Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study

Background: Widespread lasting functional connectivity (FC) and brain volume changes in cortices and subcortices after premature birth have been researched in recent studies. However, the relationship remains unclear between spontaneously slow blood oxygen dependent level (BOLD) fluctuations and gray matter volume (GMV) changes in specific brain areas, such as temporal insular cortices, and whether classification methods based on MRI could be successfully applied to the identification of preterm individuals. In this thesis I hypothesized that in prematurely born adults 1. Ongoing neural excitability and brain activity, as estimated by regional functional connectivity of resting state functional MRI (rs-fMRI) is accompanied with altered low-frequency fluctuations and neonatal complications; 2. Altered regional functional connectivity is connected with superimposed cerebral structural reductions; and 3. multivariate neuroanatomical and functional brain patterns could be treated as features to identify preterm subjects from term subjects individually. Methods: To investigate these hypotheses, the principal results of structural alterations were measured with voxel-based morphometry (VBM), while rs-fMRI outcomes were estimated with amplitude of low-frequency fluctuations (ALFF) in analysis with ninety-four very preterm/very low birth weight (VP/VLBW) and ninety-two full-term (FT) born young adults. Results: The results of the thesis support the hypotheses by showing that, in univariate results, first in VP/VLBW grownups, ALFF was decreased in the left lateral temporal cortices no matter with global signal regression, and this reduction was closely associated with neonatal complications and cognitive variables. Second overlapped brain regions were found between reduced ALFF and reduced brain volumes in the left temporal cortices, and positively associated with each other, demonstrating a potential relationship between VBM and ALFF in this brain area. In multimodal multivariate pattern recognition analysis (MVPA), the gray matter volume (GMV) classifier displayed a higher accuracy (80.7%) contrast with the ALFF classifier (77.4%). The late fusion of GMV and ALFF did not outperform single GMV modality classification by reaching 80.4% accuracy. Moderator analysis from both rs-fMRI and structural MRI (sMRI) uncovered that the neuro-prematurity performance was predominantly determined by neonatal complications. Conclusions: In conclusion, these outcomes exhibit the long term effects of premature labour on lateral temporal cortices, which changed in both ongoing BOLD fluctuations and decreased cerebral structural volumes. This thesis further provided evidence that multivariate pattern analysis such as support vector machine (SVM) may identify imaging-based biomarkers and reliably detect signatures of preterm birth

A Developmental Model of Trust in Humanoid Robots

Trust between humans and artificial systems has recently received increased attention due to the widespread use of autonomous systems in our society. In this context trust plays a dual role. On the one hand it is necessary to build robots that are perceived as trustworthy by humans. On the other hand we need to give to those robots the ability to discriminate between reliable and unreliable informants. This thesis focused on the second problem, presenting an interdisciplinary investigation of trust, in particular a computational model based on neuroscientific and psychological assumptions. First of all, the use of Bayesian networks for modelling causal relationships was investigated. This approach follows the well known theory-theory framework of the Theory of Mind (ToM) and an established line of research based on the Bayesian description of mental processes. Next, the role of gaze in human-robot interaction has been investigated. The results of this research were used to design a head pose estimation system based on Convolutional Neural Networks. The system can be used in robotic platforms to facilitate joint attention tasks and enhance trust. Finally, everything was integrated into a structured cognitive architecture. The architecture is based on an actor-critic reinforcement learning framework and an intrinsic motivation feedback given by a Bayesian network. In order to evaluate the model, the architecture was embodied in the iCub humanoid robot and used to replicate a developmental experiment. The model provides a plausible description of children's reasoning that sheds some light on the underlying mechanism involved in trust-based learning. In the last part of the thesis the contribution of human-robot interaction research is discussed, with the aim of understanding the factors that influence the establishment of trust during joint tasks. Overall, this thesis provides a computational model of trust that takes into account the development of cognitive abilities in children, with a particular emphasis on the ToM and the underlying neural dynamics.THRIVE, Air Force Office of Scientific Research, Award No. FA9550-15-1-002

Essay in Economics, Political Economy and Climate Transition

In this study, we investigate the impact of climate-related events on listed companies and their stock performance. Our focus is on the major historical greenhouse gas emitters of four different sectors (fossil fuel, transportation, automobile, and financial). We analyze the effect of climate-related events, such as natural disasters caused by human actions, climate global strikes and speeches by Greta Thunberg, on the daily abnormal returns of these companies. The results suggest that, firstly, climate-related events can result, on average, in cumulative abnormal negative returns for those companies in these sectors compared to the renewable energy sector, used as the benchmark for the green sector. Second, for some of these companies, reputation risk may be reduced by high environmental pillar scores that are not perfectly aligned with environmental performances (i.e. GHG emissions). We then assess the impact of climate sentiment on short-term stock market performance, as measured by abnormal returns, finding a positive correlation between the climate-related social media talks and cumulative abnormal returns. To conclude, external events, including climate-related rallies and speeches, are correlated with negative abnormal stock returns in line with investor expectations.In this paper we analyse how health system endowment and the quality of institutions impact perceptions towards taxation. We conduct a sentiment analysis of Twitter users’ tweets to determine whether the impact of the Covid-19 health emergency has modified the attitudes of the citizens towards taxation in the four largest European countries: France, Germany, Italy and Spain. We use a difference-in-differences estimation strategy, comparing the average sentiments of individual tweets regarding taxation in different European NUTS-2 regions, before and after the spread of the Covid-19 pandemic. Our results highlight that in regions characterised by higher health system endowment people adopted more positive attitudes towards taxation with respect to those living in regions with low levels of health system endowment over the period -. In addition, we show how higher quality institutions led to more positive perceptions in relative and absolute terms, suggesting a greater predisposition for a more progressive tax system.Lobbying can help policy makers access relevant sector-specific information and make in- formed decisions. However, lobbying can also harm economic welfare if it successfully persuades policy makers to impose unnecessary regulations or maintain excessive market barriers. This study examines the relationship between lobbying expenditures, the environmental policy stringency regulation, firm-level green innovation and environmental reputation. Using a sample of 590 firms from 43 countries across 98 industries, we analyze firm-level financial and environmental data from the period of 2012 to 2020. Our results show that highly green innovative firms tend to spend more on lobbying, and that lobbying expenditures are negatively associated with environmental performance. We also find that environmental policy stringency has a positive impact on corporate environmental performance, while innovation and other factors have mixed effects. Our study contributes to the growing literature on the intersection of political economy, innovation, and climate transition

New Pathways to support social-ecological Systems in Change

Klimawandel und Biodiversitätsverlust sowie Verstädterung und demografischer Wandel haben tiefgreifende Auswirkungen auf Städte und ihre Ökosysteme und damit auf die Lebensbedingungen der Mehrheit der Menschheit. Die Geschwindigkeit des Wandels und die Dringlichkeit der Folgen macht Umweltmonitoring zu einem potentiell interessanten Tool für nachhaltige und resiliente Stadtentwicklung. Der erste Artikel gibt einen Überblick über den aktuellen Stand der Fernerkundung in Bezug auf Stadtökologie und zeigt, dass Fernerkundung relevant für nachhaltige Stadtplanung ist. Es bestehen jedoch bestehen Mängel, da viele Studien nicht direkt umsetzbar sind. Der zweite Artikel zeigt, dass eine wachsende Stadt Möglichkeiten für den Ausbau der grünen Infrastruktur bieten kann. Im dritten Artikel wird untersucht, wie sich die städtische Dichte auf die Bereitstellung von Ökosystemdienstleistungen der grünen Infrastruktur auswirkt. Es wird gezeigt, dass eine hohe Siedlungsdichte nicht zwangsläufig zu einem geringeren Biodiversitätspotenzial oder einer geringeren Kühlkapazität führt. Allerdings sind dicht bebaute Gebiete mit geringer Vegetationsbedeckung besonders auf grüne Infrastruktur angewiesen. Der vierte Artikel befasst sich mit der Frage, wie naturbasierte Lösungen durch eine bessere Vernetzung der Beteiligten gestärkt werden können. Auf der Grundlage einer gezielten Literaturrecherche über Informationstechnologie zur Unterstützung sozial-ökologischer Systeme wird ein Instrument zur Entscheidungshilfe entwickelt. Dieses kombiniert ökologische und soziale Indikatoren, um Klimawandeladaption in Übereinstimmung mit den sozio-ökologischen Bedingungen entwickeln zu können. Der fünfte Artikel bietet eine grundsätzliche Perspektive zur Unterstützung der städtischen Nachhaltigkeit, die auf dem ökologischen-Trait Konzept basiert. Zusammen bieten die fünf Artikel Wege für die Fernerkundungswissenschaft und die angewandte Raumplanung für nachhaltige und resiliente Entwicklungen in Städten.Climate change and biodiversity loss, as well as urbanisation and demographic change, are major global challenges of the 21st century. These trends have profound impacts on cities and their ecosystems and thus on the living conditions of the majority of humanity. This raises the need for timely environmental monitoring supporting sustainable and resilient urban developments. The first article is an overview of the state of the art of remote sensing science in relation to urban ecology. The review found that remote sensing can contribute to sustainable urban policy, still insufficiencies remain as many studies are not directly actionable. The second article shows that a growing city can provide opportunities for an increase in green infrastructure. Here, remote sensing is used for long-term analysis of land-use in relation to urban forms in Berlin. The third article examines how urban density affects ecosystem service provision of urban green infrastructure. It is shown that residential density does not necessarily lead to poor biodiversity potential or cooling capacity. However, dense areas with low vegetation cover are particularly dependent on major green infrastructure. The fourth article explores ways to reinforce nature-based solutions by better connecting and informing stakeholders. Based on a focussed literature review on information technology supporting urban social-ecological systems, a decision support tool is developed. The tool combines indicators based on ecological diversity and performance with population density and vulnerability. This way, climate change adaptation can be developed in accordance with socio-ecological conditions. The concluding fifth article offers an outlook on a larger framework in support of urban sustainability, based on the ecological trait concept. Together the five research papers provide pathways for urban remote sensing science and applied spatial planning that can support sustainable and resilient developments in cities