Molecular investigations on the interactions of graphene,crude oil fractions and mineral aggregates at low,medium and high temperatures

Performance of the nanoparticle-modified asphalt binder is greatly influenced by adhesion properties between asphalt binder and nanoparticle. In this work, the adhesion properties of crude oil fractions (e.g., Saturate, Asphaltene, Resin and Aromatic components of asphalt binder), graphene and mineral aggregates (silicon dioxide) at various temperatures are investigated through molecular dynamic simulation and REAXFF force field. The results from SARA-graphene interface demonstrations that aromatic and asphaltene have 30% higher adhesion properties than saturate and resin. Also, while using graphene is valuable for the adhesion properties of the binder, it has no significant advantage over binder in binder-aggregate interactions.     

Comparative and competitive adsorption of Cu(II), Cd(II) and Pb(II) onto Sepia pharaonis endoskeleton biomass from aqueous solutions

In this research, the possibility of simultaneous removal of lead, cadmium and copper divalent ions from water samples through the use of Sepia pharaonis endoskeleton powder (SPEB) as bio‐material, was investigated. The bio‐sorbent was characterised by Fourier transform infrared spectrum (FT‐IR), atomic force microscopy (AFM) and X‐ray fluorescence (XRF). The different factors affecting the bio‐sorption process were studied. Langmuir and Freundlich isotherm models were applied to analyse the experimental data. The kinetic studies showed that the pseudo‐second order model kinetics were compatible with the investigated systems. It was found that under optimal conditions, this bio‐sorbent was efficient in the uptake of these heavy metal ions from both mono and multi‐metal solutions, and high removal percentages were achieved. This study verified the potential ability of SPEB as an efficient natural adsorbent for removal of Pb(II), Cd(II) and Cu(II) ions from river, tap and mineral water samples.     

On the ratio of independent complex Gaussian random variables

In this paper, we derive a closed form equation for the joint probability distribution \({{f_{{R}_{z}}},{\varTheta _{z}}}({r_{z}},{\theta _{z}})\) of the amplitude \({R_{z}}\) and phase \({\varTheta _{z}}\) of the ratio \({Z=\frac{X}{Y}}\) of two independent non-zero mean Complex Gaussian random variables \(X\sim CN(\nu _{x} \mathrm {e}^{j\phi _{x}},{\sigma ^{2}_{x}})\) and \(Y\sim CN(\nu _{y} \mathrm {e}^{j\phi _{y}},{\sigma ^{2}_{y}})\). The derived joint probability distribution only contains a confluent hypergeometric function of the first kind \({_1F_{1}}\) without infinite summations resulting in computational efficiency. We further derive the probability distribution for the ratio of two non-zero mean independent real Rician random variables containing an infinite summation generated by the estimation of the Cauchy product of equivalent series of two modified Bessel functions.     

Targeted delivery of melittin to cancer cells by AS1411 anti-nucleolin aptamer

Melittin, a small water-soluble cationic amphipathic α-helical linear peptide, consisted of 26 amino acids, is the honeybee venom major constituent. Several reports have proved the lytic and apoptotic effects of melittin in several cancerous cell lines. In this study, we aimed to fabricate an AS1411 aptamer–melittin to specifically deliver melittin to nucleolin positive cells (A549). Melittin was covalently attached to antinucleolin aptamer (AS1411) and its toxicity in A549 (nucleolin positive) and L929 (nucleolin negative) was studied using MTT and Annexin V flow cytometry methods. Aptamer–melittin conjugate formation was confirmed by gel electrophoresis. Hemolytic effect of aptamer–melittin conjugate was compared to melittin alone. The aptamer–melittin conjugate showed efficient cell uptake and was more cytotoxic in A549 cells than melittin (p?in vitro. This system can reduce the cytotoxic effects of melittin on cells with no nucleolin receptor overexpression which comprise most of normal cells such as L929 cells.     

An evolutionary non-linear ranking algorithm for ranking scientific collaborations

The social capital theory motivates some researchers to apply link-based ranking algorithms (e.g. PageRank) to compute the fitness level of a scholar for collaborating with other scholars on a set of skills. These algorithms are executed on the collaboration network of scholars and assign a score to each scholar based on the scores of his/her neighbors by solving a linear system in an iterative way. In this paper, we propose a new ranking algorithm by focusing on link-aggregation function and transition matrix. The evolution strategy technique is applied to find the best aggregation function and transition matrix for computing the score of a scholar in the collaboration network which is modeled by a hypergraph. Experiments conducted on two datasets gathered from ScivalExpert and VIVO show that the new non-linear ranking algorithm acts better than the other iterative ranking approaches for ranking scientific collaborations.     

Load Balanced Clustering Based on Imperialist Competitive Algorithm in Wireless Sensor Networks

Wireless Personal Communications - Energy consumption is one of the most serious issues in designing Wireless Sensor Networks (WSNs) for maximizing its lifetime and stability. Clustering is...     

An enhanced weighted greedy analysis pursuit algorithm with application to EEG signal reconstruction

In the past decade, compressed sensing (CS) has provided an efficient framework for signal compression and recovery as the intermediate steps in signal processing. The well-known greedy analysis algorithm, called Greedy Analysis Pursuit (GAP) has the capability of recovering the signals from a restricted number of measurements. In this article, we propose an extension to the GAP to solve the weighted optimization problem satisfying an inequality constraint based on the Lorentzian cost function to modify the EEG signal reconstruction in the presence of heavy-tailed impulsive noise. Numerical results illustrate the effectiveness of our proposed algorithm, called enhanced weighted GAP (ewGAP) to reinforce the efficiency of the signal reconstruction and provide an appropriate candidate for compressed sensing of the EEG signals. The suggested algorithm achieves promising reconstruction performance and robustness that outperforms other analysis-based approaches such as GAP, Analysis Subspace Pursuit (ASP), and Analysis Compressive Sampling Matching Pursuit (ACoSaMP).     

A prefetch-aware scheduling for FPGA-based multi-task graph systems

The Journal of Supercomputing - In partially run-time reconfigurable (PRR) FPGAs, hardware tasks should be configured before their execution. The configuration delay imposed by the reconfiguration...     

Polyurethane/amino‐grafted multiwalled carbon nanotube nanocomposites: Microstructure,thermal, mechanical,and rheological properties

A mixture of two different polyols, (polytetramethylene ether glycol and polydimethylsiloxane), were employed to synthesize a new structure of polyurethane (PU) with methylene diphenyl diisocyanate (MDI) and 1,4‐butanediol as chain extender. PU nanocomposites containing variable amount (0.3, 0.5, 1, and 3 wt %) of amino‐grafted multiwalled carbon nanotubes (NH₂‐MWNT) were prepared via in situ polymerization. The dispersion of NH₂‐MWNT into polymer matrix was investigated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Fourier transform infrared spectroscopy (FT‐IR) confirmed the urethane‐urea chemical bonding between the PU chains and the NH₂‐MWNT. Thermal stabilities of the nanocomposites were examined with thermogravimetric analysis (TGA) and the results indicated a remarkable improvement with increasing NH₂‐MWNT contents. The results of dynamic mechanical thermal analysis (DMTA) including storage modulus (E′) and glass transition temperature (T_g), as well as tensile properties demonstrated that the yield strength, strain‐at‐break, and young modulus were enhanced by increasing NH₂‐MWNT content. Rheological behavior including complex viscosity and storage and loss moduli of the PU nanocomposites improved with increasing NH₂‐MWNT loading, as well. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44411.     

Analysis and modeling of unipolar junction transistor with excellent performance: a novel DG MOSFET with $${N}^{+}{-}{P}^{-}$$ junction

We propose herein a new dual-gate metal–oxide–semiconductor field-effect transistor (MOSFET) with just a unipolar junction (UJ-DG MOSFET) on the source side. The UJ-DG MOSFET structure is constructed from an \({N}^{+}\) region on the source side with the rest consisting of a \({P}^{-}\) region over the gate and drain, forming an auxiliary gate over the drain region with appropriate length and work function (named A-gate), converting the drain to an \({N}^{+}\) region. The new structure behaves as a MOSFET, exhibiting better efficiency than the conventional double-gate MOSFET (C-DG MOSFET) thanks to the modified electric field. The amended electric field offers advantages including improved electrical characteristics, reliability, leakage current, \({I}_{\mathrm{ON}}/I_{\mathrm{OFF}}\) ratio, gate-induced drain leakage, and electron temperature. Two-dimensional analytical models of the surface potential and electric field over the channel and drain are applied to investigate the drain current in the UJ-DG MOSFET. To confirm their accuracy, the MOSFET characteristics obtained using the 2D Atlas simulator for the UJ-DG and C-DG are analyzed and compared.