Automatic Segmentation and Classification of Multiple Sclerosis in Multichannel MRI

We introduce a multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in automatically detecting multiple sclerosis (MS) lesions in 3-D multichannel magnetic resonance (MR) images. Our method uses segmentation to obtain a hierarchical decomposition of a multichannel, anisotropic MR scans. It then produces a rich set of features describing the segments in terms of intensity, shape, location, neighborhood relations, and anatomical context. These features are then fed into a decision forest classifier, trained with data labeled by experts, enabling the detection of lesions at all scales. Unlike common approaches that use voxel-by-voxel analysis, our system can utilize regional properties that are often important for characterizing abnormal brain structures. We provide experiments on two types of real MR images: a multichannel proton-density-, T2-, and T1-weighted dataset of 25 MS patients and a single-channel fluid attenuated inversion recovery (FLAIR) dataset of 16 MS patients. Comparing our results with lesion delineation by a human expert and with previously extensively validated results shows the promise of the approach.     

Enhanced backstepping sliding mode controller for motion tracking of a nonlinear 2-DOF piezo-actuated micromanipulation system

Microsystem Technologies - In this paper a robust backstepping sliding mode controller is developed for tracking control of 2-DOF piezo-actuated micromanipulation system. The control approach is...     

Recognition Using Region Correspondences

Recognition systems attempt to recover information about the identity of observed objects and their location in the environment. A fundamental problem in recognition is pose estimation. This is the problem of using a correspondence between some portions of an object model and some portions of an image to determine whether the image contains an instance of the object, and, in case it does, to determine the transformation that relates the model to the image. The current approaches to this problem are divided into methods that use global properties of the object (e.g., centroid and moments of inertia) and methods that use local properties of the object (e.g., corners and line segments). Global properties are sensitive to occlusion and, specifically, to self occlusion. Local properties are difficult to locate reliably, and their matching involves intensive computation.We present a novel method for recognition that uses region information. In our approach the model and the image are divided into regions. Given a match between subsets of regions (without any explicit correspondence between different pieces of the regions) the alignment transformation is computed. The method applies to planar objects under similarity, affine, and projective transformations and to projections of 3-D objects undergoing affine and projective transformations. The new approach combines many of the advantages of the previous two approaches, while avoiding some of their pitfalls. Like the global methods, our approach makes use of region information that reflects the true shape of the object. But like local methods, our approach can handle occlusion.     

Alcoholysis of palm oil mid-fraction by lipase from Rhizopus rhizopodiformis

A mycelial lipase from Rhizopus rhizopodiformis was prepared in fragment form. The lipase was examined to catalyze the alcoholysis of palm oil mid-fraction (PMF) in organic solvents. High percentage conversions of PMF to alkyl esters were achieved when methanol or propanol was used as acyl acceptor. Of the two most prevalent fatty acids in PMF, palmitic acid seemed to be preferred over oleic acid in the formation of methyl and propyl esters. The optimal ratio of oil to methanol in the alcoholysis reaction is 1 to 2 moles. The lipase exhibited high alcoholysis activities in nonpolar solvents (log P>2), such as hexane, benzene, toluene, and heptane. The enzyme showed exceptionally high thermostability.     

Enhanced mechanical flexibility and performance of sodium alginate polymer electrolyte bio‐membrane for application in direct methanol fuel cell

A new membrane was synthesized containing pure alginate, crosslinking agent (CaCl₂), and plasticizer (glycerol). Characterization studies of the membrane were applied to determine the characteristics and morphology using field emission scanning electron microscope, EDX, FTIR, XRD, and atomic force microscopy analysis. The half‐cell performance test of the membrane was verified by several tests, including proton conductivity and methanol permeability. The best membrane had high proton conductivity (10.1 × 10^?3 S cm^?1) and very low methanol permeability (1.984 × 10^?7 cm² s^?1), which consequently resulted in very high selectivity (5.0907 × 10⁴ Ss cm^?3). Glycerol had a positive modification and good influence on the alginate characteristics. Furthermore, the poor mechanical properties of the alginate biopolymer were enhanced by calcium chloride and glycerol inside the polymer. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46666.     

Improved catalytic activity by catalase immobilization using γ‐cyclodextrin and electrospun PCL nanofibers

Nanofibrous structures are promising for biocatalyst immobilization due to their large surface area which facilitates the enzyme attachment, stability, ease of separation, and fine porous structure. There is limited research available on the change in enzyme activity following interaction with cyclodextrin. In this study, catalase enzyme was immobilized into nanofibrous structures by various techniques, with and without γ‐CD addition, and the enzymatic activity of catalase was evaluated. In addition, catalase‐γ‐CD complex containing PEO polymer solution was electrospun in between PCL nanofibrous layers as a newly developed technique. The enzyme immobilized nanofibrous structures were characterized by SEM, XRD, and FT‐IR analysis methods. Among all the activity tests, best enzyme activity was recorded with catalase‐γ‐CD physical mixture encapsulated PCL nanofibrous layers. Moreover, the test results indicated that the use of cyclodextrin in immobilization process considerably improves the catalytic activity of the enzyme. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44404.     

Solid-phase extraction of Mn(II), Co(II), Ni(II), Cu(II), Cd(II) and Pb(II) ions from environmental samples by flame atomic absorption spectrometry (FAAS)

A new method using a column packed with Amberlite XAD-2010 resin as a solid-phase extractant has been developed for the multi-element preconcentration of Mn(II), Co(II), Ni(II), Cu(II), Cd(II), and Pb(II) ions based on their complex formation with the sodium diethyldithiocarbamate (Na-DDTC) prior to flame atomic absorption spectrometric (FAAS) determinations. Metal complexes sorbed on the resin were eluted by 1 mol L(-1) HNO3 in acetone. Effects of the analytical conditions over the preconcentration yields of the metal ions, such as pH, quantity of Na-DDTC, eluent type, sample volume and flow rate, foreign ions etc. have been investigated. The limits of detection (LOD) of the analytes were found in the range 0.08-0.26 microg L(-1). The method was validated by analyzing three certified reference materials. The method has been applied for the determination of trace elements in some environmental samples.     

Visual Homing: Surfing on the Epipoles

We introduce a novel method for visual homing. Using this method a robot can be sent to desired positions and orientations in 3D space specified by single images taken from these positions. Our method is based on recovering the epipolar geometry relating the current image taken by the robot and the target image. Using the epipolar geometry, most of the parameters which specify the differences in position and orientation of the camera between the two images are recovered. However, since not all of the parameters can be recovered from two images, we have developed specific methods to bypass these missing parameters and resolve the ambiguities that exist. We present two homing algorithms for two standard projection models, weak and full perspective.Our method determines the path of the robot on-line, the starting position of the robot is relatively not constrained, and a 3D model of the environment is not required. The method is almost entirely memoryless, in the sense that at every step the path to the target position is determined independently of the previous path taken by the robot. Because of this property the robot may be able, while moving toward the target, to perform auxiliary tasks or to avoid obstacles, without this impairing its ability to eventually reach the target position. We have performed simulations and real experiments which demonstrate the robustness of the method and that the algorithms always converge to the target pose.     

When is it Possible to Identify 3D Objects From Single Images Using Class Constraints?

One approach to recognizing objects seen from arbitrary viewpoint is by extracting invariant properties of the objects from single images. Such properties are found in images of 3D objects only when the objects are constrained to belong to certain classes (e.g., bilaterally symmetric objects). Existing studies that follow this approach propose how to compute invariant representations for a handful of classes of objects. A fundamental question regarding the invariance approach is whether it can be applied to a wide range of classes. To answer this question it is essential to study the set of classes for which invariance exists. This paper introduces a new method for determining the existence of invariant functions for classes of objects together with the set of images from which these invariants can be computed. We develop algebraic tests that determine whether the objects in a given class can be identified from single images. These tests apply to classes of objects undergoing affine projection. In addition, these tests allow us to determine the set of views of the objects which are degenerate. We apply these tests to several classes of objects and determine which of them is identifiable and which of their views are degenerate.