Institutional Insecurity

Already the world's second biggest energy consumer, China is presently on track to become the world's largest user of energy by the year 2030. This phenomenon has kindled a profusion of literature to address how China will meet this demand and the affect it will have on global energy security. Current analyses overwhelmingly focus on the notion that energy security is based on the assurance of reliable energy supply at a reasonable price, invoking a disproportionate emphasis on the security of China's oil supply. This is largely a result of the psychological elements arising from the uncertainty of guaranteed oil supplies for China. In reality, however, oil imports are merely one dimension of China's energy security concerns and not even the most important. Far less attention has been given to the more obscure though imperative factor of China's domestic energy institutions and their role in meeting the country's energy security challenges both at home and abroad

The globalization of Chinese energy companies

This repository item contains a report from the Boston University Global Economic Governance Initiative. The Global Economic Governance Initiative (GEGI) is a research program of the Center for Finance, Law & Policy, the Frederick S. Pardee Center for the Study of the Longer-Range Future, and the Frederick S. Pardee School of Global Studies. It was founded in 2008 to advance policy-relevant knowledge about governance for financial stability, human development, and the environment

Collaborative Deep Reinforcement Learning for Joint Object Search

We examine the problem of joint top-down active search of multiple objects under interaction, e.g., person riding a bicycle, cups held by the table, etc.. Such objects under interaction often can provide contextual cues to each other to facilitate more efficient search. By treating each detector as an agent, we present the first collaborative multi-agent deep reinforcement learning algorithm to learn the optimal policy for joint active object localization, which effectively exploits such beneficial contextual information. We learn inter-agent communication through cross connections with gates between the Q-networks, which is facilitated by a novel multi-agent deep Q-learning algorithm with joint exploitation sampling. We verify our proposed method on multiple object detection benchmarks. Not only does our model help to improve the performance of state-of-the-art active localization models, it also reveals interesting co-detection patterns that are intuitively interpretable

Thermal Field Investigations and Applications to Integral Abutment Bridges with FRP Panels

Expansion joints are often considered as one of the most vulnerable elements affecting the sustainability of traditional jointed bridges. Over the past several decades, a new type of integral abutment bridge (IAB) has been proposed, where the joints are eliminated at the abutments and/or along the length of the bridges. Although with wide acceptances, the IABs have not been largely applied in practice. Many arguments are unsettled and there are no national design guidelines currently. Among all, the thermal behavior is one of the most concerned issues, and that, to a large extent, limits the maximum length of IABs that can be constructed. Under this circumstance, a new type of fiber reinforced polymer (FRP) materials, with special material properties, are considered as an alternative to replace the traditional concrete and steel materials. However, the studies on the performances of both IABs and FRP bridges are not adequate. Therefore, an investigation on the thermal behaviors of IABs and FRP bridges is conducted. Then, an effort is made to analyze the responses by combining the FRPs with IABs, and to verify that such a configuration will help resolve the thermal issues of IABs. For FRP bridges, (1) the temperature distributions of a GFRP panel are discussed based on a field monitoring program conducted at the state of Kansas; (2) the influencing factors on the temperature distributions are studied, including the material property, environmental condition, and section hollowness; (3) the thermal gradients of the FRP panel bridges are proposed referring to the AASHTO LRFD design code; and (4) the jointed bridges’ performances, after replacing traditional slabs by FRP panels, are numerically analyzed. For IABs, (1) the thermal responses of the first full IAB in the state of Louisiana, Caminada Bay Bridge, are discussed based on a field monitoring program; (2) a parametric study is employed to analyze the effects of different parameters on the thermal performances, including the soil types, bent-pile connections, loading types, and support conditions; and (3) a numerical study is performed to verify the assumption that applying FRP panels on IABs will help resolve the thermal issues of IABs