innovative approaches. Well-designed games are powerful tools with the potential to support solving climate related challenges. In this article, we present a mapping review study of games that address climate change issues (climate games). In a search and selection process, we identified 115 climate games that were classified by applying a newly developed game typology. This allowed gaining an overview of existing climate games and identifying potentials for future game development. The game classification revealed that the majority of climate games (75%) were designed for learning purposes and addressed heterogeneous target audiences such as students, professionals, or the “general public”. The identified games covered a wide range of characteristics, e.g., regarding the topic addressed, player interaction, game-play, level of abstraction, or the media used for play. Nevertheless, we identified areas where only few or no games were found. These “gaps” provide opportunities where future games could help solving climate challenges and include, amongst others, games designed for professionals to address specific needs and games that create a direct impact outside the game environment. Regarding game design, experimenting with the abstraction of games is currently underexplored and offers potential for future developments.
The nuclear fuel cycle comprises a series of industrial processes which involve the production of electricity from uranium in nuclear power reactors. In Brazil the conversion of uranium hexafluoride (UF6) into uranium dioxide (UO2) takes place in Resende (RJ) at the Nuclear Fuel Factory (FCN). The process generates liquid effluents with significant concentrations of uranium, which might be treated before being discharged into the environment. This study investigates the recovery of uranium from three distinct liquid effluents: one with a high carbonate content and the other with an elevated fluoride concentration. This paper also presents a study on carbonate removal from an effluent that consists of a water-methanol solution generated during the filtration of the yellow cake (ammonium uranyl tricarbonate). The results showed that: (1) the uranium from the carbonated solution can be recovered through the ion exchange technique using the strong base anionic resin IRA 910-U, as the carbonate has been removed as CO2 after heating; (2) the most suitable technique to recover uranium from the fluoride solution is its precipitation as (NH4)2UO4F2 (ammonium fluorouranate peroxide), (3) the solution free of carbonate can be added to the fluoride solution and the uranium from the final solution can be recovered by precipitation as ammonium fluorouranate peroxide as well; (4) the carbonate from the water-methanol solution can be recovered as calcium carbonate through the addition of calcium chloride, or it can be recovered as ammonium sulphate through the addition of sulphuric acid. The ammonium sulphate product can be used as a fertilizer.
The development of Advanced Driver Assistance Systems (ADAS) is rapidly growing. However, most of the ADAS require field test, which is expensive, unpredictable and time consuming. In this paper we propose a multiagent-based driving simulator which integrates a human factor analysis suite and enables rapid and low-cost experimentation of mobile-device ADAS. Our architecture uses a microscopic simulator and a serious-game-based driving simulator. The latter allows the user to control a vehicle and change the correspondent simulation state in the microscopic simulator. The driving simulator also connects to an Android device and sends several kinds of data, such as current GPS coordinates or transportation network data. One important feature of this architecture is its suitability to serve as an appropriate means to conduct behaviour elicitation through peer-designed agents, so as to improve modelling of various driving styles accounting for different aspects of preferences and perception abilities, as well as other performance measures related to drivers' interaction with ADAS solutions. The potentials of our approach to aid experiments in human factor analysis are still to be tested, but are undoubtedly huge and encouraging.
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