A Socio-ecological Approach to Measure Progress for Ontario’s Transition to a Green Economy: The Use of the Happy Planet Index

Government tends to look at economic growth and GDP as the primary measure of wellbeing in society. However, GDP does not consider many environmental impacts which have critical short and long-term economic effects. Due to this miscalculation about the concept of wellbeing, governments may downplay the ecological implications of growth and its contribution to inequality and poverty. Alternative measures to GDP exist to address the social and environmental aspects needed for a sustainable society. Alternative means are usually evaluated at the national level, but due to the Canadian political separation of powers and responsibilities, provincial governments have more responsibilities for environmental and social policy. This research paper explores the Happy Planet Index (HPI) in Ontario for over ten years, evaluating to what extent the Happy Planet Index addresses flaws in a GDP-based policy framework in Ontario. HPI is an eco-efficiency indicator which measures sustainable well-being, enabling policymakers to create effective policies towards the achievement of long, happy, and sustainable lives. HPI incorporates social and environmental variables which can be used by the provincial government in policy evaluation. The index includes three indicators: life satisfaction, a subjective measure of wellbeing that looks from the individual’s perspective on how people rank their happiness and life satisfaction; health-adjusted life expectancy, the average number of years that an individual is expected to live in a healthy state, or the average lifetime someone is expected to live; and ecological footprint, which measures a person’s consumption of nature

Underestimated cost of targeted attacks on complex networks

The robustness of complex networks under targeted attacks is deeply connected to the resilience of complex systems, i.e., the ability to make appropriate responses to the attacks. In this article, we investigated the state-of-the-art targeted node attack algorithms and demonstrate that they become very inefficient when the cost of the attack is taken into consideration. In this paper, we made explicit assumption that the cost of removing a node is proportional to the number of adjacent links that are removed, i.e., higher degree nodes have higher cost. Finally, for the case when it is possible to attack links, we propose a simple and efficient edge removal strategy named Hierarchical Power Iterative Normalized cut (HPI-Ncut).The results on real and artificial networks show that the HPI-Ncut algorithm outperforms all the node removal and link removal attack algorithms when the cost of the attack is taken into consideration. In addition, we show that on sparse networks, the complexity of this hierarchical power iteration edge removal algorithm is only $O(n\log^{2+\epsilon}(n))$.Comment: 14 pages, 7 figure

Part III, Free Actions of Compact Quantum Groups on C*-Algebras

We study and classify free actions of compact quantum groups on unital C*-algebras in terms of generalized factor systems. Moreover, we use these factor systems to show that all finite coverings of irrational rotation C*-algebras are cleft

Algorithmic problems for free-abelian times free groups

We study direct products of free-abelian and free groups with special emphasis on algorithmic problems. After giving natural extensions of standard notions into that family, we find an explicit expression for an arbitrary endomorphism of \ZZ^m \times F_n. These tools are used to solve several algorithmic and decision problems for \ZZ^m \times F_n : the membership problem, the isomorphism problem, the finite index problem, the subgroup and coset intersection problems, the fixed point problem, and the Whitehead problem.Comment: 38 page

EU–originated MOOCs, with focus on multi- and single-institution platforms

No abstract available