3D Image Reconstruction From Truncated Helical Cone Beam Projection Data - A Linear Prediction Approach

With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence can give exact reconstruction. The theoretically exact helical cone-beam reconstruction algorithm proposed by Katsevich is a breakthrough and has attracted interest in the 3D reconstruction using helical cone-beam Computed Tomography.In many practical situations, the available projection data is incomplete. One such case is where the detector plane does not completely cover the full extent of the object being imaged in lateral direction resulting in truncated projections. This result in artifacts that mask small features near to the periphery of the ROI when reconstructed using the convolution back projection (CBP) method assuming that the projection data is complete. A number of techniques exist which deal with completion of missing data followed by the CBP reconstruction. In 2D, linear prediction (LP)extrapolation has been shown to be efficient for data completion, involving minimal assumptions on the nature of the data, producing smooth extensions of the missing projection data.In this paper, we propose to extend the LP approach for extrapolating helical cone beam truncated data. The projection on the multi row flat panel detectors has missing columns towards either ends in the lateral direction in truncated data situation. The available data from each detector row is modeled using a linear predictor. The available data is extrapolated and this completed projection data is backprojected using the Katsevich algorithm. Simulation results show the efficacy of the proposed method.

Predictive distribution modeling for rare Himalayan medicinal plant Berberis aristata DC

Predictive distribution modelling of Berberis aristata DC, a rare threatened plant with high medicinal values has been done with an aim to understand its potential distribution zones in Indian Himalayan region. Bioclimatic and topographic variables were used to develop the distribution model with the help of three different algorithms viz. GeneticAlgorithm for Rule-set Production (GARP), Bioclim and Maximum entroys(MaxEnt). Maximum entropy has predicted wider potential distribution (10.36%) compared to GARP (4.63%) and Bioclim (2.44%). Validation confirms that these outputs are comparable to the present distribution pattern of the B. atistata. This exercise highlights that this species favours Western Himalaya. However, GARP and MaxEnt's prediction of Eastern Himalayan states (i.e. Arunachal Pradesh, Nagaland and Manipur) are also identified as potential occurrence places require further exploration.

A Profilometric Approach to 3D Face Reconstruction and Its Application to Face Recognition

3D Face Recognition is an active area of research for past several years. For a 3D face recognition system one would like to have an accurate as well as low cost setup for constructing 3D face model. In this paper, we use Profilometry approach to obtain a 3D face model.This method gives a low cost solution to the problem of acquiring 3D data and the 3D face models generated by this method are sufficiently accurate. We also develop an algorithm that can use the 3D face model generated by the above method for the recognition purpose.

Spectral Finite Element Modeling of Complex Structures for Applications in Real-time Structural Health Monitoring

In this paper we discuss the recent progresses in spectral finite element modeling of complex structures and its application in real-time structural health monitoring system based on sensor-actuator network and near real-time computation of Damage Force Indicator (DFI) vector. A waveguide network formalism is developed by mapping the original variational problem into the variational problem involving product spaces of 1D waveguides. Numerical convergence is studied using a h()-refinement scheme, where is the wavelength of interest. Computational issues towards successful implementation of this method with SHM system are discussed.

Topology Optimization of Electrostatically Actuated Micromechanical Structures with Accurate Electrostatic Modeling of the Interpolated Material Model

In this paper, we present a novel formulation for performing topology optimization of electrostatically actuated constrained elastic structures. We propose a new electrostatic-elastic formulation that uses the leaky capacitor model and material interpolation to define the material state at every point of a given design domain continuously between conductor and void states. The new formulation accurately captures the physical behavior when the material in between a conductor and a void is present during the iterative process of topology optimization. The method then uses the optimality criteria method to solve the optimization problem by iteratively pushing the state of the domain towards that of a conductor or a void in the appropriate regions. We present examples to illustrate the ability of the method in creating the stiffest structure under electrostatic force for different boundary conditions.

Modeling urban traffic planning thro' strategic decisions- A case from Bangalore, India

This paper deals with reducing the waiting times of vehicles at the traffic junctions by synchronizing the traffic signals. Strategies are suggested for betterment of the situation at different time intervals of the day, thus ensuring smooth flow of traffic. The concept of single way systems are also analyzed. The situation is simulated in Witness 2003 Simulation package using various conventions. The average waiting times are reduced by providing an optimal combination for the traffic signal timer. Different signal times are provided for different times of the day, thereby further reducing the average waiting times at specific junctions/roads according to the experienced demands.

Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%

The determination of stem cell fate by 3D scaffold structures through the control of cell shape

Stem cell response to a library of scaffolds with varied 3D structures was investigated. Microarray screening revealed that each type of scaffold structure induced a unique gene expression signature in primary human bone marrow stromal cells (hBMSCs). Hierarchical cluster analysis showed that treatments sorted by scaffold structure and not by polymer chemistry suggesting that scaffold structure was more influential than scaffold composition. Further, the effects of scaffold structure on hBMSC function were mediated by cell shape. Of all the scaffolds tested, only scaffolds with a nanofibrous morphology were able to drive the hBMSCs down an osteogenic lineage in the absence of osteogenic supplements. Nanofiber scaffolds forced the hBMSCs to assume an elongated, highly branched morphology. This same morphology was seen in osteogenic controls where hBMSCs were cultured on flat polymer films in the presence of osteogenic supplements (OS). In contrast, hBMSCs cultured on flat polymer films in the absence of OS assumed a more rounded and less-branched morphology. These results indicate that cells are more sensitive to scaffold structure than previously appreciated and suggest that scaffold efficacy can be optimized by tailoring the scaffold structure to force cells into morphologies that direct them to differentiate down the desired lineage. Published by Elsevier Ltd.

Impact of metal on the DNA photocleavage activity and cytotoxicity of ferrocenyl terpyridine 3d metal complexes

Ferrocenyl terpyridine 3d metal complexes and their analogues, viz. [M(Fc-tpy)(2)](ClO(4))(2) (1-4), [Zn(Ph-tpy)(2)](ClO(4))(2) (5) and [Zn(Fc-dpa)(2)]X(2) (X = ClO(4), 6; PF6, 6a), where M = Fe(II) in 1, Co(II) in 2, Cu(II) in 3 and Zn(II) in 4, Fc-tpy is 4'-ferrocenyl-2,2': 6', 2 `'-terpyridine, Ph-tpy is 4'-phenyl-2,2': 6', 2 `'-terpyridine and Fc-dpa is ferrocenyl-N,N-dipicolylmethanamine, are prepared and their DNA binding and photocleavage activity in visible light studied. Complexes 2, 4, 5 and 6a that are structurally characterized by X-ray crystallography show distorted octahedral geometry with the terpyridyl ligands binding to the metal in a meridional fashion, with Fc-dpa in 6a showing a facial binding mode. The Fc-tpy complexes display a charge transfer band in the visible region. The ferrocenyl (Fc) complexes show a quasi-reversible Fc(+)-Fc redox couple within 0.48 to 0.66 V vs. SCE in DMF-0.1 M TBAP. The DNA binding constants of the complexes are similar to 10(4) M(-1). Thermal denaturation and viscometric data suggest DNA surface binding through electrostatic interaction by the positively charged complexes. Barring the Cu(II) complex 3, the complexes do not show any chemical nuclease activity in the presence of glutathione. Complexes 1-4 exhibit significant plasmid DNA photocleavage activity in visible light via a photoredox pathway. Complex 5, without the Fc moiety, does not show any DNA photocleavage activity. The Zn(II) complex 4 shows a significant PDT effect in HeLa cancer cells giving an IC(50) value of 7.5 mu M in visible light, while being less toxic in the dark (IC(50) = 49 mu M).