Determination of the spin of new resonances in electroweak gauge boson pair production at the LHC

The appearance of spin-1 resonances associated with the electroweak symmetry breaking sector is expected in many extensions of the standard model. We analyze the CERN Large Hadron Collider potential to probe the spin of possible new charged and neutral vector resonances through the purely leptonic processes pp -> Z' -> l(+) l'(-) E(T), and pp -> W' -> l'(+/-) l(+) l(-) E(T), with l, l' = e or mu. We perform a model-independent analysis and demonstrate that the spin of the new states can be determined with 99% C. L. in a large fraction of the parameter space where these resonances can be observed with 100 fb(-1). We show that the best sensitivity to the spin is obtained by directly studying correlations between the final state leptons, without the need of reconstructing the events in their center-of-mass frames.

The role of oxygen vacancy in the photoluminescence property at room temperature of the CaTiO(3)

In this paper, electron paramagnetic resonance, photoluminescence (PL) emission, and quantum mechanical calculations were used to observe and understand the structural order-disorder of CaTiO(3), paying special attention to the role of oxygen vacancy. The PL phenomenon at room temperature of CaTiO(3) is directly influenced by the presence of oxygen vacancies that yield structural order-disorder. These oxygen vacancies bonded at Ti and/or Ca induce new electronic states inside the band gap. Ordered and disordered CaTiO(3) was obtained by the polymeric precursor method. (C) 2009 American Institute of Physics. [DOI: 10.1063/1.3190524]

Spin-polarized current and shot noise in the presence of spin flip in a quantum dot via nonequilibrium Green's functions

Using nonequilibrium Green's functions we calculate the spin-polarized current and shot noise in a ferromagnet-quantum-dot-ferromagnet system. Both parallel (P) and antiparallel (AP) magnetic configurations are considered. Coulomb interaction and coherent spin flip (similar to a transverse magnetic field) are taken into account within the dot. We find that the interplay between Coulomb interaction and spin accumulation in the dot can result in a bias-dependent current polarization p. In particular, p can be suppressed in the P alignment and enhanced in the AP case depending on the bias voltage. The coherent spin flip can also result in a switch of the current polarization from the emitter to the collector lead. Interestingly, for a particular set of parameters it is possible to have a polarized current in the collector and an unpolarized current in the emitter lead. We also found a suppression of the Fano factor to values well below 0.5.

The role of electron localization in the atomic structure of transition-metal 13-atom clusters: the example of Co(13), Rh(13), and Hf(13)

The crystalline structure of transition-metals (TM) has been widely known for several decades, however, our knowledge on the atomic structure of TM clusters is still far from satisfactory, which compromises an atomistic understanding of the reactivity of TM clusters. For example, almost all density functional theory (DFT) calculations for TM clusters have been based on local (local density approximation-LDA) and semilocal (generalized gradient approximation-GGA) exchange-correlation functionals, however, it is well known that plain DFT fails to correct the self-interaction error, which affects the properties of several systems. To improve our basic understanding of the atomic and electronic properties of TM clusters, we report a DFT study within two nonlocal functionals, namely, the hybrid HSE (Heyd, Scuseria, and Ernzerhof) and GGA + U functionals, of the structural and electronic properties of the Co(13), Rh(13), and Hf(13) clusters. For Co(13) and Rh(13), we found that improved exchange-correlation functionals decrease the stability of open structures such as the hexagonal bilayer (HBL) and double simple-cubic (DSC) compared with the compact icosahedron (ICO) structure, however, DFT-GGA, DFT-GGA + U, and DFT-HSE yield very similar results for Hf(13). Thus, our results suggest that the DSC structure obtained by several plain DFT calculations for Rh(13) can be improved by the use of improved functionals. Using the sd hybridization analysis, we found that a strong hybridization favors compact structures, and hence, a correct description of the sd hybridization is crucial for the relative energy stability. For example, the sd hybridization decreases for HBL and DSC and increases for ICO in the case of Co(13) and Rh(13), while for Hf(13), the sd hybridization decreases for all configurations, and hence, it does not affect the relative stability among open and compact configurations.

On the resilience of long cycles in random graphs

In this paper we determine the local and global resilience of random graphs G(n,p) (p >> n(-1)) with respect to the property of containing a cycle of length at least (1 - alpha)n. Roughly speaking, given alpha > 0, we determine the smallest r(g) (G, alpha) with the property that almost surely every subgraph of G = G(n,p) having more than r(g) (G, alpha)vertical bar E(G)vertical bar edges contains a cycle of length at least (1 - alpha)n (global resilience). We also obtain, for alpha < 1/2, the smallest r(l) (G, alpha) such that any H subset of G having deg(H) (v) larger than r(l) (G, alpha) deg(G) (v) for all v is an element of V(G) contains a cycle of length at least (1 - alpha)n (local resilience). The results above are in fact proved in the more general setting of pseudorandom graphs.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

The role of exon shuffling in shaping protein-protein interaction networks

Background: Physical protein-protein interaction (PPI) is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results: We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners) in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains), self-interacting (able to interact with another copy of themselves) and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions: Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

Shelf and estuarine transport mechanisms affecting the supply of competent larvae in a suite of brachyuran crabs with different life histories

Supply of competent larvae to the benthic habitat is a major determinant of population dynamics in coastal and estuarine invertebrates with an indirect life cycle. Larval delivery may depend not only on physical transport mechanisms, but also on larval behavior and physiological progress to the competent stage. Yet, the combined analysis of such factors has seldom been attempted. We used time-series analyses to examine tide- and wind-driven mechanisms responsible for the supply of crab megalopae to an estuarine river under a major marine influence in SW Spain, and monitored the vertical distribution of upstream moving megalopae, their net flux and competent state. The species Panopeus africanus (estuarine), Brachynotus sexdentatus (euryhaline) and Nepinnotheres pinnotheres (coastal) comprised 80% of the whole sample, and responded in a similar way to tide and wind forcing. Tidal range was positively correlated to supply, with maxima 0 to 1 d after spring tides, suggesting selective tidal stream transport. Despite being extensively subjected to upwelling, downwind drift under the effect of westerlies, not Ekman transport, explained residual supply variation at our sampling area. Once in the estuary, net flux and competence state matched the expected trends. Net upstream flux increased from B. sexdentatus to P. africanus, favoring transport to a sheltered coastal habitat (N. pinnotheres), or to the upper estuary (P. africanus). Competence state was highest in N. pinnotheres, intermediate in B. sexdentatus and lowest in P. africanus, as expected if larvae respond to cues from adequate benthic habitat. P. africanus megalopae were found close to the bottom, not above, rendering slower upstream transport than anticipated.

The Influence of Different Land Uses on the Structure of Archaeal Communities in Amazonian Anthrosols Based on 16S rRNA and amoA Genes

Soil from the Amazonian region is usually regarded as unsuitable for agriculture because of its low organic matter content and low pH; however, this region also contains extremely rich soil, the Terra Preta Anthrosol. A diverse archaeal community usually inhabits acidic soils, such as those found in the Amazon. Therefore, we hypothesized that this community should be sensitive to changes in the environment. Here, the archaeal community composition of Terra Preta and adjacent soil was examined in four different sites in the Brazilian Amazon under different anthropic activities. The canonical correspondence analysis of terminal restriction fragment length polymorphisms has shown that the archaeal community structure was mostly influenced by soil attributes that differentiate the Terra Preta from the adjacent soil (i.e., pH, sulfur, and organic matter). Archaeal 16S rRNA gene clone libraries indicated that the two most abundant genera in both soils were Candidatus nitrosphaera and Canditatus nitrosocaldus. An ammonia monoxygenase gene (amoA) clone library analysis indicated that, within each site, there was no significant difference between the clone libraries of Terra Preta and adjacent soils. However, these clone libraries indicated there were significant differences between sites. Quantitative PCR has shown that Terra Preta soils subjected to agriculture displayed a higher number of amoA gene copy numbers than in adjacent soils. On the other hand, soils that were not subjected to agriculture did not display significant differences on amoA gene copy numbers between Terra Preta and adjacent soils. Taken together, our findings indicate that the overall archaeal community structure in these Amazonian soils is determined by the soil type and the current land use.

Variation in the Distribution of Trace Elements in Renal Cell Carcinoma

The development of cancer is a complex, multistage process during which a normal cell undergoes genetic changes that result in phenotypic alterations and in the acquisition of the ability to invade other sites. Inductively coupled plasma optical emission spectroscopy was used to estimate the contents of Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, P, Pb, and Zn in healthy kidney and renal cell carcinoma (RCC), and significant differences were found for all elements. Along with the progression of the malignant disease, a progressive decrease of Cd and K was observed. In fact, for Cd, the concentration in stage T4 was 263.9 times lower than in stage T1, and for K, the concentration in stage T4 was 1.73 times lower than in stage T1. Progressive accumulation was detected for P, Pb, and Zn in stage T4. For P, the concentration in stage T4 was 11.1 times higher than in stage T1; for Pb, the concentration in stage T4 was 232.7 times higher than in T1; and for Zn, the concentration in T4 was 8.452 times higher than in T1. This study highlights the marked differences in the concentrations of selected trace metals in different malignant tumor stages. These findings indicate that some trace metals may play important roles in the pathogenesis of RCC.

The importance of scientific literacy in fostering education for sustainability: Theoretical considerations and preliminary findings from a Brazilian experience

Scientific literacy can be considered as a new demand of post-industrial society. It seems necessary in order to foster education for sustainability throughout students` academic careers. Universities striving to teach sustainability are being challenged to integrate a holistic perspective into a traditional undergraduate curriculum, which aims at specialization. This new integrative, inter- and transdisciplinary epistemological approach is necessary to cultivate autonomous citizenship, i.e., that each citizen be prepared to understand and participate in discussions about the complex contemporary issues posed by post-industrial society. This paper presents an epistemological framework to show the role of scientific literacy in fostering education for sustainability. We present a set of 26 collaborative concept maps (CCmaps) in order to illustrate an instance of theory becoming practice. During a required course for first-year undergraduate students (ACH 0011, Natural Sciences), climate change was presented and discussed in broad perspective by using CCmaps. We present students` CCmaps to show how they use concepts from quantitative and literacy disciplines to deal with the challenges posed by the need of achieving a sustainable development. (C) 2009 Elsevier Ltd. All rights reserved.

The Emergence of Family Nursing in Brazil

A family perspective has been influencing Brazilian nursing practice and research, in particular in the past decade. Despite this development, there is evidence from research and from nurses` narratives that nurses still experience serious challenges in providing nursing care to families in Brazil. These challenges are analyzed and strategies are offered to support nurses in Brazil to ""think family"" and stimulate advanced practice in family nursing.

A comparison between the concentration of mast cells in squamous cell carcinomas of the skin and oral cavity

FUNDAMENTS: The lethality of squamous cell carcinomas (SCC) of the skin is considered low. SCC in the mouth is usually associated with poor prognosis. Current evidence suggests that mast cells in the normal tissue contribute to the tumorigenesis of SCC, probably by promoting angiogenesis. OBJECTIVE: The aim of this study was to compare the concentration of mast cells in SCC of the mouth and skin and evaluate whether there is a correlation with the degree of differentiation of these tumors. MATERIAL AND METHODS: Thirty cases of SCC of the skin and 34 of the mouth were investigated. Toluidine blue staining was used to identify mast cells in blocks containing the central portion of the neoplasm. RESULTS: A concentration of between 0 and 10 mast cells was found in one single case of SCC of the skin and there were no cases of SCC of the mouth with concentrations of mast cells in the tumor >201. In the majority of cases of SCC of the mouth (47%; n=16), mast cell concentration was between 0 and 10, with a concentration >51 mast cells in 80% of cases of SCC of the skin. All the cases of SCC of the mouth with a concentration of mast cells between 100 and 200 and 80% of those with a concentration of 51-99 were located on the lip. The concentration of mast cells was unrelated to the degree of differentiation of the tumor. CONCLUSION: The concentration of mast cells is lower in SCC of the mouth except when the tumor is located on the lip. This may reflect a lower need for cell activation in the microenvironment to improve vascularization in oral cancer.

LOW-INTENSITY PULSED ULTRASOUND PRODUCED AN INCREASE OF OSTEOGENIC GENES EXPRESSION DURING THE PROCESS OF BONE HEALING IN RATS

The aim of this study was to measure the temporal expression of osteogenic genes during the process of bone healing in low-intensity pulsed ultrasound (LIPUS) treated bone defects by means of histopathologic and real-time polymerase chain reaction (PCR) analysis. Animals were randomly distributed into two groups (n = 30): control group (bone defect without treatment) and LIPUS treated (bone defect treated with LIPUS). On days 7, 13 and 25 postinjury, 10 rats per group were sacrificed. Rats were treated with a 30 mW/cm(2) LIPUS. The results pointed out intense new bone formation surrounded by highly vascularized connective tissue presenting a slight osteogenic activity, with primary bone deposition was observed in the group exposed to LIPUS in the intermediary (13 days) and late stages of repair (25 days) in the treated animals. In addition, quantitative real-time polymerase chain reaction (RT-qPCR) showed an upregulation of bone morphogenetic protein 4 (BMP4), osteocalcin and Runx2 genes 7 days after the surgery. In the intermediary period, there was no increase in the expression. The expression of alkaline phosphatase, BMP4 and Runx2 was significantly increased at the last period. Our results indicate that LIPUS therapy improves bone repair in rats and upregulated osteogenic genes, mainly at the late stages of recovery. (E-mail: a.renno@unifesp.br) (C) 2010 Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology.

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.