Characterization of aromatic compounds and biological activities of essential oils from Tunisian aromatic plants

The aromatic compounds and biological activities of essential oils from six Tunisian aromatic plants including Artemisia herba-alba, Rosmarinus officinalis, Thymus capitatus, Mentha piperita, Ocimum basilicum and Artemisia absinthium were investigated. Hydro-distillation was used to extract essential oil from these plants. The identification of compounds from essential oils was performed using GC–MS analysis. Camphor (28.47%) was the major compound of A. absinthium essential oil. High contents of verbenone (20.99%) and camphor (19.72%) were found in R. officinalis. In the case of T. capitatus, carvacrol (81.09%), gamma terpinene (6.61%) and caryophyllene (4.87%) were identified as the major compounds. While eugenol (24.69%), linalool (18.00%) were characteristic compounds of O. basilicum essential oil, camphor (39.10%) and farnesol (14.25%) together with bornyl acetate (12.31%) were the main constituents of A. absinthium. These oils were also subjected to a screening for their antioxidant activity and essential oil from A. absinthium showed a greater antioxidant activity (IC₅₀?=?0.0063 mg/mL) compared to the standard Vitamin E (IC₅₀?=?0.019 mg/mL). The antibacterial activities of the oils against seven pathogenic strains, Pseudomonas aeruginosa, Bacillus cereus, Salmonella, Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Enterococcus faecalis and Micrococcus luteus, were tested. The highest and broadest activity was shown by M. piperita; however, Ocimum basilicum was inactive against all strains. Essential oils were also evaluated for antidiabetic and anti-acetylcholinesterase activities. The IC₅₀ values of A. herba-alba and O. basilicum against α-amylase were respectively 17.76 and 16.32 µg/mL suggesting a powerful anti-diabetic effect comparable to that of acarbose (IC₅₀?=?14.88 µg/mL). R. officinalis, M. piperita and A. absinthium exhibited an interesting acetylcholinesterase inhibition with IC₅₀ equal to 22, 24 and 58 µg/mL respectively.     

NEURAL NETWORK–BASED HEAT AND MASS TRANSFER COEFFICIENTS FOR THE HYBRID MODELING OF FLUIDIZED REACTORS

The complex flow patterns induced in fluidized bed catalytic reactors and the competing parameters affecting the mass and heat transfer characteristics make the design of such reactors a challenging task to accomplish. The models of such processes rely heavily on predictive empirical correlations for the mass and heat transfer coefficients. Unfortunately, published empirical-based correlations have the common shortcoming of low prediction efficiency compared with experimental data. In this work, an artificial neural network approach is used to capture the reactor characteristics in terms of heat and mass transfer based on published experimental data. The developed ANN-based heat and mass transfer coefficients relations were used in a conventional FCR model and simulated under industrial operating conditions. The hybrid model predictions of the melt-flow index and the emulsion temperature were compared to industrial measurements as well as published models. The predictive quality of the hybrid model was superior to other models. This modeling approach can be used as an alternative to conventional modeling methods.     

Optimal hybrid modeling approach for polymerization reactors using parameter estimation techniques

The dynamics of polymerization catalytic reactors have been investigated by many researchers during the past five decades; however, the emphasis of these studies was directed towards correlating process model parameters using empirical investigation based on small scale experimental setup and not on real process conditions. The resulting correlations are of limited practical use for industrial scale operations. A statistical study for the relative correlation of each of the effective process parameters revealed the best combination of parameters that could be used for optimizing the process model performance. Parameter estimation techniques are then utilized to find the values of these parameters that minimize a predefined objective function. Published real industrial scale data for the process was used as a basis for validating the process model. To generalize the model, an artificial neural network approach is used to capture the functional relationship of the selected parameters with the process operating conditions. The developed ANN-based correlation was used in a conventional fluidized catalytic bed reactor (FCR) model and simulated under industrial operating conditions. The new hybrid model predictions of the melt-flow index and the emulsion temperature were compared to industrial measurements as well as published models. The predictive quality of the hybrid model was superior to other models. The suggested parameter estimation and modeling approach can be used for process analysis and possible control system design and optimization investigations.     

Optimization of alkylresorcinols extraction from triticale bran using response surface methodology

Optimization conditions for alkylresorcinols (ARs) extraction from triticale bran were determined using response surface methodology. A central composite design was used to determine the effects of extraction temperature (degrees Celsius) and solid-to-solvent ratio (weight per volume) on yield of saturated, unsaturated and total ARs. Extraction of ARs was affected significantly (p value????0.05) by temperature and solid-to-solvent ratio on the yield of saturated, unsaturated and total ARs. The highest quantity of total ARs from triticale bran was extracted at 24?°C between 16 and 24?h at a solid-to-solvent ratio (weight per volume) of 1:40 and ranged from 278 to 308?mg/100?g, while saturated and unsaturated ARs were 163 to 225?mg/100?g and 22 to 29?mg/100?g, respectively. The ARs identified by high-performance liquid chromatography included: C15:0, C17:0, C19:0, C21:0, C23:0 and C25:0. Also some unsaturated analogues (12.4% to 14.0%) were found including C17:1, C19:1, C21:1 and C23:1. Analysis of variance (p value?=?0.05) indicated that the response surface methodology (RSM) developed for saturated, unsaturated and total ARs were adequate and explained most of the variability (85% to 89%) with high coefficient of multiple determination (R ²?=?0.89). The main effect of the response variable was quadratic rather than a linear function. Our results showed that RSM is a tool that is useful to optimise experimental conditions for the extraction of ARs.     

Dynamic modeling of gas phase propylene homopolymerization in fluidized bed reactors

A new model with comprehensive kinetics for propylene homopolymerization in fluidized bed reactors was developed to investigate the effect of mixing, operating conditions, kinetic and hydrodynamic parameters on the reactor performance as well as polymer properties. Presence of the particles in the bubbles and the excess gas in the emulsion phase was considered to improve the two-phase model, thus, considering the polymerization reaction to take place in both the bubble and emulsion phases. It was shown that in the practical range of superficial gas velocity and catalyst feed rate, the ratio of produced polymer in the bubble phase to the total production rate is roughly between 10% and 13%, which is a substantial amount and cannot be ignored. Simulation studies were carried out to compare the results of the improved two-phase, conventional well-mixed and constant bubble size models. The improved two-phase and well mixed models predicted a narrower and safer window at the same running conditions compared with the constant bubble size model. The improved two-phase model showed close dynamic behavior to the conventional models at the beginning of polymerization, but starts to diverge with the evolution of time.     

Detection of Streptococcus macedonicus in Greek cheeses

The aim of the present work was the detection and enumeration of Streptococcus macedonicus in Greek traditional cheeses. A total of 68 traditional cheese samples have been examined. Enumeration was performed by plating on the S. macedonicus differential medium Bromothymol Blue Streptococcus macedonicus (BBSM). Detection of S. macedonicus was confirmed by species-specific polymerase chain reaction (PCR), using as template either cheese DNA or DNA from colonies isolated from the BBSM medium. Counts of S. macedonicus on BBSM medium ranged from less than 1 to 6.84 log cfu g^?1. S. macedonicus has been detected in 15 samples out of the 68 tested, corresponding to 13 out of the 20 different cheese varieties examined, originating from various geographical areas in Greece. This indicates that S. macedonicus is widespread in Greek cheeses. However, its presence could not be correlated either with the cheese variety or the cheese manufacturing procedures.     

Dielectric relaxation of monoesters based poly(styrene-co-maleic anhydride) copolymer

A series of alkyl-grafted copolymers based on styrene-maleic anhydride (SMA) copolymers were synthesized by esterification of SMA with several long chain normal aliphatic alcohols. The prepared copolymers were characterized by FT-IR and ¹H NMR and DSC. The dielectric behavior of these copolymers was investigated in the frequency 20–10⁵ Hz and temperature −40 to 180 °C ranges. Two relaxation processes were observed, α, and β-relaxation. The former is associated with the glass-rubber transition and is characterized by the Vogel–Fulcher–Tammann temperature dependence and the latter relaxation is related to the local motion of the ester side groups attached to the polymer backbone. The apparent activation energy for the β-relaxation was found to depend significantly on the alkyl chain length. The dielectric analysis of the β-relaxation process detected is discussed.     

Use of silica gel for improving waterflooding performance of bottom-water reservoirs

This research addresses the problem of waterflooding a medium-gravity of oil-bearing formation with a water leg, and offers recommendations for process selection. In many reservoirs the presence of a bottom-water zone results in a very poor areal and vertical sweep efficiencies. However, waterflooding still remains the most widely used oil-recovery technique for these reservoirs. Waterflood performance in these reservoirs can be improved greatly with effective methods of partially plugging the bottom-water zone. One such method is the use of CO₂-activated silica gel as a blocking agent in the presence of a bottom-water zone.Thirteen large-model experiments were conducted using silica gel, to study the effect of oil-to-water zone permeability contrast and thickness ratio, oil viscosity, and CO₂ injection. A qualitative comparison is made to show the relative merit of CO₂-activated silica gel injection among other mobility control agents. Several runs were conducted to study silica gel rheology both in presence and in absence of CO₂.     

FA–QABC–MRTA: a solution for solving the multi-robot task allocation problem

Intelligent Service Robotics - The problem of task allocation in a multi-robot system is the situation where we have a set of tasks and a number of robots; then each task is assigned to the...     

An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB-IoT

Wireless Personal Communications - Smart Home is one of the most established applications of the Internet of Things. Almost every equipment we use in our daily life—appliances, electric...