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Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide.
Trying to assess the way sex differences in behavior are reflected in the brain, neuroscience reports produced diverse results triggering hot discussions on whether such differences exist and/or are worth considering in further studies. This chapter summarizes recent progress in the study of sex/gender effect on the brain as viewed from the perspective of (1) anatomy, which is based on the description of various global and local morphometric features of male and female brain structures; and (2) connections, which conceptualizes the brain as a large-scale network of structures interconnected within the human connectome which subserves the transmission and integration of information at both global and local levels. It is argued that the key to understanding the behavioral differentiation of the two sexes might lie in the differences in the architecture of their networks rather than in morphometric measures of particular structures and tissues.
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