Engineering interactions for quasiperfect transfer of polariton states through nonideal bosonic networks of distinct topologies

We present a scheme for quasiperfect transfer of polariton states from a sender to a spatially separated receiver, both composed of high-quality cavities filled by atomic samples. The sender and the receiver are connected by a nonideal transmission channel -the data bus- modelled by a network of lossy empty cavities. In particular, we analyze the influence of a large class of data-bus topologies on the fidelity and transfer time of the polariton state. Moreover, we also assume dispersive couplings between the polariton fields and the data-bus normal modes in order to achieve a tunneling-like state transfer. Such a tunneling-transfer mechanism, by which the excitation energy of the polariton effectively does not populate the data-bus cavities, is capable of attenuating appreciably the dissipative effects of the data-bus cavities. After deriving a Hamiltonian for the effective coupling between the sender and the receiver, we show that the decay rate of the fidelity is proportional to a cooperativity parameter that weighs the cost of the dissipation rate against the benefit of the effective coupling strength. The increase of the fidelity of the transfer process can be achieved at the expense of longer transfer times. We also show that the dependence of both the fidelity and the transfer time on the network topology is analyzed in detail for distinct regimes of parameters. It follows that the data-bus topology can be explored to control the time of the state-transfer process.

Many-Body Effects on the rho(xx) Ringlike Structures in Two-Subband Wells

The longitudinal resistivity rho(xx) of two-dimensional electron gases formed in wells with two subbands displays ringlike structures when plotted in a density-magnetic-field diagram, due to the crossings of spin-split Landau levels (LLs) from distinct subbands. Using spin density functional theory and linear response, we investigate the shape and spin polarization of these structures as a function of temperature and magnetic-field tilt angle. We find that (i) some of the rings ""break'' at sufficiently low temperatures due to a quantum Hall ferromagnetic phase transition, thus exhibiting a high degree of spin polarization (similar to 50%) within, consistent with the NMR data of Zhang et al. [Phys. Rev. Lett. 98, 246802 (2007)], and (ii) for increasing tilting angles the interplay between the anticrossings due to inter-LL couplings and the exchange-correlation effects leads to a collapse of the rings at some critical angle theta(c), in agreement with the data of Guo et al. [Phys. Rev. B 78, 233305 (2008)].

Reverse engineering in many-body quantum physics: Correspondence between many-body systems and effective single-particle equations

The mapping, exact or approximate, of a many-body problem onto an effective single-body problem is one of the most widely used conceptual and computational tools of physics. Here, we propose and investigate the inverse map of effective approximate single-particle equations onto the corresponding many-particle system. This approach allows us to understand which interacting system a given single-particle approximation is actually describing, and how far this is from the original physical many-body system. We illustrate the resulting reverse engineering process by means of the Kohn-Sham equations of density-functional theory. In this application, our procedure sheds light on the nonlocality of the density-potential mapping of density-functional theory, and on the self-interaction error inherent in approximate density functionals.

Theoretical investigation of atomic and electronic structures of Ga(2)O(3)(ZnO)(6)

Transparent conducting oxides (TCO) are widely used in technological applications ranging from photovoltaics to thin-film transparent field-effect transistors. In this work we report a first-principles investigation, based on density-functional theory, of the atomic and electronic properties of Ga(2)O(3)(ZnO)(6) (GZO(6)), which is a promising candidate to be used as host oxide for wide band gap TCO applications. We identify a low-energy configuration for the coherent distribution of the Ga and Zn atoms in the cation positions within the experimentally reported orthorhombic GZO(6) structure. Four Ga atoms are located in four-fold sites, while the remaining 12 Ga atoms in the unit cell form four shared Ga agglomerates (a motif of four atoms). The Zn atoms are distributed in the remaining cation sites with effective coordination numbers from 3.90 to 4.50. Furthermore, we identify the natural formation of twin-boundaries in GZO(6), which can explain the zigzag modulations observed experimentally by high-resolution transmission electron microscopy in GZO(n) (n=9). Due to the intrinsic twin-boundary formation, polarity inversion in the ZnO tetrahedrons is present which is facilitated by the formation of the Ga agglomerates. Our analysis shows that the formation of fourfold Ga sites and Ga agglomerates are stabilized by the electronic octet rule, while the distribution of Ga atoms and the formation of the twin-boundary help alleviate excess strain. Finally we identify that the electronic properties of GZO(6) are essentially determined by the electronic properties of ZnO, i.e., there are slight changes in the band gap and optical absorption properties.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

On the k-restricted structure ratio in planar and outerplanar graphs

A planar k-restricted structure is a simple graph whose blocks are planar and each has at most k vertices. Planar k-restricted structures are used by approximation algorithms for Maximum Weight Planar Subgraph, which motivates this work. The planar k-restricted ratio is the infimum, over simple planar graphs H, of the ratio of the number of edges in a maximum k-restricted structure subgraph of H to the number edges of H. We prove that, as k tends to infinity, the planar k-restricted ratio tends to 1/2. The same result holds for the weighted version. Our results are based on analyzing the analogous ratios for outerplanar and weighted outerplanar graphs. Here both ratios tend to 1 as k goes to infinity, and we provide good estimates of the rates of convergence, showing that they differ in the weighted from the unweighted case.

Estimation of the thickness and the optical parameters of several stacked thin films using optimization

The reverse engineering problem addressed in the present research consists of estimating the thicknesses and the optical constants of two thin films deposited on a transparent substrate using only transmittance data through the whole stack. No functional dispersion relation assumptions are made on the complex refractive index. Instead, minimal physical constraints are employed, as in previous works of some of the authors where only one film was considered in the retrieval algorithm. To our knowledge this is the first report on the retrieval of the optical constants and the thickness of multiple film structures using only transmittance data that does not make use of dispersion relations. The same methodology may be used if the available data correspond to normal reflectance. The software used in this work is freely available through the PUMA Project web page (http://www.ime.usp.br/similar to egbirgin/puma/). (C) 2008 Optical Society of America

GEVREY SOLVABILITY AND GEVREY REGULARITY IN DIFFERENTIAL COMPLEXES ASSOCIATED TO LOCALLY INTEGRABLE STRUCTURES

In this work we study some properties of the differential complex associated to a locally integrable (involutive) structure acting on forms with Gevrey coefficients. Among other results we prove that, for such complexes, Gevrey solvability follows from smooth solvability under the sole assumption of a regularity condition. As a consequence we obtain the proof of the Gevrey solvability for a first order linear PDE with real-analytic coefficients satisfying the Nirenberg-Treves condition (P).

Bulk structures of PtO and PtO(2) from density functional calculations

Platinum plays an important role in catalysis and electrochemistry, and it is known that the direct interaction of oxygen with Pt surfaces can lead to the formation of platinum oxides (PtO(x)), which can affect the reactivity. To contribute to the atomistic understanding of the atomic structure of PtO(x), we report a density functional theory study of the atomic structure of bulk PtO(x) (1 <= x <= 2). From our calculations, we identified a lowest-energy structure (GeS type, space group Pnma) for PtO, which is 0.181 eV lower in energy than the structure suggested by W. J. Moore and L. Pauling [J. Am. Chem. Soc. 63, 1392 (1941)] (PtS type). Furthermore, two atomic structures were identified for PtO(2), which are almost degenerate in energy with the lowest-energy structure reported so far for PtO(2) (CaCl(2) type). Based on our results and analysis, we suggest that Pt and O atoms tend to form octahedron motifs in PtO(x) even at lower O composition by the formation of Pt-Pt bonds.

Influence of land-use change on near-surface hydrological processes: Undisturbed forest to pasture

Soil compaction that follows the clearing of tropical forest for cattle pasture is associated with lower soil hydraulic conductivity and increased frequency and volume of overland flow. We investigated the frequency of perched water tables, overland flow and stormflow in an Amazon forest and in an adjacent 25-year-old pasture cleared from the same forest. We compared the results with the frequencies of these phenomena estimated from comparisons of rainfall intensity and soil hydraulic conductivity. The frequency of perched water tables based on rainfall intensity and soil hydraulic conductivity was expected to double in pasture compared with forest. This corresponded closely with an approximate doubling of the frequency of stormflow and overland flow in pasture. In contrast, the stormflow volume in pasture increased 17-fold. This disproportional increase of stormflow resulted from overland flow generation over large areas of pasture, while overland flow generation in the forest was spatially limited and was observed only very near the stream channel. In both catchments, stormflow was generated by saturation excess because of perched water tables and near-surface groundwater levels. Stormflow was occasionally generated in the forest by rapid return flow from macropores, while slow return flow from a continuous perched water table was more common in the pasture. These results suggest that deforestation for pasture alters fundamental mechanisms of stormflow generation and may increase runoff volumes over wide regions of Amazonia. (C) 2009 Elsevier B.V. All rights reserved.

A scanning electron microscopic survey of the cuticle in Cyphophthalmi (Arachnida, Opiliones) with the description of novel sensory and glandular structures

The cuticular surfaces of Cyphophthalmi (Opiliones) were studied in detail, covering a wide range of their taxonomic diversity. Previously unknown structures are described, including a sexually dimorphic row of spines and glandular openings on leg I of Fangensis cavernarum. Scanning electron micrographs of the prosomal paired hairs and the subapical process are provided for the first time. Evidence for the multi-pored nature of the shaft of solenidia as well as the hollowed nature and absence of wall pores of sensilla chaetica are also shown for the first time using scanning electron microscopy. The prosomal paired hairs may constitute a novel autapomorphy for Cyphophthalmi, as they are absent in all studied members of the other species of Opiliones. Finally, the variation in shape of some of the structures examined may be of great taxonomic value.

Obtaining and stability verification of superconducting phases of the Nb-Al and Nb-Sn systems by mechanical alloying and low-temperature heat treatments

The development of Nb(3)Al and Nb(3)Sn superconductors is of great interest for the applied superconductivity area. These intermetallics composites are obtained normally by heat treatment reactions at high temperature. Processes that allow formation of the superconducting phases at lower temperatures (<1000 degrees C), particularly for Nb(3)Al, are of great interest. The present work studies phase formation and stability of Nb(3)Al and Nb(3)Sn superconducting phases using mechanical alloying (high energy ball milling). Our main objective was to form composites near stoichiometry, which could be transformed into the superconducting phases using low-temperature heat treatments. High purity Nb-Sn and Nb-Al powders were mixed to generate the required superconducting phases (Nb-25at.%Sn and Nb-25at.%Al) in an argon atmosphere glove-box. After milling in a Fritsch mill, the samples were compressed in a hydraulic uniaxial press and encapsulated in evacuated quartz tubes for heat treatment. The compressed and heat treated samples were characterized using X-ray diffractometry. Microstructure and chemical analysis were accomplished using scanning electron microscopy and energy dispersive spectrometry. Nb(3)Al XRD peaks were observed after the sintering at 800 degrees C for the sample milled for 30 h. Nb(3)Sn XRD peaks could be observed even before the heat treatment. (C) 2009 Elsevier B.V. All rights reserved.

Chemoenzymatic synthesis: a strategy to obtain xylitol monoesters

BACKGROUND: Fatty acid sugar esters are used as non-ionic surfactants in cosmetics, foodstuffs and pharmaceuticals. In particular, monoesters of xylitol have attracted industrial interest due to their outstanding biological activities. In this work, xylitol monoesters were obtained by chemoenzymatic synthesis, in which, first, xylitol was made soluble in organic solvent by chemo-protecting reaction, followed by enzymatic esterification reaction using different acyl donors. A commercial immobilized Candida antartica lipase was used as catalyst, and reactions with pure xylitol were carried out to generate data for comparison. RESULTS: t-BuOH was found to be the most suitable solvent to carry out esterification reactions with both pure and protected xylitol. The highest yields were obtained for reactions carried out with pure xylitol, but in this case by-products, such as di- and tri-esters isomers were formed, which required a multi-step purification process. For the systems with protected xylitol, conversions of 86%, 58% and 24% were achieved using oleic, lauric and butyric acids, respectively. The structures of the monoesters were confirmed by (13)C- and (1)H-NMR and microanalysis. CONCLUSION: The chemoenzymatic synthesis of xylitol monoesters avoided laborious downstream processing when compared with reactions performed with pure xylitol. Monoesters production from protected xylitol was shown to be a practical, economical, and clean route for this process, allowing a simple separation, because there are no other products formed besides xylitol monoesters and residual xylitol. (C) 2009 Society of Chemical Industry

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

A novel subwavelength plasmon-polariton optical filter based on tilted coupled structures

This work proposes a completely new approach for the design of resonant structures aiming at wavelength-filtering applications. The structure consists of a subwavelength metal-insulator-metal (MIM) waveguide presenting tilted coupled structures transversely arranged in the midpoint between the input and output ports. The cavity-like response of this device has shown that this concept can be particularly attractive for optical filter design for telecom applications. The extra degree of freedom provided by the tilting of the cavity has proved to be not only very effective on improving the quality factor of these structures, but also to be an elegant way of extending the range of applications for tuning multiple wavelengths, if necessary.