Sharif Digital Repository

An efficient, green, novel and rapid vortex-assisted dispersive solid-phase extraction (VADSPE) technique was used for the preconcentration and determination of trace levels of Cu2+ followed by flame atomic absorption spectrometry. Graphene oxide (GO) was synthesized from graphite and then modified by pectic acid (poly-d-galacturonic acid, PA) to synthesize the pectic acid–graphene oxide (PA-GO) nanocomposite. The Fourier transform infrared spectrophotometry, field emission scanning electron microcopy, energy-dispersive X-ray spectroscopy and X-ray diffraction analysis were used to characterize the synthesized GO-PA nanocomposite. By using VADSPE technique, PA-GO was used as an adsorbent for... 

The present contribution is devoted to develop multivariate analytical figures of merit (AFOMs) as a new metric for evaluation of quantitative measurements using comprehensive two-dimensional gas chromatography–mass spectrometry (GC × GC–MS). In this regard, new definition of sensitivity (SEN) is extended to GC × GC–MS data and then, other multivariate AFOMs including analytical SEN (γ), selectivity (SEL) and limit of detection (LOD) are calculated. Also, two frequently used second- and third-order calibration algorithms of multivariate curve resolution-alternating least squares (MCR-ALS) as representative of multi-set methods and parallel factor analysis (PARAFAC) as representative of... 

The local buckling behavior of perfect/defective and single/multi-walled carbon nanotubes (CNTs) under axial compressive forces has been investigated by the molecular dynamics approach. Effects of different types of defects including vacancy and Stone-Wales (SW) defects and their configurations on CNTs with different chiralities at room temperature are studied. Results show that defects largely reduce the buckling stress and the ratio of immediate reduction in buckling compressive stress of the defective CNT to the perfect one, but have little influence on their compressive elastic modulus. SW defects usually reduce the mechanical properties more than vacancy defects, and zigzag CNTs are... 

Two novel heterogeneous hybrid catalysts were successfully synthesized using octa-aminopropyl polyhedral oligomeric silsesquioxane hydrochloride salt (OA-POSS) and ionic liquids, followed by immobilization of Cu and Ag nanoparticles. The obtained hybrid catalysts, Cu@POSS-ILs and Ag@POSS-ILs, were characterized using FT-IR, SEM, EDX, TEM, XRD and TGA. Catalytic studies demonstrated that Cu@POSS-ILs was an excellent catalyst for click reaction in aqueous medium. Furthermore, Ag@POSS-ILs was also exhibited to be an active catalyst for 4-nitrophenol (4-NP) reduction. Simple preparation and easy catalysts recovery and recyclability of Cu@POSS-ILs and Ag@POSS-ILs for at least 3 and 6 runs,... 

In this work, for the first time, we presented a novel design strategy to fabricate a new type of Octa-aminopropyl polyhedral oligomeric silsesquioxane hydrochloride salt (OA-POSS)-based Alg/PAAm DN gels, consisting of PAAm gel as the first chemical network and Alg/OA-POSS gel as the second chemical-physical network. Incorporation of OA-POSS nanoparticles with various feed ratio into the second network not only led to form strong coordination interactions but also in comparison to the other Alg/PAAm gels demonstrated superior mechanical properties. pH, temperature, contact time and salt effects parameters were studied on the swelling and dye removal properties of the synthesized DN hybrid... 

Aluminum matrix in situ nanocomposite was produced by one to six passes friction stir processing (FSP) with pre-placed Fe3O4 nanoparticles (15-20 nm). Microstructure studies showed that solid-state reactions between the aluminum matrix and Fe3O4 particles during the process led to in situ formation of Al3Fe and Al5Fe2 in the stir zone. Initial Fe3O4 as well as Al-Fe intermetallic compounds (IMCs) particles were homogeneously dispersed in a fine grain matrix after six passes of FSP. Hardness and ultimate tensile strength of the composites were increased 64 and 27%, respectively, compared to the base metal. The reasons were studied in the light of reinforcing particles distribution, formation... 

As an alternative to adaptive nonlinear schemes for dimensionality reduction, linear random projection has recently proved to be a reliable means for high-dimensional data processing. Widespread application of conventional random projection in the context of image analysis is, however, mainly impeded by excessive computational and memory requirements. In this paper, a two-dimensional random projection scheme is considered as a remedy to this problem, and the associated key notion of concentration of measure is closely studied. It is then applied in the contexts of image classification and sparse image reconstruction. Finally, theoretical results are validated within a comprehensive set of... 

The most important event following the establishmenet of the Internet network was the Web introduced by Tim Berners-Lee. Websites give their owners features that allow sharing with which they can publish their content with users and visitors. In the last 5 years, we have seen some changes in the use of web. Users want to participate in content sharing and they like to interact with each other. This is known as Web 2.0. In the last year, Web 2.0 has reached maturity and now we need a smart web which will be accordingly be called Web 3.0. Web 3.0 is based on semantic web definition. Changing the way of using the web has had a clear impact on E-Tourism and its development and also on business... 

The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the information in the signal, with high probability. Following the success in signal reconstruction, compressive framework has recently proved useful in classification, particularly hypothesis testing. In this paper, conventional random projection scheme is first extended to the image domain and the key notion of concentration of measure is closely studied. Findings are then employed to develop a 2D compressive classifier (2D-CC) for sparse images. Finally, theoretical results are validated within a realistic... 

Spectral manifold learning techniques have recently found extensive applications in machine vision. The common strategy of spectral algorithms for manifold learning is exploiting the local relationships in a symmetric adjacency graph, which is typically constructed using k-nearest neighborhood (k-NN) criterion. In this paper, with our focus on locally linear embedding as a powerful and well-known spectral technique, shortcomings of k-NN for construction of the adjacency graph are first illustrated, and then a new criterion, namely k/K-nearest neighborhood (k/K-NN) is introduced to overcome these drawbacks. The proposed criterion involves finding the sparsest representation of each sample in...