The PAX 2 picture processing system

PAX 2 digital picture processing program written in FORTRAN - subroutine annotation

Carbon Dots as Versatile Photosensitizers for Solar-Driven Catalysis with Redox Enzymes

Light-driven enzymatic catalysis is enabled by the productive coupling of a protein to a photosensitizer. Photosensitizers used in such hybrid systems are typically costly, toxic, and/or fragile, with limited chemical versatility. Carbon dots (CDs) are low-cost, nanosized light-harvesters that are attractive photosensitizers for biological systems as they are water-soluble, photostable, nontoxic, and their surface chemistry can be easily modified. We demonstrate here that CDs act as excellent light-absorbers in two semibiological photosynthetic systems utilizing either a fumarate reductase (FccA) for the solar-driven hydrogenation of fumarate to succinate or a hydrogenase (H$_{2}$ase) for reduction of protons to H$_{2}$. The tunable surface chemistry of the CDs was exploited to synthesize positively charged ammonium-terminated CDs (CD-NHMe$_{2}$$^{+}$), which were capable of transferring photoexcited electrons directly to the negatively charged enzymes with high efficiency and stability. Enzyme-based turnover numbers of 6000 mol succinate (mol FccA)$^{-1}$ and 43,000 mol H$_{2}$ (mol H$_{2}$ase)$^{-1}$ were reached after 24 h. Negatively charged carboxylate-terminated CDs (CD-CO$_{2}$$^{-}$) displayed little or no activity, and the electrostatic interactions at the CD–enzyme interface were determined to be essential to the high photocatalytic activity observed with CD-NHMe$_{2}$$^{+}$. The modular surface chemistry of CDs together with their photostability and aqueous solubility make CDs versatile photosensitizers for redox enzymes with great scope for their utilization in photobiocatalysis.This work was supported by a Cambridge Australia Poynton PhD scholarship (to G.A.M.H.), the BBSRC (BB/K010220/1 to E.R. and BB/K009885/1 to J.N.B.), an Oppenheimer PhD scholarship (to B.C.M.M.), and a Marie Curie postdoctoral fellowship (GAN 624997 to C.A.C.)

Seismic Structure, Gravity Anomalies and Flexure Along the Emperor Seamount Chain

The Hawaiian-Emperor seamount chain in the Pacific Ocean has provided fundamental insights into hotspot generated intraplate volcanism and the long-term strength of oceanic lithosphere. However, only a few seismic experiments to determine crustal and upper mantle structure have been carried out on the Hawaiian Ridge, and no deep imaging has ever been carried out along the Emperor seamounts. Here, we present the results of an active source seismic experiment using 29 Ocean-Bottom Seismometers (OBS) carried out along a strike profile of the seamounts in the region of Jimmu and Suiko guyots. Joint reflection and refraction tomographic inversion of the OBS data show the upper crust is highly heterogeneous with P wave velocities <4–5 km s−1, which are attributed to extrusive lavas and clastics. In contrast, the lower crust is remarkably homogeneous with velocities of 6.5–7.2 km s−1, which we attribute to oceanic crust and mafic intrusions. Moho is identified by a strong PmP arrival at offsets of 20–80 km, yielding depths of 13–16 km. The underlying mantle is generally homogeneous with velocities in the range 7.9–8.0 km s−1. The crust and mantle velocity structure has been verified by gravity modeling. While top of oceanic crust prior to volcano loading is not recognized as a seismic or gravity discontinuity, flexural modeling reveals a ∼5.0–5.5 km thick preexisting oceanic crust that is overlain by a ∼8 km thick volcanic edifice. Unlike at the Hawaiian Ridge, we find no evidence of magmatic underplating

Going beyond Visualization. Verbalization as Complementary Medium to Explain Machine Learning Models

In this position paper, we argue that a combination of visualization and verbalization techniques is beneficial for creating broad and versatile insights into the structure and decision-making processes of machine learning models. Explainability of machine learning models is emerging as an important area of research. Hence, insights into the inner workings of a trained model allow users and analysts, alike, to understand the models, develop justifications, and gain trust in the systems they inform. Explanations can be generated through different types of media, such as visualization and verbalization. Both are powerful tools that enable model interpretability. However, while their combination is arguably more powerful than each medium separately, they are currently applied and researched independently. To support our position that the combination of the two techniques is beneficial to explain machine learning models, we describe the design space of such a combination and discuss arising research questions, gaps, and opportunities

Dispersion force for materials relevant for micro and nanodevices fabrication

The dispersion (van der Waals and Casimir) force between two semi-spaces are calculated using the Lifshitz theory for different materials relevant for micro and nanodevices fabrication, namely, gold, silicon, gallium arsenide, diamond and two types of diamond-like carbon (DLC), silicon carbide, silicon nitride and silicon dioxide. The calculations were performed using recent experimental optical data available in the literature, usually ranging from the far infrared up to the extreme ultraviolet bands of the electromagnetic spectrum. The results are presented in the form of a correction factor to the Casimir force predicted between perfect conductors, for the separation between the semi-spaces varying from 1 nanometre up to 1 micrometre. The relative importance of the contributions to the dispersion force of the optical properties in different spectral ranges is analyzed. The role of the temperature for semiconductors and insulators is also addressed. The results are meant to be useful for the estimation of the impact of the Casimir and van der Waals forces on the operational parameters of micro and nanodevices

Studying Flow Close to an Interface by Total Internal Reflection Fluorescence Cross Correlation Spectroscopy: Quantitative Data Analysis

Total Internal Reflection Fluorescence Cross Correlation Spectroscopy (TIR-FCCS) has recently (S. Yordanov et al., Optics Express 17, 21149 (2009)) been established as an experimental method to probe hydrodynamic flows near surfaces, on length scales of tens of nanometers. Its main advantage is that fluorescence only occurs for tracer particles close to the surface, thus resulting in high sensitivity. However, the measured correlation functions only provide rather indirect information about the flow parameters of interest, such as the shear rate and the slip length. In the present paper, we show how to combine detailed and fairly realistic theoretical modeling of the phenomena by Brownian Dynamics simulations with accurate measurements of the correlation functions, in order to establish a quantitative method to retrieve the flow properties from the experiments. Firstly, Brownian Dynamics is used to sample highly accurate correlation functions for a fixed set of model parameters. Secondly, these parameters are varied systematically by means of an importance-sampling Monte Carlo procedure in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for massively parallel computers, which allows us to do the data analysis within moderate computing times. The method is applied to flow near a hydrophilic surface, where the slip length is observed to be smaller than 10nm, and, within the limitations of the experiments and the model, indistinguishable from zero.Comment: 18 pages, 12 figure

High Performance Reduction of H2O2 with an Electron Transport Decaheme Cytochrome on a Porous ITO Electrode

The decaheme cytochrome MtrC from Shewanella oneidensis MR-1 immobilized on an ITO electrode displays unprecedented H2O2 reduction activity. Although MtrC showed lower peroxidase activity in solution compared to horseradish peroxidase, the ten heme cofactors enable excellent electronic communication and a superior activity on the electrode surface. A hierarchical ITO electrode enabled optimal immobilization of MtrC and a high current density of 1 mA cm−2 at 0.4 Vvs SHE could be obtained at pH 6.5 (Eonset = 0.72 V). UV−visible and Resonance Raman spectroelectrochemical studies suggest the formation of a high valent iron-oxo species as the catalytic intermediate. Our findings demonstrate the potential of multiheme cytochromes to catalyze technologically relevant reactions and establish MtrC as a new benchmark in biotechnological H2O2 reduction with scope for applications in fuel cells and biosensors.BBSRC, ERC, DFG, Marie Sklodowska Curie fellowshi

Depinning transition of dislocation assemblies: pileup and low-angle grain boundary

We investigate the depinning transition occurring in dislocation assemblies. In particular, we consider the cases of regularly spaced pileups and low angle grain boundaries interacting with a disordered stress landscape provided by solute atoms, or by other immobile dislocations present in non-active slip systems. Using linear elasticity, we compute the stress originated by small deformations of these assemblies and the corresponding energy cost in two and three dimensions. Contrary to the case of isolated dislocation lines, which are usually approximated as elastic strings with an effective line tension, the deformations of a dislocation assembly cannot be described by local elastic interactions with a constant tension or stiffness. A nonlocal elastic kernel results as a consequence of long range interactions between dislocations. In light of this result, we revise statistical depinning theories and find novel results for Zener pinning in grain growth. Finally, we discuss the scaling properties of the dynamics of dislocation assemblies and compare theoretical results with numerical simulations.Comment: 13 pages, 8 figure