Physics and Science Policy Implications of Reduction of the U.S. Nuclear Weapons Arsenal

Maintaining the readiness U.S. nuclear weapons stockpile is a fundamental pillar of American defense policy. The biggest issue facing the national laboratories that are charged with this mission is replenishing the highly skilled and specialized manpower that is necessary for this task. This lecture presents both physics and science policy questions that must be answered. It also presents employment opportunities for young scientists and engineers.

Expected performance of the ATLAS experiment - detector, trigger and physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.

ModelDB in Computational Neuroscience Education - A research tool as interactive educational media

ModelDB's mission is to link computational models and publications, supporting the field of computational neuroscience (CNS) by making model source code readily available. It is continually expanding, and currently contains source code for more than 300 models that cover more than 41 topics. Investigators, educators, and students can use it to obtain working models that reproduce published results and can be modified to test for new domains of applicability. Users can browse ModelDB to survey the field of computational neuroscience, or pursue more focused explorations of specific topics. Here we describe tutorials and initial experiences with ModelDB as an interactive educational tool.

Multi-Contact Grasp Interaction for Virtual Environments

The grasping of virtual objects has been an active research field for several years. Solutions providing realistic grasping rely on special hardware or require time-consuming parameterizations. Therefore, we introduce a flexible grasping algorithm enabling grasping without computational complex physics. Objects can be grasped and manipulated with multiple fingers. In addition, multiple objects can be manipulated simultaneously with our approach. Through the usage of contact sensors the technique is easily configurable and versatile enough to be used in different scenarios.