Biomedical subjects

M N Karim

Publications and source records attributed to M N Karim.

4 recordsLinked to original sources

PubMed1998

Adaptive pole placement control algorithm for DO-control in beta-lactamase production.

The dissolved oxygen (DO) is an important variable in aerobic fermentations and affects the cell growth and product formation. Dissolved oxygen control is difficult in batch fermentations because of the time-varying conditions, time delays, and the probe dynamics. Modeling of the various patterns of biological activity in fermentations and their impact on the DO process dynamics is essential to both achieve a satisfactory control and to track the aforementioned patterns. An adaptive pole placement algorithm with time-delay compensation was used for controlling the DO, coupled with system identification using recursively estimated autoregressive models with exogeneous inputs (ARX). The flow rate of O2 in a constant flow rate gas inlet mixture is used as the manipulated variable. Supervision and coordination techniques are applied to improve the control performance. The control performance is affected by the accuracy of the model prediction and the selected time delay. The effect of DO level on the productivity of beta-lactamase using Bacillus subtilis under oxygen-limited conditions is investigated. Beta-lactamase stability is improved under prolonged growth conditions with low DO levels.

Aerobiosis↗

PubMed1992

Artificial neural networks in bioprocess state estimation.

The application of artificial neural networks to the estimation and prediction of bioprocess variables is presented in this paper. A neural network methodology is discussed, which uses environmental and physiological information available from on-line sensors, to estimate concentration of species in the bioreactor. Two case studies are presented, both based on the ethanol production by Zymomonas mobilis. An efficient optimization algorithm which reduces the number of iterations required for convergence is proposed. Results are presented for different training sets and different training methodologies. It is shown that the neural network estimator provides good on-line bioprocess state estimations.

Biomedical Engineering↗

PubMed1988

An analysis of sugar content of commonly used pediatric liquid medicines--its relevance to dentistry.

The sugar content of twenty-four liquid medicines commonly prescribed for infants and young children were measured and the type of sugars present were also identified in four randomly selected samples. All the liquid medicines tested contained sugar, in the range of 29.4% to 61.2%. Sucrose appeared to be the most commonly used sugar. Whilst it is agreed that sucrose makes the medicine more acceptable to children, its continual use by the pharmaceutical industry should be discontinued due to its harmful effect on the dental health of children, particularly those taking these syrup-based medicines on prolonged basis. Sugar-free alternatives such as sorbitol or saccharin should be used instead.

Carbohydrates↗

PubMedDate not supplied

Identification and control of dissolved oxygen in hybridoma cell culture in a shear sensitive environment.

The productivity of mammalian cells can be enhanced by facilitating adequate oxygen transfer into the cultivation medium. However, current methods of controlling dissolved oxygen (DO) fail to account for alterations in medium composition during the course of the fermentation. These changes, which directly affect gas solubility and overall mass transfer coefficient, may be significant and deteriorate controller's performance in the long run. In this paper, the applications of Generalized Predictive Controllers (GPC) to DO control were investigated in a shear sensitive environment and compared to PID and Model Predictive Controllers (MPC). Input and output data for system identification were initially generated by varying the composition of oxygen fed into the bioreactor from 0 to 0.21 mol % while keeping the total inlet gas flow rate at 8.75 vvm. The process was identified using an AutoRegressive model with eXogeneous inputs (ARX) model and tested on different data sets. The model parameters were then correlated with the overall mass transfer coefficients. In simulation tests, the output of the PID controller switched from minimum to maximum values while more continuous control signals were obtained with the MPC and GPC controllers. When tested in a cell-free medium, all three controllers were able to track setpoint changes with some chattering observed in the control signals. The GPC outperformed the MPC and PID controllers when applied to the cultivation of hybridoma cells.

Animals↗