Structure and properties of melt‐spun PET/MWCNT nanocomposite fibers

Polyethylene terephthalate (PET) melt‐spun fibers were modified with multiwall carbon nanotubes (MWCNT) to obtain conductive microfibers smaller than 90 μm in diameter. Physical properties such as crystallinity and orientation of as‐spun fibers were studied by X‐ray diffraction, Raman spectroscopy, and microscopy techniques at different draw ratios (DR) and MWCNT concentrations. Morphological and orientation analysis of MWCNT after melt‐spinning process showed agglomerates formation and highly oriented CNTs. The study of the orientation of PET crystalline phase in drawn fibers proved that the addition of nanoparticles decreases the orientation of crystalline units inside the fibers. The orientation of MWCNT as well as that of PET chains was studied using Raman spectroscopy at different DR and a high degree of CNT orientation was observed under high DR conditions. Mechanical and electrical properties of as‐spun fibers were also investigated. Our results showed that it was possible to achieve conductive fibers at a MWCNT concentration of 2% w/w, and more conductive fibers using higher DR were also obtained without increasing the MWCNT concentration. Mechanical properties results showed interestingly high value of maximum tensile strain at break (ε_max) of nanocomposite fibers, up to three times more than pure PET fibers. POLYM. ENG. SCI., 50:1956–1968, 2010. © 2010 Society of Plastics Engineers     

A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition

This paper addresses the QoS-aware cloud service composition problem, which is known as a NP-hard problem, and proposes a hybrid genetic algorithm (HGA) to solve it. The proposed algorithm combines two phases to perform the evolutionary process search, including genetic algorithm phase and fruit fly optimization phase. In genetic algorithm phase, a novel roulette wheel selection operator is proposed to enhance the efficiency and the exploration search. To reduce the computation time and to maintain a balance between the exploration and exploitation abilities of the proposed HGA, the fruit fly optimization phase is incorporated as a local search strategy. In order to speed-up the convergence of the proposed algorithm, the initial population of HGA is created on the basis of a heuristic local selection method, and the elitism strategy is applied in each generation to prevent the loss of the best solutions during the evolutionary process. The parameter settings of our HGA were tuned and calibrated using the taguchi method of design of experiment, and we suggested the optimal values of these parameters. The experimental results show that the proposed algorithm outperforms the simple genetic algorithm, simple fruit fly optimization algorithm, and another recently proposed algorithm (DGABC) in terms of optimality, computation time, convergence speed and feasibility rate.     

Polyaniline coated hematite sand supported on graphene oxide (HS@PANI-GO) as a new magnetic material for advanced catalytic oxidation based on sulfate radicals: optimization using response surface methodology

The cover image is based on the Research Article Polyaniline coated hematite sand supported on graphene oxide (HS@PANI-GO) as a new magnetic material for advanced catalytic oxidation based on sulfate radicals: optimization using response surface methodology by Abdellah Ait El Fakir et al., DOI: 10.1002/jctb.6070 .

     

A multiscale based approach for automatic shadow detection and removal in natural images

Multimedia Tools and Applications - Shadow is a natural phenomenon observed in most natural images. It can reveal information about the objects shape as well as the illumination direction. In...     

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.     

Effect of Back-layer on seal performance of multilayer polyethylene-based sealant films

This work studies effects of back-layer materials, thickness of sealant layer, and sealing condition on seal performance of multilayer polyethylene-based films. Multilayer films with back-layers of high-density polyethylene (HDPE), or low-density polyethylene (LDPE), or linear low-density polyethylene (LLDPE) were produced with different thicknesses of the metallocene layer. It was found that increasing the thickness of the metallocene layer improved hot tack properties. In addition, films with back-layers of LLDPE or LDPE showed higher hot tack strength compared to those with HDPE back-layer. Increasing sealing temperature reduced significantly the hot tack strength and its dependency on metallocene layer thickness. It was found that increasing delay time after sealing, before peeling test, increased hot tack strength, but the rate of hot tack evolution and the type of peeling behavior were considerably affected by the type of back-layer material. The effect of dwell time was also examined, and it was observed that increasing dwell time in the studied range did not affect the hot tack evolution. The mechanisms involved in the development of hot tack evolution were discussed, and it was shown that the back-layer effects can be explained by bulk viscoelastic energy dissipation theory.     

Enzymatic extract from flowers of Algerian spontaneous Cynara cardunculus: Milk‐clotting properties and use in the manufacture of a Camembert‐type cheese

The aim of this study was to assess the coagulant properties of crude extract from cardoon flowers (CECF) as a replacement for the imported coagulants used in the local Algerian cheese factories. Optimal coagulation activity of the extract was observed at pH 5 and 60 °C with a CaCl₂ concentration of 0.02 M. The electrophoretic pattern revealed that the crude extract contains mainly cardosins A and B. The study of interactions involved in the formation of milk gel coagulated by CECF showed that hydrogen forces, hydrophobic interactions and calcium bridges contributed highly to the formation of milk gel. Camembert‐type cheese obtained by CECF was judged by trained panellists and was found to be in agreement with standard specifications. The present study highlights the possibility of using Algerian CECF as a promising plant coagulant in cheesemaking for the dairy industry.     

Exploitation of vehicle's kinetic energy in power management of tow -wheel drive electric vehicles based on ANFIS DTC-SVM comparative study

The concept of the hybrid power system in electric vehicles means that there are many sources in this electric vehicle. The electric vehicle of two-wheel drives motors doesn't exploit the two front wheel; this kind of electric vehicle prompted us to propose using the front wheels in electric vehicle energy management, which creates another energy source. The hybrid vehicle can associate more than one source to each other to secure a long time working. The two rear wheels are generally controlled by classical controllers as the DTC-SVM controller that is one of many methods to control a motor's speed. It Based on three classical controllers. We want to replace the PI speed controller with an intelligent controller and show the possibility of integrating it in this kind of control. In this paper, we exploit the electric vehicle's Kinetic energy in energy management by combining the permanent magnet synchronous generator in the vehicle's front wheels, and integrating the ANFIS controller with back motors. The generator's power represents about 19% of the total electric vehicle power. The ANFIS management strategy gave the best résults 96.6 as efficiency and the smallest consumption of Air/fuel compared with the others methods about 55.75–199 (Ipm).