Constructing intrinsic parameters with active models for invariantsurface reconstruction

A technique for constructing a canonical surface parameterization in terms of lines of curvature is presented. Two methods of computing the canonical invariant representation are also presented. In the first method, a static instance of the controlled continuity spline is used for the stabilizer. Ways to modify it to reflect a change of parameters to the lines of curvature are described. In the second method, the dynamic instance of the controlled continuity spline called the deformable model is used. A force field defined in terms of the principal vectors is synthesized and applied to the parameter curves of the deformable model to coerce them along the lines of curvature. In essence, any transformation of parameters requires a modification of the stabilizer in the first method, whereas in the second method, it is tantamount to synthesizing a new force field. Experimental results with real and synthetic range data are included     

A unified approach to noise removal, image enhancement, and shaperecovery

We present a unified approach to noise removal, image enhancement, and shape recovery in images. The underlying approach relies on the level set formulation of the curve and surface motion, which leads to a class of PDE-based algorithms. Beginning with an image, the first stage of this approach removes noise and enhances the image by evolving the image under flow controlled by min/max curvature and by the mean curvature. This stage is applicable to both salt-and-pepper grey-scale noise and full-image continuous noise present in black and white images, grey-scale images, texture images, and color images. The noise removal/enhancement schemes applied in this stage contain only one enhancement parameter, which in most cases is automatically chosen. The other key advantage of our approach is that a stopping criteria is automatically picked from the image; continued application of the scheme produces no further change. The second stage of our approach is the shape recovery of a desired object; we again exploit the level set approach to evolve an initial curve/surface toward the desired boundary, driven by an image-dependent speed function that automatically stops at the desired boundary.     

Mössbauer and XRD studies on the effect of doping iron in KCaY(PO4)2

The effect of doping iron at the yttrium site in hexagonal KCaY(PO₄)₂ is studied for various concentrations ofx (0≤x≤1), of iron using Mössbauer and X-ray diffraction methods. For low iron concentrations, very little changes in structure are seen but atx≈0·1, onset of new peaks in the XRD pattern is observed. The Mössbauer study of the doped samples reveals that iron has a solubility of up to 2·5% in the parent phase with any excess iron precipitating out to form a new and unknown phase. From a detailed analysis of the X-ray diffraction pattern (corresponding tox=1) of the latter phase, it is found that this phase is rhombohedral with the possible space groupR3.     

High-throughput analysis of multispectral images of breast cancer tissue.

Statistical analysis of genetic changes within cell nuclei that are far from the primary tumor would help determine whether such changes have occurred prior to tumor invasion. To determine whether the gene amplification in cells is morphologically and/or genetically related to the primary tumor requires quantitative evaluation of a large number of cell nuclei from continuous meaningful structures such as milk-ducts, tumors, etc., located relatively far from the primary tumor. To address this issue, we have designed an integrated image analysis software system for high-throughput segmentation of nuclei. Filters such as Beltrami flow-based reaction-diffusion, directional diffusion, etc., were used to pre-process the images resulting in a better segmentation. The accurate shape of the segmented nucleus was recovered using an iterative "shrink-wrap" operation. The study of two cases of ductal carcinoma in situ in breast tissue supports the biological observation regarding the existence of a preferential intraductal invasion, and therefore a common origin, between the primary tumor and the gene amplification in the cell-nuclei lining the ductal structures in the breast.     

Controlled release of diclofenac sodium and ibuprofen through beads of sodium alginate and hydroxy ethyl cellulose blends

Controlled release of diclofenac sodium (DS) and ibuprofen (IB) drugs through sodium alginate (NaAlg)‐hydroxy ethyl cellulose (HEC) blend polymeric beads has been investigated. Beads were prepared by precipitating the viscous solution of NaAlg and HEC blend in alcohol followed by crosslinking with calcium chloride. Different formulations were developed in bead form by varying the amount of HEC, crosslinking agent, and drug concentration. Swelling studies in water, percent encapsulation of drugs, and release studies were carried out. The DS‐loaded beads have shown better release performance than the IB‐loaded beads. Diffusion parameters were evaluated from the Fickian diffusion theory. Mathematical modeling studies and drug release characteristics through bead matrices were studied by solving Fick's diffusion equation. The results are discussed in terms of drug release patterns and theoretical concentration profiles generated through matrices, considering spherical geometry of the beads. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 5708–5718, 2006     

Distributed star coloring of network for IP traceback

IP traceback using packet marking technique allows direct traceback of attackers. Under this strategy en route routers inject mark into packets which is later used to unambiguously identify the source of an attack. Star coloring approach allows the mark to be reused, thereby saving bit space and at the same time explicitly identify the attacker. As the Internet structure is unknown, in the present work we propose a distributed approach of assigning color (mark) to routers such that the star color template is followed without consideration of the graph structure. An algorithm is proposed to minimize the color assignment conflict. The convergence of the algorithm is also discussed. Simulation study is presented to support the convergence analysis.     

Nuclear power plant sensor fault detection using singular value decomposition-based method

In a nuclear power plant, periodic sensor calibration is necessary to ensure the correctness of measurements. Those sensors which have gone out of calibration can lead to malfunction of the plant, possibly causing a loss in revenue or damage to equipment. Continuous sensor status monitoring is desirable to assure smooth running of the plant and reduce maintenance costs associated with unnecessary manual sensor calibrations. In this paper, a method is proposed to detect and identify any degradation of sensor performance. The validation process consists of two steps: (i) residual generation and (ii) fault detection by residual evaluation. Singular value decomposition (SVD) and Euclidean distance (ED) methods are used to generate the residual and evaluate the fault on the residual space, respectively. This paper claims that SVD-based fault detection method is better than the well-known principal component analysis-based method. The method is validated using data from fast breeder test reactor.     

Optimal directionality compensation in processes with input saturation non-linearities

A notion of process directionality in input-constrained processes is defined, and the class of processes that do not exhibit the process directionality is characterized. An optimal directionality compensator for non-linear processes with actuator saturation non-linearities is presented. Given an unconstrained controller output and the characteristic (decoupling) matrix of the process under consideration, the compensator calculates an optimal constrained (feasible) process input that results in a process response as 'close' as possible to the response of the same process to the unconstrained controller output. The compensator can be used for both linear and non-linear processes, irrespective of the type of controller being used. For processes whose non-singular characteristic matrix can be made diagonal by row or column rearrangements, the optimal directionality compensator is identical to a series of limiters (clippers); this class of processes does not exhibit the process directionality over a short time horizon. The performance of the optimal directionality compensator is shown and compared with those of clipping and direction preservation, by numerical simulation of a linear example under decentralized proportional-integral control, a linear example under model-based control, and a non-linear bioreactor under input-output linearizing control.     

Structure‐Based Design of Novel Human Toll‐like Receptor 8 Agonists

Toll‐like receptor (TLR)‐8 agonists activate adaptive immune responses by inducing robust production of T helper 1‐polarizing cytokines, suggesting that TLR8‐active compounds might be promising candidate vaccine adjuvants. Recently, a C2‐butyl furo[2,3‐c]quinoline was reported with purely TLR8 agonistic activity. This compound was successfully co‐crystallized with the human TLR8 ectodomain, and the co‐crystal structure revealed ligand‐induced reorganization of the binding pocket of TLR8. The loss of a key hydrogen bond between the oxygen atom of the furanyl ring of the agonist and Thr 574 in TLR8 suggested that the furan ring is dispensable. Employing a disconnection strategy, 3‐ and 4‐substituted aminoquinolines were investigated. Focused structure‐based ligand design studies led to the identification of 3‐pentyl‐quinoline‐2‐amine as a novel, structurally simple, and highly potent human TLR8‐specific agonist (EC₅₀=0.2 μM ). Preliminary evaluation of this compound in ex vivo human blood assay systems revealed that it retains prominent cytokine‐inducing activity. Together, these results indicate the suitability of this compound as a novel vaccine adjuvant, warranting further investigation.