52 resultados para Spatial dynamic modeling


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Regional groundwater flow in high mountainous terrain is governed by a multitude of factors such as geology, topography, recharge conditions, structural elements such as fracturation and regional fault zones as well as man-made underground structures. By means of a numerical groundwater flow model, we consider the impact of deep underground tunnels and of an idealized major fault zone on the groundwater flow systems within the fractured Rotondo granite. The position of the free groundwater table as response to the above subsurface structures and, in particular, with regard to the influence of spatial distributed groundwater recharge rates is addressed. The model results show significant unsaturated zones below the mountain ridges in the study area with a thickness of up to several hundred metres. The subsurface galleries are shown to have a strong effect on the head distribution in the model domain, causing locally a reversal of natural head gradients. With respect to the position of the catchment areas to the tunnel and the corresponding type of recharge source for the tunnel inflows (i.e. glaciers or recent precipitation), as well as water table elevation, the influence of spatial distributed recharge rates is compared to uniform recharge rates. Water table elevations below the well exposed high-relief mountain ridges are observed to be more sensitive to changes in groundwater recharge rates and permeability than below ridges with less topographic relief. In the conceptual framework of the numerical simulations, the model fault zone has less influence on the groundwater table position, but more importantly acts as fast flow path for recharge from glaciated areas towards the subsurface galleries. This is in agreement with a previous study, where the imprint of glacial recharge was observed in the environmental isotope composition of groundwater sampled in the subsurface galleries. Copyright © 2012 John Wiley & Sons, Ltd.

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Proton imaging has become a common diagnostic technique for use in laser-plasma research experiments due to their ability to diagnose electric field effects and to resolve small density differences caused through shock effects. These interactions are highly dependent on the use of radiochromic film (RCF) as a detection system for the particle probe, and produces very high-resolution images. However, saturation effects, and in many cases, damage to the film limits the usefulness of this technique for high-flux particle probing. This paper outlines the use of a new technique using contact radiography of (p,n)-generated isotopes in activation samples to produce high dynamic range 2D images with high spatial resolution and extremely high dynamic range, whilst maintaining both energy resolution and absolute flux measurements. (C)007 Elsevier B.V. All rights reserved.

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Using the molecular-graphic complex Sybyl6.7.2, computational construction of spatial models for N-terminal domains (of NR1- and NR2B-subunits) of NMDA-receptor was conducted. On the basis of the constructed models and also CoMFA method the conclusion is made about presence of the binding site for the compounds similar to iphenprodyl in two N-terminal domains of NR1- and NR2B-subunits. The obtained data can be used for constructing new ligands.

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Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

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Spatial analysis was used to explore the distribution of individual species in an ectomycorrhizal (ECM) fungal community to address: whether mycorrhizas of individual ECM fungal species were patchily distributed, and at what scale; and what the causes of this patchiness might be. Ectomycorrhizas were extracted from spatially explicit samples of the surface organic horizons of a pine plantation. The number of mycorrhizas of each ECM fungal species was recorded using morphotyping combined with internal transcribed spacer (ITS) sequencing. Semivariograms, kriging and cluster analyses were used to determine both the extent and scale of spatial autocorrelation in species abundances, potential interactions between species, and change over time. The mycorrhizas of some, but not all, ECM fungal species were patchily distributed and the size of patches differed between species. The relative abundance of individual ECM fungal species and the position of patches of ectomycorrhizas changed between years. Spatial and temporal analysis revealed a dynamic ECM fungal community with many interspecific interactions taking place, despite the homogeneity of the host community. The spatial pattern of mycorrhizas was influenced by the underlying distribution of fine roots, but local root density was in turn influenced by the presence of specific fungal species.

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Dynamic switching spectroscopy piezoresponse force microscopy is developed to separate thermodynamic and kinetic effects in local bias-induced phase transitions. The approaches for visualization and analysis of five-dimensional data are discussed. The spatial and voltage variability of relaxation behavior of the a-c domain lead zirconate-titanate surface suggest the interpretation in terms of surface charge dynamics. This approach is applicable to local studies of dynamic behavior in any system with reversible bias-induced phase transitions ranging from ferroelectrics and multiferroics to ionic systems such as batteries, fuel cells, and electroresistive materials. (C) 2011 American Institute of Physics. [doi:10.1063/1.3590919]

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Emotion research has long been dominated by the “standard method” of displaying posed or acted static images of facial expressions of emotion. While this method has been useful it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correct statistical techniques that permit inferences to be made with such measures. We propose Generalized Additive Models and Generalized Additive Mixed Models as techniques that can account for the dynamic nature of such continuous measures. These models allow us to hold constant shared components of responses that are due to perceived emotion across time, while enabling inference concerning linear differences between groups. The mixed model GAMM approach is preferred as it can account for autocorrelation in time series data and allows emotion decoding participants to be modelled as random effects. To increase confidence in linear differences we assess the methods that address interactions between categorical variables and dynamic changes over time. In addition we provide comments on the use of Generalized Additive Models to assess the effect size of shared perceived emotion and discuss sample sizes. Finally we address additional uses, the inference of feature detection, continuous variable interactions, and measurement of ambiguity.

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Plant microtubules are intrinsically more dynamic than those from animals. We know little about the dynamics of the interaction of plant microtubule-associated proteins (MAPs) with microtubules. Here, we have used tobacco and Arabidopsis MAPs with relative molecular mass 65 kDa (NtMAP65-1a and AtMAP65-1), to study their interaction with microtubules in vivo. Using fluorescence recovery after photobleaching we report that the turnover of both NtMAP65-1a and AtMAP65-1 bound to microtubules is four- to fivefold faster than microtubule treadmilling (13 seconds compared with 56 seconds, respectively) and that the replacement of NtMAP65-1a on microtubules is by random association rather than by translocation along microtubules. MAP65 will only bind polymerised microtubules and not its component tubulin dimers. The turnover of NtMAP65-1a and AtMAP65-1 on microtubules is similar in the interphase cortical array, the preprophase band and the phragmoplast, strongly suggesting that their role in these arrays is the same. NtMAP65-1a and AtMAP65-1 are not observed to bind microtubules in the metaphase spindle and their rate of recovery is consistent with their cytoplasmic localisation. In addition, the dramatic reappearance of NtMAP65-1a on microtubules at the spindle midzone in anaphase B suggests that NtMAP65-1a is controlled post-translationally. We conclude that the dynamic properties of these MAPs in vivo taken together with the fact that they have been shown not to effect microtubule polymerisation in vitro, makes them ideally suited to a role in crossbridging microtubules that need to retain spatial organisation in rapidly reorganising microtubule arrays.

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Selective polypharmacology, where a drug acts on multiple rather than single molecular targets involved in a disease, emerges to develop a structure-based system biology approach to design drugs selectively targeting a disease-active protein network. We focus on the bioaminergic receptors that belong to the group of integral membrane signalling proteins coupled to the G protein and represent targets for therapeutic agents against schizophrenia and depression. Among them, it has been shown that the serotonin (5-HT2A and 5-HT6), dopamine (D2 and D3) receptors induce a cognition-enhancing effect (group 1), while the histamine (H1) and serotonin (5-HT2C) receptors lead to metabolic side effects and the 5-HT2B serotonin receptor causes pulmonary hypertension (group 2). Thus, the problem arises to develop an approach that allows identifying drugs targeting only the disease-active receptors, i.e. group 1. The recent release of several crystal structures of the bioaminergic receptors, involving the D3 and H1 receptors provides the possibility to model the structures of all receptors and initiate a study of the structural and dynamic context of selective polypharmacology. In this work, we use molecular dynamics simulations to generate a conformational space of the receptors and subsequently characterize its binding properties applying molecular probe mapping. All-against-all comparison of the generated probe maps of the selected diverse conformations of all receptors with the Tanimoto similarity coefficient (Tc) enable to separate the receptors of group 1 from group 2. The pharmacophore built based on the Tc-selected receptor conformations, using the multiple probe maps discovers structural features that can be used to design molecules selective towards the receptors of group 1. The importance of several predicted residues to ligand selectivity is supported by the available mutagenesis and ligand structure-activity relationships studies. In addition, the Tc-selected conformations of the receptors for group 1 show good performance in isolation of known ligands from a random decoy. Our computational structure-based protocol to tackle selective polypharmacology of antipsychotic drugs could be applied for other diseases involving multiple drug targets, such as oncologic and infectious disorders.

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In intelligent video surveillance systems, scalability (of the number of simultaneous video streams) is important. Two key factors which hinder scalability are the time spent in decompressing the input video streams, and the limited computational power of the processor. This paper demonstrates how a combination of algorithmic and hardware techniques can overcome these limitations, and significantly increase the number of simultaneous streams. The techniques used are processing in the compressed domain, and exploitation of the multicore and vector processing capability of modern processors. The paper presents a system which performs background modeling, using a Mixture of Gaussians approach. This is an important first step in the segmentation of moving targets. The paper explores the effects of reducing the number of coefficients in the compressed domain, in terms of throughput speed and quality of the background modeling. The speedups achieved by exploiting compressed domain processing, multicore and vector processing are explored individually. Experiments show that a combination of all these techniques can give a speedup of 170 times on a single CPU compared to a purely serial, spatial domain implementation, with a slight gain in quality.

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In highly heterogeneous aquifer systems, conceptualization of regional groundwater flow models frequently results in the generalization or negligence of aquifer heterogeneities, both of which may result in erroneous model outputs. The calculation of equivalence related to hydrogeological parameters and applied to upscaling provides a means of accounting for measurement scale information but at regional scale. In this study, the Permo-Triassic Lagan Valley strategic aquifer in Northern Ireland is observed to be heterogeneous, if not discontinuous, due to subvertical trending low-permeability Tertiary dolerite dykes. Interpretation of ground and aerial magnetic surveys produces a deterministic solution to dyke locations. By measuring relative permeabilities of both the dykes and the sedimentary host rock, equivalent directional permeabilities, that determine anisotropy calculated as a function of dyke density, are obtained. This provides parameters for larger scale equivalent blocks, which can be directly imported to numerical groundwater flow models. Different conceptual models with different degrees of upscaling are numerically tested and results compared to regional flow observations. Simulation results show that the upscaled permeabilities from geophysical data allow one to properly account for the observed spatial variations of groundwater flow, without requiring artificial distribution of aquifer properties. It is also found that an intermediate degree of upscaling, between accounting for mapped field-scale dykes and accounting for one regional anisotropy value (maximum upscaling) provides results the closest to the observations at the regional scale.

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Context. Bright points (BPs) are small-scale, magnetic features ubiquitous across the solar surface. Previously, we have observed and noted their properties for quiet Sun regions. Here, we determine the dynamic properties of BPs using simultaneous quiet Sun and active region data.

Aims. The aim of this paper is to compare the properties of BPs in both active and quiet Sun regions and to determine any difference in the dynamics and general properties of BPs as a result of the varying magnetic activity within these two regions.

Methods. High spatial and temporal resolution G-band observations of active region AR11372 were obtained with the Rapid Oscillations in the Solar Atmosphere instrument at the Dunn Solar Telescope. Three subfields of varying polarity and magnetic flux density were selected with the aid of magnetograms obtained from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Bright points within these subfields were subsequently tracked and analysed.

Results. It is found that BPs within active regions display attenuated velocity distributions with an average horizontal velocity of ~0.6 km s-1, compared to the quiet region which had an average velocity of 0.9 km s-1. Active region BPs are also ~21% larger than quiet region BPs and have longer average lifetimes (~132 s) than their quiet region counterparts (88 s). No preferential flow directions are observed within the active region subfields. The diffusion index (γ) is estimated at ~1.2 for the three regions.

Conclusions. We confirm that the dynamic properties of BPs arise predominately from convective motions. The presence of stronger field strengths within active regions is the likely reason behind the varying properties observed. We believe that larger amounts of magnetic flux will attenuate BP velocities by a combination of restricting motion within the intergranular lanes and by increasing the number of stagnation points produced by inhibited convection. Larger BPs are found in regions of higher magnetic flux density and we believe that lifetimes increase in active regions as the magnetic flux stabilises the BPs.

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Low-power processors and accelerators that were originally designed for the embedded systems market are emerging as building blocks for servers. Power capping has been actively explored as a technique to reduce the energy footprint of high-performance processors. The opportunities and limitations of power capping on the new low-power processor and accelerator ecosystem are less understood. This paper presents an efficient power capping and management infrastructure for heterogeneous SoCs based on hybrid ARM/FPGA designs. The infrastructure coordinates dynamic voltage and frequency scaling with task allocation on a customised Linux system for the Xilinx Zynq SoC. We present a compiler-assisted power model to guide voltage and frequency scaling, in conjunction with workload allocation between the ARM cores and the FPGA, under given power caps. The model achieves less than 5% estimation bias to mean power consumption. In an FFT case study, the proposed power capping schemes achieve on average 97.5% of the performance of the optimal execution and match the optimal execution in 87.5% of the cases, while always meeting power constraints.

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A constitutive equation was established to describe the deformation behavior of a nitride-strengthened (NS) steel through isothermal compression simulation test. All the parameters in the constitutive equation including the constant and the activation energy were precisely calculated for the NS steel. The result also showed that from the stress-strain curves, there existed two different linear relationships between critical stress and critical strain in the NS steel due to the augmentation of auxiliary softening effect of the dynamic strain-induced transformation. In the calculation of processing maps, with the change of Zener-Hollomon value, three domains of different levels of workability were found, namely excellent workability region with equiaxed-grain microstructure, good workability region with “stripe” microstructure, and the poor workability region with martensitic-ferritic blend microstructure. With the increase of strain, the poor workability region first expanded, then shrank to barely existing, but appeared again at the strain of 0.6.