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.     

An application system for automation of constant-time radio frequency electron paramagnetic resonance imaging

A Windows based application system for data collection, Fourier reconstruction and analysis of pure phase encoded constant-time radio frequency electron paramagnetic resonance (EPR) images, is described. The graphical user interface (GUI) of the system was written in MATLAB version 5.0, using its built-in GUI utilities. Design considerations of the application system included speed, flexibility and user-friendly data display and analysis. To maximize the speed of image data collection, MATLAB's built-in C interface system, MEX was not used for data collection. Instead, MATLAB programs call the C programs from the DOS prompt directly, based on the data collection parameters entered through the GUI. Computational procedures included various digital signal-processing steps such as filtering, interpolation etc. for the Fourier reconstruction of 2D, and 3D EPR images from the pure phase encoded data. Examples of 2D images illustrating the performance of the system are presented. Although the application system has been developed for the specific purpose of EPR imaging, it can easily be adapted to other areas such as magnetic resonance microscopy as well.     

Visual observation of phase transitions in LiKSO4 under pressure

Phase transitions in LiKSO₄ have been visually observed in a diamond-anvil cell up to 16 GPa. The observations confirm a symmetry change at 0·9 GPa and a solidstate crystal to amorphous transition at 12 GPa. The crystal exhibits a memory across the crystalline transitions. Interesting microstructural features were observed in the range of the amorphous phase.