17 research outputs found
Quantum Vacuum Experiments Using High Intensity Lasers
The quantum vacuum constitutes a fascinating medium of study, in particular
since near-future laser facilities will be able to probe the nonlinear nature
of this vacuum. There has been a large number of proposed tests of the
low-energy, high intensity regime of quantum electrodynamics (QED) where the
nonlinear aspects of the electromagnetic vacuum comes into play, and we will
here give a short description of some of these. Such studies can shed light,
not only on the validity of QED, but also on certain aspects of nonperturbative
effects, and thus also give insights for quantum field theories in general.Comment: 9 pages, 8 figur
Characteristics of luciferases from a variety of firefly species: Evidence for the presence of luciferase isozymes
Evaluation of histochemical observations of activity of acid hydrolases obtained with semipermeable membrane techniques
Avaliação histomorfométrica e ultra-estrutural da mucosa do cólon menor eqüino submetido a distensão
Evaluation of histochemical observations of activity of acid hydrolases obtained with semipermeable membrane techniques: A combined histochemical and biochemical investigation
Controlling behavior of δ-ferrite in nitrogen-containing chromium–nickel–manganese steels
Individual gene cluster statistics in noisy maps
Identification of homologous chromosomal regions is important for understanding evolutionary processes that shape genome evolution, such as genome rearrangements and large scale duplication events. If these chromosomal regions have diverged significantly, statistical tests to determine whether observed similarities in gene content are due to history or chance are imperative. Currently available methods are typically designed for genomic data and are appropriate for whole genome analyses. Statistical methods for estimating significance when a single pair of regions is under consideration are needed. We present a new statistical method, based on generating functions, for estimating the significance of orthologous gene clusters under the null hypothesis of random gene order. Our statistics is suitable for noisy comparative maps, in which a one-to-one homology mapping cannot be established. It is also designed for testing the significance of an individual gene cluster in isolation, in situations where whole genome data is not available. We implement our statistics in Mathematica and demonstrate its utility by applying it to the MHC homologous regions in human and fly