Topological order in 1D Cluster state protected by symmetry

We demonstrate how to construct the Z2*Z2 global symmetry which protects the ground state degeneracy of cluster states for open boundary conditions. Such a degeneracy ultimately arises because the set of stabilizers do not span a complete set of integrals of motion of the cluster state Hamiltonian for open boundary conditions. By applying control phase transformations, our construction makes the stabilizers into the Pauli operators spanning the qubit Hilbert space from which the degeneracy comes.Comment: 1 figure, To be published in Quantum Information Processin

Atenolol versus losartan in children and young adults with Marfan's syndrome

BACKGROUND : Aortic-root dissection is the leading cause of death in Marfan's syndrome. Studies suggest that with regard to slowing aortic-root enlargement, losartan may be more effective than beta-blockers, the current standard therapy in most centers. METHODS : We conducted a randomized trial comparing losartan with atenolol in children and young adults with Marfan's syndrome. The primary outcome was the rate of aortic-root enlargement, expressed as the change in the maximum aortic-root-diameter z score indexed to body-surface area (hereafter, aortic-root z score) over a 3-year period. Secondary outcomes included the rate of change in the absolute diameter of the aortic root; the rate of change in aortic regurgitation; the time to aortic dissection, aortic-root surgery, or death; somatic growth; and the incidence of adverse events. RESULTS : From January 2007 through February 2011, a total of 21 clinical centers enrolled 608 participants, 6 months to 25 years of age (mean [+/- SD] age, 11.5 +/- 6.5 years in the atenolol group and 11.0 +/- 6.2 years in the losartan group), who had an aorticroot z score greater than 3.0. The baseline-adjusted rate of change (+/- SE) in the aortic-root z score did not differ significantly between the atenolol group and the losartan group (-0.139 +/- 0.013 and -0.107 +/- 0.013 standard-deviation units per year, respectively; P = 0.08). Both slopes were significantly less than zero, indicating a decrease in the degree of aortic-root dilatation relative to body-surface area with either treatment. The 3-year rates of aortic-root surgery, aortic dissection, death, and a composite of these events did not differ significantly between the two treatment groups. CONCLUSIONS : Among children and young adults with Marfan's syndrome who were randomly assigned to losartan or atenolol, we found no significant difference in the rate of aorticroot dilatation between the two treatment groups over a 3-year period

The Adaptive Social Hierarchy: A self organizing network based on naturally occurring structures

Abstract—Wireless networks can be used for relaying information acquired by mobile animal borne tags. To date, no research has considered the large amount of diversity presented by the animal kingdom which impacts the design of the network. We consider here how the weight of the animal affects the size of the tag, and hence the energy that it can carry. We use a common structure in Nature, the social dominance hierarchy, and form a similar hierarchy based on energy. Nodes adjust their perceived rankings through continual tournaments using simple, locally applied rules to result in a stable and adaptive structure. We show that the number of levels in the hierarchy controls traffic density and consequently energy usage. To further conserve energy of low ranked nodes, we propose a simple cross-layer protocol. We show through simulation that our power-aware protocol outperforms those with no knowledge of energy

Implementation mapping: Using intervention mapping to develop implementation strategies

Background: The ultimate impact of a health innovation depends not only on its effectiveness but also on its reach in the population and the extent to which it is implemented with high levels of completeness and fidelity. Implementation science has emerged as the potential solution to the failure to translate evidence from research into effective practice and policy evident in many fields. Implementation scientists have developed many frameworks, theories and models, which describe implementation determinants, processes, or outcomes; yet, there is little guidance about how these can inform the development or selection of implementation strategies (methods or techniques used to improve adoption, implementation, sustainment, and scale-up of interventions) (1, 2). To move the implementation science field forward and to provide a practical tool to apply the knowledge in this field, we describe a systematic process for planning or selecting implementation strategies: Implementation Mapping. Methods: Implementation Mapping is based on Intervention Mapping (a six-step protocol that guides the design of multi-level health promotion interventions and implementation strategies) and expands on Intervention Mapping step 5. It includes insights from both the implementation science field and Intervention Mapping. Implementation Mapping involves five tasks: (1) conduct an implementation needs assessment and identify program adopters and implementers; (2) state adoption and implementation outcomes and performance objectives, identify determinants, and create matrices of change objectives; (3) choose theoretical methods (mechanisms of change) and select or design implementation strategies; (4) produce implementation protocols and materials; and (5) evaluate implementation outcomes. The tasks are iterative with the planner circling back to previous steps throughout this process to ensure all adopters and implementers, outcomes, determinants, and objectives are addressed. Discussion: Implementation Mapping provides a systematic process for developing strategies to improve the adoption, implementation, and maintenance of evidence-based interventions in real-world settings