Calibration of a desktop scanner and digital image analysis procedure for quantification of a root morphology

Selostus: Tasoskannerin ja digitaalisen kuva-analyysimenetelmän kalibrointi juurten morfologian kvantifioimiseksi

Quantification of fine root responses to selenium toxicity

Selostus: Seleenin myrkytysoireet juurissa

Quantification of Proteins and Cells: Luminometric Nonspecific Particle-Based Methods

New luminometric particle-based methods were developed to quantify protein and to count cells. The developed methods rely on the interaction of the sample with nano- or microparticles and different principles of detection. In fluorescence quenching, timeresolved luminescence resonance energy transfer (TR-LRET), and two-photon excitation fluorescence (TPX) methods, the sample prevents the adsorption of labeled protein to the particles. Depending on the system, the addition of the analyte increases or decreases the luminescence. In the dissociation method, the adsorbed protein protects the Eu(III) chelate on the surface of the particles from dissociation at a low pH. The experimental setups are user-friendly and rapid and do not require hazardous test compounds and elevated temperatures. The sensitivity of the quantification of protein (from 40 to 500 pg bovine serum albumin in a sample) was 20-500-fold better than in most sensitive commercial methods. The quenching method exhibited low protein-to-protein variability and the dissociation method insensitivity to the assay contaminants commonly found in biological samples. Less than ten eukaryotic cells were detected and quantified with all the developed methods under optimized assay conditions. Furthermore, two applications, the method for detection of the aggregation of protein and the cell viability test, were developed by utilizing the TR-LRET method. The detection of the aggregation of protein was allowed at a more than 10,000 times lower concentration, 30 μg/L, compared to the known methods of UV240 absorbance and dynamic light scattering. The TR-LRET method was combined with a nucleic acid assay with cell-impermeable dye to measure the percentage of dead cells in a single tube test with cell counts below 1000 cells/tube.

Quantification and Clinical Relevance of Cystatin C

An aging population and increasing rates of diabetes mellitus contribute to a high prevalence of kidney dysfunction – approximately 10 percent of adults in developed countries have chronic kidney disease (CKD). CKD is a progressive loss of kidney function and this remains permanent. Early recognition of this condition is important for prevention or impeding severe adverse cardiac and renal outcomes. Cystatin C is a low molecular weight cysteine protease inhibitor that has emerged as a biomarker of kidney function. The special potential of plasma cystatin C in this setting is related to its independency of muscle mass, which is a remarkable limitation of the traditional marker creatinine. Cystatin C is a sensitive marker in diagnosing mild and moderate CKD, especially in small children, in the elderly and in conditions where muscle mass is affected. Cystatin C is quantified with immunoassays, mainly based on particle-enhanced nephelometry (PENIA) or turbidimetry (PETIA). The aim of this study was to develop a rapid and reliable assay for quantification of human cystatin C in plasma or serum by utilizing time-resolved fluorescence-based immunoassay methods. This was accomplished by utilizing different antibodies, including polyclonal and 7 monoclonal antibodies against cystatin C. Different assay designs were tested and the best assay was further modified to a dry-reagent double monoclonal assay run on an automated immunonalyzer. This assay was evaluated for clinical performance in estimating reduced kidney function and in predicting risk of adverse outcomes in patients with non-ST elevation acute coronary syndrome. Of the tested assay designs, heterogeneous non-competitive assay had the best performace and was chosen to be developed further. As an automated double monoclonal assay, this assay enabled a reliable measurement of clinically relevant cystatin C concentrations. It also showed a stronger concordance with the reference clearance method than the conventional PETIA method in patients with reduced kidney function. Risk of all-cause mortality and combined events, defined by death and myocardial infarction, increased with higher cystatin C and cystatin C remained an independent predictor of death and combined events after adjustment to nonbiochemical baseline factors. In conclusion, the developed dry-reagent double monoclonal assay allows rapid and reliable quantitative measurement of cystatin C. As measured with the developed assay, cystatin C is a potential predictor of adverse outcomes in cardiac patients.

Mitigating uncertainty in logistics outsourcing with ERP systems

Outsourcing is a common strategy for companies looking for cost savings and improvements in performance. This has been especially prevalent in logistics, where warehousing and transporting are typical targets for outsourcing. However, while the benefits from logistics outsourcing are clear on paper, there are several cases companies fail to reach these benefits. The most commonly cited reasons for this are poor information flow between the company and the third party logistics partner, and a lack of integration between the two partners. Uncertainty stems from lack of information, and it can cripple the whole outsourcing operation. This is where enterprise resource planning (ERP) systems step in, as they can have a significant role in improving the flow of information, and integration, which consequently mitigates uncertainty. The purpose of the study is to examine if ERP systems have an effect on a company's decision to outsource logistics operations. Along the rapid advancements in technology during the past decades, ERP systems have also evolved. Therefore, empirical research on the subject needs constant revision as it can quickly become outdated due to ERP systems having more advanced capabilities every year. The research was conducted using a qualitative single-case study of a Finnish manufacturing firm that had outsourced warehousing and transportation operations in the Swedish market. The empirical data was gathered with use of semi-structured interviews with three employees from the case company that were closely related to the outsourcing operation. The theoretical framework that was used to analyze the empirical data was based on Transaction Cost Economics theory. The results of the study were align with the theoretical framework, in that the ERP system of the case company was seen as an enabler for their logistics outsourcing operation. However, the full theoretical benefits from ERP systems concerning extended enterprise functionality and flexibility were not attained due to the case company having an older version of their ERP system. This emphasizes the importance of having up-to-date technology if you want to overcome the shortcomings of ERP systems in outsourcing situations.

Uncertainty of Efficiency Measurements in Electric Drives

The two central goals of this master's thesis are to serve as a guidebook on the determination of uncertainty in efficiency measurements and to investigate sources of uncertainty in efficiency measurements in the field of electric drives by a literature review, mathematical modeling and experimental means. The influence of individual sources of uncertainty on the total instrumental uncertainty is investigated with the help of mathematical models derived for a balance and a direct air cooled calorimeter. The losses of a frequency converter and an induction motor are measured with the input-output method and a balance calorimeter at 50 and 100 % loads. A software linking features of Matlab and Excel is created to process measurement data, calculate uncertainties and to calculate and visualize results. The uncertainties are combined with both the worst case and the realistic perturbation method and distributions of uncertainty by source are shown based on experimental results. A comparison of the calculated uncertainties suggests that the balance calorimeter determines losses more accurately than the input-output method with a relative RPM uncertainty of 1.46 % compared to 3.78 - 12.74 % respectively with 95 % level of confidence at the 93 % induction motor efficiency or higher. As some principles in uncertainty analysis are open to interpretation the views and decisions of the analyst can have noticeable influence on the uncertainty in the measurement result.

Quantification of Toxin Biosynthesis Genes In Cyanobacteria and Dinoflagellates - Genetic Factors as Predictors of Toxin Production in the Environment

Harmful algal blooms (HABs) are events caused by the massive proliferation of microscopic, often photosynthetic organisms that inhabit both fresh and marine waters. Although HABs are essentially a natural phenomenon, they now cause worldwide concern. Recent anthropogenic effects, such as climate change and eutrophication via nutrient runoff, can be seen in their increased prevalence and severity. Cyanobacteria and dinoflagellates are often the causative organisms of HABs. In addition to adverse effects caused by the sheer biomass, certain species produce highly potent toxic compounds: hepatotoxic microcystins are produced exclusively by cyanobacteria and neurotoxic saxitoxins, also known as paralytic shellfish toxins (PSTs), by both cyanobacteria and dinoflagellates. Specific biosynthetic genes in the cyanobacterial genomes direct the production of microcystin and paralytic shellfish toxins. Recently also the first paralytic shellfish toxin gene sequences from dinoflagellate genomes have been elucidated. The public health risks presented by HABs are evident, but the monitoring and prediction of toxic events is challenging. Characterization of the genetic background of toxin biosynthesis, including that of microcystins and paralytic shellfish toxins, has made it possible to develop highly sensitive molecular tools which have shown promise in the monitoring and study of potentially toxic microalgae. In this doctoral work, toxin-specific genes were targeted in the developed PCR and qPCR assays for the detection and quantification of potentially toxic cyanobacteria and dinoflagellates in the environment. The correlation between the copy numbers of the toxin biosynthesis genes and toxin production were investigated to assess whether the developed methods could be used to predict toxin concentrations. The nature of the correlation between gene copy numbers and amount of toxin produced varied depending on the targeted gene and the producing organism. The combined mcyB copy numbers of three potentially microcystin-producing cyanobacterial genera showed significant positive correlation to the observed total toxin production. However, the presence of PST-specific sxtA, sxtG, and sxtB genes of cyanobacterial origin was found to be a poor predictor of toxin production in the studied area. Conversely, the dinoflagellate sxtA4 was a good qualitative indicator of a neurotoxic bloom both in the laboratory and in the field, and population densities reflected well the observed toxin concentrations. In conclusion, although the specificity of each potential targeted toxin biosynthesis gene must be assessed individually during method development, the results obtained in this doctoral study support the use of quantitative PCR -based approaches in the monitoring of toxic cyanobacteria and dinoflagellates.

Offshoring and outsourcing under demand uncertainty -a supply chain management analysis

Outsourcing and offshoring or any combinations of these have not just become a popular phenomenon, but are viewed as one of the most important management strategies due to the new possibilities from globalization. They have been seen as a possibility to save costs and improve customer service. Executing offshoring and offshore outsourcing successfully can be more complex than initially expected. Potential cost savings resulting from of offshoring and offshore outsourcing are often based on lower manufacturing costs. However, these benefits might be conflicted by a more complex supply chain with service level challenges that can respectively increase costs. Therefore analyzing the total cost effects of offshoring and outsourcing is necessary. The aim of this Master´s Thesis was to to construct a total cost model using academic literature to calculate the total costs and analyze the reasonability of offshoring and offshore outsourcing production of a case company compared to insourcing production. The research data was mainly quantitative and collected mainly from the case company past sales and production records. In addition management level interviews from the case company were conducted. The information from these interviews was used for the qualification of the necessary quantitative data and adding supportive information that could not be gathered from the quantitative data. Both data collection and analysis were guided by a theoretical frame of reference that was based on academic literature concerning offshoring and outsourcing, statistical calculation of demand and total costs. The results confirm the theories that offshoring and offshore outsourcing would reduce total costs as both offshoring and offshore outsourcing options result in lower total annual costs than insourcing mainly due to lower manufacturing costs. However, increased demand uncertainty would make the alternative of offshore outsourcing more risky and difficult to manage. Therefore when assessing the overall impact of the alternatives, offshoring is the most preferable option. As the main cost savings in offshore outsourcing came from lower manufacturing costs, more specifically labour costs, the logistics costs in this case company did not have an essential effect in total costs. The management should therefore pay attention initially to manufacturing costs and then logistics costs when choosing the best production sourcing option for the company.

Opportunity meets uncertainty. Towards sustainable business in the Arctic region

The Arctic region is experiencing a significant change in terms of climate change and a growing economic interest towards its natural resources and emerging business opportunities. The purpose of this study is to explore how can Finnish companies create sustainable business in the Arctic. This is done by examining the arctic business environment, identifying sectors with growth potential, addressing challenges related to operating in the Arctic and suggesting how to ensure sustainability and succeed in the globally competed arctic market. The theoretical framework is based on theories of sustainable development, corporate social responsibility and the role of strategy in creating sustainable business. Empirical data was collected by using qualitative research methods: first, background knowledge was formed based on written documents and, secondly, six expert interviews were conducted in early 2014. The interviewees represented the viewpoints of companies, political decision makers and NGO’s. The analysis of the data was conducted using thematic categorization. The empirical findings of the study suggest that in order to create sustainable business in the Arctic companies should adopt a long-term perspective, embrace a holistic approach to sustainability, understand interdependencies between the dimensions of sustainability and aim at high-level engagement in responsible behavior. To succeed in the arctic market core competencies, customer needs, multivendor cooperation and long-term presence need to be invested in on a company level. In addition, to promote and advance arctic development on a national level support is needed in terms of investments in infrastructure, funding research and design, creating a regulative framework and removing barriers of trade.