44 resultados para Artificial Selection


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The main objective of the study was to identify and evaluate criteria for international partner selection in university-university context. This study attempted at promoting better understanding of how universities should proceed in selecting partners for producing joint research publications. Thus, the aim of the study was to gain an understanding of how research collaborations can be developed and how partners can be selected. The choice of a right partner has been identified as a precondition for partnership success. In international research collaborations partnering scientists with different skills and backgrounds bring together complementary knowledge into research projects, which in most cases results in a higher quality output. Therefore, prior to selecting a partner, the set of criteria should be established. This research examined twelve Russian universities with the status of national research university as potential partners for Lappeenranta University of Technology, and selected the most appropriate universities based on established set of criteria. Potential partners’ evaluation was done using secondary sources by tracking partners’ academic success during the period 2005 – 2010. Based on established criteria, the study calculated the partnership index for each university. The results of the research reveal that among twelve examined universities there are four potential partners who have been rather active in publishing scientific articles during 2005 – 2010.

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In this study, feature selection in classification based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classifier. As the similarity classifier we used Yu's similarity, we tested our similarity on the real world data set which is dermatological data set. By performing feature selection based on fuzzy entropy measures before classification on our data set the empirical results were very promising, the highest classification accuracy of 98.83% was achieved when testing our similarity measure to the data set. The achieved results were then compared with some other results previously obtained using different similarity classifiers, the obtained results show better accuracy than the one achieved before. The used methods helped to reduce the dimensionality of the used data set, to speed up the computation time of a learning algorithm and therefore have simplified the classification task

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In development of human medicines, it is important to predict early and accurately enough the disease and patient population to be treated as well as the effective and safe dose range of the studied medicine. This is pursued by using preclinical research models, clinical pharmacology and early clinical studies with small sample sizes. When successful, this enables effective development of medicines and reduces unnecessary exposure of healthy subjects and patients to ineffectice or harmfull doses of experimental compounds. Toremifene is a selective estrogen receptor modulator (SERM) used for treatment of breast cancer. Its development was initiated in 1980s when selection of treatment indications and doses were based on research in cell and animal models and on noncomparative clinical studies including small number of patients. Since the early development phase, the treatment indication, the patient population and the dose range were confirmed in large comparative clinical studies in patients. Based on the currently available large and long term clinical study data the aim of this study was to investigate how the early phase studies were able to predict the treatment indication, patient population and the dose range of the SERM. As a conclusion and based on the estrogen receptor mediated mechanism of action early studies were able to predict the treatment indication, target patient population and a dose range to be studied in confirmatory clinical studies. However, comparative clinical studies are needed to optimize dose selection of the SERM in treatment of breast cancer.

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Acquisitions are a way for a company to grow, enter new geographical areas, buy out competition or diversify. Acquisitions have recently grown in both size and value. Despite of this, only approximately 25 percent of acquisitions reach their targets and goals. Companies making serial acquisitions seem to be exceptionally successful and succeed in the majority of their acquisitions. The main research question this study aims to answer is: “What issues impact the selection of acquired companies from the point of view of a serial acquirer? The main research question is answered through three sub questions: “What is a buying process for a serial acquirer like?”, “What are the motives for a serial acquirer to buy companies?” and “What is the connection between company strategy and serial acquisitions?”. The case company KONE is a globally operating company which mainly produces and maintains elevators and escalators. Its headquarter is located in Helsinki, Finland. The company has a long history of making acquisitions and does 20- 30 acquisitions a year. By a key person interview, the acquisition process of the case company is compared with the literature about successful serial acquirers. The acquisition motives in this case are reflected upon three of the acquisition motive theories by Trautwein: efficiency theory, monopoly theory and valuation theory. The linkage between serial acquisitions and company strategy is studied through the key person interview. The main research findings are that the acquisition process of KONE is compatible with a successful acquisition process recognized in literature (RAID). This study confirms the efficiency theory as an acquisition motive and more closely the operational synergies. The monopoly theory can only vaguely be supported by this study, but cannot be totally rejected because of the structure of the industry. The valuation theory does not get any support in this study and can therefore be rejected. The linkage between company strategy and serial acquisitions is obvious and making acquisitions can be seen as growth strategy and a part of other company strategies.

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Ceramides comprise a class of sphingolipids that exist only in small amounts in cellular membranes, but which have been associated with important roles in cellular signaling processes. The influences that ceramides have on the physical properties of bilayer membranes reach from altered thermodynamical behavior to significant impacts on the molecular order and lateral distribution of membrane lipids. Along with the idea that the membrane physical state could influence the physiological state of a cell, the membrane properties of ceramides have gained increasing interest. Therefore, membrane phenomena related to ceramides have become a subject of intense study both in cellular as well as in artificial membranes. Artificial bilayers, the so called model membranes, are substantially simpler in terms of contents and spatio-temporal variation than actual cellular membranes, and can be used to give detailed information about the properties of individual lipid species in different environments. This thesis focuses on investigating how the different parts of the ceramide molecule, i.e., the N-linked acyl chain, the long-chain sphingoid base and the membrane-water interface region, govern the interactions and lateral distribution of these lipids in bilayer membranes. With the emphasis on ceramide/sphingomyelin(SM)-interactions, the relevance of the size of the SMhead group for the interaction was also studied. Ceramides with methylbranched N-linked acyl chains, varying length sphingoid bases, or methylated 2N (amide-nitrogen) and 3O (C3-hydroxyl) at the interface region, as well as SMs with decreased head group size, were synthesized and their bilayer properties studied by calorimetric and fluorescence spectroscopic techniques. In brief, the results showed that the packing of the ceramide acyl chains was more sensitive to methyl-branching in the mid part than in the distal end of the N-linked chain, and that disrupting the interfacial structure at the amide-nitrogen, as opposed to the C3-hydroxyl, had greater effect on the interlipid interactions of ceramides. Interestingly, it appeared that the bilayer properties of ceramides could be more sensitive to small alterations in the length of the long-chain base than what was previously reported for the N-linked acyl chain. Furthermore, the data indicated that the SM-head group does not strongly influence the interactions between SMs and ceramides. The results in this thesis illustrate the pivotal role of some essential parts of the ceramide molecules in determining their bilayer properties. The thesis provides increased understanding of the molecular aspects of ceramides that possibly affect their functions in biological membranes, and could relate to distinct effects on cell physiology.

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In today's logistics environment, there is a tremendous need for accurate cost information and cost allocation. Companies searching for the proper solution often come across with activity-based costing (ABC) or one of its variations which utilizes cost drivers to allocate the costs of activities to cost objects. In order to allocate the costs accurately and reliably, the selection of appropriate cost drivers is essential in order to get the benefits of the costing system. The purpose of this study is to validate the transportation cost drivers of a Finnish wholesaler company and ultimately select the best possible driver alternatives for the company. The use of cost driver combinations as an alternative is also studied. The study is conducted as a part of case company's applied ABC-project using the statistical research as the main research method supported by a theoretical, literature based method. The main research tools featured in the study include simple and multiple regression analyses, which together with the literature and observations based practicality analysis forms the basis for the advanced methods. The results suggest that the most appropriate cost driver alternatives are the delivery drops and internal delivery weight. The possibility of using cost driver combinations is not suggested as their use doesn't provide substantially better results while increasing the measurement costs, complexity and load of use at the same time. The use of internal freight cost drivers is also questionable as the results indicate weakening trend in the cost allocation capabilities towards the end of the period. Therefore more research towards internal freight cost drivers should be conducted before taking them in use.

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Predation is an important selective force that has led to the evolution of a variety of fascinating anti-predator adaptations, such as many types of protective coloration and prey behaviours. Because the evolution of life has begun in the aquatic environment and many anti-predator adaptations are found already in relative primitive taxa, it is likely that many of these adaptations evolved initially in the aquatic environment. Yet, there has been surprisingly little research on the mechanisms and function of antipredator adaptations in aquatic systems. To understand the function of anti-predator adaptations and natural selection imposed on prey appearance and behaviour, I have investigated how protective coloration can be used, either as such or together with behavioural adaptations, to manipulate predator behaviour and decrease predation risk. To this end I conducted a series of behaviour ecological laboratory experiments in which I manipulated the visual appearance of artificial backgrounds and prey items. In paper I of this thesis, I investigated background choice as an anti-predator strategy, by observing the habitat choice of the least killifish (Heterandria formosa) between pairs of artificial backgrounds, both in the presence and absence of predation threat. It has been suggested that prey could decrease their risk of being detected by predators either by preferring backgrounds into which they blend or by preferring visually complex backgrounds. The least killifish preferred a background that matched their patterning to a background that mismatched it, showing that they are able to respond to cues of visual similarity between their colour pattern and the surrounding environment. Interestingly however, in female least killifish visual complexity of the background was a more important cue for habitat safety and may override or act together with background matching when searching for a safe habitat. It is possible that in females, preference for visually complex backgrounds is associated with lower opportunity costs than preference for matching backgrounds would be. Generally, the least killifish showed stronger preference while under predation threat, indicating that their background choice behaviour is an antipredator adaptation. Many aquatic prey species have eyespots, which are colour patterns that consist of roughly concentric rings and have received their name because they for humans often resemble the vertebrate eye. I investigated the anti-predator function of eyespots against predation by fish in papers II, III and IV. Some eyespots have been suggested to benefit prey by diverting the strikes of predators away from vital parts of the prey body or towards a direction that facilitates prey escape. Although proposed over a century ago, the divertive effect of eyespots has proven to be difficult to show experimentally. In papers II and III, I tested for divertive effect of eyespots towards attacking fish by presenting artificial prey with eyespots to laboratory reared three-spined sticklebacks (Gasterosteus aculeatus). I found that eyespots strongly influenced the behaviour of attacking sticklebacks and effectively drew their strikes towards the eyespots. To further investigate this divertive effect and whether the specific shape of eyespots is important for it, I tested in paper III the response of fish also to other markings than eyespots. I found that eyespots were generally more effective in diverting the first strikes of attacking fish compared to other prey markings. My findings suggest that the common occurrence of eyespots in aquatic prey species can at least partly be explained by the divertive effect of the eyespot shape, possibly together with the relative simple developmental mechanisms underlying circular colour patterns. An eyebar is a stripe that runs through the eye, and this pattern has been suggested to obscure the real eyes of the prey by visually blending parts of the eyes and head of the prey and by creating false edges. In paper III, I show that an eyebar effectively disrupts an eyelike shape. This suggests that eyebars provide an effective way to conceal the eyes and consequently obstruct detection and recognition of prey. This experiment also demonstrates that through concealment of the eyes, eyebars could be used to enhance the divertive effect of eyespots, which can explain the common occurrence of eyebars in many species of fish that have eyespots. Larger eyespots have been shown to intimidate some terrestrial predators, such as passerine birds, either because they resemble the eyes of the predator’s own enemy or because highly salient features may have an intimidating effect. In papers II and IV, I investigated whether the occurrence of eyespots in some aquatic prey could be explained by their intimidating effect predatory fish. In paper IV, I also investigated the reason for the intimidating effect of eyelike prey marks. In paper II, I found no clear intimidating effect of eyespots, whereas in paper IV, using a different approach, I found that sticklebacks hesitated to attack towards eyelike but not towards non-eyelike marks. Importantly, paper IV therefore presents the first rigorous evidence for the idea that eye mimicry, and not merely conspicuousness, underlies the intimidating effect. It also showed that the hesitation shown by fish towards eyelike marks is partly an innate response that is reinforced by encounters with predators. Collectively, this thesis shows that prey colour pattern and the visual appearance of the habitat influence the behaviour of fish. The results demonstrate that protective coloration provides numerous distinctive ways for aquatic prey to escape predation. Thus, visual perception and behaviour of fish are important factors shaping the appearance and behaviours of aquatic prey.

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In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

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Service provider selection has been said to be a critical factor in the formation of supply chains. Through successful selection companies can attain competitive advantage, cost savings and more flexible operations. Service provider management is the next crucial step in outsourcing process after the selection has been made. Without proper management companies cannot be sure about the level of service they have bought and they may suffer from service provider's opportunistic behavior. In worst case scenario the buyer company may end up in locked-in situation in which it is totally dependent of the service provider. This thesis studies how the case company conducts its carrier selection process along with the criteria related to it. A model for the final selection is also provided. In addition, case company's carrier management procedures are reflected against recommendations from previous researches. The research was conducted as a qualitative case study on the principal company, Neste Oil Retail. A literature review was made on outsourcing, service provider selection and service provider management. On the basis of the literature review, this thesis ended up recommending Analytic hierarchy process as the preferred model for the carrier selection. Furthermore, Agency theory was seen to be a functional framework for carrier management in this study. Empirical part of this thesis was conducted in the case company by interviewing the key persons in the selection process, making observations and going through documentations related to the subject. According to the results from the study, both carrier selection process as well as carrier management were closely in line with suggestions from literature review. Analytic hierarchy process results revealed that the case company considers service quality as the most important criteria with financial situation and price of service following behind with almost identical weights with each other. Equipment and personnel was seen as the least important selection criterion. Regarding carrier management, the study resulted in the conclusion that the company should consider engaging more in carrier development and working towards beneficial and effective relationships. Otherwise, no major changes were recommended for the case company processes.

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The main goal of this thesis is to increase understanding on evolutionary and ecological factors that have contributed to differences in parasite numbers in insects. Furthermore, the thesis addresses the effects of parasites on their hosts. The most important findings were: The Northern damselfly’s (Coenagrion hastulatum) immune response to artificial pathogen increased with increasing parasite numbers (Article I). Marginal, more isolated C. hastulatum populations on the edge of distribution have fewer parasites when compared to distribution’s core populations (Article II). The Banded damselfly Calopteryx splendens individuals with higher homozygosity have more parasites, however, the rate of homozygosity did not differ between populations (Article III). Parasite prevalence was affected by whether the host species occurred in allopatric or sympatric population: sympatric C. splendens populations with sister species the Beautiful damselfly Calopteryx virgo harbored more parasites (Article IV). Parasites were associated with the wing spot size, an ornament under sexual selection, and thus may play an important role in character displacement, i.e. the size of the wing spot (Article V). To conclude with, this thesis brings about new information on the parasite infection patterns in insects, proposing several factors to contribute to these patters, as well as it addresses the effects of parasites on their hosts, from individual to population level.

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Ribonucleic acid (RNA) has many biological roles in cells: it takes part in coding, decoding, regulating and expressing of the genes as well as has the capacity to work as a catalyst in numerous biological reactions. These qualities make RNA an interesting object of various studies. Development of useful tools with which to investigate RNA is a prerequisite for more advanced research in the field. One of such tools may be the artificial ribonucleases, which are oligonucleotide conjugates that sequence-selectively cleave complementary RNA targets. This thesis is aimed at developing new efficient metal-ion-based artificial ribonucleases. On one hand, to solve the challenges related to solid-supported synthesis of metal-ion-binding conjugates of oligonucleotides, and on the other hand, to quantify their ability to cleave various oligoribonucleotide targets in a pre-designed sequence selective manner. In this study several artificial ribonucleases based on cleaving capability of metal ion chelated azacrown moiety were designed and synthesized successfully. The most efficient ribonucleases were the ones with two azacrowns close to the 3´- end of the oligonucleotide strand. Different transition metal ions were introduced into the azacrown moiety and among them, the Zn2+ ion was found to be better than Cu2+ and Ni2+ ions.

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Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.

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The aim of this research is to examine the pricing anomalies existing in the U.S. market during 1986 to 2011. The sample of stocks is divided into decile portfolios based on seven individual valuation ratios (E/P, B/P, S/P, EBIT/EV, EVITDA/EV, D/P, and CE/P) and price momentum to investigate the efficiency of individual valuation ratio and their combinations as portfolio formation criteria. This is the first time in financial literature when CE/P is employed as a constituent of composite value measure. The combinations are based on median scaled composite value measures and TOPSIS method. During the sample period value portfolios significantly outperform both the market portfolio and comparable glamour portfolios. The results show the highest return for the value portfolio that was based on the combination of S/P & CE/P ratios. The outcome of this research will increase the understanding on the suitability of different methodologies for portfolio selection. It will help managers to take advantage of the results of different methodologies in order to gain returns above the market.

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An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a “virtual” best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.