On modeling chronic detachment of periphyton in artificial rough, open channel flow

Periphyton communities, which are native to river beds, serve as a functional indicator of river health but remain one of the least-studied communities despite the significant increase in the examination of aquatic microbial communities in recent years. In this study, we tested the relevance of three formulations of the chronic detachment term in a simple model for the biomass dynamics of periphyton. Numerical simulations of the periphyton biomass dynamics were performed by using three different descriptors for the flow conditions: the discharge Q, the friction velocity u⁄, and the roughness Reynolds number k+ = u⁄ks/m (where m is water kinetic viscosity and ks is the Nikuradse equivalent sand roughness). Comparisons of numerical simulation results with experimental data from literature revealed chronic detachment to be better simulated by taking the roughness Reynolds number as the external variable of detachment. These results support the idea that transport phenomena that occur in the nearbed layer, e.g. chronic detachment of periphyton matter or vertical transport of nutrients and pollutants in submerged aquatic canopies, are not related to a single turbulence descriptor such as the friction velocity u⁄. Its description requires at least two descriptors, here the friction velocity u⁄ and the Nikuradse equivalent sand roughness ks, which depend on the initial form and dimensions of the colonized substratum, and its changes owing to the thickness, resistance, and composition of the epilithic matter

Ecological Invasion, Roughened Fronts, and a Competitor's Extreme Advance: Integrating Stochastic Spatial-Growth Models

Both community ecology and conservation biology seek further understanding of factors governing the advance of an invasive species. We model biological invasion as an individual-based, stochastic process on a two-dimensional landscape. An ecologically superior invader and a resident species compete for space preemptively. Our general model includes the basic contact process and a variant of the Eden model as special cases. We employ the concept of a "roughened" front to quantify effects of discreteness and stochasticity on invasion; we emphasize the probability distribution of the front-runner's relative position. That is, we analyze the location of the most advanced invader as the extreme deviation about the front's mean position. We find that a class of models with different assumptions about neighborhood interactions exhibit universal characteristics. That is, key features of the invasion dynamics span a class of models, independently of locally detailed demographic rules. Our results integrate theories of invasive spatial growth and generate novel hypotheses linking habitat or landscape size (length of the invading front) to invasion velocity, and to the relative position of the most advanced invader.Comment: The original publication is available at www.springerlink.com/content/8528v8563r7u2742

Multivariate NIR studies of seed-water interaction in Scots Pine Seeds (Pinus sylvestris L.)

This thesis describes seed-water interaction using near infrared (NIR) spectroscopy, multivariate regression models and Scots pine seeds. The presented research covers classification of seed viability, prediction of seed moisture content, selection of NIR wavelengths and interpretation of seed-water interaction modelled and analysed by principal component analysis, ordinary least squares (OLS), partial least squares (PLS), bi-orthogonal least squares (BPLS) and genetic algorithms. The potential of using multivariate NIR calibration models for seed classification was demonstrated using filled viable and non-viable seeds that could be separated with an accuracy of 98-99%. It was also shown that multivariate NIR calibration models gave low errors (0.7% and 1.9%) in prediction of seed moisture content for bulk seed and single seeds, respectively, using either NIR reflectance or transmittance spectroscopy. Genetic algorithms selected three to eight wavelength bands in the NIR region and these narrow bands gave about the same prediction of seed moisture content (0.6% and 1.7%) as using the whole NIR interval in the PLS regression models. The selected regions were simulated as NIR filters in OLS regression resulting in predictions of the same quality (0.7 % and 2.1%). This finding opens possibilities to apply NIR sensors in fast and simple spectrometers for the determination of seed moisture content. Near infrared (NIR) radiation interacts with overtones of vibrating bonds in polar molecules. The resulting spectra contain chemical and physical information. This offers good possibilities to measure seed-water interactions, but also to interpret processes within seeds. It is shown that seed-water interaction involves both transitions and changes mainly in covalent bonds of O-H, C-H, C=O and N-H emanating from ongoing physiological processes like seed respiration and protein metabolism. I propose that BPLS analysis that has orthonormal loadings and orthogonal scores giving the same predictions as using conventional PLS regression, should be used as a standard to harmonise the interpretation of NIR spectra

Statistical pairwise interaction model of stock market

Financial markets are a classical example of complex systems as they comprise many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or others are agent-based models with rules designed in order to recover some empirical behaviours. Here we show that the pairwise model is actually a statistically consistent model with observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach based only on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviours, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.Comment: 11 pages, 8 figure

Contribution of cellular automata to the understanding of corrosion phenomena

We present a stochastic CA modelling approach of corrosion based on spatially separated electrochemical half-reactions, diffusion, acido-basic neutralization in solution and passive properties of the oxide layers. Starting from different initial conditions, a single framework allows one to describe generalised corrosion, localised corrosion, reactive and passive surfaces, including occluded corrosion phenomena as well. Spontaneous spatial separation of anodic and cathodic zones is associated with bare metal and passivated metal on the surface. This separation is also related to local acidification of the solution. This spontaneous change is associated with a much faster corrosion rate. Material morphology is closely related to corrosion kinetics, which can be used for technological applications.Comment: 13 pages, 9 figure