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Low-cost microextraction and preconcentration procedures for biomedical applications
Vašátko, Jan ; Diviš, Pavel (referee) ; Dvořák, Miloš (advisor)
This thesis focuses on low-cost microextraction techniques and their application for purification and preconcentration of biological samples, specifically on the experimental study of supported liquid membrane (SLM) extraction. The described microextraction technique uses commercially available filtration plates as the extraction units and allows the extraction of basic drugs from biological samples of urine and blood (in the form of dried blood spots). The experimental part includes the optimization of microextraction conditions of basic drugs from real samples through a SLM coupled in-line to lab-made capillary electrophoresis. The basic optimization of microextraction conditions involved selecting the appropriate organic phase for membrane impregnation (1:1 mixture of ENB and DHE), appropriate agitation speed for sample convection during extraction (1000 rpm), and optimal ratio of donor to acceptor volumes for high preconcentration of the analytes (400:15 µL). After basic optimization, the effect of donor alkalization with NaOH on extraction recovery (ER) was investigated. For all matrices used (saline solution, undiluted human urine samples, human capillary blood eluted from dry blood spots with deionized water), the highest ER values were achieved using a neutral donor and an acidic acceptor. The extraction time (60 minutes) was optimized based on the time profile of the microextraction for 120 minutes. This optimized microextraction method is suitable for the determination of basic drugs in real matrices with sufficient sample clean-up, preconcentration and ER values.
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Mathematical Modeling of Company Efficiency Using Neural Networks in Maple
Bartulec, Tomasz ; Vašátko, Jiří (referee) ; Chvátalová, Zuzana (advisor)
The goal of this thesis is to study the possibilities of Artificial neural network as an innovative mathematical methods for financial analysis of company performance, to find out what are today´s requests for performance evaluation of companies are and to identify possible ways how to use this relatively new concept in this area. When processing the possibilities of the computer program Maple for mathematical calculations will be applied. Intermediate objectives are then acquainted with the basic principle on which the artificial neural networks works, to analyze the financial performance of specific company and evaluate potential predictive abilities of the proposed network. The result of the work should be evaluating the success of this approach to financial analysis and evaluation of its use in practice.
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Application of electrochemical methods for the determination of platinum metals
Vašátko, Jan ; Řezáčová, Veronika (referee) ; Komendová, Renata (advisor)
This bachelor thesis deals with the optimization of platinum determination conditions using electrochemical methods, namely voltammetric analysis. The theoretical part describes the physical and chemical properties of platinum and platinum group metals, their occurrence and their use. The theoretical part also deals with the toxicity of platinum group metals and their environmental cycles. Finally, other possible methods of determination are mentioned, including a detailed description of the voltammetric analysis. The experimental part describes the process of optimization of the conditions of voltammetric analysis of platinum and the application of the optimised method on real samples.
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Low-cost microextraction and preconcentration procedures for biomedical applications
Vašátko, Jan ; Diviš, Pavel (referee) ; Dvořák, Miloš (advisor)
This thesis focuses on low-cost microextraction techniques and their application for purification and preconcentration of biological samples, specifically on the experimental study of supported liquid membrane (SLM) extraction. The described microextraction technique uses commercially available filtration plates as the extraction units and allows the extraction of basic drugs from biological samples of urine and blood (in the form of dried blood spots). The experimental part includes the optimization of microextraction conditions of basic drugs from real samples through a SLM coupled in-line to lab-made capillary electrophoresis. The basic optimization of microextraction conditions involved selecting the appropriate organic phase for membrane impregnation (1:1 mixture of ENB and DHE), appropriate agitation speed for sample convection during extraction (1000 rpm), and optimal ratio of donor to acceptor volumes for high preconcentration of the analytes (400:15 µL). After basic optimization, the effect of donor alkalization with NaOH on extraction recovery (ER) was investigated. For all matrices used (saline solution, undiluted human urine samples, human capillary blood eluted from dry blood spots with deionized water), the highest ER values were achieved using a neutral donor and an acidic acceptor. The extraction time (60 minutes) was optimized based on the time profile of the microextraction for 120 minutes. This optimized microextraction method is suitable for the determination of basic drugs in real matrices with sufficient sample clean-up, preconcentration and ER values.
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Application of electrochemical methods for the determination of platinum metals
Vašátko, Jan ; Řezáčová, Veronika (referee) ; Komendová, Renata (advisor)
This bachelor thesis deals with the optimization of platinum determination conditions using electrochemical methods, namely voltammetric analysis. The theoretical part describes the physical and chemical properties of platinum and platinum group metals, their occurrence and their use. The theoretical part also deals with the toxicity of platinum group metals and their environmental cycles. Finally, other possible methods of determination are mentioned, including a detailed description of the voltammetric analysis. The experimental part describes the process of optimization of the conditions of voltammetric analysis of platinum and the application of the optimised method on real samples.
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Mathematical Modeling of Company Efficiency Using Neural Networks in Maple
Bartulec, Tomasz ; Vašátko, Jiří (referee) ; Chvátalová, Zuzana (advisor)
The goal of this thesis is to study the possibilities of Artificial neural network as an innovative mathematical methods for financial analysis of company performance, to find out what are today´s requests for performance evaluation of companies are and to identify possible ways how to use this relatively new concept in this area. When processing the possibilities of the computer program Maple for mathematical calculations will be applied. Intermediate objectives are then acquainted with the basic principle on which the artificial neural networks works, to analyze the financial performance of specific company and evaluate potential predictive abilities of the proposed network. The result of the work should be evaluating the success of this approach to financial analysis and evaluation of its use in practice.
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