A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

Toxic Epidermal Necrolysis-like Cutaneous Lupus Erythematosus: A Series of Three Patients

Toxic epidermal necrolysis-like lesions have been described in the setting of lupus erythematosus, and have been considered as a specific hyperacute variant of cutaneous lupus erythematosus, with features different from classical drug-related toxic epidermal necrolysis. We report here a series of three patients with lupus erythematosus who presented with severe worsening of their cutaneous disease in a toxic epidermal necrolysis-like fashion. We compared these cases with cases reported previously. Based on this discussion, we speculate that some of these patients may have classical drug-related toxic epidermal necrolysis rather than lupus erythematosus-related toxic epidermal necrolysis.

Polar organic marker compounds in atmospheric aerosols during the LBA-SMOCC 2002 biomass burning experiment in Rondonia, Brazil: sources and source processes, time series, diel variations and size distributions

Measurements of polar organic marker compounds were performed on aerosols that were collected at a pasture site in the Amazon basin (Rondonia, Brazil) using a high-volume dichotomous sampler (HVDS) and a Micro-Orifice Uniform Deposit Impactor (MOUDI) within the framework of the 2002 LBA-SMOCC (Large-Scale Biosphere Atmosphere Experiment in Amazonia - Smoke Aerosols, Clouds, Rainfall, and Climate: Aerosols From Biomass Burning Perturb Global and Regional Climate) campaign. The campaign spanned the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). In the present study a more detailed discussion is presented compared to previous reports on the behavior of selected polar marker compounds, including levoglucosan, malic acid, isoprene secondary organic aerosol (SOA) tracers and tracers for fungal spores. The tracer data are discussed taking into account new insights that recently became available into their stability and/or aerosol formation processes. During all three periods, levoglucosan was the most dominant identified organic species in the PM(2.5) size fraction of the HVDS samples. In the dry period levoglucosan reached concentrations of up to 7.5 mu g m(-3) and exhibited diel variations with a nighttime prevalence. It was closely associated with the PM mass in the size-segregated samples and was mainly present in the fine mode, except during the wet period where it peaked in the coarse mode. Isoprene SOA tracers showed an average concentration of 250 ng m(-3) during the dry period versus 157 ng m(-3) during the transition period and 52 ng m(-3) during the wet period. Malic acid and the 2-methyltetrols exhibited a different size distribution pattern, which is consistent with different aerosol formation processes (i.e., gas-to-particle partitioning in the case of malic acid and heterogeneous formation from gas-phase precursors in the case of the 2-methyltetrols). The 2-methyltetrols were mainly associated with the fine mode during all periods, while malic acid was prevalent in the fine mode only during the dry and transition periods, and dominant in the coarse mode during the wet period. The sum of the fungal spore tracers arabitol, mannitol, and erythritol in the PM(2.5) fraction of the HVDS samples during the dry, transition, and wet periods was, on average, 54 ng m(-3), 34 ng m(-3), and 27 ng m(-3), respectively, and revealed minor day/night variation. The mass size distributions of arabitol and mannitol during all periods showed similar patterns and an association with the coarse mode, consistent with their primary origin. The results show that even under the heavy smoke conditions of the dry period a natural background with contributions from bioaerosols and isoprene SOA can be revealed. The enhancement in isoprene SOA in the dry season is mainly attributed to an increased acidity of the aerosols, increased NO(x) concentrations and a decreased wet deposition.

Multimode Vibrational Couplings in Resonant Positron Annihilation

The mechanisms for multimode vibrational couplings in resonant positron annihilation are not well understood. We show that these resonances can arise from positron-induced distortions of the potential energy surface (target response to the positron field). Though these distortions can transfer energy into single- and multiquantum vibrations, they have so far been disregarded as a pathway to resonant annihilation. We also compare the existing annihilation theories and show that the currently accepted model can be cast as a special case of the Feshbach annihilation theory.

Magnetic resonant x-ray diffraction study of europium telluride

Here we use magnetic resonant x-ray diffraction to study the magnetic order in a 1.5 mu m EuTe film grown on (111) BaF(2) by molecular-beam epitaxy. At Eu L(II) and L(III) absorption edges, a resonant enhancement of more than two orders was observed for the sigma ->pi(') diffracted intensity at half-order reciprocal-lattice points, consistent with the magnetic character of the scattering. We studied the evolution of the (1/21/21/2) magnetic reflection with temperature. When heating toward the Neel temperature (T(N)), the integrated intensity decreased monotonously and showed no hysteresis upon cooling again, indicating a second-order phase transition. A power-law fit to the magnetization versus temperature curve yielded T(N)=9.99(1) K and a critical exponent beta=0.36(1), which agrees with the renormalization theory results for three-dimensional Heisenberg magnets. The fits to the sublattice magnetization dependence with temperature, disregarding and considering fourth-order exchange interactions, evidenced the importance of the latter for a correct description of magnetism in EuTe. A value of 0.009 was found for the (2j(1)+j(2))/J(2) ratio between the Heisenberg J(2) and fourth-order j(1,2) exchange constants. The magnetization curve exhibited a round-shaped region just near T(N) accompanied by an increase in the magnetic peak width, which was attributed to critical scattering above T(N). The comparison of the intensity ratio between the (1/21/21/2) and the (1/21/21/2) magnetic reflections proved that the Eu(2+) spins align within the (111) planes, and the azimuthal dependence of the (1/21/21/2) magnetic peak is consistent with the model of equally populated S domains.

Magnetic ordering of EuTe/PbTe multilayers determined by x-ray resonant diffraction

In this work we use resonant x-ray diffraction combined with polarization analysis of the diffracted beam to study the magnetic ordering in EuTe/PbTe multilayers. The presence of satellites at the (1/2 1/2 1/2) magnetic reflection of a 50 /repetition EuTe/PbTe superlattice demonstrated the existence of magnetic correlations among the alternated EuTe layers. The behavior of the satellites intensity as T increases toward the Neel temperature T(N) indicates that these correlations persist nearly up to T(N) and suggests the preferential decrease of the magnetic order parameter of external monolayers of each EuTe layer within the superlattice. (C) 2008 American Institute of Physics.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

THE LOWER CENTRAL AND DERIVED SERIES OF THE BRAID GROUPS OF THE SPHERE

In this paper, we determine the lower central and derived series for the braid groups of the sphere. We are motivated in part by the study of Fadell-Neuwirth short exact sequences, but the problem is important in its own right. The braid groups of the 2-sphere S(2) were studied by Fadell, Van Buskirk and Gillette during the 1960s, and are of particular interest due to the fact that they have torsion elements (which were characterised by Murasugi). We first prove that for all n epsilon N, the lower central series of the n-string braid group B(n)(S(2)) is constant from the commutator subgroup onwards. We obtain a presentation of Gamma(2)(Bn(S(2))), from which we observe that Gamma(2)(B(4)(S(2))) is a semi-direct product of the quaternion group Q(8) of order 8 by a free group F(2) of rank 2. As for the derived series of Bn(S(2)), we show that for all n >= 5, it is constant from the derived subgroup onwards. The group Bn(S(2)) being finite and soluble for n <= 3, the critical case is n = 4 for which the derived subgroup is the above semi-direct product Q(8) (sic) F(2). By proving a general result concerning the structure of the derived subgroup of a semi-direct product, we are able to determine completely the derived series of B(4)(S(2)) which from (B(4)(S(2)))(4) onwards coincides with that of the free group of rank 2, as well as its successive derived series quotients.

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Vegetable Oil Quenchants: Calculation and Comparison of The Cooling Properties of a Series of Vegetable Oils

The compositions of canola, soybean, corn, cottonseed and sunflower oils suggest that they exhibit substantially different propensity for oxidation following the order of Canola < corn < cottonseed < sunflower approximate to soybean. These data suggest that any of the vegetable oils evaluated could be blended with minimal impact on viscosity although compositional differences would surely affect oxidative stability. Cooling curve analysis showed that similar cooling profiles were obtained for different vegetable oils. Interestingly, no film boiling or transition nucleate boiling was observed with any of the vegetable oils and heat transfer occurs only by pure nucleate boiling and convection. High-temperature cooling properties of vegetable oils are considerable faster than those observed for petroleum oil-based quenchants. (C)2010 Journal of Mechanical Engineering. All rights reserved.

Investigation of the residence time distribution in a plate heat exchanger with series and parallel arrangements using a non-ideal tracer detection technique

The objective was to study the flow pattern in a plate heat exchanger (PHE) through residence time distribution (RTD) experiments. The tested PHE had flat plates and it was part of a laboratory scale pasteurization unit. Series flow and parallel flow configurations were tested with a variable number of passes and channels per pass. Owing to the small scale of the equipment and the short residence times, it was necessary to take into account the influence of the tracer detection unit on the RID data. Four theoretical RID models were adjusted: combined, series combined, generalized convection and axial dispersion. The combined model provided the best fit and it was useful to quantify the active and dead space volumes of the PHE and their dependence on its configuration. Results suggest that the axial dispersion model would present good results for a larger number of passes because of the turbulence associated with the changes of pass. This type of study can be useful to compare the hydraulic performance of different plates or to provide data for the evaluation of heat-induced changes that occur in the processing of heat-sensitive products. (C) 2011 Elsevier Ltd. All rights reserved.

a-SiC : H anti-resonant layer ARROW waveguides

Over the last decades, anti-resonant reflecting optical waveguides (ARROW) have been used in different integrated optics applications. In this type of waveguide, light confinement is partially achieved through an anti-resonant reflection. In this work, the simulation, fabrication and characterization of ARROW waveguides using dielectric films deposited by a plasma-enhanced chemical vapor deposition (PECVD) technique, at low temperatures(similar to 300 degrees C), are presented. Silicon oxynitride (SiO(x)N(y)) films were used as core and second cladding layers and amorphous hydrogenated silicon carbide(a-SiC:H) films as first cladding layer. Furthermore, numerical simulations were performed using homemade routines based on two computational methods: the transfer matrix method (TMM) for the determination of the optimum thickness of the Fabry-Perot layers; and the non-uniform finite difference method (NU-FDM) for 2D design and determination of the maximum width that yields single-mode operation. The utilization of a silicon carbide anti-resonant layer resulted in low optical attenuations, which is due to the high refractive index difference between the core and this layer. Finally, for comparison purposes, optical waveguides using titanium oxide (TiO(2)) as the first ARROW layer were also fabricated and characterized.

Generation of self-similar Gaussian time series by means of the DWT and DWPT variance maps

Due to the several kinds of services that use the Internet and data networks infra-structures, the present networks are characterized by the diversity of types of traffic that have statistical properties as complex temporal correlation and non-gaussian distribution. The networks complex temporal correlation may be characterized by the Short Range Dependence (SRD) and the Long Range Dependence - (LRD). Models as the fGN (Fractional Gaussian Noise) may capture the LRD but not the SRD. This work presents two methods for traffic generation that synthesize approximate realizations of the self-similar fGN with SRD random process. The first one employs the IDWT (Inverse Discrete Wavelet Transform) and the second the IDWPT (Inverse Discrete Wavelet Packet Transform). It has been developed the variance map concept that allows to associate the LRD and SRD behaviors directly to the wavelet transform coefficients. The developed methods are extremely flexible and allow the generation of Gaussian time series with complex statistical behaviors.

Forecasting fuel ethanol consumption in Brazil by time series models: 2006-2012

This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.