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Reducing costs for DNA and RNA sequencing by sample pooling using a metagenomic approach
No full textDNA and RNA sequencing are widely used techniques to investigate genomic modifications and gene expression. The costs for sequencing dropped dramatically in the last decade. However, due to material and labor intense steps, the sample preparation costs could not keep up with that pace. About 80% of the total costs occur prior to sequencing during DNA/RNA extraction, enrichment steps and subsequent library preparation. In this study, we investigate the potential of pooling different organisms samples prior to DNA/RNA extraction to significantly reduce costs in preparative steps. Similar to the common procedure of ligated DNA tags to pool (c)DNA samples, sequence diversity of different organisms intrinsically provide unique sequences that allow separation of reads after sequencing. With this approach, sample pooling can occur before DNA/RNA isolation and library preparation. We show that pooled sequencing of three related bacterial organisms is possible without loss of data quality at a cost reduction of approx. 50% in DNA- and RNA-seq approaches. Furthermore, we show that this approach is highly efficient down to the level of a shared genus and is, therefore, widely applicable in sequencing facilities and companies with diverse sample pools.Gefördert durch den Open-Access-Publikationsfonds der UB Marburg
Temporal recalibration in response to delayed visual feedback of active versus passive actions: an fMRI study
No full textThe brain can adapt its expectations about the relative timing of actions and their sensory outcomes in a process known as temporal recalibration. This might occur as the recalibration of timing between the sensory (e.g. visual) outcome and (1) the motor act (sensorimotor) or (2) tactile/proprioceptive information (inter-sensory). This fMRI recalibration study investigated sensorimotor contributions to temporal recalibration by comparing active and passive conditions. Subjects were repeatedly exposed to delayed (150 ms) or undelayed visual stimuli, triggered by active or passive button presses. Recalibration effects were tested in delay detection tasks, including visual and auditory outcomes. We showed that both modalities were affected by visual recalibration. However, an active advantage was observed only in visual conditions. Recalibration was generally associated with the left cerebellum (lobules IV, V and vermis) while action related activation (active > passive) occurred in the right middle/superior frontal gyri during adaptation and test phases. Recalibration transfer from vision to audition was related to action specific activations in the cingulate cortex, the angular gyrus and left inferior frontal gyrus. Our data provide new insights in sensorimotor contributions to temporal recalibration via the middle/superior frontal gyri and inter-sensory contributions mediated by the cerebellum.Gefördert durch den Open-Access-Publikationsfonds der UB Marburg
Nitren-Vermittelte Asymmetrische C-H Funktionalisierungen mit Chiralen Rutheniumkomplexen
No full textTransition metal catalysis is a common tool for the synthesis of enantioenriched compounds and has been well-established in organic chemistry. Nitrene chemistry, a “hot area” in recent years, has proven to be very efficient in introducing C-N bonds due to the high value of amine-containing scaffolds in various functional materials, natural products, and pharmaceuticals. This thesis presents novel catalytic asymmetric transformations mediated by a ruthenium nitrene intermediate and the synthesis as well as modification of new ruthenium complexes.Die Übergangsmetallkatalyse ist ein gängiges Werkzeug zur Synthese enantiomeren-angereicherter Verbindungen und hat sich in der organischen Chemie gut etabliert. Die Nitrenchemie, welche in den letzten Jahren einen immer größeren Stellenwert eingenommen hat, hat sich aufgrund des hohen Werts aminhaltiger Grundgerüste in verschiedenen Funktionsmaterialien, Naturprodukten und Pharmazeutika als sehr effizient bei der Einführung von C-N-Bindungen erwiesen. Diese Arbeit präsentiert die Entwicklung und Modifikation neuartiger Rutheniumkomplexe und deren Anwendung in katalytischen asymmetrischen Transformationen, die als Schlüsselintermediat ein Ruthenium-Nitren-Spezies aufweisen
Model-Driven Optimization with a Focus on the Effectiveness and Efficiency of Evolutionary Algorithms
No full textOptimization problems are ubiquitous in software engineering. They arise, for example, when searching for a modular software design or planning a cost-efficient development process. Search-based software engineering (SBSE) is concerned with solving optimization problems by applying search-based algorithms. Among the most popular are evolutionary algorithms, which are the focus of this thesis. Following the example of natural evolution, they use selection, mutation, and crossover operators to evolve existing solutions.
In the hope of enabling the use of SBSE without optimization expertise, model-driven optimization (MDO) relies on model-driven engineering (MDE); models and model transformations are used to specify optimization problems and solution algorithms. Two ways of representing solutions, the model-based approach (MB-MDO) and the rule-based approach, have established. However, the implications of choosing one over the other are not clear. Therefore, we compare both approaches qualitatively and quantitatively and pursue MB-MDO as the more promising approach in the rest of the thesis.
How to design efficient and effective evolutionary algorithms is a central question in MB-MDO. Moreover, how to perform crossover there is not yet known. We first present a framework that highlights and explains the core concepts of evolutionary algorithms in MB-MDO and formalizes them based on graph transformation theory. It not only contributes to the understanding of evolutionary algorithms in MB-MDO, but in particular facilitates their precise specification, analysis, and evaluation. The framework is used to define important properties of mutation operators and to evaluate their impact on the efficiency and effectiveness of evolutionary algorithms. Furthermore, a general, graph-based approach for the construction of crossover operators in MB-MDO is presented. The general approach is also concretized for the Eclipse Modeling Framework (EMF). Finally, an evaluation of a prototypical implementation shows the relevance of crossover operators for evolutionary algorithms in MB-MDO.Optimierungsprobleme sind in der Softwareentwicklung allgegenwärtig. Sie treten beispielsweise bei der Suche nach einem modularen Softwaredesign oder der Planung eines kosteneffizienten Entwicklungsprozesses auf. Die suchbasierte Softwaretechnik (SBSE, von engl. search-based software engineering) befasst sich mit der Lösung von Optimierungsproblemen durch Anwendung suchbasierter Optimierungsverfahren. Zu den beliebtesten gehören evolutionäre Algorithmen, die im Mittelpunkt dieser Arbeit stehen. Angelehnt an die natürliche Evolution werden bei diesen Selektions-, Mutations- und Kreuzungoperatoren verwendet, um bestehende Lösungen weiterzuentwickeln.
In der Hoffnung, den Einsatz von SBSE ohne tiefere Optimierungskenntnisse zu ermöglichen, setzt die modellgetriebene Optimierung (MDO, von engl. model-driven optimization) auf modellgetriebene Entwicklung (MDE, von engl. model-driven engineering); Modelle und Modelltransformationen werden zur Spezifikation von Optimierungsproblemen und Lösungsalgorithmen herangezogen. Dabei haben sich zwei Arten Lösungen zu repräsentieren etabliert, der modellbasierte (MB-MDO, von engl. model-based MDO) und der regelbasierte Ansatz. Es ist jedoch nicht klar, welche Auswirkungen die Entscheidung für den einen oder anderen Ansatz hat. Daher vergleichen wir beide Ansätze sowohl qualitativ als auch quantitativ und verfolgen im weiteren Verlauf der Arbeit MB-MDO als den vielversprechenderen Ansatz.
Wie sich effiziente und effektive evolutionäre Algorithmen entwickeln lassen, ist in MB-MDO eine zentrale Frage. Darüberhinaus ist dort noch kein Ansatz zur Umsetzung von Kreuzungsoperatoren bekannt. Wir stellen zunächst ein Framework vor, welches die Kernkonzepte evolutionärer Algorithmen in MB-MDO herausstellt, erklärt und diese auf Grundlage der Graphentransformationstheorie formalisiert. Es trägt damit nicht nur zum Verständnis evolutionärer Algorithmen in MB-MDO bei, sondern ermöglicht insbesondere deren präsize Spezifikation, Analyse und Evaluation. Mit Hilfe des Frameworks werden zwei wichtige Eigenschaften von Mutationsoperatoren definiert und deren Einfluss auf die Effizienz und Effektivität evolutionärer Algorithmen evaluiert. Desweiteren wird ein genereller, graphbasierter Ansatz zur Konstruktion von Kreuzungsoperatoren in MB-MDO vorgestellt. Der generelle Ansatz wird zudem für das Eclipse Modeling Framework (EMF) konkretisiert. Die Evaluation einer prototypischen Implementierung zeigt abschließend die Relevanz von Kreuzungsoperatoren für evolutionäre Algorithmen in MB-MDO
Direct Distribution of Rents and the Resource Curse in Iran: A Micro-econometric Analysis
No full textResource-rich economies and ethnically divided societies are linked to higher income inequality at the macro level. Our goal is to empirically examine the income inequality and welfare effects of the direct distribution of resource rents and subsequent taxation in Iran. We use rich micro survey data covering 140,000 individuals from more than 36,000 Iranian urban and rural households in 2009. Our micro-simulations show that the direct distribution of resource rents among all citizens and the imposition of an additional direct income tax have a significant negative effect on the household GINI index and on poverty. We also examine three alternative policies to the resource dividend (RD) policy. The results indicate that the RD policy is the most successful policy for addressing rents-induced inequality in Iran compared with the alternative policies
Influences on change in expected and actual health behaviors among first-year university students
No full textBackground:First-year students often adopt health risk behaviorsduring theirfirst semester such as increased consumption ofunhealthy food, decreased physical activity, and increased alcoholuse. Expectations, social tie’sefforts to motivate behavior, andcoresidence with parents can influence said behaviors.Aims:We assessed how students’health behaviors andexpectations change over thefirst semester, and how theaforementioned factors influence the maintenance or change ofbehavior and expectations.Methods:A longitudinal survey design was implemented. A total ofN= 163 Germanfirst-year students (81% female; 18% male; 1% non-binary;Mage= 21.20,SD= 2.66) completed online questionnaires,including the NCHRBS and AUDIT, during the Covid-19 pandemicat the beginning (November 2020) and after the end (May 2021)of theirfirst semester.Results:Current and expected food consumption and physicalactivity became healthier over time. The current and expectednumber of drinks consumed per month increased. Change inexpectations for physical activity, number of drinks and bingedrinking were predicted by the initial respective behavior. Thenumber of drinks and expected physical activity becameunhealthier in relation to reported initial parental influence todrink and to be physically inactive. Moving out of the parentalhome predicted an increase in current and expected number ofdrinks and in current and expected binge drinking. These effectsof moving out were not mediated by perceived parental or peerinfluence.Conclusions:Interventions should target these behaviors andexpectations during thefirst semester and address parentalinfluence on physical activity and alcohol use.Gefördert durch den Open-Access-Publikationsfonds der UB Marburg
Testing the sequence of successional processes in miniature ecosystems
No full textDispersal, environmental filtering, and biotic interactions define the species inventory of local communities. Along successional gradients, these assembly processes are predicted to sequentially vary in their relative importance with dispersal as the dominating process early in succession, followed by environmental filtering and biotic interactions at later stages. While observational data from field studies supported this prediction, controlled experiments confirming a sequence of successional processes are still lacking. We designed miniature ecosystems to explicitly test these assumptions under controlled laboratory conditions. Our “Ecosystems on a Plate” (EsoaP) are 3D-printed customized microplates with 24 connected wells allowing us to track dispersal, niche filtering, and biotic interactions among bacteria and plants in time and space. Within EsoaPs, we created heterogeneous habitat landscapes by well-specific nutrient levels or by providing plant seedlings as mutualistic partners in a checkerboard pattern. Bacteria of a single strain were released in one well and subsequently distributed themselves within the plates. We measured the spatial distribution of bacterial abundances at two time points as a function of abiotic or biotic heterogeneity. Bacterial abundance distribution confirmed a shift from initial dispersal-dominated processes to later niche filtering and biotic interactions as more important processes. Our approach follows the principles of open science as the affordable availability of 3D printers as well as shared STL files makes EsoaPs disseminatable and accessible to all levels of society, facilitating future experimental research.Gefördert durch den Open-Access-Publikationsfonds der UB Marburg
Stock Market Reactions to Legislated Tax Changes: Evidence from the United States, Germany, and the United Kingdom
No full textWe study the effect of tax policy on stock market returns in the US, Germany, and the UK using GARCH models and a unique daily dataset of legislative tax changes during the pe-riod 1978 to 2018. We find that days of discretionary tax legislation during all stages of the process often matter for returns, both in terms of statistical significance as well as economic relevance. Further disaggregating the tax shocks shows that news about personal income tax cuts affects stock market returns positively, whereas business tax legislation is rarely influential. We find evidence of stock market spillovers, mainly from US tax changes to European stock markets. In several cases, we measure significant effects of changes in tax legislation on the days the changes are implemented. The US House Committee Report appears to be the most influential legislative stage. During the financial crisis, stock markets were more responsive to tax legislation. Finally, S&P500 returns tend to react at earlier legislative stages than do DAX returns, whereas FT30 returns barely react on days of do-mestic legislative action
Pandemic Shocks and Household Spending
No full textWe study the response of daily household spending to the unexpected component of the COVID-19 pandemic, which we label as pandemic shock. Based on daily forecasts of the number of fatalities, we construct the surprise component as the difference between the actual and the expected number of deaths. We allow for state-dependent effects of the shock depending on the position on the curve of infections. Spending falls after the shock and is particularly sensitive to the shock when the number of new infections is strongly increasing. If the number of infections grows moderately, the drop in spending is smaller. We also estimate the effect of the shock across income quartiles. In each state, low-income households exhibit a significantly larger drop in consumption than high-income households. Thus, consumption inequality increase after a pandemic shock. Our results hold for the US economy and the key US states. The findings remain unchanged if we choose alternative state-variables to separate regimes
Whatever it Takes to Understand a Central Banker – Embedding their Words Using Neural Networks.
No full textDictionary approaches are at the forefront of current techniques
for quantifying central bank communication. This paper proposes embeddings - a language model trained using machine learning techniques - to locate words and documents in a multidimensional vector space. To accomplish this, we utilize a text corpus that is unparalleled in size and diversity in the central bank communication literature, as well as introduce a novel approach to text quantification from computational linguistics. This allows us to provide high-quality central bank-specific textual representations and demonstrate their applicability by developing an index that tracks deviations in the Fed's communication towards inflation targeting. Our findings indicate that these deviations in communication significantly impact monetary policy actions, substantially reducing the reaction towards inflation deviation in the US