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School-based drug prevention, popular with the public and politicians alike, is now a nearly universal experience for American youth. Analysis has shown that the best programs can reduce use of a wide range of substances. But questions remain regarding how to think about and, hence, fund, these programs. Should they be viewed principally as weapons in the war against illicit drugs, or, at the other extreme, do prevention programs benefit students and society most by reducing use of alcohol and tobacco? The authors address these questions by comparing for the first time the social benefits of school-based prevention programs' long-run impacts on a diverse set of different substances.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Although criminal justice systems in developed Western countries are much alike in form, structure, and function, the American system is unique. While it is structurally similar to those of other Western countries, the punishments it imposes are often vastly harsher. No other Western country retains capital punishment or regularly employs life-without-parole, three-strikes, or lengthy mandatory minimum sentencing laws. As a result, the U.S. imprisonment rate of nearly 800 per 100,000 residents dwarfs rates elsewhere. The Oxford Handbook of Crime and Criminal Justice is an essential guide to the development and operation of the American criminal justice system. A leading scholar in the field ...
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In this book, leading authors in the field discuss the habitats of tomorrow. These habitats will be connected through autonomous and assistive systems, turning habitats into health resorts. This book discusses how assistance technologies enable a smooth transition from comfortable health support to medical or nursing care. The contributions have been chosen and invited at the 9th AAL congress, Frankfurt.
The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.