RIG-I contributes to the innate immune response after cerebral ischemia

BACKGROUND: Focal cerebral ischemia induces an inflammatory response that when exacerbated contributes to deleterious outcomes. The molecular basis regarding the regulation of the innate immune response after focal cerebral ischemia remains poorly understood. METHODS: In this study we examined the expression of retinoic acid-inducible gene (RIG)-like receptor-I (RIG-I) and its involvement in regulating inflammation after ischemia in the brain of rats subjected to middle cerebral artery occlusion (MCAO). In addition, we studied the regulation of RIG-I after oxygen glucose deprivation (OGD) in astrocytes in culture. RESULTS: In this study we show that in the hippocampus of rats, RIG-I and IFN-α are elevated after MCAO. Consistent with these results was an increased in RIG-I and IFN-α after OGD in astrocytes in culture. These data are consistent with immunohistochemical analysis of hippocampal sections, indicating that in GFAP-positive cells there was an increase in RIG-I after MCAO. In addition, in this study we have identified n-propyl gallate as an inhibitor of IFN-α signaling in astrocytes. CONCLUSION: Our findings suggest a role for RIG-I in contributing to the innate immune response after focal cerebral ischemia

The RANSAC method for generating fracture networks from micro-seismic event data

Fracture network modeling is an essential part of the design, development and performance assessment of Enhanced Geothermal Systems. These systems are created from geothermal resources, usually located several kilometers below the surface of the Earth, by establishing a network of connected fractures through which fluid can flow. The depth of the reservoir makes it impossible to make direct measurements of fractures and data are collected from indirect measurements such as geophysical surveys. An important source of indirect data is the seismic event point cloud generated by the fracture stimulation process. Locations of these points are estimated from recorded micro-seismic signals generated by fracture initiation, propagation and slip. This point cloud can be expressed as a set of three-dimensional coordinates with attributes, for example Seijk={(x,y,z); a{pipe}x,y,z∈R, a∈I}. We describe two methods for reconstructing realistic fracture trace lines and planes given the point cloud of seismic events data: Enhanced Brute-Force Search and RANSAC. The methods have been tested on a synthetic data set and on the Habanero data set of Geodynamics' geothermal project in the Cooper Basin of South Australia. Our results show that the RANSAC method is an efficient and suitable method for the conditional simulation of fracture networks. © 2013 International Association for Mathematical Geosciences.Younes Fadakar Alghalandis, Peter A. Dowd, Chaoshui X

A spatial clustering approach for stochastic fracture network modelling

Fracture network modelling plays an important role in many application areas in which the behaviour of a rock mass is of interest. These areas include mining, civil, petroleum, water and environmental engineering and geothermal systems modelling. The aim is to model the fractured rock to assess fluid flow or the stability of rock blocks. One important step in fracture network modelling is to estimate the number of fractures and the properties of individual fractures such as their size and orientation. Due to the lack of data and the complexity of the problem, there are significant uncertainties associated with fracture network modelling in practice. Our primary interest is the modelling of fracture networks in geothermal systems and, in this paper, we propose a general stochastic approach to fracture network modelling for this application. We focus on using the seismic point cloud detected during the fracture stimulation of a hot dry rock reservoir to create an enhanced geothermal system; these seismic points are the conditioning data in the modelling process. The seismic points can be used to estimate the geographical extent of the reservoir, the amount of fracturing and the detailed geometries of fractures within the reservoir. The objective is to determine a fracture model from the conditioning data by minimizing the sum of the distances of the points from the fitted fracture model. Fractures are represented as line segments connecting two points in two-dimensional applications or as ellipses in three-dimensional (3D) cases. The novelty of our model is twofold: (1) it comprises a comprehensive fracture modification scheme based on simulated annealing and (2) it introduces new spatial approaches, a goodness-of-fit measure for the fitted fracture model, a measure for fracture similarity and a clustering technique for proposing a locally optimal solution for fracture parameters. We use a simulated dataset to demonstrate the application of the proposed approach followed by a real 3D case study of the Habanero reservoir in the Cooper Basin, Australia. © 2013 Springer-Verlag Wien.S. Seifollahi, P. A. Dowd, C. Xu, A. Y. Fadaka

Optimal subwavelength design for efficient light trapping in central slit of plasmonics-based metal-semiconductor-metal photodetector

© 2015, Springer Science+Business Media New York. We present the analysis of a novel plasmonics-based metal-semiconductor-metal photodetector that dramatically modifies the light transmission spectra when the sub-wavelength central slit is partly covered with a gold (Au) thin film. The simulation results reveal surface plasmons together with the optimized nano-gratings impact in this special design for quality light absorption inside the device active region. Finite-difference time-domain method has been utilized to simulate the behavior of the proposed novel photodetector structure with significant improved light absorption capacity