Modular framework for outlier detection

Outlier detection is an important form of data analysis because outliers in several cases contain the interesting and important pieces of information. In the recent years, many different outlier detection algorithms have been devised for finding different kinds of outliers in varying contexts and environments. Some effort has been put to study how to effectively combine different outlier detection methods. The combination of outlier detection algorithms as an ensemble was studied in this thesis by designing a modular framework for outlier detection, which combines arbitrary outlier detection techniques. This work resulted in an example implementation of the framework. Outlier detection capability of the ensemble method was validated using datasets and methods found in outlier detection research. The framework achieved better results than the individual outlier algorithms. Future research includes how to handle large datasets effectively and the possibilities for real-time outlier monitoring.

Capillary electrophoresis: Applicability and method validation for biorefinery analytics

Wood-based bioprocesses present one of the fields of interest with the most potential in the circular economy. Expanding the use of wood raw material in sustainable industrial processes is acknowledged on both a global and a regional scale. This thesis concerns the application of a capillary zone electrophoresis (CZE) method with the aim of monitoring wood-based bioprocesses. The range of detectable carbohydrate compounds is expanded to furfural and polydatin in aquatic matrices. The experimental portion has been conducted on a laboratory scale with samples imitating process samples. This thesis presents a novel strategy for the uncertainty evaluation via in-house validation. The focus of the work is on the uncertainty factors of the CZE method. The CZE equipment is sensitive to ambient conditions. Therefore, a proper validation is essential for robust application. This thesis introduces a tool for process monitoring of modern bioprocesses. As a result, it is concluded that the applied CZE method provides additional results to the analysed samples and that the profiling approach is suitable for detecting changes in process samples. The CZE method shows significant potential in process monitoring because of the capability of simultaneously detecting carbohydrate-related compound clusters. The clusters can be used as summary terms, indicating process variation and drift.

Detection, Identification and Molecular Variation of Human Enteroviruses

Picornaviruses are the most common human viruses and the identification of the picornaviruses is nowadays based on molecular techniques, for example, reverse transcriptase polymerase chain reaction (RT-PCR). One aim of this thesis was to improve the identification of picornaviruses, especially rhino- and enteroviruses, with a real-time assay format and, also, to improve the differentiation of the viruses with genus-specific locked nucleic acid (LNA) probes. Another aim was to identify and study the causative agent of the enterovirus epidemics that appeared in Finland during seasons 2008-2010. In this thesis, the first version of picornavirus qRT-PCR with a melting curve analysis was used in a study of rhinovirus transmission within families with a rhinovirus positive index child where rhinovirus infection was monitored in all family members. In conclusion, rhinoviruses spread effectively within families causing mostly symptomatic infections in children and asymptomatic infections in adults. To improve the differentiation between rhino- and enterovirus the picornavirus qRT-PCR was modified with LNA-incorporated probes. The LNA probes were validated with picornavirus prototypes and different clinical specimen types. The LNA probe-based picornavirus qRT-PCR was able to differentiate all rhino- and enteroviruses correctly, which makes it suitable for diagnostic use. Moreover, in this thesis enterovirus outbreaks were studied with a well-observed method to create a strain-specific qRT-PCR from the typing region VP1 protein. In a hand-foot-and-mouth-disease (HFMD) outbreak in 2008, the causative agent was identified as CV-A6 and when the molecular evolution of the new HFMD CV-A6 strain was studied it was found that CV-A6 was the emerging agent for HFMD and onychomadesis. Furthermore, unusual E-30 meningitis epidemics that apeared during seasons 2009 and 2010 were studied with strain-specific qRT-PCR. The E-30 affected mostly adolescents and was probably spread in sports teams.