Kinetic model for water/oil absorption of mesquite gum (Prosopis juliflora) and gum arabic (Acacia senegal)

The water and oil uptake of mesquite and arabic gums in powdered form was studied at temperatures of 23, 35 and 45°C. A previously proposed equation to predict osmotic equilibrium was tested using the experimental data with both gums and a good statistical fit was obtained. Mesquite gum showed the highest water and oil absorption at all temperatures studied. Temperature dependence of the reciprocal of the S₁ and WL_∞ were determined using an Arrhenius equation. The activation energy for water and oil absorption for gum arabic was 21.98 and 39.57 kJ mol⁻¹, compared to that of mesquite gum having values of 15.79 and 46.16 kJ mol⁻¹, respectively. A second order kinetic model was obtained for water and oil absorption for both gums.     

Analysis of the cooling capability of steam generators during the loss of residual heat removal system at midloop operation with closed primary system

Loss of residual heat removal system (RHRS) at midloop operation is one of the most significant core damage risk contributor at low power and shutdown conditions. During this kind of transients the reflux-condensation is one of the cooling mechanisms anticipated in the abnormal procedure of loss of RHRS at midloop level. In this sense, several simulations of loss of the RHRS with closed primary system with the TRACE V4.160 code have been performed considering different availability of steam generators. The present study aims to analyze the thermal-hydraulic behavior after the loss of RHRS at midloop conditions with the reflux-condensation as the only cooling mechanism available and to investigate the capability of this cooling mechanism. The simulation results show that one steam generator is sufficient to remove core decay heat of 11 MW obtaining an equilibrium pressure, but the core uncovery depends on the number of steam generators operating. Finally, an analysis of the abnormal procedure and the event trees of the loss of RHRS sequences at midloop operation has been performed taking into account the results obtained in the simulation with TRACE.     

Downhole Upgrading of Extra-heavy Crude Oil Using Hydrogen Donors and Methane Under Steam Injection Conditions

An extra-heavy crude oil underground upgrading process is described which involves the downhole addition of a hydrogen donor additive under steam injection conditions (280-315°C and residence times of at least 24-h). Laboratory experiments showed a 4° increase in the API gravity (from 9 to 12°) of the upgraded product, a two-fold reduction in the viscosity and, an approximately 8% decrease in the asphaltene content with respect to the original crude. Further increases on the temperature led to products with improved properties reaching 15°API at 315°C. It was found that the presence of the natural formation (catalysts) and methane (natural gas) is necessary to enhance the properties of the upgraded crude oil. From GC and GC-MS results a reaction pathway is proposed that involves hydrogen transfers from tetralin to the extra-heavy crude oil resulting in the formation of 1,2-dihydronaphthalene. This compound is then transformed into naphthalene, further upgrading of crude oil through hydrogen donation. The results of the experiments carried out in the presence and absence of the mineral formation and with an inert solid (SiC) strongly indicate that the former acts as a catalyst and not as a heat transfer matrix. Isotopic labeling studies (CD₄ and ¹³CH₄) give evidences that, most probably, methane is involved in the upgrading reactions.     

Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection

Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature and here the study centres on the use of the Generalized Radial Basis Function Neural Networks (GRBFNNs). An interesting property of the GRBF is that it can continuously and smoothly reproduce different RBFs by changing a real parameter τ. In addition, the mixed use of different RBF shapes in only one RBFNN is allowed. Generalized Radial Basis Function (GRBF) is based on Generalized Gaussian Distribution (GGD), which adds a shape parameter, τ, to standard Gaussian Distribution. Moreover, this paper describes a hybrid approach, Hybrid Algorithm (HA), which combines evolutionary and gradient-based learning methods to estimate the architecture, weights and node topology of GRBFNN classifiers. The feasibility and benefits of the approach are demonstrated by means of six gene microarray classification problems taken from bioinformatic and biomedical domains. Three filters were applied: Fast Correlation-Based Filter (FCBF), Best Incremental Ranked Subset (BIRS), and Best Agglomerative Ranked Subset (BARS); this was done in order to identify salient expression genes from among the thousands of genes in microarray data that can directly contribute to determining the class membership of each pattern. After different gene subsets were obtained, the proposed methodology was performed using the selected gene subsets as new input variables. The results confirm that the GRBFNN classifier leads to a promising improvement in accuracy.     

Distinct Expression Patterns of Cxcl12 in Mesenchymal Stem Cell Niches of Intact and Injured Rodent Teeth

Specific stem cell populations within dental mesenchymal tissues guarantee tooth homeostasis and regeneration throughout life. The decision between renewal and differentiation of stem cells is greatly influenced by interactions with stromal cells and extracellular matrix molecules that form the tissue specific stem cell niches. The Cxcl12 chemokine is a general marker of stromal cells and plays fundamental roles in the maintenance, mobilization and migration of stem cells. The aim of this study was to exploit Cxcl12-GFP transgenic mice to study the expression patterns of Cxcl12 in putative dental niches of intact and injured teeth. We showed that endothelial and stromal cells expressed Cxcl12 in the dental pulp tissue of both intact molars and incisors. Isolated non-endothelial Cxcl12⁺ dental pulp cells cultured in different conditions in vitro exhibited expression of both adipogenic and osteogenic markers, thus suggesting that these cells possess multipotent fates. Taken together, our results show that Cxcl12 is widely expressed in intact and injured teeth and highlight its importance as a key component of the various dental mesenchymal stem cell niches.     

A genetic tango attack against the David–Prasad RFID ultra‐lightweight authentication protocol

Radio frequency identification (RFID) is a powerful technology that enables wireless information storage and control in an economical way. These properties have generated a wide range of applications in different areas. Due to economic and technological constrains, RFID devices are seriously limited, having small or even tiny computational capabilities. This issue is particularly challenging from the security point of view. Security protocols in RFID environments have to deal with strong computational limitations, and classical protocols cannot be used in this context. There have been several attempts to overcome these limitations in the form of new lightweight security protocols designed to be used in very constrained (sometimes called ultra‐lightweight) RFID environments. One of these proposals is the David–Prasad ultra‐lightweight authentication protocol. This protocol was successfully attacked using a cryptanalysis technique named Tango attack. The capacity of the attack depends on a set of boolean approximations. In this paper, we present an enhanced version of the Tango attack, named Genetic Tango attack, that uses Genetic Programming to design those approximations, easing the generation of automatic cryptanalysis and improving its power compared to a manually designed attack. Experimental results are given to illustrate the effectiveness of this new attack.     

Study of polymer–solvent interactions by gas chromatography. Copolymers of vinyl acetate and vinyl alcohol with hydrocarbons and alcohols

The specific retention volumes of nine hydrocarbons and 12 alcohols were measured at several temperatures within the range 120–150°C in columns whose stationary phases were poly(vinyl acetate) (PVAc) and four copolymers of vinyl acetate and vinyl alcohol with 94.8, 74.4, 60.9, and 43.4 mol % of vinyl acetate units (mol % VAc). No chromatographic retention for hydrocarbons was detected in columns loaded with poly(vinyl alcohol) (PVA) or a copolymer with 11.9 mol % VAc. The retention trends are discussed and the polymers solubility parameters (δ₂) were computed from the measured Flory–Huggins χ parameters. The copolymers δ₂ values increase almost linearly with decreasing mol % VAc; PVAc, however, has a distinct behavior. The limitations of the approach in the prediction of χ parameters are discussed.