Characterization of the structure and properties of processed alumina-graphene and alumina-zirconia composites

The onset of hybrid alumina-based composites, which combines two or more nano-particles within the alumina matrix has already shown promising improvements in the matrix material. However, variations in mechanical properties including the optimum compositions that give improved properties faced with the development of alumina-based composites require further studies to understand the underlying mechanisms and synergistic effects of the nano-particle additions on the alumina matrix. In the current study, the structure and properties of Al?O?-graphene (0.5 wt%) and Al?O?–ZrO? (4 wt% and 10 wt%) composites fabricated via hot-pressing was studied as a baseline for multiple combinations. Even though the addition of 10 wt%ZrO? resulted in a 23% reduction in the grain size of the alumina matrix, the 4 wt%ZrO? addition resulted in a 14% increase in grain size as compared to the parent alumina matrix. X-ray diffraction analysis revealed that there was approximately 85% monoclinic (m-ZrO₂) vs. 15% tetragonal (t-ZrO₂) crystal structures in the A4ZrO? sample whilst the A₁₀ZrO? had approximately 93% m-ZrO₂ vs. 7% t-ZrO₂. The high-volume fraction of the monoclinic crystal structures in the A₁₀ZrO? accounts for the induced microcracks in the sample since the transition from the ductile-tetragonal to brittle-monoclinic is associated with the exertion of compressive stresses on the alumina matrix by the associated elastic volume expansion of m-ZrO₂. Also, the addition of 0.5 wt%graphene resulted in about 37% reduction in the grain size of the alumina matrix, and approximately 10% increase in hardness as a result of the distribution of graphene along the grain boundaries of the parent alumina matrix, which restricts grain coalescence and growth during processing. Furthermore, an increase up to 115% and 164% were observed in the fracture toughness (K_IC) with the inclusion of 0.5 wt%graphene and 10 wt%ZrO? respectively, which was primarily ascribed to the fine-grained microstructures and toughening mechanisms of the intergranular graphene and ZrO? particles.     

Gastroparesis after celiac plexus block

Pectin constituents, which were about 70 w/w% of extracellular polysaccharides (ECP) from a cell-suspension culture of Mentha, were purified by gel filtration chromatography, and their sugar composition and linkage were investigated. Two major constituents identified were (1-->3)-linked galactan carrying arabinosyl residues on C-6 and (1-->4)-alpha-linked galacturonan partially interspersed with (1-->2)-linked rhamnosyl resides. Acetylated or methylated pectins were not identified on 1H-NMR analysis.     

Decentralized Dynamic Event-Triggered Communication and Active Suspension Control of In-Wheel Motor Driven Electric Vehicles with Dynamic Damping

This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second,a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.     

Green synthesised zinc oxide nanostructures through Periploca aphylla extract shows tremendous antibacterial potential against multidrug resistant pathogens

To grapple with multidrug resistant bacterial infections, implementations of antibacterial nanomedicines have gained prime attention of the researchers across the globe. Nowadays, zinc oxide (ZnO) at nano‐scale has emerged as a promising antibacterial therapeutic agent. Keeping this in view, ZnO nanostructures (ZnO‐NS) have been synthesised through reduction by P. aphylla aqueous extract without the utilisation of any acid or base. Structural examinations via scanning electron microscopy (SEM) and X‐ray diffraction have revealed pure phase morphology with highly homogenised average particle size of 18 nm. SEM findings were further supplemented by transmission electron microscopy examinations. The characteristic Zn–O peak has been observed around 363 nm using ultra‐violet–visible spectroscopy. Fourier‐transform infrared spectroscopy examination has also confirmed the formation of ZnO‐NS through detection of Zn–O bond vibration frequencies. To check the superior antibacterial activity of ZnO‐NS, the authors'' team has performed disc diffusion assay and colony forming unit testing against multidrug resistant E. coli, S. marcescens and E. cloacae. Furthermore, protein kinase inhibition assay and cytotoxicity examinations have revealed that green fabricated ZnO‐NS are non‐hazardous, economical, environmental friendly and possess tremendous potential to treat lethal infections caused by multidrug resistant pathogens.Inspec keywords: nanomedicine, zinc compounds, II‐VI semiconductors, wide band gap semiconductors, nanoparticles, scanning electron microscopy, X‐ray diffraction, antibacterial activity, transmission electron microscopy, particle size, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, enzymes, biochemistry, molecular biophysics, microorganisms, drugs, toxicology, bonds (chemical), semiconductor growth, nanofabrication, vibrational modesOther keywords: green synthesised zinc oxide nanostructures, Periploca aphylla extract, antibacterial potential, multidrug resistant pathogens, multidrug resistant bacterial infections, antibacterial nanomedicines, P. aphylla aqueous extract, structural examinations, scanning electron microscopy, X‐ray diffraction, pure phase morphology, homogenised average particle size, SEM, transmission electron microscopy, Fourier‐transform infrared spectroscopy, bond vibration frequency, antibacterial activity, disc diffusion assay, colony forming unit testing, S. marcescens, E. cloacae, E. coli, ultraviolet‐visible spectroscopy, protein kinase inhibition assay, cytotoxicity, lethal infections, ZnO     

A Service Level Agreement Aware Online Algorithm for Virtual Machine Migration

The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be designed. One specific area where energy efficient algorithms are required is virtual machine consolidation. With virtual machine consolidation, the objective is to utilize the minimum possible number of hosts to accommodate the required virtual machines, keeping in mind the service level agreement requirements. This research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized host. The online algorithm is analyzed using a competitive analysis approach. In addition, an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark algorithms. Our proposed online algorithm consumed 25% less energy and performed 43% fewer migrations than the benchmark algorithms.     

A bigraphical model for specifying cloud-based elastic systems and their behaviour

The few recent years have witnessed the appearance of a new kind of self-adaptive systems called cloud based-elastic systems. These systems are particularly appealing for their ability to maintain a decent quality of service and reduce a system’s operating cost at the same time. They achieve this by dynamically adjusting resources allocation in terms of elasticity. Meanwhile, complexity of structural and behavioural aspects related to cloud-based elastic systems increase the difficulty of designing and developing such systems. In this paper, we address this challenge by proposing a formal approach based on bigraphical reactive systems for modelling both structural and behavioural aspects of cloud-based elastic systems. In particular, we represent their behaviour in terms of client/application interactions and elasticity methods at different levels using bigraphical reaction rules. The feasibility of the proposed approach is illustrated through a motivating example running on the top of an Amazon Elastic Compute Cloud (EC2) infrastructure.     

Morphological, structural, and functional properties of maranta (Maranta arundinacea L) starch

Starch isolated from maranta (Maranta arundinacea) tuber and studied for its various physicochemical characteristics. The amylose content of the starch was 24.8%. SEM showed that the granules were small indented and spherical. Maranta starch granule size has a range of 2.92–6.42 μm, (mean of 4.84 μm), length/degree of 1.20, and roundness of 0.73. Maranta starch has a gelatinization temperature of 74.8°C, peak viscosity of 498 BU, and cold paste viscosity of 669 BU. It also possessed higher freeze-thaw stability. Dynamic rheological properties of maranta starch, measured using parallel plate geometry showed increased storage modulus (G’) values, while loss modulus (G″) values were decreased with increasing frequency values (0–100 Hz). The low gelatinization temperature and high freeze thaw stability of starch indicates its potential for application as a thickener in food industries.     

Exploration of connectivity with SEM: An fMRI study of resting state

In this era, the neuroscientists get attention to find a network of brain which is activated in resting state of mind. It is challenging for any analytical technique to find out the connectivity among Brodmann areas of brain in resting state. To find network, a study was conducted in which brains are scan by functional magnetic resonance imaging of four healthy right handed individuals. Exploratory factor analysis was used to explore that which Brodmann areas are related to each other and then structural equation model has applied on explored factors (lobes) to find a network of activated brain in resting state. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 264–269, 2016