14 research outputs found
Patterns Of Chronic Graft-Vs-Host Disease And Associated Mortality After Myeloablative Conditioning Incorporating Fludarabine, Busulfan And ATG
Short Gamma Ray Bursts: a bimodal origin?
Short-hard Gamma Ray Bursts (SGRBs) are currently thought to arise from
gravitational wave driven coalescences of double neutron star systems forming
either in the field or dynamically in globular clusters. For both channels we
fit the peak flux distribution of BATSE SGRBs to derive the local burst
formation rate and luminosity function. We then compare the resulting redshift
distribution with Swift 2-year data, showing that both formation channels are
needed in order to reproduce the observations. Double neutron stars forming in
globular clusters are found to dominate the distribution at z<0.3, whereas the
field population from primordial binaries can account for the high-z SGRBs.
This result is not in contradiction with the observed host galaxy type of
SGRBs.Comment: 5 pages, 2 figures, accepted for publication in MNRA
A REACTIVE PATH-FOLLOWING CONTROLLER TO GUARANTEE OBSTACLE AVOIDANCE DURING THE TRANSIENT PHASE
Patterns Of Chronic Graft-Vs-Host Disease And Associated Mortality After Myeloablative Conditioning Incorporating Fludarabine, Busulfan And ATG
Translocation of 14C-assimilates in roses. II. The effect of shoot darkening and cytokinin application
Capturing the Connectivity of High-Dimensional Geometric Spaces by Parallelizable Random Sampling Techniques
Applications such as robot programming, design for manufactur- ing, animation of digital actors, rationale drug design, and surgical planning, require computing paths in high-dimensional geometric spaces, a provably hard problem. Recently, a general path-planning approach based on a parallelizable random sampling scheme has emerged as an effective approach to solve this problem. In this approach, the path planner captures the connectivity of a space F by building a probabilistic roadmap, a network of simple paths connecting points picked at random in F. This paper combines results previously presented in separate papers. It describes a basic probabilistic roadmap planner that is easily parallelizable, and it analyzes the performance of this planner as a function of how well F satisfies geometric properties called e-goodness, expansiveness, and path clearance. While e-goodness allows us to study how well a probabilistic roadmap covers F, expansiveness and path clearance allow us to compare the connectedness of the roadmap to that of F