This new edition includes a complete revision of the chapter on medication, detailing when to use certain drugs and the side effects that can be expected, and includes a thorough review and update of older medications.
The ADHD label had been rampantly overused on children with completely different problems when the controversial first edition of ADHD was praised by practitioners and parents alike as a timely book whose message was long overdue. This new edition includes a complete revision of the chapter on medication, detailing when to use certain drugs and the side effects that can be expected, and including a thorough review and update of older medications. Special problems for teenagers with ADHD are addressed, including sexual relationships, pregnancy, substance abuse, driving, and general teen attitudes. Material has been added to help parents find their way through the legal maze of public education where children are often wrongly first stigmatized with the ADHD label.
This text on the theory and applications of network science is aimed at beginning graduate students in statistics, data science, computer science, machine learning, and mathematics, as well as advanced students in business, computational biology, physics, social science, and engineering working with large, complex relational data sets. It provides an exciting array of analysis tools, including probability models, graph theory, and computational algorithms, exposing students to ways of thinking about types of data that are different from typical statistical data. Concepts are demonstrated in the context of real applications, such as relationships between financial institutions, between genes or proteins, between neurons in the brain, and between terrorist groups. Methods and models described in detail include random graph models, percolation processes, methods for sampling from huge networks, network partitioning, and community detection. In addition to static networks the book introduces dynamic networks such as epidemics, where time is an important component.
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