Sustainable linguistic repository built on DSpace

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

Making the impact on research and society : nichesourcing of Uralic language material for the benefit of linguistic research and native-speakers

Presentation at the 12th Bibliotheca Baltica Symposium at Södertörn University Library

A 37-kb restriction map of the human immunoglobulin lambda variable locus, VB cluster, harboring four functional genes and two non-coding Vl sequences

The human immunoglobulin lambda variable locus (IGLV) is mapped at chromosome 22 band q11.1-q11.2. The 30 functional germline v-lambda genes sequenced untill now have been subgrouped into 10 families (Vl1 to Vl10). The number of Vl genes has been estimated at approximately 70. This locus is formed by three gene clusters (VA, VB and VC) that encompass the variable coding genes (V) responsible for the synthesis of lambda-type Ig light chains, and the Jl-Cl cluster with the joining segments and the constant genes. Recently the entire variable lambda gene locus was mapped by contig methodology and its one- megabase DNA totally sequenced. All the known functional V-lambda genes and pseudogenes were located. We screened a human genomic DNA cosmid library and isolated a clone with an insert of 37 kb (cosmid 8.3) encompassing four functional genes (IGLV7S1, IGLV1S1, IGLV1S2 and IGLV5a), a pseudogene (VlA) and a vestigial sequence (vg1) to study in detail the positions of the restriction sites surrounding the Vl genes. We generated a high resolution restriction map, locating 31 restriction sites in 37 kb of the VB cluster, a region rich in functional Vl genes. This mapping information opens the perspective for further RFLP studies and sequencing

Effects of prenatal exposure to a mild chronic variable stress on body weight, preweaning mortality and rat behavior

Early stimulation has been shown to produce long-lasting effects in many species. Prenatal exposure to some strong stressors may affect development of the nervous system leading to behavioral impairment in adult life. The purpose of the present work was to study the postnatal harmful effects of exposure to variable mild stresses in rats during pregnancy. Female Holtzman rats were submitted daily to one session of a chronic variable stress (CVS) during pregnancy (prenatal stress; PS group). Control pregnant rats (C group) were undisturbed. The pups of PS and C dams were weighed and separated into two groups 48 h after delivery. One group was maintained with their own dams (PS group, N = 70; C group, N = 36) while the other PS pups were cross-fostered with C dams (PSF group, N = 47) and the other C pups were cross-fostered with PS dams (CF group, N = 58). Pups were undisturbed until weaning (postnatal day 28). The male offspring underwent motor activity tests (day 28), enriched environment tests (day 37) and social interaction tests (day 42) in an animal activity monitor. Body weight was recorded on days 2, 28 and 60. The PS pups showed lower birth weight than C pups (Duncan's test, P<0.05). The PS pups suckling with their stressed mothers displayed greater preweaning mortality (C: 23%, PS: 60%; c2 test, P<0.05) and lower body weight than controls at days 28 and 60 (Duncan's test, P<0.05 and P<0.01, respectively). The PS, PSF and CF groups showed lower motor activity scores than controls when tested at day 28 (Duncan's test, P<0.01 for PS group and P<0.05 for CF and PSF groups). In the enriched environment test performed on day 37, between-group differences in total motor activity were not detected; however, the PS, CF and PSF groups displayed less exploration time than controls (Duncan's test, P<0.05). Only the PS group showed impaired motor activity and impaired social behavior at day 42 (Duncan's test, P<0.05). In fact, CVS treatment during gestation plus suckling with a previously stressed mother caused long-lasting physical and behavioral changes in rats. Cross-fostering PS-exposed pups to a dam which was not submitted to stress counteracted most of the harmful effects of the treatment. It is probable that prenatal stress plus suckling from a previously stressed mother can induce long-lasting changes in the neurotransmitter systems involved in emotional regulation. Further experiments using neurochemical and pharmacological approaches would be interesting in this model.

Expression of anti-Z-DNA single chain antibody variable fragment on the filamentous phage surface

We describe the expression of an anti-Z-DNA single chain variable region antibody fragment (scFv) on a filamentous phage surface. Four vectors for phage display were constructed. Two of them are able to display multiple copies of the antibody fragment, and the others can be used to make monovalent libraries. The vectors use different promoter/leader sequences to direct the expression of the fused proteins. All were able to promote the assembly of fusion virion particles. In this paper we also show the affinity selection (biopanning) of those phage-antibodies based on the capacity of their products to recognize the antigen. We used biotinylated Z-DNA and the selection was performed in a solution phase fashion. The data presented here indicate that these vectors can be further used to construct anti-nucleic acid antibody fragment libraries that can be used to study the basis of nucleic acid-protein interaction and its role in autoimmunity mechanisms.

Association between EcoRI fragment-length polymorphism of the immunoglobulin lambda variable 8 (IGLV8) gene family with rheumatoid arthritis and systemic lupus erythematosus

The human immunoglobulin lambda variable 8 (IGLV8) subgroup is a gene family containing three members, one of them included in a monomorphic 3.7-kb EcoRI genomic fragment located at the major lambda variable locus on chromosome 22q11.1 (gene IGLV8a, EMBL accession No. Z73650) at 100% frequency in the normal urban population. The second is a polymorphic RFLP allele included in a 6.0-kb EcoRI fragment at 10% frequency, and the third is located in a monomorphic 8.0-kb EcoRI fragment at 100% frequency, the last being translocated to chromosome 8q11.2 and considered to be an orphan gene. Our Southern blot-EcoRI-RFLP studies in normal individuals and in patients with rheumatoid arthritis (RA) or with systemic lupus erythematosus (SLE), using a specific probe for the IGLV8 gene family (probe pVL8, EMBL accession No. X75424), have revealed the two monomorphic genomic fragments containing the IGLV8 genes, i.e., the 3.7-kb fragment from chromosome 22q11.1 and the 8.0-kb fragment from 8q11.2, both occurring at 100% frequency (103 normal individuals, 48 RA and 28 SLE patients analyzed), but absence of the 6.0-kb IGLV8 polymorphic RFLP allele in all RA or SLE patients. As expected, the frequency of the 6.0-kb allele among the normal individuals was 10%. These findings suggest an association between the absence of the 6.0-kb EcoRI fragment and rheumatoid arthritis and systemic lupus erythematosus.

Lebesgue and Sobolev spaces with variable exponents

Kirjallisuusarvostelu

Fuzzy tolerance/equivalence relations from intersection, union and complement operators and their application to a clustering method

This master thesis work introduces the fuzzy tolerance/equivalence relation and its application in cluster analysis. The work presents about the construction of fuzzy equivalence relations using increasing generators. Here, we investigate and research on the role of increasing generators for the creation of intersection, union and complement operators. The objective is to develop different varieties of fuzzy tolerance/equivalence relations using different varieties of increasing generators. At last, we perform a comparative study with these developed varieties of fuzzy tolerance/equivalence relations in their application to a clustering method.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

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.

Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

Fuzzy expert system in the prediction of neonatal resuscitation

In view of the importance of anticipating the occurrence of critical situations in medicine, we propose the use of a fuzzy expert system to predict the need for advanced neonatal resuscitation efforts in the delivery room. This system relates the maternal medical, obstetric and neonatal characteristics to the clinical conditions of the newborn, providing a risk measurement of need of advanced neonatal resuscitation measures. It is structured as a fuzzy composition developed on the basis of the subjective perception of danger of nine neonatologists facing 61 antenatal and intrapartum clinical situations which provide a degree of association with the risk of occurrence of perinatal asphyxia. The resulting relational matrix describes the association between clinical factors and risk of perinatal asphyxia. Analyzing the inputs of the presence or absence of all 61 clinical factors, the system returns the rate of risk of perinatal asphyxia as output. A prospectively collected series of 304 cases of perinatal care was analyzed to ascertain system performance. The fuzzy expert system presented a sensitivity of 76.5% and specificity of 94.8% in the identification of the need for advanced neonatal resuscitation measures, considering a cut-off value of 5 on a scale ranging from 0 to 10. The area under the receiver operating characteristic curve was 0.93. The identification of risk situations plays an important role in the planning of health care. These preliminary results encourage us to develop further studies and to refine this model, which is intended to implement an auxiliary system able to help health care staff to make decisions in perinatal care.

Selection of patients for myocardial perfusion scintigraphy based on fuzzy sets theory applied to clinical-epidemiological data and treadmill test results

Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Variable positive end-expiratory pressure can maintain oxygenation in experimental acute respiratory distress syndrome induced by oleic acid in dogs

The use of positive end-expiratory pressure (PEEP) or lung recruitment maneuvers (RM) to improve oxygenation in acute respiratory distress syndrome (ARDS) is used but it may reduce cardiac output (CO). Intermittent PEEP may avoid these complications. Our objective was to determine if variable PEEP compared with constant PEEP is capable of maintaining arterial oxygenation and minimizing hemodynamic alterations with or without RM. Eighteen dogs with ARDS induced by oleic acid were randomized into three equal groups: group 1, low variable PEEP; group 2, high variable PEEP, and group 3, RM + high variable PEEP. All groups were submitted to constant PEEP, followed by variable PEEP (PEEP was increased from 5 to 10 cmH2O in group 1, and from 5 to 18 cmH2O in the other two groups). PaO2 was higher in group 3 (356.2 ± 65.4 mmHg) than in group 1 (92.7 ± 29.7 mmHg) and group 2 (228.5 ± 72.4 mmHg), P < 0.05. PaO2 was maintained during variable PEEP except in group 2 (318.5 ± 82.9 at constant PEEP to 228.5 ± 72.4 at variable PEEP). There was a reduction in CO in group 3 after RM (3.9 ± 1.1 before to 2.7 ± 0.5 L·min-1·(m2)-1 after; P < 0.05), but there was not any difference between constant and variable PEEP periods (2.7 ± 0.5 and 2.4 ± 0.7 L·min-1·(m2)-1; P > 0.05. Variable PEEP is able to maintain PaO2 when performed in combination with RM in dogs with ARDS. After RM, CO was reduced and there was no relevant difference between the variable and constant PEEP periods.

A conjugate of an anti-midkine single-chain variable fragment to doxorubicin inhibits tumor growth

Doxorubicin (DOX) was conjugated to a single-chain variable fragment (scFv) against human midkine (MK), and the conjugate (scFv-DOX) was used to target the chemotherapeutic agent to a mouse solid tumor model in which the tumor cells expressed high levels of human MK. The His-tagged recombinant scFv was expressed in bacteria, purified by metal affinity chromatography, and then conjugated to DOX using oxidative dextran (Dex) as a linker. The molecular formula of this immunoconjugate was scFv(Dex)1.3(DOX)20. In vitro apoptosis assays showed that the scFv-DOX conjugate was more cytotoxic against MK-transfected human adenocarcinoma cells (BGC823-MK) than untransfected cells (55.3 ± 2.4 vs 22.4 ± 3.8%) for three independent experiments. Nude mice bearing BGC823-MK solid tumors received scFv-DOX or equivalent doses of scFv + DOX for 2 weeks and tumor growth was more effectively inhibited by the scFv-DOX conjugate than by scFv + DOX (51.83% inhibition vs 40.81%). Histological analysis of the tumor tissues revealed that the highest levels of DOX accumulated in tumors from mice treated with scFv-DOX and this resulted in more extensive tumor cell death than in animals treated with the equivalent dose of scFv + DOX. These results show that the scFv-DOX conjugate effectively inhibited tumor growth in vivo and suggest that antigen-specific scFv may be competent drug-carriers.