Analysis and comparison of displacement granular pile anchors

Granular piles can resist only compressive and shear loads owing to their inherent nature. By a simple modification of providing a pedestal/geogrid at the bottom and attaching a cable to the same, they are made to resist pullout/uplift forces. This paper presents an analysis of granular pile anchor (GPA), considering it and the in situ soil to behave linearly and the in situ ground to be semi-infinite. A parametric study presents results in the form of variations of normalised shear stress, displacement influence coefficient and axial uplift force with depth with relative stiffness factor. Two methods for the estimation of deformation moduli of the GPA and the in situ soil are proposed. Based on the estimated values of the moduli, the displacements of GPA were estimated and the results compared with test results of Kumar (2002). The predicted displacements compare well with the measured ones.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.