Concentrations of uranium-238 and thorium-232 in soil, water, grass, moss and oil-palm fruit samples collected from an area of high background radiation were determined using neutron activation analysis (NAA). U-238 concentration in soil ranged from 4.9 mg kg(-1) (58.8 Bq kg(-1)) to 40.4 mg kg(-1) (484.8 Bq kg(-1)), Th-232 concentration ranged from 14.9 mg kg(-1) (59.6 Bq kg(-1)) to 301.0 mg kg(-1) (1204 Bq kg(-1)). The concentration of U-238 in grass samples ranged from below the detection limit to 0.076 mg kg(-1) (912 mBq kg(-1)), and Th-232 ranged from 0.008 mg kg(-1) (32 mBq kg(-1)) to 0.343 mg kg(-1) (1.372 Bq kg(-1)). U-238 content in water samples ranged from 0.33 mg kg(-1) (4.0 Bq L(-1)) to 1.40 mg kg(-1) (16.8 Bq L(-1)), and Th-232 ranged from 0.19 mg kg(-1) (0.76 Bq L(-1)) to 0.66 mg kg(-1) (2.64 Bq L(-1)). It can be said that the concentrations of environmental U-238 and Th-232 in grass and water samples in the study area are insignificant. Mosses were found to be possible bio-radiological indicators due to their high absorption of the heavy radioelements from the environment.
Wavelet-based image coding algorithms (lossy and lossless) use a fixed perfect reconstruction filter-bank built into the algorithm for coding and decoding of images. However, no systematic study has been performed to evaluate the coding performance of wavelet filters on medical images. We evaluated the best types of filters suitable for medical images in providing low bit rate and low computational complexity. In this study a variety of wavelet filters are used to compress and decompress computed tomography (CT) brain and abdomen images. We applied two-dimensional wavelet decomposition, quantization and reconstruction using several families of filter banks to a set of CT images. Discreet Wavelet Transform (DWT), which provides efficient framework of multi-resolution frequency was used. Compression was accomplished by applying threshold values to the wavelet coefficients. The statistical indices such as mean square error (MSE), maximum absolute error (MAE) and peak signal-to-noise ratio (PSNR) were used to quantify the effect of wavelet compression of selected images. The code was written using the wavelet and image processing toolbox of the MATLAB (version 6.1). This results show that no specific wavelet filter performs uniformly better than others except for the case of Daubechies and bi-orthogonal filters which are the best among all. MAE values achieved by these filters were 5 x 10(-14) to 12 x 10(-14) for both CT brain and abdomen images at different decomposition levels. This indicated that using these filters a very small error (approximately 7 x 10(-14)) can be achieved between original and the filtered image. The PSNR values obtained were higher for the brain than the abdomen images. For both the lossy and lossless compression, the 'most appropriate' wavelet filter should be chosen adaptively depending on the statistical properties of the image being coded to achieve higher compression ratio.
A total of 1,134 finger-pricked blood samples were collected from residents of Setiu, Terengganu. A drop of blood was used to make thick blood smear and about four drops were used for obtaining serum. The smears were stained and examined by the State Vector Control Unit in Kuala Terengganu, while the serum samples were tested for specific IgG4 antibodies to a novel recombinant antigen using Brugia-Elisa. Prevalence of filariasis in these areas were found to be 0.26% (3/1,134) using thick blood smear examination and 2.47% (28/1,134) using Brugia-Elisa, thus demonstrating the greater sensitivity of the latter test. In addtion, Brugia-Elisa showed a high level of specificity (97.8%, 1,106/1,131) when compared to thick blood smear examination.
Measurements of environmental terrestrial gamma radiation dose-rate (TGRD) have been made in Johore, Malaysia. The focus is on determining a relationship between geological type and TGRD levels. Data were compared using the one way analysis of variance (ANOVA), in some instances revealing significant differences between TGRD measurements and the underlying geological structure.