The tangential variation of a localized flux-type eigenvalue problem

In this work the differentiability of the principal eigenvalue lambda = lambda(1)(Gamma) to the localized Steklov problem -Delta u + qu = 0 in Omega, partial derivative u/partial derivative nu = lambda chi(Gamma)(x)u on partial derivative Omega, where Gamma subset of partial derivative Omega is a smooth subdomain of partial derivative Omega and chi(Gamma) is its characteristic function relative to partial derivative Omega, is shown. As a key point, the flux subdomain Gamma is regarded here as the variable with respect to which such differentiation is performed. An explicit formula for the derivative of lambda(1) (Gamma) with respect to Gamma is obtained. The lack of regularity up to the boundary of the first derivative of the principal eigenfunctions is a further intrinsic feature of the problem. Therefore, the whole analysis must be done in the weak sense of H(1)(Omega). The study is of interest in mathematical models in morphogenesis. (C) 2011 Elsevier Inc. All rights reserved.

Nonlocal growth processes and conformal invariance

Up to now the raise-and-peel model was the single known example of a one-dimensional stochastic process where one can observe conformal invariance. The model has one parameter. Depending on its value one has a gapped phase, a critical point where one has conformal invariance, and a gapless phase with changing values of the dynamical critical exponent z. In this model, adsorption is local but desorption is not. The raise-and-strip model presented here, in which desorption is also nonlocal, has the same phase diagram. The critical exponents are different as are some physical properties of the model. Our study suggests the possible existence of a whole class of stochastic models in which one can observe conformal invariance.

Using complex networks to quantify consistency in the use of words

In this paper we have quantified the consistency of word usage in written texts represented by complex networks, where words were taken as nodes, by measuring the degree of preservation of the node neighborhood. Words were considered highly consistent if the authors used them with the same neighborhood. When ranked according to the consistency of use, the words obeyed a log-normal distribution, in contrast to Zipf's law that applies to the frequency of use. Consistency correlated positively with the familiarity and frequency of use, and negatively with ambiguity and age of acquisition. An inspection of some highly consistent words confirmed that they are used in very limited semantic contexts. A comparison of consistency indices for eight authors indicated that these indices may be employed for author recognition. Indeed, as expected, authors of novels could be distinguished from those who wrote scientific texts. Our analysis demonstrated the suitability of the consistency indices, which can now be applied in other tasks, such as emotion recognition.

Exploration of the parameter space in an agent-based model of tuberculosis spread: emergence of drug resistance in developing vs developed countries

In this work we present an agent-based model for the spread of tuberculosis where the individuals can be infected with either drug-susceptible or drug-resistant strains and can also receive a treatment. The dynamics of the model and the role of each one of the parameters are explained. The whole set of parameters is explored to check their importance in the numerical simulation results. The model captures the beneficial impact of the adequate treatment on the prevalence of tuberculosis. Nevertheless, depending on the treatment parameters range, it also captures the emergence of drug resistance. Drug resistance emergence is particularly likely to occur for parameter values corresponding to less efficacious treatment, as usually found in developing countries.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Magnetic fabric of Araguainha complex impact structure (Central Brazil): Implications for deformation mechanisms and central uplift formation

The weakening mechanisms involved in the collapse of complex impact craters are controversial. The Araguainha impact crater, in Brazil, exposes a complex structure of 40 km in diameter, and is an excellent object to address this issue. Its core is dominated by granite. In addition to microstructural observations, magnetic studies reveal its internal fabric acquired during the collapse phase. All granite samples exhibit impact-related planar deformation features (PDFs) and planar fractures (PFs), which were overprinted by cataclasis. Cataclastic deformation has evolved from incipient brittle fracturing to the development of discrete shear bands in the center of the structure. Fracture planes are systematically decorated by tiny grains (<10 mu m) of magnetite and hematite, and the orientation of magnetic lineation and magnetic foliation obtained by the anisotropies of magnetic susceptibility (AMS) and anhysteretic remanence (AAR) are perfectly coaxial in all studied sites. Therefore, we could track the orientation of deformation features which are decorated by iron oxides using the AMS and AAR. The magnetic fabrics show a regular pattern at the borders of the central peak, with orientations consistent with the fabric of sediments at the crater's inner collar and complex in the center of the structure. Both the cataclastic flow revealed from microstructural observations and the structural pattern of the magnetic anisotropy match the predictions from numerical models of complex impact structures. The widespread occurrence of cataclasis in the central peak, and its orientations revealed by magnetic studies indicate that acoustic fluidization likely operates at all scales, including the mineral scales. The cataclastic flow made possible by acoustic fluidization results in an apparent plastic deformation at the macroscopic scale in the core. (C) 2012 Elsevier B.V. All rights reserved.

RGMa and RGMb expression pattern during chicken development suggest unexpected roles for these repulsive guidance molecules in notochord formation, somitogenesis, and myogenesis

Background: Repulsive guidance molecules (RGM) are high-affinity ligands for the Netrin receptor Neogenin, and they are crucial for nervous system development including neural tube closure; neuronal and neural crest cell differentiation and axon guidance. Recent studies implicated RGM molecules in bone morphogenetic protein signaling, which regulates a variety of developmental processes. Moreover, a role for RGMc in iron metabolism has been established. This suggests that RGM molecules may play important roles in non-neural tissues. Results: To explore which tissues and processed may be regulated by RGM molecules, we systematically investigated the expression of RGMa and RGMb, the only RGM molecules currently known for avians, in the chicken embryo. Conclusions: Our study suggests so far unknown roles of RGM molecules in notochord, somite and skeletal muscle development. Developmental Dynamics, 2012. (C) 2012 Wiley Periodicals, Inc.

The star formation rate in the inner Milky Way Galaxy

The present star formation rate (SFR) in the inner Galaxy is puzzling for the chemical evolution models (CEM). No static CEM is able to reproduce the peak of the SFR in the 4 kpc ring. The main reason is probably a shortage of gas, which could be due to the dynamical effects produced by the galactic bar, not considered by these models. We developed a CEM that includes radial gas flows in order to mimic the effects of the galactic bar in the first 5 kpc of the galactic disk. In this model, the star formation (SF) is a two-step process: first, the diffuse gas forms molecular clouds. Then, stars form from cloud-cloud collisions or by the interaction between massive stars and the molecular gas. The former is called spontaneous and the latter induced SF. The mass in the different phases of each region changes by the processes associated with the stellar formation and death by: the SF due to spontaneous fragmentation of gas in the halo; formation of gas clouds in the disk from the diffuse gas; induced SF in the disk due to the interaction between massive stars and gas clouds; and finally, the restitution of the diffuse gas associated to these process of cloud and star formation. In the halo, the star formation rate for the diffuse gas follows a Schmidt law with a power n = 1.5. In the disk, the stars form in two steps: first, molecular clouds are formed from the diffuse gas also following a Schmidt law with n=1.5 and a proportionality factor. Including a specific pattern of radial gas flows, the CEM is able to reproduce with success the peak in the SFR at 4 kpc (fig. 1).

Lapa das boleiras rockshelter: stratigraphy and formation processes at a paleoamerican site in Central Brazil

Lapa clas Boleiras rockshelter, a Paleoamerican archaeological site in Central Brazil, was intensely occupied by humans from 10,000 C-14 BP (11.8 cal kyr BP), until approximately 7500 C-14 BP (8.4 cal kyr BP). In this paper we present some interpretations about the formation processes operating on the site. One of our main conclusions is that the bulk of accumulated sediments at the site is of anthropogenic origin: they are constituted by volumetrically significant quantities of plant ash remains, what is somewhat unexpectedly in view of prevailing models about the lifestyle of Paleoamerican hunter-gatherers in South America. The evidence we discuss below is also consistent with paleoenvironmental data that suggest a dry period during the mid-Holocene in the region, probably leading to a decrease in human occupation [Araujo, A.G.M., Neves, W., Pilo, L.B., Atui, J.P., 2005. Holocene dryness and human Occupation in Brazil during the `Archaic Gap`. Quaternary Research 64, 298-307]. We surmise that both factors underpin a surprising reduction in sediment accumulation at the site during the mid-Holocene. (C) 2008 Published by Elsevier Ltd.

Exact field-driven interface dynamics in the two-dimensional stochastic Ising model with helicoidal boundary conditions

We investigate the interface dynamics of the two-dimensional stochastic Ising model in an external field under helicoidal boundary conditions. At sufficiently low temperatures and fields, the dynamics of the interface is described by an exactly solvable high-spin asymmetric quantum Hamiltonian that is the infinitesimal generator of the zero range process. Generally, the critical dynamics of the interface fluctuations is in the Kardar-Parisi-Zhang universality class of critical behavior. We remark that a whole family of RSOS interface models similar to the Ising interface model investigated here can be described by exactly solvable restricted high-spin quantum XXZ-type Hamiltonians. (C) 2012 Elsevier B.V. All rights reserved.

RefZ Facilitates the Switch from Medial to Polar Division during Spore Formation in Bacillus subtilis

During sporulation, Bacillus subtilis redeploys the division protein FtsZ from midcell to the cell poles, ultimately generating an asymmetric septum. Here, we describe a sporulation-induced protein, RefZ, that facilitates the switch from a medial to a polar FtsZ ring placement. The artificial expression of RefZ during vegetative growth converts FtsZ rings into FtsZ spirals, arcs, and foci, leading to filamentation and lysis. Mutations in FtsZ specifically suppress RefZ-dependent division inhibition, suggesting that RefZ may target FtsZ. During sporulation, cells lacking RefZ are delayed in polar FtsZ ring formation, spending more time in the medial and transition stages of FtsZ ring assembly. A RefZ-green fluorescent protein (GFP) fusion localizes in weak polar foci at the onset of sporulation and as a brighter midcell focus at the time of polar division. RefZ has a TetR DNA binding motif, and point mutations in the putative recognition helix disrupt focus formation and abrogate cell division inhibition. Finally, chromatin immunoprecipitation assays identified sites of RefZ enrichment in the origin region and near the terminus. Collectively, these data support a model in which RefZ helps promote the switch from medial to polar division and is guided by the organization of the chromosome. Models in which RefZ acts as an activator of FtsZ ring assembly near the cell poles or as an inhibitor of the transient medial ring at midcell are discussed.

Effects of the antimycobacterial compound 2-phenoxy-1-phenylethanone on rat hepatocytes and formation of metabolites

Context: Neolignans are usually dimers formed by oxidative coupling of allyl and propenyl phenols, and the neolignan analogue, 2-phenoxy-1-phenylethanone (LS-2) is a promising antimycobacterial compound showing very weak cytotoxicity in mammalian cells and lack of acute toxicity in murine models. Objectives: To investigate the mechanism of action of LS-2 in rat hepatocytes by evaluating the activity levels of enzymes related to oxidation status and drug-metabolizing activity. Materials and methods: Hepatocytes were treated with LS-2 from 0.05 up to 1 mM, for 24 and 48 h, and reduced glutathione (GSH), lipid peroxidation and cytochrome P450 enzyme (CYP450) activity were assayed. A homologous series of phenoxazone ethers were used as substrates to measure the enzymatic profile. The biotransformation of LS-2 was studied in hepatocytes by gas chromatography-mass spectrometry (GC-MS) for detection and analysis of possible metabolites. Results: Hepatocytes treated with LS-2 up to 1 mM for 24 or 48 h did not induce the formation of GSH and lipid peroxidation. O-Dealkylation activities of the isoenzymes CYP4501A1, CYP4501A2, CYP4502B1 and CYP4502B2 were also not detected in the hepatocytes treated with LS-2 for 24 or 48 h. Discussion and conclusion: The results indicate that LS-2 or its two detected metabolites, 2-phenoxy-1-phenylethanol and 2,4-(2-hydroxy-2-phenylethoxy) phenol, are not cytotoxic to rat hepatocytes. These compounds maintain a balance between the production of pro-oxidant agents and their respective antioxidant systems. The data show that enzymes related to oxidation status and drug-metabolizing activities are not involved in the mechanism of action of LS-2.

SPATIAL PATTERN OF FOUR FOREST COMMUNITIES BY RIPLEY'S K FUNCTION IN SAO PAULO STATE

Investigating tree's spatial patterns according to their size classes and according to their more abundant species can provide evidences about the structure of the vegetal community, since the spatial pattern is a key question for forestry ecology studies. The tree spatial organization patterns on the environment depend on several ecological processes and on the specific characteristics of each environment, so that the best understanding of this frame provides important elements for the knowledge on forestry formation. This paper aimed to study tree spatial patterns, according to the diameter classes and from four most abundant species in different forests, in order to provide evidences regarding to the ecology of each vegetal community. The spatial pattern description in each forestry formation was developed using Ripley's K function. The studied forestry formations were: Ombrophilous Forest, Cerradao, Seasonal Forest and Restinga Forest. In this work, a 10.24 ha plot was installed in each forestry formation, and every tree, with a circumference at breast height (CBH) larger than 15 cm were measured, georeferenced and identified. The obtained data highlights the aggregated character in tropical forests, as observed in every studied forest. The 'Cerraddo' and 'Restinga' forest trees showed close aggregate patterns. In the Ombrophilous forest, for all distance scales, the aggregate pattern was meaningful. In the seasonal forest, a random tendency was observed, although a meaningful aggregation was observed in all short distances. The spatial pattern by diameter classes was generally aggregated for trees smaller than 10 cm of diameter and between 10 and 20 cm and random for the others, proving the existence of a tendency which in young trees is more aggregated than in old ones. The spatial pattern of the dominant species is always strongly similar to the general pattern of each forestry formation. The differences between the spatial patterns of two or three coincident species, among the forestry formations, indicate that its pattern is influenced by each different environment. This stands out the importance of its self-ecology and of its ecological processes, intrinsic of each community that can explain the observed patterns.