微波辅助燃烧法制备镁铝尖晶石纳米粉体的研究

Stoichiometric MgAl2O4 spinel nanoparticles were synthesized by microwave assisted combustion reaction from aluminium nitrate nanohydrate(Al(NO3)3.9H2O) and Sol-Gel prepared magnesium hydroxide(Mg(OH)2) in the presence of urea((NH2)2CO) as a fuel,in about 20 min of irradiation.X-ray diffraction(XRD) studies reveal that mi-crowave assisted combustion synthesis route yields single-phase spinel nanoparticles with larger crystalline size(around 75 nm) than other conventional heating methods.Scanning electronic microscope(SEM) images show nanoparticles with spherical shape and homogenous morphology.The surface area measurements(SBET) show crystals with 2.11 m2/g and 0.0033 mL/g pore volume.     

Possibility of using chemical fertilizers instead of 9K medium in bioleaching process of low-grade sulfide copper ores

The possibility of applying chemical fertilizers as a source of nutrients for bacterial growth in bioleaching process was investigated. In the first part of the experiment the nutrient content of four sulfide copper ore samples was determined. The results confirmed that the amount of calcium, magnesium and sulfur were sufficient to support bacterial growth, whereas nitrogen, phosphorous and potassium were not sufficient. Therefore, N, P, and K from a chemical fertilizer source were applied to the sulfide copper ores to make a cost-effective bioleaching process. According to shake flask experiments by using mesophilic, iron-sulfur oxidizing bacteria, bacterial activity and copper recovery in some proposed media was satisfactory compared to 9K medium. Additionally, potassium had positive effect on the copper ore bioleaching while NO₃⁻ and Cl⁻ had inhibitory effect on the bacterial activity.     

Thermophysical Properties of Ionic Liquid, 1-Pentyl-3-methylimidazolium Chloride in Water at Different Temperatures

Osmotic coefficients, , electrical conductance data, Λ, and refractive indices, n _D, of aqueous solutions of the ionic liquid, 1-pentyl-3-methylimidazolium chloride [PnMIm]Cl have been measured at T = (298.15, 308.15, 318.15, and 328.15) K. Measurements of osmotic coefficients were carried out by the vapor-pressure osmometry method (VPO). Osmotic coefficient values show that ion–solvent interactions are stronger at lower temperature. The osmotic coefficients were correlated to the Pitzer-ion interaction and modified NRTL (MNRTL) models. From these data, mean molal activity coefficients, γ±, and excess Gibbs free energies, G ^E, have been calculated. Electrical conductance data have been applied for determination of association constants, K _a, and limiting molar conductances, Λ ₀, using the low concentration chemical model (lcCM). Calculated ion-association constant, K _a, values show that ion-association effects increase at high temperatures which is in agreement with osmotic coefficient results. Experimental results of refractive indices for the binary system are reported, and have been fitted by a polynomial expansion.     

双K-BRB防屈约束支撑在侧向载荷下的行为

防屈约束支撑(BRB)是一种能有效抵抗具有高地震能量吸收能力的侧向载荷的系统.虽然防屈约束支撑已经证实具有令人满意的行为,但系统刚度不理想,它能被防屈约束支撑的配置变化抵消.为此,研究了双K-BRB(DK)防屈约束支撑的配置,以实现更合适的行为.同时,还提出了设计该系统所需的数学公式.将DK系统与其他传统BRB进行比较...     

Using three chemical looping reactors in ammonia production process – A novel plant configuration for a green production

Production of three pure streams of H₂, N₂ and CO₂ makes the chemical looping reactors as an attractive intermediate technology to provide the feedstock of ammonia synthesis loop. As a goal of paper, for the first time, a novel and green plant configuration using three chemical looping reactors is proposed for ammonia production in which needed hydrogen and nitrogen are produced by means of a process simpler than the conventional technologies. Due to the reduction in plant units and also 30% increase in production ratio and simultaneously production of economically valuable by-products of H₂, N₂ and CO₂, significant potential for investment cost reduction along with CO₂ capture and storage can be anticipated. Moreover, the proposed plant for ammonia production is very flexible in terms of adjusting the desired main products.     

A new feature subset selection using bottom-up clustering

Feature subset selection and/or dimensionality reduction is an essential preprocess before performing any data mining task, especially when there are too many features in the problem space. In this paper, a clustering-based feature subset selection (CFSS) algorithm is proposed for discriminating more relevant features. In each level of agglomeration, it uses similarity measure among features to merge two most similar clusters of features. By gathering similar features into clusters and then introducing representative features of each cluster, it tries to remove some redundant features. To identify the representative features, a criterion based on mutual information is proposed. Since CFSS works in a filter manner in specifying the representatives, it is noticeably fast. As an advantage of hierarchical clustering, it does not need to determine the number of clusters in advance. In CFSS, the clustering process is repeated until all features are distributed in some clusters. However, to diffuse the features in a reasonable number of clusters, a recently proposed approach is used to obtain a suitable level for cutting the clustering tree. To assess the performance of CFSS, we have applied it on some valid UCI datasets and compared with some popular feature selection methods. The experimental results reveal the efficiency and fastness of our proposed method.     

A study on virtual machine deployment for application outsourcing in mobile cloud computing

In mobile cloud computing, application offloading is implemented as a software level solution for augmenting computing potentials of smart mobile devices. VM is one of the prominent approaches for offloading computational load to cloud server nodes. A challenging aspect of such frameworks is the additional computing resources utilization in the deployment and management of VM on Smartphone. The deployment of Virtual Machine (VM) requires computing resources for VM creation and configuration. The management of VM includes computing resources utilization in the monitoring of VM in entire lifecycle and physical resources management for VM on Smartphone. The objective of this work is to ensure that VM deployment and management requires additional computing resources on mobile device for application offloading. This paper analyzes the impact of VM deployment and management on the execution time of application in different experiments. We investigate VM deployment and management for application processing in simulation environment by using CloudSim, which is a simulation toolkit that provides an extensible simulation framework to model the simulation of VM deployment and management for application processing in cloud-computing infrastructure. VM deployment and management in application processing is evaluated by analyzing VM deployment, the execution time of applications and total execution time of the simulation. The analysis concludes that VM deployment and management require additional resources on the computing host. Therefore, VM deployment is a heavyweight approach for process offloading on smart mobile devices.     

The three-parameter corresponding states principle

A multiproperty approach for the evaluation of the existing three-parameter corresponding states principles (CSP) and calculation of the corresponding states parameter is presented. This technique is based on the assumption that contribution of the third parameter to the thermophysical properties is much smaller than the contributions of the first two parameters. The first two parameters are, generally, the molecular energy and length parameters, /k and (or critical temperature and volume, T _c and V _c ). Based on the present multiproperty technique, several existing three-parameter CSPs are evaluated. It is demonstrated that the three-parameter CSP, which is based on the two- and three-body intermolecular potential parameters, effectively satisfies the requirements of this technique. The corresponding states parameters of several compounds, including normal alkane hydrocarbons (CH₄ to C₂₀H₄₂), for which proper thermophysical data are available, are calculated through the present technique, and they are reported here.     

Unsupervised feature selection in linked biological data

Pattern Analysis and Applications - Feature selection techniques have become an apparent need in many bioinformatics applications, especially when there exist a huge number of features. For...     

Modified glassy carbon electrode with multiwall carbon nanotubes as a voltammetric sensor for determination of noscapine in biological and pharmaceutical samples

A simple and highly sensitive method is described for direct voltammetric determination of noscapine in blood and pharmaceutical sample. Glassy carbon electrode with effective method is modified with multiwall carbon nanotubes (MWNTs) to cause activation of multiwall carbon nanotubes structures for electrocatalyzes of noscapine oxidation. The cyclic voltammetric (CV) results indicated that MWNTs remarkably enhances electrocatalytic activity toward the oxidation of noscapine, which is leading to considerable improvement of anodic peak current for noscapine, and allows the development of a highly sensitive voltammetric sensor for detection of noscapine in pharmaceutical and clinical samples. Under the optimum condition, the calibration curve was linear in the concentration range 4.0 × 10⁻⁷–1.0 × 10⁻⁴ mol L⁻¹ with the detection limit of 8.0 × 10⁻⁸ mol L⁻¹ and relative standard deviation (R.S.D.%) lower than 1.0% (n = 5). Finally, some kinetic parameters were determined and multistep mechanism for oxidation of noscapine for first time was proposed.