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Writing is an essential part of a successful career in science. As such, many undergraduate science courses have begun to implement writing assignments that reflect "real-world" applications and focus on a critical analysis of current literature; these assignments are often in the form of a review or a research proposal. The semester-long project described herein is a unique marriage of these two ideas: students first select a topic and conduct a literature review, and then choose an area of that same topic to investigate further in a peer-reviewed grant proposal. A modified version of this project, which incorporates peer-reviewed oral presentations, is also discussed. This project is designed for an upper-level undergraduate course, typically having 15−20 students, and the approach (or parts of the approach) has been successfully incorporated in an advanced organic chemistry course, a biochemistry capstone course, and courses in endocrinology, as well as ecophysiology.

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Recovery of interdependent infrastructure networks in the presence of catastrophic failure is crucial to the economy and welfare of society. Recently, centralized methods have been developed to address optimal resource allocation in postdisaster recovery scenarios of interdependent infrastructure systems that minimize total cost. In real-world systems, however, multiple independent, possibly noncooperative, utility network controllers are responsible for making recovery decisions, resulting in suboptimal decentralized processes. With the goal of minimizing recovery cost, a best-case decentralized model allows controllers to develop a full recovery plan and negotiate until all parties are satisfied (an equilibrium is reached). Such a model is computationally intensive for planning and negotiating, and time is a crucial resource in postdisaster recovery scenarios. Furthermore, in this work, we prove this best-case decentralized negotiation process could continue indefinitely under certain conditions. Accounting for network controllers' urgency in repairing their system, we propose an ad hoc sequential game-theoretic model of interdependent infrastructure network recovery represented as a discrete time noncooperative game between network controllers that is guaranteed to converge to an equilibrium. We further reduce the computation time needed to find a solution by applying a best-response heuristic and prove bounds on ε-Nash equilibrium, where ε depends on problem inputs. We compare best-case and ad hoc models on an empirical interdependent infrastructure network in the presence of simulated earthquakes to demonstrate the extent of the tradeoff between optimality and computational efficiency. Our method provides a foundation for modeling sociotechnical systems in a way that mirrors restoration processes in practice.