Wisconsin: Round 1 - State Level Field Network Study of the Implementation of the Affordable Care Act

This report is part of a series of 21 state and regional studies examining the rollout of the ACA. The national network -- with 36 states and 61 researchers -- is led by the Rockefeller Institute of Government, the public policy research arm of the State University of New York, the Brookings Institution, and the Fels Institute of Government at the University of Pennsylvania.The drive to enroll consumers in private health insurance coverage has fostered new alignment among consumer advocates, insurance agents and brokers, community-based organizations, the Wisconsin Department of Health Services, and the health care and insurance sectors. The unique policy position on Medicaid expansion in Wisconsin brings collaboration between those who support the ACA and those who may not support the ACA, but recognize that the governor's entitlement reform plan depends on effective outreach and enrollment into the federally facilitated marketplace. The limited federal funding available for outreach and enrollment has also required public/private partnerships and unlikely alliances. Wisconsin's decision against full Medicaid expansion and instead to cover all adults up to 100 percent of the FPL, but remove adults above that level, provides a boost for the commercial insurance sector. Nearly 80,000 adults will transfer from Medicaid to marketplace coverage and be sent to purchase subsidized coverage on the exchange

Systematic Power Counting in Cutoff Effective Field Theories for Nucleon-Nucleon Interactions and the Equivalence With PDS

An analytic expression for the ${}^1S_0$ phase shifts in nucleon-nucleon scattering is derived in the context of the Schr\"odinger equation in configuration space with a short distance cutoff and with a consistent power counting scheme including pionic effects. The scheme treats the pion mass and the inverse scattering length over the intrinsic short distance scale as small parameters. Working at next-to-leading order in this scheme, we show that the expression obtained is identical to one obtained using the recently introduced PDS approach which is based on dimensional regularization with a novel subtraction scheme. This strongly supports the conjecture that the schemes are equivalent provided one works to the same order in the power counting.Comment: 6 pages; replaced version has corrected typos (We thank Mike Birse for pointing them out to u

Hollow Heaps

We introduce the hollow heap, a very simple data structure with the same amortized efficiency as the classical Fibonacci heap. All heap operations except delete and delete-min take $O(1)$ time, worst case as well as amortized; delete and delete-min take $O(\log n)$ amortized time on a heap of $n$ items. Hollow heaps are by far the simplest structure to achieve this. Hollow heaps combine two novel ideas: the use of lazy deletion and re-insertion to do decrease-key operations, and the use of a dag (directed acyclic graph) instead of a tree or set of trees to represent a heap. Lazy deletion produces hollow nodes (nodes without items), giving the data structure its name.Comment: 27 pages, 7 figures, preliminary version appeared in ICALP 201

Demonstrating genuine multipartite entanglement and nonseparability without shared reference frames

Multipartite nonlocality is of great fundamental interest and constitutes a useful resource for many quantum information protocols. However, demonstrating it in practice, by violating a Bell inequality, can be difficult. In particular, standard experimental setups require the alignment of distant parties' reference frames, which can be challenging or impossible in practice. In this work we study the violation of certain Bell inequalities, namely the Mermin, Mermin-Klyshko and Svetlichny inequalities, without shared reference frames, when parties share a Greenberger-Horne-Zeilinger (GHZ) state. Furthermore, we analyse how these violations demonstrate genuine multipartite features of entanglement and nonlocality. For 3, 4 and 5 parties, we show that it is possible to violate these inequalities with high probability, when the parties choose their measurements from the three Pauli operators, defined only with respect to their local frames. Moreover, the probability of violation, and the amount of violation, are increased when each party chooses their measurements from the four operators describing the vertices of a tetrahedron. We also consider how many randomly chosen measurement directions are needed to violate the Bell inequalities with high probability. We see that the obtained levels of violation are sufficient to also demonstrate genuine multipartite entanglement and nonseparability. Finally, we show analytically that choosing from two measurement settings per party is sufficient to demonstrate the maximum degree of genuine multipartite entanglement and nonseparability with certainty when the parties' reference frames are aligned in one direction so that they differ only in rotations around one axis

Privacy risks in trajectory data publishing: reconstructing private trajectories from continuous properties

Location and time information about individuals can be captured through GPS devices, GSM phones, RFID tag readers, and by other similar means. Such data can be pre-processed to obtain trajectories which are sequences of spatio-temporal data points belonging to a moving object. Recently, advanced data mining techniques have been developed for extracting patterns from moving object trajectories to enable applications such as city traffic planning, identification of evacuation routes, trend detection, and many more. However, when special care is not taken, trajectories of individuals may also pose serious privacy risks even after they are de-identified or mapped into other forms. In this paper, we show that an unknown private trajectory can be reconstructed from knowledge of its properties released for data mining, which at first glance may not seem to pose any privacy threats. In particular, we propose a technique to demonstrate how private trajectories can be re-constructed from knowledge of their distances to a bounded set of known trajectories. Experiments performed on real data sets show that the number of known samples is surprisingly smaller than the actual theoretical bounds