Selective determination of urea using urease immobilized on ZnO nanowires

Well-aligned zinc oxide (ZnO) nanowire arrays were fabricated on gold-coated plastic substrates using a low-temperature aqueous chemical growth (ACG) method. The ZnO nanowire arrays with 50–130 nm diameters and ∼1 μm in lengths were used in an enzyme-based urea sensor through immobilization of the enzyme urease that was found to be sensitive to urea concentrations from 0.1 mM to 100 mM. Two linear sensitivity regions were observed when the electrochemical responses (EMF) of the sensors were plotted vs. the logarithmic concentration range of urea from 0.1 mM to 100 mM. The proposed sensor showed a sensitivity of 52.8 mV/decade for 0.1–40 mM urea and a fast response time less than 4 s was achieved with good selectivity, reproducibility and negligible response to common interferents such as ascorbic acid and uric acid, glucose, K⁺ and Na⁺ ions.     

Power quality diagnosis using time frequency analysis and rule based techniques

Diagnosing a power quality disturbance means identifying the type and cause of the disturbance. Fast diagnosis of power quality disturbances is important so as to assist network operators in performing counter measures and implementing suitable power quality mitigation actions. In this study a novel method for performing power quality diagnosis is presented by using the S-transform and rule based classification techniques. The proposed power quality diagnosis method was evaluated for its functionality in detecting the type of short duration voltage disturbances and identifying the cause of the disturbances which may be due to permanent or non permanent faults. Based on the results, this new method has the potential to be used in the existing real time power quality monitoring system in Malaysia to expedite the diagnosis on the recorded voltage disturbances.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.     

Predicting performance in ASEAN banks: an integrated fuzzy MCDM–neural network approach

This paper presents a performance assessment of 88 Association of Southeast Asian Nations banks from 2010 to 2013, using an integrated three‐stage approach on financial criteria that emulates the CAMELS rating system. More precisely, fuzzy analytic hierarchy process is used first to assess the relative weights of a number of criteria related to capital adequacy (C), asset quality (A), management quality (M), earnings (E), liquidity (L), and sensitivity to market risk (S) based on the opinion of 88 Association of Southeast Asian Nations experts. Then, these weights are used as technique for order of preference by similarity to ideal solution inputs to assess their relative efficiency. Lastly, neural networks are combined with technique for order of preference by similarity to ideal solution results to produce a model for banking performance with effective predictive ability. The results reveal that contextual variables have a prominent impact on efficiency. Specifically, parsimony in equity leveraging derived from Islamic finance principles may be the underlying cause in explaining higher efficiency levels.     

A survey on search results diversification techniques

The quantity of information placed on the web has been greater than before and is increasing rapidly day by day. Searching through the huge amount of data and finding the most relevant and useful result set involves searching, ranking, and presenting the results. Most of the users probe into the top few results and neglect the rest. In order to increase user’s satisfaction, the presented result set should not only be relevant to the search topic, but should also present a variety of perspectives, that is, the results should be different from one another. The effectiveness of web search and the satisfaction of users can be enhanced through providing various results of a search query in a certain order of relevance and concern. The technique used to avoid presenting similar, though relevant, results to the user is known as a diversification of search results. This article presents a survey of the approaches used for search result diversification. To this end, this article not only provides a technical survey of existing diversification techniques, but also presents a taxonomy of diversification algorithms with respect to the types of search queries.     

Crystal dislocation in SEM with image processing

Image processing algorithm is implemented to detect the grain boundary of the crystal using (SEM) Scanning Electron Microscopy. This paper presents a method for edge-detection in color image based on Sobel, Canny operator’s algorithm and discrete wavelet transform. The performance of these methods is effective and faster. Filtering is another approach to clear the noise of an image. Scanning Electron Microscopy (SEM) used to inspect semiconductor materials and devices for several decades, continues to increase in importance. Removal of noise is an important step in the image restoration process, but de-noising of the image has remained a challenging problem in recent research associated with image process. De-noising is used to remove the noise from corrupted images, while retaining the edges and other detailed features too are an essential part of de-noising.     

Metal-on-metal hip simulator study of increased wear particle surface area due to 'severe' patient activity

This study investigated changes in metal-on-metal (MOM) hip wear and wear particle characteristics arising from a more aggressive patient activity level compared with normal walking. The test hypothesis was that 'severe'-gait conditions will change wear, wear particle sizes, and morphology owing to a decline in joint lubrication. Four carbon MOM hip bearings 40 mm high were subjected to normal-walking and fast-jogging simulations in an orbital hip joint simulator with 25 per cent alpha-calf serum as a lubricant. Co-Cr-Mo wear particles were extracted using an enzymatic method, and prolate ellipsoid equations were used to estimate particle volume and surface area. Fast-jogging simulations generated a sevenfold increase in volumetric wear, a 33 per cent increase in mean wear particle size, and a threefold increase in the number of larger (needle) particles compared with walking. This resulted in a twentyfold increase in total wear particle surface area per 10(6) cycles compared with walking, thereby confirming our hypothesis. The clinical significance of this result suggests that highly active MOM patients may exhibit greater ion release than less active patients.     

Removal of mercaptans from a gas stream using continuous adsorption-regeneration

The removal of the mercaptan, 1-methyl-1-propanethiol, from aqueous solutions using a non-porous, electrically conducting carbon-based adsorbent (Nyex 1000) was investigated. The adsorption process was found to be rapid (equilibrium capacity achieved within 5 minutes) with low adsorptive capacity (of the order of 0.4 mg g(-1)) when compared with activated carbon. Electrochemical regeneration of the Nyex 1000 in a simple divided electrochemical cell within a sequential batch treatment unit restored 100% of the adsorbent's adsorptive capacity using treatment times as low as 20 minutes by passing a current of 0.5 A. The sorptive characteristics of a Nyex-water slurry were also modelled and investigated both in a bubble column and in a continuous adsorption-regeneration treatment system. It was demonstrated that the continuous removal-destruction system could achieve a step reduction in challenge gas concentration of approximately 75% for a period of 35 minutes with a current of 5 Amps. This was attributed to mass transfer enhanced by a combination of adsorption and chemical reaction with free chlorine species generated in the electrochemical process.