In an online anonymous study we compared 2409 contemplative practitioners to 450 non-meditators on measures of psychological functioning. The meditators followed five traditions: Tibetan and Theravada Buddhism, Centering Prayer, Yoga and Mindfulness. Meditators were lower in depression, neuroticism, empathic distress, and types of empathy-based guilt, and higher in empathy (cognitive and emotional), agreeableness, conscientiousness, openness, resilience, and compassionate altruism towards strangers. Comparing traditions found Tibetans and Centering Prayer higher in altruism towards strangers and Centering Prayer lower in neuroticism. In all traditions, intensity and duration of practice predicted positive outcomes. Meditators whose goal was benefit to others, compared to those whose goal was benefit to the self, were lower in depression, empathic distress, and neuroticism, and higher in cognitive empathy, resilience, and altruism towards strangers. Religion-based practitioners were lower in guilt, empathic distress, depression and neuroticism, and higher in conscientiousness, resilience, and altruism towards others compared secular meditators.
Pelagic Chlorophyll-a concentrations are key for evaluation of the environmental status and productivity of marine systems. In this study, chlorophyll-a concentrations for the Helgoland Roads Time Series were modeled using a number of measured water and environmental parameters. We chose three common Machine Learning algorithms from the literature: Support Vector Machine Regressor, Neural Networks Multi-layer Perceptron Regressor and Random Forest Regressor. Results showed that Support Vector Machine Regressor slightly outperformed other models. The evaluation with a test dataset and verification with an independent validation dataset for chlorophyll-a concentrations showed a good generalization capacity, evaluated by the root mean squared errors of less than 1 µg L-1. Feature selection and engineering are important and improved the models significantly, as measured in performance, improving by a minimum of 48% the adjusted R2. We tested SARIMA in comparison and found that the univariate nature of SARIMA does not allow for better results than the Machine Learning models. Additionally, the computer processing time needed was much higher (prohibitive) for SARIMA.
At a time when students are increasingly turning to the Web as their primary source of information it is well worth continuing to consider ways and means of taking advantage of this trend, and to perhaps relocate attention to traditional information sources presented in new ways. This paper makes the case that Open Access to electronic scholarly journals creates an opportunity for schools and school libraries to benefit from use of these journals.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.