14,941 research outputs found

    Central-provincial Politics and Industrial Policy-making in the Electric Power Sector in China

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    In addition to the studies that provide meaningful insights into the complexity of technical and economic issues, increasing studies have focused on the political process of market transition in network industries such as the electric power sector. This dissertation studies the central–provincial interactions in industrial policy-making and implementation, and attempts to evaluate the roles of Chinese provinces in the market reform process of the electric power sector. Market reforms of this sector are used as an illustrative case because the new round of market reforms had achieved some significant breakthroughs in areas such as pricing reform and wholesale market trading. Other policy measures, such as the liberalization of the distribution market and cross-regional market-building, are still at a nascent stage and have only scored moderate progress. It is important to investigate why some policy areas make greater progress in market reforms than others. It is also interesting to examine the impacts of Chinese central-provincial politics on producing the different market reform outcomes. Guangdong and Xinjiang are two provinces being analyzed in this dissertation. The progress of market reforms in these two provinces showed similarities although the provinces are very different in terms of local conditions such as the stages of their economic development and energy structures. The actual reform can be understood as the outcomes of certain modes of interactions between the central and provincial actors in the context of their particular capabilities and preferences in different policy areas. This dissertation argues that market reform is more successful in policy areas where the central and provincial authorities are able to engage mainly in integrative negotiations than in areas where they engage mainly in distributive negotiations

    Change of depressive symptoms during the course of electroconvulsive therapy (ECT) and predictive value of these symptoms for ECT outcome

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    Aim: Research examining change in symptoms of depression during treatment with electroconvulsive therapy (ECT) and proposing reliable predictors of ECT outcome is limited and previous studies have led to inconclusive results. This dissertation aims to explore the change of depressive symptomatology assessed with Montgomery-Åsberg Depression Rating Scale (MADRS) single items throughout the course of ECT and analyse the predictive value of these MADRS single items and their change throughout the course of ECT treatment regarding ECT outcome. Methods: This retrospective naturalistic study analysed MADRS data from 96 depressed psychiatric inpatients. MADRS data were routinely collected at three time points during the course of ECT treatment. ANOVAs for repeated measures were used to explore change of depressive symptomatology throughout the course of ECT. In order to analyse the predictive value of depressive symptomatology and its change regarding ECT treatment outcome logistic and linear regression models were applied. Results: Strongest reductions throughout the course of ECT treatment were found for MADRS items apparent sadness, reported sadness and inability to feel, assessing affective symptoms of depression. Lowest reductions were found for items assessing concentration difficulties and suicidal thoughts. MADRS single items were found to be potent predictors of ECT outcome, particularly the following items addressing affective symptomatology: apparent sadness, reported sadness, and inability to feel. Regression models that contained reported sadness indicated the most potent effects with as much as 80% correct prediction of ECT outcome. In order to determine a favorable MADRS cutoff value for ECT response, we conducted ROC analyses. Conclusions: Affective symptoms of depression decreased the most throughout the course of antidepressant ECT treatment. A favorable ECT outcome appears to be associated with more pronounced affective depressive symptomatology at baseline before treatment start and a stronger decline of affective symptomatology throughout the course of ECT. Additionally, precise cut-off values for clinical use after future validation were suggested. In search of reliable and easy-to-assess predictors of ECT outcome, depressive symptoms measured with MADRS single items could be regarded as a cost- and time-effective, valuable addition to clinical decision-making. In general, these findings illustrate the potential of a symptom-based approach, which might pose a useful expansion to the prevailing focus on depression sum-scores and generalized diagnostic categories in depression research and treatment.Ziel: Bislang liegen wenig belastbare Ergebnisse zur Veränderung distinkter depressiver Symptome durch die Behandlung mit EKT sowie zu zuverlässigen Prädiktoren einer erfolgreichen antidepressiven Behandlung mit EKT vor. Vorangegangene Studien haben zudem teils widersprüchliche Ergebnisse hervorgebracht. Diese Dissertation untersucht daher die Veränderung depressiver Symptome während der Behandlung mit EKT sowie die Vorhersagekraft initial bestehender depressiver Symptome und ihrer Veränderungen für eine erfolgreiche EKT-Behandlung. Einzelne depressive Symptome wurden dabei mittels Einzel-Items der Montgomery-Åsberg Depression Rating Scale (MADRS) erfasst. Methodik: In dieser naturalistischen retrospektiven Studie wurden MADRS Daten von 96 depressiven Patienten ausgewertet, die sich in stationärer psychiatrischer Behandlung befanden. Dabei wurden Daten von drei Messzeitpunkten im Verlauf der EKT-Behandlung analysiert. ANOVAs für Messwiederholungen wurden verwendet, um die Veränderung der depressiven Symptome im Verlauf der EKT-Behandlung zu untersuchen. Logistische und lineare Regressionsmodelle wurden angewandt, um die Vorhersagekraft distinkter depressiver Symptome und ihrer Veränderungen für eine erfolgreiche EKT-Behandlung zu explorieren. Ergebnisse: Die stärkste Symptomreduktion im Verlauf der EKT-Behandlung wurde für affektive Symptome gefunden; für die Items Sichtbare Traurigkeit, Berichtete Traurigkeit und Gefühllosigkeit. Die geringste Symptomreduktion wurde in Bezug auf Konzentrationsschwierigkeiten sowie Suizidgedanken gefunden. MADRS Einzel-Items waren wirksame Prädiktoren für das Ergebnis der EKT-Behandlung, insbesondere die o.g. affektiven Symptome. Die stärksten Effekte wurden dabei für Regressionsmodelle mit dem Item Berichtete Traurigkeit gefunden, mit bis zu 80% korrekter Vorhersage des Behandlungsergebnisses. Mittels ROC-Analysen konnten Schwellenwerte für die Vorhersage einer erfolgreichen EKT-Behandlung definiert werden. Schlussfolgerungen: Im Verlauf der antidepressiven Behandlung mit EKT reduzierte sich die affektive depressive Symptomatik am meisten. Eine stärker ausgeprägte affektive Symptomatik zu Behandlungsbeginn sowie eine stärkere Abnahme dieser affektiven Symptome im Behandlungsverlauf scheinen mit einem günstigeren Behandlungsergebnis einherzugehen. Dementsprechend könnten depressive Symptome erfasst anhand von MADRS Einzel-Items einfache, zuverlässige sowie zeit- und kostensparende Prädiktoren für erfolgreiche EKTBehandlungen darstellen und somit einen wertvollen Beitrag zur klinischen Entscheidungsfindung leisten. Diese Befunde verdeutlichen zudem den zusätzlichen Nutzen symptombasierter Depressionsforschung und –behandlung als Ergänzung zur weiterhin vorherrschenden Fokussierung auf Summenscores und übergeordnete Diagnosekriterien

    Identifying and responding to people with mild learning disabilities in the probation service

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    It has long been recognised that, like many other individuals, people with learningdisabilities find their way into the criminal justice system. This fact is not disputed. Whathas been disputed, however, is the extent to which those with learning disabilities arerepresented within the various agencies of the criminal justice system and the ways inwhich the criminal justice system (and society) should address this. Recently, social andlegislative confusion over the best way to deal with offenders with learning disabilities andmental health problems has meant that the waters have become even more muddied.Despite current government uncertainty concerning the best way to support offenders withlearning disabilities, the probation service is likely to continue to play a key role in thesupervision of such offenders. The three studies contained herein aim to clarify the extentto which those with learning disabilities are represented in the probation service, toexamine the effectiveness of probation for them and to explore some of the ways in whichprobation could be adapted to fit their needs.Study 1 and study 2 showed that around 10% of offenders on probation in Kent appearedto have an IQ below 75, putting them in the bottom 5% of the general population. Study 3was designed to assess some of the support needs of those with learning disabilities in theprobation service, finding that many of the materials used by the probation service arelikely to be too complex for those with learning disabilities to use effectively. To addressthis, a model for service provision is tentatively suggested. This is based on the findings ofthe three studies and a pragmatic assessment of what the probation service is likely to becapable of achieving in the near future

    Discovering the hidden structure of financial markets through bayesian modelling

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    Understanding what is driving the price of a financial asset is a question that is currently mostly unanswered. In this work we go beyond the classic one step ahead prediction and instead construct models that create new information on the behaviour of these time series. Our aim is to get a better understanding of the hidden structures that drive the moves of each financial time series and thus the market as a whole. We propose a tool to decompose multiple time series into economically-meaningful variables to explain the endogenous and exogenous factors driving their underlying variability. The methodology we introduce goes beyond the direct model forecast. Indeed, since our model continuously adapts its variables and coefficients, we can study the time series of coefficients and selected variables. We also present a model to construct the causal graph of relations between these time series and include them in the exogenous factors. Hence, we obtain a model able to explain what is driving the move of both each specific time series and the market as a whole. In addition, the obtained graph of the time series provides new information on the underlying risk structure of this environment. With this deeper understanding of the hidden structure we propose novel ways to detect and forecast risks in the market. We investigate our results with inferences up to one month into the future using stocks, FX futures and ETF futures, demonstrating its superior performance according to accuracy of large moves, longer-term prediction and consistency over time. We also go in more details on the economic interpretation of the new variables and discuss the created graph structure of the market.Open Acces

    The potential of shade trees to improve microclimate in coffee production systems and contribute to the protection of coffee yield and quality in a changing climate

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    Climate change is a major challenge to which global coffee production must adapt. With Coffea arabica being especially sensitive to rising temperatures, shade trees present a promising adaptation strategy, as there is some evidence that they can modify microclimate. Employing an interdisciplinary approach, combining biophysical and sociological research, this study investigated the effect of shade on coffee production on the southern slope of Mt. Kilimanjaro with the aim of finding suitable strategies to optimise coffee production systems and ensure optimal yield and quality, thus assuring farmers’ livelihoods into the future, in the face of climate change. Precipitation records from coffee plantations were analysed for changes in weather patterns in the last two decades. The influence of shade on microclimate, leaf temperature, coffee yield and physical quality aspects was assessed in coffee plantations and smallholder systems. Additionally, focus group discussions and interviews with small-scale farmers were conducted to explore farmers’ knowledge on the impacts of weather extremes on coffee production and the ecosystem services different tree species provide. This research shows that climate change at Mt. Kilimanjaro manifests as droughts and shorter wet seasons with less frequent but heavier rainfall events, challenges to which coffee farmers will have to adapt. Shade trees show potential in adaptation of coffee production systems to climate change, as they reduce maximum air temperatures and can reduce leaf temperature extremes during hot periods, without having negative effects on nocturnal temperatures, which are beneficial for coffee production. In coffee plantations, no effect of shade on yields was observed while a slight reduction was observed for smallholder systems. Coffee quality benefits from shade, as different shade components are associated with an increase in bean size and weight. Farmers identified Albizia schimperiana as an important tree species, providing regulatory ecosystem services to improve coffee production. Recommendations need to take farmers’ priorities into account, including their willingness to trade some reduction in coffee production for other services, such as food, fodder or firewood, which were identified as the most important ecosystem services for farmers at Mt. Kilimanjaro

    Development of in-vitro in-silico technologies for modelling and analysis of haematological malignancies

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    Worldwide, haematological malignancies are responsible for roughly 6% of all the cancer-related deaths. Leukaemias are one of the most severe types of cancer, as only about 40% of the patients have an overall survival of 10 years or more. Myelodysplastic Syndrome (MDS), a pre-leukaemic condition, is a blood disorder characterized by the presence of dysplastic, irregular, immature cells, or blasts, in the peripheral blood (PB) and in the bone marrow (BM), as well as multi-lineage cytopenias. We have created a detailed, lineage-specific, high-fidelity in-silico erythroid model that incorporates known biological stimuli (cytokines and hormones) and a competing diseased haematopoietic population, correctly capturing crucial biological checkpoints (EPO-dependent CFU-E differentiation) and replicating the in-vivo erythroid differentiation dynamics. In parallel, we have also proposed a long-term, cytokine-free 3D cell culture system for primary MDS cells, which was firstly optimized using easily-accessible healthy controls. This system enabled long-term (24-day) maintenance in culture with high (>75%) cell viability, promoting spontaneous expansion of erythroid phenotypes (CD71+/CD235a+) without the addition of any exogenous cytokines. Lastly, we have proposed a novel in-vitro in-silico framework using GC-MS metabolomics for the metabolic profiling of BM and PB plasma, aiming not only to discretize between haematological conditions but also to sub-classify MDS patients, potentially based on candidate biomarkers. Unsupervised multivariate statistical analysis showed clear intra- and inter-disease separation of samples of 5 distinct haematological malignancies, demonstrating the potential of this approach for disease characterization. The work herein presented paves the way for the development of in-vitro in-silico technologies to better, characterize, diagnose, model and target haematological malignancies such as MDS and AML.Open Acces

    Socio-endocrinology revisited: New tools to tackle old questions

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    Animals’ social environments impact their health and survival, but the proximate links between sociality and fitness are still not fully understood. In this thesis, I develop and apply new approaches to address an outstanding question within this sociality-fitness link: does grooming (a widely studied, positive social interaction) directly affect glucocorticoid concentrations (GCs; a group of steroid hormones indicating physiological stress) in a wild primate? To date, negative, long-term correlations between grooming and GCs have been found, but the logistical difficulties of studying proximate mechanisms in the wild leave knowledge gaps regarding the short-term, causal mechanisms that underpin this relationship. New technologies, such as collar-mounted tri-axial accelerometers, can provide the continuous behavioural data required to match grooming to non-invasive GC measures (Chapter 1). Using Chacma baboons (Papio ursinus) living on the Cape Peninsula, South Africa as a model system, I identify giving and receiving grooming using tri-axial accelerometers and supervised machine learning methods, with high overall accuracy (~80%) (Chapter 2). I then test what socio-ecological variables predict variation in faecal and urinary GCs (fGCs and uGCs) (Chapter 3). Shorter and rainy days are associated with higher fGCs and uGCs, respectively, suggesting that environmental conditions may impose stressors in the form of temporal bottlenecks. Indeed, I find that short days and days with more rain-hours are associated with reduced giving grooming (Chapter 4), and that this reduction is characterised by fewer and shorter grooming bouts. Finally, I test whether grooming predicts GCs, and find that while there is a long-term negative correlation between grooming and GCs, grooming in the short-term, in particular giving grooming, is associated with higher fGCs and uGCs (Chapter 5). I end with a discussion on how the new tools I applied have enabled me to advance our understanding of sociality and stress in primate social systems (Chapter 6)
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