78 resultados para computational geometry


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The dinuclear complex [{Ru(CN)4}2(μ-bppz)]4− shows a strongly solvent-dependent metal–metal electronic interaction which allows the mixed-valence state to be switched from class 2 to class 3 by changing solvent from water to CH2Cl2. In CH2Cl2 the separation between the successive Ru(II)/Ru(III) redox couples is 350 mVand the IVCT band (from the UV/Vis/NIR spectroelectrochemistry) is characteristic of a borderline class II/III or class III mixed valence state. In water, the redox separation is only 110 mVand the much broader IVCT transition is characteristic of a class II mixed-valence state. This is consistent with the observation that raising and lowering the energy of the d(π) orbitals in CH2Cl2 or water, respectively, will decrease or increase the energy gap to the LUMO of the bppz bridging ligand, which provides the delocalisation pathway via electron-transfer. IR spectroelectrochemistry could only be carried out successfully in CH2Cl2 and revealed class III mixed-valence behaviour on the fast IR timescale. In contrast to this, time-resolved IR spectroscopy showed that the MLCTexcited state, which is formulated as RuIII(bppz˙−)RuII and can therefore be considered as a mixed-valence Ru(II)/Ru(III) complex with an intermediate bridging radical anion ligand, is localised on the IR timescale with spectroscopically distinct Ru(II) and Ru(III) termini. This is because the necessary electron-transfer via the bppz ligand is more difficult because of the additional electron on bppz˙− which raises the orbital through which electron exchange occurs in energy. DFT calculations reproduce the electronic spectra of the complex in all three Ru(II)/Ru(II), Ru(II)/Ru(III) and Ru(III)/Ru(III) calculations in both water and CH2Cl2 well as long as an explicit allowance is made for the presence of water molecules hydrogen-bonded to the cyanides in the model used. They also reproduce the excited-state IR spectra of both [Ru(CN)4(μ-bppz)]2– and [{Ru(CN)4}2(μ-bppz)]4− very well in both solvents. The reorganization of the water solvent shell indicates a possible dynamical reason for the longer life time of the triplet state in water compared to CH2Cl2.

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Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

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A representation of the conformal mapping g of the interior or exterior of the unit circle onto a simply-connected domain Ω as a boundary integral in terms ofƒ|∂Ω is obtained, whereƒ :=g -l. A product integration scheme for the approximation of the boundary integral is described and analysed. An ill-conditioning problem related to the domain geometry is discussed. Numerical examples confirm the conclusions of this discussion and support the analysis of the quadrature scheme.

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The impact of ceiling geometries on the performance of lightshelves was investigated using physical model experiments and radiance simulations. Illuminance level and distribution uniformity were assessed for a working plane in a large space located in sub-tropical climate regions where innovative systems for daylighting and shading are required. It was found that the performance of the lightshelf can be improved by changing the ceiling geometry; the illuminance level increased in the rear of the room and decreased in the front near the window compared to rooms having conventional horizontal ceilings. Moreover, greater uniformity was achieved throughout the room as a result of reducing the difference in the illuminance level between the front and rear of the room. Radiance simulation results were found to be in good agreement with physical model data obtained under a clear sky and high solar radiation. The best ceiling shape was found to be one that is curved in the front and rear of the room.

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p-(Dimethylamino)phenyl pentazole, DMAP-N5 (DMAP = Me2N−C6H4), was characterized by picosecond transient infrared spectroscopy and infrared spectroelectrochemistry. Femtosecond laser excitation at 310 or 330 nm produces the DMAP-N5 (S1) excited state, part of which returns to the ground state (τ = 82 ± 4 ps), while DMAP-N and DMAP-N3 (S0) are generated as double and single N2-loss photoproducts with η ≈ 0.14. The lifetime of DMAP-N5 (S1) is temperature and solvent dependent. [DMAP-N3]+ is produced from DMAP-N5 in a quasireversible, one-electron oxidation process (E1/2 = +0.67 V). Control experiments with DMAP-N3 support the findings. DFT B3LYP/6-311G** calculations were used to identify DMAP-N5 (S1), DMAP-N3 +, and DMAP-N in the infrared spectra. Both DMAP-N5 (S1) and [DMAP-N5]+ have a weakened N5 ring structure.

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The electronic properties of four divinylanthracene-bridged diruthenium carbonyl complexes [{RuCl(CO)(PMe3)3}2(μ[BOND]CH[DOUBLE BOND]CHArCH[DOUBLE BOND]CH)] (Ar=9,10-anthracene (1), 1,5-anthracene (2), 2,6-anthracene (3), 1,8-anthracene (4)) obtained by molecular spectroscopic methods (IR, UV/Vis/near-IR, and EPR spectroscopy) and DFT calculations are reported. IR spectroelectrochemical studies have revealed that these complexes are first oxidized at the noninnocent bridging ligand, which is in line with the very small ν(C[TRIPLE BOND]O) wavenumber shift that accompanies this process and also supported by DFT calculations. Because of poor conjugation in complex 1, except oxidized 1+, the electronic absorption spectra of complexes 2+, 3+, and 4+ all display the characteristic near-IR band envelopes that have been deconvoluted into three Gaussian sub-bands. Two of the sub-bands belong mainly to metal-to-ligand charge-transfer (MLCT) transitions according to results from time-dependent DFT calculations. EPR spectroscopy of chemically generated 1+–4+ proves largely ligand-centered spin density, again in accordance with IR spectra and DFT calculations results.

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In recent years, computational fluid dynamics (CFD) has been widely used as a method of simulating airflow and addressing indoor environment problems. The complexity of airflows within the indoor environment would make experimental investigation difficult to undertake and also imposes significant challenges on turbulence modelling for flow prediction. This research examines through CFD visualization how air is distributed within a room. Measurements of air temperature and air velocity have been performed at a number of points in an environmental test chamber with a human occupant. To complement the experimental results, CFD simulations were carried out and the results enabled detailed analysis and visualization of spatial distribution of airflow patterns and the effect of different parameters to be predicted. The results demonstrate the complexity of modelling human exhalation within a ventilated enclosure and shed some light into how to achieve more realistic predictions of the airflow within an occupied enclosure.

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Adsorption of l-alanine on the Cu{111} single crystal surface was investigated as a model system for interactions between small chiral modifier molecules and close-packed metal surfaces. Synchrotron-based X-ray photoelectron spectroscopy (XPS) and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy are used to determine the chemical state, bond coordination and out-of-plane orientation of the molecule on the surface. Alanine adsorbs in its anionic form at room temperature, whilst at low temperature the overlayer consists of anionic and zwitterionic molecules. NEXAFS spectra exhibit a strong angular dependence of the π ⁎ resonance associated with the carboxylate group, which allows determining the tilt angle of this group with respect to the surface plane (48° ± 2°) at room temperature. Low-energy electron diffraction (LEED) shows a p(2√13x2√13)R13° superstructure with only one domain, which breaks the mirror symmetry of the substrate and, thus, induces global chirality to the surface. Temperature-programmed XPS (TP-XPS) and temperature-programmed desorption (TPD) experiments indicate that the zwitterionic form converts into the anionic species (alaninate) at 293 K. The latter desorbs/decomposes between 435 K and 445 K.

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Radar reflectivity measurements from three different wavelengths are used to retrieve information about the shape of aggregate snowflakes in deep stratiform ice clouds. Dual-wavelength ratios are calculated for different shape models and compared to observations at 3, 35 and 94 GHz. It is demonstrated that many scattering models, including spherical and spheroidal models, do not adequately describe the aggregate snowflakes that are observed. The observations are consistent with fractal aggregate geometries generated by a physically-based aggregation model. It is demonstrated that the fractal dimension of large aggregates can be inferred directly from the radar data. Fractal dimensions close to 2 are retrieved, consistent with previous theoretical models and in-situ observations.

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The idea of buildings in harmony with nature can be traced back to ancient times. The increasing concerns on sustainability oriented buildings have added new challenges in building architectural design and called for new design responses. Sustainable design integrates and balances the human geometries and the natural ones. As the language of nature, it is, therefore, natural to assume that fractal geometry could play a role in developing new forms of aesthetics and sustainable architectural design. This paper gives a brief description of fractal geometry theory and presents its current status and recent developments through illustrative review of some fractal case studies in architecture design, which provides a bridge between fractal geometry and architecture design.

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LRRK2 was identified in 2004 as the causative protein product of the Parkinson’s disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson’s disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson’s. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson’s disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkin- son’s disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation.

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A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion for the finite mixture model. Since the constraint on the mixing coefficients of the finite mixture model is on the multinomial manifold, we use the well-known Riemannian trust-region (RTR) algorithm for solving this problem. The first- and second-order Riemannian geometry of the multinomial manifold are derived and utilized in the RTR algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with an accuracy competitive with those of existing kernel density estimators.

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Anticipation is an emerging concept that can provide a bridge between the deepest philosophical theories about the nature of life and cognition on one hand and the empirical biological sciences steeped in reductionist and Newtonian conception of causality. Three conceptions of anticipation have been emerging from the literature that may be operationalised in a way leading to a viable empirical programme. The discussion of the research into a novel dynamical concept of anticipating synchronisation lends credence to such a possibility and suggests further links between the three anticipation paradigms. A careful progress mindful to the deep philosophical concerns but also respecting empirical evidence will ultimately lead towards unifying theoretical and empirical biological sciences and may offer progress where reductionist science have been so far faltering.