Charged and strange hadron elliptic flow in Cu plus Cu collisions at root s(NN)=62.4 and 200 GeV

We present the results of an elliptic flow, v(2), analysis of Cu + Cu collisions recorded with the solenoidal tracker detector (STAR) at the BNL Relativistic Heavy Ion Collider at root s(NN) = 62.4 and 200 GeV. Elliptic flow as a function of transverse momentum, v(2)(p(T)), is reported for different collision centralities for charged hadrons h(+/-) and strangeness-ontaining hadrons K(S)(0), Lambda, Xi, and phi in the midrapidity region vertical bar eta vertical bar < 1.0. Significant reduction in systematic uncertainty of the measurement due to nonflow effects has been achieved by correlating particles at midrapidity, vertical bar eta vertical bar < 1.0, with those at forward rapidity, 2.5 < vertical bar eta vertical bar < 4.0. We also present azimuthal correlations in p + p collisions at root s = 200 GeV to help in estimating nonflow effects. To study the system-size dependence of elliptic flow, we present a detailed comparison with previously published results from Au + Au collisions at root s(NN) = 200 GeV. We observe that v(2)(p(T)) of strange hadrons has similar scaling properties as were first observed in Au + Au collisions, that is, (i) at low transverse momenta, p(T) < 2 GeV/c, v(2) scales with transverse kinetic energy, m(T) - m, and (ii) at intermediate p(T), 2 < p(T) < 4 GeV/c, it scales with the number of constituent quarks, n(q.) We have found that ideal hydrodynamic calculations fail to reproduce the centrality dependence of v(2)(p(T)) for K(S)(0) and Lambda. Eccentricity scaled v(2) values, v(2)/epsilon, are larger in more central collisions, suggesting stronger collective flow develops in more central collisions. The comparison with Au + Au collisions, which go further in density, shows that v(2)/epsilon depends on the system size, that is, the number of participants N(part). This indicates that the ideal hydrodynamic limit is not reached in Cu + Cu collisions, presumably because the assumption of thermalization is not attained.

Finite-temperature Casimir effect for graphene

We adopt the Dirac model for quasiparticles in graphene and calculate the finite-temperature Casimir interaction between a suspended graphene layer and a parallel conducting surface. We find that at high temperature, the Casimir interaction in such system is just one-half of that for two ideal conductors separated by the same distance. In this limit, a single graphene layer behaves exactly as a Drude metal. In particular, the contribution of the TE mode is suppressed, while the contribution of the TM mode saturates at the ideal-metal value. The behavior of the Casimir interaction for intermediate temperatures and separations accessible in experiments is studied in some detail. We also find an interesting interplay between two fundamental constants of graphene physics: the fine-structure constant and the Fermi velocity.

Thermo-solvatochromism in binary mixtures of water and ionic liquids: on the relative importance of solvophobic interactions

The thermo-solvatochromism of 2,6-dibromo-4-[(E)-2-(1-methylpyridinium-4-yl)ethenyl] phenolate, MePMBr(2), has been studied in mixtures of water, W, with ionic liquids, ILs, in the temperature range of 10 to 60 degrees C, where feasible. The objectives of the study were to test the applicability of a recently introduced solvation model, and to assess the relative importance of solute-solvent solvophobic interactions. The ILs were 1-allyl-3-alkylimidazolium chlorides, where the alkyl groups are methyl, 1-butyl, and 1-hexyl, respectively. The equilibrium constants for the interaction of W and the ILs were calculated from density data; they were found to be linearly dependent on N(C), the number of carbon atoms of the alkyl group; van't Hoff equation (log K versus 1/T) applied satisfactorily. Plots of the empirical solvent polarities, E(T) (MePMBr(2)) in kcal mol(-1), versus the mole fraction of water in the binary mixture, chi(w), showed non-linear, i.e., non-ideal behavior. The dependence of E(T) (MePMBr(2)) on chi(w), has been conveniently quantified in terms of solvation by W, IL, and the ""complex"" solvent IL-W. The non-ideal behavior is due to preferential solvation by the IL and, more efficiently, by IL-W. The deviation from linearity increases as a function of increasing N(C) of the IL, and is stronger than that observed for solvation of MePMBr(2) by aqueous 1-propanol, a solvent whose lipophilicity is 12.8 to 52.1 times larger than those of the ILs investigated. The dependence on N(C) is attributed to solute-solvent solvophobic interactions, whose relative contribution to solvation are presumably greater than that in mixtures of water and 1-propanol.

Mechanism and model of the oscillatory electro-oxidation of methanol

A mechanism for the kinetic instabilities observed in the galvanostatic electro-oxidation of methanol is suggested and a model developed. The model is investigated using stoichiometric network analysis as well as concepts from algebraic geometry (polynomial rings and ideal theory) revealing the occurrence of a Hopf and a saddle-node bifurcation. These analytical solutions are confirmed by numerical integration of the system of differential equations. (C) 2010 American Institute of Physics

Human multipotent adipose-derived stem cells restore dystrophin expression of Duchenne skeletal-muscle cells in vitro

Background information. DMD (Duchenne muscular dystrophy) is a devastating X-linked disorder characterized by progressive muscle degeneration and weakness. The use of cell therapy for the repair of defective muscle is being pursued as a possible treatment for DMD. Mesenchymal stem cells have the potential to differentiate and display a myogenic phenotype in vitro. Since liposuctioned human fat is available in large quantities, it may be an ideal source of stem cells for therapeutic applications. ASCs (adipose-derived stem cells) are able to restore dystrophin expression in the muscles of mdx (X-linked muscular dystrophy) mice. However, the outcome when these cells interact with human dystrophic muscle is still unknown. Results. We show here that ASCs participate in myotube formation when cultured together with differentiating human DMD myoblasts, resulting in the restoration of dystrophin expression. Similarly, dystrophin was induced when ASCs were co-cultivated with DMD myotubes. Experiments with GFP (green fluorescent protein)-positive ASCs and DAPI (4,6-diamidino-2-phenylindole)-stained DMD myoblasts indicated that ASCs participate in human myogenesis through cellular fusion. Conclusions. These results show that ASCs have the potential to interact with dystrophic muscle cells, restoring dystrophin expression of DMD cells in vitro. The possibility of using adipose tissue as a source of stem cell therapies for muscular diseases is extremely exciting.

Coconut coir as biosorbent for Cr(VI) removal from laboratory wastewater

A high cost-effective treatment of sulphochromic waste is proposed employing a raw coconut coir as biosorbent for Cr(VI) removal. The ideal pH and sorption kinetic, sorption capacities, and sorption sites were the studied biosorbent parameters. After testing five different isotherm models with standard solutions, Redlich-Peterson and Toth best fitted the experimental data, obtaining a theoretical Cr(VI) sorption capacity (SC) of 6.3 mg g(-1). Acid-base potentiometric titration indicated around of 73% of sorption sites were from phenolic compounds, probably lignin. Differences between sorption sites in the coconut coir before and after Cr adsorption identified from Fourier transform infrared spectra suggested a modification of sorption sites after sulphochromic waste treatment, indicating that the sorption mechanism involves organic matter oxidation and chromium uptake. For sulphocromic waste treatment, the SC was improved to 26.8 +/- 0.2 mg g(-1), and no adsorbed Cr(VI) was reduced, remaining only Cr(III) in the final solution. The adsorbed material was calcinated to obtain Cr2O3, with a reduction of more than 60% of the original mass. (c) 2008 Elsevier B.V. All rights reserved.

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

An improved continuous medium technique for structural frame analysis

This paper presents an improved constitutive equation of frame in the context of continuous medium technique. This improved constitutive equation, which is a consistent formulation of column global bending, is applicable to a complete class of frameworks including the ideal shear frame panel, for which the beams are assumed to be rigid, and the associated column system, for which the rigidity of beams is negligible. Global buckling and second-order effects of the frame structure are discussed. The main results can be extended to other types of lateral stiffening elements as built-up columns. A worked example is presented in order to compare the main results with those obtained by the classic matrix method. Copyright (C) 2007 John Wiley & Sons, Ltd.

A study of plastic deformation around a defect using the magnetic Barkhausen noise in ASTM 36 steel

The present work presents the measurements of the magnetic Barkhausen noise (MBN) in ASTM 36 steel samples around a pit under plastic deformation. The contour maps obtained from these Barkhausen noise measurements are compared with the finite element analysis of the ideal plastic deformation. Also, a parameter of the Barkhausen signal to detect the plastic deformation around the pit in ASTM 36 steel is obtained. Additionally to that, we propose another MBN parameter to estimate the pit width using the Barkhausen noise. (c) 2007 Elsevier Ltd. All rights reserved.

Characterization of mixed waste of granite and LD slag

This study focuses on the technical feasibility of the utilization of waste from the cutting of granite to adjust the chemical composition of slag from steelworks LD, targeting the addition of clinker Portland cement. For this, chemical characterization of the waste, its mixture and fusion was performed, obtaining a CaO/SiO(2) relationship of around 0.9 to 1.2 for the steelworks slag. We selected samples of the waste, mixed, melted and cooled in water and in the oven. Samples cooled in water, after examining with X-ray difractrograms, had been predominantly amorphous. For samples cooled in the furnace, which had vitreous, there was the presence of mineralogical phases Akermanita and Gehlenita, which is considered as the ideal stage for the mineral water activity of the slag. The adjustment of the chemical composition of the slag from steel works by the addition of waste granite was efficient, transforming the waste into a product that is the same as blast furnace slag and can be used in the manufacture of cement.

Thermomechanical processing for recovery of desired < 001 > fiber texture in electric motor steels

A processing route has been developed for recovering the desired lambda fiber in iron-silicon electrical steel needed for superior magnetic properties in electric motor application. The lambda fiber texture is available in directionally solidified iron-silicon steel with the < 001 > columnar grains but was lost after heavy rolling and recrystallization required for motor laminations. Two steps of light rolling each followed by recrystallization were found to largely restore the desired fiber texture. This strengthening of the < 001 > fiber texture had been predicted on the basis of the strain-induced boundary migration (SIBM) mechanism during recrystallization of lightly rolled steel from existing grains of near the ideal orientation, due to postulated low stored energies. Taylor and finite element models supported the idea of the low stored energy of the lambda fiber grains. The models also showed that the lambda fiber grains, though unstable during rolling, only rotated away from their initial orientations quite slowly.

Phase Equilibrium and Optimization Tools: Application for Enhanced Structured Lipids for Foods

Solid-liquid phase equilibrium modeling of triacylglycerol mixtures is essential for lipids design. Considering the alpha polymorphism and liquid phase as ideal, the Margules 2-suffix excess Gibbs energy model with predictive binary parameter correlations describes the non ideal beta and beta` solid polymorphs. Solving by direct optimization of the Gibbs free energy enables one to predict from a bulk mixture composition the phases composition at a given temperature and thus the SFC curve, the melting profile and the Differential Scanning Calorimetry (DSC) curve that are related to end-user lipid properties. Phase diagram, SFC and DSC curve experimental data are qualitatively and quantitatively well predicted for the binary mixture 1,3-dipalmitoyl-2-oleoyl-sn-glycerol (POP) and 1,2,3-tripalmitoyl-sn-glycerol (PPP), the ternary mixture 1,3-dimyristoyl-2-palmitoyl-sn-glycerol (MPM), 1,2-distearoyl-3-oleoyl-sn-glycerol (SSO) and 1,2,3-trioleoyl-sn-glycerol (OOO), for palm oil and cocoa butter. Then, addition to palm oil of Medium-Long-Medium type structured lipids is evaluated, using caprylic acid as medium chain and long chain fatty acids (EPA-eicosapentaenoic acid, DHA-docosahexaenoic acid, gamma-linolenic-octadecatrienoic acid and AA-arachidonic acid), as sn-2 substitutes. EPA, DHA and AA increase the melting range on both the fusion and crystallization side. gamma-linolenic shifts the melting range upwards. This predictive tool is useful for the pre-screening of lipids matching desired properties set a priori.

Adaptation for tandem cold mill models

The ideal conditions for the operation of tandem cold mills are connected to a set of references generated by models and used by dynamic regulators. Aiming at the optimization of the friction and yield stress coefficients an adaptation algorithm is proposed in this paper. Experimental results obtained from an industrial cold rolling mill are presented. (C) 2008 Elsevier B.V. All rights reserved.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Storage as a tool to improve wood fuel quality

This work analysed the influence of storage in the quality of forest biomass for energy generation in the region of Lages, Brazil. Logs of Pinus taeda L. and Eucalyptus dunnii Maiden were harvested and piled during the four different seasons: spring, summer, fall and winter. The analyses were performed immediately after harvesting (without being stored), after two, four and six months of storage. The evaluated properties were: moisture content, gross and net calorific value, ash content and solubility in cold water, hot water and sodium hydroxide. The species composition, storage span, harvesting season and storage season influenced the forest biomass characteristics. In general, eucalyptus presented better results than pine, losing moisture faster, having less alteration in the chemical composition and producing greater energetic gain over storage time. For both species, the ideal storage time was four months. Furthermore, spring and summer were the best harvesting seasons. Thus, if the forest biomass is harvested at the end of winter or beginning of spring with subsequent storage during the summer, this biomass will have the best performance for energy production. (C) 2011 Elsevier Ltd. All rights reserved.