The population genetic structure of clonal organisms generated by exponentially bounded and fat-tailed dispersal

Long distance dispersal (LDD) plays an important role in many population processes like colonization, range expansion, and epidemics. LDD of small particles like fungal spores is often a result of turbulent wind dispersal and is best described by functions with power-law behavior in the tails ("fat tailed"). The influence of fat-tailed LDD on population genetic structure is reported in this article. In computer simulations, the population structure generated by power-law dispersal with exponents in the range of -2 to -1, in distinct contrast to that generated by exponential dispersal, has a fractal structure. As the power-law exponent becomes smaller, the distribution of individual genotypes becomes more self-similar at different scales. Common statistics like G(ST) are not well suited to summarizing differences between the population genetic structures. Instead, fractal and self-similarity statistics demonstrated differences in structure arising from fat-tailed and exponential dispersal. When dispersal is fat tailed, a log-log plot of the Simpson index against distance between subpopulations has an approximately constant gradient over a large range of spatial scales. The fractal dimension D-2 is linearly inversely related to the power-law exponent, with a slope of similar to -2. In a large simulation arena, fat-tailed LDD allows colonization of the entire space by all genotypes whereas exponentially bounded dispersal eventually confines all descendants of a single clonal lineage to a relatively small area.

Determination of the optical properties of plastic films used as cladding materials in novel energy efficient greenhouses

Greenhouse cladding materials are a major component in the design of energy efficient greenhouses. The optical properties of cladding materials determine a major part of the overall performance of a greenhouse both in terms of the energy balance of the greenhouse and on crop behavior. Various film plastic greenhouse-cladding materials were measured under laboratory conditions using a spectroradiometer equipped with an integrating sphere. Films were measured over a range of angles of incidence and the effect of increasing distance between double films was also measured. PAR transmission remained nearly constant for angles of incidence increased up to 30 degrees but fell rapidly thereafter as the angles of incidence increased up to 90 degrees. Increasing distance between double films did not significantly affect PAR transmission in all films examined. These results are discussed in relation to the design criteria for an energy efficient greenhouse.

Surface geometry of Cu{531}

We present a combined quantitative low-energy electron diffraction (LEED) and density-functional theory (DFT) study of the chiral Cu{531} surface. The surface shows large inward relaxations with respect to the bulk interlayer distance of the first two layers and a large expansion of the distance between the fourth and fifth layers. (The latter is the first layer having the same coordination as the Cu atoms in the bulk.) Additional calculations have been performed to study the likelihood of faceting by comparing surface energies of possible facet terminations. No overall significant reduction in energy with respect to planar {531} could be found for any of the tested combinations of facets, which is in agreement with the experimental findings.

Regulation of the neural circuitry of emotion by compassion meditation: effects of meditative expertise

Recent brain imaging studies using functional magnetic resonance imaging (fMRI) have implicated insula and anterior cingulate cortices in the empathic response to another's pain. However, virtually nothing is known about the impact of the voluntary generation of compassion on this network. To investigate these questions we assessed brain activity using fMRI while novice and expert meditation practitioners generated a loving-kindness-compassion meditation state. To probe affective reactivity, we presented emotional and neutral sounds during the meditation and comparison periods. Our main hypothesis was that the concern for others cultivated during this form of meditation enhances affective processing, in particular in response to sounds of distress, and that this response to emotional sounds is modulated by the degree of meditation training. The presentation of the emotional sounds was associated with increased pupil diameter and activation of limbic regions (insula and cingulate cortices) during meditation (versus rest). During meditation, activation in insula was greater during presentation of negative sounds than positive or neutral sounds in expert than it was in novice meditators. The strength of activation in insula was also associated with self-reported intensity of the meditation for both groups. These results support the role of the limbic circuitry in emotion sharing. The comparison between meditation vs. rest states between experts and novices also showed increased activation in amygdala, right temporo-parietal junction (TPJ), and right posterior superior temporal sulcus (pSTS) in response to all sounds, suggesting, greater detection of the emotional sounds, and enhanced mentation in response to emotional human vocalizations for experts than novices during meditation. Together these data indicate that the mental expertise to cultivate positive emotion alters the activation of circuitries previously linked to empathy and theory of mind in response to emotional stimuli.

Target integration and the attentional blink

If people monitor a visual stimulus stream for targets they often miss the second (T2) if it appears soon after the first (T1)-the attentional blink. There is one exception: T2 is often not missed if it appears right after T1, i.e., at lag 1. This lag-l sparing is commonly attributed to the possibility that T1 processing opens an attentional gate, which may be so sluggish that an early T2 can slip in before it closes. We investigated why the gate may close and exclude further stimuli from processing. We compared a control approach, which assumes that gate closing is exogenously triggered by the appearance of nontargets, and an integration approach, which assumes that gate closing is under endogenous control. As predicted by the latter but not the former, T2 performance and target reversals were strongly affected by the temporal distance between T1 and T2, whereas the presence or the absence of a nontarget intervening between T1 and T2 had little impact. (c) 2005 Elsevier B.V. All rights reserved.

Finding the point on Bezier Curves with the normal vector passing an external point

Two algorithms for finding the point on non-rational/rational Bezier curves of which the normal vector passes through a given external point are presented. The algorithms are based on Bezier curves generation algorithms of de Casteljau's algorithm for non-rational Bezier curve or Farin's recursion for rational Bezier curve, respectively. Orthogonal projections from the external point are used to guide the directional search used in the proposed iterative algorithms. Using Lyapunov's method, it is shown that each algorithm is able to converge to a local minimum for each case of non-rational/rational Bezier curves. It is also shown that on convergence the distance between the point on curves to the external point reaches a local minimum for both approaches. Illustrative examples are included to demonstrate the effectiveness of the proposed approaches.

The role of spectral- and temporal-envelope room-acoustic cues in auditory selective attention

Listeners can attend to one of several simultaneous messages by tracking one speaker’s voice characteristics. Using differences in the location of sounds in a room, we ask how well cues arising from spatial position compete with these characteristics. Listeners decided which of two simultaneous target words belonged in an attended “context” phrase when it was played simultaneously with a different “distracter” context. Talker difference was in competition with position difference, so the response indicates which cue‐type the listener was tracking. Spatial position was found to override talker difference in dichotic conditions when the talkers are similar (male). The salience of cues associated with differences in sounds, bearings decreased with distance between listener and sources. These cues are more effective binaurally. However, there appear to be other cues that increase in salience with distance between sounds. This increase is more prominent in diotic conditions, indicating that these cues are largely monaural. Distances between spectra calculated using a gammatone filterbank (with ERB‐spaced CFs) of the room’s impulse responses at different locations were computed, and comparison with listeners’ responses suggested some slight monaural loudness cues, but also monaural “timbre” cues arising from the temporal‐ and spectral‐envelope differences in the speech from different locations.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Dual-orthogonal radial basis function networks for nonlinear time series prediction

A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.

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.

Manipulating resource allocation in plants

The distribution of nutrients and assimilates in different organs and tissues is in a constant state of flux throughout the growth and development of a plant. At key stages during the life cycle profound changes occur, and perhaps one of the most critical of these is during seed filling. By restricting the competition for reserves in Arabidopsis plants, the ability to manipulate seed size, seed weight, or seed content has been explored. Removal of secondary inflorescences and lateral branches resulted in a stimulation of elongation of the primary inflorescence and an increase in the distance between siliques. The pruning treatment also led to the development of longer and larger siliques that contained fewer, bigger seeds. This seems to be a consequence of a reduction in the number of ovules that develop and an increase in the fatty acid content of the seeds that mature. The data show that shoot architecture could have a substantial impact on the partitioning of reserves between vegetative and reproductive tissues and could be an important trait for selection in rapid phenotyping screens to optimize crop performance.

On discrimination algorithms for ill-posed problems with an application to magnetic tomography

In this paper we explore classification techniques for ill-posed problems. Two classes are linearly separable in some Hilbert space X if they can be separated by a hyperplane. We investigate stable separability, i.e. the case where we have a positive distance between two separating hyperplanes. When the data in the space Y is generated by a compact operator A applied to the system states ∈ X, we will show that in general we do not obtain stable separability in Y even if the problem in X is stably separable. In particular, we show this for the case where a nonlinear classification is generated from a non-convergent family of linear classes in X. We apply our results to the problem of quality control of fuel cells where we classify fuel cells according to their efficiency. We can potentially classify a fuel cell using either some external measured magnetic field or some internal current. However we cannot measure the current directly since we cannot access the fuel cell in operation. The first possibility is to apply discrimination techniques directly to the measured magnetic fields. The second approach first reconstructs currents and then carries out the classification on the current distributions. We show that both approaches need regularization and that the regularized classifications are not equivalent in general. Finally, we investigate a widely used linear classification algorithm Fisher's linear discriminant with respect to its ill-posedness when applied to data generated via a compact integral operator. We show that the method cannot stay stable when the number of measurement points becomes large.

The spatial impact of visual distractors on saccade latency

Remote transient changes in the environment, such as the onset of visual distractors, impact on the exe- cution of target directed saccadic eye movements. Studies that have examined the latency of the saccade response have shown conflicting results. When there was an element of target selection, saccade latency increased as the distance between distractor and target increased. In contrast, when target selection is minimized by restricting the target to appear on one axis position, latency has been found to be slowest when the distractor is shown at fixation and reduces as it moves away from this position, rather than from the target. Here we report four experiments examining saccade latency as target and distractor posi- tions are varied. We find support for both a dependence of saccade latency on distractor distance from target and from fixation: saccade latency was longer when distractor is shown close to fixation and even longer still when shown in an opposite location (180°) to the target. We suggest that this is due to inhib- itory interactions between the distractor, fixation and the target interfering with fixation disengagement and target selection.

An analysis of the determinants of cross-border real estate development flows

This paper investigates the scale and drivers of cross-border real estate development in western and central and eastern Europe (CEE). Drawing upon existing literature on the integration of international real estate markets, we make some inferences on expected patterns of cross-border real estate development from this literature review. The paper draws upon a transactions database in order to assess the penetration of national markets by international real estate developers. The determinants of cross-border transaction flows are modeled as a function the range of economic and real estate variables. Whilst western European markets tend to be dominated by local developers, much higher levels of market penetration by international real estate developers are found in the less mature markets of central and eastern Europe. Empirical modelling based on gravity model specifications reveal the importance of size of the economies, distance between countries, extent of globalization and EU membership as significant determinants of cross-border real estate development flow.

Assessment of surface winds over the Atlantic, Indian and Pacific Ocean sectors of the Southern Ocean in CMIP5 models: historical bias, forcing response, and state dependence

An assessment of the fifth Coupled Models Intercomparison Project (CMIP5) models’ simulation of the near-surface westerly wind jet position and strength over the Atlantic, Indian and Pacific sectors of the Southern Ocean is presented. Compared with reanalysis climatologies there is an equatorward bias of 3.7° (inter-model standard deviation of ± 2.2°) in the ensemble mean position of the zonal mean jet. The ensemble mean strength is biased slightly too weak, with the largest biases over the Pacific sector (-1.6±1.1 m/s, 27 -22%). An analysis of atmosphere-only (AMIP) experiments indicates that 41% of the zonal mean position bias comes from coupling of the ocean/ice models to the atmosphere. The response to future emissions scenarios (RCP4.5 and RCP8.5) is characterized by two phases: (i) the period of most rapid ozone recovery (2000-2049) during which there is insignificant change in summer; and (ii) the period 2050-2098 during which RCP4.5 simulations show no significant change but RCP8.5 simulations show poleward shifts (0.30, 0.19 and 0.28°/decade over the Atlantic, Indian and Pacific sectors respectively), and increases in strength (0.06, 0.08 and 0.15 m/s/decade respectively). The models with larger equatorward position biases generally show larger poleward shifts (i.e. state dependence). This inter-model relationship is strongest over the Pacific sector (r=-0.89) and insignificant over the Atlantic sector (r=-0.50). However, an assessment of jet structure shows that over the Atlantic sector jet shift is significantly correlated with jet width whereas over the Pacific sector the distance between the sub-polar and sub-tropical westerly jets appears to be more important.