Statistical Optimization for Production of Light Olefins in a Fluidized‐Bed Reactor

The methanol‐to‐olefins reaction (MTO) was studied in a small‐scale fluidized‐bed reactor over synthesized silicoaluminophosphate (SAPO‐34) catalysts. Mesoporous nanocrystalline SAPO‐34 molecular sieves were synthesized hydrothermally by ultrasonic and microwave‐assisted aging processes in the presence of hexadecyltrimethylammonium bromide (CTAB) and tetradecyldimethyl(3‐trimethoxysilylpropyl)ammonium chloride (TPOAC) as surfactant agents. The Box‐Behnken experimental design method was applied to determine the optimum operating parameters of this process conducted in the fluidized‐bed reactor. The optimum conditions in terms of reaction temperature, ratio of inlet gas velocity to minimum fluidizing velocity, and MeOH weight fraction were evaluated.     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

Access point selection in the network of Internet of things (IoT) considering the strategic behavior of the things and users

The Journal of Supercomputing - With the expansion in the use of IoT, increasing the efficiency of these networks has become even more significant. Objects need reliable communications at suitable...     

Endothelin receptors mediating vasoconstriction in rat pressurized small arteries

The effects of endothelin-1 (ET-1), a nonselective ETA and ETB receptor agonist, and sarafotoxin S6c, a selective ETB agonist, were investigated in the presence and absence of BQ123 and BQ788, ETA- and ETB-selective antagonists, respectively, in rat mesenteric small arteries, using a perfusion pressurized arteriograph in which segments of vessels were cannulated and exposed to constant pressure and flow. ET-1 (10(-13)-10(-7) M) induced vasoconstriction in both intact and endothelium-denuded arteries in a concentration-dependent manner. BQ123 (10(-7) and 10(-6) M) inhibited the effect of ET-1, displacing the concentration-response curve to the right in a concentration-dependent manner. The effect of ET-1 was not significantly affected by BQ788 (10(-7) and 10(-6) M), a selective antagonist of ETB receptors. Sarafotoxin S6c (10(-11)-10(-7) M) also induced a slight concentration-dependent vasoconstriction. The effect of sarafotoxin S6c (10(-8) M) was inhibited by the ETB-selective antagonist BQ788 (10(-7) M), but was not significantly changed by BQ123 (10(-7) M). Vasoconstriction induced by sarafotoxin S6c (10(-8) M) in a single bolus concentration was significantly greater than the contraction induced by the same concentration as part of a cumulative concentration-response curve, indicating desensitization or downregulation of ETB receptors during the latter. Repeated application of single concentrations of sarafotoxin S6c (10(-8) M) caused progressively smaller contraction of arteries. These results show the existence of both ETA and ETB vasoconstrictor receptors located on smooth muscle of small arteries. They also show that ETB receptors induce a smaller constrictor effect, and rapidly undergo desensitization after sustained or repeated activation.     

Synthesis of poly(methyl methacrylate)/silica nanocomposite through emulsion polymerization using dimethylaminoethyl methacrylate

Polymer/Silica nanocomposite latex particles were prepared by emulsion polymerization of methyl methacrylate (MMA) with dimethylaminoethyl methacrylate (DM). The reaction was performed using a nonionic surfactant and in the presence of silica nanoparticles as the seed. The polymer‐coated silica nanoparticles with polymer content and number average particle sizes ranged from 32 to 93 wt % and 114–310 nm, respectively, were obtained depending on reaction conditions. Influences of some synthetic conditions such as MMA, DM, surfactant concentration, and the nature of initiator on the coating of the silica nanoparticles were studied. Electrostatic attraction between anionic surface of silica beads and cationic amino groups of DM is the main driving force for the formation of the nanocomposites. It was demonstrated that the ratio of DM/MMA is important factor in stability of the system. The particle size, polymer content, efficiency of the coating reaction, and morphology of resulted nanocomposite particles showed a dependence on the amount of the surfactant. Zeta potential measurements confirmed that the DM was located at the surface of the nanocomposites particles. Thermogravimeteric analysis indicated a relationship between the composition of polymer shell and polymer content of the nanocomposites. The nanocomposites were also characterized by FTIR and differential scanning calorimetry techniques. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.     

Performance improvement of OFDM systems using compressive sensing with group LASSO signal reconstruction algorithm

Wireless Networks - Orthogonal frequency division multiplexing (OFDM) has been investigated for the high-speed transmission of data in radio frequency and optical wireless communications. The OFDM...     

ETAS: predictive scheduling of functions on worker nodes of Apache OpenWhisk platform

The Journal of Supercomputing - Fast execution of functions is an inevitable challenge in the serverless computing landscape. Inefficient dispatching, fluctuations in invocation rates, burstiness...     

Robust Output Feedback Controller Design for Time‐Delayed Teleoperation: Experimental Results

In this paper, a robust output feedback control strategy is proposed for a nonlinear teleoperation system which can deal with stability as well as transparency despite the variable time‐delay and uncertain dynamics. The proposed approach is composed of two steps. First, local Lyapunov based adaptive controllers are applied to both master and slave sides in order to suppress the nonlinearities in the system dynamics. Afterwards, a new observer‐based controller scheme is proposed to achieve stability and performance (transparency) of the teleoperation system. Using the Lyapunov techniques, stability and performance objectives are cast as some linear matrix inequality (LMI) feasibility conditions. To evaluate the performance of the proposed controller, a set of simulations and experiments are performed. Through simulation results, it is demonstrated that the proposed approach significantly outperforms the existing methodologies reported in the literature.