A new dual-boron-cored luminogen ligated with a nitrogen-containing multidentate ligand and four bulky phenyl rings was readily synthesized. The unique molecular structure endows this BN-containing luminogen with rich photophysical properties in either solution or in the solid state, including a large Stokes shift, aggregation induced emission activity and reversible piezochromism. Furthermore, this BN-containing luminogen exhibits good capabilities for imaging living cells and sensing of fluoride anions.

Signed language interpreting in South Africa has not received much academic attention, despite the profession having undergone major transformation since the advent of democracy. This study aims to create a better understanding of signed language interpreters’ behaviour in one specific setting in South Africa – post-secondary education. During the researcher’s own practice as an educational interpreter at a post-secondary institution, she experienced role conflict and found little information available to assist her in making professional decisions on which direction to take. This provided the impetus to embark on this research. The study begins by outlining the field of liaison interpreting and educational interpreting, and examining the existing literature regarding the interpreter’s role and norms in interpreting. It then goes on to examine authentic interpreted texts, filmed in actual lectures in post-secondary settings. These texts are analysed with reference to interpreter shifts and deviations from the source text, with particular focus on interpreter-generated utterances (additions), borrowing (fingerspelling), omissions (both errors and conscious choice) and various types of collaboration between the interpreter and primary participants. These shifts are examined in more detail to explore whether they indicate any change in the interpreter’s role. Further, interpreters’ own views about their practice, elicited from individual interviews, enable the reader to understand how the interpreters view the role(s) that they fulfil. The research will provide information for interpreter trainers about the roles assumed by SASL interpreters in higher education and provide a platform from which to scaffold future educational interpreter research and training. / Linguistics and Modern Languages / M.A. (Linguistics)

Ein großer Anteil des Datenverkehrs in „Internet Service Provider“ (ISP)-Netzen wird heutzutage von „Content Delivery Networks“ (CDNs) verursacht. Betreiber von CDNs verwenden Lastverteilungsmechanismen um die Auslastung ihrer CDN-Infrastruktur zu vergleichmäßigen (Load Balancing). Dies geschieht ohne Abstimmung mit den ISP-Betreibern. Es können daher große Verkehrslastverschiebungen sowohl innerhalb eines ISP-Netzes, als auch auf den Verbindungsleitungen zwischen ISP-Netz und CDNs auftreten. In der vorliegenden Arbeit wird untersucht, welche nicht-kooperativen Möglichkeiten ein ISP hat, um Verkehrslastverschiebungen, welche durch Lastverteilungsmechanismen innerhalb eines CDNs verursacht werden, entgegenzuwirken bzw. abzumildern. Die Grundlage für diese Untersuchung bildet die Analyse des Serverauswahlverhaltens des YouTube-CDNs. Hierzu ist ein aktives Messverfahren entwickelt worden, um das räumliche und zeitliche Verhalten der YouTube-Serverauswahl bestimmen zu können. In zwei Messstudien wird die Serverauswahl in deutschen und europäischen ISP-Netzen untersucht. Auf Basis dieser Studien wird ein Verkehrsmodell entwickelt, welches die durch Änderungen der YouTube-Serverauswahl verursachten Verkehrslastverschiebungen abbildet. Das Verkehrsmodell wiederum bildet die Grundlage für die Bestimmung optimaler Routen im ISP-Netz, welche hohe Robustheit gegenüber CDN-bedingte Verkehrslastverschiebungen aufweisen (Alpha-robuste Routingoptimierung). Für die Lösung des robusten Routing-Optimierungsproblems wird ein iteratives Verfahren entwickelt sowie eine kompakte Reformulierung vorgestellt. Die Leistungsfähigkeit des Alpha-robusten Routings wird anhand von drei Beispielnetztopologien untersucht. Das neue Verfahren wird mit alternativen robusten Routingverfahren und einem nicht-robusten Verfahren verglichen. Neben der robusten Routingoptimierung werden in der Arbeit drei weitere Ideen für nicht-kooperative Methoden vorgestellt (BGP-, IP-Präix- und DNS-basierte Methode), um CDN-bedingten Verkehrslastverschiebungen entgegenzuwirken.

Ethiopia is one of the sub-Saharan Africa countries whose energy depends on traditional use of biomass such as wood, charcoal, agricultural residues and animal dung. The traditional use of biomass mainly wood and charcoal leads the country to massive deforestation and forest degradation. Negative environmental impacts from poorly managed municipal solid waste are also serious problems in the country. Moreover, there is a wide range of fossil fuels demand in the country fully covered by importing which results to a significant expenditure from the country’s budget. This study investigates the long-term shifts in bioenergy use of the country and evaluates the expected social, environmental and economical implications. For this purpose, three scenarios are formulated within a timeframe that goes from 2013 to 2030. The baseline scenario assumes the existing energy practices of the country would undergo no significant change in the future while the moderate shift and high shift scenarios consider the long-term shifts in bioenergy use with and without considering constraints respectively. In this context, long-term shifts means: transition from traditional use of biomass to efficient and modern in the household sector, biofuels deployment in the transport sector, introduction of agricultural residues as a fuel for cement production, and electricity generation from bagasse and municipal solid waste. To model and analyze the scenarios, the long-range energy alternatives planning system (LEAP) software tool is used. Taking the results of high shift scenario by 2030, the use of improved wood stoves and fuel switch stoves could save 65 million tons of wood. The foreign currency saving from using biofuels and agricultural residues as fossil fuels substitute would reach to 674 million USD. The greenhouse gas emissions reduction is equivalent to 46 million tons of CO2e which is about 18.4% of the CO2e abatement target of the country for 2030. The corresponding revenue from carbon trading schemes would reach to 231 million USD. Electricity generation from bagasse and municipal solid waste would be 3,672 GWh that is around 3.7% of the total electricity generation target for 2030.

Problem statement: Accurate and reliable forecasts of trends in the housing market can be useful information for market participants as well as policy makers. This information may be useful to minimize risk related to market uncertainty. Since the burst of the housing bubble in the early 1990s the price level of single-family houses has risen sharply in Sweden. The Swedish housing market has experienced an unusually long period of high growth rates in transaction prices which has opened up for discussions about the risk of another housing bubble. Business and property cycles have shown to contain asymmetries, which linear models are unable to pick up and therefore inappropriate to analyze cycles. Approach: Therefore, this study uses non-linear models which are able to pick up the asymmetries. The estimated models are variations of the Markov-switching regression model, i.e. the Markov-switching autoregressive (MS-AR) model and the Markov-switching dynamic regression (MS-DR) model. Results: Our ndings show that the MS-AR(4) model allowing for varying variance across regimes estimated using the growth rate of FASTPI produce superior forecasts over other MSAR models as well as variations of the MS-DR model. The average expected duration to remain in a positive growth regime is between 6.3 and 7.3 years and the average expected duration to remain in a negative growth regime is between 1.2 to 2.5 years. Conclusion: The next regime shift in the Swedish housing market is projected to occur between 2018 and 2019, counting the contraction period in 2012 as the most recent negative regime. Our ndings support other studies ndings which indicate that the longer the market has remained in one state, the greater is the risk for a regime shift. / Problemformulering: Noggranna och tillforlitliga prognoser om utvecklingen pa bostadsmarknaden kan vara anvandbar information for marknadsaktorer samt beslutsfattare. Denna information kan vara anvandbar for att minimera risken relaterad till osakerheten pa marknaden. Sen bostadsbubblan sprack i borjan av 1990-talet har prisnivan for smahus okat kraftigt i Sverige. Den svenska bostadsmarknaden har upplevt en ovanligt lang period av hog tillvaxt i transaktionspriser som har oppnat upp for diskussioner om risken for en ny bostadsbubbla. Konjunkturoch fastighetscykler har visat sig innehalla asymmetrier som linjara modeller inte kan uppfanga och darfor visat sig vara olampliga for att analysera cykler. Tillvagagangssatt: Darfor anvander den har studien icke-linjara modeller som kan uppfanga dessa asymmetrier. De skattade modellerna ar variationer av Hamiltons Markov-switchingmodell, dvs. en autoregressiv Markov-switchingmodell (MS-AR) och en dynamisk Markov-switchingmodell (MS-DR). Resultat: Resultatet visar att MS-AR(4)-modellen som tar hansyn till varierande varians over regimerna estimerad med tillvaxten av FASTPI producerar overlagsna prognoser jamfort med andra MS-AR-modeller samt variationer av MS-DR-modellen. Den genomsnittliga forvantade varaktigheten att benna sig i en positiv regim ar mellan 6,3 och 7,3 ar och den  genomsnittliga forvantade varaktigheten att benna sig i en negativ regim ar mellan 1,2 till 2,5 ar. Slutsats: Nasta regimskifte pa den svenska bostadsmarknaden beraknas ske mellan 2018 och 2019, antaget att nedgangen under 2012 ar den senaste negativa regimen. Resultatet stodjer tidigare studier, som tyder pa att ju langre marknaden har varit i ett tillstand, desto storre ar risken for ett regimskifte.

The aim of this Master Thesis is to present an annotated translation of the first chapter of the novel Die Waffen nieder! (1889) from Bertha von Suttner that is presently functional. The novel was already translated under the title Odzbrojte! (1896). The first part of this Master Thesis contains the Czech translation of the first chapter from the novel itself. The second part, which is a translation commentary, divided into subchapters. The beginning of the translation commentary explains the choice of the original text and presents a detailed translation analysis. The next part of the translation commentary contains information about the strategy of solving translation problems, translation shifts and collaborative translation. Key Words: Bertha von Suttner, Die Waffen nieder!, Lay Down Your Arms!, translation analysis, translation commentary, translation problems, translation shifts

Certaines lignées de plantes tendent à rester dans le même biome au cours du temps (conservatisme de biome), tandis que d’autres semblent s’adapter plus facilement à de nouveaux biomes (changements de biome). Les ~396 espèces (14 genres) de la sous-famille des Cercidoideae se retrouvent dans plusieurs biomes à travers le monde, en particulier dans les régions tropicales de l’Amérique du Sud, de l’Asie et de l’Afrique. Ces espèces diffèrent aussi au niveau de leur port, pouvant être des arbres, arbustes, lianes ou herbacées. Après avoir établi une liste révisée d’espèces de la sous-famille, incluant tous les synonymes connus et leurs noms acceptés, des données d’occurrence ont été téléchargées depuis le Global Biodiversity Information Facility (GBIF) et d’autres bases de données d’herbiers. Après avoir nettoyé les données d’occurrences, des cartes de répartition des espèces ont été produites. Ces cartes ont été comparées avec des cartes publiées de biomes tropicaux afin d’attribuer chaque espèce à un biome et à un continent. Les biomes de forêt tropicale humide (179 espèces), de savane (117 espèces), succulent (65 espèces) et tempéré (7 espèces et sous-espèces) ont été identifiés comme importants pour décrire la répartition globale des Cercidoideae, avec plusieurs espèces se trouvant dans plus d’un biome. Après avoir reconstruit une phylogénie calibrée dans le temps, nous avons effectué des estimations de caractères ancestraux afin d’évaluer le nombre et la direction des changements de biome, de port et de continent. Les analyses suggèrent que plusieurs changements de biomes ont eu lieu dans l’histoire évolutive de la sous-famille, les changements du biome succulent à la forêt tropicale humide et de la forêt tropicale humide à la savane étant les plus communs, tandis qu’il n’y avait aucun changement depuis la savane. Sept changements de port ont eu lieu, dont trois qui sont associés à des changements de biome (un est caractéristique du genre Tylosema (Schweinf.) Torre & Hillc., un du genre Lysiphyllum (Benth.) de Wit et un de l’espèce Phanera retusa Benth.). Les analyses montrent aussi que les changements de biomes tendent à avoir lieu au sein d’un même continent et que les dispersions vers de nouveaux continents tendent à se produire au sein d’un même biome. Par contraste avec d’autres sous-familles de légumineuses plus conservées au niveau des biomes, les changements fréquents observés au sein des Cercidoideae suggèrent une capacité d’adaptation à des environnements significativement différents à travers le temps. / Some plant lineages remain within the same biome over time (biome conservatism), whereas others seem to adapt more easily to new biomes (biome shifts). The ~396 species (14 genera) in subfamily Cercidoideae of Leguminosae (Fabaceae) are found in many biomes around the world, particularly in the tropical regions of South America, Asia and Africa, and display a variety of habits/growth forms (small trees, shrubs, lianas and herbs). After establishing an updated expert-verified species list, including all known synonyms and their accepted names, we downloaded and cleaned occurrence records from the Global Biodiversity Information Facility (GBIF) and other herbarium databases to produce species distribution maps. These maps were compared with existing biome maps to attribute species to biomes and continents. Rainforest (179 species), savanna (117 species), succulent (65 species) and temperate (7 species and subspecies) biomes were found to be important in describing the global distribution of Cercidoideae, with many species occurring in multiple biomes. After reconstructing a time-calibrated phylogeny, we performed ancestral state reconstructions to evaluate the number and direction of shifts in biome, habit and continents. Analyses suggest multiple biome shifts throughout the phylogeny, shifts from succulent to rainforest and from rainforest to savanna being the most common, while no shifts were observed from the savanna. Seven shifts in habit occurred, of which at least three were associated with biome shifts (one subtends the genus Tylosema (Schweinf.) Torre & Hillc., one subtends the genus Lysiphyllum (Benth.) de Wit and one occurs in Phanera retusa Benth.). Analyses also show that biome shifts tend to occur within the same continent and that dispersals to new continents tend to occur within the same biome. In contrast to other more biome-conserved legume subfamilies, the frequent shifts observed in Cercidoideae suggest ability for adaptation to significantly different environments through time.

[pt] As estruturas civis durante toda a sua vida útil estão sujeitas a diversas ações de deterioração, desgastes ou corrosão de seus membros, que podem gerar variações em suas características físicas. Estas ações podem causar danos ao seu funcionamento, podendo chegar até ao colapso, em casos mais extremos. Além disso, o avanço tecnológico que permite a concepção de estruturas cada vez mais esbeltas, e que geram assim possíveis vibrações excessivas, elevam o monitoramento estrutural a um patamar de extrema importância e atenção na ótica dos gestores desses sistemas. Particularmente, no caso de obras de infraestrutura como pontes e passarelas, as grandes dimensões são características significativas que tornam as práticas de monitoramento e inspeção mais difíceis. Dessa forma, com o objetivo auxiliar no monitoramento estrutural e direcionar inspeções visuais, diversos métodos de identificação de danos são estudados com base nas características dinâmicas das estruturas, como as frequências naturais e os modos de vibração. A revisão de literatura, porém, demonstra que há uma dificuldade na aplicação desta identificação em estruturas mais complexas de grande porte. Assim, este trabalho visa estudar esta dificuldade e propor uma solução baseada na construção de um índice, composto pelos modos de vibração. Além disso, através da aplicação de algoritmos de aprendizado de máquina e de reconhecimento de padrões, como as Redes Neurais Artificiais (RNAs), propõese aumentar a eficiência do processo de localização espacial e quantificação dos danos. Em seguida, a metodologia proposta é, então, aplicada em um modelo de passarela metálica inspirado em uma estrutura real presente na região do Terminal Centro Olímpico da cidade do Rio de Janeiro – RJ. A identificação de danos é estudada através da aplicação do índice proposto, incorporando as redes neurais e avaliando do impacto da variação dos parâmetros da RNA na eficiência global da detecção. / [en] Civil structures are subjected to different deterioration and corrosion actions throughout their entire service life, which can generate variations in their physical characteristics. These actions can cause damage to its functioning, and possibly leading to collapse in more severe cases. In addition, technology development which allows the design of increasingly slender structures, can produce excessive vibrations, which elevates the importance ofstructural monitoring to a higher level from the perspective of infrastructure managers. Particularly, in the case of bridges and walkaways, due to their large dimensions make monitoring and inspection even more difficult. Thus, with the aim of providing methods to assist in structural monitoring and facilitate visual inspections, several damage identification methods are investigated, which are based on structures dynamic characteristics, such as natural frequencies and mode shapes. The conducted literature review revealed that there is a difficulty in applying these identification methods in large-scale and complex structures. Thus, this research aims to study these barriers and propose a solution based on the development of a new damage index based on the structure s mode shapes. Furthermore, through the application of machine learning algorithms and pattern recognition, such as Artificial Neural Networks (ANN), it is proposed to increase the efficiency of the damage identification and quantification process. Then, the proposed methodology is tested numerically on a steel footbridge model inspired by a real structure located in the region of the Olympic Center Terminal, in the city of Rio de Janeiro – RJ. The damage identification method is studied through the application of the proposed damage index, incorporating the neural network and assessing the impact of ANNs parameters variation in the global efficiency of the damage detection method.

[pt] A teoria moderna de carteiras estabelece que a alocação ótima de ativos é uma função da média-variância da distribuição dos retornos. Na prática, estes retornos são modelados por distribuições Gaussianas e seus parâmetros são estimados a partir dos dados históricos do mercado, utilizando técnicas descritivas da estatística Frequentista. A dinâmica atual dos mercados globalizados gera períodos aleatórios de alta e baixa volatilidade e/ou saltos nos retornos dos ativos, provocando mudanças de regime ou quebras estruturais na série temporal dos retornos, tornando-os não Gaussianos. Consequentemente, a teoria moderna de carteiras precisa ser adaptada para atender a estas novas condições do mercado. Para contornar o problema das mudanças de regime, propõe-se a substituição do mecanismo de otimização baseada no índice de Sharpe pela otimização baseada na medida Ômega. Isto porque a medida Ômega tem a vantagem de quantificar o risco-retorno de qualquer distribuição de probabilidade e não somente distribuições Gaussianas como acontece com o índice de Sharpe, ou seja, as distribuições de retornos não Gaussianos provocadas pelas mudanças de regime são tratadas naturalmente pela medida Ômega. Para contornar o problema das quebras estruturais, propõe-se a substituição do procedimento de estimação dos parâmetros da distribuição dos retornos, baseada em técnicas da estatística Frequentista por técnicas da estatística Bayesiana. Isto porque a estatística Bayesiana, tem a vantagem de combinar as informações públicas do mercado (dados históricos dos retornos) com informações privadas do investidor (visões prospectivas do mercado) permitindo corrigir a quebra estrutural e, na sequência, tratar o retorno não Gaussiano, utilizando o mecanismo de otimização baseada na medida Ômega. / [en] Modern portfolio theory states that the optimal asset allocation is a function of the mean-variance of the distribution of returns. In practice, these returns are modeled by Gaussian distributions and their parameters are estimated from historical market data, using descriptive techniques of Frequentist statistics. The current dynamics of globalized markets generate random periods of high and low volatility and/or jumps in asset returns, causing regime shifts or structural breaks in the time series of returns, making them non Gaussian. Consequently, modern portfolio theory needs to be adapted to meet these new market conditions. To circumvent the problem of regime shifts, it is proposed to replace the optimization mechanism based on the Sharpe index by the optimization based on the Omega measure. This is because the Omega measure has the advantage of quantifying the risk-return of any probability distribution and not only Gaussian distributions as with the Sharpe index, that is, non Gaussian returns distributions caused by regime shifts are treated naturally by the Omega measure. To circumvent the problem of structural breaks, it is proposed to replace the estimation procedure for the parameters of the distribution of returns, based on Frequentist statistics techniques, by Bayesian statistical techniques. This is because the Bayesian statistic has the advantage of combining public market information (historical return data) with private investor information (prospective market views) allowing to correct the structural break, and subsequently, treating the non Gaussian return using the optimization based on the Omega measure.

<p dir="ltr">Data is collected everywhere in our world; however, it often is noisy and incomplete. Different sources of data may have different characteristics, quality levels, or come from dynamic and diverse environments. This poses challenges for both humans who want to gain insights from data and machines which are learning patterns from data. How can we leverage the diversity of data across domains to enhance our understanding and decision-making? In this thesis, we address this question by proposing novel methods and applications that use multiple domains as more holistic sources of information for both human and machine learning tasks. For example, to help human operators understand environmental dynamics, we show the detection and localization of distribution shifts to problematic features, as well as how interpretable distributional mappings can be used to explain the differences between shifted distributions. For robustifying machine learning, we propose a causal-inspired method to find latent factors that are robust to environmental changes and can be used for counterfactual generation or domain-independent training; we propose a domain generalization framework that allows for fast and scalable models that are robust to distribution shift; and we introduce a new dataset based on human matches in StarCraft II that exhibits complex and shifting multi-agent behaviors. We showcase our methods across various domains such as healthcare, natural language processing (NLP), computer vision (CV), etc. to demonstrate that learning from data across domains can lead to more faithful representations of data and its generating environments for both humans and machines.</p>