|Date||September 19, 2014||Time||12:00 pm|
|Location||Baylor Sciences Building, Room E.125|
Applications of Raman Spectroscopy to Biological Systems
Raman spectroscopy is an attractive analytical tool for several reasons. It is nondestructive, requires little to no sample preparation, and is discriminatory between chemical species. In principle its use in biological investigations should be able to reveal new and interesting information about the chemical makeup and possibly dynamics of living organism both in situ and in vitro. In practice there are several difficulties with using the technique in this manner. This talk aims to shed light on both the applications of Raman for biological analysis and highlight the potential problems, along with their workarounds and possible solutions. It will also present a new and interesting imaging technique using gold nanoparticles (GNPs) to enhance the Raman signal in a living cell.
Programmable Self-Assembly of Two-Dimensional Shapes with Seed-Initiated Algorithm in a Thousand Robot Swarm
Self-assembly is a type of process in which a disordered system of individuals forms an organized structure through local interactions among individuals without human intervention. In this article, researchers mimic the collective intelligence in nature to create artificial system of a thousand-robot swarm, and make the swarm forms a target two- dimensional shape from a random shape using programmable selfassembly. First, a thousand autonomous robots capable of computation, locomotion, sensing and communication are produced. All of them are programmed with self-assembly algorithm and an image of the specific target shape. The algorithm composes three primitive collective behaviors which are edge-following, gradient formation and localization. Second, the robots are tightly packed into an arbitrary shaped group with some seed robots fixed in some locations. Then, robots starts edge following and moving robots continually compute their location and gradient value. After a robot enters the desired shape, it becomes stationary if it meets one of the two termination conditions. This process continues until the shape is filled with robots. At the end, the author talked about several additional algorithm strategies to address the issues of errors caused by imprecise locomotion, noisy distance sensing, message loss, etc.
For more information, please contact: Dr. Ken Park 254-710-2282
|Publisher||Department of Physics|
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