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The ability to maintain functionality in transport infrastructure is critical during disruptions. To ensure operational robustness in transportation networks, it is necessary to identify the most vital or critical roads (or links), then reinforce them to increase their resilience. In the literature, conventional approaches to analyze road network robustness have involved efforts to first remove selected road segments (one by one, not collectively), then measure the impact of these changes. Based on these results, the levels of impact are ranked and links that demonstrate the most significant impacts are deemed to be the most critical. One of the most significant limitations of such approaches, however, is that they disregard the combined effect of road connectivity. This study advances the state of knowledge in transportation-based resilience analysis through the development of an approach to assess the impact of “critical combination scenarios”. The methodology involves a two-phase process. The first phase is based on the sensor (loop detector) location problem, within which, a selected number of high demand roads are identified as “candidate” critical links. Then, the second phase employs a series of discrete network design problem (DNDP) to find a variety of critical combination scenarios. The DNDPs are solved based on a system optimal relaxation method using Bender’s Decomposition. Building further from these results, the extent to which a road network is robust (or fragile) is analyzed. The results of the DNDP solutions are demonstrated to be similar to a Lorenz Curve in which the area under the Lorenz Curve (in percentage) can be viewed as a global robustness index. This index can be used to compare and assess the robustness of different road networks and mitigation scenarios. To illustrate the practical utility of this method, this research applied the methodology to the Winnipeg, Canada road network. [ABSTRACT FROM AUTHOR]

This paper presents the development effort that created a robust representation of the combined capacity expansion of the U.S. and Canadian electric sectors within the NREL ReEDS model. The abbreviated scenario analysis effort was designed to understand drivers behind various Canadian–U.S. power sector futures out to 2036. We model the impact of natural gas prices, increased Canadian hydropower deployment, and increased renewable energy (RE) penetrations. The sample results analyzed in this paper show the highly dynamic nature of the modeling tool as it performs a simultaneous optimization of the two countries’ generation portfolios. The interactions between the two countries go beyond energy generation and also include firm capacity contracts and renewable energy certificates (RECs). The reference scenario results show a significant increase in wind generation in both the United States and Canada with a gradual retirement of coal and nuclear energy. The evolution of net energy and firm capacity exchange was very dynamic through the span of the analysis period and drives significant investment in transmission capacity across the border, almost doubling the existing capacity of transmission lines. The exchange of energy was driven by regional stories. ISO-NE and NYISO import energy throughout the analysis period. However, in the Western Interconnection we observed increasing imports to Canada from the United States, whereas the exchanges with MISO switched directions. [ABSTRACT FROM AUTHOR]

Abstract: For the discrimination of four tectonic settings of island arc, continental arc, within-plate (continental rift and ocean island together), and collision, we present three sets of new diagrams obtained from linear discriminant analysis of natural logarithm transformed ratios of major elements, immobile major and trace elements, and immobile trace elements in acid magmas. The use of discordant outlier-free samples prior to linear discriminant analysis had improved the success rates by about 3% on the average. Success rates of these new diagrams were acceptably high (about 69% to 97% for the first set, about 69% to 99% for the second set, and about 60% to 96% for the third set). Testing of these diagrams for acid rock samples (not used for constructing them) from known tectonic settings confirmed their overall good performance. Application of these new diagrams to Precambrian case studies provided the following generally consistent results: a continental arc setting for the Caribou greenstone belt (Canada) at about 3000Ma, São Francisco craton (Brazil) at about 3085–2983Ma, Penakacherla greenstone terrane (Dharwar craton, India) at about 2700Ma, and Adola (Ethiopia) at about 885–765Ma; a transitional continental arc to collision setting for the Rio Maria terrane (Brazil) at about 2870Ma and Eastern felsic volcanic terrain (India) at about 2700Ma; a collision setting for the Kolar suture zone (India) at about 2610Ma and Korpo area (Finland) at about 1852Ma; and a within-plate (likely a continental rift) setting for Malani igneous suite (India) at about 745–700Ma. These applications suggest utility of the new discrimination diagrams for all four tectonic settings. In fact, all three sets of diagrams were shown to be robust against post-emplacement compositional changes caused by analytical errors, element mobility related to low or high temperature alteration, or Fe-oxidation caused by weathering. [Copyright &y& Elsevier]

Abstract: Introduction: The concept of knowledge translation as defined by the Canadian Institutes for Health Research and the Knowledge to Action Cycle, described by Graham et al (), are used to make a case for the importance of using a conceptual model to describe moving knowledge into action in the area of falls prevention. Method: There is a large body of research in the area of falls prevention. It would seem that in many areas it is clear what is needed to prevent falls and further syntheses can determine where the evidence is sufficiently robust to warrant its implementation as well as where the gaps are that require further basic research. Conclusion: The phases of the action cycle highlight seven areas that should be paid attention to in order to maximize chances of successful implementation. [Copyright &y& Elsevier]

Abstract: This paper uses sequential stochastic dominance procedures to compare the joint distribution of health and income across space and time. It is the first application of which we are aware of methods to compare multidimensional distributions of income and health using procedures that are robust to aggregation techniques. The paper’s approach is more general than comparisons of health gradients and does not require the estimation of health equivalent incomes. We illustrate the approach by contrasting Canada and the US using comparable data. Canada dominates the US over the bottom part of the bi-dimensional distribution of health and income, though not generally over the uni-dimensional distributions of health or income. The paper also finds that welfare for both Canadians and Americans has not unambiguously improved during the last decade over the joint distribution of income and health, in spite of the fact that the uni-dimensional distributions of income have clearly improved during that period. [Copyright &y& Elsevier]