Vibration control of cantilever beam

The paper describes two approaches to problem of active damping of vibrations of cantilever beam. First one uses standard LTI (linear time invariant) mathematical model of the system and state feedback with the state observer designed by pole placement method. The incomplete pole assignment method is used instead of the standard full assignment. The second one is based on experimental identification of the first mode shape and design dynamic compensator. Experimental results of both methods are compared. The problem of robustness of the compensator by frequency domain method based on the unstructured uncertainty of the model is also addresse

Roles of the Nfu Fe-S targeting factors in the trypanosome mitochondrion

Iron–sulphur clusters (ISCs) are protein co-factors essential for a wide range of cellular functions. The core iron–sulphur cluster assembly machinery resides in the mitochondrion, yet due to export of an essential precursor from the organelle, it is also needed for cytosolic and nuclear iron–sulphur cluster assembly. In mitochondria all [4Fe–4S] iron–sulphur clusters are synthesised and transferred to specific apoproteins by so-called iron–sulphur cluster targeting factors. One of these factors is the universally present mitochondrial Nfu1, which in humans is required for the proper assembly of a subset of mitochondrial [4Fe–4S] proteins. Although most eukaryotes harbour a single Nfu1, the genomes of Trypanosoma brucei and related flagellates encode three Nfu genes. All three Nfu proteins localise to the mitochondrion in the procyclic form of T. brucei, and TbNfu2 and TbNfu3 are both individually essential for growth in bloodstream and procyclic forms, suggesting highly specific functions for each of these proteins in the trypanosome cell. Moreover, these two proteins are functional in the iron–sulphur cluster assembly in a heterologous system and rescue the growth defect of a yeast deletion mutant

Fluctuation induces evolutionary branching in a modeled microbial ecosystem

The impact of environmental fluctuation on species diversity is studied with a model of the evolutionary ecology of microorganisms. We show that environmental fluctuation induces evolutionary branching and assures the consequential coexistence of multiple species. Pairwise invasibility analysis is applied to illustrate the speciation process. We also discuss how fluctuation affects species diversity.Comment: 4 pages, 4 figures. Submitted to Physical Review Letter

Noise-driven oscillations in microbial population dynamics

Microbial populations in the natural environment are likely to experience growth conditions very different from those of a typical laboratory xperiment. In particular, removal rates of biomass and substrate are unlikely to be balanced under realistic environmental conditions. Here, we consider a single population growing on a substrate under conditions where the removal rates of substrate and biomass are not necessarily equal. For a large population, with deterministic growth dynamics, our model predicts that this system can show transient (damped) oscillations. For a small population, demographic noise causes these oscillations to be sustained indefinitely. These oscillations arise when the dynamics of changes in biomass are faster than the dynamics of the substrate, for example, due to a high microbial death rate and/or low substrate flow rates. We show that the same mechanism can produce sustained stochastic oscillations in a two-species, nutrient-cycling microbial ecosystem. Our results suggest that oscillatory population dynamics may be a common feature of small microbial populations in the natural environment, even in the absence of complex interspecies interactions.Comment: 25 pages, 11 figure

Integrating Flux Balance Analysis into Kinetic Models to Decipher the Dynamic Metabolism of Shewanella oneidensis MR-1

Shewanella oneidensis MR-1 sequentially utilizes lactate and its waste products (pyruvate and acetate) during batch culture. To decipher MR-1 metabolism, we integrated genome-scale flux balance analysis (FBA) into a multiple-substrate Monod model to perform the dynamic flux balance analysis (dFBA). The dFBA employed a static optimization approach (SOA) by dividing the batch time into small intervals (i.e., ∼400 mini-FBAs), then the Monod model provided time-dependent inflow/outflow fluxes to constrain the mini-FBAs to profile the pseudo-steady-state fluxes in each time interval. The mini-FBAs used a dual-objective function (a weighted combination of “maximizing growth rate” and “minimizing overall flux”) to capture trade-offs between optimal growth and minimal enzyme usage. By fitting the experimental data, a bi-level optimization of dFBA revealed that the optimal weight in the dual-objective function was time-dependent: the objective function was constant in the early growth stage, while the functional weight of minimal enzyme usage increased significantly when lactate became scarce. The dFBA profiled biologically meaningful dynamic MR-1 metabolisms: 1. the oxidative TCA cycle fluxes increased initially and then decreased in the late growth stage; 2. fluxes in the pentose phosphate pathway and gluconeogenesis were stable in the exponential growth period; and 3. the glyoxylate shunt was up-regulated when acetate became the main carbon source for MR-1 growth