Impact of mass lumping on gravity and Rossby waves in 2D finite-element shallow-water models

The goal of this study is to evaluate the effect of mass lumping on the dispersion properties of four finite-element velocity/surface-elevation pairs that are used to approximate the linear shallow-water equations. For each pair, the dispersion relation, obtained using the mass lumping technique, is computed and analysed for both gravity and Rossby waves. The dispersion relations are compared with those obtained for the consistent schemes (without lumping) and the continuous case. The P0-P1, RT0 and P-P1 pairs are shown to preserve good dispersive properties when the mass matrix is lumped. Test problems to simulate fast gravity and slow Rossby waves are in good agreement with the analytical results.

A swarm intelligence method for feature tracking in AMV derivation

Feature tracking is a key step in the derivation of Atmospheric Motion Vectors (AMV). Most operational derivation processes use some template matching technique, such as Euclidean distance or cross-correlation, for the tracking step. As this step is very expensive computationally, often shortrange forecasts generated by Numerical Weather Prediction (NWP) systems are used to reduce the search area. Alternatives, such as optical flow methods, have been explored, with the aim of improving the number and quality of the vectors generated and the computational efficiency of the process. This paper will present the research carried out to apply Stochastic Diffusion Search, a generic search technique in the Swarm Intelligence family, to feature tracking in the context of AMV derivation. The method will be described, and we will present initial results, with Euclidean distance as reference.

Ocean acoustic models for low frequency propagation in 2D and 3D environments

In this paper we are mainly concerned with the development of efficient computer models capable of accurately predicting the propagation of low-to-middle frequency sound in the sea, in axially symmetric (2D) and in fully 3D environments. The major physical features of the problem, i.e. a variable bottom topography, elastic properties of the subbottom structure, volume attenuation and other range inhomogeneities are efficiently treated. The computer models presented are based on normal mode solutions of the Helmholtz equation on the one hand, and on various types of numerical schemes for parabolic approximations of the Helmholtz equation on the other. A new coupled mode code is introduced to model sound propagation in range-dependent ocean environments with variable bottom topography, where the effects of an elastic bottom, of volume attenuation, surface and bottom roughness are taken into account. New computer models based on finite difference and finite element techniques for the numerical solution of parabolic approximations are also presented. They include an efficient modeling of the bottom influence via impedance boundary conditions, they cover wide angle propagation, elastic bottom effects, variable bottom topography and reverberation effects. All the models are validated on several benchmark problems and versus experimental data. Results thus obtained were compared with analogous results from standard codes in the literature.

Application of Gaussian multi-scale representation to feature tracking in meteorological satellite imagery

Gaussian multi-scale representation is a mathematical framework that allows to analyse images at different scales in a consistent manner, and to handle derivatives in a way deeply connected to scale. This paper uses Gaussian multi-scale representation to investigate several aspects of the derivation of atmospheric motion vectors (AMVs) from water vapour imagery. The contribution of different spatial frequencies to the tracking is studied, for a range of tracer sizes, and a number of tracer selection methods are presented and compared, using WV 6.2 images from the geostationary satellite MSG-2.

From symmetry breaking to Poisson Point Process in 2D Voronoi Tessellations: the generic nature of hexagons

We bridge the properties of the regular triangular, square, and hexagonal honeycomb Voronoi tessellations of the plane to the Poisson-Voronoi case, thus analyzing in a common framework symmetry breaking processes and the approach to uniform random distributions of tessellation-generating points. We resort to ensemble simulations of tessellations generated by points whose regular positions are perturbed through a Gaussian noise, whose variance is given by the parameter α2 times the square of the inverse of the average density of points. We analyze the number of sides, the area, and the perimeter of the Voronoi cells. For all valuesα >0, hexagons constitute the most common class of cells, and 2-parameter gamma distributions provide an efficient description of the statistical properties of the analyzed geometrical characteristics. The introduction of noise destroys the triangular and square tessellations, which are structurally unstable, as their topological properties are discontinuous in α = 0. On the contrary, the honeycomb hexagonal tessellation is topologically stable and, experimentally, all Voronoi cells are hexagonal for small but finite noise withα <0.12. For all tessellations and for small values of α, we observe a linear dependence on α of the ensemble mean of the standard deviation of the area and perimeter of the cells. Already for a moderate amount of Gaussian noise (α >0.5), memory of the specific initial unperturbed state is lost, because the statistical properties of the three perturbed regular tessellations are indistinguishable. When α >2, results converge to those of Poisson-Voronoi tessellations. The geometrical properties of n-sided cells change with α until the Poisson- Voronoi limit is reached for α > 2; in this limit the Desch law for perimeters is shown to be not valid and a square root dependence on n is established. This law allows for an easy link to the Lewis law for areas and agrees with exact asymptotic results. Finally, for α >1, the ensemble mean of the cells area and perimeter restricted to the hexagonal cells agree remarkably well with the full ensemble mean; this reinforces the idea that hexagons, beyond their ubiquitous numerical prominence, can be interpreted as typical polygons in 2D Voronoi tessellations.

Temporally stable feature clusters for maritime object tracking in visible and thermal imagery

This paper describes a new approach to detect and track maritime objects in real time. The approach particularly addresses the highly dynamic maritime environment, panning cameras, target scale changes, and operates on both visible and thermal imagery. Object detection is based on agglomerative clustering of temporally stable features. Object extents are first determined based on persistence of detected features and their relative separation and motion attributes. An explicit cluster merging and splitting process handles object creation and separation. Stable object clus- ters are tracked frame-to-frame. The effectiveness of the approach is demonstrated on four challenging real-world public datasets.

Eye-tracking for avatar eye-gaze and interactional analysis in immersive collaborative virtual environments

Participants' eye-gaze is generally not captured or represented in immersive collaborative virtual environment (ICVE) systems. We present EyeCVE. which uses mobile eye-trackers to drive the gaze of each participant's virtual avatar, thus supporting remote mutual eye-contact and awareness of others' gaze in a perceptually unfragmented shared virtual workspace. We detail trials in which participants took part in three-way conferences between remote CAVE (TM) systems linked via EyeCVE. Eye-tracking data was recorded and used to evaluate interaction, confirming; the system's support for the use of gaze as a communicational and management resource in multiparty conversational scenarios. We point toward subsequent investigation of eye-tracking in ICVEs for enhanced remote social-interaction and analysis.

Room-acoustic factors in attentional tracking

In a “busy” auditory environment listeners can selectively attend to one of several simultaneous messages by tracking one listener's voice characteristics. Here we ask how well other cues compete for attention with such characteristics, using variations in the spatial position of sound sources in a (virtual) seminar room. Listeners decided which of two simultaneous target words belonged in an attended “context” phrase when it was played with a simultaneous “distracter” context that had a different wording. Talker difference was in competition with a position difference, so that the target‐word chosen indicates which cue‐type the listener was tracking. The main findings are that room‐acoustic factors provide some tracking cues, whose salience increases with distance separation. This increase is more prominent in diotic conditions, indicating that these cues are largely monaural. The room‐acoustic factors might therefore be the spectral‐ and temporal‐envelope effects of reverberation on the timbre of speech. By contrast, the salience of cues associated with differences in sounds' bearings tends to decrease with distance, and these cues are more effective in dichotic conditions. In other conditions, where a distance and a bearing difference cooperate, they can completely override a talker difference at various distances.

Study of optimization for cooperative motion between two humans in mutual tracking

Verbal communication is essential for human society and human civilization. Non-verbal communication, on the other hand, is more widely used not only by human but also other kind of animals, and the content of information is estimated even larger than the verbal communication. Among the non-verbal communication mutual motion is the simplest and easiest to study experimentally and analytically. We measured the power spectrum of the hand velocity in various conditions and clarified the following points on the feed-back and feed- forward mechanism as basic knowledge to understand the condition of good communication.

Single-particle tracking uncovers dynamics of glutamate-induced retrograde transport of NF-κB p65 in living neurons

Retrograde transport of NF-κB from the synapse to the nucleus in neurons is mediated by the dynein/dynactin motor complex and can be triggered by synaptic activation. The calibre of axons is highly variable ranging down to 100 nm, aggravating the investigation of transport processes in neurites of living neurons using conventional light microscopy. In this study we quantified for the first time the transport of the NF-κB subunit p65 using high-density single-particle tracking in combination with photoactivatable fluorescent proteins in living mouse hippocampal neurons. We detected an increase of the mean diffusion coefficient (Dmean) in neurites from 0.12 ± 0.05 µm2/s to 0.61 ± 0.03 µm2/s after stimulation with glutamate. We further observed that the relative amount of retrogradely transported p65 molecules is increased after stimulation. Glutamate treatment resulted in an increase of the mean retrograde velocity from 10.9 ± 1.9 to 15 ± 4.9 µm/s, whereas a velocity increase from 9 ± 1.3 to 14 ± 3 µm/s was observed for anterogradely transported p65. This study demonstrates for the first time that glutamate stimulation leads to an increased mobility of single NF-κB p65 molecules in neurites of living hippocampal neurons.

Measuring root traits in barley (Hordeum vulgare ssp vulgare and ssp spontaneum) seedlings using gel chambers, soil sacs and X-ray microtomography

Root characteristics of seedlings of five different barley genotypes were analysed in 2D using gel chambers, and in 3D using soil sacs that were destructively harvested and pots of soil that were assessed non-invasively using X-ray microtomography. After 5 days, Chime produced the greatest number of root axes (similar to 6) and Mehola significantly less (similar to 4) in all growing methods. Total root length was longest in GSH01915 and shortest in Mehola for all methods, but both total length and average root diameter were significantly larger for plants grown in gel chambers than those grown in soil. The ranking of particular growth traits (root number, root angular spread) of plants grown in gel plates, soil sacs and X-ray pots was similar, but plants grown in the gel chambers had a different order of ranking for root length to the soil-grown plants. Analysis of angles in soil-grown plants showed that Tadmore had the most even spread of individual roots and Chime had a propensity for non-uniform distribution and root clumping. The roots of Mehola were less well spread than the barley cultivars supporting the suggestion that wild and landrace barleys tend to have a narrower angular spread than modern cultivars. The three dimensional analysis of root systems carried out in this study provides insights into the limitations of screening methods for root traits and useful data for modelling root architecture.

A contour-advective semi-lagrangian numerical algorithm for simulating fine-scale conservative dynamical fields

This paper describes a novel numerical algorithm for simulating the evolution of fine-scale conservative fields in layer-wise two-dimensional flows, the most important examples of which are the earth's atmosphere and oceans. the algorithm combines two radically different algorithms, one Lagrangian and the other Eulerian, to achieve an unexpected gain in computational efficiency. The algorithm is demonstrated for multi-layer quasi-geostrophic flow, and results are presented for a simulation of a tilted stratospheric polar vortex and of nearly-inviscid quasi-geostrophic turbulence. the turbulence results contradict previous arguments and simulation results that have suggested an ultimate two-dimensional, vertically-coherent character of the flow. Ongoing extensions of the algorithm to the generally ageostrophic flows characteristic of planetary fluid dynamics are outlined.

Factors governing cellular convection in orographic precipitation

The development of shallow cellular convection in warm orographic clouds is investigated through idealized numerical simulations of moist flow over topography using a cloud-resolving numerical model. Buoyant instability, a necessary element for moist convection, is found to be diagnosed most accurately through analysis of the moist Brunt–Väisälä frequency (N_m) rather than the vertical profile of θ_e. In statically unstable orographic clouds (N_m^2) < 0), additional environmental and terrain-related factors are shown to have major effects on the amount of cellularity that occurs in 2D simulations. One of these factors, the basic-state wind shear, may suppress convection in 2D yet allow for longitudinal convective roll circulations in 3D. The presence of convective structures within an orographic cloud substantially enhanced the maximum rainfall rates, precipitation efficiencies, and precipitation accumulations in all simulations.