This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., "mechanistic" principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.

This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., "mechanistic" principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.

"Being Killed by the Siren is a wonderful way to die" Introducing a new character to the world of contemporary fantasy The ancients called her by many names: the Nereid, a Morgan, or an Undine. The Greeks called her a Nymph. They are all very beautiful names for a beautiful killer of humans. If you are in her company near water, and should she wish for you to go farther, then you have already gone too far... Her name is Eleanor Orlen, and she is the last of her kind. She is the Siren Once an object of romantic myth and legend, it took until the 20th Century for humans to find a use for her... "the perfect killer." Eleanor leaves no fingerprints, and can beguile her way into any place, mind or secret. When seen at her most beautiful, few have lived to describe her. She has the ability to vanish without trace, bear horrific injuries and is difficult to kill unless you know how. She is also lonely, lost, scared and frustrated, and finds herself trapped in a modern and at times cruel world. Those who entrap her, the mysterious Brabant Committee, do so with a simple ultimatum - work for us, or perish. Eleanor must conduct her hated tasks against an ever more dangerous background, with even the Vatican tracking her. Forever young and forever lonely, all she wants is her freedom, but time is now running out... A hunter is closing in. A man whose greatest wish is to make a species become extinct. The Call of the Siren is the first book in the Siren Trilogy. .".".This mixture of an espionage thriller and a contemporary fantasy, felt like something John le Carre might have produced if he'd been tasked with writing something similar to Twilight.""

libro si ispira al famoso flusso di coscienza di Joyce, ma con una netta distinzione per quanto concerne l'ambientazione (non piu una citta, ma l'interno di una casa) e la rivelazione finale (non piu una semplice epifania, tanto cara a Joyce, ma una epifania che acquisisce in questo racconto il carattere di agnizione). Una confessione del protagonista, uno shock per la coprotagonista del racconto. Un finale inaspettato...