Modeling the effect of intercalators on the high-force stretching behavior of DNA

DNA is structurally and mechanically altered by the binding of intercalator molecules. Intercalation strongly affects the force-extension behavior of DNA, in particular the overstretching transition. We present a statistical model that captures all relevant findings of recent force-extension experiments. Two predictions from our model are presented. The first suggests the existence of a novel hyper-stretching regime in the presence of intercalators and the second, a linear dependence of the overstretching force on intercalator concentration, is verified by re-analyzing available experimental data. Our model pins down the physical principles that govern intercalated DNA mechanics, providing a predictive understanding of its limitations and possibilities.Comment: 5 pages, 4 figure

Religion, competition and liability: Dutch cooperative banking in crisis, 1919-1927

What accounts for the differences in the performance of cooperatively-owned banks in the Dutch financial crisis of the early 1920s? This thesis measures and explains the (relative) performance of boerenleenbanken (rural Raiffeisen banks) and middenstandsbanken (urban Schulze-Delitzsch banks) during the Netherlands' interwar banking crisis by applying various economic methods to new historical evidence. The thesis asks: (1) what were the effects on risk-taking behaviour of differences in the religious attitudes of bankers and their customers? (2) what was the relationship between interbank competition and financial stability? and (3) what was the consequence of the liability choices made by shareholders for their banks' continued survival? Using a combination of economic theory, quantitative financial analysis and qualitative business histories, this thesis finds that: (1) banks serving small religious groups were less willing, despite being more able, to take on risks than those serving majority denominations; (2) those banks that were subject to the lowest competitive pressures enjoyed the most liquid investment portfolios; and (3) the choice of liability limitation available to bankers in uenced their balance sheet risks, for the worse. Together, these findings lead to the conclusion that social, organisational and institutional factors each explain part of the heterogeneity in the fate of the Netherlands' cooperative banks during a period which includes unprecedented debt- deflationary financial turmoil: hence, (1) strict membership criteria and the use of personal guarantors in loan agreements acted as strong devices to allow banks for minorities, regardless of their denomination, to screen and monitor their customers; (2) the switching costs associated with religious affiliation resulted in a competition- stability tradeoff during periods of extreme distress; and (3) the stakeholders of the banks which failed were probably less risk-averse than those of banks which did not, the consequence of endogenous group formation by risk type

Long distance synchronization of mobile robots

This paper considers the long distance master-slave and mutual synchronization of unicycle-type mobile robots. The issues that arise when the elements of a robotic network are placed in different locations are addressed, specifically the time-delay induced by the communication channel linking the robots. Experiments between wirelessly controlled mobile robots located in Eindhoven, The Netherlands and Tokyo, Japan demonstrate the applicability of the proposed approach

Experimental and theoretical study of semiconductor laser dynamics due to filtered optical feedback

We report experimental results on the nonlinear dynamical response of a semiconductor laser subjected to time-delayed (>5 ns), frequency selective, optical feedback from a Fabry-Pe´rot interferometer type of filter. Three regimes of interest, based on the relative value of the filter bandwidth with respect to the relevant laser parameters (relaxation oscillation frequency and external cavity mode spacing), are identified, viz. a wide filter case, an intermediate filter width case, and a narrow filter case. The dynamical response of the laser is shown to be quite different in each of these regimes. The principal results are 1) the laser's linewidth enhancement factor, coupled with the nonlinear response of the filter, can be exploited to induce nonlinear dynamics in the instantaneous optical frequency of the laser light on a time scale related to the time-delay of the feedback, 2) a mode mismatch effect which arises from a detuning between the filter center frequency and the nearest external cavity mode and manifests itself in a reduction of the maximum light available for feedback, and 3) a reduction in, or even disappearance of, relaxation oscillations in the laser dynamics when a filter of appropriate width is chosen. More generally, it is observed that certain dynamics that occur due to unfiltered optical feedback may be suppressed when the feedback light is spectrally filtered

Learning and Adaptation in Polycentric Transport Governance:The Case of the Dutch Brabant Accessibility Agenda

The future of urban-regional transport crucially depends on the ability of transport governance systems to adapt. Polycentric theory claims that the presence of polycentric attributes and conditions enables governance systems to learn and adapt. However, an analysis of the Dutch Brabant Accessibility Agenda shows that their presence says little about the adaptive capacity of transport governance systems because learning and adaptation are influenced by dependencies. To optimize the adaptive capacity of transport governance systems, it is therefore vital to acknowledge both the diverse ways in how they learn and adapt, and the dependencies that shape these processes

Meta-Learning for Symbolic Hyperparameter Defaults

Hyperparameter optimization in machine learning (ML) deals with the problem of empirically learning an optimal algorithm configuration from data, usually formulated as a black-box optimization problem. In this work, we propose a zero-shot method to meta-learn symbolic default hyperparameter configurations that are expressed in terms of the properties of the dataset. This enables a much faster, but still data-dependent, configuration of the ML algorithm, compared to standard hyperparameter optimization approaches. In the past, symbolic and static default values have usually been obtained as hand-crafted heuristics. We propose an approach of learning such symbolic configurations as formulas of dataset properties from a large set of prior evaluations on multiple datasets by optimizing over a grammar of expressions using an evolutionary algorithm. We evaluate our method on surrogate empirical performance models as well as on real data across 6 ML algorithms on more than 100 datasets and demonstrate that our method indeed finds viable symbolic defaults.Comment: Pieter Gijsbers and Florian Pfisterer contributed equally to the paper. V1: Two page GECCO poster paper accepted at GECCO 2021. V2: The original full length paper (8 pages) with appendi