Adaptive resolution schemes allow the simulation of a molecular fluid treating simultaneously different subregions of the system at different levels of resolution. In this work we present a new scheme formulated in terms of a global Hamiltonian. Within this approach equilibrium states corresponding to well defined statistical ensembles can be generated making use of all standard Molecular Dynamics or Monte Carlo methods. Models at different resolutions can thus be coupled, and thermodynamic equilibrium can be modulated keeping each region at desired pressure or density without disrupting the Hamiltonian framework.

For simulation studies of (macro) molecular liquids it would be of significant interest to be able to adjust or increase the level of resolution within one region of space, while allowing for the free exchange of molecules between open regions of different resolution or representation. We generalize the adaptive resolution idea and suggest an interpretation in terms of an effective generalized grand canonical approach. The method is applied to liquid water at ambient conditions.

Abstract:The overarching goal of this research was to explore accurate methods of mapping irrigated crops, where digital cadastre information is unavailable: (a) Boundary separation by object-oriented image segmentation using very high spatial resolution (2.5-5 m) data was followed by (b) identification of crops and crop rotations by means of phenology, tasselled cap, and rule-based classification using high resolution (15-30 m) bi-temporal data. The extensive irrigated cotton production system of the Khorezm province in Uzbekistan, Central Asia, was selected as a study region. Image segmentation was carried out on pan-sharpened SPOT data. Varying combinations of segmentation parameters (shape, compactness, and color) were tested for optimized boundary separation. The resulting geometry was validated against polygons digitized from the data and cadastre maps, analysing similarity (size, shape) and congruence. The parameters shape and compactness were decisive for segmentation accuracy. Differences between crop phenologies were analyzed at field level using bi-temporal ASTER data. A rule set based on the tasselled cap indices greenness and brightness allowed for classifying crop rotations of cotton, winter-wheat and rice, resulting in an overall accuracy of 80 %. The proposed field-based crop classification method can be an important tool for use in water demand estimations, crop yield simulations, or economic models in agricultural systems similar to Khorezm. OPEN ACCESSRemote Sens. 2010, 2 1036

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For the example of C60 solutes in toluene, we present the implementation of the adaptive resolutions scheme (AdResS) for molecular simulations into GROMACS. In AdResS a local, typically all-atom cavity is coupled to a surrounding of coarse-grained, simplified molecules. This methodology can not only be used to reduce the CPU time demand of atomistic simulations but also to systematically investigate the relative influence of different interactions on structure formation. For this, we vary the thickness of the all atom layer of toluene around the C60 and analyze the first toluene layers in comparison to a full bulk simulation.

We outline a method to investigate the role of nuclear quantum effects in liquid water making use of a force field derived from ab initio simulations. Starting from a first-principles molecular dynamics simulation, we obtain an effective force field for bulk liquid water using the force-matching technique. After validating that our effective model reproduces the key structural and dynamic properties of the reference system, we use it to perform path integral simulations to investigate the role played by nuclear quantum effects on bulk water, probing radial distribution functions, vibrational spectra, and hydrogen bond fluctuations. Our approach offers a practical route to derive ab initio quality molecular models to study quantum effects at a low computational cost.

The proton-gated ion channel from Gloeobacter violaceus (GLIC) is a prokaryotic homolog of the eukaryotic nicotinic acetylcholine receptor that responds to the binding of neurotransmitter acetylcholine and mediates fast signal transmission. Recent emergence of a high-resolution crystal structure of GLIC captured in a potentially open state allowed detailed, atomic-level insight into ion conduction and selectivity mechanisms in these channels. Herein, we have examined the barriers to ion conduction and origins of ion selectivity in the GLIC channel by the construction of potential-of-mean-force profiles for sodium and chloride ions inside the transmembrane region. Our calculations reveal that the GLIC channel is open for a sodium ion to transport, but presents a ∼11 kcal/mol free energy barrier for a chloride ion. Our collective findings identify three distinct contributions to the observed preference for the permeant ions. First, there is a substantial contribution due to a ring of negatively charged glutamate residues (E-2') at the narrow intracellular end of the channel. The negative electrostatics of this region and the ability of the glutamate side chains to directly bind cations would strongly favor the passage of sodium ions while hindering translocation of chloride ions. Second, our results imply a significant hydrophobic contribution to selectivity linked to differences in the desolvation penalty for the sodium versus chloride ions in the central hydrophobic region of the pore. This hydrophobic contribution is evidenced by the large free energy barriers experienced by Cl⁻ in the middle of the pore for both GLIC and the E-2'A mutant. Finally, there is a distinct contribution arising from the overall negative electrostatics of the channel.

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