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The United States of America and Brazil are the world’s first and second-largest biofuels producers. The United States (U.S.) has dedicated a significant portion of agricultural land for crops to produce biodiesel, while Brazil has been using sugar cane as raw material to produce ethanol. To make the world’s top producers in global biofuel markets, various institutions in each country have played significant roles. These institutions include renewable energy legislators, bioenergy policymakers, and energy ministries of their governments. This study delineates the historical role of these institutions responsible for the sustainable development of biofuel industries in both countries. It also provides an overview of economic impacts as a result of institutional decisions. The study reveals that systematic legislations and sustainable and robust renewable energy policies of government institutions have helped the U.S. and Brazil to boost their bio-economies. As both countries intend to keep expanding their biofuel productions, the role of key government institutions is vital in the sustainability of biofuels.

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IntroductionThe present work proposes a model based on Markov Logic Network (MLN) [16] for representing emergency situations involving smoke and fire on offshore petroleum platforms. The model is tested for two important situations, FIRE and EVACUATE. In the FIRE situation, fire is observed due to smoke at some place on the platform, and all workers need to muster to their primary muster station. In the EVACUATE situation, the fire is escalated so that some escape routes to the primary muster station are blocked and all personnel needs to muster at the lifeboat or alternative muster station. The purpose of this work is to have a model that can be used by a software agent so that the agent can exhibit human-like situation awareness (SA). Such agents can subsequently be used, for example, in training simulators to enrich trainees' experience by showing them various scenarios in which the agent shows recognition of different situations (to makes various decisions). A participant can learn from the agent what information is important in a given scenario for correct SA.Representing the emergency response of agents operating in a virtual environment (VE) is a challenging and active research area. Emergencies on board can arise from Abstract Situation awareness is the first and most important step in emergency management. It is a dynamic step involving evolving conditions and environments. It is an area of active research. This study presents a Markov Logic Network to model SA focusing on fire accidents and emergency evacuation. The model has been trained using empirical data obtained from case studies. The case studies involved human participants who were trained for responding to emergencies involving fire and smoke using a virtual environment. The simulated (queried) and empirical findings are reasonably consistent. The proposed model enables implementing an agent that exploits environmental cues and cognitive states to determine the type of emergency currently being faced. Considering each emergency type as a situation, the model can be used to develop a repertoire of situations for agents so that the repertoire can act as an agent's experience for later decision-making. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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