Deep levels in a-plane, high Mg-content MgxZn1-xO epitaxial layers grown by molecular beam epitaxy

Deep level defects in n-type unintentionally doped a-plane MgxZn1−xO, grown by molecular beam epitaxy on r-plane sapphire were fully characterized using deep level optical spectroscopy (DLOS) and related methods. Four compositions of MgxZn1−xO were examined with x = 0.31, 0.44, 0.52, and 0.56 together with a control ZnO sample. DLOS measurements revealed the presence of five deep levels in each Mg-containing sample, having energy levels of Ec − 1.4 eV, 2.1 eV, 2.6 V, and Ev + 0.3 eV and 0.6 eV. For all Mg compositions, the activation energies of the first three states were constant with respect to the conduction band edge, whereas the latter two revealed constant activation energies with respect to the valence band edge. In contrast to the ternary materials, only three levels, at Ec − 2.1 eV, Ev + 0.3 eV, and 0.6 eV, were observed for the ZnO control sample in this systematically grown series of samples. Substantially higher concentrations of the deep levels at Ev + 0.3 eV and Ec − 2.1 eV were observed in ZnO compared to the Mg alloyed samples. Moreover, there is a general invariance of trap concentration of the Ev + 0.3 eV and 0.6 eV levels on Mg content, while at least and order of magnitude dependency of the Ec − 1.4 eV and Ec − 2.6 eV levels in Mg alloyed samples

Fractal structure in the color distribution of natural images

The colorimetric organization of RGB color images is investigated through the computation of the correlation integral of their three-dimensional histogram. For natural color images, as a common behavior, the correlation integral is found to follow a power law, with a noninteger exponent characteristic of a given image. This behavior identifies a fractal or multiscale self-similar distribution of the colors contained in typical natural images. This finding of a possible fractal structure in the colorimetric organization of natural images complement other fractal properties previously observed in their spatial organization. Such fractal colorimetric properties may be helpful to the characterization and modeling of natural images, and may contribute to progress in vision

Analysis of Clean Transition Metal Surfaces by Core Level Spectroscopy

The shifts in the binding energy of core electrons detected by high resolution X-ray photoelectron spectroscopy are a very sensitive probe of the chemical bonding of the excited atom. Since the surface atoms have their geometrical environment perturbed, their core levels are shifted from their bulk positions. A very large number of experiments have been performed on the 4f core level positions of tantalum and tungsten for various orientations of the surface plane. Systematic trends have been put forward and explained by theoretical models. Furthermore, the analysis of the angular variation of the core level line intensities gives structural information when compared with theoretical calculations. In the case of W(100) a single scattering theory is sufficient to reproduce experimental data. Finally we show that, in some particular cases, the core level lineshapes may differ strongly from a Doniach Sunjic model. The temperature dependence of their widths due to core hole-phonon coupling can be reproduced within the independent boson theory

Demonstrating the decoupling regime of the electron-phonon interaction in a quantum dot using chirped optical excitation

Excitation of a semiconductor quantum dot with a chirped laser pulse allows excitons to be created by rapid adiabatic passage. In quantum dots this process can be greatly hindered by the coupling to phonons. Here we add a high chirp rate to ultra-short laser pulses and use these pulses to excite a single quantum dot. We demonstrate that we enter a regime where the exciton-phonon coupling is effective for small pulse areas, while for higher pulse areas a decoupling of the exciton from the phonons occurs. We thus discover a reappearance of rapid adiabatic passage, in analogy to the predicted reappearance of Rabi rotations at high pulse areas. The measured results are in good agreement with theoretical calculations.Comment: Main manuscript 5 pages and 4 figures, Supplementary Information 5 pages and 3 figures, submitted to PR

Differential selection pressures exerted by host resistance quantitative trait loci on a pathogen population: a case study in an apple × Venturia inaequalis pathosystem

Understanding how pathogens evolve according to pressures exerted by their plant hosts is essential for the derivation of strategies aimed at the durable management of resistant cultivars. The spectrum of action of the resistance factors in the partially resistant cultivars is thought to be an important determinant of resistance durability. However, it has not yet been demonstrated whether the pressures exerted by quantitative resistance are different according to their spectrum of action.To investigate selection pressures exerted by apple genotypes harbouring various resistance quantitative trait loci (QTLs) on a mixed inoculum of the scab disease agent, Venturia inaequalis, we monitored V. inaequalis isolate proportions on diseased apple leaves of an F1 progeny using quantitative pyrosequencing technology and QTL mapping. Broad-spectrum resistances did not exert any differential selection pressures on the mixed inoculum, whereas narrow-spectrum resistances decreased the frequencies of some isolates in the mixture relative to the susceptible host genotypes. Our results suggest that the management of resistant cultivars should be different according to the spectrum of action of their resistance factors. The pyramiding of broad-spectrum factors or the use of a mixture of apple genotypes that carry narrow-spectrum resistance factors are two possible strategies for the minimization of resistance erosion

Fractal capacity dimension of three-dimensional histogram from color images

To contribute to the important task of characterizing the complex multidimensional structure of natural images, a fractal characterization is proposed for the colorimetric organization of natural color images. This is realized from their three-dimensional RGB color histogram, by applying a box-counting procedure to assess the dimensionality of its support. Regular scaling emerges, almost linear over the whole range of accessible scales, and with non-integer slope in log-log allowing the definition of a capacity dimension for the histogram. This manifests a fractal colorimetric organization with a self-similar structure of the color palette typically composing natural images. Such a fractal characterization complements other previously known fractal properties of natural images, some reported recently in their colorimetric organization, and others reported more classically in their spatial organization. Such fractal multiscale features uncovered in natural images provide helpful clues relevant to image modeling, processing and visual perception

Multifractal analysis of three-dimensional histogram from color images

Natural images, especially color or multicomponent images, are complex information-carrying signals. To contribute to the characterization of this complexity, we investigate the possibility of multiscale organization in the colorimetric structure of natural images. This is realized by means of a multifractal analysis applied to the three-dimensional histogram from natural color images. The observed behaviors are confronted to those of reference models with known multifractal properties. We use for this purpose synthetic random images with trivial monofractal behavior, and multidimensional multiplicative cascades known for their actual multifractal behavior. The behaviors observed on natural images exhibit similarities with those of the multifractal multiplicative cascades and display the signature of elaborate multiscale organizations stemming from the histograms of natural color images. This type of characterization of colorimetric properties can be helpful to various tasks of digital image processing, as for instance modeling, classification, indexing

Fractal analysis tools for characterizing the colorimetric organization of digital image

The colorimetric organization of RGB color images is analyzed through the computation of algorithms which can characterize fractal organizations in the support and population of their three-dimensional color histogram. These algorithms have shown that complex organizations across scales exist in the colorimetric domain for natural images with often non-integer fractal dimension over a certain range of scale. In this paper, we applythis method of colorimetric characterization to synthetic images produced by rendering techniques of increasing sophistication. We show that the fractal or scale invariant signatures are more pronounced when the realism of the synthetic images increases. Such results could have interesting applications to improve the colorimetric realism of synthetic images. This also may contribute to progress in classification and vision, in using fractal colorimetric properties to differentiate natural and synthetic images

In situ relationships between microbiota and potential pathobiota in Arabidopsis thaliana.

A current challenge in microbial pathogenesis is to identify biological control agents that may prevent and/or limit host invasion by microbial pathogens. In natura, hosts are often infected by multiple pathogens. However, most of the current studies have been performed under laboratory controlled conditions and by taking into account the interaction between a single commensal species and a single pathogenic species. The next step is therefore to explore the relationships between host-microbial communities (microbiota) and microbial members with potential pathogenic behavior (pathobiota) in a realistic ecological context. In the present study, we investigated such relationships within root-associated and leaf-associated bacterial communities of 163 ecologically contrasted Arabidopsis thaliana populations sampled across two seasons in southwest of France. In agreement with the theory of the invasion paradox, we observed a significant humped-back relationship between microbiota and pathobiota α-diversity that was robust between both seasons and plant organs. In most populations, we also observed a strong dynamics of microbiota composition between seasons. Accordingly, the potential pathobiota composition was explained by combinations of season-specific microbiota operational taxonomic units. This result suggests that the potential biomarkers controlling pathogen\u27s invasion are highly dynamic