Regulatory requirements for nuclear power plant site selection in Malaysia-a review.

Malaysia has initiated a range of pre-project activities in preparation for its planned nuclear power programme. Clearly one of the first steps is the selection of sites that are deemed suitable for the construction and operation of a nuclear power plant. Here we outline the Malaysian regulatory requirements for nuclear power plant site selection, emphasizing details of the selection procedures and site characteristics needed, with a clear focus on radiation safety and radiation protection in respect of the site surroundings. The Malaysia Atomic Energy Licensing Board (AELB) site selection guidelines are in accord with those provided in International Atomic Energy Agency (IAEA) and United Stated Nuclear Regulatory Commission (USNRC) documents. To enhance the suitability criteria during selection, as well as to assist in the final decision making process, possible assessments using the site selection characteristics and information are proposed.

Landfill area estimation based on integrated waste disposal options and solid waste forecasting using modified ANFIS model.

Solid waste prediction is crucial for sustainable solid waste management. The collection of accurate waste data records is challenging in developing countries. Solid waste generation is usually correlated with economic, demographic and social factors. However, these factors are not constant due to population and economic growth. The objective of this research is to minimize the land requirements for solid waste disposal for implementation of the Malaysian vision of waste disposal options. This goal has been previously achieved by integrating the solid waste forecasting model, waste composition and the Malaysian vision. The modified adaptive neural fuzzy inference system (MANFIS) was employed to develop a solid waste prediction model and search for the optimum input factors. The performance of the model was evaluated using the root mean square error (RMSE) and the coefficient of determination (R(2)). The model validation results are as follows: RMSE for training=0.2678, RMSE for testing=3.9860 and R(2)=0.99. Implementation of the Malaysian vision for waste disposal options can minimize the land requirements for waste disposal by up to 43%.

Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model.

Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management.

Predicting terrestrial gamma dose rate based on geological and soil information: case study of Perak state, Malaysia.

An extensive terrestrial gamma radiation dose (TGRD) rate survey has been conducted in Perak State, Peninsular Malaysia. The survey has been carried out taking into account geological and soil information, involving 2930 in situ surveys. Based on geological and soil information collected during TGRD rate measurements, TGRD rates have been predicted in Perak State using a statistical regression analysis which would be helpful to focus surveys in areas that are difficult to access. An equation was formulated according to a linear relationship between TGRD rates, geological contexts and soil types. The comparison of in situ measurements and predicted TGRD dose rates was tabulated and showed good agreement with the linear regression equation. The TGRD rates in the study area ranged from 38 nGy h(-1) to 1039 nGy h(-1) with a mean value of 224 ± 138 nGy h(-1). This value is higher than the world average as reported in UNSCEAR 2000. The TGRD rates contribute an average dose rate of 1.37 mSv per year. An isodose map for the study area was developed using a Kriging method based on predicted and in situ TGRD rate values.

Prediction of municipal solid waste generation using nonlinear autoregressive network.

Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.

Solid waste forecasting using modified ANFIS modeling.

UNLABELLED: Solid waste prediction is crucial for sustainable solid waste management. Usually, accurate waste generation record is challenge in developing countries which complicates the modelling process. Solid waste generation is related to demographic, economic, and social factors. However, these factors are highly varied due to population and economy growths. The objective of this research is to determine the most influencing demographic and economic factors that affect solid waste generation using systematic approach, and then develop a model to forecast solid waste generation using a modified Adaptive Neural Inference System (MANFIS). The model evaluation was performed using Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and the coefficient of determination (R²). The results show that the best input variables are people age groups 0-14, 15-64, and people above 65 years, and the best model structure is 3 triangular fuzzy membership functions and 27 fuzzy rules. The model has been validated using testing data and the resulted training RMSE, MAE and R² were 0.2678, 0.045 and 0.99, respectively, while for testing phase RMSE =3.986, MAE = 0.673 and R² = 0.98. IMPLICATIONS: To date, a few attempts have been made to predict the annual solid waste generation in developing countries. This paper presents modeling of annual solid waste generation using Modified ANFIS, it is a systematic approach to search for the most influencing factors and then modify the ANFIS structure to simplify the model. The proposed method can be used to forecast the waste generation in such developing countries where accurate reliable data is not always available. Moreover, annual solid waste prediction is essential for sustainable planning.

Preparation of highly porous binderless activated carbon electrodes from fibres of oil palm empty fruit bunches for application in supercapacitors.

Fibres from oil palm empty fruit bunches, generated in large quantities by palm oil mills, were processed into self-adhesive carbon grains (SACG). Untreated and KOH-treated SACG were converted without binder into green monolith prior to N2-carbonisation and CO2-activation to produce highly porous binderless carbon monolith electrodes for supercapacitor applications. Characterisation of the pore structure of the electrodes revealed a significant advantage from combining the chemical and physical activation processes. The electrochemical measurements of the supercapacitor cells fabricated using these electrodes, using cyclic voltammetry, electrochemical impedance spectroscopy and galvanostatic charge-discharge techniques consistently found that approximately 3h of activation time, achieved via a multi-step heating profile, produced electrodes with a high surface area of 1704m(2)g(-1) and a total pore volume of 0.889cm(3)g(-1), corresponding to high values for the specific capacitance, specific energy and specific power of 150Fg(-1), 4.297Whkg(-1) and 173Wkg(-1), respectively.

Pregnancies in renal transplant recipients--with a focus on the maternal issues.

One hundred and thirteen pregnancies in 73 women who received a renal transplant were studied. The duration between the transplant operation and the conception averaged 19.9 months with a range of I month to 72 months. The mean age was 28 years. The majority (50 recipients had one pregnancy each, but two women had 5 children each and one had seven children). Only 12 (11.5%) out of the 113 pregnancies ended up with spontaneous abortions. The maternal medical problems encountered were reversible rejection in 11%, hypertension in 43%, UTI in 17% and gestational diabetes in 21%. It was noted that there was high incidence of preterm delivery in 64% of the pregnancies Caesarian section was required in 72% % of the cases. In conclusion we observed a high prevalence of successful pregnancies with no adverse effect on the allograft function and excellent fetal outcome (which is described in a separate paper focusing on the fetal outcome).

Pregnancies in renal transplant recipients--with a focus on babies.

We studied 113 pregnancies in 72 renal transplant recipients. The mean duration between the transplant operation and the first pregnancies was 19.9 months (1-72). This paper focuses on the findings in babies and their outcome. The male babies were 34% of the total. 28% of the babies were delivered vaginally and 72% by Caesarian section. It was noted that there was high incidence of preterm delivery in 64% of the pregnancies. The birth weights were also less than that observed in the general population. 84% was under 50th percentile for weight with 19% being under the 10th percentile. (Saudi growth chart, KACST) The mean hospital stay was 18 days (2-44). The Apgar score was less than 7 in only 10% of the cases and 10 in 50.9%. The incidence of congenital defects was low and no different than the general population (we encountered only 4 cases with minor defects). Despite exposure to cyclosporine throughout the pregnancy and having reduced Nephron mass by virtue of their low birth weight we could not find any glomerular or tubular defects, hypertension or prorienuria in 41 children with a mean age of 52 months. We advised against breast feeding in view of the presence of cyclosporine in the mothers' milk.

Henna as an antimicrobial agent.

Synopsis Powdered henna leaf as used as a cosmetic in the Middle East has been tested for its antimicrobial qualities against a series of common organisms. It has been shown to be effective against bacteria and some common fungi, but to have only limited potency against Candida albicans and Trichosporon beigelii.