A biophysical exploration of proteins and their substrates

Wuite, G.J.L. [Promotor

A Comprehensive Stress Drop Map From Trench to Depth in the Northern Chilean Subduction Zone

We compute stress drops for earthquakes in Northern Chile recorded between 2007 and 2021. By applying two analysis techniques, (a) the spectral ratio (SR) method and (b) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s functions (EGF) for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell-wise obtained global EGF's to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismotectonic domains. Albeit only small differences of median stress drop, strike-perpendicular depth sections clearly reveal systematic variations, with earthquakes at different seismotectonic locations exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth-dependent increase of median stress drop. Additionally, we observe spatio-temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures

Nebraska’s Natural Resource District System: Collaborative Approaches to Adaptive Groundwater Quality Governance

Nonpoint source pollution of groundwater by nitrates from agricultural activity is a persistent problem for which developing effective policy approaches has proven difficult. There is little empirical information on forms of governance or regime attributes that effectively and sustainably address agricultural nonpoint source pollution of groundwater. Nebraska’s Natural Resource District (NRD) system is a rare example of a groundwater governance regime that is putting programmes in place that are likely to generate sustainable groundwater quality outcomes. We focus on three groundwater nitrate management programmes in the state that collectively represent the broader NRD system. The research shows that four elements of Nebraska’s groundwater governance regime are fundamental to its success in addressing groundwater nitrates: 1) the local nature of governance, which builds trust among stakeholders; 2) the significant authority granted to the local districts by the state, allowing for the development of locally tailored solutions; 3) the collaborative governance approach, which allows potential scale imbalances to be overcome; and 4) the taxing authority granted to NRDs, which enables them to fund locally tailored management solutions. We find that these aspects of the NRD system have created conditions that enable adaptive, collaborative governance that positions the state well to address emerging groundwater quality challenges. We present aspects of the governance regime that are generalisable to other American states as efforts to address nitrate pollution in groundwater increase

Surface state charge dynamics of a high-mobility three dimensional topological insulator

We present a magneto-optical study of the three-dimensional topological insulator, strained HgTe using a technique which capitalizes on advantages of time-domain spectroscopy to amplify the signal from the surface states. This measurement delivers valuable and precise information regarding the surface state dispersion within <1 meV of the Fermi level. The technique is highly suitable for the pursuit of the topological magnetoelectric effect and axion electrodynamics.Comment: Published version, online Sept 23, 201

Temperature dependence of the charge carrier mobility in gated quasi-one-dimensional systems

The many-body Monte Carlo method is used to evaluate the frequency dependent conductivity and the average mobility of a system of hopping charges, electronic or ionic on a one-dimensional chain or channel of finite length. Two cases are considered: the chain is connected to electrodes and in the other case the chain is confined giving zero dc conduction. The concentration of charge is varied using a gate electrode. At low temperatures and with the presence of an injection barrier, the mobility is an oscillatory function of density. This is due to the phenomenon of charge density pinning. Mobility changes occur due to the co-operative pinning and unpinning of the distribution. At high temperatures, we find that the electron-electron interaction reduces the mobility monotonically with density, but perhaps not as much as one might intuitively expect because the path summation favour the in-phase contributions to the mobility, i.e. the sequential paths in which the carriers have to wait for the one in front to exit and so on. The carrier interactions produce a frequency dependent mobility which is of the same order as the change in the dc mobility with density, i.e. it is a comparably weak effect. However, when combined with an injection barrier or intrinsic disorder, the interactions reduce the free volume and amplify disorder by making it non-local and this can explain the too early onset of frequency dependence in the conductivity of some high mobility quasi-one-dimensional organic materials.Comment: 9 pages, 8 figures, to be published in Physical Review

Towards More Robust Evaluation of the Predictive Performance of Physiologically Based Pharmacokinetic Models:Using Confidence Intervals to Support Use of Model-Informed Dosing in Clinical Care

Background and ObjectiveWith the rise in the use of physiologically based pharmacokinetic (PBPK) modeling over the past decade, the use of PBPK modeling to underpin drug dosing for off-label use in clinical care has become an attractive option. In order to use PBPK models for high-impact decisions, thorough qualification and validation of the model is essential to gain enough confidence in model performance. Currently, there is no agreed method for model acceptance, while clinicians demand a clear measure of model performance before considering implementing PBPK model-informed dosing. We aim to bridge this gap and propose the use of a confidence interval for the predicted-to-observed geometric mean ratio with predefined boundaries. This approach is similar to currently accepted bioequivalence testing procedures and can aid in improved model credibility and acceptance.MethodsTwo different methods to construct a confidence interval are outlined, depending on whether individual observations or aggregate data are available from the clinical comparator data sets. The two testing procedures are demonstrated for an example evaluation of a midazolam PBPK model. In addition, a simulation study is performed to demonstrate the difference between the twofold criterion and our proposed method.ResultsUsing midazolam adult pharmacokinetic data, we demonstrated that creating a confidence interval yields more robust evaluation of the model than a point estimate, such as the commonly used twofold acceptance criterion. Additionally, we showed that the use of individual predictions can reduce the number of required test subjects. Furthermore, an easy-to-implement software tool was developed and is provided to make our proposed method more accessible.ConclusionsWith this method, we aim to provide a tool to further increase confidence in PBPK model performance and facilitate its use for directly informing drug dosing in clinical care