Structural Properties and Complexity of a New Network Class: Collatz Step Graphs

In this paper, we introduce a biologically inspired model to generate complex networks. In contrast to many other construction procedures for growing networks introduced so far, our method generates networks from one-dimensional symbol sequences that are related to the so called Collatz problem from number theory. The major purpose of the present paper is, first, to derive a symbol sequence from the Collatz problem, we call the step sequence, and investigate its structural properties. Second, we introduce a construction procedure for growing networks that is based on these step sequences. Third, we investigate the structural properties of this new network class including their finite scaling and asymptotic behavior of their complexity, average shortest path lengths and clustering coefficients. Interestingly, in contrast to many other network models including the small-world network from Watts & Strogatz, we find that CS graphs become ‘smaller’ with an increasing size.     

Protein diffusion in crowded electrolyte solutions

We report on a combined cold neutron backscattering and spin-echo study of the short-range and long-range nanosecond diffusion of the model globular protein bovine serum albumin (BSA) in aqueous solution as a function of protein concentration and NaCl salt concentration. Complementary small angle X-ray scattering data are used to obtain information on the correlations of the proteins in solution. Particular emphasis is put on the effect of crowding, i.e. conditions under which the proteins cannot be considered as objects independent of each other. We thus address the question at which concentration this crowding starts to influence the static and in particular also the dynamical behaviour. We also briefly discuss qualitatively which charge effects, i.e. effects due to the interplay of charged molecules in an electrolyte solution, may be anticipated. Both the issue of crowding as well as that of charge effects are particularly relevant for proteins and their function under physiological conditions, where the protein volume fraction can be up to approximately 40% and salt ions are ubiquitous. The interpretation of the data is put in the context of existing studies on related systems and of existing theoretical models.     

Establishment of the introduced kelp Undaria pinnatifida in Tasmania depends on disturbance to native algal assemblages

Despite recent rapid increases in the occurrence of nonindigenous marine organisms in the marine environment, few studies have critically examined the invasion process for a marine species. Here we use manipulative experiments to examine processes of invasion for the Asian kelp Undaria pinnatifida (Harvey) Suringar at two sites on the east coast of Tasmania. Disturbance to reduce cover of the native algal canopy was found to be critical in the establishment of U. pinnatifida, while the presence of a stable native algal canopy inhibited invasion. In the first sporophyte growth season following disturbance of the canopy, U. pinnatifida recruited in high densities (up to 19 plants m⁻²) while remaining rare or absent in un-manipulated plots. The timing of disturbance was also important. U. pinnatifida recruited in higher densities in plots where the native canopy was removed immediately prior to the sporophyte growth season (winter 2000), compared with plots where the canopy was removed 6 months earlier during the period of spore release (spring 1999). Removal of the native canopy also resulted in a significant increase in cover of sediment on the substratum. In the second year following canopy removal, U. pinnatifida abundance declined significantly, associated with a substantial recovery of native canopy-forming species. A feature of the recovery of the native algal canopy was a significant shift in species composition. Species dominant prior to canopy removal showed little if any signs of recovery. The recovery was instead dominated by canopy-forming species that were either rare or absent in the study areas prior to manipulation of the canopy.     

A Multiplex Label-Free Approach to Avian Influenza Surveillance and Serology

Influenza serology has traditionally relied on techniques such as hemagglutination inhibition, microneutralization, and ELISA. These assays are complex, challenging to implement in a format allowing detection of several types of antibody-analyte interactions at once (multiplex), and troublesome to implement in the field. As an alternative, we have developed a hemagglutinin microarray on the Arrayed Imaging Reflectometry (AIR) platform. AIR provides sensitive, rapid, and label-free multiplex detection of targets in complex analyte samples such as serum. In preliminary work, we demonstrated the application of this array to the testing of human samples from a vaccine trial. Here, we report the application of an expanded label-free hemagglutinin microarray to the analysis of avian serum samples. Samples from influenza virus challenge experiments in mallards yielded strong, selective detection of antibodies to the challenge antigen in most cases. Samples acquired in the field from mallards were also analyzed, and compared with viral hemagglutinin inhibition and microneutralization assays. We find that the AIR hemagglutinin microarray can provide a simple and robust alternative to standard methods, offering substantially greater information density from a simple workflow.     

Second-harmonic generation from organic molecules incorporated in sol-gel matrices

Orientation of optically nonlinear organic molecules inside sol-gel matrices upon application of an external D.C. electrical field is demonstrated for the first time. The quadratic nonlinear response of silicon oxide or transition metal oxide based gels containing organic molecules has been determined from Electric Field Induced Second Harmonic (EFISH) measurements. Large concentrations of Optically Nonlinear Organic Molecules (ONOM) have been either incorporated inside the macromolecular network or chemically bonded to the oxide backbone of the gels. These results demonstrate the feasibility of permanently poled doped sol-gel matrices. Moreover, EFISH measurements performed on organic molecules appear to be a useful tool for monitoring the changes occurring during sol-gel transformations.     

Flow cytometry controls, instrument setup, and the determination of positivity.

A frequent goal of flow cytometric analysis is to classify cells as positive or negative for a given marker, or to determine the precise ratio of positive to negative cells. This requires good and reproducible instrument setup, and careful use of controls for analyzing and interpreting the data. The type of controls to include in various kinds of flow cytometry experiments is a matter of some debate and discussion. In this tutorial, we classify controls in various categories, describe the options within each category, and discuss the merits of each option.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.