Influence of chitosan/clay functional bionanocomposite activated with rosemary essential oil on the shelf life of fresh silver carp

A combination of chitosan biopolymer, nanoclay and rosemary essential oil was prepared as a functional bionanocomposite (FBN). Its ability to improve the shelf life of refrigerated (4 ± 1 °C) silver carp fillets was studied. The fresh fillets were left untreated as a control or coated with chitosan, chitosan/clay bionanocomposite and chitosan/clay/rosemary essential oil (Ch/clay/REO) FBN. Then, they were evaluated for chemical, microbial and sensory properties over 16‐day storage. The samples coated with the FBN had the lowest pH and total volatile basic nitrogen. Ch/clay/REO coating efficiently retarded lipid oxidation by decreasing peroxide, free fatty acid and thiobarbituric acid production in the samples. The coating also reduced total viable and psychrotrophic count of the fillets more than 1.5 log by the end of storage.     

Comparing rutting of airfield pavements to simulations using Pavement Analysis Using Nonlinear Damage Approach (PANDA)

This study presents the rutting performance results of full-scale pavement test sections subjected to F-15E and C-17 aircraft wheels at two different temperatures. Pavement structures for the tests were constructed under shelter in the U.S. Army Engineer Research and Development Center's (ERDC) pavement test facility. The full-scale test results are used to validate viscoelastic, viscoplastic and hardening-relaxation constitutive relationships implemented in the Pavement Analysis Using Nonlinear Damage Approach (PANDA) model. PANDA is a mechanistic-based model which incorporates nonlinear viscoelastic, viscoplastic, hardening-relaxation, viscodamage, moisture-induced damage and ageing constitutive relationships. Results of dynamic modulus and different repeated creep-recovery laboratory tests are analysed to extract the parameters associated with viscoelastic, viscoplastic and hardening-relaxation constitutive relationships implemented in PANDA. Once calibrated, PANDA is used to predict the rutting performance observed in full-scale pavement test sections. The simulation results illustrate that PANDA is capable of predicting the rutting of airfield pavements subjected to heavy aircraft wheel loads at intermediate and high temperatures. It is shown that PANDA successfully predicts the effect of shear flow and upheaval at the edges of the wheel. The data from simulation suggested that PANDA, once calibrated, can provide insight into the critical locations of tensile and compressive stresses within the pavement structure. PANDA simulations not only provide a tool for evaluating existing structures, but also can be used in designing more sustainable pavement structures and materials.     

Effect of parameters on roll dynamic response of an articulated vehicle carrying liquids

Directional response and roll stability characteristics of a partly filled tractor semi-trailer vehicle, with cylindrical tank, under different parameters and conditions are investigated. The effective parameters and conditions in the stability of a tractor semi-trailer carrying liquid can be considered as filled volume, kinematic viscosity of liquid cargo and vehicle steering input. The dynamic interaction of liquid cargo with the tractor semi-trailer vehicle is evaluated by integrating a dynamic slosh model of the partly filled tank with five-degrees-offreedom of a tractor semi-trailer tank model. The dynamic fluid slosh within the tank is modeled using three-dimensional Navier-Stokes equations, coupled with the volume-of-fluid equations and analyzed using FLUENT software. The coupled tank-vehicle model is subsequently analyzed to determine the roll stability characteristics for different conditions and maneuvers. The results show effects of parameter variations on roll stability of the vehicle carrying liquid and also fluid’s behavior in interaction with a vehicle’s dynamics.     

CPTR: conditional probability tree based routing in opportunistic networks

In opportunistic networks due to the inconsistency of the nodes link, routing is carried out dynamically and we cannot use proactive routes. In these networks, nodes use opportunities gained based on store-carry-forward patterns to forward messages. Every node that receives a message when it encounters another node makes decision regarding the forwarding or not forwarding the node encountered. In some previous methods, the recognition of whether encounter with current node is considered as an appropriate opportunity or not has been carried out based on the comparison of the probability of carrier node and the node encountered. In these methods, if the message is delivered to the encountered node, a better opportunity would be lost. To fight with this challenge we have posed CPTR method by using conditional probability tree method through which in addition to the probability of the delivery of carrier and encountered nodes’ message delivery, the opportunities for after encounter will be involved in messages’ forwarding. Results of simulation showed that the proposed method can improve the ratio of delivery and delay of message delivery compared to other similar methods in networks with limited buffer.     

Zinc oxide nanoparticles: solvent-free synthesis,characterization and application as heterogeneous nanocatalyst for photodegradation of dye from aqueous phase

In present study, for the first time, ZnO nanoparticles have been synthesized via a simple, novel, solvent and template free solid-state thermal decomposition of the mixed Zn(NO₃)·6H₂O and cochineal powders as a novel starting reagent at 600?°C for 3 h. The as-prepared product was analyzed by XRD, EDS, SEM, TEM, FT-IR and DRS. Besides, the effect of cochineal powder on the morphology and particle size of ZnO nanoparticles was investigated. The results exhibited that cochineal powder prevents the sintering of nanoparticles and leads to formation of uniform particles. Moreover, the efficiency of ZnO nanoparticles as a photocatalyst for the decolorization of methylene orange (MO) has been evaluated and 90% degradation of MO was obtained after 120 min.     

Simple size-controlled fabrication of Zn2SnO4 nanostructures and study of their behavior in dye sensitized solar cells

Zn₂SnO₄ nanostructures were obtained via facile and rapid co-precipitation approach in presence of amines with different long chain as a novel basic and capping agents. The effect of different amines such as NH₃, ethylenediamine, triethylenetetramine, tetraethylenepentamine on the size of Zn₂SnO₄ nanostructures were investigated. The results demonstrated that applying the appropriate amount of organic amine could be effective in particle size control. The obtained nanostructure products were specified by powder X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectra, scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX) and ultraviolet–visible (UV–vis) spectroscopy. Dye sensitized solar cells (DSSC) were created by the constructed electrodes as working electrode and then were studied by current density–voltage (J–V) curve. It was found that incorporating of TiO₂ nanoparticles to optimized Zn₂SnO₄ nanostructures has significant role on the constructed DSSCs photovoltaic properties.     

Application of artificial neural network for vapor liquid equilibrium calculation of ternary system including ionic liquid: Water, ethanol and 1-butyl-3-methylimidazolium acetate

A feed forward three-layer artificial neural network (ANN) model was developed for VLE prediction of ternary systems including ionic liquid (IL) (water+ethanol+1-butyl-3- methyl-imidazolium acetate), in a relatively wide range of IL mass fractions up to 0.8, with the mole fractions of ethanol on IL-free basis fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and 0.98. The output results of the ANN were the mole fraction of ethanol in vapor phase and the equilibrium temperature. The validity of the model was evaluated through a test data set, which were not employed in the training case of the network. The performance of the ANN model for estimating the mole fraction and temperature in the ternary system including IL was compared with the non-random-two-liquid (NRTL) and electrolyte non-random-two-liquid (eNRTL) models. The results of this comparison show that the ANN model has a superior performance in predicting the VLE of ternary systems including ionic liquid.