An Octagonal Shaped Monopole Antenna for UWB Applications with Band Notch Characteristics

Wireless Personal Communications - This article presents a microstrip-fed octagonal shaped monopole antenna with dual band notched characteristics for UWB applications. Partial ground plane has...     

Three-dimensional anatomical model-based segmentation of MR brainimages through principal axes registration

Model-based segmentation and analysis of brain images depends on anatomical knowledge which may be derived from conventional atlases. Classical anatomical atlases are based on the rigid spatial distribution provided by a single cadaver. Their use to segment internal anatomical brain structures in a high-resolution MR brain image does not provide any knowledge about the subject variability, and therefore they are not very efficient in analysis. The authors present a method to develop three-dimensional computerized composite models of brain structures to build a computerized anatomical atlas. The composite models are developed using the real MR brain images of human subjects which are registered through the principal axes transformation. The composite models provide probabilistic spatial distributions, which represent the variability of brain structures and can be easily updated for additional subjects. The authors demonstrate the use of such a composite model of ventricular structure to help segmentation of the ventricles and cerebrospinal fluid of MR brain images. Here, a composite model of ventricles using a set of 22 human subjects is developed and used in a model-based segmentation of ventricles, sulci, and white matter lesions. To illustrate the clinical usefulness, automatic volumetric measurements on ventricular size and cortical atrophy for an additional eight alcoholics and 10 normal subjects were made. The volumetric quantitative results indicated regional brain atrophy in chronic alcoholics     

Thin conducting polypyrrole film on insulating surface and its applications

An electrically conductive plastic material was obtained by the polymerization of pyrrole on insulating polymeric materials and nylon cloth impregnated with the oxidant by vapour phase technique, resulting in a uniform, smooth and adherent coating of conducting polymer having a surface resistance ranging from 200 Ω/□ to 20 kΩ/□, which makes it suitable for applications as an antistatic material.     

The metabolic anatomy of tremor in Parkinson's disease

OBJECTIVE: To identify regional metabolic brain networks related specifically to the presence of tremor in PD. BACKGROUND: The pathophysiology of parkinsonian tremor is unknown. Because tremor in PD occurs mainly in repose, we used resting state PET with 18F-fluorodeoxyglucose (FDG) to identify specific metabolic brain networks associated with this clinical manifestation. METHODS: We studied two discrete groups of eight PD patients with and without tremor using FDG/PET. Both patient groups were matched for gender, age, and Unified Parkinson Disease Rating Scale ratings for akinesia and rigidity. Ten normal volunteer subjects served as controls. RESULTS: Network analysis with the Scaled Subprofile Model was performed in two steps. 1) We computed the expression of the PD-related pattern (PDRP) identified by us previously in each of the PD patients and control subjects. Although PDRP subject scores were abnormally elevated in the combined PD cohort (p < 0.005), these values did not differ in the PD patient groups with and without tremor (p = 0.36). 2) We used SSM to analyze the data from the combined PD cohort comprising both patient groups. We found that PD patients with tremor were characterized by increased expression of a metabolic network comprising the thalamus, pons, and premotor cortical regions. Subject scores for this pattern were elevated in the tremor group compared with the atremulous patient group and the normal control group (p < 0.005). CONCLUSIONS: The findings suggest that PD patients with tremor are characterized by distinct increases in the functional activity of thalamo-motor cortical projections. Modulation of this functional anatomic pathway is likely to be the mechanism for successful interventions for the relief of parkinsonian tremor.     

Hexagonal (superlattice) form of Ga2Te3

Gallium telluride (Ga₂Te₃) was synthesized at different temperatures (850 to 460° C) using different cooling rates. Materials synthesized at higher temperatures (including quenched materials from the melt) always yielded zinc-blende lattice with well resolved _{1 2} doublet X-ray powder diffraction lines. In the material synthesized at lower temperature ( 460°C), we obtained additional (superlattice) lines as reported by Newman and Cundall [4]. It was possible to index these reflections not only on an orthorhombic unit cell (a=0.417, b=2.360, c=1.252 nm) but also on cubic (a=1.7678 nm) and hexagonal (a=0.832, c=3.065 nm) unit cells. To us, the hexagonal cell appears to be more realistic. If sufficient time is given to reach equilibrium, the whole of the zinc-blende form of Ga₂Te₃ is transformed to the hexagonal form. It has been further observed that conversion of the hexagonal into the cubic form and vice versa can be brought about by heating the material at temperatures greater or less than 460° C, respectively. Lastly, the zinc-blende phase of Ga₂Te₃ is metastable and slowly transforms to hexagonal form at room temperature.     

Structure–property relationships for sulfonated poly(butylene terephthalate)

Structure–property relationships have been developed for sulfonated poly(butylene terephthalate) copolymers. The compositional variables investigated were sulfonate content, molecular weight, and polymer endgroup composition, and the fundamental polymer properties evaluated were melt viscosity, crystallization kinetics, and impact strength. It was found that all compositional variables significantly affect all of the polymer properties of interest. The most interesting effect is the influence of polymer endgroup composition on polymer properties. The trends indicate that the carboxylic acid endgroups form intermolecular interactions with sodium sulfonate groups, resulting in a decrease in the strength of intermolecular ionic interactions between sodium sulfonate groups. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 4662–4771, 2006     

Synthesis and characterization of poly(o-ethoxyaniline): A processable conducting polymer

The synergic effect of the substituentlike ethoxy group on the electronic properties of conducting polyaniline was investigated. The presence of substituents affects not only the electrochemical polymerization window but also brings about changes in optical and electronic properties of the parent polymer polyaniline. The study indicates that electrochemical polymerization of (o-ethoxyaniline) yields a conducting polymer that shows a multiple color transition (yellow → green) on switching the potential between the reduced and oxidized states with an electrochromic response time of 40 ms in addition to its solubility in dimethyl sulfoxide, N-methyl pyrrolidinone, etc. However, the chemical polymerization of the monomer yields a crimson red polymer that is less conducting but has solubility in ethanol/methanol. Evaluation of this alcohol soluble polymer as a corrosion inhibitor for iron in acidic medium shows that it offers corrosion inhibition efficiency of 90%. © 1995 John Wiley & Sons, Inc.     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Analysis of mammographic microcalcifications using gray-level image structure features

At present, mammography associated with clinical breast examination and breast self-examination is the only effective and viable method for mass breast screening. The presence of microcalcifications is one of the primary signs of breast cancer. It is, difficult however, to distinguish between benign and malignant microcalcifications associated with breast cancer. Here, the authors define a set of image structure features for classification of malignancy. Two categories of correlated gray-level image structure features are defined for classification of "difficult-to-diagnose" cases. The first category of features includes second-order histogram statistics-based features representing the global texture and the wavelet decomposition-based features representing the local texture of the microcalcification area of interest. The second category of features represents the first-order gray-level histogram-based statistics of the segmented microcalcification regions and the size, number, and distance features of the segmented microcalcification cluster. Various features in each category were correlated with the biopsy examination results of 191 "difficult-to-diagnose" cases for selection of the best set of features representing the complete gray-level image structure information. The selection of the best features was performed using the multivariate cluster analysis as well as a genetic algorithm (GA)-based search method. The selected features were used for classification using backpropagation neural network and parameteric statistical classifiers. Receiver operating characteristic (ROC) analysis was performed to compare the neural network-based classification with linear and k-nearest neighbor (KNN) classifiers. The neural network classifier yielded better results using the combined set of features selected through the GA-based search method for classification of "difficult-to-diagnose" microcalcifications.     

Examining knowledge contribution from the perspective of an online identity in blogging communities

Knowledge contribution is one of the essential factors behind the success of blogging communities (BCs). This research studies knowledge contribution behavior in a BC from the perspective of knowledge contributors and their characteristics using the lens of social identity theory. Social identity theory asserts that individuals are fundamentally motivated to present or communicate their identities in everyday social life through behavior. A similar line of reasoning can be used to argue that members of a BC would also be motivated to communicate their online identities through their behavior, that is, through knowledge contribution in the BC. Specifically, this study conceptualized the online identity and examined the effects of its personal (online kindness, online social skills, and online creativity) and social aspects (BC involvement) on knowledge contribution. The data was collected using an online survey from the members of Cyworld, a popular BC in South Korea and a few other countries (members from South Korea were included in this study). The results indicate that both the personal and social aspects of online identity and their interactions significantly influenced knowledge contribution. Based on the findings, this study offers suggestions to organizers of BCs to enhance the knowledge contribution from their members.