Bøger i BestMasters serien

Michael Lepper presents a detailed room temperature scanning tunneling microscopy study of Nickel-tetraphenyltetrabenzoporphyrin on Cu(111), a prototype system for the fabrication of functional molecular architectures. The peculiar adsorption behavior, in particular the observation of three different coexisting supramolecular arrangements and the identification of two different intramolecular conformations within one arrangement, yield valuable insights into the specific molecular interactions and the self-assembly process in general.

In this book Simona Roccioletti reviews several valuable studies about risk measures and their properties; The main contribution of the work is the application of "Test 1" and "Test 2" developed by Acerbi and Szekely (2014) on different models and for five global market indexes.

This thesis uses neoclassical growth models toevaluate what effect the limited availability of nonrenewable resources has onthe economy's (world's) growth potential. After a thorough analysis of the models it isconcluded that the ultimate solution to long-term economic growth is a backstoptechnology.

By drawing up a model of the internal communication system of Bangladeshi ready-made garment factories, Helene Blumer identifies the existence and intensity of its communication flows.

Leonid Ryvkin gives a motivated and self-sustainedintroduction to n-plectic geometry with a special focus on symmetries. Therelevant algebraic structures from scratch are developed. The author generalizesknown symplectic notions, notably observables and symmetries, to the n-plecticcase, culminating in solving the existence question for co-moment maps forgeneral pre-n-plectic manifolds. Finally partial results scattered along theliterature are derived from our general result.

Manuel Kroiss examines the differentiation of hematopoietic stem cells using machine learning methods. This work is based on experiments focusing on the lineage choice of CMPs, the progenitors of HSCs, which either become MEP or GMP cells. The author presents a novel approach to distinguish MEP from GMP cells using machine learning on morphology features extracted from bright field images. He tests the performance of different models and focuses on Recurrent Neural Networks with the latest advances from the field of deep learning. Two different improvements to recurrent networks were tested: Long Short Term Memory (LSTM) cells that are able to remember information over long periods of time, and dropout regularization to prevent overfitting. With his method, Manuel Kroiss considerably outperforms standard machine learning methods without time information like Random Forests and Support Vector Machines.

Carolin Loos introduces two novel approaches for theanalysis of single-cell data. Both approaches can be used to study cellularheterogeneity and therefore advance a holistic understanding of biologicalprocesses. The first method, ODE constrained mixture modeling, enables theidentification of subpopulation structures and sources of variability in single-cellsnapshot data. The second method estimates parameters of single-cell time-lapsedata using approximate Bayesian computation and is able to exploit the temporalcross-correlation of the data as well as lineage information. 

Daniel Halwidl presents the development of an effusive molecular beam apparatus, which allows the dosing of gases, liquids, and solids in ultra-high vacuum. The apparatus is designed to adsorb precise and reproducible doses to a defined area on metal oxide samples, which is required in Temperature Programmed Desorption and other surface chemistry experiments. The design and the construction of the apparatus is described. The properties of the molecular beam are experimentally confirmed. The beam profile has a core diameter of 3.5 mm and a standard core pressure of 4 x 10-8 mbar, while the background pressure is 4 orders of magnitude lower. 

In experiments on aprototypical combustor, Richard Steinert identifies new insights on the impactof noise on the phenomenon known as thermoacoustic instability. The phenomenonis a concerning issue which creates a technical limit on the efficiency andenvironmental impact of fossil fuels combustion in industrial combustors. Itposes a threat to the structural integrity of practical systems such as gasturbine combustors and rocket engines. The experiments demonstrate thatthermoacoustic systems feature an interesting noise-induced behaviour known ascoherence resonance - a coherent response of dynamical systems close to theirstability boundary that is induced by stochastic excitation. The work containedin this publication is an example illustrating the importance of fundamentalconsiderations in solving perplexing engineering issues.

This thesis presents a scalable, generic methodology for microbial phenotype prediction based on supervised machine learning, several models for biological and ecological traits of high relevance, and the deployment in metagenomic datasets. The results suggest that the presented prediction tool can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomic studies. Unraveling relationships between a living organism's genetic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.

In this thesis accurate predictions for the spectroscopic parameters of l-C3H+ and C4 are made from state-of-the-art electronic structure calculations. Both molecules are of interest to interstellar cloud chemistry and only scarce experimental information about their rovibrational properties is available. Christopher J. Stein recapitulates the basics of the computational methods applied and gives an in-depth description of the computer program developed for the rovibrational calculations.

Carina Klein examines the quality of the existing modern ammonoid zonation based on three methods, being Unitary Associations (UA), Constrained Optimization (CONOP) as well as Ranking and Scaling (RASC). The author sets out which of these three methods is best suitable to refine these zones. The results obtained are compared to each other with regard to ammonoid succession and resolution as well as with empirical data from selected reference sections. The analysis reveals that the UA and RASC methods are the most suitable since the results best mirror the empirical data from the single outcrops.

The book introduces the New Keynesian framework, historically through a literature overview and through a step-by-step derivation of a New Keynesian Phillips curve, an intertemporal IS curve, and a targeting rule for the central bank.

Maximilian Lantelme examines the historical growth and decline developments of large German family and non-family businesses between 1971 and 2011.

Swen Nadkarni delivers a systematic review of the literature on factors of leadership, composed of management, ownership and generation, and their influence on innovation in family businesses.

This book brings together the research fields of start-up ecosystems and diaspora entrepreneurship. The findings prove impacts of diaspora ventures on the dynamics of the Berlin start-up ecosystem and are applied to a modified version of the ANDE toolkit.

The publication examines, for example, pay-for-delay strategies, market foreclosure, resale price maintenance, but also mergers and acquisitions, while taking into account market specificities such as the unique research and development process.

Georg Zimmermann provides a mathematically rigorous treatment of basic survival analytic methods. The author shows both the step-by-step analyses of that dataset and the theory the analyses are based on.

Hannah Minges focuses on the investigation of two different FAD-dependent halogenases in order to analyze and improve their applicability for chemoenzymatic approaches in chemistry.

In his research, David Dannheisig investigates the influence of lysine129 acetylation on the biological function of survivin including alteration of nucleocytoplasmic shuttling as well as dimerization behavior.

In her research, Inga Lilge focuses on a systematic study of poly(acrylamide) (PAAm) brushes prepared by surface-initiated atom transfer radical polymerization (SI-ATRP). In addition to the analysis of the time dependence of the polymer brush growth, the conformation of the polymer brushes is varied by grafting or cross-linking density.

Emil Kraft analyses the French capacity remuneration mechanism design and develops a capacity market model that draws upon an agent-based simulation.

Verena Anna Berger investigates the question to what extent credit default swap spreads are impacted by an increase of government bond yields within the European area. The main findings which are calculated by using the Fontana-Scheicher model show that a negative impact on credit default swap spreads is observed based on the analysed data.

Dominik Volland studies the construction of a discrete counterpart to the Hilbert transform in the realm of a nonlinear discrete complex analysis given by circle packings. The author demonstrates that the discrete Hilbert transform is well-defined in this framework by proving a conjecture on discrete problems formulated by Wegert.

Models of the present and the future value network are drawn, which show the expanding need of information exchange between the value network and the supply chain. To ensure the information exchange, the need of a non-proprietary data exchange platform in the agricultural sector is being suggested.

The author shows that receiving more information enables subjects to make better estimations, whereas more information improves the quality of estimations significantly only if it is a lot more information.

Sebastian Frericks examines, based on a qualitative content analysis, the factors that lead large German listed companies to downfall. Within the following comprehensive cross-study, the author presents relations between motives, factors, field of business and type of downfall.

In his study Christian Boedinger utilizes satellite imagery in combination with machine learning to derive maps of land use and land cover (LULC) in four study sites along a climatic gradient and to monitor vegetation using monthly Normalized Difference Vegetation Index (NDVI) time series.

Afferents from the pectines project into a distinct neuropil of the central nervous system, located behind the fourth walking leg neuropils. Denise Drozd analyzes afferents of single pegs in Mesobuthus eupeus by backfilling, combined with immunohistological labeling of neuropil regions.

Matthaus Jager examines the simulation of liquid-gas flow in fuel tank systems and its application to sloshing problems. The second step involves the cell-centered finite volume method and its application to fluid dynamic problems with free surfaces using a volume of fluid approach.