Post Traumatic Stress Disorder (PTSD) is reported to be caused by traumatic events that are outside the range of usual human experiences including (but not limited to) military combat, violent personal assault, being kidnapped or taken hostage and terrorist attacks. Initial data suggests that 1 out of 6 Iraq War veterans are exhibiting symptoms of depression, anxiety and PTSD. Virtual Reality (VR) exposure treatment has been used in previous treatments of PTSD patients with reports of positive outcomes. The aim of the current paper is to present the rationale, technical specifications, application features and user-centered design process for the development of a Virtual Iraq PTSD VR therapy application. The VR treatment environment is being created via the recycling of virtual graphic assets that were initially built for the U.S. Army-funded combat tactical simulation scenario and commercially successful X-Box game, Full Spectrum Warrior, in addition to other available and newly created assets. Thus far we have created a series of customizable virtual scenarios designed to represent relevant contexts for exposure therapy to be conducted in VR, including a city and desert road convoy environment. User-Centered tests with the application are currently underway at the Naval Medical Center-San Diego and within an Army Combat Stress Control Team in Iraq with clinical trials scheduled to commence in February 2006.

Heurlsttcs are considered which attempt to maintain a binary search tree in a near optimal form, assuming that elements are requested with fixed, but unknown, independent probabilities.A "move to root'" heuristic is shown to yield an expected search time within a constant factor of that of an optimal static binary search tree.On the other hand, a closely related "simple exchange" technique is shown not to have this property.The rate of convergence of the move to root heuristic is discussed Also considered is the more general case m whmh elements not in the tree may have nonzero probabihty of being requested.

We consider heuristics which attempt to maintain a binary search tree in a near optimal form, assuming that elements are requested with fixed, but unknown, independent probabilities. A "move to root" heuristic is shown to yield an expected search time within a constant factor of that of an optimal static binary search tree. On the other hand, a closely related "simple exchange" technique is shown not to have this property. The rate of convergence of the "move to root" heuristic is discussed. We also consider the more general case in which elements not in the tree may have non-zero probability of being requested.