Manufacturing Of Robust Natural Fiber Preforms Utilizing Bacterial Cellulose as Binder

We present a novel method of manufacturing rigid and robust short natural fiber preforms using a papermaking process. Bacterial cellulose acts simultaneously as the binder for the loose fibers and provides rigidity to the fiber preforms. These preforms can be infused with a resin to produce truly green hierarchical composites

Native small airways secrete bicarbonate.

Since the discovery of Cl(-) impermeability in cystic fibrosis (CF) and the cloning of the responsible channel, CF pathology has been widely attributed to a defect in epithelial Cl(-) transport. However, loss of bicarbonate (HCO3(-)) transport also plays a major, possibly more critical role in CF pathogenesis. Even though HCO3(-) transport is severely affected in the native pancreas, liver, and intestines in CF, we know very little about HCO3(-) secretion in small airways, the principle site of morbidity in CF. We used a novel, mini-Ussing chamber system to investigate the properties of HCO3(-) transport in native porcine small airways (∼ 1 mm φ). We assayed HCO3(-) transport across small airway epithelia as reflected by the transepithelial voltage, conductance, and equivalent short-circuit current with bilateral 25-mM HCO3(-) plus 125-mM NaGlu Ringer's solution in the presence of luminal amiloride (10 μM). Under these conditions, because no major transportable anions other than HCO3(-) were present, we took the equivalent short-circuit current to be a direct measure of active HCO3(-) secretion. Applying selective agonists and inhibitors, we show constitutive HCO3(-) secretion in small airways, which can be stimulated significantly by β-adrenergic- (cAMP) and purinergic (Ca(2+)) -mediated agonists, independently. These results indicate that two separate components for HCO3(-) secretion, likely via CFTR- and calcium-activated chloride channel-dependent processes, are physiologically regulated for likely roles in mucus clearance and antimicrobial innate defenses of small airways

Concurrent absorption and secretion of airway surface liquids and bicarbonate secretion in human bronchioles.

Although small airways account for the largest fraction of the total conducting airway surfaces, the epithelial fluid and electrolyte transport in small, native airway epithelia has not been well characterized. Investigations have been limited, no doubt, by the complex tissue architecture as well as by its inaccessibility, small dimensions, and lack of applicable assays, especially in human tissues. To better understand how the critically thin layer of airway surface liquid (ASL) is maintained, we applied a "capillary"-Ussing chamber (area ≈1 mm2) to measure ion transport properties of bronchioles with diameters of ~2 mm isolated from resected specimens of excised human lungs. We found that the small human airway, constitutively and concurrently, secretes and absorbs fluid as observed in porcine small airways (50). We found that the human bronchiolar epithelium is also highly anion selective and constitutively secretes bicarbonate ( HCO3- ), which can be enhanced pharmacologically by cAMP as well as Ca2+-mediated agonists. Concurrent secretion and absorption of surface liquid along with HCO3- secretion help explain how the delicate volume of the fluid lining the human small airway is physiologically buffered and maintained in a steady state that avoids desiccating or flooding the small airway with ASL

Virtual Collaborative R&D Teams in Malaysia Manufacturing SMEs

This paper presents the results of empirical research conducted during March to September 2009. The study focused on the influence of virtual research and development (R&D) teams within Malaysian manufacturing small and medium sized enterprises (SMEs). The specific objective of the study is better understanding of the application of collaborative technologies in business, to find the effective factors to assist SMEs to remain competitive in the future. The paper stresses to find an answer for a question “Is there any relationship between company size, Internet connection facility and virtuality?”. The survey data shows SMEs are now technologically capable of performing the virtual collaborative team, but the infrastructure usage is less. SMEs now have the necessary technology to begin the implementation process of collaboration tools to reduce research and development (R&D) time, costs and increase productivity. So, the manager of R&D should take the potentials of virtual teams into account

Multistrategy Self-Organizing Map Learning for Classification Problems

Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test

Biostabilised icosahedral gold nanoparticles: synthesis, cyclic voltammetric studies and catalytic activity towards 4-nitrophenol reduction

A green and cost-effective biosynthetic approach for the preparation of icosahedral gold nanoparticles (AuNPs) using an aqueous leaf extract of Polygonum minus as reducing and stabilising factor is described. The reduction of Au3+ ions to elemental Au rapidly occurred and is completed within 20 minutes at room temperature. The size of the nanoparticles is highly sensitive to the AuCl4 −/leaf extract concentration ratio and pH. Transmission electron microscopy and X-ray diffraction data indicated that the nanoparticles were in a crystalline shape (face-centred cubic), mostly icosahedral and nearly monodispersed with an average size of 23 nm. Cyclic voltammetric studies suggested that flavonoids, such as quercetin and myricetin present in the leaf extract had a tendency to donate electrons to Au3+ ions and the formation of elemental Au was possible due to the transfer of electrons from these flavonoids to Au3+ ions. Infrared absorption of the AuNPs and the leaf extract revealed that the oxidised (quinone) form of quercetin and myricetin were presumably the main stabilising agents in the formation of stable nanoparticles. The present biosynthesis of AuNPs was simple, rapid, cost-effective and environmentally friendly. The newly prepared biostabilised icosahedral AuNPs show good catalytic activity in the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP)

Relevant test set using feature selection algorithm for early detection of dyslexia

The objective of feature selection is to find the most relevant features for classification. Thus, the dimensionality of the information will be reduced and may improve classification’s accuracy. This paper proposed a minimum set of relevant questions that can be used for early detection of dyslexia. In this research, we investigated and proposed a feature selection algorithm that is correlation based feature selection (CFS) and generate classification modelsbased on five different classifiers namely Bayes Net, Simple Logistic and Decision Table. This paper used dataset collected from a computer based screening test developed consists of 50 questions. The result shows that the new set of question suggested from the feature selection algorithm was significantly achieved 100% accuracy of classification and less time was taken for conducting screening test among students.Keywords: feature selection; dyslexic children; computer based screening test

Embedded Scale United Moment Invariant for Identification of Handwriting Individuality

Past few years, a lot of research on moment functions have been explored in pattern recognition. Several new techniques have been investigated to improve conventional regular moment by proposing the scaling factor of geometrical function. In this paper, integrated scaling formulations of Aspect Invariant Moment and Higher Order Scaling Invariant with United Moment Invariant are presented in Writer Identification to seek the invarianceness of authorship or individuality of handwriting perseverance. Mathematical proving and results of computer simulations are included to verify the validity of the proposed technique in identifying eccentricity of the author in Writer Identification

DISCRETIZATION OF INTEGRATED MOMENT INVARIANTS FOR WRITER IDENTIFICATION

Conservative regular moments have been proven to exhibit some shortcomings in the original formulations of moment functions in terms of scaling factor. Hence, an incorporated scaling factor of geometric functions into United Moment Invariant function is proposed for mining the feature of unconstrained words. Subsequently, the discrete proposed features undertake discretization procedure prior to classification for better feature representation and splendid classification accuracy. Collectively, discrete values are finite intervals in a continuous spectrum of values and well known to play important roles in data mining and knowledge discovery. Many induction algorithms found in the literature requires that training data contains only discrete features and some works better on discretized data; in particular rule based approaches like rough sets. Hence, in this study, an integrated scaling formulation of Aspect Scaling Invariant is presented in Writer Identification to hunt for the individuality perseverance. Successive exploration is executed to investigate for the suitability of discretization techniques in probing the issues of writer authorship. Mathematical proving and results of computer simulations are embraced to attest the feasibility of the proposed technique in Writer Identification. The results disclose that the proposed discretized invariants reveal 99% accuracy of classification by using 3520 training data and 880 testing data