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To inaugurate a new series, Lives of Women in Science, Rutgers University Press is reissuing this much-acclaimed biography of Sofia Kovalevskaia, the renowned nineteenth-century mathematician, writer, and revolutionary.

Sofia Kovalevskaia's interest in mathematics was roused at an early age--her attic nursery had been wallpapered with lecture notes for a course on calculus. She spent hours studying the mysterious walls, trying to figure out which page followed from the next. Kovalevskaia (1850-1891) became the only woman mathematician whose name all mathematicians recognize, thanks to her contributions to mathematical analysis. Indeed, she was the first professional woman scientist to win international eminence in any field: the first woman doctorate in mathematics, the first to hold a chair in mathematics, the first to sit on the editorial board of a major scientific journal.

She was also an accomplished writer, a proponent of women's rights and education, a wife and mother in an unconventional marriage, and a champion of radical political causes in Russia and Western Europe--a friend and correspondent of Dostoyevsky, Chekhov, George Eliot, Kropotkin, Helmholtz, and Darwin. This sympathetic portrait of a remarkable woman will appeal to any reader, non-mathematicians and mathematicians alike.

The Walt Disney Company offers a vast universe of movies, television shows, theme parks, and merchandise, all carefully crafted to present an image of wholesome family entertainment. Yet Disney also produced one of the most infamous Hollywood films, Song of the South. Using cartoon characters and live actors to retell the stories of Joel Chandler Harris, SotS portrays a kindly black Uncle Remus who tells tales of Brer Rabbit, Brer Fox, and the “Tar Baby” to adoring white children. Audiences and critics alike found its depiction of African Americans condescending and outdated when the film opened in 1946, but it grew in popularity—and controversy—with subsequent releases. Although Disney has withheld the film from American audiences since the late 1980s, SotS has an enthusiastic fan following, and pieces of the film—such as the Oscar-winning “Zip-a-Dee-Doo-Dah”—remain throughout Disney’s media universe.

Disney’s Most Notorious Film examines the racial and convergence histories of Song of the South to offer new insights into how audiences and Disney have negotiated the film’s controversies over the last seven decades. Jason Sperb skillfully traces the film’s reception history, showing how audience perceptions of SotS have reflected debates over race in the larger society. He also explores why and how Disney, while embargoing the film as a whole, has repurposed and repackaged elements of SotS so extensively that they linger throughout American culture, serving as everything from cultural metaphors to consumer products.

Based on comparative surveys, the author presents a study of social transformation in Central and Eastern Europe after 1989. Focusing on Bulgaria, Czech Republic, Hungary, Poland, Russia and Slovakia, the author provides information relating to social structure, mobility, inequality, lifestyle and economic stratification. Applying the Erikson-Goldthorpe classification of class positions, Domanski effectively presents fully comparable data to enable political comparisons to be made with other countries, especially those with firmly established free market economies. As such, "On the Verge of Convergence" seeks to provide a clearer understanding of the on-going process of social transformation within developing capitalist societies.

Revelation & Convergence brings together professors of literature, theology, and history to help both critics and readers better understand Flannery O’Connor’s religious imagination.

AI and data-driven methods, particularly machine and deep learning models, have revolutionized image processing tasks such as object detection and segmentation, as well as inverse sensing tasks such as atmospheric condition monitoring. These models enable highly accurate predictions from large, labelled datasets. However, one of the key challenges with current AI systems is their opacity. While they deliver precise results, they often fail to provide clear insights into the underlying mechanisms driving these predictions. The lack of interpretability, especially in the context of sensing data, complicates the understanding of how internal features are represented and utilized. This issue is particularly pronounced in smart environment applications, where artificial intelligence techniques are increasingly employed, yet their internal workings remain largely opaque.