An experimental study of forced convective heat transfer for fully developed Al 2 O 3 –water nanofluid in an annulus tube

Nanofluids have been known as practical materials to ameliorate heat transfer within diverse industrial systems. The current work presents an empirical study on forced convection effects of Al₂O₃–water nanofluid within an annulus tube. A laminar flow regime has been considered to perform the experiment in high Reynolds number range using several concentrations of nanofluid. Also, the boundary conditions include a constant uniform heat flux applied on the outer shell and an adiabatic condition to the inner tube. Nanofluid particle is visualized with transmission electron microscopy to figure out the nanofluid particles. Additionally, the pressure drop is obtained by measuring the inlet and outlet pressure with respect to the ambient condition. The experimental results showed that adding nanoparticles to the base fluid will increase the heat transfer coefficient (HTC) and average Nusselt number. In addition, by increasing viscosity effects at maximum Reynolds number of 1140 and increasing nanofluid concentration from 1% to 4% (maximum performance at 4%), HTC increases by 18%.     

Antisense oligonucleotide inhibition of hepatitis C virus gene expression in transformed hepatocytes

Genetic and biochemical studies have provided convincing evidence that the 5' noncoding region (5' NCR) of hepatitis C virus (HCV) is highly conserved among viral isolates worldwide and that translation of HCV is directed by an internal ribosome entry site (IRES) located within the 5' NCR. We have investigated inhibition of HCV gene expression using antisense oligonucleotides complementary to the 5' NCR, translation initiation codon, and core protein coding sequences. Oligonucleotides were evaluated for activity after treatment of a human hepatocyte cell line expressing the HCV 5' NCR, core protein coding sequences, and the majority of the envelope gene (E1). More than 50 oligonucleotides were evaluated for inhibition of HCV RNA and protein expression. Two oligonucleotides, ISIS 6095, targeted to a stem-loop structure within the 5' NCR known to be important for IRES function, and ISIS 6547, targeted to sequences spanning the AUG used for initiation of HCV polyprotein translation, were found to be the most effective at inhibiting HCV gene expression. ISIS 6095 and 6547 caused concentration-dependent reductions in HCV RNA and protein levels, with 50% inhibitory concentrations of 0.1 to 0.2 microM. Reduction of RNA levels, and subsequently protein levels, by these phosphorothioate oligonucleotides was consistent with RNase H cleavage of RNA at the site of oligonucleotide hybridization. Chemically modified HCV antisense phosphodiester oligonucleotides were designed and evaluated for inhibition of core protein expression to identify oligonucleotides and HCV target sequences that do not require RNase H activity to inhibit expression. A uniformly modified 2'-methoxyethoxy phosphodiester antisense oligonucleotide complementary to the initiator AUG reduced HCV core protein levels as effectively as phosphorothioate oligonucleotide ISIS 6095 but without reducing HCV RNA levels. Results of our studies show that HCV gene expression is reduced by antisense oligonucleotides and demonstrate that it is feasible to design antisense oligonucleotide inhibitors of translation that do not require RNase H activation. The data demonstrate that chemically modified antisense oligonucleotides can be used as tools to identify important regulatory sequences and/or structures important for efficient translation of HCV.     

Study of the morphology and mechanical properties of polypropylene composites with silica or rice‐husk

The mechanical, morphological behavior and water absorption characteristics of polypropylene (PP) and silica, or PP and rice‐husk, composites have been studied. The silica used in this study as filler was a commercial type produced from soluble glass or rice husks. The compatibilizing effect of PP grafted with monomethyl itaconate (PP‐g‐MMI) and/or with vinyltriethoxysilane (PP‐g‐VTES) as polar monomers on the mechanical properties and water absorption was also investigated. In general, a high loading of the studied fillers in the polymer matrix increases the stiffness and the water absorption capacity. This effect is more noticeable in the tensile modulus of the PP/silica composite with PP‐g‐VTES as compatibilizer. However, the increase of the rice‐husk charge as a natural filler in the PP matrix decreases the stiffness, and in the presence of PP‐g‐MMI as compatibilizer in PP/rice‐husk, the tensile modulus and water absorption of the composite were improved. The better adhesion and phase continuity in the PP/silica and PP/rice‐husk composites with different compatibilizers was confirmed by the morphological study. Copyright © 2004 Society of Chemical Industry     

Strength evaluation of granite block samples with different predictive models

Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (V_p) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R²) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.

     

Influence of grafted polypropylene on the mechanical properties of mineral‐filled polypropylene composites

The purpose of this work was to study how mineral fillers would behave in a polypropylene (PP) matrix when PP modified with maleic anhydride (MA) and/or itaconic acid (IA) was used as a coupling agent in the preparation of mineral‐filled PP composites. The composites were characterized with tensile mechanical measurements and morphological analysis. The optimum amount of the coupling agent to be used to obtain composites with improved mechanical properties was established. The results indicated that these coupling agents enhanced the tensile strength of the composites significantly, and the extent of the coupling effect depended on the nature of the interface that formed. The incorporation of coupling agents enhanced the resistance to deformation of the composite. The behavior of IA‐modified PP as a coupling agent was similar to that of a commercial MA‐modified PP for the filled PP composites. Evidence of improved interfacial bonding was revealed by scanning electron microscopy studies, which examined the surfaces of fractured tensile test specimens; their microstructures confirmed the mechanical results with respect to the observed homogeneous or optimized dispersion of the mineral‐filler phase in these composites. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 2343–2350, 2007     

Polynomial time approximation algorithms for proportionate open‐shop scheduling

This paper deals with the presentation of polynomial time (approximation) algorithms for a variant of open‐shop scheduling, where the processing times are only machine‐dependent. This variant of scheduling is called proportionate scheduling and its applications are used in many real‐world environments. This paper develops three polynomial time algorithms for the problem. First, we present a polynomial time algorithm that solves the problem optimally if , where n and m denote the numbers of jobs and machines, respectively. If, on the other hand, , we develop a polynomial time approximation algorithm with a worst‐case performance ratio of that improves the bound existing for general open‐shops. Next, in the case of , we take into account the problem under consideration as a master problem and convert it into a simpler secondary approximation problem. Furthermore, we formulate both the master and secondary problems, and compare their complexity sizes. We finally present another polynomial time algorithm that provides optimal solution for a special case of the problem where .     

Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine

Neural Computing and Applications - This paper proposes a novel extreme learning machine (ELM)-based fixed time adaptive trajectory control for electronic throttle valve system with uncertain...     

Improved bioavailability and pharmacokinetics of tea polyphenols by encapsulation into gelatin nanoparticles

The authors prepared surface modified (with polyelectrolyte layers), tea polyphenols (TPP) encapsulated, gelatin nanoparticles (TPP‐GNP) and characterised them. The size of the spherical nanoparticles was ∼50 nm. Number of polyelectrolyte layers and incubation time influenced the encapsulation efficiency (EE); highest EE was noted in nanoparticles with six polyelectrolyte layers (TPP‐GNP‐6L) incubated for 4 h. TPP released from TPP‐GNP‐6L in simulated biological fluids indicated protection and controlled release of TPP due to encapsulation. Mathematical modelling indicated anomalous type as a predominant mode of TPP release. TPP‐GNP‐6L exhibited enhanced pharmacokinetics in rabbit model compared with free TPP. The area under the concentration‐time curve and mean residence time were significantly higher in TPP‐GNP‐6L compared with free TPP which provide an evidence of higher bioavailability of TPP due to encapsulation. The authors demonstrated that encapsulation of TPP into GNPs favoured slow and sustained release of TPP with improved pharmacokinetics and bioavailability thereby can prolong the action of TPP.Inspec keywords: gelatin, nanoparticles, encapsulation, biomedical materials, nanomedicine, particle size, polymer electrolytes, polymer films, nanofabricationOther keywords: bioavailability, pharmacokinetics, gelatin nanoparticles, surface modified tea polyphenols, polyelectrolyte layers, spherical nanoparticle size, incubation time, encapsulation efficiency, TPP‐GNP‐6L, simulated biological fluids, mathematical modelling, TPP release, rabbit model, concentration‐time curve, mean residence time, time 4 h     

Nadir compromise programming: A model for optimization of multi-objective portfolio problem

In problem of portfolio selection, financial Decision Makers (DMs) explain objectives and investment purposes in the frame of multi-objective mathematic problems which are more consistent with decision making realities. At present, various methods have introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. Considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective problems. In order to illustrate NCP performance and operational capability, we implement a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.