High dose N ion implantation effects on surface treated UNCD films

Ion implantation is commonly used to modify the surface or near-surface properties of materials. In this work, plasma treated ultrananocrystalline diamond (UNCD) films were implanted using 100 and 200 keV high dose (10¹⁶ ions/cm²) nitrogen ions and annealed. Detailed studies have been carried out to reveal the structural and chemical states of the surface treated UNCD films before implantation, as-implanted, and after annealing by using Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and electron field emission (EFE) measurements. The high dose N ion implantation induced the formation of amorphous phase, which are converted into graphitic phase after annealing, and improved the field emission properties of UNCD films. The improved field emission is attributed to the surface charge transfer doping mechanism.     

Fluid‐particle drag in inertial polydisperse gas–solid suspensions

In this article, we extend the low Reynolds number fluid‐particle drag relation proposed by Yin and Sundaresan for polydisperse systems to include the effect of moderate fluid inertia. The proposed model captures the fluid‐particle drag results obtained from lattice‐Boltzmann simulations of bidisperse and ternary suspensions at particle mixture Reynolds numbers ranging from 0 ≤ Re_mix ≤ 40, over a particle volume fraction range of 0.2 ≤ ? ≤ 0.4, volume fraction ratios of 1 ≤ ?_i/?_j ≤ 3, and particle diameter ratios of 1 ≤ d_i/d_j ≤ 2.5. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Olfactory receptor-based polypeptide sensor for acetic acid VOC detection

Rapid detection of food-borne pathogens in packaged food products can prevent the spread of infectious diseases. This study investigates the application of novel sensing material that is sensitive to specific indicator volatile organic compound (VOC) related to Salmonella contamination in packaged meat. Specifically, the objective was to develop an olfactory receptor-based synthetic polypeptide sensor for the detecting acetic acid in low concentrations and at room temperature. Synthetic polypeptide was deposited on a quartz crystal microbalance (QCM) electrode and was evaluated for detecting acetic acid at 10–100 ppm. Developed sensor exhibited repeatable response to a particular concentration of acetic acid and displayed reproducibility among multiple sensors during acetic acid detection. Mean estimated lower detection limits of these sensors were about 1–3 ppm and linear calibration models showed linear relationships. Thus, the QCM sensors exhibited a great potential for detecting low concentrations of acetic acid at room temperature and can be used in the sensor array for packaged meat spoilage and contamination detection.     

Quantitative assessment of collagen fibre orientations from two-dimensional images of soft biological tissues

In this work, we outline an automated method for the extraction and quantification of material parameters characterizing collagen fibre orientations from two-dimensional images. Morphological collagen data among different length scales were obtained by combining the established methods of Fourier power spectrum analysis, wedge filtering and progressive regions of interest splitting. Our proposed method yields data from which we can determine parameters for computational modelling of soft biological tissues using fibre-reinforced constitutive models and gauge the length scales most appropriate for obtaining a physically meaningful measure of fibre orientations, which is representative of the true tissue morphology of the two-dimensional image. Specifically, we focus on three parameters quantifying different aspects of the collagen morphology: first, using maximum-likelihood estimation, we extract location parameters that accurately determine the angle of the principal directions of the fibre reinforcement (i.e. the preferred fibre directions); second, using a dispersion model, we obtain dispersion parameters quantifying the collagen fibre dispersion about these principal directions; third, we calculate the weighted error entropy as a measure of changes in the entire fibre distributions at different length scales, as opposed to their average behaviour. With fully automated imaging techniques (such as multiphoton microscopy) becoming increasingly popular (which often yield large numbers of images to analyse), our method provides an ideal tool for quickly extracting mechanically relevant tissue parameters which have implications for computational modelling (e.g. on the mesh density) and can also be used for the inhomogeneous modelling of tissues.     

Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment

A common algorithm to solve the shortest path problem (SPP) is the Dijkstra algorithm. In this paper, a generalized Dijkstra algorithm is proposed to handle SPP in an uncertain environment. Two key issues need to be addressed in SPP with fuzzy parameters. One is how to determine the addition of two edges. The other is how to compare the distance between two different paths with their edge lengths represented by fuzzy numbers. To solve these problems, the graded mean integration representation of fuzzy numbers is adopted to improve the classical Dijkstra algorithm. A numerical example of a transportation network is used to illustrate the efficiency of the proposed method.     

Green-Inspired Fabrication of Silver Nanoparticles and Examine its Potential In-Vitro Cytotoxic and Antibacterial Activities

Journal of Inorganic and Organometallic Polymers and Materials - The present work demonstrates the non-hazardous and environmentally benevolent green fabrication of silver nanoparticles using...     

Identification of a structural element in phospholipase C beta2 that interacts with G protein betagamma subunits

To delineate the specific regions of phospholipase C beta2 (PLC beta2) involved in binding and activation by G protein betagamma subunits, we synthesized peptides corresponding to segments of PLC beta2. Two overlapping peptides corresponding to Asn-564-Lys-583 (N20K) and Glu-574-Lys-593 (E20K) inhibited the activation of PLC beta2 by betagamma subunits (IC50 50 and 150 microM, respectively), whereas two control peptides did not. N20K and E20K, but not the control peptides, inhibited betagamma-dependent ADP-ribosylation of Galphai1 by pertussis toxin and betagamma-dependent activation of phosphoinositide 3-kinase. To demonstrate direct binding of the peptides to betagamma subunits, the peptides were chemically cross-linked to purified beta1gamma2. N20K and E20K cross-linked to both beta1 and gamma2 subunits, whereas the control peptides did not. Cross-linking to beta and gamma was inhibited by incubation with excess PLC beta2 or PLC beta3, whereas cross-linking to gamma but not beta was inhibited by r-myr-alphai1. These data together demonstrate specificity of N20K and E20K for G betagamma binding and inhibition of effector activation by betagamma subunits. The results suggest that an overlapping region of the two active peptides, Glu-574-Lys-583, mimics a region of PLC beta2 that is involved in binding to betagamma subunits. Changing a tyrosine to a glutamine in this overlapping region of the peptides inhibited binding of the peptide to betagamma subunits. Alignment of these peptides with the three-dimensional structure from PLC delta1 identifies a putative alpha helical region on the surface of the catalytic domain of PLC beta2 that could interact with betagamma subunits.     

Decoupled approach to multidisciplinary design optimization under uncertainty

We propose solution methods for multidisciplinary design optimization (MDO) under uncertainty. This is a class of stochastic optimization problems that engineers are often faced with in a realistic design process of complex systems. Our approach integrates solution methods for reliability-based design optimization (RBDO) with solution methods for deterministic MDO problems. The integration is enabled by the use of a deterministic equivalent formulation and the first order Taylor’s approximation in these RBDO methods. We discuss three specific combinations: the RBDO methods with the multidisciplinary feasibility method, the all-at-once method, and the individual disciplinary feasibility method. Numerical examples are provided to demonstrate the procedure. Anukal Chiralaksanakul is currently a full-time lecturer in the Graduate School of Business Administration at National Institute of Development Administration (NIDA), Bangkok, Thailand.     

Structural Health Monitoring of Railroad Wheels Using Wheel Impact Load Detectors

This paper proposes two quantitative criteria for removing railroad wheels from service, based on real-time structural health monitoring trends that are developed using data collected from trains while in service. The data is collected using wheel impact load detectors (WILDs). These impact load trends are able to distinguish wheels with a high probability of failure from high-impact wheels with a low probability of failure. The trends indicate the critical wheels that actually need to be removed, while at the same time allowing wheels that aren’t critical to remain in service. As a result, the safety of the railroad will be much improved by being able to identify and remove wheels that have high likelihood of causing catastrophic failures.