DXAGE: A New Method for Age at Death Estimation Based on Femoral Bone Mineral Density and Artificial Neural Networks

Age at death estimation in adult skeletons is hampered, among others, by the unremarkable correlation of bone estimators with chronological age, implementation of inappropriate statistical techniques, observer error, and skeletal incompleteness or destruction. Therefore, it is beneficial to consider alternative methods to assess age at death in adult skeletons. The decrease in bone mineral density with age was explored to generate a method to assess age at death in human remains. A connectionist computational approach, artificial neural networks, was employed to model femur densitometry data gathered in 100 female individuals from the Coimbra Identified Skeletal Collection. Bone mineral density declines consistently with age and the method performs appropriately, with mean absolute differences between known and predicted age ranging from 9.19 to 13.49 years. The proposed method—DXAGE—was implemented online to streamline age estimation. This preliminary study highlights the value of densitometry to assess age at death in human remains.     

Buy Today,Pay Tomorrow: Formal Credit Supply and Domestic Electrical and Electronic Goods Consumption in São Paulo's Urban Periphery

Since the beginning of the twenty-first century, expansion of the formal credit supply in Brazil has promoted the ‘financial inclusion’ of the low-income population, especially through instalment plans offered by large retail chains. This article aims to analyse the impacts of formal credit availability on the consumption of electrical and electronic goods by residents of Jardim Helena, a neighbourhood in São Paulo's periphery. Through the collection and analysis of qualitative and quantitative data, this study reveals how the instalment plan can stimulate consumption among the low-income population, with a significant impact on household budgets, raising the risk of indebtedness.