Surface versus bulk activity of lysozyme deposited on hydrogel contact lens materials in vitro

Purpose

To determine and compare the levels of surface versus bulk active lysozyme deposited on several commercially available hydrogel contact lens materials.

Robust geocast routing protocols for safety and comfort applications in VANETs

Routing in cooperative vehicular networks is a challenging task because of high mobility of vehicles and difficulty of localization. In this paper, we study the geocast routing problem in Vehicular Ad‐hoc NETworks (VANETs), which aims at delivering data to a specific group of mobile vehicles identified by their geographical location. Although many geocast routing protocols have been proposed, only partial inherent constraints of VANETs (such as mobility, internal network fragmentation problem, external network fragmentation problem, and overload) are taken into account. Therefore, we propose two novel and robust geocast routing protocols: the first one, called Robust Geocast Routing Protocol for Safety Applications (RGRP‐SA), is dedicated to road safety applications, while the second, namely, Robust Geocast Routing Protocol for Comfort Applications (RGRP‐CA), is designed for comfort applications. Simulations conducted in NS‐2 demonstrate that our safety‐oriented RGRP‐SA protocol outperforms Inter‐Vehicle Geocast protocol and Mobicast Routing Protocol in VANETs by sending up to 25% more packets, cutting the end‐to‐end delay in half, and solving the internal network fragmentation problem. Besides, it is also shown that our comfort‐oriented RGRP‐CA protocol serves well comfort applications with only light overhead by solving internal and external network fragmentation problems and providing more reliable data delivery (with a 25% higher packet delivery ratio) and higher network throughput utilization in comparison with Mobicast with Carry‐and‐Forward protocol. Copyright © 2015 John Wiley & Sons, Ltd.     

Bioconvective electromagnetic nanofluid transport from a wedge geometry: Simulation of smart electro‐conductive bio‐nanopolymer processing

A mathematical model is presented for steady, two‐dimensional, stagnation‐point flow, heat, mass, and micro‐organism transfer in a viscous, incompressible, bioconvective, electromagnetic nanofluid along a wedge with Stefan blowing effects, hydrodynamic slip, and multiple convective boundary conditions. Gyrotactic micro‐organisms are present in the nanofluid and bioconvection arises, characterized by micro‐organisms swimming under a competing torque. Similarity transformations are used to render the system of governing partial differential equations into a system of coupled similarity equations. The transformed equations are solved numerically with the BVP5C method. The impact of emerging parameters on dimensionless velocity, temperature, magnetic induction function, nanoparticle volume fraction, and density of motile micro‐organisms is studied graphically. Furthermore, the responses of the local skin friction, local Nusselt number, local Sherwood number, and the wall gradient of density of motile micro‐organism number to variation in these parameters are elaborated. Validation of solutions with previous studies based on special cases of the general model is included. The simulations are relevant to the processing of biological, electro‐conductive nanomaterials and industrial hygienic coating systems exploiting combined electromagnetics, nanosystems, and microscopic, bio‐propulsion mechanisms.     

A fast and robust segmentation of magnetic resonance brain images using a combination of the pyramidal approach and level set method

We propose in this article an approach to optimize the processing time and to improve the quality of brain magnetic resonance images segmentation. Level set method (LSM) was adopted with a periodic reinitialization process to prevent the LS function from being too steep or too flat near the interface. Although it is used to maintain the stability of the interface evolution and gives interesting results, it requires a longer processing time. To overcome this disadvantage and reduce the processing time, we propose a hybridization with a regular Gaussian pyramid, which reduces the resolution of the initial image and prevents the possibility of local minima. To compare the different segmentation algorithms, we used six types of quality measurements: specificity, sensitivity, Dice similarity, the Jaccard index, and the correctly and incorrectly marked pixels. A comparison between the results obtained by LSM, LSM with reinitialization, the approach of Barman et al., An International Journal 1 (2011), particle swarm optimization based on the Chan and Vese model (Mandal et al., Engineering Applications of Artificial Intelligence 35 (2014), 199‐214) and by our hybrid approach reveals a clear efficiency of our hybridization strategy. The processing time was significantly reduced, and the quality of segmentation was improved. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 243–253, 2016     

Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: application to railway track circuit diagnosis

Using a statistical model in a diagnosis task generally requires a large amount of labeled data. When ground truth information is not available, too expensive or difficult to collect, one has to rely on expert knowledge. In this paper, it is proposed to use partial information from domain experts expressed as belief functions. Expert opinions are combined in this framework and used with measurement data to estimate the parameters of a statistical model using a variant of the EM algorithm. The particular application investigated here concerns the diagnosis of railway track circuits. A noiseless Independent Factor Analysis model is postulated, assuming the observed variables extracted from railway track inspection signals to be generated by a linear mixture of independent latent variables linked to the system component states. Usually, learning with this statistical model is performed in an unsupervised way using unlabeled examples only. In this paper, it is proposed to handle this learning process in a soft-supervised way using imperfect information on the system component states. Fusing partially reliable information about cluster membership is shown to significantly improve classification results.     

Heterogeneous Advanced Photo-Fenton Oxidation of Phenolic Aqueous Solutions over Iron-Containing SBA-15 Catalyst

Iron-containing SBA-15 catalysts have been prepared following different synthesis routes, direct synthesis by adjusting pH at 3 and 6 and with post synthesis procedure. Activity and stability of these materials were assessed on the photo-Fenton degradation of phenolic aqueous solutions by H2O2 using near ultraviolet irradiation （254 nm） at room temperature and initial neutral pH. Their catalytic performance was mentioned in terms of phenol and TOC （total organic carbon） conversions. Several complementary techniques, including X-ray, nitrogen sorption isotherms, UV （Ultraviolet） visible, were used to evaluate the final structural and textural properties of calcined Fe-SBA 15 materials. These materials show a high activity and stability of iron species.     

Review on polyphosphazenes-based materials for bone and skeleton tissue engineering

The skeleton performs motley of functions. Defected bones and metameric loss of bone are often resulted due to innate abnormalities and accidental injuries. An assessment is made on the diversity of chemistry of phosphazene with an inflection on new developments and their importance in tissue engineering. Tissue engineering mostly uses polymers that can biodegrade in porous/permeable scaffolds form for treating damaged tissues and skeleton. Demand of these polymers is increasing as timely substrates for tissue regeneration in contrast to the mostly used polyethylene terephalate, polyorthoesters, and poly(α-amino acids). Polyphosphazenes as biodegradable polymers have great potential for applications of tissue engineering. Due to biodegradability of P–N backbone, vast diversity of structure and high functional density polyphosphazenes provides many advantages for the formation of biologically compatible macromolecules. However, the nature of the side group determines the degradation ability of such polymers. These biodegradable polymers (polyphosphazenes) provide harmless and pH neutral substances because phosphates and ammonia have high buffer capacity. This review article focuses on the biocompatible polyphosphazenes and their utilization as regeneration of tissues, skeleton, and bones with a particular focus on materials that contains only polyphosphazenes, blends of polyphosphazene, and composites made from polyphosphazene.