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Late-stage functionalization of natural products offers an elegant route to create novel entities in a relevant biological target space. In this context, enzymes capable of halogenating sp3 carbons with high stereo- and regiocontrol under benign conditions have attracted particular attention. Enabled by a combination of smart library design and machine learning, we engineer the iron/α-ketoglutarate dependent halogenase WelO5* for the late-stage functionalization of the complex and chemically difficult to derivatize macrolides soraphen A and C, potent anti-fungal agents. While the wild type enzyme WelO5* does not accept the macrolide substrates, our engineering strategy leads to active halogenase variants and improves upon their apparent kcat and total turnover number by more than 90-fold and 300-fold, respectively. Notably, our machine-learning guided engineering approach is capable of predicting more active variants and allows us to switch the regio-selectivity of the halogenases facilitating the targeted analysis of the derivatized macrolides’ structure-function activity in biological assays.

Neste ensaio, demonstra-se que qualquer grupo de difeomorfismos que preserve orientação e aja na 2-esfera, estendendo propriamente o grupo conforme das transformações de Möbius, precisa ser ao menos 4 transitivo ou, mais precisamente, 4-transitivo por arcos. Isso significa que quaisquer duas listas ordenadas de quatro pontos distintos podem ser aplicadas uma sobre a outra por alguma transformação do grupo, isotópica à identidade. Argumenta-se, também, que tais grupos apresentam sempre um elemento de entropia topológica positiva, para o qual é dada uma descrição como isotópico a um homeomorfismo pseudo-Anosov relativo da esfera 4-perfurada. Além disso, apresenta-se uma caracterização elementar em termos de transitividade das transformações de Möbius dentro do grupo total de difeomorfismos. It is proven in this essay that any group of orientation preserving diffeomorphisms acting on the 2-sphere and properly extending the conformal group of Möbius transformations must be at least 4-transitive or, more precisely, arc 4-transitive. This means that any two ordered lists of four distinct points can be mapped one onto the other via a transformation in the group, isotopic to the identity. In addition, it is shown that any such group must always contain an element of positive topological entropy, for which a description as isotopic to a relative pseudo-Anosov homeomorphism of the 4-punctured sphere is provided. Furthermore, an elementary characterisation of the Möbius transformations within the full group of sphere diffeomorphisms is given in terms of transitivity.

Diffusion Models have achieved state-of-the-art results in image generating tasks, yet face different challenges when used in different domains. We first give a brief overview of the Diffusion Models architecture. Then, we present a new model and architecture called SVGFusion that applies the principles of Diffusion Models to generate Vector Graphics. Vector Graphics have a complex structure and are vastly different than pixel images, and thus the main challenge when working with Vector Graphics is how to represent their complex structure in a way that a Diffusion Model can effectively process. We will explain this and the further challenges that we encountered during the process and how we successfully addressed some of them. We demonstrate the effectiveness of our approach by training a sample model on a decently sized dataset as well as running valuable experiments. Furthermore, we offer useful insights, recommendations and code to researchers who wish to further explore this topic.

The purpose of this document is to develop a concept for action plans within the framework of SALUTE4CE project, specifically, for urban pilot project areas where urban environmental acupuncture is being applied and their respective Functional Urban Areas (FUAs). The action plan concept incorporates the methodology for selecting urban environmental acupuncture (UEA) sites and this includes the typology and selection of interventions created within the SALUTE4CE project. The transnational action plan concept is comprised of three main sections: general considerations, creating local action plans and plan implementation.

In der Anwendung als Leitermaterialien werden nach dem Stand der Technik Metalle wie Kupfer oder Aluminium eingesetzt. Dies betrifft beispielsweise Hochspannungsleitungen, Motorwicklungen oder die Infrastruktur in Städten. Insbesondere im Fall von Kupfer handelt es sich um ein teures und schweres Material. Graphen-basierte Leitermaterialien (GCMs, engl. graphene-based conductor materials) stellen eine potentiell günstige und hoch leitfähige Alternative dar, die metallische Leiter ersetzen kann. GCMs sind mechanisch flexibel, wesentlich leichter als Metalle und korrosionsbeständig. Um das Potential ihrer elektrischen Leitfähigkeit voll auszuschöpfen bedarf es jedoch einer gezielten Materialoptimierung. In der vorliegenden Arbeit wird die elektrische Leitfähigkeit von GCMs systematisch in Simulationen und Experimenten untersucht. Mit einem vereinfachten Modell eines GCMs wird der theoretische Maximalwert der Leitfähigkeit mathematisch hergeleitet. Weiterhin wird die Abhängigkeit der Leitfähigkeit von mikroskopischen Materialparametern quantifiziert. In Finite Elemente Simulationen werden realistischere sowie defektbehaftete Geometrien betrachtet und die Erkenntnisse aus dem analytischen Modell erweitert. Die sinnvolle Modellierung von physikalischen Eingangsgrößen als statistische Verteilungen erfordert Strukturen mit mehreren Zehntausend Graphenplättchen. Zu diesem Zweck wird ein effizientes Netzwerkmodell konzeptioniert und implementiert. Mit dem Modell werden darüberhinaus Ergebnisse mit der Literatur verglichen, Oberflächenkontakte betrachtet und eine beispielhafte Materialbewertung durchgeführt. Weiterhin werden konkrete Richtlinien zur Herstellung von hochleitfähigen GCMs abgeleitet. Um die Simulationen zu validieren und das Potential von GCMs experimentell zu bewerten, wird eine Prozesskette zur Herstellung von Graphenfilmen aufgebaut. Dabei werden flüssige Graphen- oder Graphenoxiddispersionen als Ausgangsmaterial gewählt, da in dieser Art große Mengen Graphen verarbeitet werden können. Mittels Zentrifugierung werden die Größen der Graphenplättchen variiert. Iodwasserstoffsäure wird als Reduktionsmittel eingesetzt und bewertet, ebenso wie eine thermische Materialbehandlung. Zur Materialcharakterisierung werden Rasterelektronenmikroskopie, Raman-Mikroskopie und eine Wirbelstrommessung der Leitfähigkeit eingesetzt. Zwei Studien zur Abhängigkeit der Leitfähigkeit von mikroskopischen Parametern werden experimentell realisiert. Die Ergebnisse zeigen gute Übereinstimmung zur Vorhersage durch das Netzwerkmodell und untermauern so die zuvor beschriebenen Wirkzusammenhänge. In the application as conductor materials, metals such as copper or aluminum represent the state of the art. This applies for example to high-voltage lines, motor windings or the infrastructure in cities. However, metals, and especially copper, are expensive and heavy. Graphene-based conductor materials (GCMs) represent a cost-competitive and highly conductive alternative to metallic conductors. GCMs are mechanically flexible, lightweight and corrosion-resistant. But in order to fully exploit the potential of their electrical conductivity, a systematic material optimization is required. In this thesis, the electrical conductivity of GCMs is investigated in simulations and experiments. Using a simplified model of a GCM, the theoretical maximum value of the conductivity is derived mathematically. Furthermore, the dependence of the conductivity on microscopic material parameters is quantified. For a deeper insight, finite element simulations are used to study more realistic as well as defective geometries. The meaningful modeling of physical parameters as statistical distributions requires structures with tens of thousands of graphene flakes. To this end, an efficient network model is designed and implemented. The network model is further used to compare results with the literature, to consider surface contacts and to perform an exemplary material evaluation. From the simulation results, specific guidelines for the production of highly conductive GCMs are derived. In order to validate the simulations and to evaluate the potential of GCMs experimentally, a process chain for the preparation of graphene films is set up. Liquid graphene or graphene oxide dispersions are chosen as the starting materials, since large amounts of graphene can be processed in this way. The sizes of the graphene flakes are varied via centrifugation. Hydriodic acid is employed and evaluated as a reducing agent, as is thermal treatment. Scanning electron microscopy, Raman microscopy and an eddy current measurement of the conductivity are used for material characterization. Two studies on the dependence of the electrical conductivity on microscopic parameters are experimentally realized. The results show good agreement with the prediction by the network model and thus support the previously established theoretical description.

Aktuell liegt der Anteil von Studentinnen in den MINT Studiengängen ca. 17 % niedriger als in anderen Studiengängen. Welche Faktoren führen zu dieser Situation? Eine Vielzahl an Faktoren wirkt sich auf die Studienwahl und -persistenz aus. Die zugrundeliegende Masterarbeit untersuchte die Beziehungen zwischen Geschlecht, Social Belonging, Belonging Uncertainty, Stereotype Fit und Chilly Climate. Besonders lag der Fokus auf der Erforschung des Einflusses von Social Belonging auf Erfolgsparamenter (Identifikation, Erfolgserwartung, Turnover Intention, Notendurchschnitt und Anzahl der Drittversuche zum Bestehen einer Prüfungsleistung). Außerdem wurde untersucht, ob Stereotype Fit als Mediator die Beziehung zwischen Geschlecht und Social Belonging beeinflusst. Grundlage der Studie bildete eine Online-Umfrage an der Fakultät Physik der TU Dresden. Die Ergebnisse zeigen, dass Frauen geringere Werte im Bereich Social Belonging und Stereotype Fit angaben, sowie höhere Werte im Bereich Belonging Uncertainty. Identifikation wurde sowohl durch Social Belonging, als auch Belonging Uncertainty vorhergesagt. Die Erfolgserwartung wurde signifikant von Geschlecht und Social Belonging beeinflusst. Für den Notendurschnitt und die Turnover Intention war Social Belonging der einzige signifikante Prädiktor. Die Anzahl der Drittversuche wurde positiv von Belonging Uncertainty vorhergesagt. Die Hypothese, dass Stereotype Fit ein Mediator ist, ließ sich mit den Daten nicht belegen. Stattdessen zeigen explorative Mediationsanalysen, dass eher Social Belonging und Belonging Uncertainty die Mediatoren der Beziehung zwischen Geschlecht und Stereotype Fit sind. Alle Ergebnisse deuten darauf hin, dass Social Belonging ein wichtiger Faktor für den Erfolg von Frauen in MINT-Fächern ist. Daraus lässt sich ableiten, dass eine Förderung von Social Belonging im Studium positive Auswirkungen auf den Erfolg von Frauen haben würde. Aktuelle Forschungsergebnisse zeigen, dass sich Social Belonging durch kostengünstige und kurze Interventionen steigern lässt. Eine Umsetzung von Fördermöglichkeiten im Bildungskontext wird im Rahmen von weiterer Forschung empfohlen. Mein herzlicher Dank geht an Dr. Anika Ihmels für die empowernde Betreuung während der Masterarbeit sowie die Fakultät Physik, deren Gleichstellungsbeauftragten und den FSR Physik, welche die Umfrage unterstützten und ermöglichten. Currently, the percentage of female students in STEM majors is about 17% lower than in other majors. What factors lead to this situation? A variety of factors impact student choice and persistence. The underlying master's thesis examined the relationships between gender, social belonging, belonging uncertainty, stereotype fit, and chilly climate. In particular, the focus was on exploring the influence of social belonging on selected success parameters (identification, expectation of success, turnover intention, grade point average, and number of third attempts to pass an exam performance). It also examined whether Stereotype Fit acts as a mediator on the relationship between gender and Social Belonging. The study was based on an online survey at the Faculty of Physics at the TU Dresden. The results show that women reported lower scores in Social Belonging and Stereotype Fit, and higher scores in Belonging Uncertainty. Identification was predicted by both Social Belonging and Belonging Uncertainty. Expectation of success was significantly affected by gender and Social Belonging. For grade point average and turnover intention, Social Belonging was the only significant predictor. The number of third attempts was positively predicted by Belonging Uncertainty. The hypothesis that Stereotype Fit is a mediator could not be supported by the data. Instead, exploratory mediation analyses show that Social Belonging and Belonging Uncertainty are more likely to be mediators of the relationship between gender and Stereotype Fit. All results suggest that Social Belonging is an important factor for women's success in STEM fields. Therefore, it can be inferred that promoting Social Belonging in college would have a positive impact on women's success. Current research shows that Social Belonging can be increased through low-cost and brief interventions. Implementation of promotional opportunities in the educational context is recommended as part of further research. My sincere thanks go to Dr. Anika Ihmels for the empowering supervision during the master thesis as well as the Faculty of Physics, its Equal Opportunity Officer and the FSR Physics, who made the survey possible and supported it.

In the last years, the amount of available data in the field of computational biology steadily increased. In order to be able to analyze these data, various algorithms have been developed by bioinformaticians to process them efficiently. Moreover, computational models were developed to predict for instance biological relationships of species. Furthermore, the prediction of properties like the structure of certain biological molecules is modeled by complex algorithms. Despite these advances in handling such complicated tasks with automated workflows and a huge variety of freely available tools, the expert still needs to supervise the data analysis pipeline inspecting the quality of both the input data and the results. Additionally, choosing appropriate parameters of a model is quite involved. Visual support puts the expert into the data analysis loop by providing visual encodings of the data and the analysis results together with interaction facilities. In order to meet the requirements of the experts, the visualizations usually have to be adapted for the application purpose or completely new representations have to be developed. Furthermore, it is necessary to combine these visualizations with the algorithms of the experts to prepare the data. These in-situ visualizations are needed due to the amount of data handled within the analysis pipeline in this domain. In this thesis, algorithms and visualizations are presented that were developed in two different research areas of computational biology. On the one hand, the multi-replicate peak-caller Sierra Platinum was developed, which is capable of predicting significant regions of histone modifications occurring in genomes based on experimentally generated input data. This algorithm can use several input data sets simultaneously to calculate statistically meaningful results. Multiple quality measurements and visualizations were integrated into to the data analysis pipeline to support the analyst. Based on these in-situ visualizations, the analyst can modify the parameters of the algorithm to obtain the best results for a given input data set. Furthermore, Sierra Platinum and related algorithms were benchmarked against an artificial data set to evaluate the performance under specific conditions of the input data set, e.g., low read quality or undersequenced data. It turned out that Sierra Platinum achieved the best results in every test scenario. Additionally, the performance of Sierra Platinum was evaluated with experimental data confirming existing knowledge. It should be noticed that the results of the other algorithms seemed to contradict this knowledge. On the other hand, this thesis describes two new visualizations for RNA secondary structures. First, the interactive dot plot viewer iDotter is described that is able to visualize RNA secondary structure predictions as a web service. Several interaction techniques were implemented that support the analyst exploring RNA secondary structure dot plots. iDotter provides an API to share or archive annotated dot plots. Additionally, the API enables the embedding of iDotter in existing data analysis pipelines. Second, the algorithm RNApuzzler is presented that generates (outer-)planar graph drawings for all RNA secondary structure predictions. Previously presented algorithms failed in always producing crossing-free graphs. First, several drawing constraints were derived from the literature. Based on these, the algorithm RNAturtle was developed that did not always produced planar drawings. Therefore, some drawing constraints were relaxed and additional drawing constraints were established. Building on these modified constraints, RNApuzzler was developed. It takes the drawing generated by RNAturtle as an input and resolves the possible intersections of the graph. Due to the resolving mechanism, modified loops can become very large during the intersection resolving step. Therefore, an optimization was developed. During a post-processing step the radii of the heavily modified loops are reduced to a minimum. Based on the constraints and the intersection resolving mechanism, it can be shown that RNApuzzler is able to produce planar drawings for any RNA secondary structure. Finally, the results of RNApuzzler are compared to other algorithms.

The workshop program will focus on adsorption measurement techniques and methodologies for the assessment of adsorption properties and textural/structural characterization of novel nanoporous materials including zeolites, carbons, MOFs as well as materials consisting of hierarchically structured pore networks. A major point will be the correlation of textural properties, adsorption behavior, catalytic reaction pathways as well as transport properties with applications in gas and energy storage, separations and catalysis. Within this framework, the workshop will offer a platform for scientific discussions and for a knowledge transfer between various scientific areas where diffusion and transport properties of porous materials are of importance.