Synthesis and characterization of processable multi-walled carbon nanotubes-sulfonated polydiphenylamine graft copolymers

Water soluble and processable nanocomposites composed of multi-walled carbon nanotubes (MWNTs) and poly(diphenylamine sulfonic acid) (PDPASA) are synthesized and characterized. Two types of methodologies are adopted. MWNTs are covalently functionalized with 2,5-diaminobenzene sulfonic acid (DABSA) and further in situ polymerized with diphenylamine-4-sulfonic acid (DPASA). This results in the formation of nanocomposites, MWNT(DABSA)-g-PDPASA, in which PDPASA is presented as the graft chains onto MWNTs. In another approach, DPASA is in situ polymerized in presence of unfunctionalized MWNTs, results in a nanocomposite in which MWNTs are present as entrapped mass in PDPASA matrix. Both nanocomposites are found to be water soluble and can form free standing films. The conductivity of MWNT(DABSA)-g-PDPASA and MWNT/PDPASA is found to be 1.25 mS x cm(-1) and 0.65 mS x cm(-1), respectively, which is higher than that of pristine PDPASA (0.25 x 10(-5) S x cm(-1)). The nanocomposites are characterized for their structure, morphology, optical and thermal properties.     

Application of heat transfer on MHD shear thickening fluid flow past a stretched surface with variable heat source/sink

The purpose of this study is to explore the viscous dissipation stimulus on the steady convective magnetohydrodynamic shear thickening liquid stream across a vertically stretched sheet. The impact of thermic heat, first-order velocity slip, and variable heat generation/absorption are considered and also ignored the effect of magnetic Reynold's number. We converted flow controlling equations into the set of dimensionless nonlinear ordinary differential equations by employing similarity variables to solve these coupled equations by R–K and shooting technique. The effect of different dimensionless variables on velocity, heat, friction factor, and local Nusselt numbers are presented through graphs and tables. Depreciation in velocity and growth in temperature distribution is detected when the Casson fluid parameter is increased. Temperature is the increasing function of the Eckert number.     

The effect of humic acids on the cytotoxicity of silver nanoparticles to a natural aquatic bacterial assemblage

The effect of a terrestrial humic acid (HA) and a river HA on the cytotoxicity of silver nanoparticles (AgNPs) to natural aquatic bacterial assemblages (0 μM, 2.5 μM and 5 μM) was measured with spread plate counting. The effect of HA (20 and 40 ppm) on the cytotoxicity of AgNPs ranging in size between 15 and 25 nm was tested in the presence and in the absence of natural sunlight. The experiment was a full factorial, completely randomized design and the results were analyzed using the General Linear Model in SAS. LSMEANS was used to separate the means or combinations of means. Significant main effects of all independent variables, plus interaction effects in all cases except HA/LI and HA/AgNPs/LI were observed. The toxicity of AgNPs to natural aquatic bacterial assemblages appears to be concentration dependent for concentrations between 0 μM and 5 μM. The data indicate that the light exposure inhibited viability more than the darkness exposure. The HA treatment groups in the presence of light showed greater reduced viability count compared to darkness exposure groups. The inhibition of bacterial viability counts by AgNPs exposure was less in the light treatment groups containing a terrestrial HA compared to that with a river HA. Difference in the extent of reactive oxygen species formation and adsorption/binding of AgNPs was speculated to account for the observed phenomenon.     

GAMS: A stylistic approach to economic modelling

GAMS (General Algebraic Modelling System) is a software package which will make numerical optimization a much simpler endeavor for specialists from a wide range of disciplines. The need for writing personal fortran codes for optimizers and unfriendly fixed-formatfortran type input files is no longer necessary. This review gives an overall view of GAMS' capabilities and uses in the field of numerical optimization.     

Approximate Signal Processing

It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing these tradeoffs. One of the objectives of this paper is to suggest that there is the potential for developing a more formal approach, including utilizing current research in Computer Science on Approximate Processing and one of its central concepts, Incremental Refinement. Toward this end, we first summarize a number of ideas and approaches to approximate processing as currently being formulated in the computer science community. We then present four examples of signal processing algorithms/systems that are structured with these goals in mind. These examples may be viewed as partial inroads toward the ultimate objective of developing, within the context of signal processing design and implementation, a more general and rigorous framework for utilizing and expanding upon approximate processing concepts and methodologies.     

Compound parabolic concentrator probe for efficient light collection in spectroscopy of biological tissue

We describe a compound parabolic concentrator (CPC)-based probe for enhanced signal collection in the spectroscopy of biological tissues. Theoretical considerations governing signal enhancement compared with conventional collection methods are given. A ray-tracing program was used to analyze the throughput of CPC's with shape deviations and surface imperfections. A modified CPC shape with 99% throughput was discovered. A 4.4-mm-long CPC was manufactured and incorporated into an optical fiber-based near-infrared Raman spectrometer system. For human tissue samples, light collection was enhanced by a factor of 7 compared with collection with 0.29-NA optical fibers.     

OntoSTEP: Enriching product model data using ontologies

The representation and management of product lifecycle information is critical to any manufacturing organization. Different modeling languages are used at different lifecycle stages, for example STEP’s EXPRESS may be used at a detailed design stage, while UML may be used for initial design stages. It is necessary to consolidate product information created using these different languages to build a coherent knowledge base. In this paper, we present an approach to enable the translation of STEP schema and its instances to Ontology Web Language (OWL). This gives a model–which we call OntoSTEP–that can easily be integrated with any OWL ontologies to create a semantically rich model. As an example, we combine geometry information represented in STEP with non-geometry information, such as function and behavior, represented using the NIST’s Core Product Model (CPM). A plug-in for Protégé is developed to automate the different steps of the translation. As additional benefits, reasoning, inference procedures, and queries can be performed on enriched legacy CAD models. We describe the rules for the translation from EXPRESS to OWL, and illustrate the benefits of OWL translation with an example. We will also describe how these mapping rules can be implemented through meta-model based transformations, which can be used to map other languages to OWL.     

MapReduce paradigm: DNA sequence clustering based on repeats as features

Clustering is one of the major operations to analyse genome sequence data. Sophisticated sequencing technologies generate huge DNA sequence data; consequently, the complexity of analysing sequences is also increased. So, there is an enormous need for faster sequence analysis algorithms. Most of the existing tools focused on alignment-based approaches, which are slow-paced for sequence comparison. Alignment-free approaches are more successful for fast clustering. The state-of-the-art methods have been applied to cluster small genome sequences of various species; however, they are sensitive to large size sequences. To subdue this limitation, we propose a novel alignment-free method called DNA sequence clustering with map-reduce (DCMR). Initially, MapReduce paradigm is used to speed up the process of extracting eight different types of repeats. Then, the frequency of each type of repeat in a sequence is considered as a feature for clustering. Finally, K-means (DCMR-Kmeans) and K-median (DCMR-Kmedian) algorithms are used to cluster large DNA sequences by using extracted features. The two variants of proposed method are evaluated to cluster large genome sequences of 21 different species and the results show that sequences are very well clustered. Our method is tested for different benchmark data sets like viral genome, influenza A virus, mtDNA, and COXI data sets. Proposed method is compared with MeshClust, UCLUST, STARS, and ClustalW. DCMR-Kmeans outperforms MeshClust, UCLUST, and DCMR-Kmedian with respect to purity and NMI on virus data sets. The computational time of DCMR-Kmeans is less than STARS, DCMR-Kmedian, and much less than UCLUST on COXI data set.     

Energy‐aware dynamic task offloading and collective task execution in mobile cloud computing

There is a good opportunity for enlightening the services of the mobile devices by introducing computational offloading using cloud technology. Offloading is a process for managing the complexity of the mobile environment by migrating computational load to the cloud. The mobile devices oblige the quick response for the offloading requests; it is dependent on network connectivity. The cloud services take long set‐up time irrespective of network connectivity. In this paper, new system architecture for the dynamic task offloading in the mobile cloud environment is proposed. The architecture includes the offloading algorithm that concentrates on energy consumption of the tasks both in the local and remote environment. The proposed algorithm formulates a collective task execution model for minimizing the energy consumption. The architecture concentrates on the network model by considering the task completion time in three different network scenarios. The experimental results show the efficiency of the suggested architecture in reducing the energy consumption and completion time of the tasks.     

Influence of structural defects on gas adsorption properties of anthophyllite asbestos

The surface area of anthophyllite asbestos variants with different stages of fiber development is found to be not proportional to the fineness of the fibrils. Coarser variants have transitional pores whereas the asbestiform is microporous. HRTEM images show structural intergrowths of Mg(OH)₂ in an anthophyllite lattice, whereas the intergrowths are absent in the asbestiform anthophyllite. Conversion of brucite intergrowth into a noncrystalline phase results in the generation of transitional pores.