Gravitationally Induced Neutrino-Oscillation Phases

In this essay, we introduce a new effect of gravitationally induced quantum mechanical phases in neutrino oscillations. These phases arise from an hitherto unexplored interplay of gravitation and the principle of the linear superposition of quantum mechanics. In the neighborhood of a 1.4 solar-mass neutron star, gravitationally induced quantum mechanical phases are roughly 20% of their kinematical counterparts. When this information is coupled with the mass square differences implied by the existing neutrino-oscillation data we find that the new effect may have profound consequences for type-II supernova evolution.Comment: First Prize Gravity Research Foundation Essay (1996). Added two appendices. Appendix A: Erratum. Appendix B: Neutrino oscillations as a new energy transport mechanism for supernova explosions (taken from a 1996 JRO Fellowship proposal

Health Inequality

There are many reasons why poverty matters, but it is especially troubling that it affects such fundamental outcomes as health and access to health care. If poverty did not bring about all manner of health risks, we would likely be somewhat less troubled by it. But of course poverty and other forms of social and economic disadvantage do often translate into deficits in health and health care. The purpose of this brief is to examine long-term trends in American health and to lay out the current state of evidence on the extent to which health and health care are unequally distributed. We also note how the recent economic downturn affected these trends and disparities. The key backdrop to this assessment is the tripling of U.S. health expenditures since the 1960s. In 2012, per capita expenditures on health were $8,915, more than double those from 1995, though growth has slowed in the past 4 years.1 Some of this rise is attributable to population aging. Costs associated with Medicare, a program established in 1965 to subsidize health care for those aged 65 and older, have grown as the elderly population constitutes an ever-larger portion of the U.S. population. Still, overall U.S. health expenditures have increased faster than the growth of the elderly population and faster than health expenditures in other OECD countries.2 It is possible that such rising costs have led to a more unequal distribution of health and health care. At the same time, health inequalities may also be affected by the economy (e.g., recessions), changes in how insurance is provided, and any number of other factors. In this brief, our objective is not to attempt to tease out the causes of any possible changes in health inequalities, but rather to provide a descriptive summary of the current evidence on trends in (a) health, (b) foregone health care and insurance coverage, and (c) health risk factors. To preview our results, we find first that some health indicators, such as life expectancy, show an overall improvement. But not all indicators are improving. For example, an increasing number of Americans report delaying or foregoing health care, particularly during the recent economic recession. Second, economic and racial disparities in health indicators are often substantial, and when changes in these disparities are observed, they usually take the form of an increase in absolute size. Third, a large proportion of Americans still remain uninsured in 2012 (i.e., 15 percent), although the proportion of children who are uninsured declined by nearly 2 percentage points between the late 1990s and 2012

Simultaneous Parameter Calibration, Localization, and Mapping

The calibration parameters of a mobile robot play a substantial role in navigation tasks. Often these parameters are subject to variations that depend either on changes in the environment or on the load of the robot. In this paper, we propose an approach to simultaneously estimate a map of the environment, the position of the on-board sensors of the robot, and its kinematic parameters. Our method requires no prior knowledge about the environment and relies only on a rough initial guess of the parameters of the platform. The proposed approach estimates the parameters online and it is able to adapt to non-stationary changes of the configuration. We tested our approach in simulated environments and on a wide range of real-world data using different types of robotic platforms. (C) 2012 Taylor & Francis and The Robotics Society of Japa