Photoluminescence and UV photosensitivity of few-layered MoS2 nanosheets synthesized under different hydrothermal growth times

Journal of Materials Science - MoS2 flower-like microspheres composed of 2D nanosheets were prepared using the simple and cost-effective method of hydrothermal. The effects of hydrothermal process...     

An efficient synthesis of novel sulfonyl[3.3.3]heteropropellanes from sulfonylacetamidines and ninhydrin-malononitrile adduct

The synthesis in good yields of a novel class of sulfonyl[3.3.3]heteropropellanes via a one pot, five-component reaction between sodium arylsulfinates, trichloroacetonitrile, primary amines, and the malononitrile-ninhydrin adduct in H₂O at room temperature has been reported.     

A dynamic data dissemination mechanism for Cassandra NoSQL data store

The Journal of Supercomputing - Cassandra as a type of NoSQL databases has been put forward so as to surmount the hurdles of traditional relational databases in the scope of big data as well as...     

Effects of drying methods on qualitative and quantitative properties of essential oil of two basil landraces

Sweet basil, a plant that is extensively cultivated in some countries, is used to enhance the flavour of salads, sauces, pasta and confectioneries as both a fresh and dried herb. To determine the effect of drying methods on qualitative and quantitative characteristics of the plant and essential oil of basil, two landraces, Purple and Green, were dried in sunlight, shade, mechanical ovens at 40 °C and 60 °C, a microwave oven at 500 W and by freeze-drying. For comparison, the essential oils of all samples were extracted by hydrodistillation and analyzed using GC and GC–MS. The highest essential oil yields (v/w on dry weight basis) were obtained from shade-dried tissue in both landraces followed by the freeze-dried sample of the purple landrace and the fresh sample of green landrace. Increasing the drying temperature significantly decreased the essential oil content of all samples. Significant changes in the chemical profile of the essential oils from each of the landrace were associated with the drying method, including the loss of most monoterpene hydrocarbons, as compared with fresh samples. No significant differences occurred among several constituents in the extracted essential oils, including methyl chavicol (estragole), the major compound in the oil of both landraces, whether the plants were dried in the shade or sun, oven at 40 °C or freeze-dried, as compared with a fresh sample. The percentage methyl chavicol in the oil, however, decreased significantly when the plant material was dried in the oven at 60 °C or microwaved. In addition, linalool, the second major compound in the purple landrace, and geranial and neral, major compounds in the green landrace, decreased significantly when the plant tissue was dried in the oven at 60 °C or microwaved.     

CogNS: A Simulation Framework for Cognitive Radio Networks

Cognitive radio technology has been used to efficiently utilize the spectrum in wireless networks. Although many research studies have been done recently in the area of cognitive radio networks (CRNs), little effort has been made to propose a simulation framework for CRNs. In this paper, a simulation framework based on NS2 (CogNS) for cognitive radio networks is proposed. This framework can be used to investigate and evaluate the impact of lower layers, i.e., MAC and physical layer, on the transport and network layers protocols. Due to the importance of packet drop probability, end-to-end delay and throughput as QoS requirements in real-time reliable applications, these metrics are evaluated over CRNs through CogNS framework. Our simulations demonstrate that the design of new network and transport layer protocols over CRNs should be considered based on CR-related parameters such as activity model of primary users, sensing time and frequency.     

Superparamagnetic magnetite nanoparticles for cancer cells treatment via magnetic hyperthermia: effect of natural capping agent,particle size and concentration

Journal of Materials Science: Materials in Electronics - Superparamagnetic iron oxide nanoparticles (SPMNPs) continue to emerge as one of the most potential candidates in biomedical applications....     

An efficient hybrid algorithm based on modified imperialist competitive algorithm and K-means for data clustering

Clustering techniques have received attention in many fields of study such as engineering, medicine, biology and data mining. The aim of clustering is to collect data points. The K-means algorithm is one of the most common techniques used for clustering. However, the results of K-means depend on the initial state and converge to local optima. In order to overcome local optima obstacles, a lot of studies have been done in clustering. This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Modify Imperialist Competitive Algorithm (MICA) and K-means (K), which is called K-MICA, for optimum clustering N objects into K clusters. The new Hybrid K-ICA algorithm is tested on several data sets and its performance is compared with those of MICA, ACO, PSO, Simulated Annealing (SA), Genetic Algorithm (GA), Tabu Search (TS), Honey Bee Mating Optimization (HBMO) and K-means. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handling data clustering.