API-CALC 1.0: a computer program for calculating the average probability of identity allowing for substructure, inbreeding and the presence of close relatives

Individual identification via DNA profiling is important in molecular ecology, particularly in the case of noninvasive sampling. A key quantity in determining the number of loci required is the probability of identity (PIave), the probability of observing two copies of any profile in the population. Previously this has been calculated assuming no inbreeding or population structure. Here we introduce formulae that account for these factors, whilst also accounting for relatedness structure in the population. These formulae are implemented in API-CALC 1.0, which calculates PIave for either a specified value, or a range of values, for F-IS and F-ST.

Disease progression in heterosexual patients infected with closely related subtype B strains of HIV type 1 with differing coreceptor usage properties

Previously we described a heterosexual outbreak of HIV-1 subtype B in a town in the north of England (Doncaster) where 11 of 13 infections were shown to be linked by phylogenetic analysis of the env gp120 region. The 11 infections were related to a putative index case, Don1, and further divided into two groups based on the patients' disease status, their viral sequences, and other epidemiological information. Here we describe two further findings. First, we found that viral isolates and gp120 recombinant viruses derived from patients from one group used the CCR5 coreceptor, whereas viruses from the other group could use both the CCR5 and CXCR4 coreceptors. Patients with the X4/R5 dual tropic strains were symptomatic when diagnosed and progressed rapidly, in contrast to the other patient group that has remained asymptomatic, implying a link between the tropism of the strains and disease outcome. Second, we present additional sequence data derived from the index case, demonstrating the presence of sequences from both clades, with an average interclade distance of 9.56%, providing direct evidence of a genetic link between these two groups. This new study shows that Don1 harbored both strains, implying he was either dually infected or that over time intrahost diversification from the R5 to R5/X4 phenotype occurred. These events may account for/have led to the spread of two genetically related strains with different pathogenic properties within the same heterosexual community.

Perceptual grouping and distance estimates in typical and atypical development: comparing performance across perception, drawing and construction tasks

Perceptual grouping is a pre-attentive process which serves to group local elements into global wholes, based on shared properties. One effect of perceptual grouping is to distort the ability to estimate the distance between two elements. In this study, biases in distance estimates, caused by four types of perceptual grouping, were measured across three tasks, a perception, a drawing and a construction task in both typical development (TD: Experiment 1) and in individuals with Williams syndrome (WS: Experiment 2). In Experiment 1, perceptual grouping distorted distance estimates across all three tasks. Interestingly, the effect of grouping by luminance was in the opposite direction to the effects of the remaining grouping types. We relate this to differences in the ability to inhibit perceptual grouping effects on distance estimates. Additive distorting influences were also observed in the drawing and the construction task, which are explained in terms of the points of reference employed in each task. Experiment 2 demonstrated that the above distortion effects are also observed in WS. Given the known deficit in the ability to use perceptual grouping in WS, this suggests a dissociation between the pre-attentive influence of and the attentive deployment of perceptual grouping in WS. The typical distortion in relation to drawing and construction points towards the presence of some typical location coding strategies in WS. The performance of the WS group differed from the TD participants on two counts. First, the pattern of overall distance estimates (averaged across interior and exterior distances) across the four perceptual grouping types, differed between groups. Second, the distorting influence of perceptual grouping was strongest for grouping by shape similarity in WS, which contrasts to a strength in grouping by proximity observed in the TD participants. (c) 2008 Elsevier Inc. All rights reserved.

Communicating eye gaze across a distance without rooting participants to the spot

Eye gaze is an important conversational resource that until now could only be supported across a distance if people were rooted to the spot. We introduce EyeCVE, the worldpsilas first tele-presence system that allows people in different physical locations to not only see what each other are doing but follow each otherpsilas eyes, even when walking about. Projected into each space are avatar representations of remote participants, that reproduce not only body, head and hand movements, but also those of the eyes. Spatial and temporal alignment of remote spaces allows the focus of gaze as well as activity and gesture to be used as a resource for non-verbal communication. The temporal challenge met was to reproduce eye movements quick enough and often enough to interpret their focus during a multi-way interaction, along with communicating other verbal and non-verbal language. The spatial challenge met was to maintain communicational eye gaze while allowing free movement of participants within a virtually shared common frame of reference. This paper reports on the technical and especially temporal characteristics of the system.

Application of auto regressive models of wavelet sub-bands for classifying Terahertz pulse measurements

This paper presents an approach for automatic classification of pulsed Terahertz (THz), or T-ray, signals highlighting their potential in biomedical, pharmaceutical and security applications. T-ray classification systems supply a wealth of information about test samples and make possible the discrimination of heterogeneous layers within an object. In this paper, a novel technique involving the use of Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) models on the wavelet transforms of measured T-ray pulse data is presented. Two example applications are examined - the classi. cation of normal human bone (NHB) osteoblasts against human osteosarcoma (HOS) cells and the identification of six different powder samples. A variety of model types and orders are used to generate descriptive features for subsequent classification. Wavelet-based de-noising with soft threshold shrinkage is applied to the measured T-ray signals prior to modeling. For classi. cation, a simple Mahalanobis distance classi. er is used. After feature extraction, classi. cation accuracy for cancerous and normal cell types is 93%, whereas for powders, it is 98%.

The surface geometries of the medium and high coverage carbon monoxide structures c(2 × 4)–(2CO) and p(root7- x root7)R19°–(4CO) structure

The surface geometries of the p (root7- x root7)R19degrees-(4CO) and c(2 x 4)-(2CO) layers on Ni {111} and the clean Ni {111} surface were determined by low energy electron diffraction structure analysis. For the clean surface small but significant contractions of d(12) and d(23) (both 2.02 Angstrom) were found with respect to the bulk interlayer distance (2.03 Angstrom). In the c(2 x 4)-(2CO) structure these distances are expanded, with values of d(12) = 2.08 Angstrom and d(23) = 2.06 Angstrom and buckling of 0.08 and 0.02 Angstrom, respectively, in the first and second layer. CO resides near hcp and fcc hollow sites with relatively large lateral shifts away from the ideal positions leading to unequal C-Ni bond lengths between 1.76 and 1.99 Angstrom. For the p(root7- x root7-)R19'-(4CO) layer two best fit geometries were found, which agree in most of their atomic positions, except for one out of four CO molecules, which is either near atop or between bridge and atop. The remaining three molecules reside near hcp and fcc sites, again with large lateral deviations from their ideal positions. The average C Ni bond length for these molecules is, however, the same as for CO on hollow sites at low coverage. The average CNi bond length at hollow sites, the interlayer distances, and buckling in the first Ni layer are similar to the c(2 x 4)(2CO) geometry, only the buckling in the second layer (0.08 Angstrom) is significantly larger. Lateral and vertical shifts of the Ni atoms in the first layer lead to unsymmetric environments for the CO molecules, which can be regarded as an imprint of the chiral p(root7- x root7-)R19degrees lattice geometry onto the substrate.

Experimental measurement and numerical simulation of horizontal-coupled slinky ground source heat exchangers

Results from both experimental measurements and 3D numerical simulations of Ground Source Heat Pump systems (GSHP) at a UK climate are presented. Experimental measurements of a horizontal-coupled slinky GSHP were undertaken in Talbot Cottage at Drayton St Leonard site, Oxfordshire, UK. The measured thermophysical properties of in situ soil were used in the CFD model. The thermal performance of slinky heat exchangers for the horizontal-coupled GSHP system for different coil diameters and slinky interval distances was investigated using a validated 3D model. Results from a two month period of monitoring the performance of the GSHP system showed that the COP decreased with the running time. The average COP of the horizontal-coupled GSHP was 2.5. The numerical prediction showed that there was no significant difference in the specific heat extraction of the slinky heat exchanger at different coil diameters. However, the larger the diameter of coil, the higher the heat extraction per meter length of soil. The specific heat extraction also increased, but the heat extraction per meter length of soil decreased with the increase of coil central interval distance.

Computer generation and quantitative morphometric analysis of virtual neurons

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.

Analysis of spectroscopic measurements of leaf water content at terahertz frequencies using linear transforms

We provide a unified framework for a range of linear transforms that can be used for the analysis of terahertz spectroscopic data, with particular emphasis on their application to the measurement of leaf water content. The use of linear transforms for filtering, regression, and classification is discussed. For illustration, a classification problem involving leaves at three stages of drought and a prediction problem involving simulated spectra are presented. Issues resulting from scaling the data set are discussed. Using Lagrange multipliers, we arrive at the transform that yields the maximum separation between the spectra and show that this optimal transform is equivalent to computing the Euclidean distance between the samples. The optimal linear transform is compared with the average for all the spectra as well as with the Karhunen–Loève transform to discriminate a wet leaf from a dry leaf. We show that taking several principal components into account is equivalent to defining new axes in which data are to be analyzed. The procedure shows that the coefficients of the Karhunen–Loève transform are well suited to the process of classification of spectra. This is in line with expectations, as these coefficients are built from the statistical properties of the data set analyzed.