A Behavioral Model of Cyclical Dieting

This paper presents a behavioral economics model with bounded rationality to describe an individual¡¯s food consumption choices that lead to weight gain and dieting. Using a physiological relationship determining calories needed to maintain weight, we simulate the food consumption choices of a representative female over a 30 year period. Results show that a diet will reduce weight only temporarily. Recurrence of weight gain leads to cyclical dieting, which reduces the trend rate of weight increase. Dieting frequency is shown to depend on decision period length, dieting costs, and habit persistence.Dieting, Behavioral economics, Weight cycles,

ATLAS Virtual Visits: Bringing the World into the ATLAS Control Room

The newfound ability of Social Media to transform public communication back to a conversational nature provides HEP with a powerful tool for Outreach and Communication. By far, the most effective component of nearly any visit or public event is that fact that the students, teachers, media, and members of the public have a chance to meet and converse with real scientists. While more than 30,000 visitors passed through the ATLAS Visitor Centre in 2011, nearly 7 billion did not have a chance to make the trip. Clearly this is not for lack of interest. Rather, the costs of travel, in terms of time and money, and limited parking, put that number somewhat out of reach. On the other hand, during the LHC “First Physics” event of 2010, more than 2 million visitors joined the experiment control rooms via webcast for the celebration. This document presents a project developed for the ATLAS Experiment's Outreach and Education program that complements the webcast infrastructure with video conferencing and wireless sound systems, allowing the public to interact with hosts in the control room with minimal disturbance to the shifters. These “Virtual Visits” have included high school classes, LHC Masterclasses, conferences, expositions and other events in Europe, USA, Japan and Australia, to name a few. We discuss the technology used, potential pitfalls (and ways to avoid them), and our plans for the future.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98637/1/1742-6596_396_6_062008.pd

Photon lifetime in a cavity containing a slow-light medium

We investigate experimentally the lifetime of the photons in a cavity containing a medium exhibiting strong positive dispersion. This intracavity positive dispersion is provided by a metastable helium gas at room temperature in the electromagnetically induced transparency (EIT) regime, in which light propagates at a group velocity of the order of 10000 m/s. The results definitely prove that the lifetime of the cavity photons is governed by the group velocity of light in the cavity, and not its phase velocity.Comment: Accepted for publication in Optics Letter

A Lesson on Homophobia and Teasing

Homophobia and gay-related teasing are already present among young children. This lesson introduces the term “prejudice” and places the concept of homophobia within the context of bullying and teasing with which 8–11 year olds are already familiar. The lesson builds empathy as children think about and discuss how they have felt when they have been teased or called a name and how they think people in gay or lesbian families would feel. The lesson celebrates the lives of gay and lesbian people as it celebrates diversity among all people and families. Children are encouraged to think about the diversity within their own lives and to think about how all people have pride about who they are and who is in their families

Interacting double dark resonances in a hot atomic vapor of helium

We experimentally and theoretically study two different tripod configurations using metastable helium ($^4$He*), with the probe field polarization perpendicular and parallel to the quantization axis, defined by an applied weak magnetic field. In the first case, the two dark resonances interact incoherently and merge together into a single EIT peak with increasing coupling power. In the second case, we observe destructive interference between the two dark resonances inducing an extra absorption peak at the line center.Comment: 7 pages, 7 figure

Doctor of Philosophy

dissertationAlthough renal transplant is the preferred modality for end-stage renal disease, it brings with it a number of challenges primarily associated with lack of individualized approach. The goals of the present project were: (1) to determine the most significant and clinically practical predictors of kidney transplant outcomes (patient survival, allograft survival, posttransplant complications) using United States Renal Data System (USRDS) data; (2) based on the selected predictors, to generate prediction models of renal transplant outcomes. Our initial study developed prediction models using logistic regression and treebased algorithms derived from data provided by the United Network of Organ Sharing (UNOS). A series of follow-up projects, using data supplied by the United States Renal Data System (USRDS), was performed. We were able to capture significant associations between donor, recipient, and transplant procedure variables (that could not be derived from UNOS data) and the allograph and recipient survival. Among our important findings, compared to peritoneal dialysis (PD), hemodialysis is associated with increased risk of graft failure and recipient death; preemptive retransplantation is associated with an increased risk of graft failure; increased time on dialysis between transplants is associated with a negative effect upon graft and recipient survival in most patient subgroups; short-term (6 months or less) dialysis had no negative effect on graft survival compared to preemptive transplants; certain socioeconomic factors, such as higher education level, citizenship, and type of insurance coverage, influenced graft and recipient outcomes, independent of racial differences; and that one particular iv immunosuppressive medication regimen was superior to others in prolonging graft and recipient survival. Based on these results, we developed a more comprehensive prediction model of the graft outcome using URSDS data using logistic regression and tree-based models. The new models included both deceased and living donor graft recipients, was based on the longer list of pertinent predictors while still being practical in the clinical setting, and addressed the probability of graft failure at five different time points (1, 3, 5, 7, and 10- year allograft survival). The models have been validated on the independent dataset and demonstrated performance suggesting implementation in the clinical decision support system