Landscape structure affects dispersal in the greater white-toothed shrew: inference between genetic and simulated ecological distances

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

The effect of 17-B estradiol therapy on bone mineral density and structure of alveolar bone in the ovariectomized rat model of postmenopausal osteoporosis

The ovariectomized (OVX) rat, a preclinical model for studying postmenopausal bone loss, may also be used to study differences in alveolar bone (AB). The objectives of this study were to quantify the differences in AB following estrogen replacement therapy (ERT), and to investigate the relationship between AB structure and density, and trabecular bone at the femoral neck (FN) and third lumbar vertebral body (LB3). Estrogen treated rats had a higher bone volume fraction (BV/TV) at the AB region (9.8% P < 0.0001), FN (12% P < 0.0001), and LB3 (11.5% P < 0.0001) compared to the OVX group. BV/TV of the AB was positively correlated with the BV/TV at the FN (r = 0.69 P < 0.0001) and the LB3 (r = 0.75 P < 0.0001). The trabecular number (Tb.N), trabecular separation (Tb.Sp), and structure model index (SMI) were also positively correlated (P < 0.05) between the AB and FN (r = 0.42, 0.49, and 0.73, respectfully) and between the AB and LB3 (r = 0.44, 0.63, and 0.69, respectfully). Given the capacity of AB to respond to ERT, future preclinical drug/nutritional intervention studies aimed at improving skeletal health should include the AB as a region of interest (ROI).

Model-Based Matching of Line Drawings by Linear Combinations of Prototypes

We describe a technique for finding pixelwise correspondences between two images by using models of objects of the same class to guide the search. The object models are 'learned' from example images (also called prototypes) of an object class. The models consist of a linear combination ofsprototypes. The flow fields giving pixelwise correspondences between a base prototype and each of the other prototypes must be given. A novel image of an object of the same class is matched to a model by minimizing an error between the novel image and the current guess for the closest modelsimage. Currently, the algorithm applies to line drawings of objects. An extension to real grey level images is discussed.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

Backward elimination model construction for regression and classification using leave-one-out criteria

A fundamental principle in practical nonlinear data modeling is the parsimonious principle of constructing the minimal model that explains the training data well. Leave-one-out (LOO) cross validation is often used to estimate generalization errors by choosing amongst different network architectures (M. Stone, "Cross validatory choice and assessment of statistical predictions", J. R. Stast. Soc., Ser. B, 36, pp. 117-147, 1974). Based upon the minimization of LOO criteria of either the mean squares of LOO errors or the LOO misclassification rate respectively, we present two backward elimination algorithms as model post-processing procedures for regression and classification problems. The proposed backward elimination procedures exploit an orthogonalization procedure to enable the orthogonality between the subspace as spanned by the pruned model and the deleted regressor. Subsequently, it is shown that the LOO criteria used in both algorithms can be calculated via some analytic recursive formula, as derived in this contribution, without actually splitting the estimation data set so as to reduce computational expense. Compared to most other model construction methods, the proposed algorithms are advantageous in several aspects; (i) There are no tuning parameters to be optimized through an extra validation data set; (ii) The procedure is fully automatic without an additional stopping criteria; and (iii) The model structure selection is directly based on model generalization performance. The illustrative examples on regression and classification are used to demonstrate that the proposed algorithms are viable post-processing methods to prune a model to gain extra sparsity and improved generalization.

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

Structure of luminescent mono and di-urethanesil nanocomposites doped with Eu3+ ions

A structure modeling of two families of sol-gel derived Eu3+-doped organic/inorganic hybrids based on the results of small-angle X-ray scattering experiments is reported. The materials are composed of poly(oxyethylene) chains grafted at one or both ends to siloxane groups and are called mono- and di-urethanesils, respectively. A theoretical function corresponding to a two-level hierarchical structure model fits well the experimental Scattering curves. The first level corresponds to small siloxane clusters embedded in a polymeric matrix. The secondary level is associated to the existence of siloxane cluster rich domains surrounded by a cluster-depleted polymeric matrix. Results show that increasing europium doping favors the growth of the secondary domains. (C) 2002 Elsevier B.V. B.V. All rights reserved.

The small x behavior of the gluon structure function from total cross-sections

Within a QCD-based eikonal model with a dynamical infrared gluon mass scale we discuss how the small x behavior of the gluon distribution function at moderate Q 2 is directly related to the rise of total hadronic cross-sections. In this model the rise of total cross-sections is driven by gluon-gluon semihard scattering processes, where the behavior of the small x gluon distribution function exhibits the power law xg(x, Q 2) = h(Q 2)x( -∈). Assuming that the Q 2 scale is proportional to the dynamical gluon mass one, we show that the values of h(Q 2) obtained in this model are compatible with an earlier result based on a specific nonperturbative Pomeron model. We discuss the implications of this picture for the behavior of input valence-like gluon distributions at low resolution scales. © 2008 World Scientific Publishing Company.

Structural investigation of Nb-based layer sulfides

In this work we have investigated the intercalation of electron-donors between NbS2 slabs in Nb-based layer sulfides. Two series of Sr substituted Nb-based misfit sulfides belonging to the 1.5Q/1H and 1Q/1H series of misfit layer compounds have been synthesised. For large lanthanides (Ln=La, Ce), only the 1Q/1H compounds formed whereas for smaller lanthanides and yttrium, both types of phases can be obtained. The crystal structure of misfit sulfide (Pr0.55Sr0.45S)1.15NbS2 has been refined using the composite approach. In the Q-slab, Pr-atoms are partly replaced by Sr with a random distribution over one cation position. The crystal structure of misfit sulfide [(Sm1/3Sr2/3S)1.5]1.15NbS2 belonging to the 1.5Q/1H series have also been determined. The obtained results suggest a preferred occupancy of the cation positions in the slab where Sr atoms mainly occupy positions on the exterior of the slab while Sm atoms are in the center of the slab. The (La1-xSrxS)1.15NbS2 solid solution (0.1<x<0.9) has also been studied. It was found that the maximum value of Sr substitution is 40-50% and therefore, the minimal value of charge transfer to stabilize this structure type is about 0.6ē per Nb atom. An attempt to synthesize SrxNbS2 (0.1≤x≤0.5) intercalates was made but single phases were not obtained and increasing the temperature from 1000оС to 1100оС leads to the decomposition of these intercalates. Single crystals of Sr0.22Nb1.05S2 and Sr0.23NbS2 were found and their structures were determined. The structures belong to two different types of packings with statistical distribution of Sr between layers. A new superconducting sulfide, "EuNb2S5", was investigated by ED and HREM and its structure model consisting of Nb7S14 and (Eu3S4)2 slabs alternating along the c-axis is suggested. An attempt to suggest a model for the structure of "SrNb2S5" by means of X-ray single crystal diffraction was made. The proposed structure consists of two types of slabs: a Nb7S14 and a [Sr6(NbS4)2S] slab with niobium in tetrahedral coordination. It is shown that "SrNb2S5" and "EuNb2S5" are have similar structures. For the first time, single crystals of the complex sulfide BaNb0.9S3 have also been studied by means of X-ray single crystal diffraction. The single crystal refinement and EDX analysis showed the existence of cation vacancies at the niobium position. BaNb0.9S3 has also been studied by ED and no superstructure was found which implies that and the vacancies are statistically distributed. No improvement of the magnetic properties of the studied compounds was observed in comparison to NbS2.

Investigating the Effects of Various Crowd Characteristics on the Dynamic Properties of an Occupied Structure

One of the challenges for structural engineers during design is considering how the structure will respond to crowd-induced dynamic loading. It has been shown that human occupants of a structure do not simply add mass to the system when considering the overall dynamic response of the system, but interact with it and may induce changes of the dynamic properties from those of the empty structure. This study presents an investigation into the human-structure interaction based on several crowd characteristics and their effect on the dynamic properties of an empty structure. The dynamic properties including frequency, damping, and mode shapes were estimated for a single test structure by means of experimental modal analysis techniques. The same techniques were utilized to estimate the dynamic properties when the test structure was occupied by a crowd with different combinations of size, posture, and distribution. The goal of this study is to isolate the occupant characteristics in order to determine the significance of each to be considered when designing new structures to avoid crowd serviceability issues. The results are presented and summarized based on the level of influence of each characteristic. The posture that produces the most significant effects based on the scope of this research is standing with bent knees with a maximum decrease in frequency of the first mode of the empty structure by 32 percent atthe highest mass ratio. The associated damping also increased 36 times the damping of the empty structure. In addition to the analysis of the experimental data, finite element models and a two degree-of-freedom model were created. These models were used to gain an understanding of the test structure, model a crowd as an equivalent mass, and also to develop a single degree-of-freedom (SDOF) model to best represent a crowd of occupants based on the experimental results. The SDOF models created had an averagefrequency of 5.0 Hz, within the range presented in existing biomechanics research, and combined SDOF systems of the test structure and crowd were able to reproduce the frequency and damping ratios associated with experimental tests. Results of this study confirmed the existence of human-structure interaction andthe inability to simply model a crowd as only additional mass. The two degree-offreedom model determined was able to predict the change in natural frequency and damping ratio for a structure occupied by multiple group sizes in a single posture. These results and model are the preliminary steps in the development of an appropriate methodfor modeling a crowd in combination with a more complex FE model of the empty structure.

Design-based stereology to quantify structural properties of artificial and natural snow using thin sections

The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

Agent-based model for the effect of curing temperature on cement hydration

The agent-based model presented here, comprises an algorithm that computes the degree of hydration, the water consumption and the layer thickness of C-S-H gel as functions of time for different temperatures and different w/c ratios. The results are in agreement with reported experimental studies, demonstrating the applicability of the model. As the available experimental results regarding elevated curing temperature are scarce, the model could be recalibrated in the future. Combining the agent-based computational model with TGA analysis, a semiempirical method is achieved to be used for better understanding the microstructure development in ordinary cement pastes and to predict the influence of temperature on the hydration process.

The influence of substrate kinetics on the microbial community structure in granular anaerobic biomass

The development of a strong, active granular sludge bed is necessary for optimal operation of upflow anaerobic sludge blanket reactors. The microbial and mechanical structure of the granules may have a strong influence on desirable properties such as growth rate, settling velocity and shear strength. Theories have been proposed for granule microbial structure based on the relative kinetics of substrate degradation, but contradict some observations from both modelling and microscopic studies. In this paper, the structures of four granule types were examined from full-scale UASB reactors, treating wastewater from a cannery, a slaughterhouse, and two breweries. Microbial structure was determined using fluorescence in situ hybridisation probing with 16S rRNA-directed oligonucleotide probes, and superficial structure and microbial density (volume occupied by cells and microbial debris) assessed using scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The granules were also modelled using a distributed parameter biofilm model, with a previously published biochemical model structure, biofilm modelling approach, and model parameters. The model results reflected the trophic structures observed, indicating that the structures were possibly determined by kinetics. Of particular interest were results from simulations of the protein grown granules, which were predicted to have slow growth rates, low microbial density, and no trophic layers, the last two of which were reflected by microscopic observations. The primary cause of this structure, as assessed by modelling, was the particulate nature of the wastewater, and the slow rate of particulate hydrolysis, rather than the presence of proteins in the wastewater. Because solids hydrolysis was rate limiting, soluble substrate concentrations were very low (below Monod half saturation concentration), which caused low growth rates. (C) 2003 Elsevier Ltd. All rights reserved.

A quasi-chemical viscosity model for fully liquid slags in the Al2O3-CaO-'FeO'-SiO2 system

A structurally based viscosity model for fully liquid silicate slags has been proposed and applied to the Al2O3-CaO-'FeO'-SiO2 system at metallic iron saturation. The model links the slag viscosity to the internal structure of melts through the concentrations of various anion/cation structural units (SUs). The concentrations of structural units are equivalent to the second nearest neighbor bond concentrations calculated by the quasi-chemical thermodynamic model. This viscosity model describes experimental data over the entire temperature and composition range within the Al2O3-CaO-'FeO'-SiO2 system at metallic iron saturation and can be extended to other industrial slag systems.