Robust banded protoxylem pattern formation through microtubule-based directional ROP diffusion restriction

A Novel Plasma Membrane-Anchored Protein Regulates Xylem Cell-Wall Deposition through Microtubule-Dependent Lateral Inhibition of Rho GTPase Domains

Anisotropic diffusion is widely used for noise reduction. The performance of anisotropic diffusion, in general, depends on the shape of the energy surface. The partial differential equation model is established and analyzed in the continuous domain while is implemented in the discrete domain. Therefore, the anisotropic diffusion bears some fuzziness due to the approximation. We present a novel noise removal algorithm based on fuzzy logic and anisotropic diffusion theory. The experimental results demonstrate that the proposed method has the advantage of maximizing noise reduction and preserving fine details of the images. In addition, the method can enhance the contrast of the images well.

The aim of the present study was to investigate a new type of Bayesian reconstruction method which utilizes partial differential equations (PDE) image models as a prior. PDE image models are very popular in image restoration and segmentation. Our method introduces such models to emission tomography reconstruction by using Bayesian one step late (OSL) algorithm and an OS acceleration one. In a PDE based model, the image can be viewed as the solution of an evolutionary differential equation. It can be thought as a descent of an energy function which entitled us to use PDE models in Bayesian reconstruction. In this paper, three different PDE models are studied, two of them are based on anisotropic diffusion model, and another is based on a complex diffusion model. All of them have the properties of edge-preserving and denoising as the latest median root prior (MRP). We validated the effectiveness of the method using a Zubal phantom in numerical experiments and compared it to the classical MLEM and MRP reconstruction. The results show that the proposed PDE model method is better than the MLEM and the MRP reconstruction methods in visualization, bias and variance, and are more suitable for OS acceleration than MRP.

We propose an innovative procedure for extracting decay regions from color images of stony materials. The use of appropriate image analysis techniques can offer an important contribution to be used together with the traditional methodologies for studying and diagnosing the decay of stony materials that constitute ancient monuments. The presented approach is constituted by the PDE (Partial Differential Equations) model of anisotropic diffusion and by the level set/fast marching method. The anisotropic diffusion is applied in order to limit the smoothing at the zones of high gradient. In the segmentation process, the numerical technique of the level set/fast marching is applied in order to extract from the image only the color region examined. The study case concerns impressive remains of the city of Aosta (Italy).

This review examines visually guided search behavior during walking in different species and developmental stages of insects having contrasting habitat utilization strategies. The discussion focuses on mantises, short-horned grasshoppers and crickets. Although generally short-horned grasshoppers are travelers, whereas mantises are ambush predators, all of these insects exhibit visually guided behavior during walking in the search for food sites and shelter. In crickets, which are central place foragers, visually guided behavior during walking is also important for nest site homing. Despite differences in habitat utilization, these three insect groups all use searches incorporating intermittent locomotion, where the distances traveled and duration of pauses have a distinct functional significance. However, there are also locomotion pattern variations, such as loops, zigzags, spiral patterns and straight lines. Search strategies during walking include searches with and without visual landmarks. The detection and recognition of stationary visual landmarks is based on self-induced retinal image displacement, with differing underlying neuronal mechanisms in the three insect groups. If a visual landmark is identified as a suitable target, a direct approach is elicited under either open- or closed-loop conditions, depending on the situation. In the presence of more than one suitable target object, the behavioral response can be temporarily restricted to stimuli associated with a particular area of the visual field, while information from other areas of the visual field is suppressed. The review concludes that there are gaps in knowledge concerning the various questions and thus further research is needed.

A high-order non field-aligned approach for the discretization of strongly anisotropic diffusion operators in magnetic fusion

Sodium polyanionic compounds with transition metals are of considerable research interest for the search of new cathode materials for sodium-ion batteries. In this work, we employed ab initio calculations to evaluate three key battery properties: phase stability, diffusion barriers and redox voltage of low-symmetry molybdates NaMFe(MoO4 )3 (M=Mg, Ni) with α- and β-NaFe2 (MoO4 )3 structures. First, we showed that the Hubbard Ucorrection within the GGA + Uapproach is necessary to correctly refer these molybdates to semiconductors. The sodium diffusion along various pathways was thoroughly examined, which allowed us to establish the most probable pathways with the lowest migration barriers. These compounds have different directions of sodium diffusion with twice different barriers that was associated to the peculiarities of their crystal structure. The high potentials and structural stability during sodium extraction, along with low-diffusion barriers predicted for NaMFe(MoO4 )3 (M=Mg, Ni) indicate that these molybdates may be promising high-voltage cathode materials for sodium-ion batteries.

Using a first-principles calculation method, we investigate the adsorption and diffusion of a Ag adatom on the H-terminated and clean Si(111) surface, which would be useful in understanding the initial stages of metal growth on semiconductor substrates. We perform extensive searches for metastable surface structures induced by the Ag adatom adsorption, and then find its diffusion barriers and pathways on both kinds of the substrates. The calculated barrier for the Ag atom on the H-terminated surface is only 0.14 eV. On the clean surface, the diffusion barriers inside a half\char21{}unit cell (HUC) and between HUC's are calculated at 0.27 and 0.88 eV, respectively. The present results provide a qualitative description of the Ag growth modes on the Si(111) surfaces: the three-dimensional island growth on the H-terminated surface and the formation of the wetting layer on the clean surface. In addition, the calculated barrier of 0.88 eV agrees well with the diffusion barrier measured by recent scanning-tunneling microscopy.

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities ('noise') inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this 'noisy' environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations ('noise') in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.

Many ecological systems exhibit self-organized spatial patterns due to local interactions. Such patterns can promote species diversity and therefore serve as an important mechanism for biodiversity maintenance. Previous work has shown that when species interactions occurred at local spatial scales, species diversity was greatest when robust mosaic spatial patterns formed. Also, intransitive interactions led to the emergence of spiral patterns, frequently resulting in multispecies coexistence. In some instances, intransitive interactions reduced species diversity as the consequence of competitive hierarchies. Here, we extend and broaden this line of investigation and examine the role of global competition along a continuum ranging from spatial mosaics to spiral patterns. While previous models have predicted that species diversity is reduced when interactions occur over larger spatial scales, our model considers the effects of various levels of mixing on species diversity, in the context of various network structures as measured by the covariance of row and column sums of the competition matrix. First, we compare local competition (unmixed system) versus global competition (mixed systems) and show that greater species diversity is maintained under a positive covariance. Second, we show that under various levels of mixing, species diversity declines more rapidly under a negative covariance. Lastly, we demonstrate that time to extinction in our model occurs much more rapidly under a negative covariance.

A new rapid auto-adapting diffusion function for adaptive anisotropic image de-noising and sharply conserved edges

Passive source localization in shallow water has always been an important and challenging problem. Implementing scientific research, surveying, and monitoring using a short, less than ten meter long, horizontal linear array has received considerable attention in the recent years. The short array can be conveniently placed on autonomous underwater vehicles and deployed for adaptive spatial sampling. However, it is usually difficult to obtain a sufficient spatial gain for localizing long-range sources due to its limited physical size. To address this problem, a localization approach is proposed which is based on matched-field processing of the likelihood of the passive source localization in shallow water, as well as inter-position processing for the improved localization performance and the enhanced stability of the estimation process. The ability of the proposed approach is examined through the two-dimensional synthetic test cases which involves ocean environmental mismatch and position errors of the short array. The presented results illustrate the localization performance for various source locations at different signal- to-noise ratios and demonstrate the build up over time of the positional parameters of the estimated source as the short array moves at a low speed along a straight line at a certain depth.

A region-based fuzzy shock filter with anisotropic diffusion is presented for image noise removal and edge sharpening. An image is divided into three-type different regions according to image features. For different regions, a binary shock-type backward diffusion or a fuzzy backward diffusion is performed in the gradient direction to the isophote line, incorporating a forward diffusion in the tangent direction. Gaussian smoothing to the second normal derivative results in a robust process against noise. Experiments on real images show that this method produces better visual results of the enhanced images than some related equations.

In this paper, we present a numerical technique for simplification of the texture of 3D maps. In the simplification process, we first select textures that can be segmented by straight lines using Hough transform. The selected texture images are simplified by the Hough transform. The other texture are filtered by the anisotropic diffusion and then the details are removed to reduce their data sizes. The representative colors of the image are chosen from the image, and the image is quantized based on those colors. The simplified image, with all major features of the original image preserved, has much smaller size as compared to the original.

After a brief review of recent modeling of growth during Pulsed Laser Deposition (PLD), we present the study of a role of adatom interactions on growth of surface islands during PLD in submonolayer regime. We employ kinetic Monte Carlo simulation with reversible growth, see e.g. [1]. Attachment of monomers to islands is irreversible at low temperatures while it becomes reversible at higher temperatures, small islands become unstable with growing temperature. In the case of real system we have to take into account not only diffusion of monomers but also diffusivity of dimers and larger clusters and theirs stability. Our new code allows us to study processes which proceed on different time scales which are typical in PLD experiments: fast deposition (on scale order of 10−5 s) during individual pulses, and relaxation of a system between pulses (on scale order of 0.1 s). We calculate and compare the temperature dependence of island density for two modes pulsed deposition and continuous Molecular Beam Epitaxy (MBE) growth. The island densities in PLD mode are substantially higher than in MBE mode, provided the temperature is sufficiently high. In the case of PLD, we observe anomalous temperature dependence of the island density in a certain temperature interval. It is due to the interplay between a cluster decay time and an interval between pulses. The cluster decay time depends not only on temperature but also on clusters size and shape. The anomalous behavior is caused by the temperature limited stability of the closed—compact clusters. This scenario was revealed for the simplified model with only nearest—neighbor interaction. Now, it is elucidated further and we also include interaction to second and third neighbors. We analyze role of the closed—compact surface island in kinetics of both growth modes. Furthermore, by varying interactions energies, diffusion barrier and parameters of deposition, we compare results of simulations with the PLD experiment for Fe/Mo system [2].