Bioautomation

Volume 13, Issue 2
Editorial
In Memoriam
Anniversary
New Books
Forthcoming Events
1^st National Conference with International Participation on Biomedical and Bioprocess Engineering - BM & BP'2009
22^nd International Symposium "Bioprocess Systems - BioPS'2010"
Important Note
Because of changing the numbering style of the Journal in 2009 from four volumes per year to one volume with four issues per year, volume 13 issue 2 follows immediately after volume 12.
Invited Paper
Analyses of Methods and Algorithms for Modelling and Optimization of Biotechnological Processes	1-18
Stoyan Stoyanov [ +/- abstract ] [ full text ]
A review of the problems in modeling, optimization and control of biotechnological processes and systems is given in this paper. An analysis of existing and some new practical optimization methods for searching global optimum based on various advanced strategies - heuristic, stochastic, genetic and combined are presented in the paper. Methods based on the sensitivity theory, stochastic and mix strategies for optimization with partial knowledge about kinetic, technical and economic parameters in optimization problems are discussed. Several approaches for the multi-criteria optimization tasks are analyzed. The problems concerning optimal controls of biotechnological systems are also discussed.
Bioinformatics
Numerical Modelling of Drug Release from 2D HPMC-Matrices	19-26
Rumiana Blagoeva, Assen Nedev [ +/- abstract ] [ full text ]
The article considers numerical modelling of drug release from HPMC-matrices assuming the main controlling processes are diffusion of water and drug and swelling of the matrix. A detailed mathematical description of matrix swelling, connected with the free boundary conditions of the arisen model problem, is introduced. A numerical approach to solution of the posed nonlinear 2D problem is developed on the basis of finite element domain approximation and time difference method. It is implemented in noncommercial software which is used for numerical simulation of fractional drug release under various shapes and sizes of the tablets. This investigation of the effect of aspect ratio (radius/height) and sizes of HPMC tablets on drug release is an inexpensive and effective tool to modify the release kinetics. The proposed numerical approach enables further generalization of the model and performing more profound investigations of the effect of the initial drug loading, matrix erosion and type of release medium.
Statistical Procedures for Finding Distribution Fits over Datasets with Applications in Biochemistry	27-44
Natalia Nikolova, Daniela Toneva, Ana-Maria Tenekedjieva [ +/- abstract ] [ full text ]
A common problem in statistics is finding a distribution that fits to a certain dataset. Many theoretical distributions have been developed to give a good description of the empirical observations, and consequently, theory offers a variety of algorithms to test the quality of the resulting fits. It is reasonable to expect that each set of measurements should be described with the same theoretical distribution if one and the same experimental mechanism was applied. This paper presents procedures to find a theoretical distribution that best fits to several datasets. The procedure goes further, answering the questions of whether the given datasets come from the same general population, and assessing if the difference between the fitted distributions of two datasets are statistically significant. Kuiper test is used in all steps of the analysis. In two of those a Monte Carlo simulation procedure is elaborated to construct the Kuiper statistic's distribution. A platform with original program functions in MATLAB R2009a is created on the basis of the described procedures. It is applied to datasets from a biochemical experiment, which investigates the resulting density of fibrin network under different thrombin concentrations. The developed procedure has wide applications in different fields, as it models the behavior of datasets, generated through the same mechanism. The possibility to fit one type of distribution over different datasets allows comparing samples, performing interpolation and extrapolation procedures, and investigating the influence of the input conditions of an experiment over the parameters of the fitted distributions.
Bioprocess Systems
Application of Different Mixing Systems for the Batch Cultivation of the Saccharomyces cerevisiae. Part I: Experimental Investigations and Modelling	45-60
Uldis Viesturs, Andrejs Berzins, Juris Vanags, Stoyan Tzonkov, Tatiana Ilkova, Mitko Petrov, Tania Pencheva [ +/- abstract ] [ full text ]
Experimental investigations in different mixing conditions (impulse and vibromixing) in a Saccharomyces cerevisiae batch cultivation are presented in this paper. The investigation is carried out in a 5 l laboratory bioreactor (working volume 3 l). Mathematical models of the process for the two mixing systems are developed. The obtained results have shown that the models are adequate and will be used for process optimisation for the two mixing systems.
Preferences based Control Design of Complex Fed-batch Cultivation Process	61-72
Yuri Pavlov [ +/- abstract ] [ full text ]
In the paper is presented preferences based control design and stabilization of the growth rate of fed-batch cultivation processes. The control is based on an enlarged Wang-Monod-Yerusalimsky kinetic model. Expected utility theory is one of the approaches for utilization of conceptual information (expert preferences). In the article is discussed utilization of stochastic machine learning procedures for evaluation of expert utilities as criteria for optimization.
Biomedical Systems
Meta-analytic Tools for Research on Gestational Diabetes Mellitus	73-83
Anthony Shannon, C. K. Wong [ +/- abstract ] [ full text ]
The purpose of this paper is to utilize the approach of meta-analysis to survey trends in the diagnosis and management of gestational diabetes mellitus.
Rhythm Analysis by Heartbeat Classification in the Electrocardiogram	84-96
Ivaylo Christov, Irena Jekova, Vessela Krasteva, Ivan Dotsinsky, Todor Stoyanov [ +/- abstract ] [ full text ]
The morphological and rhythm analysis of the electrocardiogram (ECG) is based on ventricular beats detection, wave parameters measurement, as amplitudes, widths, polarities, intervals and relations between them, and a subsequent classification supporting the diagnostic process. Number of algorithms for detection and classification of the QRS complexes have been developed by researchers in the Centre of Biomedical Engineering � Bulgarian Academy of Sciences, and are reviewed in this material. Combined criteria have been introduced dealing with the QRS areas and amplitudes, the waveshapes evaluated by steep slopes and sharp peaks, vectorcardiographic (VCG) loop descriptors, RR intervals irregularities. Algorithms have been designed for application on a single ECG lead, a synthesized lead derived by multichannel synchronous recordings, or simultaneous multilead analysis. Some approaches are based on templates matching, cross-correlation or rely on a continuous updating of adaptive thresholds. Various beat classification methods have been designed involving discriminant analysis, the K-th nearest neighbors, fuzzy sets, genetic algorithms, neural networks, etc. The efficiency of the developed methods has been assessed using internationally recognized arrhythmia ECG databases with annotated beats and rhythm disturbances. In general, high values for specificity and sensitivity competitive to those reported in the literature have been achieved.