No abstract

Puberty is an important stage of development as a child's sexual and physical characteristics mature because of hormonal changes. To better understand puberty-related effects on brain development, we investigated the magnetic resonance imaging (MRI) data of 306 subjects from 4 to 18 years of age. Subjects were grouped into before and during puberty groups according to their sexual maturity levels measured by the puberty scores. An appearance model-based automatic segmentation method with patch-based local refinement was employed to segment the MRI data and extract the volumes of medial temporal lobe (MTL) structures including the amygdala (AG), the hippocampus (HC), the entorhinal/perirhinal cortex (EPC), and the parahippocampal cortex (PHC). Our analysis showed age-related volumetric changes for the AG, HC, right EPC, and left PHC but only before puberty. After onset of puberty, these volumetric changes then correlate more with sexual maturity level, as measured by the puberty score. When normalized for brain volume, the volumes of the right HC decrease for boys; the volumes of the left HC increase for girls; and the volumes of the left and right PHC decrease for boys. These findings suggest that the rising levels of testosterone in boys and estrogen in girls might have opposite effects, especially for the HC and the PHC. Our findings on sex-specific and sexual maturity-related volumes may be useful in better understanding the MTL developmental differences and related learning, memory, and emotion differences between boys and girls during puberty.

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A cyber-physical system (CPS) is an integration of computation with physical processes whose behavior is defined by both computational and physical parts of the system. In this paper, we present a view of the challenges and opportunities for design automation of CPS. We identify a combination of characteristics that define the challenges unique to the design automation of CPS. We then present selected promising advances in depth, focusing on four foundational directions: combining model-based and data-driven design methods; design for humanin-the-loop systems; component-based design with contracts, and design for security and privacy. These directions are illustrated with examples from two application domains: smart energy systems and next-generation automotive systems.