Based on interviews with victims, investigators, and the people who sell counterfeits, "Knockoff" reveals the link between what we see as innocent fakes and organized crime.

As editor in chief of Glossy magazine, Imogen Tate is queen of the fashion world … until Eve, her conniving twenty-something former assistant, returns from business school with plans to knock Imogen off her pedestal, take over her job, and re-launch Glossy as an app. Suddenly, the Louboutin is on the other foot; Imogen may have Alexander Wang and Diane von Furstenberg on speed dial, but she doesn’t know Facebook from Foursquare and once got her phone stuck in Japanese for three days. But Imogen will do anything to reclaim her kingdom—even if it means channeling her inner millennial and going head to head with a social-media monster.

From the shopping mall to the corner bistro, knockoffs are everywhere in today's marketplace. Conventional wisdom holds that copying kills creativity, and that laws that protect against copies are essential to innovation--and economic success. But are copyrights and patents always necessary? In The Knockoff Economy, Kal Raustiala and Christopher Sprigman provocatively argue that creativity can not only survive in the face of copying, but can thrive. The Knockoff Economy approaches the question of incentives and innovation in a wholly new way--by exploring creative fields where copying is generally legal, such as fashion, food, and even professional football. By uncovering these important but rarely studied industries, Raustiala and Sprigman reveal a nuanced and fascinating relationship between imitation and innovation. In some creative fields, copying is kept in check through informal industry norms enforced by private sanctions. In others, the freedom to copy actually promotes creativity. High fashion gave rise to the very term "knockoff," yet the freedom to imitate great designs only makes the fashion cycle run faster--and forces the fashion industry to be even more creative. Raustiala and Sprigman carry their analysis from food to font design to football plays to finance, examining how and why each of these vibrant industries remains innovative even when imitation is common. There is an important thread that ties all these instances together--successful creative industries can evolve to the point where they become inoculated against--and even profit from--a world of free and easy copying. And there are important lessons here for copyright-focused industries, like music and film, that have struggled as digital technologies have made copying increasingly widespread and difficult to stop. Raustiala and Sprigman's arguments have been making headlines in The New Yorker, the New York Times, the Financial Times, the Boston Globe, Le Monde, and at the Freakonomics blog, where they are regular contributors. By looking where few had looked before--at markets that fall outside normal IP law--The Knockoff Economy opens up fascinating creative worlds. And it demonstrates that not only is a great deal of innovation possible without intellectual property, but that intellectual property's absence is sometimes better for innovation.

When fashion columnist Lacey Smithsonian learns that a new fashion museum will soon grace decidedly unfashionable D.C., it's more than a good story-it's a chance to show off her vintage Hugh Bentley suit. And it's not long before the dapper designer himself spots Lacey in the crowd. A reporter at heart, she manages to get all the juicy details about his past-including a long-unsolved mystery about a missing employee. Could it be linked to the disappearance of a Washington intern or the recent Bentley boutique robbery? Lacey sets out to unravel the murderous details in a fabric of lies, greed-and (gasp!) very bad taste...

Driven by a counterintuitive thesis that has been highlighted in both The New Yorker and The New York Times¸ The Knockoff Economy is an engrossing and highly entertaining tour through the economic sectors where piracy both rules and invigorates.

West Palm Beach paralegal, discount shopping queen, and slacker extraordinaire Finley Anderson Tanner discovers she has a knack for sleuthing when her boss forces her to help a client prove that her husband's death was no accident, with the help of a sexy P.I. Reprint.

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.

This textbook integrates important mathematical foundations, efficient computational algorithms, applied statistical inference techniques, and cutting-edge machine learning approaches to address a wide range of crucial biomedical informatics, health analytics applications, and decision science challenges. Each concept in the book includes a rigorous symbolic formulation coupled with computational algorithms and complete end-to-end pipeline protocols implemented as functional R electronic markdown notebooks. These workflows support active learning and demonstrate comprehensive data manipulations, interactive visualizations, and sophisticated analytics. The content includes open problems, state-of-the-art scientific knowledge, ethical integration of heterogeneous scientific tools, and procedures for systematic validation and dissemination of reproducible research findings. Complementary to the enormous challenges related to handling, interrogating, and understanding massive amounts of complex structured and unstructured data, there are unique opportunities that come with access to a wealth of feature-rich, high-dimensional, and time-varying information. The topics covered in Data Science and Predictive Analytics address specific knowledge gaps, resolve educational barriers, and mitigate workforce information-readiness and data science deficiencies. Specifically, it provides a transdisciplinary curriculum integrating core mathematical principles, modern computational methods, advanced data science techniques, model-based machine learning, model-free artificial intelligence, and innovative biomedical applications. The book’s fourteen chapters start with an introduction and progressively build foundational skills from visualization to linear modeling, dimensionality reduction, supervised classification, black-box machine learning techniques, qualitative learning methods, unsupervised clustering, model performance assessment, feature selection strategies, longitudinal data analytics, optimization, neural networks, and deep learning. The second edition of the book includes additional learning-based strategies utilizing generative adversarial networks, transfer learning, and synthetic data generation, as well as eight complementary electronic appendices. This textbook is suitable for formal didactic instructor-guided course education, as well as for individual or team-supported self-learning. The material is presented at the upper-division and graduate-level college courses and covers applied and interdisciplinary mathematics, contemporary learning-based data science techniques, computational algorithm development, optimization theory, statistical computing, and biomedical sciences. The analytical techniques and predictive scientific methods described in the book may be useful to a wide range of readers, formal and informal learners, college instructors, researchers, and engineers throughout the academy, industry, government, regulatory, funding, and policy agencies. The supporting book website provides many examples, datasets, functional scripts, complete electronic notebooks, extensive appendices, and additional materials.

After a fatal car crash, the FBI opens a probe into counterfeit consumer products. The investigation centers on a chain of discount stores, selling everything from false perfumes to false auto parts. The owner of the chain reacts by contracting for the murder of the distributor to keep him from talking. A first novel.

When her "charmingly eccentric" mother Vivian is accused of killing mousy-haired busybody Connie Grimes after they were both involved in a bit of a scuffle, Brandy Borne must find the truth, which immerses her in a scandal involving questionable antiques and dark family secrets.