Dynamic estimation of specific growth rates and concentrations of bacteria for the anaerobic digestion

The paper proposes an observability analysis and estimation schemes for specific growth rates and biomass concentrations of the anaerobic digestion process. A 3-stage model of 5 dynamic states is assumed, describing the hydrolysis, acidogenesis and methanogenesis of two different populations of microorganisms (acidogenic and methanogenic). The main result is that the specific growth rates of the two populations of bacteria can be stability estimated only from easily measured quantities -- the dilution rate and the flow rates of methane and carbon dioxide in the biogas. The estimation schemes thus obtained have quite interesting features one of which is their freeness of most yield coefficients often hard to identify. The analysis rests on the differential algebraic approach of observation problems. The results are currently being confronted to experimental data from a 100m3 pilot bioreactor fed with cattle dung. Realistic simulations are presented in this paper as illustrations of the estimator performance

Parameter and State Estimation of an Anaerobic Digestion of Organic Wastes Model with Addition of Stimulating Substances

New control inputs are introduced in the 5th order mass-balance non-linear model of the anaerobic digestion, which reflects the addition of stimulating substances (acetate and glucose). Laboratory experiments have been done with step-wise and pulse changes of these new inputs. On the basis of the step responses of the measured variables (biogas flow rate and acetate concentration in the bioreactor) and iterative methodology, involving non-linear optimisation and simulations, the model coefficients have been estimated. The model validity has been proved by another set of experiments. The observation part is built on a two-step structure. One estimator and two observers are designed on the basis of this process model. Their stability has been proved and their performances have been investigated with experimental data and simulations

Assessment of the compost from the methane fermentation of litter from broiler production with a view to its utilization in organic plant production

The aim of the present research is to make an ecological assessment of the compost obtained from litter from broiler production /LBP/ according to the requirements of Ordinance №22/2001 for the MRL/Maximum Residue Level/ values of toxic elements and according to the Norms of the Canadian Ministry of Agriculture /2002/ with a view to its utilization in the organic production of plants. This research is necessary because, unlike broiler dung and domestic organic waste, LBP is heterogeneous in content and it includes different sources of cellulose / in Bulgaria hay is the most common as well as some part of the fodder/

Exploratory Spatial Analysis of in vitro Respiratory Syncytial Virus Co-infections

The cell response to virus infection and virus perturbation of that response is dynamic and is reflected by changes in cell susceptibility to infection. In this study, we evaluated the response of human epithelial cells to sequential infections with human respiratory syncytial virus strains A2 and B to determine if a primary infection with one strain will impact the ability of cells to be infected with the second as a function of virus strain and time elapsed between the two exposures. Infected cells were visualized with fluorescent markers, and location of all cells in the tissue culture well were identified using imaging software. We employed tools from spatial statistics to investigate the likelihood of a cell being infected given its proximity to a cell infected with either the homologous or heterologous virus. We used point processes, K-functions, and simulation procedures designed to account for specific features of our data when assessing spatial associations. Our results suggest that intrinsic cell properties increase susceptibility of cells to infection, more so for RSV-B than for RSV-A. Further, we provide evidence that the primary infection can decrease susceptibility of cells to the heterologous challenge virus but only at the 16 h time point evaluated in this study. Our research effort highlights the merits of integrating empirical and statistical approaches to gain greater insight on in vitro dynamics of virus-host interactions

The NCATS BioPlanet – An Integrated Platform for Exploring the Universe of Cellular Signaling Pathways for Toxicology, Systems Biology, and Chemical Genomics

Chemical genomics aims to comprehensively define, and ultimately predict, the effects of small molecule compounds on biological systems. Chemical activity profiling approaches must consider chemical effects on all pathways operative in mammalian cells. To enable a strategic and maximally efficient chemical profiling of pathway space, we have created the NCATS BioPlanet, a comprehensive integrated pathway resource that incorporates the universe of 1,658 human pathways sourced from publicly available, manually curated sources, which have been subjected to thorough redundancy and consistency cross-evaluation. BioPlanet supports interactive browsing, retrieval, and analysis of pathways, exploration of pathway connections, and pathway search by gene targets, category, and availability of corresponding bioactivity assay, as well as visualization of pathways on a 3-dimensional globe, in which the distance between any two pathways is proportional to their degree of gene component overlap. Using this resource, we propose a strategy to identify a minimal set of 362 biological assays that can interrogate the universe of human pathways. The NCATS BioPlanet is a public resource, which will be continually expanded and updated, for systems biology, toxicology, and chemical genomics, available at http://tripod.nih.gov/bioplanet/

Exploratory Spatial Analysis of in vitro Respiratory Syncytial Virus Co-infections

The cell response to virus infection and virus perturbation of that response is dynamic and is reflected by changes in cell susceptibility to infection. In this study, we evaluated the response of human epithelial cells to sequential infections with human respiratory syncytial virus strains A2 and B to determine if a primary infection with one strain will impact the ability of cells to be infected with the second as a function of virus strain and time elapsed between the two exposures. Infected cells were visualized with fluorescent markers, and location of all cells in the tissue culture well were identified using imaging software. We employed tools from spatial statistics to investigate the likelihood of a cell being infected given its proximity to a cell infected with either the homologous or heterologous virus. We used point processes, K-functions, and simulation procedures designed to account for specific features of our data when assessing spatial associations. Our results suggest that intrinsic cell properties increase susceptibility of cells to infection, more so for RSV-B than for RSV-A. Further, we provide evidence that the primary infection can decrease susceptibility of cells to the heterologous challenge virus but only at the 16 h time point evaluated in this study. Our research effort highlights the merits of integrating empirical and statistical approaches to gain greater insight on in vitro dynamics of virus-host interactions

A dynamic estimation scheme for specific growth rates of bacteria for an anaerobic wastewater treatment process

International audienceThe paper proposes an observability analysis and estimation schemes for specific growth rates for a wastewater treatment process. A 2-stage model of 6 dynamic states is assumed, describing the acidogenesis and methanogenesis of two different populations of microorganisms (acidogenic and methanogenic), and the evaluation of the total carbon dioxide production including the soluble part. The main result is that the specific growth rates of the two populations of bacteria can be stability estimated only from easily measured quantities -- the dilution rate and the flow rates of methane and carbon dioxide in the biogas

On the biomass specific growth rates estimation for anaerobic digestion using differential algebraic techniques

International audienceThe paper deals with identifiability and observability of anaerobic digestion (AD) processes. In such kind of processes, generally carried out in continuously stirred tank bioreactors, the organic matter is depolluted by microorganisms into biogas and compost in the absence of oxygen. The biogas is an additional energy source, which can replace fossil fuel sources. The differential algebraic approach of general observation problems has been applied to investigate the identification and observation of a simple AD model. The major discovery is that the biomass specific growth rate can be stably estimated from easily measured quantities: the dilution rate and the biogas flow rate. Next if the yield coefficients are assumed known then, of course, the biomass concentration is observable. Unfortunately, even under the latter strongest assumption the substrate concentration is not observable. This concentration becomes observable if an additional model, say the Monod model, is assumed for the specific growth rate. Illustrative simulations are presented

Software sensors for specific growth rates and concentrations of bacteria in the anaerobic digestion of organic waste

The paper deals with experimental studies and software sensor design for anaerobic digestion of cattle dung in a pilot plant. Software sensors for acidogenic and methanogenic bacterial concentrations and specific growth rates have been designed based upon a three-stage anaerobic digestion model, and mathematical tools stemming from differential algebra. For the first time in the known literature, they allow estimation of bacterial concentrations without having recourse to the time and resource consuming stage of bacterial specific growth rate empirical modeling. The proposed software sensors use only online values of the dilution rate, and biogas flow rate together with methane and carbon dioxide percentage in the biogas. Therefore they are simple, and easy to implement. Potential usages of the proposed software sensors are on-line monitoring (which is very useful for stable operation of industrial biogas plants) of anaerobic digestion processes, and implementation of sophisticated control strategies