Pentachlorophenol (PCP) is a priority environmental pollutant in North America that was widely used as a wide-spectrum biocide in the last century. Pentachlorophenol 4-monooxygenase (PcpB) is the first and rate-limiting enzyme in the PCP biodegradation pathway in <i>Sphingobium chlorophenolicum</i> ATCC 39723.<p> Pentachlorophenol 4-monooxygenase (PcpB) catalyzes the hydroxylation of pentachlorophenol in the pentachlorophenol biodegradation pathway in Sphingobium chlorophenolicum. Previous studies from two different research groups proposed oppositely that the catalytic product of PcpB was tetrachlorohydroquinone (TCHQ) and tetrachlorobenzoquinone (TCBQ). We re-examined the identity of the catalytic product of PcpB, because TCHQ and TCBQ are present in a redox-equilibrium in aqueous solutions and the chemical reagents NADPH, ethyl acetate and glutathione used for the product detection in the previous studies may shift the redox-equilibrium. In this study, we investigated the effects of NADPH, ethyl acetate and glutathione on the redox-equilibrium and product distribution. Under newly designed experimental conditions, we confirmed unambiguously that the catalytic product of PcpB is TCHQ instead of TCBQ. We also propose that TCBQ may be produced non-specifically by peroxidases within the bacterial cells and that TCBQ reductase (PcpD) might act as a self-protective rather than a PCP-degradation enzyme. <p> There is no glutathione S-transferase (GST) activity for wild type of PcpC, PcpC (C13S) mutant and a surface loop deletion mutant PcpC (LD). In the crystallization studies, PcpC (C13S), PcpB and PcpA were over-expressed and purified to >95% purity using Ni-NTA based affinity chromatography. Initial crystallization conditions have been obtained for all three enzymes from both in-house screening using the screening kits from Qiagen-Nextal and high throughput screening at the Hauptman-Woodward Institute, Buffalo, New York. Further structural determination studies will be undertaken upon obtaining large crystals suitable for X-ray diffraction data collection.

In this thesis it has been studied how operational and workshop data can be used to improve the handling of field quality (FQ) issues for electronic units. This was done by analysing how failure rates can be predicted, how failure mechanisms can be detected and how data-based lifetime models could be developed. The work has been done on an electronic control unit (ECU) that has been subject to a field quality (FQ) issue, determining thermomechanical stress on the solder joints of the BGAs (Ball Grid Array) on the PCBAs (Printed circuit board assembly) to be the main cause of failure. The project is divided into two parts. Part one, "PCBA" where a laboratory study on the effects of thermomechanical cycling on solder joints for different electrical components of the PCBAs are investigated. The second part, "ECU" is the main part of the project investigating data-driven solutions using operational and workshop history data. The results from part one show that the Weibull distribution commonly used to predict lifetimes of electrical components, work well to describe the laboratory results but also that non parametric methods such as kernel distribution can give good results. In part two when Weibull together with Gamma and Normal distributions were tested on the real ECU (electronic control unit) data, it is shown that none of them describe the data well. However, when random forest is used to develop data-based models most of the ECU lifetimes of a separate test dataset can be correctly predicted within a half a year margin. Further using random survival forest it was possible to produce a model with just 0.06 in (OOB) prediction error. This shows that machine learning methods could potentially be used in the purpose of condition based maintenance for ECUs.

As electronics are getting both smaller and more advanced, the need to verify and validate remains and the means are getting more complex the more functions and components are added. Traditionally, in-circuit tests (ICTs) are performed by probing dedicated test points on the Printed Circuit Board Assembly (PCBA) in a test sequence that is unique to each product. But as the density of components increases, the choice between component and test point must be considered. Instead of decreasing the reliability during verification by having to remove less system-critical test points, this thesis suggests the use of a near-field probe (NFP) based around a Giant Magneto-Resistance (GMR) sensor to possibly replace the need for a physical test point by instead performing contactless testing. The use of a GMR sensor allows for bandwidth from 0 Hz up to the MHz range, whereas commercial NFPs are based on a different technique and are operational from the MHz range and up. The goal of this project was to improve the non-linearity of typically 15% present in the AAH002-02 model from NVE by the use of an analogue closed-loop magnetic feedback circuit. The project successfully improved the linearity to 99.8% by the use of an instrumentation amplifier, a subtractor and a push-pull amplifier in conjunction with a 3x30 turn planar coil embedded in a PCB, located beneath the sensor Integrated Circuit (IC). The resulting linearity was verified by a Helmholtz coil where a uniform magnetic field was produced with linearly increased field strength, and calculated using the R2 value from a linear regression analysis on the acquired data. In the future, the data acquired from this kind of NFP could be used together with a Machine Learning (ML) model to remove the manual labour required when constructing these product-unique test sequences. / Dagens elektronik blir både mindre och mer avancerad, men behovet av verifiering och validering av dessa kvarstår och metoderna för detta ökar i komplexitet ju fler funktioner och komponenter som läggs till. Dagens kretskortstester genomförs genom att sondera dedikerade testpunkter strategiskt utplacerade på kretskortet enligt en testsekvens som är unikt skapad för varje produkt. Men med att densiteten av komponenter ökar måste valet mellan komponent och testpunkt tas i beaktning. Instället för att minska tillförlitligheten vid validering genom att ta bort mindre kritiska testpunkter föreslår denna avhandling användandet av en närfältssond baserad runt en Giant Magneto-Resistance (GMR)-sensor för att möjligen ersätta behovet av en fysisk testpunkt genom att istället genomföra kontaktlös testning. Användandet av en GMR-sensor tillåter en bandbredd från 0 Hz upp till MHzområdet, där kommersiella närfältssonder är baserade på annan teknik och är funktionsdugliga från MHz-området och uppåt. Målet med detta projekt var att förbättra olinjäriteten på typiskt 15% som är närvarande hos en sensor av modell AAH002-02 från NVE genom en analog magnetisk återkopplingskrets med sluten slinga. Projektet lyckades förbättra linjäriteten till 99.8% genom användandet av en intrumentförstärkare, en subtraherare och en push-pull-förstärkare i samverkan med en plan spole på 3x30 varv inbyggd i ett mönsterkort placerd under sensorns integrerade krets. Den resulterande linjäriteten validerades med hjälp av en Helmholtz-spole där ett uniformt magnetfält producerades med linjärt ökande fältstyrka och beräknades genom R2 -värdet från en linjär regression-analys på den inhämtade datan. I framtiden kan datan som inhämtats från den här sortens närfältssond kunna användas tillsammans med en maskininlärningsmodell för att ersätta det manuella arbetet som idag krävs för att konstruera dessa produktunika testsekvenser