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We derive a closed form expression for the sum of all the infrared divergent contributions to the free energy of a gas of gravitons. An important ingredient of our calculation is the use of a gauge fixing procedure such that the graviton propagator becomes both traceless and transverse. This has been shown to be possible, in a previous work, using a general gauge fixing procedure, in the context of the lowest order expansion of the Einstein-Hilbert action, describing noninteracting spin-two fields. In order to encompass the problems involving thermal loops, such as the resummation of the free energy, in the present work, we have extended this procedure to the situations when the interactions are taken into account.

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In this paper we study the one-and two-loop contribution to the free energy in QED with Lorentz symmetry breaking introduced via constant CPT-even Lorentz-breaking parameters at the high temperature limit. We find the impact of the Lorentz-violating term for the free energy and carry out a numerical estimation for the Lorentz-breaking parameter.

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Using ab initio methods, we propose a simple and effective way to substitutionally dope graphene sheets with boron. The method consists of selectively exposing each side of the graphene sheet to different elements. We first expose one side of the membrane to boron while the other side is exposed to nitrogen. Proceeding this way, the B atoms will be spontaneously incorporated into the graphene membrane without any activation barrier. In a second step, the system should be exposed to a H-rich environment, which will remove the CN radical from the layer and form HCN, leading to a perfect substitutional doping.

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In this paper we detail some results advanced in a recent letter [Prado et al., Phys. Rev. Lett. 102, 073008 (2009).] showing how to engineer reservoirs for two-level systems at absolute zero by means of a time-dependent master equation leading to a nonstationary superposition equilibrium state. We also present a general recipe showing how to build nonadiabatic coherent evolutions of a fermionic system interacting with a bosonic mode and investigate the influence of thermal reservoirs at finite temperature on the fidelity of the protected superposition state. Our analytical results are supported by numerical analysis of the full Hamiltonian model.

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Background: Schistosoma mansoni is the major causative agent of schistosomiasis. The parasite takes advantage of host signals to complete its development in the human body. Tumor necrosis factor-alpha (TNF-alpha) is a human cytokine involved in skin inflammatory responses, and although its effect on the adult parasite's metabolism and egg-laying process has been previously described, a comprehensive assessment of the TNF-alpha pathway and its downstream molecular effects is lacking. Methodology/Principal Findings: In the present work we describe a possible TNF-alpha receptor (TNFR) homolog gene in S. mansoni (SmTNFR). SmTNFR encodes a complete receptor sequence composed of 599 amino acids, and contains four cysteine-rich domains as described for TNFR members. Real-time RT-PCR experiments revealed that SmTNFR highest expression level is in cercariae, 3.5 (+/- 0.7) times higher than in adult worms. Downstream members of the known human TNF-alpha pathway were identified by an in silico analysis, revealing a possible TNF-alpha signaling pathway in the parasite. In order to simulate parasite's exposure to human cytokine during penetration of the skin, schistosomula were exposed to human TNF-alpha just 3 h after cercariae-to-schistosomula in vitro transformation, and large-scale gene expression measurements were performed with microarrays. A total of 548 genes with significantly altered expression were detected, when compared to control parasites. In addition, treatment of adult worms with TNF-alpha caused a significantly altered expression of 1857 genes. Interestingly, the set of genes altered in adults is different from that of schistosomula, with 58 genes in common, representing 3% of altered genes in adults and 11% in 3 h-old early schistosomula. Conclusions/Significance: We describe the possible molecular elements and targets involved in human TNF-alpha effect on S. mansoni, highlighting the mechanism by which recently transformed schistosomula may sense and respond to this host mediator at the site of cercarial penetration into the skin.

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We study the free-fall of a quantum particle in the context of noncommutative quantum mechanics (NCQM). Assuming noncommutativity of the canonical type between the coordinates of a two-dimensional configuration space, we consider a neutral particle trapped in a gravitational well and exactly solve the energy eigenvalue problem. By resorting to experimental data from the GRANIT experiment, in which the first energy levels of freely falling quantum ultracold neutrons were determined, we impose an upper-bound on the noncommutativity parameter. We also investigate the time of flight of a quantum particle moving in a uniform gravitational field in NCQM. This is related to the weak equivalence principle. As we consider stationary, energy eigenstates, i.e., delocalized states, the time of flight must be measured by a quantum clock, suitably coupled to the particle. By considering the clock as a small perturbation, we solve the (stationary) scattering problem associated and show that the time of flight is equal to the classical result, when the measurement is made far from the turning point. This result is interpreted as an extension of the equivalence principle to the realm of NCQM. (C) 2010 American Institute of Physics. [doi:10.1063/1.3466812]

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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.

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Background: Persistent infection by high risk HPV types (e.g. HPV-16, -18, -31, and -45) is the main risk factor for development of cervical intraepithelial neoplasia and cervical cancer. Tumor necrosis factor (TNF) is a key mediator of epithelial cell inflammatory response and exerts a potent cytostatic effect on normal or HPV16, but not on HPV18 immortalized keratinocytes. Moreover, several cervical carcinoma-derived cell lines are resistant to TNF anti-proliferative effect suggesting that the acquisition of TNF-resistance may constitute an important step in HPV-mediated carcinogenesis. In the present study, we compared the gene expression profiles of normal and HPV16 or 18 immortalized human keratinocytes before and after treatment with TNF for 3 or 60 hours. Methods: In this study, we determined the transcriptional changes 3 and 60 hours after TNF treatment of normal, HPV16 and HPV18 immortalized keratinocytes by microarray analysis. The expression pattern of two genes observed by microarray was confirmed by Northern Blot. NF-kappa B activation was also determined by electrophoretic mobility shift assay (EMSA) using specific oligonucleotides and nuclear protein extracts. Results: We observed the differential expression of a common set of genes in two TNF-sensitive cell lines that differs from those modulated in TNF-resistant ones. This information was used to define genes whose differential expression could be associated with the differential response to TNF, such as: KLK7 (kallikrein 7), SOD2 (superoxide dismutase 2), 100P (S100 calcium binding protein P), PI3 (protease inhibitor 3, skin-derived), CSTA (cystatin A), RARRES1 (retinoic acid receptor responder 1), and LXN (latexin). The differential expression of the KLK7 and SOD2 transcripts was confirmed by Northern blot. Moreover, we observed that SOD2 expression correlates with the differential NF-kappa B activation exhibited by TNF-sensitive and TNF-resistant cells. Conclusion: This is the first in depth analysis of the differential effect of TNF on normal and HPV16 or HPV18 immortalized keratinocytes. Our findings may be useful for the identification of genes involved in TNF resistance acquisition and candidate genes which deregulated expression may be associated with cervical disease establishment and/or progression.

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We used morphological and molecular approaches to evaluate the diversity of free-living marine nematodes (order Enoplida) at four coastal sites in the Gulf of California and three on the Pacific coast of Baja California, Mexico. We identified 22 morphological species belonging to six families, of which Thoracostomopsidae and Oncholaimidae were the most diverse. The genus Mesacanthion (Thoracostomopsidae) was the most widespread and diverse. Five allopatric species, genetically and morphologically differentiated, were found in two localities in the Gulf of California (M. sp1 and M. sp2) and three in the Pacific coast (M. sp3, M. sp4 and M. sp5). Overall, we produced 19 and 20 sequences for the 18S and 28S genes, respectively. Neither gene displayed intraspecific polymorphisms, which allowed us to establish that some morphological variation was likely either ontogenetic or due to phenotypic plasticity. Although 18S and 28S phylogenies were topologically congruent (incongruence length difference test, P > 0.05), divergences between species were much higher in the 28S gene. Moreover, this gene possessed a stronger phylogenetic signal to resolve relationships involving Rhabdodemania and Bathylaimus. On the other hand, the close relationship of Pareurystomina (Enchilidiidae) with oncholaimids warrants further study. The 28S sequences (D2D3 domain) may be better suited for DNA barcoding of marine nematodes than those from the 18S rDNA, particularly for differentiating closely related or cryptic species. Finally, our results underline the relevance of adopting an integrative approach encompassing morphological and molecular analyses to improve the assessment of marine nematode diversity and advance their taxonomy.

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A flow system designed with solenoid micro-pumps is proposed for fast and greener spectrophotometric determination of free glycerol in biodiesel. Glycerol was extracted from samples without using organic solvents. The determination involves glycerol oxidation by periodate, yielding formaldehyde followed by formation of the colored (3,5-diacetil-1,4-dihidrolutidine) product upon reaction with acetylacetone. The coefficient of variation, sampling rate and detection limit were estimated as 1.5% (20.0 mg L(-1) glycerol, n =10), 34 h(-1), and 1.0 mg L(-1) (99.7% confidence level), respectively. A linear response was observed from 5 to 50 mg L(-1), with reagent consumption estimated as 345 mu g of KIO(4) and 15 mg of acetylacetone per determination. The procedure was successfully applied to the analysis of biodiesel samples and the results agreed with the batch reference method at the 95% confidence level. (C) 2010 Elsevier B.V. All rights reserved.

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A green and highly sensitive analytical procedure was developed for the determination of free chlorine in natural waters, based on the reaction with N,N-diethyl-p-phenylenediamine (DPD). The flow system was designed with solenoid micro-pumps in order to improve mixing conditions by pulsed flows and to minimize reagent consumption as well as waste generation. A 100-cm optical path flow cell based on a liquid core waveguide was employed to increase sensitivity. A linear response was observed within the range 10.0 to 100.0 mu g L(-1), with the detection limit, coefficient of variation and sampling rate estimated as 6.8 mu g (99.7% confidence level), 0.9% (n = 20) and 60 determinations per hour, respectively. The consumption of the most toxic reagent (DPD) was reduced 20,000-fold and 30-fold in comparison to the batch method and flow injection with continuous reagent addition, respectively. The results for natural and tap water samples agreed with those obtained by the reference batch spectrophotometric procedure at the 95% confidence level. (C) 2010 Elsevier By. All rights reserved.

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A new procedure for spectrofluorimetric determination of free and total glycerol in biodiesel samples is presented. It is based on the oxidation of glycerol by periodate, forming formaldehyde, which reacts with acetylacetone, producing the luminescent 3,5-diacetyl-1,4-dihydrolutidine. A flow system with solenoid micro-pumps is proposed for solution handling. Free glycerol was extracted off-line from biodiesel samples with water, and total glycerol was converted to free glycerol by saponification with sodium ethylate under sonication. For free glycerol, a linear response was observed from 5 to 70 mg L(-1) with a detection limit of 0.5 mg L(-1), which corresponds to 2 mg kg(-1) in biodiesel. The coefficient of variation was 0.9% (20 mg L(-1), n = 10). For total glycerol, samples were diluted on-line, and the linear response range was 25 to 300 mg L(-1). The detection limit was 1.4 mg L(-1) (2.8 mg kg(-1) in biodiesel) with a coefficient of variation of 1.4% (200 mg L(-1), n = 10). The sampling rate was ca. 35 samples h(-1) and the procedure was applied to determination of free and total glycerol in biodiesel samples from soybean, cottonseed, and castor beans.

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Biomass burning is an important source of atmospheric Particulate Matter (PM) in Brazil: the burning of forests in the northwest and of sugar cane plantations in the southeast are important examples. The objective of this work is the measurement of the PM emission profile of burning of sugar cane and other characteristic vegetative burning in the region of Sao Carlos-SP/Brazil. Samples of PM(10) and PM(2.5) were collected in different conditions, including small laboratory controlled burnings and real ones. The samples were analysed by X-Ray Fluorescence (XRF) and 14 chemical elements quantified. t-Student tests were performed to compare the obtained profiles, using as a reference a vegetative burn profile taken from the USEPA data bank SPECIATE. All measured profiles presented significant amounts of Cl and K, which are confirmed as tracers of sugar cane foliage burning.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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Given a prime power q, define c (q) as the minimum cardinality of a subset H of F 3 q which satisfies the following property: every vector in this space di ff ers in at most 1 coordinate from a multiple of a vector in H. In this work, we introduce two extremal problems in combinatorial number theory aiming to discuss a known connection between the corresponding coverings and sum-free sets. Also, we provide several bounds on these maps which yield new classes of coverings, improving the previous upper bound on c (q)