Supersymmetric models often predict a lightest superpartner (LSP) which is electrically charged and stable on the timescales of collider experiments. If such a particle were to be observed experimentally, is it possible to determine whether or not it is stable on cosmological timescales? Charged, stable particles are usually considered to be excluded by cosmological arguments coupled with terrestrial searches for anomalously heavy water molecules. But when the cosmology is significantly altered, as can happen in models with large extra dimensions, these arguments are in turn significantly weakened. In this paper we suggest an alternate way to use searches for superheavy water to constrain the lifetimes of long-lived, charged particles, independent of most cosmological assumptions. By considering SUSY production by cosmic rays in the upper atmosphere, we are able to use current bounds on superheavy water to constrain the mass scale of squarks and gluinos to be greater than about 230 GeV, assuming a stable, charged LSP. This bound can be increased, but only by significantly increasing the size of the initial water sample tested.

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The Open University has been undertaking an extended initiative to improve student retention through enhanced support for at-risk students. This initiative has evolved through a series of stages from ad hoc small scale local interventions relying largely on tutors and student self-referral, to an institutionwide pro-active system implemented by specialist staff, backed by costeffectiveness data based on evaluations of controlled experiments, and driven by management information systems. This article will outline the similarities and differences between retention in distance learning in the United Kingdom (UK) and in United States (US) colleges, illustrate the way a program of planned interventions was evaluated at the Open University, explain how the cost-effectiveness of interventions was established, and describe the integrated proactive system now in operation.

This article describes the week-to-week dynamics of a five-week decision science elective practice course in Dartmouth's MBA program. The course begins with a refresher assignment in simulation and optimization. Next come two intense weeks of spreadsheet modeling to value an industrial asset in the status quo and with capital investments. The course then focuses on negotiating with potential buyers. I urge students to craft effective arguments to persuade decision makers of the best course of action. In closing, I propose an effort by faculty from multiple business schools to develop jointly a suite of multi-week cases, to be taught concurrently, with modest prizes for the best student work.Editor's note: This is a pdf copy of an html document which resides at http://ite.pubs.informs.org/Vol6No1/ Regan/

I teach a short elective course on decision science to 40 percent of the second-year class in Dartmouth’s MBA program. Students use MS/OR to clarify the value of an industrial asset in a spin-off negotiation. Students design, build, and refine spreadsheet models incrementally. I introduce techniques to support each week’s case challenges. The decision context evolves with new information and unexpected demands. My teaching success depends on quick, detailed feedback and effectively guiding students with varying proficiency. My hybrid role as practitioner-professor developed over several years. I encourage practitioners and full-time faculty to collaborate on similar courses or segments of longer courses.