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The explosive expansion of the population of the Metropolitan Region of Curitiba raised a high increase in the demand for water resources and the uncontrolled settlement poses a large problem for the environment. The greatest menace to the water supply sources of this region is the urban occupation (invasion) into the areas that contain these resources. This occupation continues with its slow, silent, although progressive march, threatening precious and irreplaceable resources. From this background an area in the direct vicinity north-east of Curitiba has been studied. In this area a drinking water reservoir was constructed in the time that the study took place in the Iraí-basin. The Iraí-reservoir even though an area around the lake will be protected may be polluted by two tributaries which flow through more or less densely populated areas. In the study area on the same time wells have been constructed. To estimate what the impact may be from the possibly polluted reservoir on the aquifer a groundwater flow model has been constructed. On the same time to estimate the water balance and the spatial distribution of pollution vulnerability the hydrological model MODBIL has been used. Also other methods have been used to estimate the pollution vulnerability to make a comparison and because none of the methods takes every aspect into account. With the calibrated groundwater flow model for the situation before the construction of the Iraí-reservoir and after its construction, simple particle tracking transport models are constructed as scenarios how the water of the aquifer may be influenced.
Recent advances in the development of immunoassays and nucleic acid assays have improved the performance and increased the sensitivity of sensors that are based on biochemical recognition. The new approaches taken by researchers include detecting pathogens by detecting their nucleic acids, using new nontoxic reporter entities for generating signals, and downscaling and miniaturizing sensors to micromigration and microfluidic formats. This dissertation connects some of these successful approaches, thereby leading to the development of novel nucleic acid sensors for rapid and easy detection of pathogens. The author's goal was to develop diagnostic tools that enable investigators to detect pathogens rapidly and on site. While the sensors can be used to detect any pathogen, the author first customized them for detecting particularly Cryptosporidium parvum, a pathogen whose detection is important, yet presents many challenges. Chapter 2 of this thesis presents a novel test-strip for the detection of C. parvum. The test-strip is designed to detect nucleic acids rather than proteins or other epitopes. While test strips are commonly used for sensors based on immunological recognition, this format is very new in applications in which nucleic acids are detected. Further, to indicate the presence or absence of a specific target on the test strip, dye-entrapped, oligonucleotide-tagged liposomes are employed. Using liposomes as reporter particles has advantages over using other reporter labels, because the cavity that the phospholipidic membranes of the liposomes form can be filled with up to 106 dye molecules. By using heterobifunctional linkers liposomes can be tagged with oligonucleotides, thereby enabling their use in nucleic acid hybridization assays. The developed test-strip provides an internal control. The limit of detection is 2.7 fmol/mL with a sample volume of 30 mL. In chapter 3 the detection of nucleic acids by means of oligonucleotide-tagged liposomes is scaled down to a microfluidic assay format. Because the application of biosensors to microfluidic formats is very new in the field of analytical chemistry, the first part of this chapter is devoted to developing the design and the method to fabricate the microchip devices. The performance of the microchips is then optimized by investigating the interactions of nucleic acids and liposomes with the material the chips consist of and by passivating the surface of the chips with blocking reagents. The developed microfluidic chip enabled us to reduce the sample volume needed for one assay to 12.5 mL. The limit of detection of this assay was determined to be 0.4 fmol/mL. Chapters 4 and 5 expand on the development of the microfluidic assay. A prototype microfluidic array that is able to detect multiple analytes in a single sample simultaneously is developed. Using such an array will enable investigators to detect pathogens that occur in the same environment, for example, C. parvum and Giardia duodenalis by conducting a single test. The array's ability to perform multiple sample analysis is shown by detecting different concentrations of target nucleic acids. Further, the author developed a microfluidic chip in which interdigitated microelectrode arrays (IDAs) that consist of closely spaced microelectrodes are integrated. The IDAs facilitate electrochemical detection of cryptosporidial RNA. Electrochemical detection schemes offer benefits of technical simplicity, speed, and sensitivity. In this project liposomes are filled with electrochemically active molecules and are then utilized to generate electrochemical signals. Chapter 6 explores the feasibility of liposomes for enhancing signals derived from nucleic acid hybridization in surface plasmon resonance (SPR) spectroscopy. SPR spectroscopy offers advantages because nucleic acid hybridization can be monitored in real time and under homogeneous conditions because no washing steps are required. SPR spectroscopy is very sensitive and it can be expected that, in the future, SPR will be integrated into microfluidic nucleic acid sensors.
In the last 40 years, complexity theory has grown to a rich and powerful field in theoretical computer science. The main task of complexity theory is the classification of problems with respect to their consumption of resources (e.g., running time or required memory). To study the computational complexity (i.e., consumption of resources) of problems, similar problems are grouped into so called complexity classes. During the systematic study of numerous problems of practical relevance, no efficient algorithm for a great number of studied problems was found. Moreover, it was unclear whether such algorithms exist. A major breakthrough in this situation was the introduction of the complexity classes P and NP and the identification of hardest problems in NP. These hardest problems of NP are nowadays known as NP-complete problems. One prominent example of an NP-complete problem is the satisfiability problem of propositional formulas (SAT). Here we get a propositional formula as an input and it must be decided whether an assignment for the propositional variables exists, such that this assignment satisfies the given formula. The intensive study of NP led to numerous related classes, e.g., the classes of the polynomial-time hierarchy PH, P, #P, PP, NL, L and #L. During the study of these classes, problems related to propositional formulas were often identified to be complete problems for these classes. Hence some questions arise: Why is SAT so hard to solve? Are there modifications of SAT which are complete for other well-known complexity classes? In the context of these questions a result by E. Post is extremely useful. He identified and characterized all classes of Boolean functions being closed under superposition. It is possible to study problems which are connected to generalized propositional logic by using this result, which was done in this thesis. Hence, many different problems connected to propositional logic were studied and classified with respect to their computational complexity, clearing the borderline between easy and hard problems.