Finnish Maritime Personnel's Conceptions on Safety Management and Safety Culture

The purpose of this thesis is to explore Finnish maritime personnel’s conceptions of safety management and its relationship with the concept of safety culture. In addition, the aim is to evaluate the impact of the ISM Code on the prevailing safety culture in the Finnish shipping business. A total of 94 interviewees and seven Finnish shipping companies were involved in this study. Thematic interviews were applied as the main research method for the study. The results were analysed qualitatively. The results indicate that maritime safety culture can simultaneously demonstrate features of integration, differentiation and ambiguity. Basically, maritime personnel have a positive attitude towards safety management systems since they consider safety management beneficial and essential in general. However, the study also found considerable criticism among the interviewees. The interviewed maritime personnel did not criticise the ISM Code as such, yet they criticised the way the ISM Code has been applied in practise. In order to understand the multiple perspectives of safety culture more comprehensively, multiple theoretical perspectives and methodological approaches are needed. This study indicates that safety culture and the impacts of the ISM Code should not be unambiguously studied solely quantitative methods or qualitative methods. By examining safety culture from several methodological and theoretical perspectives, one may gain a more versatile and holistic overview of safety culture.

Creating and measuring customer value in digital businesses

Most economic transactions nowadays are due to the effective exchange of information in which digital resources play a huge role. New actors are coming into existence all the time, so organizations are facing difficulties in keeping their current customers and attracting new customer segments and markets. Companies are trying to find the key to their success and creating superior customer value seems to be one solution. Digital technologies can be used to deliver value to customers in ways that extend customers’ normal conscious experiences in the context of time and space. By creating customer value, companies can gain the increased loyalty of existing customers and better ways to serve new customers effectively. Based on these assumptions, the objective of this study was to design a framework to enable organizations to create customer value in digital business. The research was carried out as a literature review and an empirical study, which consisted of a web-based survey and semi-structured interviews. The data from the empirical study was analyzed as mixed research with qualitative and quantitative methods. These methods were used since the object of the study was to gain deeper understanding about an existing phenomena. Therefore, the study used statistical procedures and value creation is described as a phenomenon. The framework was designed first based on the literature and updated based on the findings from the empirical study. As a result, relationship, understanding the customer, focusing on the core product or service, the product or service quality, incremental innovations, service range, corporate identity, and networks were chosen as the top elements of customer value creation. Measures for these elements were identified. With the measures, companies can manage the elements in value creation when dealing with present and future customers and also manage the operations of the company. In conclusion, creating customer value requires understanding the customer and a lot of information sharing, which can be eased by digital resources. Understanding the customer helps to produce products and services that fulfill customers’ needs and desires. This could result in increased sales and make it easier to establish efficient processes.

Assessing the Role of Vocabulary Breadth and Depth in Reading Comprehension: A Quantitative Study of Finnish EFL Learners

In this MA thesis, Finnish learners of English were studied in order to examine the relationship between second language vocabulary size, vocabulary depth, and reading comprehension. In addition, given the well-established connection between vocabulary size and reading comprehension, the second aim of the study was to see whether assessing vocabulary depth could add another dimension in predicting and explaining reading comprehension proficiency. Two groups were studied: the first group consisted of 39 Finnish upper secondary school students (the TOKA group) whereas the second group consisted of 19 university students of English at the University of Turku (the YLI group). Thus, comparisons were made between the results of a less advanced and a very advanced group of English learners, which was the third aim of the study. The participants in both groups filled in a background information form and took three tests: a multiple-choice reading comprehension test, a multiple-choice vocabulary size test, and a test designed to elicit information on learners’ depth of vocabulary knowledge of certain English words. The data were analysed using statistical methods. The results of the study show that the scores on the three tests were positively correlated in both study groups as well as in the two groups together. However, the correlations were higher in the TOKA group and in the two groups in total than in the YLI group. When examining the variance in reading comprehension test scores explained by vocabulary size and vocabulary depth, the figures of explained variance were again higher in the TOKA group and in the two groups in total than in the YLI group. When it comes to the results of the YLI group, vocabulary depth did not indeed seem to add any explained variance into the explanation of reading comprehension test scores. Based on the results of the study, it seems that vocabulary size and depth have a less significant role in the reading comprehension skills of more advanced learners of English. When looking at the less advanced TOKA group, on the other hand, vocabulary size and depth seem to be clear indicators of reading proficiency. In addition, the test results of the YLI group were clearly more uniform than those of the TOKA group. The variance in the test results of the TOKA group was large.

Tissue Proteomes: Quantitative Mass Spectrometry of Murine Liver and Ovarian Endometrioma

A human genome contains more than 20 000 protein-encoding genes. A human proteome, instead, has been estimated to be much more complex and dynamic. The most powerful tool to study proteins today is mass spectrometry (MS). MS based proteomics is based on the measurement of the masses of charged peptide ions in a gas-phase. The peptide amino acid sequence can be deduced, and matching proteins can be found, using software to correlate MS-data with sequence database information. Quantitative proteomics allow the estimation of the absolute or relative abundance of a certain protein in a sample. The label-free quantification methods use the intrinsic MS-peptide signals in the calculation of the quantitative values enabling the comparison of peptide signals from numerous patient samples. In this work, a quantitative MS methodology was established to study aromatase overexpressing (AROM+) male mouse liver and ovarian endometriosis tissue samples. The workflow of label-free quantitative proteomics was optimized in terms of sensitivity and robustness, allowing the quantification of 1500 proteins with a low coefficient of variance in both sample types. Additionally, five statistical methods were evaluated for the use with label-free quantitative proteomics data. The proteome data was integrated with other omics datasets, such as mRNA microarray and metabolite data sets. As a result, an altered lipid metabolism in liver was discovered in male AROM+ mice. The results suggest a reduced beta oxidation of long chain phospholipids in the liver and increased levels of pro-inflammatory fatty acids in the circulation in these mice. Conversely, in the endometriosis tissues, a set of proteins highly specific for ovarian endometrioma were discovered, many of which were under the regulation of the growth factor TGF-β1. This finding supports subsequent biomarker verification in a larger number of endometriosis patient samples.

Comparison of five popular normalization methods using a spike-in proteomics data set

Mass spectrometry (MS)-based proteomics has seen significant technical advances during the past two decades and mass spectrometry has become a central tool in many biosciences. Despite the popularity of MS-based methods, the handling of the systematic non-biological variation in the data remains a common problem. This biasing variation can result from several sources ranging from sample handling to differences caused by the instrumentation. Normalization is the procedure which aims to account for this biasing variation and make samples comparable. Many normalization methods commonly used in proteomics have been adapted from the DNA-microarray world. Studies comparing normalization methods with proteomics data sets using some variability measures exist. However, a more thorough comparison looking at the quantitative and qualitative differences of the performance of the different normalization methods and at their ability in preserving the true differential expression signal of proteins, is lacking. In this thesis, several popular and widely used normalization methods (the Linear regression normalization, Local regression normalization, Variance stabilizing normalization, Quantile-normalization, Median central tendency normalization and also variants of some of the forementioned methods), representing different strategies in normalization are being compared and evaluated with a benchmark spike-in proteomics data set. The normalization methods are evaluated in several ways. The performance of the normalization methods is evaluated qualitatively and quantitatively on a global scale and in pairwise comparisons of sample groups. In addition, it is investigated, whether performing the normalization globally on the whole data or pairwise for the comparison pairs examined, affects the performance of the normalization method in normalizing the data and preserving the true differential expression signal. In this thesis, both major and minor differences in the performance of the different normalization methods were found. Also, the way in which the normalization was performed (global normalization of the whole data or pairwise normalization of the comparison pair) affected the performance of some of the methods in pairwise comparisons. Differences among variants of the same methods were also observed.