Preparation,characterization, and some physical properties of polypropylene/poly(methyl acrylate)‐grafted glass wool composites

Polypropylene/poly(methyl acrylate)‐grafted glass wool (PMA‐g‐GW) mixes were prepared. The polymerization process was carried out using potassium persulfate (PPS) and PPS/acetone sodium bisulfite (ASBS) as a redox‐pair initiation system at 60 and 70°C. The effect of using PPS or PPS/ASBS on the grafting percent and conversion percent reveals that the conversion percent values on using PPS as an initiator are higher than those of PPS/ASBS, while in the case of grafting, the inverse is true, that is, using PPS as an initiator gives grafting percent values lower than those that can be obtained using PPS/ASBS. The dielectric properties, thermal diffusivity, specific heat capacity, and thermal conductivity of PP loaded with modified glass wool as a function of different types and concentrations of initiators—used in the grafting polymerization process, namely, PPS and the redox initiating system—were also studied. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 723–732, 2003     

Surface characterization and biological properties of regular dentin,demineralized dentin,and deproteinized dentin

Bone autografts are often used for reconstruction of bone defects; however, due to the limitations of autografts, researchers have been in search of bone substitutes. Dentin is of particular interest for this purpose due to high similarity to bone. This in vitro study sought to assess the surface characteristics and biological properties of dentin samples prepared with different treatments. This study was conducted on regular (RD), demineralized (DemD), and deproteinized (DepD) dentin samples. X-ray diffraction and Fourier transform infrared spectroscopy were used for surface characterization. Samples were immersed in simulated body fluid, and their bioactivity was evaluated under a scanning electron microscope. The methyl thiazol tetrazolium assay, scanning electron microscope analysis and quantitative real-time polymerase chain reaction were performed, respectively to assess viability/proliferation, adhesion/morphology and osteoblast differentiation of cultured human dental pulp stem cells on dentin powders. Of the three dentin samples, DepD showed the highest and RD showed the lowest rate of formation and deposition of hydroxyapatite crystals. Although, the difference in superficial apatite was not significant among samples, functional groups on the surface, however, were more distinct on DepD. At four weeks, hydroxyapatite deposits were noted as needle-shaped accumulations on DemD sample and numerous hexagonal HA deposit masses were seen, covering the surface of DepD. The methyl thiazol tetrazolium, scanning electron microscope, and quantitative real-time polymerase chain reaction analyses during the 10-day cell culture on dentin powders showed the highest cell adhesion and viability and rapid differentiation in DepD. Based on the parameters evaluated in this in vitro study, DepD showed high rate of formation/deposition of hydroxyapatite crystals and adhesion/viability/osteogenic differentiation of human dental pulp stem cells, which may support its osteoinductive/osteoconductive potential for bone regeneration.     

A wrapper‐based feature selection for improving performance of intrusion detection systems

Along with expansion in using of Internet and computer networks, the privacy, integrity, and access to digital resources have been faced with permanent risks. Due to the unpredictable behavior of network, the nonlinear nature of intrusion attempts, and the vast number of features in the problem environment, intrusion detection system (IDS) is regarded as the main problem in the security of computer networks. A feature selection technique helps to reduce complexity in terms of both the executive load and the storage by selecting the optimal subset of features. The purpose of this study is to identify important and key features in building an IDS. To improve the performance of IDS, this paper proposes an IDS that its features are optimally selected using a new hybrid method based on fruit fly algorithm (FFA) and ant lion optimizer (ALO) algorithm. The simulation results on the dataset KDD Cup99, NSL‐KDD, and UNSW‐NB15 have shown that the FFA–ALO has an acceptable performance according to the evaluation criteria such as accuracy and sensitivity than previous approaches.     

High Gain Modified Dual-Band and Dual-Circularly Polarized Array Antenna

Wireless Personal Communications - A novel design of double-layer dual-band circularly polarized array antennas (DDCPAAs) is presented in this paper. First, a DDCP single antenna is introduced as...     

Inter-cell interference in multi-tier heterogeneous cellular networks: modeling and constraints

Telecommunication Systems - Interference is the main source of capacity limitation in wireless networks. In some medium access technologies in cellular networks, such as OFDMA, the allocation of...     

The preparation of an amino acid-based surfactant and its potential application as an EOR agent

Most of the synthetic surfactants investigated with the aim of enhanced chemically oil recovery in the literature have environmental drawbacks. In this work, application of an environmentally-friendly synthetic surfactant as an enhanced oil recovery agent is introduced by measuring interfacial tension of water–kerosene systems and wettability alteration of carbonate pellets. For this purpose, an amino acid-based surfactant was initially synthesized using a new synthetic approach which was subsequently confirmed by spectra of Fourier transform infrared and Proton nuclear magnetic resonance. Results showed a value of critical micelle concentration in the range of 9000–9100 ppm for this surfactant. Results also demonstrated a decrease of 38.53% in water–kerosene system interfacial tension and a 17.76% reduction in oil-wetness of the carbonate pellets.     

Adsorptive desulfurization and denitrogenation of model fuel by mesoporous adsorbents (MSU-S and CoO-MSU-S)

Adsorption of heterocyclic sulfur- and nitrogen-containing compounds by mesostructure adsorbent (MSU-S) and its modified form with cobalt oxide is studied using model fuel. The results of characteristic tests (XRD, N₂ adsorption–desorption, FTIR, and SEM) indicate that CoO impregnation causes a negative impact on mesoporous structure, crystalline phase, and particle shape along with a positive effect on surface ion exchange. CoO modification increased the adsorption loadings of DBT and BT to about 33.6% and 45.7%, respectively. For nitrogen compounds adsorption with the model fuel, adsorption loadings of quinoline and carbazole increase by 6.7% and 8.6%, respectively. Data fitting for carbazole, DBT, and BT is achieved better by the Langmuir model than the Freundlich model, and the data of quinoline fitted very well to the Freundlich model for CoO-MSU-S.     

Application of LS-SVM strategy to estimate H2S loading capacity in different ionic liquids and alkanolamines

Favorable properties of aqueous solutions are improved with the addition of different materials for separation of hydrogen sulfide (H₂S). Also, equilibrium data and available equations for solubility estimation of this gas are only valid for specific solutions and limited ranges of temperature and pressure. In this regard, a machine learning model based on Support vector machine (SVM) algorithm is proposed and developed with mixtures containing different amines and ionic liquids to predict H₂S solubility over wide ranges of temperature (298–434.5 K), pressure (13–9319 kPa), overall mass concentration (3.82–100%) and mixture's apparent molecular weight (18.39–556.17 g/mol). The accuracy of the performance of this network was evaluated by regression analysis on calculated and experimental data, which had not been used in network training.     

Modeling of CO2-brine interfacial tension: Application to enhanced oil recovery

Development of reliable and accurate models to estimate carbon dioxide–brine interfacial tension (IFT) is necessary, since its experimental measurement is time-consuming and requires expensive experimental apparatus as well as complicated interpretation procedure. In the current study, feed forward artificial neural network is used for estimation of CO₂–brine IFT based on data from published literature which consists of a number of carbon dioxide–brine interfacial tension data covering broad ranges of temperature, total salinity, mole fractions of impure components and pressure. Trial-and-error method is utilized to optimize the artificial neural network topology in order to enhance its capability of generalization. The results showed that there is good agreement between experimental values and modeling results. Comparison of the empirical correlations with the proposed model suggests that the current model can predict the CO₂–brine IFT more accurately and robustly.