Generation of attenuation corrected images from lidar data

The interpretation of data generated by aerosol backscatter lidars is often facilitated by presentation of RHI and PPI images. These pictures are especially useful in studies of atmospheric boundary layer structure where convective elements, stratifications and aerosol laden plumes can be easily delineated. Procedures used at the University of Wisconsin to generate lidar images on a color enhanced raster scan display are described

Virus-enabled synthesis of titanium oxide nanowires

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2006.Includes bibliographical references (p. 21-23).Bio-assisted materials fabrication methods allow for the production of high technology materials and devices at lower costs and with less environmental impact. To expand the biological toolkit for synthesizing materials, we demonstrated titanium oxide nanowire synthesis with use of engineered M13 virus at room temperature. In this virus-enabled synthesis process, negatively-charged titanium fluoro complexes nucleate at positive amine sites on the virus, and a subsequent anion-scavenging reaction drives the synthesis of titanium oxide on the virus. TEM imagery provided visual validation of the nanowire formation, and XRD analysis identified the crystalline structure as anatase.by Forrest Liau.S.B

Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling

Learning about the social structure of hidden and hard-to-reach populations --- such as drug users and sex workers --- is a major goal of epidemiological and public health research on risk behaviors and disease prevention. Respondent-driven sampling (RDS) is a peer-referral process widely used by many health organizations, where research subjects recruit other subjects from their social network. In such surveys, researchers observe who recruited whom, along with the time of recruitment and the total number of acquaintances (network degree) of respondents. However, due to privacy concerns, the identities of acquaintances are not disclosed. In this work, we show how to reconstruct the underlying network structure through which the subjects are recruited. We formulate the dynamics of RDS as a continuous-time diffusion process over the underlying graph and derive the likelihood for the recruitment time series under an arbitrary recruitment time distribution. We develop an efficient stochastic optimization algorithm called RENDER (REspoNdent-Driven nEtwork Reconstruction) that finds the network that best explains the collected data. We support our analytical results through an exhaustive set of experiments on both synthetic and real data.Comment: A full version with technical proofs. Accepted by AAAI-1