Modernin arkeologian anti antiikintutkimukselle

Eeva-Maria Viitanen

Suomalaisen nuorisotutkimuksen anti yksissä kansissa

Hannu Välimäki

Itsetuhon laillistettu (anti)sankari

Luettua

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Effects of Cytochrome P450 Enzyme Inhibitors on the Pharmacokinetics of Nonsteroidal Anti-inflammatory Drugs and Venlafaxine

Cytochrome P450 (CYP) enzymes play a pivotal role in the metabolism of many drugs. Inhibition of CYP enzymes usually increases the plasma concentrations of their substrate drugs and can thus alter the safety and efficacy of these drugs. The metabolism of many widely used nonsteroidal antiinflammatory drugs (NSAIDs) as well as the metabolism of the antidepressant venlafaxine is nown to be catalyzed by CYP enzymes. In the present studies, the effect of CYP inhibition on the armacokinetics and pharmacodynamics of NSAIDs and venlafaxine was studied in clinical trials with healthy volunteers and with a crossover design, by using different antifungal agents as CYP inhibitors. The results of these studies demonstrate that the inhibition of CYP enzymes leads to increased concentrations of NSAIDs. In most cases, the exposure to ibuprofen, diclofenac, etoricoxib, and meloxicam was increased 1.5to 2 fold when they were used concomitantly with antifungal agents. CYP2D6 inhibitor, terbinafine, substantially increased the concentration of parent venlafaxine, whereas the concentration of active moiety of venlafaxine (parent drug plus active metabolite) was only slightly increased. Voriconazole, an inhibitor of the minor metabolic pathway of venlafaxine, produced only minor changes in the pharmacokinetics of venlafaxine. These studies show that an evident increase in the concentrations of NSAIDs may be expected, if they are used concomitantly with CYP inhibitors. However, as NSAIDs are generally well tolerated, use of single doses of NSAIDs concomitantly with CYP inhibitors is not likely to adversely affect patient safety, whereas clinical relevance of longterm concomitant use of NSAIDs with CYP inhibitors needs further investigation. CYP2D6 inhibitors considerably affect the pharmacokinetics of venlafaxine, but the clinical significance of this interaction remains unclear.

Fourier self-deconvolution in coherent anti-Stokes Raman scattering spectrum analysis

Coherent anti-Stokes Raman scattering (CARS) microscopy is rapidly developing into a unique microscopic tool in biophysics, biology and the material sciences. The nonlinear nature of CARS spectroscopy complicates the analysis of the received spectra. There were developed mathematical methods for signal processing and for calculations spectra. Fourier self-deconvolution is a special high pass FFT filter which synthetically narrows the effective trace bandwidth features. As Fourier self-deconvolution can effectively reduce the noise, which may be at a higher spatial frequency than the peaks, without losing peak resolution. The idea of the work is to experiment the possibility of using wavelet decomposition in spectroscopic for background and noise removal, and Fourier transformation for linenarrowing.