Detection of edges from projections

In a number of applications of computerized tomography, the ultimate goal is to detect and characterize objects within a cross section. Detection of edges of different contrast regions yields the required information. The problem of detecting edges from projection data is addressed. It is shown that the class of linear edge detection operators used on images can be used for detection of edges directly from projection data. This not only reduces the computational burden but also avoids the difficulties of postprocessing a reconstructed image. This is accomplished by a convolution backprojection operation. For example, with the Marr-Hildreth edge detection operator, the filtering function that is to be used on the projection data is the Radon transform of the Laplacian of the 2-D Gaussian function which is combined with the reconstruction filter. Simulation results showing the efficacy of the proposed method and a comparison with edges detected from the reconstructed image are presented

Altered ultrastructure of rinderpest virus and its nucleocapsids induced by 5-fluorouracil

he ultrastructure of purified rinderpest virus and intracellular viral nucleocapsids from infected vero cells treated with a subtoxic dose of 5-fluorouracil (5-Fu) (1 mug/ml), has been analysed by transmission electron microscopy, and compared with that of normal virus particle and nucleocapsids. The results reveal dramatic alterations in the structure of both virions and nucleocapsids. The surface glycoprotein projection of virions was not seen or present at a much reduced level. The intracellular nucleocapsids showed pronounced structural changes,with respect to size, shape and fine structure. The length of treated nucleocapsids is much smaller as compared to the control. The central hollow core is missing in case of drug-treated nucleocapsid and the herring bone structure is replaced by a 'beads on string' structure. The presence of N protein, which is a major structural component of nucleocapsids was seen in 5-Fu-treated cells, but it was associated with a predominantly diffused form of nucleocapsids as seen by immunoelectron microscopy. We report here the first definitive and visual evidence of altered structure of virions and their nucleocapsids after 5-Fu treatment

Theoretical and Computational Analysis of Static and Dynamic Anomalies in Water-DMSO Binary Mixture at Low DMSO Concentrations

Experiments have repeatedly observed both thermodynamic and dynamic anomalies in aqueous binary mixtures, surprisingly at low solute concentration. Examples of such binary mixtures include water-DMSO, water-ethanol, water-tertiary butyl alcohol (TBA), and water-dioxane, to name a few. The anomalies have often been attributed to the onset of a structural transition, whose nature, however, has been left rather unclear. Here we study the origin of such anomalies using large scale computer simulations and theoretical analysis in water-DMSO binary mixture. At very low DMSO concentration (below 10%), small aggregates of DMSO are solvated by water through the formation of DMSO-(H2O)(2) moieties. As the concentration is increased beyond 10-12% of DMSO, spanning clusters comprising the same moieties appear in the system. Those clusters are formed and stabilized not only through H-bonding but also through the association of CH3 groups of DMSO. We attribute the experimentally observed anomalies to a continuum percolation-like transition at DMSO concentration X-DMSO approximate to 12-15%. The largest cluster size of CH3-CH3 aggregation clearly indicates the formation of such percolating clusters. As a result, a significant slowing down is observed in the decay of associated rotational auto time correlation functions (of the S = O bond vector of DMSO and O-H bond vector of water). Markedly unusual behavior in the mean square fluctuation of total dipole moment again suggests a structural transition around the same concentration range. Furthermore, we map our findings to an interacting lattice model which substantiates the continuum percolation model as the reason for low concentration anomalies in binary mixtures where the solutes involved have both hydrophilic and hydrophobic moieties.

Concise row-pruning algorithm to invert a matrix

Presented here, in a vector formulation, is an O(mn2) direct concise algorithm that prunes/identifies the linearly dependent (ld) rows of an arbitrary m X n matrix A and computes its reflexive type minimum norm inverse A(mr)-, which will be the true inverse A-1 if A is nonsingular and the Moore-Penrose inverse A+ if A is full row-rank. The algorithm, without any additional computation, produces the projection operator P = (I - A(mr)- A) that provides a means to compute any of the solutions of the consistent linear equation Ax = b since the general solution may be expressed as x = A(mr)+b + Pz, where z is an arbitrary vector. The rank r of A will also be produced in the process. Some of the salient features of this algorithm are that (i) the algorithm is concise, (ii) the minimum norm least squares solution for consistent/inconsistent equations is readily computable when A is full row-rank (else, a minimum norm solution for consistent equations is obtainable), (iii) the algorithm identifies ld rows, if any, and reduces concerned computation and improves accuracy of the result, (iv) error-bounds for the inverse as well as the solution x for Ax = b are readily computable, (v) error-free computation of the inverse, solution vector, rank, and projection operator and its inherent parallel implementation are straightforward, (vi) it is suitable for vector (pipeline) machines, and (vii) the inverse produced by the algorithm can be used to solve under-/overdetermined linear systems.

Moments estimation in Radon space

In this paper, we show a method of obtaining general and orthogonal moments, specifically Legendre and Zernicke moments, from the Radon Transform data of a two-dimensional function. The regular or geometric moments are first evaluated directly from the projection data and the orthogonal moments are derived from these regular moments.

Crossover dynamics at large metastability in gas-liquid nucleation

We have developed an alternate description of dynamics of nucleation in terms of an extended set of order parameters. The order parameters consist of an ordered set of kth largest clusters, ordered such that k = 1 is the largest cluster in the system, k = 2 is the second largest cluster, and so on. We have derived an analytic expression for the free energy for the kth largest cluster, which is in excellent agreement with the simulated results. At large supersaturation, the free energy barrier for the growth of the kth largest cluster disappears and the nucleation becomes barrierless. The major success of this extended theoretical formalism is that it can clearly explain the observed change in mechanism at large metastability P. Bhimalapuram et al., Phys. Rev. Lett. 98, 206104 (2007)] and the associated dynamical crossover. The classical nucleation theory cannot explain this crossover. The crossover from activated to barrierless nucleation is found to occur at a supersaturation where multiple clusters cross the critical size. We attribute the crossover as the onset of the kinetic spinodal. We have derived an expression for the rate of nucleation in the barrierless regime by modeling growth as diffusion on the free energy surface of the largest cluster. The model reproduces the slower increase in the rate of growth as a function of supersaturation, as observed in experiments.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Reduced Order Suboptimal Control Design for a Class of Nonlinear Distributed Parameter Systems Using POD and /spl thetas/-D Techniques

A new computational tool is presented in this paper for suboptimal control design of a class of nonlinear distributed parameter systems. First proper orthogonal decomposition based problem-oriented basis functions are designed, which are then used in a Galerkin projection to come up with a low-order lumped parameter approximation. Next, a suboptimal controller is designed using the emerging /spl thetas/-D technique for lumped parameter systems. This time domain sub-optimal control solution is then mapped back to the distributed domain using the same basis functions, which essentially leads to a closed form solution for the controller in a state feedback form. Numerical results for a real-life nonlinear temperature control problem indicate that the proposed method holds promise as a good suboptimal control design technique for distributed parameter systems.

Image reconstruction from incomplete projections data: A multiresolution modeling approach

Computerized tomography is an imaging technique which produces cross sectional map of an object from its line integrals. Image reconstruction algorithms require collection of line integrals covering the whole measurement range. However, in many practical situations part of projection data is inaccurately measured or not measured at all. In such incomplete projection data situations, conventional image reconstruction algorithms like the convolution back projection algorithm (CBP) and the Fourier reconstruction algorithm, assuming the projection data to be complete, produce degraded images. In this paper, a multiresolution multiscale modeling using the wavelet transform coefficients of projections is proposed for projection completion. The missing coefficients are then predicted based on these models at each scale followed by inverse wavelet transform to obtain the estimated projection data.

Orientational relaxation in dipolar systems: How much do we understand the role of correlations

Dipolar systems, both liquids and solids, constitute a class of naturally abundant systems that are important in all branches of natural science. The study of orientational relaxation provides a powerful method to understand the microscopic properties of these systems and, fortunately, there are many experimental tools to study orientational relaxation in the condensed phases. However, even after many years of intense research, our understanding of orientational relaxation in dipolar systems has remained largely imperfect. A major hurdle towards achieving a comprehensive understanding is the long range and complex nature of dipolar interactions which also made reliable theoretical study extremely difficult. These difficulties have led to the development of continuum model based theories, which although they provide simple, elegant expressions for quantities of interest, are mostly unsatisfactory as they totally neglect the molecularity of inter-molecular interactions. The situation has improved in recent years because of renewed studies, led by computer simulations. In this review, we shall address some of the recent advances, with emphasis on the work done in our laboratory at Bangalore. The reasons for the failure of the continuum model, as revealed by the recent Brownian dynamics simulations of the dipolar lattice, are discussed. The main reason is that the continuum model predicts too fast a decay of the torque-torque correlation function. On the other hand, a perturbative calculation, based on Zwanzig's projection operator technique, provides a fairly satisfactory description of the single particle orientational dynamics for not too strongly polar dipolar systems. A recently developed molecular hydrodynamic theory that properly includes the effects of intermolecular orientational pair correlations provides an even better description of the single-particle orientational dynamics. We also discuss the rank dependence of the dielectric friction. The other topics reviewed here includes dielectric relaxation and solvation dynamics, as they are intimately connected with orientational relaxation. Recent molecular dynamics simulations of the dipolar lattice are also discussed. The main theme of the present review is to understand the effects of intermolecular interactions on orientational relaxation. The presence of strong orientational pair correlation leads to a strong coupling between the single particle and the collective dynamics. This coupling can lead to rich dynamical properties, some of which are detailed here, while a major part remains yet unexplored.

Non-interferometric methods of phase estimation for application in optical tomography

We describe here two non-interferometric methods for the estimation of the phase of transmitted wavefronts through refracting objects. The phase of the wavefronts obtained is used to reconstruct either the refractive index distribution of the objects or their contours. Refraction corrected reconstructions are obtained by the application of an iterative loop incorporating digital ray tracing for forward propagation and a modified filtered back projection (FBP) for reconstruction. The FBP is modified to take into account non-straight path propagation of light through the object. When the iteration stagnates, the difference between the projection data and an estimate of it obtained by ray tracing through the final reconstruction is reconstructed using a diffraction tomography algorithm. The reconstruction so obtained, viewed as a correction term, is added to the estimate of the object from the loop to obtain an improved final refractive index reconstruction.

Albedo enhancement of marine clouds to counteract global warming: impacts on the hydrological cycle

Recent studies have shown that changes in solar radiation affect the hydrological cycle more strongly than equivalent CO(2) changes for the same change in global mean surface temperature. Thus, solar radiation management ``geoengineering'' proposals to completely offset global mean temperature increases by reducing the amount of absorbed sunlight might be expected to slow the global water cycle and reduce runoff over land. However, proposed countering of global warming by increasing the albedo of marine clouds would reduce surface solar radiation only over the oceans. Here, for an idealized scenario, we analyze the response of temperature and the hydrological cycle to increased reflection by clouds over the ocean using an atmospheric general circulation model coupled to a mixed layer ocean model. When cloud droplets are reduced in size over all oceans uniformly to offset the temperature increase from a doubling of atmospheric CO(2), the global-mean precipitation and evaporation decreases by about 1.3% but runoff over land increases by 7.5% primarily due to increases over tropical land. In the model, more reflective marine clouds cool the atmospheric column over ocean. The result is a sinking motion over oceans and upward motion over land. We attribute the increased runoff over land to this increased upward motion over land when marine clouds are made more reflective. Our results suggest that, in contrast to other proposals to increase planetary albedo, offsetting mean global warming by reducing marine cloud droplet size does not necessarily lead to a drying, on average, of the continents. However, we note that the changes in precipitation, evaporation and P-E are dominated by small but significant areas, and given the highly idealized nature of this study, a more thorough and broader assessment would be required for proposals of altering marine cloud properties on a large scale.

Soft classification based Sub-pixel allocation model

Land cover (LC) refers to what is actually present on the ground and provide insights into the underlying solution for improving the conditions of many issues, from water pollution to sustainable economic development. One of the greatest challenges of modeling LC changes using remotely sensed (RS) data is of scale-resolution mismatch: that the spatial resolution of detail is less than what is required, and that this sub-pixel level heterogeneity is important but not readily knowable. However, many pixels consist of a mixture of multiple classes. The solution to mixed pixel problem typically centers on soft classification techniques that are used to estimate the proportion of a certain class within each pixel. However, the spatial distribution of these class components within the pixel remains unknown. This study investigates Orthogonal Subspace Projection - an unmixing technique and uses pixel-swapping algorithm for predicting the spatial distribution of LC at sub-pixel resolution. Both the algorithms are applied on many simulated and actual satellite images for validation. The accuracy on the simulated images is ~100%, while IRS LISS-III and MODIS data show accuracy of 76.6% and 73.02% respectively. This demonstrates the relevance of these techniques for applications such as urban-nonurban, forest-nonforest classification studies etc.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.