Numerical simulation of concentration over-voltage in a polymer electrolyte fuel cell under low-hydrogen conditions

This article elucidates the effect of low hydrogen concentration fuel gas on polymer electrolyte fuel cell (PEFC) performance, with particular emphasis on the transport of chemical species in the anode separator channel and the electrochemical reactions. A numerical simulation model for PEFCs was developed; the model combined a computational fluid dynamics model for mass transfer in the anode separator and the gas diffusion layer(GDL)as well as a PEFC electrochemical reaction model takinginto account the activation, concentration, and resistance over-voltages. The emphasis in this study is placed on obtaining a basic understanding of how three-dimensional flow and low-hydrogen fuel transport phenomena in the anode separator channelimpactthe electrochemical processes occurring in PEFCs. Comparison of the numerical simulation results with experimental data indicates that the performance degradation in PEFCs is negligible for hydrogen concentrations over 30%, whereas it becomes significant for concentrations below 10%. Furthermore, the numerical simulationresults showthat controlling the fuel supply flow rate stimulates hydrogen transport inthe GDL and the catalyst layer, which consequently enhances PEFC performance under low-hydrogen conditions

Nutritional status and the use of protease inhibitors among HIV-infected children in Klang Valley, Malaysia

This study determined the association between nutritional status and the use of protease inhibitors (PI) containing regimen among HIV-infected children receiving treatment at the referral centres in Klang Valley. A total of 95 children currently on antiretroviral (ARV) therapy, aged one to eighteen years, were recruited using purposive sampling. Demographic data, anthropometric measurements, medical history, were collected using a structured questionnaire. Serum micronutrients levels and lipid profile were also examined using blood samples. Mean age was 8.8 3.9 years and 44.2% were on PI. Age (2=10.351, p = .006), weight-for-age ( 2 = 6.567, p = .010), serum selenium ( 2 = 4.225, p = .040) and HDL-C (2=7.539, p=.006) were significantly associated with the use of PI. Fewer children on PI were deficient in selenium as compared to those not on PI. On the contrary, more children on PI were underweight and had low HDL-C. The use of PI was found to have both positive and negative effects with better selenium level but poorer HDL-C level and weight status

Factors influencing intention to use diminishing partnership home financing

Abstract Purpose – The purpose of this study is to examine the acceptance level of a new Islamic home financing concept, diminishing partnership (DP), by consumers in Malaysia using the theory of reasoned action as the guiding principle. Design/methodology/approach – Cross sectional data were collected through a survey and analysed by means of factor analysis, correlation and regression analysis. Findings – Positive attitude or degree of favorableness towards the DP concept and religious and social influence are jointly responsible in determining the intention to engage in DP though the former commands greater influence. Research limitations/implications – The use of convenience sampling and postgraduate students may not sufficiently capture the variations that could potentially exist in the market. Practical implications – Introducing a leading Islamic finance product requires more than just a mere Shariah Board approval as customers are far more critical than has often been assumed. Demand for the home diminishing product has clearly been substantiated. It is a challenge for bankers to devise products that use the spirit of the concept very closely without compromising its salient features. Marketing strategies to consumers with different religious backgrounds have also been identified. Originality/value – This study examines customers’ acceptance level of a new Islamic home financing concept among multi ethnic/religion consumers with growing interest and consciousness about Islamic financial products

A review of medical error taxonomies: a human factors perspective

Although a large number of medical error taxonomies have been published, there is little evidence to suggest that these taxonomies have been systematically compared. This paper describes a study comparing 26 medical error taxonomies using a human factors perspective. The taxonomies were examined to determine if they classified systemic factors of medical errors and if they utilized theoretical error concepts in their classifications. Scope of classification was also examined. It was found that two-thirds of the taxonomies classified systemic factors of medical errors and only a third utilized theoretical error concepts. Medical error taxonomies based on theoretical error concepts were more likely to be generic in applicability and also more likely to classify systemic factors and psychological error mechanisms of medical errors. In addition to terminology, the medical error taxonomies also varied in terms of domain-specificity, granularity, and developmental process. Different medical error taxonomies provide different information; how these differences affect medical error management needs to be investigated

A Review on Carbon Fiber Reinforced Polymer as Wrapping Structures For Pipeline

To maintain the continuous product flow in the pipe, the durability of the pipe structure is achieved through pipe insulation. The composite material will be used as the main material, since it may have the combined characteristics of the constituents or have substantially different properties than the individual constituents. Replacing the damaged pipe with a new one will not only consume high cost but also will create a complication for product flow. As to alleviate such situations this research focusses on using the carbon fiber as the wrapping material. To identify the suitable design and optimization of laminated carbon fiber on piping systems, the defect, leakage and imperfection on pipe should be identified. The effect of different laminate optimization through Classical Laminate Theory CLT and experimental data too need to be considered as it changes the mechanical properties of the composite material. The microstructure of the composite too will be validated as an extra reference for the theoretical and experimental data on its effect in the microstructure after the loadin

A Review on Carbon Fiber Reinforced Polymer as Wrapping Structures For Pipeline

To maintain the continuous product flow in the pipe, the durability of the pipe structure is achieved through pipe insulation. The composite material will be used as the main material, since it may have the combined characteristics of the constituents or have substantially different properties than the individual constituents. Replacing the damaged pipe with a new one will not only consume high cost but also will create a complication for product flow. As to alleviate such situations this research focusses on using the carbon fiber as the wrapping material. To identify the suitable design and optimization of laminated carbon fiber on piping systems, the defect, leakage and imperfection on pipe should be identified. The effect of different laminate optimization through Classical Laminate Theory CLT and experimental data too need to be considered as it changes the mechanical properties of the composite material. The microstructure of the composite too will be validated as an extra reference for the theoretical and experimental data on its effect in the microstructure after the loadin

Adaptive Neuro-Fuzzy Inference System for diagnosis risk in dengue patients

Dengue disease is considered as one of the life threatening disease that has no vaccine to reduce its case fatality. In clinical practice the case fatality of dengue disease can be reduced to 1 if the dengue patients are hospitalized and prompt intravenous fluid therapy is administrated. Yet, it has been a great challenge to the physicians to decide whether to hospitalize the dengue patients or not due to the overlapping of the medical diagnosis criteria of the disease. Beside that physicians cannot decide to admit all patients because this will have major impact on health care cost saving due to the huge incident of dengue disease in the country. Even if the physicians managed to identify the critical cases to be hospitalized, most of the tools that have been used for monitoring those patients are invasive. Therefore, this study was conducted to develop a non-invasive accurate diagnostic system that can assist the physicians to diagnose the risk in dengue patients and therefore attain the correct decision. Bioelectrical Impedance Analysis measurements, Symptoms and Signs presented with dengue patients were incorporated with Adaptive Neuro-Fuzzy Inference System (ANFIS) to construct two diagnostic models. The first model was developed by systematically optimizing the initial ANFIS model parameters while the second model was developed by employing the subtractive clustering algorithm to optimize the initial ANFIS model parameters. The results showed that the ANFIS model based on subtractive clustering technique has superior performance compared with the other model. Overall diagnostic accuracy of the proposed system is 86.13 with 87.5 sensitivity and 86.7 specificity. © 2011 Elsevier Ltd. All rights reserved

Neural network diagnostic system for dengue patients risk classification

With the dramatic increase of the worldwide threat of dengue disease, it has been very crucial to correctly diagnose the dengue patients in order to decrease the disease severity. However, it has been a great challenge for the physicians to identify the level of risk in dengue patients due to overlapping of the medical classification criteria. Therefore, this study aims to construct a noninvasive diagnostic system to assist the physicians for classifying the risk in dengue patients. Systematic producers have been followed to develop the system. Firstly, the assessment of the significant predictors associated with the level of risk in dengue patients was carried out utilizing the statistical analyses technique. Secondly, Multilayer perceptron neural network models trained via Levenberg-Marquardt and Scaled Conjugate Gradient algorithms was employed for constructing the diagnostic system. Finally, precise tuning for the models' parameters was conducted in order to achieve the optimal performance. As a result, 9 noninvasive predictors were found to be significantly associated with the level of risk in dengue patients. By employing those predictors, 75 prediction accuracy has been achieved for classifying the risk in dengue patients using Scaled Conjugate Gradient algorithm while 70.7 prediction accuracy were achieved by using Levenberg-Marquardt algorithm. © Springer Science+Business Media, LLC 2010

The Use of GPR in Delineating an Iron Sand Boundary and the Determination of Its Electromagnetic Wave Velocity: A Case Study in Jepara, Central Java

 Exploring the vertical extent of iron sand deposit is challenging as conventional geophysical methods (electrical resistivity, geomagnetic, and seismic refraction) are inappropriate and unsuccessful in delineating the iron sand deposit from the bedrock. Ground-penetrating radar (GPR) offers a solution to the above problem as radar is not affected negatively by the physical properties of iron sand. In the year 2003, a RAMAC's GPR survey was carried out in the coast of Bayuran in the Regency of Jepara, Central Java to map the distribution of sub-bottom iron sand. The sand is highly magnetic. The survey used 100 MHz antennas. The survey is also complimented by a novel method in determining the electromagnetic (EM) wave velocity of iron sand. Combination of reflection profiling and CMP sounding was deployed. Results of CMP sounding were processed using CMP-semblance analysis that produces the RMS velocity in velocity-time spectra. The RMS velocity is then converted to interval velocity using Dix's formula and is found to be about 135 mm/ns. Meanwhile, combination of magnetic susceptibility, relative permittivity, and dissipation factors produces radiowaves velocity of iron sand as a function of frequency. The velocities of radiowaves estimated from laboratory match that estimated from CMP analysis