Electronic properties of magnetically doped nanotubes

Effect of doping of carbon nanotubes by magnetic transition metal atoms has been considered in this paper. In the case of semiconducting tubes, it was found that the system has zero magnetization, whereas in metallic tubes the valence electrons of the tube screen the magnetization of the dopants: the coupling to the tube is usually antiferromagnetic (except for Cr).     

A novel design of 8-bit adder/subtractor by quantum-dot cellular automata

Application of quantum-dot is a promising technology for implementing digital systems at nano-scale. QCA supports the new devices with nanotechnology architecture. This technique works based on electron interactions inside quantum-dots leading to emergence of quantum features and decreasing the problem of future integrated circuits in terms of size. In this paper, we will successfully design, implement and simulate a new full adder based on QCA with the minimum delay, area and complexities. Also, new XOR gates will be presented which are used in 8-bit controllable inverter in QCA. Furthermore, a new 8-bit full adder is designed based on the majority gate in the QCA, with the minimum number of cells and area which combines both designs to implement an 8-bit adder/subtractor in the QCA. This 8-bit adder/subtractor circuit has the minimum delay and complexity. Being potentially pipeline, the QCA technology calculates the maximum operating speed.     

Parallel Lagrange interpolation on <Emphasis Type="Italic">k</Emphasis>-ary <Emphasis Type="Italic">n</Emphasis>-cubes with maximum channel utilization

This paper proposes an efficient parallel algorithm for computing Lagrange interpolation on k-ary n-cube networks. This is done using the fact that a k-ary n-cube can be decomposed into n link-disjoint Hamiltonian cycles. Using these n link-disjoint cycles, we interpolate Lagrange polynomial using full bandwidth of the employed network. Communication in the main phase of the algorithm is based on an all-to-all broadcast algorithm on the n link-disjoint Hamiltonian cycles exploiting all network channels, and thus, resulting in high-efficiency in using network resources. A performance evaluation of the proposed algorithm reveals an optimum speedup for a typical range of system parameters used in current state-of-the-art implementations.

An ant colony optimization algorithm for the bi-objective shortest path problem

Multi-objective shortest path problem (MOSP) is an extension of a traditional single objective shortest path problem that seeks for the efficient paths satisfying several conflicting objectives between two nodes of a network. MOSP is one of the most important problems in network optimization with wide applications in telecommunication industries, transportation and project management. This research presents an algorithm based on multi-objective ant colony optimization (ACO) to solve the bi-objective shortest path problem. To analyze the efficiency of the algorithm and check for the quality of solutions, experimental analyses are conducted. Two sets of small and large sized problems that generated randomly are solved. Results on the set problems are compared with those of label correcting solutions that is the most known efficient algorithm for solving MOSP. To compare the Pareto optimal frontiers produced by the suggested ACO algorithm and the label correcting algorithm, some performance measures are employed that consider and compare the distance, uniformity distribution and extension of the Pareto frontiers. The results on the set of instance problems show that the suggested algorithm produces good quality non-dominated solutions and time saving in computation of large-scale bi-objective shortest path problems.     

Revisiting the free transverse vibration of embedded single-layer graphene sheets acted upon by an in-plane magnetic field

Murmu et al. [23] recently presented a nonlocal model for the transverse vibration of simply supported graphene sheets in the presence of a unidirectional in-plane magnetic field. Further studies showed that the majority of Lorentz’s force components were improperly provided and led to invalid governing equations. To remove such deficiencies, the most general form of Lorentz’s force components is carefully extracted in the present work. The nonlocal equations of motion of the problem are reconstructed and solved again. The influences of crucial parameters on the flexural frequencies of magnetically affected graphene sheets and nanoribbons are examined in detail. Furthermore, the crucial discrepancies between the results obtained in this study and those of the abovementioned previous work are rationally discussed. Some erroneous results of the latter are also rectified.     

Synergistic effect of nanoparticles and Thalassospira sp. isolated from Bahregan area in biodegradation of oil sludge

Oil sludge is obtained from the contaminated site of Bahregan area in the Persian Gulf in Iran. Chemotaxis was used for the isolation of alkane-degrading bacteria from oil sludge and the alk genes were determined with specific primers. bac1 identified in Thalassospira was selected as a powerful strain for biodegradation of oil sludge. Biodegradation of oil sludge by bac1 in the presence of nanoparticles was investigated by GC-MS analysis. Synergistic effect of Fe₂O₃ and Fe₃O₄ nanoparticles on bacteria increases the biodegradation of oil sludge and produces cyclosiloxane compound which is used in the field of medicine; however, the Thalassospira reduced its toxicity in the environment.     

An efficient extraction and clean‐up procedure for pesticide determination in olive oil

This work reports a simple, rapid, and effective extraction method based on liquid–liquid extraction (LLE) followed by matrix solid‐phase dispersion‐sonication for detection, identification and quantification of multiclass pesticides in virgin olive oil using liquid chromatography mass spectrometry (LC‐QTOF‐MS). LLE to extract pesticide residues in virgin olive oil was performed in order to study the centrifugation efficiency to obtain high recovery yield and low co‐extract fat residue in the final extract. Different suitable parameters of MSPD procedure were evaluated, such as nature of dispersing phase, clean‐up adsorbent, and volume of eluting solvent (acetonitrile) in different extraction conditions, with or without sonication. The best results were obtained using 5 g of virgin olive oil, 2 g of PSA as dispersant sorbent, 2 g of Florisil/GCB (70:30 w/w) as clean‐up sorbent, and 15 mL of acetonitrile as eluting solvent under conditions of 15 min ultrasonic bath at RT. Method validation was performed in order to study sensitivity, linearity, precision, and accuracy. Average recoveries ranged between 73.7 and 104.2% with relative SDs 5.3–13.4% at three concentration levels (25, 50, and 100 µg/kg). Detection and quantification limits ranged from 1.5 to 5 µg/kg and 3 to 9 µg/kg, respectively.     

A semantic social network-based expert recommender system

This research work presents a framework to build a hybrid expert recommendation system that integrates the characteristics of content-based recommendation algorithms into a social network-based collaborative filtering system. The proposed method aims at improving the accuracy of recommendation prediction by considering the social aspect of experts’ behaviors. For this purpose, content-based profiles of experts are first constructed by crawling online resources. A semantic kernel is built by using the background knowledge derived from Wikipedia repository. The semantic kernel is employed to enrich the experts’ profiles. Experts’ social communities are detected by applying the social network analysis and using factors such as experience, background, knowledge level, and personal preferences. By this way, hidden social relationships can be discovered among individuals. Identifying communities is used for determining a particular member’s value according to the general pattern behavior of the community that the individual belongs to. Representative members of a community are then identified using the eigenvector centrality measure. Finally, a recommendation is made to relate an information item, for which a user is seeking an expert, to the representatives of the most relevant community. Such a semantic social network-based expert recommendation system can provide benefits to both experts and users if one looks at the recommendation from two perspectives. From the user’s perspective, she/he is provided with a group of experts who can help the user with her/his information needs. From the expert’s perspective she/he has been assigned to work on relevant information items that fall under her/his expertise and interests.     

A new quantum-dot cellular automata full-adder

A novel expandable five-input majority gate for quantum-dot cellular automata and a new full-adder cell are presented. Quantum-dot cellular automata (QCA) is an emerging technology and a possible alternative for semiconductor transistor based technologies. A novel QCA majority-logic gate is proposed. This component is suitable for designing QCA circuits. The gate is simple in structure and powerful in terms of implementing digital functions. By applying these kinds of gates, the hardware requirement for a QCA design can be reduced and circuits can be simpler in level, gate counts and clock phases. In order to verify the functionality of the proposed device, some physical proofs are provided. The proper functionality of the FA is checked by means of computer simulations using QCADesigner tool. Both simulation results and physical relations confirm our claims and its usefulness in designing every digital circuit.