A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation

The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites.

DTM generation from LIDAR data using skewness balancing

LIght Detection And Ranging (LIDAR) data for terrain and land surveying has contributed to many environmental, engineering and civil applications. However, the analysis of Digital Surface Models (DSMs) from complex LIDAR data is still challenging. Commonly, the first task to investigate LIDAR data point clouds is to separate ground and object points as a preparatory step for further object classification. In this paper, the authors present a novel unsupervised segmentation algorithm-skewness balancing to separate object and ground points efficiently from high resolution LIDAR point clouds by exploiting statistical moments. The results presented in this paper have shown its robustness and its potential for commercial applications.

Potential surfaces from vibration-rotation data

The problems of inverting experimental information obtained from vibration-rotation spectroscopy to determine the potential energy surface of a molecule are discussed, both in relation to semi-rigid molecules like HCN, NO2, H2CO, etc., and in relation to non-rigid or floppy molecules with large amplitude vibrations like HCNO, C3O2, and small ring molecules. Although standard methods exist for making the necessary calculations in the former case, they are complex, and they require an abundance of precise data on the spectrum that is rarely available. In the case of floppy molecules there are often data available over many excited states of the large amplitude vibration, but there are difficulties in knowing the precise form of the large amplitude coordinate(s), and in allowing for the vibrational averaging effects of the other modes. In both cases difficulties arise from the curvilinear nature of the vibrational paths which are not adequately handled by our present theories.

Regional response differences across the human amygdaloid complex during social conditioning

The amygdala is consistently implicated in biologically relevant learning tasks such as Pavlovian conditioning. In humans, the ability to identify individual faces based on the social outcomes they have predicted in the past constitutes a critical form of associative learning that can be likened to “social conditioning.” To capture such learning in a laboratory setting, participants learned about faces that predicted negative, positive, or neutral social outcomes. Participants reported liking or disliking the faces in accordance with their learned social value. During acquisition, we observed differential functional magnetic resonance imaging activation across the human amygdaloid complex consistent with previous lesion, electrophysiological, and functional neuroimaging data. A region of the medial ventral amygdala and a region of the dorsal amygdala/substantia innominata showed signal increases to both Negative and Positive faces, whereas a lateral ventral region displayed a linear representation of the valence of faces such that Negative > Positive > Neutral. This lateral ventral locus also differed from the dorsal and medial loci in that the magnitude of these responses was more resistant to habituation. These findings document a role for the human amygdala in social learning and reveal coarse regional dissociations in amygdala activity that are consistent with previous human and nonhuman animal data.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

A novel Bayesian approach to drug design with simple and complex enzymes: Use with lens aldehyde dehydrogenase and the glyoxalase pathway

Purpose: Acquiring details of kinetic parameters of enzymes is crucial to biochemical understanding, drug development, and clinical diagnosis in ocular diseases. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. Methods: We have developed Bayesian utility functions to minimise kinetic parameter variance involving differentiation of model expressions and matrix inversion. These have been applied to the simple kinetics of the enzymes in the glyoxalase pathway (of importance in posttranslational modification of proteins in cataract), and the complex kinetics of lens aldehyde dehydrogenase (also of relevance to cataract). Results: Our successful application of Bayesian statistics has allowed us to identify a set of rules for designing optimum kinetic experiments iteratively. Most importantly, the distribution of points in the range is critical; it is not simply a matter of even or multiple increases. At least 60 % must be below the KM (or plural if more than one dissociation constant) and 40% above. This choice halves the variance found using a simple even spread across the range.With both the glyoxalase system and lens aldehyde dehydrogenase we have significantly improved the variance of kinetic parameter estimation while reducing the number and costs of experiments. Conclusions: We have developed an optimal and iterative method for selecting features of design such as substrate range, number of measurements and choice of intermediate points. Our novel approach minimises parameter error and costs, and maximises experimental efficiency. It is applicable to many areas of ocular drug design, including receptor-ligand binding and immunoglobulin binding, and should be an important tool in ocular drug discovery.

Two new mu-(1,3-azido)-bridged polymers: alternating single and double bridges in a 1D nickel(II) complex and uniform bridge in a 2D copper(II) complex: Syntheses, single-crystal structures and magnetic studies

Two polymeric azido bridged complexes [Ni2L2(N-3)(3)](n)(ClO4). (1) and [Cu(bpdS)(2)(N-3)],(ClO4),(H2O)(2.5n) (2) [L = Schiff base, obtained from the condensation of pyridine-2-aldehyde with N,N,2,2-tetramethyl-1,3-propanediamine; bpds = 4,4'-bipyridyl disulfide] have been synthesized and their crystal structures have been determined. Complex 1, C26H42ClN15Ni2O4, crystallizes in a triclinic system, space group P1 with a 8.089(13), b = 9.392(14), c = 12.267(18) angstrom, a = 107.28(l), b 95.95(1), gamma = 96.92(1)degrees and Z = 2; complex 2, C20H21ClCuN7O6.5S4, crystallizes in an orthorhombic system, space group Pnna with a = 10.839(14), b = 13.208(17), c = 19.75(2) angstrom and Z = 4. The crystal structure of I consists of 1D polymers of nickel(L) units, alternatively connected by single and double bridging mu-(1,3-N-3) ligand with isolated perchlorate anions. Variable temperature magnetic susceptibility data of the complex have been measured and the fitting,of magnetic data was carried out applying the Borris-Almenar formula for such types of alternating one-dimensional S = 1 systems, based on the Hamiltonian H = -J Sigma(S2iS2i-1 + aS(2i)S(2i+1)). The best-fit parameters obtained are J = -106.7 +/- 2 cm(-1); a = 0.82 +/- 0.02; g = 2.21 +/- 0.02. Complex 2 is a 2D network of 4,4 topology with the nodes occupied by the Cu-II ions, and the edges formed by single azide and double bpds connectors. The perchlorate anions are located between pairs of bpds. The magnetic data have been fitted considering the complex as a pseudo-one-dimensional system, with all copper((II)) atoms linked by [mu(1,3-azido) bridging ligands at axial positions (long Cu...N-3 distances) since the coupling through long bpds is almost nil. The best-fit parameters obtained with this model are J = -1.21 +/- 0.2 cm(-1), g 2.14 +/- 0.02. (c) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005).

High-affinity small molecule-phospholipid complex formation: Binding of siramesine to phosphatidic acid

Siramesine (SRM) is a sigma-2 receptor agonist which has been recently shown to inhibit growth of cancer cells. Fluorescence spectroscopy experiments revealed two distinct binding sites for this drug in phospholipid membranes. More specifically, acidic phospholipids retain siramesine on the bilayer surface due to a high-affinity interaction, reaching saturation at an apparent 1:1 drug-acidic phospholipid stoichiometry, where after the drug penetrates into the hydrocarbon core of the membrane. This behavior was confirmed using Langmuir films. Of the anionic phospholipids, the highest affinity, comparable to the affinities for the binding of small molecule ligands to proteins, was measured for phosphatidic acid (PA, mole fraction Of X-PA = 0.2 in phosphatidylcholine vesicles), yielding a molecular partition coefficient of 240 +/- 80 x 10(6). An MD simulation on the siramesine:PA interaction was in agreement with the above data. Taking into account the key role of PA as a signaling molecule promoting cell growth our results suggest a new paradigm for the development of anticancer drugs, viz. design of small molecules specifically scavenging phospholipids involved in the signaling cascades controlling cell behavior.

Synthesis, structure and properties of a mononuclear and an end-on double azido-bridged copper(II) complex incorporating an N,N,N,O-coordinating tripodal ligand

The blue coloured complex [Cu(HL)(H2O)(ClO4)]ClO.H2O.MeOH (1.H2O.MeOH) has been synthesised in excellent yields by reacting Cu(ClO4)(2).6H(2)O with N,N-bis(2-methylpyridyl)(3,5-dimethyl-2-hydroxybenzyl)amine (HL) in methanol. The same reaction, when carried out in the presence of sodium azide, afforded a dark-blue complex of formula [Cu-2(HL)(2)(mu-1,1-N-3)(2)](ClO4)(2) (2). The crystal and molecular structures of the complexes have been solved. Variable-temperature magnetic susceptibility data in the range of 2-300 K for 2 reveal the existence of an antiferromagnetic interaction through an end-on azido linker. Temperature-dependent susceptibility studies for 2 were fitted using the Bleaney-Bowers expression, which led to the parameters J = -3.2 cm(-1), g = 2.12 and R = 2.14 x 10(-4). (C) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2004.

[Cr(C6H18N4)(SbS3)], a chromium complex containing an unusual bidentate SbS33- ligand

A new chromium-antimony-sulfide, [Cr(C6H18N4)(SbS3)], has been synthesised under solvothermal conditions from CrCl3. 6H(2)O, Sb2S3 and S in the presence of triethylenetetramine at 433 K and characterised by single-crystal X-ray diffraction, thermogravimetry, elemental analysis and SQUID magnetometry. The structure of [Cr(C6H18N4)(SbS3)] consists of neutral mononuclear chromium-centred complexes, in which the Cr3+ is chelated by one tetradentate triethylenetetramine molecule and a bidentate SbS33- ligand, yielding distorted octahedral coordination. Intermolecular hydrogen bonds link individual molecules into layers within the ac plane. Within a layer, molecules occur in pairs with each member related by a centre of inversion. The Cr...Cr separation within a pair is approximately 6.5 Angstrom. Magnetic susceptibility data reveal Curie-Weiss behaviour with mu(eff) = 3.819(3)/mu(B) and a negligible Weiss constant, indicative of non-interacting Cr3+ ions. (C) 2003 Elsevier Science Ltd. All rights reserved.

Mapping fibre orientation in complex-shaped biological systems with micrometre resolution by scanning X-ray microdiffraction

A fully automated procedure to extract and to image local fibre orientation in biological tissues from scanning X-ray diffraction is presented. The preferred chitin fibre orientation in the flow sensing system of crickets is determined with high spatial resolution by applying synchrotron radiation based X-ray microbeam diffraction in conjunction with advanced sample sectioning using a UV micro-laser. The data analysis is based on an automated detection of azimuthal diffraction maxima after 2D convolution filtering (smoothing) of the 2D diffraction patterns. Under the assumption of crystallographic fibre symmetry around the morphological fibre axis, the evaluation method allows mapping the three-dimensional orientation of the fibre axes in space. The resulting two-dimensional maps of the local fibre orientations - together with the complex shape of the flow sensing system - may be useful for a better understanding of the mechanical optimization of such tissues.

Knowledge-elicitation and data-mining: fusing human and industrial plant information

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process. (C) 2005 Elsevier Ltd. All rights reserved.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Solving surface structures from normal incidence X-ray standing wave data

A program is provided to determine structural parameters of atoms in or adsorbed on surfaces by refinement of atomistic models towards experimentally determined data generated by the normal incidence X-ray standing wave (NIXSW) technique. The method employs a combination of Differential Evolution Genetic Algorithms and Steepest Descent Line Minimisations to provide a fast, reliable and user friendly tool for experimentalists to interpret complex multidimensional NIXSW data sets.

A square-planar nickel(II) monoradical complex with a bis(salicylidene)diamine ligand

The new square-planar Ni-II-N2O2 complex [Ni(L-Me)] (1(Me)), where L-Me, stands for the dianionic phenolato form of N,N'bis(3,5-di-tert-butyl-salicylidene)-4,5-dimethyl-1,2-phenyl- enediamine ((LH2)-L-Me), has been synthesised and fully characterised. X-ray crystallography was also used for the characterisation. The electrochemical one-electron oxidation of 1(Me) produces the thermally stable (within the temperature range 10-295 K) cationic species (1(Me))(+). The UV/Vis and X-band EPR experimental data, supported by DFT calculations, indicate that (1(Me))(+), is best described as a Ni-II monoradical complex and, thus, does NOT exist in a Ni-III ground state, in contrast to its demethylated counterpart [Ni(L-H)](+) (1(H))(+) below 170 K.