Assessment of practicality of remote sensing techniques for a study of the effects of strip mining in Alabama

Because of the volume of coal produced by strip mining, the proximity of mining operations, and the diversity of mining methods (e.g. contour stripping, area stripping, multiple seam stripping, and augering, as well as underground mining), the Warrior Coal Basin seemed best suited for initial studies on the physical impact of strip mining in Alabama. Two test sites, (Cordova and Searles) representative of the various strip mining techniques and environmental problems, were chosen for intensive studies of the correlation between remote sensing and ground truth data. Efforts were eventually concentrated in the Searles Area, since it is more accessible and offers a better opportunity for study of erosional and depositional processes than the Cordova Area

Examining mindfulness and its relation to self-differentiation and alexithymia

Published online first in 10 July 2013Research supports the association between mindfulness, emotion regulation, stress reduction, and interpersonal/relational wellness. The present study evaluated the potential effect of mindfulness on some indicators of psychological imbalance such as low self-differentiation and alexithymia. In this cross-sectional study, a sample of 168 undergraduates (72 % women) completed measures of perceived mindfulness (CAMS-R and PHLMS), self-differentiation (SIPI), and alexithymia (TAS-20). Results revealed positive correlations between the different dimensions of mindfulness and negative correlations between those dimensions, selfdifferentiation, and alexithymia. The dimensions of quality of mindfulness and acceptance were mediators in the relationship between self-differentiation and alexithymia. A nonsignificant interaction between gender and alexithymia was found. All mindfulness dimensions, but self-differentiation, contributed to explain the allocation of the non-alexithymic group. These results indicate that mindfulness seems to be a construct with great therapeutic and research potential at different levels, suggesting that some aspects of mindfulness seem to promote a better self-differentiation and prevent alexithymia

Application of Probabilistic Neural Networks in Modelling Structural Deterioration of Stormwater Pipes

In Australia, when stormwater systems were first introduced over 100 years ago, they were constructed independently of the sewer systems, and they are normally the responsibility of the third level of government, i.e., local government or city councils. Because of the increasing age of these stormwater systems and their worsening performance, there are serious concerns in a significant number of city councils regarding their deterioration. A study has been conducted on the structural deterioration of concrete pipes that make up the bulk of the stormwater pipe systems in these councils. In an attempt to look for a reliable deterioration model, a probabilistic neural network (PNN) model was developed using the data set supplied from participating councils. The PNN model was validated with snapshot-based sample data, which makes up the data set. The predictive performance of the PNN model was compared with a traditional parametric model using discriminant analysis on the same data set. Structural deterioration was hypothesised to be influenced by a set of explanatory factors, including pipe design and construction factors—such as pipe size, buried depth—and site factors— such as soil type, moisture index, tree root intrusion, etc. The results show that the PNN model has a better predictive power and uses significantly more input variables (i.e., explanatory factors) than the discriminant model. More importantly, the key factors for prediction in the PNN model are difficult to interpret, suggesting that besides prediction accuracy, model interpretation is an important issue for further investigation