Ultrafast absorption kinetics of NADH in folded and unfolded conformations

The non-radiative energy transfer is shown to occur on a ~3ps time scale for NADH in the folded form in H2O. Addition of methanol thermodynamically favours the open form, for which energy transfer does not occur

Nutrient supply to anticyclonic meso-scale eddies off western Australia estimated with artificial tracers released in a circulation model

The phytoplankton distribution off western Australia in the period from April to October is unique in that high biomass is generally associated with anticyclonic eddies and not with cyclonic eddies. As the western Australian region is oligotrophic this anomalous feature must be related to differing nutrient supply pathways to the surface mixed layer of cyclonic and anticyclonic eddies. A suite of modelled abiotic tracers suggests that cyclonic eddies are predominantly supplied by diapycnal processes that remain relatively weak until June–July, when they rapidly increase because of deepening surface mixed layers, which start to tap into the nutrient-replete waters below the euphotic zone. To the contrary, we find that anticyclonic eddies are predominantly supplied by injection of shelf waters, which carry elevated levels of inorganic nutrients and biomass. These injections start with the formation of the eddies in April–May, continue well into the austral winter and reach as far as several hundred kilometers offshore. The diapycnal supply of nutrients is suppressed in anticyclonic eddies since the injection of warm, low-salinity shelf waters delays the erosion of the density gradient at the base of the mixed layer. Our results are consistent with the observed seasonal cycles of chlorophyll a and observation of particulate organic matter export out of the surface mixed layer of an anticyclonic eddy in the region

Multiple packets of neutral molecules revolving for over a mile

The level of control that one has over neutral molecules in beams dictates their possible applications. Here we experimentally demonstrate that state-selected, neutral molecules can be kept together in a few mm long packet for a distance of over one mile. This is accomplished in a circular arrangement of 40 straight electrostatic hexapoles through which the molecules propagate over 1000 times. Up to 19 packets of molecules have simultaneously been stored in this ring structure. This brings the realization of a molecular low-energy collider within reach

Manufacturing Execution Systems and Business Intelligence for Production Environments

In the domain of production, Manufacturing Execution Systems (MES) are becoming increasingly popular. State of the art MES not only bring interfaces to a large variety of shop floor systems, they also come with functionality for data integration, data analysis, and dashboard generation – features commonly associated with Business Intelligence (BI) systems. At the same time, Data Warehouse (DHW) based BI infrastructures are increasingly extended to the support of operational managerial levels (Operational BI). This contribution sheds light on whether or not BI systems and MES are at odds and in how far they are complementary. To achieve this, two subsequent studies have been conducted: a case study based exploration and a quantitative online survey. The study results motivate an integration framework for MES and BI systems

Fidelity and level correlations in the transition from regularity to chaos

Mean fidelity amplitude and parametric energy--energy correlations are calculated exactly for a regular system, which is subject to a chaotic random perturbation. It turns out that in this particular case under the average both quantities are identical. The result is compared with the susceptibility of chaotic systems against random perturbations. Regular systems are more susceptible against random perturbations than chaotic ones.Comment: 7 pages, 1 figur

The k-Point Random Matrix Kernels Obtained from One-Point Supermatrix Models

The k-point correlation functions of the Gaussian Random Matrix Ensembles are certain determinants of functions which depend on only two arguments. They are referred to as kernels, since they are the building blocks of all correlations. We show that the kernels are obtained, for arbitrary level number, directly from supermatrix models for one-point functions. More precisely, the generating functions of the one-point functions are equivalent to the kernels. This is surprising, because it implies that already the one-point generating function holds essential information about the k-point correlations. This also establishes a link to the averaged ratios of spectral determinants, i.e. of characteristic polynomials

Structural Analysis to Determine the Core of Hypoxia Response Network

The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network's dynamics. The question that begs for an answer is how to identify the core that is representative of a network's dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent

Implementing an Insect Brain Computational Circuit Using III–V Nanowire Components in a Single Shared Waveguide Optical Network

Recent developments in photonics include efficient nanoscale optoelectronic components and novel methods for sub-wavelength light manipulation. Here, we explore the potential offered by such devices as a substrate for neuromorphic computing. We propose an artificial neural network in which the weighted connectivity between nodes is achieved by emitting and receiving overlapping light signals inside a shared quasi 2D waveguide. This decreases the circuit footprint by at least an order of magnitude compared to existing optical solutions. The reception, evaluation and emission of the optical signals are performed by a neuron-like node constructed from known, highly efficient III-V nanowire optoelectronics. This minimizes power consumption of the network. To demonstrate the concept, we build a computational model based on an anatomically correct, functioning model of the central-complex navigation circuit of the insect brain. We simulate in detail the optical and electronic parts required to reproduce the connectivity of the central part of this network, using experimentally derived parameters. The results are used as input in the full model and we demonstrate that the functionality is preserved. Our approach points to a general method for drastically reducing the footprint and improving power efficiency of optoelectronic neural networks, leveraging the superior speed and energy efficiency of light as a carrier of information.Comment: 28 pages, 6 figures; supplementary information 15 pages, 8 figure

Thermal roughening of an SOS-model with elastic interaction

We analyze the effects of a long-ranged step-step interaction on thermal roughening within the framework of a solid-on-solid model of a crystal surface by means of Monte Carlo simulation. A repulsive step-step interaction is modeled by elastic dipoles located on sites adjacent to the steps. In order to reduce the computational effort involved in calculating interaction energy based on long-ranged potentials, we employ a multi-grid scheme. As a result of the long-range character of the step interaction, the roughening temperature increases drastically compared to a system with short-range cutoff as a consequence of anti-correlations between surface defects