Comparison of single and joint effects of Zn and Cu in continuous flow and batch reactors

BACKGROUND: Microbial behavior in batch reactors may be different from that in continuous flow reactors, which is expected to affect microbial response to heavy metal exposure. Four parallel continuous flow reactors and batch growth tests were used to investigate the single and joint toxicity of Zn and Cu to Artrobacter sp. JM018. RESULTS: The results indicated that Cu is more toxic than Zn under all conditions. In the batch reactors, all Zn concentrations showed a stimulatory effect on microbial growth. However in the continuous system, 125 µmol L^?1 Zn exposure produced inhibition. In the case of mixed Zn and Cu exposures in the batch system, the presence of Zn reduced the severity of Cu inhibition, with a net impact of reduced growth in all cases, whereas in the continuous system microbial growth and substrate utilization rates sharply decreased and ceased. CONCLUSION: The results clearly showed that growth in batch reactors underestimated significantly the heavy metal inhibition, compared with the continuous system. Therefore, the results of batch reactor tests should not be used directly when heavy metal inhibition is to be interpreted for continuous flow systems. Copyright © 2011 Society of Chemical Industry     

A CELL KINETIC STUDY ON THE CANCER PROBLEM BASED ON THE AUTOMATIC CONTROL THEORY USING DIGITAL SIMULATION

Abstract

This paper deals with a general multi-loop automatic control system of the cell renewal process which makes possible the study of the dynamic response of a complete cell group or a compartment. At the same time the behavior of a single cell is observed as to the variability of its mean life span and the possibility of its irradication at any desired moment.

By means of the special block-oriented programming language ASIM (Analog SIMulation) of AEG-Telefunken numerous disturbed cases have been simulated, for example the response to perturbation of the cell numbers in different compartments has been calculated and thoroughly studied.

Several cell renewal systems, both normal and impaired growth, have been simulated and the results interpreted. The mean life span of the cells has been varied and structural changes of the feedback loops of the complex multivariable control system have been carried out.

The aforementioned cases in particular lead to the basic question whether malignant disorders are to be interpreted as unstable closed-loop control systems, the cause for the malignant growth being a structural defect of the feedback mechanism.     

State estimation of dynamical systems with nonlinearities by using proportional-integral observer

In this paper the application of a PI observer technique to dynamical systems with nonlinearities is proposed. The PI observer has two feedback loops, a proportional loop and an integral loop of the estimation error. In this way the PI observer combines the structures of the practical orientated nonlinearity observer developed by the third author and the classical Luenberger observer. The structure and the estimation performance of the PI observer are discussed and analysed. The results show that the PI observer can estimate the states not only of linear systems, but also, more significantly, of systems with any arbitrary external input which appear as unknown input, nonlinearity or unmodelled dynamics. It is shown that the PI observer works with weak assumptions, which can be fulfilled by many classes of systems to be observed. Owing to the weak assumptions it can improve many observer-based technical solutions as diagnosis or control based on observers. In the paper the conditions are given and proved. The design method is declared and carried out with illustrative examples of a linear system and of a nonlinear system of a link manipulator with flexible joints. The results are good and they show the efficiency of the PI observer. In the case of nonlinear systems the advantages of ‘robustness’ and the model independency of the proposed observer scheme can be shown clearly.     

Competitiveness analysis of automotive industry in Turkey using Bayesian networks

The purpose of this study is to analyze the relations between the factors that enable national competitive advantage and the establishment of competitive superiority in automotive industry through a comprehensive analytical model. Bayesian networks (BN) are used to investigate the associations of different factors in the automotive industry which lead to competitive advantage. The results of the study focus on building a road map for the automotive sector policy makers in their way to improve the competitiveness through scenario analysis. Using the probabilistic dependency structure of the Bayesian network all of the variables in the model can be estimated. Thus, with the proposed model the automotive industry can be analyzed as a whole system and not only in terms of single variables. Findings of the model indicate that technological developments in automotive industry can alter the nature of competition in this industry.     

Experiences in building a Grid-based platform to serve Earth observation training activities

Earth observation data processing and storing can be done nowadays only using distributed systems. Experiments dealing with a large amount of data are possible within the timeframe of a lesson and can give trainees the freedom to innovate. Following these trends and ideas, we have built a proof-of-the-concept platform, named GiSHEO, for Earth observation educational tasks. It uses Grid computing technologies to analyze and store remote sensing data, and combines them with eLearning facilities. This paper provides an overview of the GiSHEO's platform architecture and of its technical and innovative solutions.     

Investigation of surface roughness in the milling of Al7075 and open-cell SiC foam composite and optimization of machining parameters

In the present study, aluminum alloy 7075 (Al7075)-based open-cell silicon carbide (SiC) foam composite was fabricated and the machinability of both Al7075 and the open-cell SiC foam Al metal matrix composite was investigated during milling using an uncoated carbide tool. The machining trials were conducted using the Taguchi L₂₇ full-factorial orthogonal array, and the milling parameters were optimized for surface roughness. Analysis of variance was employed to determine the effect of the cutting variables on surface roughness. The experimental results were evaluated by signal-to-noise ratio, 3D surface graphs, artificial neural networks (ANNs) and main effect graphs. The analysis results show that the feed rate was the most significant milling parameter affecting surface roughness of both Al7075 and the open-cell SiC foam composite. Prediction models have been developed for the surface roughness through regression analysis and ANNs. Confirmation experiments were performed to identify the performance of mathematical models, and the surface roughness was predicted with a mean squared error equal to 1.6 and 0.24 % in the milling of Al7075 and open-cell SiC foam composite, respectively. The test result showed that the three-dimensional open-pore SiC foam network reinforcement was restricted the movement of the soft matrix and provided an acceptable surface quality in the milling of MMCs.

     

Influence of Growth Rate on Eutectic Spacing,Microhardness, and Ultimate Tensile Strength in the Directionally Solidified Al-Cu-Ni Eutectic Alloy

Metallurgical and Materials Transactions B - In this work, the mechanical properties of the Al-Cu-Ni eutectic alloy, Al-32.5 wt pct Cu-1 wt pct Ni, were investigated in terms of...     

Effects of Different Oil Sources and Residues on Biomass and Metabolite Production by Yarrowia lipolytica YB 423-12

Yarrowia lipolytica is known to have the ability to assimilate hydrophobic substrates like triglycerides, fats, and oils, and to produce single-cell oils, lipases, and organic acids. The aim of the present study was to investigate the effects of different oil sources (borage, canola, sesame, Echium, and trout oils) and oil industry residues (olive pomace oil, hazelnut oil press cake, and sunflower seed oil cake) on the growth, lipid accumulation, and lipase and citric acid production by Y. lipolytica YB 423-12. The maximum biomass and lipid accumulation were observed with linseed oil. Among the tested oil sources and oil industry residues, hazelnut oil press cake was the best medium for lipase production. The Y. lipolytica YB 423-12 strain produced 12.32 ± 1.54 U/mL (lipase activity) of lipase on hazelnut oil press cake medium supplemented with glucose. The best substrate for citric acid production was found to be borage oil, with an output of 5.34 ± 0.94 g/L. The biotechnological production of valuable metabolites such as single-cell oil, lipase, and citric acid could be achieved by using these wastes and low-cost substrates with this strain. Furthermore, the cost of the bio-process could also be significantly reduced by the utilization of various low-cost raw materials, residues, wastes, and renewable resources as substrates for this yeast.     

Interval analysis based robust truss optimization with continuous and discrete variables using mix-coded genetic algorithm

The problem of optimizing truss structures in the presence of uncertain parameters considering both continuous and discrete design variables is studied. An interval analysis based robust optimization method combined with the improved genetic algorithm is proposed for solving the problem. Uncertain parameters are assumed to be bounded in specified intervals. The natural interval extensions are employed to obtain explicitly a conservative approximation of the upper and lower bounds of the structural response, and hereby the bounds of the objective function and the constraint function. This way the uncertainty design may be performed in a very efficient manner in comparison with the probabilistic analysis based method. A mix-coded genetic algorithm (GA), where the discrete variables are coded with binary numbers while the continuous variables are coded with real numbers, is developed to deal with simultaneously the continuous and discrete design variables of the optimization model. An improved differences control strategy is proposed to avoid the GA getting stuck in local optima. Several numerical examples concerning the optimization of plane and space truss structures with continuous, discrete or mixed design variables are presented to validate the method developed in the present paper. Monte Carlo simulation shows that the interval analysis based optimization method gives much more robust designs in comparison with the deterministic optimization method.     

Comparison of lactic acid bacteria diversity during the fermentation of Tarhana produced at home and on a commercial scale

Food Science and Biotechnology - In this study, lactic acid bacteria diversity during the fermentation of homemade and commercially prepared Tarhana, a traditional fermented cereal food from...