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.     

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.     

Estimating recent growth in the cuttlefish Sepia officinalis: are nucleic acid-based indicators for growth and condition the method of choice?

A laboratory calibration study was undertaken with juvenile Sepia officinalis (80-85 g initial wet weight) to investigate the effects of different food rations and different starving intervals on RNA/dry weight (DW) ratios and RNA/DNA ratios in cephalopod mantle muscle at two different temperatures. The digestive gland index was also used as an additional indicator of recent growth. High food rations and low temperature went along with high RNA/DW ratios and high RNA/DNA ratios. Starving resulted in a linear decline in growth performance and a concomitant decrease in RNA/DW and RNA/DNA ratio, with RNA/DNA ratios representing the growth data better. RNA/DNA ratios decreased faster at higher temperatures. A fluorimetric assay for nucleic acid analysis was optimized for cephalopod mantle tissues and yielded reproducible RNA/DNA ratios with a relative variance below 10%. Thus, it may be possible to use this estimator of recently encountered feeding regime for the evaluation of mortality rates of early teuthid paralarvae to eventually support stock management. Also, log relative digestive gland weight showed a strong relationship with starving time, but, surprisingly, not with temperature. Data from the two temperatures analyzed could be combined to form a common regression line of relative digestive gland index with starving time. This indicator for recent growth might be especially suitable for large specimens with a well-developed digestive gland.     

Can zoosporic true fungi grow or survive in extreme or stressful environments?

Zoosporic true fungi are thought to be ubiquitous in many ecosystems, especially in cool, moist soils and freshwater habitats which are rich in organic matter. However, some of the habitats where these fungi are found may periodically experience extreme conditions, such as soils in extremely dry, hot and cold climates, acidic and alkaline soils, polluted rivers, anaerobic soil and water, saline soil and water, periglacial soils, oligotrophic soils, tree canopies and hydrothermal vents. It is clear that many ecotypes of zoosporic true fungi have indeed adapted to extreme or stressful environmental conditions. This conclusion is supported by studies in both the field and in the laboratory. Therefore, in our opinion, at least some true zoosporic fungi can be considered to be extremophiles.