58 resultados para analytical approaches


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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Paper-based analytical technologies enable quantitative and rapid analysis of analytes from various application areas including healthcare, environmental monitoring and food safety. Because paper is a planar, flexible and light weight substrate, the devices can be transported and disposed easily. Diagnostic devices are especially valuable in resourcelimited environments where diagnosis as well as monitoring of therapy can be made even without electricity by using e.g. colorimetric assays. On the other hand, platforms including printed electrodes can be coupled with hand-held readers. They enable electrochemical detection with improved reliability, sensitivity and selectivity compared with colorimetric assays. In this thesis, different roll-to-roll compatible printing technologies were utilized for the fabrication of low-cost paper-based sensor platforms. The platforms intended for colorimetric assays and microfluidics were fabricated by patterning the paper substrates with hydrophobic vinyl substituted polydimethylsiloxane (PDMS) -based ink. Depending on the barrier properties of the substrate, the ink either penetrates into the paper structure creating e.g. microfluidic channel structures or remains on the surface creating a 2D analog of a microplate. The printed PDMS can be cured by a roll-ro-roll compatible infrared (IR) sintering method. The performance of these platforms was studied by printing glucose oxidase-based ink on the PDMS-free reaction areas. The subsequent application of the glucose analyte changed the colour of the white reaction area to purple with the colour density and intensity depending on the concentration of the glucose solution. Printed electrochemical cell platforms were fabricated on paper substrates with appropriate barrier properties by inkjet-printing metal nanoparticle based inks and by IR sintering them into conducting electrodes. Printed PDMS arrays were used for directing the liquid analyte onto the predetermined spots on the electrodes. Various electrochemical measurements were carried out both with the bare electrodes and electrodes functionalized with e.g. self assembled monolayers. Electrochemical glucose sensor was selected as a proof-of-concept device to demonstrate the potential of the printed electronic platforms.

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Cardiac troponin (cTn) I and T are the recommended biomarkers for the diagnosis and risk stratification of patients with suspected acute coronary syndrome (ACS), a major cause of cardiovascular death and disability worldwide. It has recently been demonstrated that cTn-specific autoantibodies (cTnAAb) can negatively interfere with cTnI detection by immunoassays to the extent that cTnAAb-positive patients may be falsely designated as cTnI-negative. The aim of this thesis was to develop and optimize immunoassays for the detection of both cTnI and cTnAAb, which would eventually enable exploring the clinical impact of these autoantibodies on cTnI testing and subsequent patient management. The extent of cTnAAb interference in different cTnI assay configurations and the molecular characteristics of cTnAAbs were investigated in publications I and II, respectively. The findings showed that cTnI midfragment targeting immunoassays used predominantly in clinical practice are affected by cTnAAb interference which can be circumvented by using a novel 3+1-type assay design with three capture antibodies against the N-terminus, midfragment and C-terminus and one tracer antibody against the C-terminus. The use of this assay configuration was further supported by the epitope specificity study, which showed that although the midfragment is most commonly targeted by cTnAAbs, the interference basically encompasses the whole molecule, and there may be remarkable individual variation at the affected sites. In publications III and IV, all the data obtained in previous studies were utilized to develop an improved version of an existing cTnAAb assay and a sensitive cTnI assay free of this specific analytical interference. The results of the thesis showed that approximately one in 10 patients with suspected ACS have detectable amounts of cTnAAbs in their circulation and that cTnAAbs can inhibit cTnI determination when targeted against the binding sites of assay antibodies used in its immunological detection. In the light of these observations, the risk of clinical misclassification caused by the presence of cTnAAbs remains a valid and reasonable concern. Because the titers, affinities and epitope specificities of cTnAAbs and the concentration of endogenous cTnI determine the final effect of circulating cTnAAbs, appropriately sized studies on their clinical significance are warranted. The new cTnI and cTnAAb assays could serve as analytical tools for establishing the impact of cTnAAbs on cTnI testing and also for unraveling the etiology of cTn-related autoimmune responses.

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Preparative liquid chromatography is one of the most selective separation techniques in the fine chemical, pharmaceutical, and food industries. Several process concepts have been developed and applied for improving the performance of classical batch chromatography. The most powerful approaches include various single-column recycling schemes, counter-current and cross-current multi-column setups, and hybrid processes where chromatography is coupled with other unit operations such as crystallization, chemical reactor, and/or solvent removal unit. To fully utilize the potential of stand-alone and integrated chromatographic processes, efficient methods for selecting the best process alternative as well as optimal operating conditions are needed. In this thesis, a unified method is developed for analysis and design of the following singlecolumn fixed bed processes and corresponding cross-current schemes: (1) batch chromatography, (2) batch chromatography with an integrated solvent removal unit, (3) mixed-recycle steady state recycling chromatography (SSR), and (4) mixed-recycle steady state recycling chromatography with solvent removal from fresh feed, recycle fraction, or column feed (SSR–SR). The method is based on the equilibrium theory of chromatography with an assumption of negligible mass transfer resistance and axial dispersion. The design criteria are given in general, dimensionless form that is formally analogous to that applied widely in the so called triangle theory of counter-current multi-column chromatography. Analytical design equations are derived for binary systems that follow competitive Langmuir adsorption isotherm model. For this purpose, the existing analytic solution of the ideal model of chromatography for binary Langmuir mixtures is completed by deriving missing explicit equations for the height and location of the pure first component shock in the case of a small feed pulse. It is thus shown that the entire chromatographic cycle at the column outlet can be expressed in closed-form. The developed design method allows predicting the feasible range of operating parameters that lead to desired product purities. It can be applied for the calculation of first estimates of optimal operating conditions, the analysis of process robustness, and the early-stage evaluation of different process alternatives. The design method is utilized to analyse the possibility to enhance the performance of conventional SSR chromatography by integrating it with a solvent removal unit. It is shown that the amount of fresh feed processed during a chromatographic cycle and thus the productivity of SSR process can be improved by removing solvent. The maximum solvent removal capacity depends on the location of the solvent removal unit and the physical solvent removal constraints, such as solubility, viscosity, and/or osmotic pressure limits. Usually, the most flexible option is to remove solvent from the column feed. Applicability of the equilibrium design for real, non-ideal separation problems is evaluated by means of numerical simulations. Due to assumption of infinite column efficiency, the developed design method is most applicable for high performance systems where thermodynamic effects are predominant, while significant deviations are observed under highly non-ideal conditions. The findings based on the equilibrium theory are applied to develop a shortcut approach for the design of chromatographic separation processes under strongly non-ideal conditions with significant dispersive effects. The method is based on a simple procedure applied to a single conventional chromatogram. Applicability of the approach for the design of batch and counter-current simulated moving bed processes is evaluated with case studies. It is shown that the shortcut approach works the better the higher the column efficiency and the lower the purity constraints are.

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Cardiac troponins (cTn) I and T are the current golden standard biochemical markers in the diagnosis and risk stratification of patients with suspected acute coronary syndrome. During the past few years, novel assays capable of detecting cTn‐concentrations in >50% of apparently healthy individuals have become readily available. With the emerging of these high sensitivity cTn assays, reductions in the assay specificity have caused elevations in the measured cTn levels that do not correlate with the clinical picture of the patient. The increased assay sensitivity may reveal that various analytical interference mechanisms exist. This doctoral thesis focused on developing nanoparticle‐assisted immunometric assays that could possibly be applied to an automated point‐of‐care system. The main objective was to develop minimally interference‐prone assays for cTnI by employing recombinant antibody fragments. Fast 5‐ and 15‐minute assays for cTnI and D‐dimer, a degradation product of fibrin, based on intrinsically fluorescent nanoparticles were introduced, thus highlighting the versatility of nanoparticles as universally applicable labels. The utilization of antibody fragments in different versions of the developed cTnI‐assay enabled decreases in the used antibody amounts without sacrificing assay sensitivity. In addition, the utilization of recombinant antibody fragments was shown to significantly decrease the measured cTnI concentrations in an apparently healthy population, as well as in samples containing known amounts of potentially interfering factors: triglycerides, bilirubin, rheumatoid factors, or human anti‐mouse antibodies. When determining the specificity of four commercially available antibodies for cTnI, two out of the four cross‐reacted with skeletal troponin I, but caused crossreactivity issues in patient samples only when paired together. In conclusion, the results of this thesis emphasize the importance of careful antibody selection when developing cTnI assays. The results with different recombinant antibody fragments suggest that the utilization of antibody fragments should strongly be encouraged in the immunoassay field, especially with analytes such as cTnI that require highly sensitive assay approaches.

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This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

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The aim of this study was to examine community and individual approaches in responses to mass violence after the school shooting incidents in Jokela (November 2007) and Kauhajoki (September 2008), Finland. In considering the community approach, responses to any shocking criminal event may have integrative, as well as disintegrative effects, within the neighborhood. The integration perspective argues that a heinous criminal event within one’s community is a matter of offence to collectively held feelings and beliefs, and increases perceived solidarity; whereas the disintegration perspective suggests that a criminal event weakens the social fabric of community life by increasing fear of crime and mistrust among locals. In considering the individual approach, socio-demographic factors, such as one’s gender, are typically significant indicators, which explain variation in fear of crime. Beyond this, people are not equally exposed to violent crime and therefore prior victimization and event related experiences may further explain why people differ in their sensitivity to risk from mass violence. Finally, factors related to subjective mental health, such as depressed mood, are also likely to moderate individual differences in responses to mass violence. This study is based on the correlational design of four independent cross-sectional postal surveys. The sampling frames (N=700) for the surveys were the Finnish speaking adult population aged 18–74-years. The first mail survey in Jokela (n=330) was conducted between May and June 2008, approximately six months from the shooting incident at the local high-school. The second Jokela survey (n=278) was conducted in May–June of 2009, 18 months removed from the incident. The first survey in Kauhajoki (n=319) was collected six months after the incident at the local University of Applied Sciences, March– April 2009, and the second (n=339) in March–April 2010, approximately 18 months after the event. Linear and ordinal regression and path analysis are used as methods of analyses. The school shootings in Jokela and Kauhajoki were extremely disturbing events, which deeply affected the communities involved. However, based on the results collected, community responses to mass violence between the two localities were different. An increase in social solidarity appears to apply in the case of the Jokela community, but not in the case of the Kauhajoki community. Thus a criminal event does not necessarily impact the wider community. Every empirical finding is most likely related to different contextual and event-specific factors. Beyond this, community responses to mass violence in Jokela also indicated that the incident was related to a more general sense of insecurity and was also associating with perceived community deterioration and further suggests that responses to mass violence may have both integrating and disintegrating effects. Moreover, community responses to mass violence should also be examined in relation to broader social anxieties and as a proxy for generalized insecurity. Community response is an emotive process and incident related feelings are perhaps projected onto other identifiable concerns. However, this may open the door for social errors and, despite integrative effects, this may also have negative consequences within the neighborhood. The individual approach suggests that women are more fearful than men when a threat refers to violent crime. Young women (aged 18–34) were the most worried age and gender group as concerns perception of threat from mass violence at schools compared to young men (aged 18–34), who were also the least worried age and gender group when compared to older men. It was also found that concerns about mass violence were stronger among respondents with the lowest level of monthly household income compared to financially better-off respondents. Perhaps more importantly, responses to mass violence were affected by the emotional proximity to the event; and worry about the recurrence of school shootings was stronger among respondents who either were a parent of a school-aged child, or knew a victim. Finally, results indicate that psychological wellbeing is an important individual level factor. Respondents who expressed depressed mood consistently expressed their concerns about mass violence and community deterioration. Systematic assessments of the impact of school shooting events on communities are therefore needed. This requires the consolidation of community and individual approaches. Comparative study designs would further benefit from international collaboration across disciplines. Extreme school violence has also become a national concern and deeper understanding of crime related anxieties in contemporary Finland also requires community-based surveys.

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Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

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There are more than 7000 languages in the world, and many of these have emerged through linguistic divergence. While questions related to the drivers of linguistic diversity have been studied before, including studies with quantitative methods, there is no consensus as to which factors drive linguistic divergence, and how. In the thesis, I have studied linguistic divergence with a multidisciplinary approach, applying the framework and quantitative methods of evolutionary biology to language data. With quantitative methods, large datasets may be analyzed objectively, while approaches from evolutionary biology make it possible to revisit old questions (related to, for example, the shape of the phylogeny) with new methods, and adopt novel perspectives to pose novel questions. My chief focus was on the effects exerted on the speakers of a language by environmental and cultural factors. My approach was thus an ecological one, in the sense that I was interested in how the local environment affects humans and whether this human-environment connection plays a possible role in the divergence process. I studied this question in relation to the Uralic language family and to the dialects of Finnish, thus covering two different levels of divergence. However, as the Uralic languages have not previously been studied using quantitative phylogenetic methods, nor have population genetic methods been previously applied to any dialect data, I first evaluated the applicability of these biological methods to language data. I found the biological methodology to be applicable to language data, as my results were rather similar to traditional views as to both the shape of the Uralic phylogeny and the division of Finnish dialects. I also found environmental conditions, or changes in them, to be plausible inducers of linguistic divergence: whether in the first steps in the divergence process, i.e. dialect divergence, or on a large scale with the entire language family. My findings concerning Finnish dialects led me to conclude that the functional connection between linguistic divergence and environmental conditions may arise through human cultural adaptation to varying environmental conditions. This is also one possible explanation on the scale of the Uralic language family as a whole. The results of the thesis bring insights on several different issues in both a local and a global context. First, they shed light on the emergence of the Finnish dialects. If the approach used in the thesis is applied to the dialects of other languages, broader generalizations may be drawn as to the inducers of linguistic divergence. This again brings us closer to understanding the global patterns of linguistic diversity. Secondly, the quantitative phylogeny of the Uralic languages, with estimated times of language divergences, yields another hypothesis as to the shape and age of the language family tree. In addition, the Uralic languages can now be added to the growing list of language families studied with quantitative methods. This will allow broader inferences as to global patterns of language evolution, and more language families can be included in constructing the tree of the world’s languages. Studying history through language, however, is only one way to illuminate the human past. Therefore, thirdly, the findings of the thesis, when combined with studies of other language families, and those for example in genetics and archaeology, bring us again closer to an understanding of human history.

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Today industries and commerce in Ghana are facing enormous energy challenge. The pressure is on for industries to reduce energy consumption, lower carbon emissions and provide se-cured power supply. Industrial electric motor energy efficiency improvement is one of the most important tools to reduce global warming threat and reduce electricity bills. In order to develop a strategic industrial energy efficiency policy, it is therefore necessary to study the barriers that inhibit the implementation of cost – effective energy efficiency measures and the driving forces that promote the implementation. The aim of this thesis is to analyse the energy consumption pattern of electric motors, study factors that promote or inhibit energy efficiency improvements in EMDS and provide cost – effective solutions that improve energy efficiency to bridge the existing energy efficiency gap in the surveyed industries. The results from this thesis has revealed that, the existence of low energy efficiency in motor-driven systems in the surveyed industries were due to poor maintenance practices, absence of standards, power quality issues, lack of access to capital and limited awareness to the im-portance of energy efficiency improvements in EMDS. However, based on the results pre-sented in this thesis, a policy approach towards industrial SMEs should primarily include dis-counted or free energy audit in providing the industries with the necessary information on potential energy efficiency measures, practice best motor management programmes and estab-lish a minimum energy performance standard (MEPS) for motors imported into the country. The thesis has also shown that education and capacity development programmes, financial incentives and system optimization are effective means to promote energy efficiency in elec-tric motor – driven systems in industrial SMEs in Ghana