<p>Dyskinesias or abnormal involuntary movements are a debilitating complication of long-term levodopa treatment of Parkinson’s disease (PD) that is widely experienced and may compromise the efficacy of the drug therapy. Tardive dyskinesia is another important adverse effect seen with antipsychotic drug treatment. The neural mechanisms underlying levodopa- and neuroleptic-induced dyskinesia are not clear and involvement of the endogenous opioid neuropeptide system has been implicated. In this thesis, the role of the opioid system is investigated in models of dyskinesia and PD using behavioral, neurochemical and advanced analytical chemistry techniques. In addition, the motor effects of a new partial dopamine agonist with normalizing properties on both reduced and elevated dopamine transmission are studied and a new model for tardive dyskinesia is presented.</p><p>Using microdialysis in combination with micro-electrospray mass spectrometry, the <i>in vivo</i> processing of the opioid neuropeptide dynorphin A(1-17) was studied and 32 metabolites were detected in the striatum. Altered <i>in vivo</i> metabolism of the peptide was found in a model of PD with more metabolites formed in the dopamine-depleted striatum. Moreover, dynorphin A(1-17) was differently processed in levodopa-, bromocriptine and saline-treated animals. </p><p>Levodopa treatment caused an increase in the mRNA expression of the precursor of dynorphin, preproenkephalin-B as well as the precursor of enkephalin, preproenkephalin-A, in all sub-regions of the dopamine-depleted striatum. A non-selective opioid receptor antagonist, naloxone, was found to reduce levodopa-induced dyskinesia with maintained antiparkinsonian response and a normalization of hyperkinesia. Moreover, the new drug GMC1111 showed dopamine stabilizing properties in models of levodopa-induced dyskinesia and PD. This might prove useful in the treatment of PD.</p><p>Altogether, these results suggest that the endogenous opioid system is involved in the pathophysiology of levodopa-induced dyskinesia.</p>

Dyskinesias or abnormal involuntary movements are a debilitating complication of long-term levodopa treatment of Parkinson’s disease (PD) that is widely experienced and may compromise the efficacy of the drug therapy. Tardive dyskinesia is another important adverse effect seen with antipsychotic drug treatment. The neural mechanisms underlying levodopa- and neuroleptic-induced dyskinesia are not clear and involvement of the endogenous opioid neuropeptide system has been implicated. In this thesis, the role of the opioid system is investigated in models of dyskinesia and PD using behavioral, neurochemical and advanced analytical chemistry techniques. In addition, the motor effects of a new partial dopamine agonist with normalizing properties on both reduced and elevated dopamine transmission are studied and a new model for tardive dyskinesia is presented. Using microdialysis in combination with micro-electrospray mass spectrometry, the in vivo processing of the opioid neuropeptide dynorphin A(1-17) was studied and 32 metabolites were detected in the striatum. Altered in vivo metabolism of the peptide was found in a model of PD with more metabolites formed in the dopamine-depleted striatum. Moreover, dynorphin A(1-17) was differently processed in levodopa-, bromocriptine and saline-treated animals. Levodopa treatment caused an increase in the mRNA expression of the precursor of dynorphin, preproenkephalin-B as well as the precursor of enkephalin, preproenkephalin-A, in all sub-regions of the dopamine-depleted striatum. A non-selective opioid receptor antagonist, naloxone, was found to reduce levodopa-induced dyskinesia with maintained antiparkinsonian response and a normalization of hyperkinesia. Moreover, the new drug GMC1111 showed dopamine stabilizing properties in models of levodopa-induced dyskinesia and PD. This might prove useful in the treatment of PD. Altogether, these results suggest that the endogenous opioid system is involved in the pathophysiology of levodopa-induced dyskinesia.

In many important real world applications the initial representation of the data is inconvenient, or even prohibitive for further analysis. For example, in image analysis, text analysis and computational genetics high-dimensional, massive, structural, incomplete, and noisy data sets are common. Therefore, feature extraction, or revelation of informative features from the raw data is one of fundamental machine learning problems. Efficient feature extraction helps to understand data and the process that generates it, reduce costs for future measurements and data analysis. The representation of the structured data as a compact set of informative numeric features allows applying well studied machine learning techniques instead of developing new ones.. The dissertation focuses on supervised and semi-supervised feature extraction methods, which optimize the dependence structure of features. The dependence is measured using the kernel estimator of Hilbert-Schmidt norm of covariance operator (HSIC measure). Two dependence structures are investigated: in the first case we seek features which maximize the dependence on the dependent variable, and in the second one, we additionally minimize the mutual dependence of features. Linear and kernel formulations of HBFE and HSCA are provided. Using Laplacian regularization framework we construct semi-supervised variants of HBFE and HSCA. Suggested algorithms were investigated experimentally using conventional and multilabel classification data... [to full text] / Daugelis praktiškai reikšmingu sistemu mokymo uždaviniu reikalauja gebeti panaudoti didelio matavimo, strukturizuotus, netiesinius duomenis. Vaizdu, teksto, socialiniu bei verslo ryšiu analize, ivairus bioinformatikos uždaviniai galetu buti tokiu uždaviniu pavyzdžiais. Todel požymiu išskyrimas dažnai yra pirmasis žingsnis, kuriuo pradedama duomenu analize ir nuo kurio priklauso galutinio rezultato sekme. Šio disertacinio darbo tyrimo objektas yra požymiu išskyrimo algoritmai, besiremiantys priklausomumo savoka. Darbe nagrinejamas priklausomumas, nusakytas kovariacinio operatoriaus Hilberto-Šmidto normos (HSIC mato) branduoliniu ivertiniu. Pasiulyti šiuo ivertiniu besiremiantys HBFE ir HSCA algoritmai leidžia dirbti su bet kokios strukturos duomenimis, bei yra formuluojami tikriniu vektoriu terminais (tai leidžia optimizavimui naudoti standartinius paketus), bei taikytini ne tik prižiurimo, bet ir dalinai prižiurimo mokymo imtims. Pastaruoju atveju HBFE ir HSCA modifikacijos remiasi Laplaso reguliarizacija. Eksperimentais su klasifikavimo bei daugiažymio klasifikavimo duomenimis parodyta, jog pasiulyti algoritmai leidžia pagerinti klasifikavimo efektyvuma lyginant su PCA ar LDA.

Daugelis praktiškai reikšmingu sistemu mokymo uždaviniu reikalauja gebeti panaudoti didelio matavimo, strukturizuotus, netiesinius duomenis. Vaizdu, teksto, socialiniu bei verslo ryšiu analize, ivairus bioinformatikos uždaviniai galetu buti tokiu uždaviniu pavyzdžiais. Todel požymiu išskyrimas dažnai yra pirmasis žingsnis, kuriuo pradedama duomenu analize ir nuo kurio priklauso galutinio rezultato sekme. Šio disertacinio darbo tyrimo objektas yra požymiu išskyrimo algoritmai, besiremiantys priklausomumo savoka. Darbe nagrinejamas priklausomumas, nusakytas kovariacinio operatoriaus Hilberto-Šmidto normos (HSIC mato) branduoliniu ivertiniu. Pasiulyti šiuo ivertiniu besiremiantys HBFE ir HSCA algoritmai leidžia dirbti su bet kokios strukturos duomenimis, bei yra formuluojami tikriniu vektoriu terminais (tai leidžia optimizavimui naudoti standartinius paketus), bei taikytini ne tik prižiurimo, bet ir dalinai prižiurimo mokymo imtims. Pastaruoju atveju HBFE ir HSCA modifikacijos remiasi Laplaso reguliarizacija. Eksperimentais su klasifikavimo bei daugiažymio klasifikavimo duomenimis parodyta, jog pasiulyti algoritmai leidžia pagerinti klasifikavimo efektyvuma lyginant su PCA ar LDA. / In many important real world applications the initial representation of the data is inconvenient, or even prohibitive for further analysis. For example, in image analysis, text analysis and computational genetics high-dimensional, massive, structural, incomplete, and noisy data sets are common. Therefore, feature extraction, or revelation of informative features from the raw data is one of fundamental machine learning problems. Efficient feature extraction helps to understand data and the process that generates it, reduce costs for future measurements and data analysis. The representation of the structured data as a compact set of informative numeric features allows applying well studied machine learning techniques instead of developing new ones.. The dissertation focuses on supervised and semi-supervised feature extraction methods, which optimize the dependence structure of features. The dependence is measured using the kernel estimator of Hilbert-Schmidt norm of covariance operator (HSIC measure). Two dependence structures are investigated: in the first case we seek features which maximize the dependence on the dependent variable, and in the second one, we additionally minimize the mutual dependence of features. Linear and kernel formulations of HBFE and HSCA are provided. Using Laplacian regularization framework we construct semi-supervised variants of HBFE and HSCA. Suggested algorithms were investigated experimentally using conventional and multilabel classification data... [to full text]

Introduction: Breastfeeding offers the substance exposed mother and child potential short and long-term health benefits, with breast milk shown to alleviate the severity of Neonatal Abstinence Syndrome. Substance dependent women, however, have limited success establishing breastfeeding with physical, psychological and institutional factors cited as barriers. This study aimed to develop and test the feasibility of an evidence informed and theory based intervention to support continued breastfeeding for this group. Methods: The research was a two-phase feasibility study. Phase 1 informed intervention development using a mixed methodology approach which included (a) a comprehensive systematic literature review of breastfeeding support for women from disadvantaged groups (b) expert advisory group recommendations and (c) ‘think aloud’ verbal protocols with opioid dependent women. Phase 2 underpinned the evidence with the theoretical constructs of behaviour change, prior to testing the acceptability and implementation fidelity of the intervention in a feasibility study with an embedded small-scale randomised controlled trial. Results: Phase 1 identified the barriers to breastfeeding continuation as low maternal self-efficacy; neonatal feeding difficulties associated with withdrawal and unsupportive healthcare practices. Evidence and theory synthesis resulted in an integrated breastfeeding support model founded on practical, informational, psychological, person-centred and environmental components. Phase 2 demonstrated that the intervention was feasible to implement and acceptable to participants. The randomised controlled trial reported higher rates of continued breastfeeding and a greater level of maternal confidence in breastfeeding ability in the intervention group compared to the control group. Breastfed infants were less likely to require pharmacological management and had corresponding shorter durations of hospitalisation than formula fed infants. Conclusion: The research provided an original contribution to the development of a complex healthcare intervention which is meaningful to both existing research and clinical practice. The findings highlighted the potential of the intervention to support breastfeeding for the substance exposed mother and baby, which has wide ranging implications for the improved health and social equalities of this group.

This is the first research to empirically study the congruity in supply chain operations strategies. The tests show that the congruity in supply chain operations strategies are related to performance and also moderate the association between performance and the types of supply chain relationships. 308 manufacturing firms were studied for empirical tests. Various methods including multiple regressions, cluster analyses, and logistic regressions are applied in this study. Based on the tests, five hypotheses are supported and only one hypothesis is inconclusive. This dissertation contributes in different thresholds. First, by studying operations strategies through a different angle (the supply chain instead of a firm) this study reconciles results in the relationships between performance and operations strategies and between performance and supply chain relationships. Therefore, this study contributes to reconciling two long-term puzzles in both operations strategies and supply chain management literatures. Second, this research draws on three different disciplines, operations strategies, supply chain management and organization theory (resource dependence theory). This interdisciplinary approach provides a broader perspective in operations management research. Third, through this research, guidelines are provided for not only powerful firms but also the weak ones on how to improve their performance through developing different types of supply chain relationships and integrating their operations strategies with their supply chain members.

Essa dissertação pretende mostrar que, na fase de formulação da política nacional de concessão de benefícios tributários, não existem obstáculos impeditivos à imposição da agenda do governo. Essa fase é antes marcada pela discricionariedade do Executivo na apresentação frequente de Medidas Provisórias que criam benefícios tributários. Além disso, o processo não é fechado à participação, pois, durante a tramitação destas proposições no Congresso Nacional, está sujeito à atuação de grupos de interesse privilegiados buscando sua parcela de benefícios distributivos. Por outro lado, existem entraves significativos colocados à fase da implementação das proposições que concedem benefícios tributários. Por ser uma política de difícil acompanhamento, sua execução está sujeita a impasses, negociações e busca de consensos entre setores da burocracia pública e destes com os órgãos de controle externo, o que impõe uma trajetória incremental à fase da implementação, e dificulta a avaliação da eficiência, eficácia e efetividade dos benefícios tributários. Além disso, a política nacional de concessão de benefícios tributários tem características de dependência de trajetória, pois, ao resolver problemas pontuais no varejo, tem se tornado a opção de ação governamental mais viável na ausência de uma reforma tributária abrangente. / This dissertation purpose to show that, at the formulation stage of national tax breaks concession policy, there are no obstacles impending the governments agenda imposition. Rather, this stage is marked by Executives discretion in the frequent presentation of Provisional Measures that create tax breaks. Also, the process is not closed to participation, because during the course of these proposals in Congress, this is liable of privileged interest groups action seeking their portion of distributive benefits. On the other hand, there are significant barriers imposed at the implementation stage of the tax breaks proposals. Because there is a policy of difficult monitoring, its execution is liable to impasses, negotiations and attempts to build consensus among sectors of the public bureaucracy and the latter with external control agencies, compelling an incremental path to the implementation stage, and hampers the evaluation of efficiency, efficacy and effectiveness of tax breaks. Furthermore, the national tax breaks concession policy has path dependence characteristics, because, to solving specific problems at retail, has become the most practicable option of governmental action in the absence of a comprehensive tax reform.

In the present thesis we deal with dependence among extremal values within time series. Concerning this type of relations the commonly used autocorrelation function does not provide sufficient information. Moreover, autocorrelation function is suitable for Gaussian processes while nowadays we often work with heavy-tailed time series. In this thesis we cover two measures of extremal dependence that are used for this type of data. We introduce the coefficient of tail dependence, measure of extremal dependence based on tail characteristics of joint survival function. The second measure is called extremogram, which depends only on the extreme values in the sequence. In addition to the theoretical part, simulation study and application to real data of both described measures including their comparison are performed. Results are stated together with tables and graphical output.

The motivation of the bachelor thesis is to provide an understanding of democracy in Iraq from 2003 until present. After the fall of Saddam’s regime, there have been general elections but there is still an unstable democracy in Iraq. What are the reasons behind the failure of democracy in Iraq? Of course, there are many reasons behind this but my choice is to focus on three specific ones. How do these three variables that I have chosen, affect the possibility of democracy in Iraq? These two questions will be answered in this bachelor thesis, using Path Dependence Theory and Dahl’s Polyarchy Model and its Criteria that help to analyze and answer the research questions. Iraq has many major problems but the three I have focused on are ethnic and religious divides between Shia and Sunni, the violent environment and the presence of terrorist groups.

Philosophiae Doctor - PhD / The thesis examines how elite perspectives on foreign aid affect the subsequent path of aid dependence. The focus is on aid-seeking foreign policy change. Two foreign policy change cases are examined for the study, which took place in Korea under Park Chung-hee and in Ghana under Rawlings through a lens of comparative historical analysis. The thesis aims to make two original contributions to knowledge. First, it explains recipient foreign policy using two different forms of mercantilism, and second, it reveals the dependent path created by the mercantilist oriented elite. Mercantilism in the thesis is used as dual-frameworked concept. First, it is a lens to see state behaviour. Despite the fact that mercantilism has been mainly used to explain a donor‘s behaviour, it can elucidate that of an aid-recipient state when the aid-seeking country is in dire need of the foreign aid for the survival of the state. The thesis applies mercantilism to explain aid-receiving countries‘behaviour. Second, more importantly, mercantilism also explains elite perspectives. The elite in aid receiving countries search for foreign aid not only for the wealth and power of their state, but also for the prosperity and survival of themselves. Mercantilism is used as an ostensible principle in practicing the private search for advantages of the elite. The thesis uses the dual-mercantilism idea to examine aid-seeking foreign policy in Korea and Ghana. In Korea, the elite saw the key to their survival in industrialising the nation, and their search for foreign aid took place based on that raison d’être. In Ghana, on the other hand, the elite found the way to their survival and prosperity in acquiring more foreign aid and the aid per se became the ultimate goal. The thesis finds industrial mercantilism a useful framework to understand the elite perspective in Korea