Efficient numerical solution for highly transient flows

The numerical solutions for different formulations of the conservation equations based on the dependent variables, pressure (P), enthalpy (h), density (ρ), entropy (s) and flow velocity (u) for highly transient flows are presented. The models are each in turn applied for simulating the transient fluid flow dynamics following the rupture of a real and a number of hypothetical pipelines containing liquid, flashing liquid, two-phase and a permanent gas. In the case of the flashing liquid and two-phase pipelines, a significant reduction in the computational run time for the Phu and Psu based simulations as compared to the conventional Pρu formulation is observed. The above effect is found to be much less pronounced for the liquid and permanent gas inventories.     

Dyeing of chrome tanned collagen modified by in situ grafting with 2‐EHA and MAC

The aim of this study deals with the modification of the chrome tanned collagen (leather) by in situ grafting with 2‐ethyl hexyl acrylate (2‐EHA) and methacrylic acid (MAC) to improve its dyeability using Amecid Floxine 2GN (C.I. Acid Red 1) and Remazol Black B (C.I. Reactive Black 5). The optimum condition of in situ grafting has been evaluated. FTIR spectra of the ungrafted and the in situ grafted chrome tanned collagen showed that the corresponding band of the acrylate carbonyl ester occurs at 1730–1735 cm^?1 when compared with the ungrafted ones. The colorimetric data of the in situ grafted and dyed samples exhibited improvement in color shade, dye bath exhaustion, wash and light fastness relative to the ungrafted and dyed ones. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 174–179, 2006     

Preparation and antimicrobial activity of poly (vinyl chloride)/gelatin/montmorillonite biocomposite films

The aim of this study was using a novel antimicrobial thermoplastic plasticizer based on aliphatic anhydride derivative dodecenyl succinic anhydride (DSA) for blending poly (vinyl chloride), PVC, with gelatin in presence of montmorillonite (MMT) using Brabender via polymer melting technique. This anhydride-based plasticizer blended the membrane ingredients homogenously under melting process. The used plasticizer exhibited high performance antimicrobial potency for some biomedical and industrial applications. The prepared biocomposite films were evaluated for antimicrobial activity using agar disc diffusion method against gram-positive and gram-negative bacteria such as: Staphylococcus aureus (S. aureus), Klebsiella pneumonia (K. pneumonia), Bacillus cereus (B. cereus), Bacillus subtilis (B. subtilis) and Escherichia coli (E. coli). The majority of these biocomposites, except the plasticized PVC with DOP, have shown inhibitory effect at different concentrations (1.0–20) mg/ml against all above mentioned bacteria. However, C. albicans and A. niger were the most resistant strains.     

Synthesis and in vitro release study of ibuprofen-loaded gelatin graft copolymer nanoparticles

Objective: This work deals with the preparation, characterization and in vitro release study of IBU-loaded gel graft copolymer nanoparticles.

Method: Gelatin (Gel) graft copolymer nanoparticles were prepared using styrene (Sty) and/or 2-hydroxyethyl methacrylate (HEMA) monomers in the presence of potassium persulfate and glutaraldehyde as an initiator and cross-linker, respectively. The prepared nanoparticles as sustained release drug carriers were investigated using the nonsteriodal anti-inflammatory model drug, ibuprofen (IBU).

Results: The prepared nanoparticles as sustained release drug carriers were investigated using the nonsteriodal anti-inflammatory model drug, IBU. The prepared Gel/HEMA and Gel/Sty nanoparticles exhibited particles size ranging from 15 to 17?nm and from 0.42 to 5?mm, respectively. The dissolution of IBU in phosphate buffer, pH 7.4, at 37°C from the prepared nanoparticles was evaluated using UV spectroscopy. In addition, the prepared nanoparticles were characterized using Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), transmitting electron microscope (TEM) and zeta potential/particle size analyzer. In vitro dissolution study showed that the dissolution rates of the crosslinked nanoparticles were retarded relative to the uncrosslinked ones. Moreover, the released amount constantly decreases with increasing gluteraldehyde content in the gel nanoparticles.

Conclusion: Crosslinked gel-based graft copolymers exhibited slow IBU release within six hours. Furthermore, results from different characterization techniques such as TEM, particles size and zeta potential measurements confirmed the formation of pH-responsive gel-graft copolymer nanoparticles.     

Novel nanocomposites based on gelatin/HPET/chitosan with high performance acid red 150 dye adsorption

In this study, the properties of gelatin and chitosan are combined in the presence of hydrolyzed poly(ethylene terphthalate), HPET, and laponite to produce a novel hybrid natural-synthetic material for anionic dyes removal applications. Adsorption studies of acid red 150 from aqueous solution with respect to the initial dye concentration, temperature, time, pH, and sorbent dosage were investigated. The Langmuir adsorption model was applied to describe the equilibrium isotherms. The prepared nanocomposites were characterized using different techniques, such as FTIR, DSC, SEM, and TEM. The suitability of the adsorbent was tested by fitting the adsorption data with Langmuir isotherm. The results showed that the adsorption of AR150 was increased with an increasing in both of the dye and chitosan concentrations.     

Development and physicochemical characterization of clindamycin resinate for taste masking in pediatrics

Purpose: To evaluate the physicochemical characteristics of clindamycin HCl in a complex form (resinate) with ion exchange resin (IER) (Amberlite IRP69).

Methods: Drug–resin complex was prepared by simple aqueous binding method. Drug binding study was carried out at different drug and resin concentrations. Several physicochemical characterization studies were conducted to evaluate the resinate complex. These studies included flow properties, in vitro drug release in SGF and SIF, DSC, TGA, mass spectroscopy and XPRD evaluations. In addition, stability study of resinate complex was conducted at 25?and 40?°C for up to 1 month.

Results: Clindamycin and Amberlite IRP69 have formed a complex (resinate) and have shown good flow properties, good thermal properties and chemical stability (short term over 4 weeks) at 25 and 40?°C. Clindamycin release profiles from resinate in SGF and SIF have shown immediate release characteristics and release in simulated saliva has shown dependence on water volume.

Conclusion: The clindamycin stable complex with IER (Amberlite IRP69) has the potential for further development as a compatible pediatric liquid formulation (suspension) or a fast disintegrating tablet.     

Dilute magnetic semiconductor of ZnCoSe thin films: Structural,optical, and magnetic characteristics

A series of Zn_1−xCo_xSe (x = 0, 0.025, 0.050, 0.075, and 0.100) films using were evaporated (thickness of 1 μm) using electron beam gun. The effect of Co doping on the structural, optical, and magnetic properties has been investigated. X-ray diffraction studies confirm formation of zinc blend structure for all Zn_1−xCo_xSe films. The crystallite size increases and the lattice strain decreases with the increase in Co content. The elemental constituents were characterized by energy dispersive X-ray. Optical studies showed an increase in refractive index and a decrease in energy gap with the increase in the cobalt doping. The dispersion of the refractive index has been analyzed in terms of the Wemple-DiDomenico single oscillator model. The oscillator parameters including the single oscillator energy (E_o), the dispersion energy (E_d), and the static refractive index (n₀) were estimated. Magnetization measurements via vibrating sample magnetometer showed a hysteresis loop and confirmed room-temperature ferromagnetism in Co-doped ZnSe films.     

Innately adaptive robotics through embodied evolution

Autonomous adaptation in robots has become recognised as crucial for devices deployed in remote or inhospitable environments. The aim of this work is to investigate autonomous robot adaptation, focussing on damage recovery and adaptation to unknown environments. An embodied evolutionary algorithm is introduced and its capabilities demonstrated with experimental results. This algorithm is shown to be able to control the motion of a robot snake effectively; this same algorithm inherently recovers the snake’s motion after damage. Another experiment shows that the algorithm is capable of contorting a shape-changing antenna in such a way as to minimise the affect of background noise on it, thus allowing the antenna to achieve a better signal.     

Short-term traffic flow forecasting: parametric and nonparametric approaches via emotional temporal difference learning

Information signal from real case and natural complex dynamical systems such as traffic flow are usually specified by irregular motions. Chaotic nonlinear dynamics approach is now the most powerful tool for scientists to deal with complexities in real cases, and neural networks and neuro-fuzzy models are widely used for their capabilities in nonlinear modeling of chaotic systems more than the traditional methods. As mentioned, the traffic flow conditions caused the forecasting values of traffic flow to lack robustness and accuracy. In this paper, the traffic flow forecasting is analyzed with emotional concepts and multi-agent systems (MASs) points of view as a new method in this field. The findings enabled the researchers to develop a newly object-oriented method of forecasting traffic flow. Its architecture is based on a temporal difference (TD) Q-learning with a neuro-fuzzy structure, which is the nonparametric approach. The performance of TD Q-learning is improved by emotional learning. The proposed method on the present conditions and the action of the system according to the criteria could forecast traffic signals so that the objectives are reached in minimum time. The ability of presented learning algorithm to prospect gains from future actions and obtain rewards from its past experiences allows emotional TD Q-learning algorithm to improve its decisions for the best possible actions. In addition, to study in a more practical situation, the neuro-fuzzy behaviors could be modeled by MAS. The proposed method (intelligent/nonparametric approach) is compared by parametric approach, autoregressive integrated moving average (ARIMA) method, which is implemented by multi-layer perceptron neural networks and called ARIMANN. Here, the ARIMANN is updated by backpropagation and temporal difference backpropagation for the first time. The simulation results revealed that the studied forecaster could discover the optimal forecasting by means of the Q-learning algorithm. Difficult to handle through parametric and classic methods, the real traffic flow signals used for fitting the algorithms is obtained from a two-lane street I-494 in Minnesota City.