Predictions of micelle-water partition coefficients and retention in micellar electrokinetic chromatography from solute structure. 2. Fragmental constant approach

The fragmental constant approach (FCA) was used to calculate water-sodium dodecyl sulfate (SDS) micelle partition coefficients, K(mw), for uncharged solutes from their structure. Subsequently, the availability of K(mw) values allows prediction of retention factor, k, in micellar electrokinetic chromatography (MEKC) using the simple relationship k = K(mw)phi, where phi is the phase ratio. The FCA model describes a micelle-water partition coefficient as the sum of the partition coefficients of the constituent atomic/molecular fragments, measured by fragmental constant values, f (i), as well as correction factors to account for various "intramolecular effects" that cause deviations from the predicted partition coefficients as, log K(mw) = sum(n)(i=1)aif i+sum(m)(i=1)kiCm. The fragmental constants for a set of 41 fragments were determined using a training set of 229 aromatic solutes and 198 aliphatic compounds. The K(mw) of the aromatic compounds in the training set were determined by MEKC, while the K(mw) of the aliphatic solutes were estimated using the linear solvation energy relationship (LSER) for the SDS micelles. The fragments consisted of both aromatic fragments (i.e., directly attached to an aromatic ring) and aliphatic fragments. The FCA predictions agree nicely with the observed and LSER partition coefficient values, even for complex molecular structures such as beta-blocker drugs. The results show the great potential of the FCA for a priori prediction of retention behavior in MEKC from solute structure.     

The effect of emulsifiers,sugar, shortening and soya flour on the staling of barbari flat bread

A standard method has been developed to bake barbari flat-type bread. Instron was used to measure the hardness of the crumb of bread samples as a criterion of staling. Different combinations of emulsifiers, sugar, shortening and soya flour were added to the formula of barbari bread to find their effect on the retardation of hardness. Addition of soya flour increased the loaf weight but decreased its total organoleptic score. Added amounts of different additives tried in this experiment improved the hardness approximately to the same level. The best result was obtained by the addition of sodium stearoyl-2-lactylate and shortening.     

Two-Photon Photovoltaic Effect in Silicon

Optical amplification, wavelength conversion, and a myriad of other functions that were once considered to be beyond silicon's reach have been made possible by the material's nonlinear optical properties. The common feature of such devices is the high optical intensity that is required to induce the nonlinear optical interactions. Concurrent with the useful nonlinearities (Raman and Kerr) are two-photon absorption and free carrier scattering, which are two related and harmful phenomena that render silicon lossy at high intensities. This paper explores the use of the two-photon photovoltaic effect as a means to counter these phenomena in an energy-efficient manner. The effect reduces losses due to free carrier scattering and serendipitously scavenges the optical energy lost to two-photon absorption. Analytical and numerical modeling of the two-photon photovoltaic effect in silicon devices is presented. The model is validated through comparison with experimental results and is used to establish the limits of this approach for creating energy-efficient silicon photonic devices.     

Improving inter-node communications in multi-core clusters using a contention-free process mapping algorithm

High performance clusters, which are established by connecting many computing nodes together, are known as one of main architectures to obtain extremely high performance. Currently, these systems are moving from multi-core architectures to many-core architectures to enhance their computational capabilities. This trend would eventually cause network interfaces to be a performance bottleneck because these interfaces are few in number and cannot handle multiple network requests at a time. The consequence of such issue would be higher waiting time at the network interface queue and lower performance. In this paper, we tackle this problem by introducing a process mapping algorithm, which attempts to improve inter-node communications in multi-core clusters. Our mapping strategy reduces accesses to the network interface by distributing communication-intensive processes among computing nodes, which leads to lower waiting time at the network interface queue. Performance results for synthetic and real workloads reveal that the proposed strategy improves the performance from 8 % up to 90 % in tested cases compared to other methods.     

Neural Network Identification Based Multivariable Feedback Linearization Robust Control for a Two-Link Manipulator

Regarding to the variations of the load and unmodeled dynamic, robot manipulators are known as a nonlinear dynamic system. Overcoming such problems like uncertainties and nonlinear characteristics in the model of two-link manipulator is the principal goal of this paper. To approach to this aim, a neural network is combined with a linear robust control in which the result has the advantages of, the first, approximated nonlinear elements and the second, the guaranteed robustness. To design the proposed controller, at first, multivariable feedback linearization is employed to convert the nonlinear model to linear one. Second, the unknown parameters of the system are identified by neural network based on a new proposed learning rule. Third, Mixed linear feedback-H_?∞? robust control method is proposed to stabilize the closed loop system. The closed loop system based on the proposed controller is analyzed and some numerical simulations are performed. Results show suitable responses of the closed loop system.     

An integrated robust probing motion planning and control scheme: A tube-based MPC approach

‘This paper introduces the integration of a probing scheme into a robust MPC-based robot motion planning and control algorithm. The proposed solution tackles the output-feedback tube-based MPC problem using the partially-closed loop strategy to incorporate future measurements in a computationally efficient manner. This combination will provide not only a robust controller but also avoids overly conservative planning which is a drawback of the original implementation of the output-feedback tube-based MPC. The proposed solution is composed of two controllers: (i) a nominal MPC controller with probing feature to plan a globally convergent trajectory in conjunction with active localization, and (ii) an ancillary MPC controller to stabilize the robot motion around the planned trajectory. The performance and real-time implementation of the proposed planning and control algorithms have been verified through both extensive numerical simulations and experiments with a mobile robot.     

Stabilization of gas-lift oil wells by a nonlinear model predictive control scheme based on adaptive neural network models

Producing oil from gas-lift wells are often faced with severe producing oscillatory flow regimes. A major source of the oscillations is recognized as casing–heading instability which is caused by dynamic interaction between injection gas and multiphase fluid. This phenomenon poses strict production-related challenges in terms of lower average production and strain on downstream equipment. In this paper, an effective solution is proposed based on integration of an online interpretation dynamic model and a nonlinear model predictive control (NMPC) scheme. The paper uses adaptive growing and pruning radial basis function (GAP-RBF) neural networks (NNs) to recursively capture the essential dynamics of casing–heading instability in a nonlinear model structure. Extended Kalman filter (EKF) and unscented Kalman filter (UKF) are comparatively investigated to adaptively train modified GAP-RBF NNs. NMPC methodology is developed on the basis of the identified nonlinear NN model for real-time stabilization of casing–heading instability in an oil reservoir equipped with a gas-lift production well. A set of test studies has been conducted to explore the superior performance of the proposed adaptive NMPC controller under different scenarios for an oil reservoir simulated in ECLIPSE and linked to a complementary gas-lifted oil well simulated in programming environment.     

Effect of bank slope on the flow patterns in river intakes

In this work, we studied the dimensions of stream tube in the vertical as well as inclined bank conditions. Data were collected from both a physical model and a 3-D numerical model（SSIIM 2）. Equations for predicting stream tube dimensions were presented and compared with existing formulae. In comparison with vertical bank, it is found that inclining bank causes the bottom stream tube width to be greater than at the surface. The strength of secondary current formed at the entrance of branch channel is reduced. These changes in flow pattern can reduce the amount of sediment delivery into the intake.     

Ethanol production by Mucor indicus and Rhizopus oryzae from rice straw by separate hydrolysis and fermentation

Rice straw was successfully converted to ethanol by separate enzymatic hydrolysis and fermentation by Mucor indicus, Rhizopus oryzae, and Saccharomyces cerevisiae. The hydrolysis temperature and pH of commercial cellulase and β-glucosidase enzymes were first investigated and their best performance obtained at 45 °C and pH 5.0. The pretreatment of the straw with dilute-acid hydrolysis resulted in 0.72 g g^?1 sugar yield during 48 h enzymatic hydrolysis, which was higher than steam-pretreated (0.60 g g^?1) and untreated straw (0.46 g g^?1). Furthermore, increasing the concentration of the dilute-acid pretreated straw from 20 to 50 and 100 g L^?1 resulted in 13% and 16% lower sugar yield, respectively. Anaerobic cultivation of the hydrolyzates with M. indicus resulted in 0.36–0.43 g g^?1 ethanol, 0.11–0.17 g g^?1 biomass, and 0.04–0.06 g g^?1 glycerol, which is comparable with the corresponding yields by S. cerevisiae (0.37–0.45 g g^?1 ethanol, 0.04–0.10 g g^?1 biomass and 0.05–0.07 glycerol). These two fungi produced no other major metabolite from the straw and completed the cultivation in less than 25 h. However, R. oryzae produced lactic acid as the major by-product with yield of 0.05–0.09 g g^?1. This fungus had ethanol, biomass and glycerol yields of 0.33–0.41, 0.06–0.12, and 0.03–0.04 g g^?1, respectively.