Water Pollution Assessment of an Abandoned Copper Mine in Lasail, Sultanate of Oman

Abandoned mining sites are largely responsible for the release of heavy metals into water systems. This study assessed heavy metalsin the water collected from the mine sumps and bore-wells of an abandoned copper mine in Lasail, northern Oman. Other physiochemicalparameters of the water were also evaluated. The waters were extremely acidic with very high electrical conductivity.Aluminium (Al), boron (B), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn) and zinc (Zn) were in very high concentrations,well above the limits recommended by Oman and World Health Organisation (WHO) standards. The principal componentanalysis (PCA) explained 93% of the variability. The impact of mining on the water quality of Lasail area is presented and remediationmeasures are recommended.

Deciduous Dental Morphological Diversity in Contemporary Colombian Ethnic Groups

Biocultural diversity of contemporarySouth American populations has not been studiedextensively, therefore delineating some of the patterns ofphenotypic variation may be useful for understandingtheir ongoing evolution. Thirty-seven deciduous dentalnonmetric traits were scored on 200 dental casts thatwere obtained from four contemporary Colombianethnic groups with different ancestry. Inter-group affinitieswere assessed by means of a principal componentanalysis based on trait frequencies. African-AmericanColombian groups share several dental morphologicalaffinities with other New World African derived populationsas well as with Sub-Saharan African dental samples.Colombian Amerindians have a relative affinity withprehistoric Native North American samples, but a clearassociation with living North American Indians andrecent Northeast Asian Sinodont populations was notevident. The biologically admixed group or “Mestizo”has a more complicated pattern of phenotypic relationships,with an African and an Amerindian but not anevident European component. From an evolutionarypoint of view, gene flow probably is the most importantfactor that changed the original gene pool through time.These groups have a complex landscape of bioculturalvariation reflected by their different microevolutionaryhistories.

Impact of wealth inequality on child nutrition in Bangladesh

Background The prevalence of malnutrition in Bangladesh isamong the highest in the world. Millions of women and childrensuffer from one or more forms of main utrition, including low birthweight, wasting, stunting, underweight, vitamin A deficiency,iodine deficiency disorders, and anemia. Today malnutritionnot only affects individuals, but its effects are passed from onegeneration to the next as malnourished mothers give birth toinfants wh o struggle to develop and thrive.Objective To assess the economic impact on child nutrition inBangladesh.Methods The 2011 Bangladesh Demographic Health Survey datawas used for this study. In this study, quintiles were calculatedbased on asset and wealth scores by use of principal componentanalysis. To understand the nutritional status and healthinequality, concentration index was also calculated.Results The negative concentration index showed a higher rateof malnutrition in the children less than five years of age from thepoorest class. Furthermore, the ratio of poorest to richest indicatedthat stunting and underweight conditions in rural children underfive years of age were almost two times higher than that of therichest children. This inequality in the health situation of childrenmay be explained in terms of income inequality. In Bangladesh,about 40% of the wealth is concentrated in 10% of the families.The results are discussed as possible input for public policy.Conclusion Bangladeshi children under the age of five yearsand in the poorest economic class are nearly twice as likely to beunderweight or stunted compared to children of similar age in therichest economic class

THE IDENTIFICATION OF EAR PRINTS USING COMPLEX GABOR FILTERS

Biometrics is a method used to recognize humans based on one or a few characteristicsphysical or behavioral traits that are unique such as DNA, face, fingerprints, gait, iris, palm, retina,signature and sound. Although the facts that ear prints are found in 15% of crime scenes, ear printsresearch has been very limited since the success of fingerprints modality. The advantage of the useof ear prints, as forensic evidence, are it relatively unchanged due to increased age and have fewervariations than faces with expression variation and orientation. In this research, complex Gaborfilters is used to extract the ear prints feature based on texture segmentation. Principal componentanalysis (PCA) is then used for dimensionality-reduction where variation in the dataset ispreserved. The classification is done in a lower dimension space defined by principal componentsbased on Euclidean distance. In experiments, it is used left and right ear prints of ten respondentsand in average, the successful recognition rate is 78%. Based on the experiment results, it isconcluded that ear prints is suitable as forensic evidence mainly when combined with otherbiometric modalities.Keywords: Biometrics; Ear prints; Complex Gabor filters; Principal component analysis;Euclidean distance

Sistem Deteksi Penyakit Pengeroposan Tulang Dengan Metode Jaringan Syaraf Tiruan Backpropagation Dan Representasi Ciri Dalam Ruang Eigen

There are various ways to detect osteoporosis disease (bone loss). One of them is by observing the osteoporosisimage through rontgen picture or X-ray. Then, it is analyzed manually by Rheumatology experts. Article present the creationof a system which could detect osteoporosis disease on human, by implementing the Rheumatology principles. The main areasidentified were between wrist and hand fingers. The working system in this software included 3 important processing, whichwere process of basic image processing, pixel reduction process, pixel reduction, and artificial neural networks. Initially, thecolor of digital X-ray image (30 x 30 pixels) was converted from RGB to grayscale. Then, it was threshold and its gray levelvalue was taken. These values then were normalized to an interval [0.1, 0.9], then reduced using a PCA (Principal ComponentAnalysis) method. The results were used as input on the process of Backpropagation artificial neural networks to detect thedisease analysis of X-ray being inputted. It can be concluded that from the testing result, with a learning rate of 0.7 andmomentum of 0.4, this system had a success rate of 73 to 100 percent for the non-learning data testing, and 100 percent forlearning data.Keywords: osteoporosis, image processing, PCA, artificial neural networks