Abhishek Dutta

Experimental methods and modeling techniques for description of cell population heterogeneity

With the continuous development, in the last decades, of analytical techniques providing complex information at single cell level, the study of cell heterogeneity has been the focus of several research projects within analytical biotechnology. Nonetheless, the complex interplay between environmental changes and cellular responses is yet not fully understood, and the integration of this new knowledge into the strategies for design, operation and control of bioprocesses is far from being an established reality. Indeed, the impact of cell heterogeneity on productivity of large scale cultivations is acknowledged but seldom accounted for. In order to include population heterogeneity mechanisms in the development of novel bioprocess control strategies, a reliable mathematical description of such phenomena has to be developed. With this review, we search to summarize the potential of currently available methods for monitoring cell population heterogeneity as well as model frameworks suitable for describing dynamic heterogeneous cell populations. We will furthermore underline the highly important coordination between experimental and modeling efforts necessary to attain a reliable quantitative description of cell heterogeneity, which is a necessity if such models are to contribute to the development of improved control of bioprocesses.

Cadmium(II), Lead(II), and Copper(II) Biosorption on Baker’s Yeast (Saccharomyces cerevesiae)

AbstractThe biosorption properties of ethylenediaminetetraacetate (EDTA)-treated biomass of baker’s yeast (Saccharomyces cerevisiae) are studied for the removal of Cadmium(Cd), Lead(Pb), and Copper(Cu) from artificially prepared industrial wastewater. The metal ions are chosen for biosorption studies with regard to their availability in industry and potential pollution impact. The optimum biosorption capacity of these metal ions on the biomass is obtained at pH 5. It is observed that the sorption capacity of EDTA-treated biomass increases when the initial concentration of the metal ions is increased. Both Langmuir and Freundlich isotherm models are used to fit experimental biosorption equilibrium data. The maximum biosorption capacity as determined via the Langmuir isotherm is 32.26, 200.0, and 17.24  mg/g for Cd(II), Pb(II), and Cu(II) ions, respectively. The kinetics of biosorption is studied using both pseudo first order and pseudo second order models. Based on a linear regression correlation coefficie...

Cell mass and cell cycle dynamics of an asynchronous budding yeast population: experimental observations, flow cytometry data analysis, and multi-scale modeling.

Despite traditionally regarded as identical, cells in a microbial cultivation present a distribution of phenotypic traits, forming a heterogeneous cell population. Moreover, the degree of heterogeneity is notably enhanced by changes in micro‐environmental conditions. A major development in experimental single‐cell studies has taken place in the last decades. It has however not been fully accompanied by similar contributions within data analysis and mathematical modeling. Indeed, literature reporting, for example, quantitative analyses of experimental single‐cell observations and validation of model predictions for cell property distributions against experimental data is scarce. This study focuses on the experimental and mathematical description of the dynamics of cell size and cell cycle position distributions, of a population of Saccharomyces cerevisiae, in response to the substrate consumption observed during batch cultivation. The good agreement between the proposed multi‐scale model (a population balance model [PBM] coupled to an unstructured model) and experimental data (both the overall physiology and cell size and cell cycle distributions) indicates that a mechanistic model is a suitable tool for describing the microbial population dynamics in a bioreactor. This study therefore contributes towards the understanding of the development of heterogeneous populations during microbial cultivations. More generally, it consists of a step towards a paradigm change in the study and description of cell cultivations, where average cell behaviors observed experimentally now are interpreted as a potential joint result of various co‐existing single‐cell behaviors, rather than a unique response common to all cells in the cultivation. Biotechnol. Bioeng. 2013; 110: 812–826.

Tuning algorithms for fractional order internal model controllers for time delay processes

ABSTRACT This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.

Implementation of Homotopy Perturbation Method to Solve a Population Balance Model in Fluidized Bed

Abstract: A particle population balance formulation for a circulating fluidized bed, involving aggregation and breakage of particles, is solved using the homotopy perturbation method (HPM). The homotopy method deforms a difficult problem into a simple problem, which then can be easily solved. The HPM solution is compared with the solution obtained using a standard finite difference method. Using homotopy, a good approximation of the finite difference solution is obtained within a few iteration steps. The results reveal that the homotopy method is an effective and simple tool to solve nonlinear partial integro-differential equations and has a wide scope and applicability to solve complex engineering problems. The reliability of the algorithm is tested using three different feed inlet particle size (diameter) distributions to indicate the robustness of this method.

Robust and two-level (nonlinear) predictive control of switched dynamical systems with unknown references for optimal wet-clutch engagement

Modeling and control of clutch engagement has been recognized as a challenging control problem, due to nonlinear and time-varying dynamics, that is, switching between two discontinuous dynamic phases: the fill and the slip. Furthermore, the reference trajectories for obtaining an optimal clutch engagement are not a priori known and may require adaptation to varying operating conditions. Two (nonlinear) model predictive control strategies are proposed based on the partial or full (non)linear identification of these two phases. First, a local linear model of the fill phase is identified and a robust model predictive control is designed to account for the consequent uncertainty in the slip phase. Second, (non)linear models of both the fill and the slip phases are identified and a two-level (nonlinear) model predictive control controller is proposed, where two (nonlinear) model predictive control controllers are designed for the two phases tracking references generated and continuously adapted by high-level iterative learning controllers. The robust and two-level (nonlinear) model predictive controls are validated on a real clutch. The results obtained from the real setup show that the proposed control strategies lead to an optimal engagement of the wet-clutch system.

Role of Fermentation in Improving Nutritional Quality of Soybean Meal - A Review.

Soybean meal (SBM), a commonly used protein source for animal feed, contains anti-nutritional factors such as trypsin inhibitor, phytate, oligosaccharides among others, which limit its utilization. Microbial fermentation using bacteria or fungi has the capability to improve nutritional value of SBM by altering the native composition. Both submerged and solid state fermentation processes can be used for this purpose. Bacterial and fungal fermentations result in degradation of various anti-nutritional factors, an increase in amount of small-sized peptides and improved content of both essential and non-essential amino acids. However, the resulting fermented products vary in levels of nutritional components as the two species used for fermentation differ in their metabolic activities. Compared to SBM, feeding non-ruminants with fermented SBM has several beneficial effects including increased average daily gain, improved growth performance, better protein digestibility, decreased immunological reactivity and undesirable morphological changes like absence of granulated pinocytotic vacuoles.

A Linear Driving Force (LDF) Approximation of Moisture Diffusion Kinetics in White Rice

Soaking characteristics of white rice grain in water are studied at 25, 40, 60, 70 and 80 °C. The kinetics of mass transfer are modeled using a linear driving force (LDF) approximation with constant diffusivity, which is capable of predicting the moisture ratio profile with time. This approximation is a relatively new approach in food engineering applications for systems in which the rate of mass transfer is controlled by intra-particle diffusion and nonlinear adsorption through porous adsorbent. The mass transfer is also modeled through Ficks law for unsteady-state diffusion using finite difference (FD) method, and compared with the LDF model. In general, the moisture uptake curves calculated with this new approximation compare favorably with the finite difference solution obtained in spherical coordinates, producing results of similar accuracy. Both the methods give a good agreement with the experimental data. The values of the effective diffusion coefficients are between 7.33×10-11 m2/s and 1.43×10-10 m2/s for a temperature of 25 and 80 °C respectively. Although gelatinization of starch is observed at a higher temperature which influences the increase in moisture content, the moisture uptake curves calculated with this new approximation compare favorably with the numerical solution of the non-linear diffusion equation. As such, it can be safely used to predict the unsteady-state moisture absorption kinetics of a rice grain, for the temperature range investigated.

Robust predictive control design for optimal wet-clutch engagement

Modeling of hydraulic clutch transmissions is far from straightforward due to their nonlinear hybrid dynamics, i.e. switching between three dynamic phases. In this paper we identify a local linear model only for the constrained first phase, based on which a predictive controller is used to track a suitable engagement signal. The robustness of this controller in the latter two phases is guaranteed by making the constraints inactive and pre-tuning the control parameters based on its closed loop formulation and applying robust stability theorem. This controller is then implemented in real-time on a wet-clutch test setup and is shown to achieve optimal engagement.

Robust penalty adaptive model predictive control (PAMPC) of constrained, underdamped, noncollocated systems

This paper investigates the control challenges posed by noncollocated mechatronic systems and motivates the need for a model-based control technique towards such systems. A novel way of online constraint handling by penalty adaptation (PAMPC) is proposed and shown to be of particular relevance towards robust control of underdamped, noncollocated systems by exploiting the structure of such systems. Further, a new tunneling approach is proposed for PAMPC to maintain feasibility under uncertainty. The PAMPC is shown to be optimal for control of a benchmark mass–spring–damper system, which poses all the mentioned challenges.