Xu Zhang – författare

Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture fills a clear gap in literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics. The book’s focus on complex mechanisms and coupling phenomena, discussed with practical examples, makes it a valuable resource for advanced researchers. Practical examples and case studies enable readers to understand both the underlying engineering problems and the application of machine learning methods to enhance fatigue life prediction analysis for solid materials and structures.Provides a systematic summary of machine learning methods applied to solid deformation, fatigue and fracture analysisFills a clear gap in the literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanicsIntroduces the application of physics-informed machine learning in multiaxial fatigue life predictionIntroduces the application of physics-informed machine learning in predicting the fatigue life of additively manufactured metallic metalsIncludes numerous practical examples and case studies and draws on the authors’ extensive experience in multiscale simulation of solid materials and fatigue life prediction

Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture fills a clear gap in literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics. The book's focus on complex mechanisms and coupling phenomena, discussed with practical examples, makes it a valuable resource for advanced researchers. Practical examples and case studies enable readers to understand both the underlying engineering problems and the application of machine learning methods to enhance fatigue life prediction analysis for solid materials and structures. - Provides a systematic summary of machine learning methods applied to solid deformation, fatigue and fracture analysis- Fills a clear gap in the literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics- Introduces the application of physics-informed machine learning in multiaxial fatigue life prediction- Introduces the application of physics-informed machine learning in predicting the fatigue life of additively manufactured metallic metals- Includes numerous practical examples and case studies and draws on the authors' extensive experience in multiscale simulation of solid materials and fatigue life prediction

Cities for Driverless Vehicles examines the relationship between autonomous vehicles, transport infrastructure requirements and urban forms, as well as explores ways to adopt autonomous vehicles into future cities. With insights drawn from urban planners and professionals across the world, the book informs you how our future cities will look, what legal requirements will need to be met, how pedestrians will interact with driverless vehicles, the Mobility as a Service (MaaS) concept, and how planners can prepare for the new technological age. Informed research and expert transport modelling is underpinned by international case studies along with the action plans required to make the transition a smooth, orderly and safe one for future generations.This bookincludes plans for industry professionals on understanding new and upcoming technology and provides thoughts for further research and developmentdetails the infrastructure that the vehicles will interact with, including hard solutions and soft benefitsreveals how to plan for a future with MaaSconcludes each chapter with plausible and desirable future scenarios for the reader to take away and consider.With technology changing the face of future travel faster than ever before, the need to be ahead of the curve has never been greater. This forward-thinking book is, therefore, an ideal and necessary purchase for urban and transport planners, infrastructure engineers, vehicle manufacturers, and policy and decision makers tasked with future-proofing urban areas.

This detailed volume explores robust analytical workflows for post-translational modification (PTM) analysis in both basic and translational contexts. After brief foundational reviews of the field, the book delves into detailed experimental and computational protocols for traditional bottom-up strategies and top-down proteoform analysis, as well as PTM analysis of biotherapeutic proteins, reflecting the growing emphasis on PTMs as critical quality attributes in biologic drug development and regulation. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step and readily reproducible laboratory protocols, and tips for troubleshooting and avoiding known pitfalls.Authoritative and practical, Protein Post-Translational Modifications: Methods and Protocols serves as a foundational and forward-looking resource to support and inspire continued exploration in this rapidly evolving field.

This detailed volume explores robust analytical workflows for post-translational modification (PTM) analysis in both basic and translational contexts. After brief foundational reviews of the field, the book delves into detailed experimental and computational protocols for traditional bottom-up strategies and top-down proteoform analysis, as well as PTM analysis of biotherapeutic proteins, reflecting the growing emphasis on PTMs as critical quality attributes in biologic drug development and regulation. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step and readily reproducible laboratory protocols, and tips for troubleshooting and avoiding known pitfalls.Authoritative and practical, Protein Post-Translational Modifications: Methods and Protocols serves as a foundational and forward-looking resource to support and inspire continued exploration in this rapidly evolving field.

It is a longstanding unsolved problem to characterize the optimal feedbacks for general SLQs (i.e., stochastic linear quadratic control problems) with random coefficients in infinite dimensions; while the same problem but in finite dimensions was just addressed very recently. This paper is devoted to giving a solution to this problem under some assumptions which can be verified for interesting concrete models. More precisely, under these assumptions, we establish the equivalence between the existence of optimal feedback operator for infinite dimensional SLQs and the solvability of the corresponding operator-valued, backward stochastic Riccati equations. A key contribution of this work is to introduce a suitable notion of solutions (i.e., transposition solutions to the aforementioned Riccati equations), which plays a crucial role in both the statement and the proof of our main results.

Emotionally Intelligent Digital Learning explores how AI can transform digital education by supporting both academic success and student well-being. Instead of focusing solely on cognitive performance, this book introduces emotionally aware technologies that recognize student emotions in real time, offer personalized emotional support, and build mental resilience.Through real-world case studies, ranging from virtual empathy training in nursing to tools that reveal emotional manipulation on social media, the authors explore how AI can foster emotional intelligence, empathy, and digital self-awareness.Blending insights from psychology, computer science, and education, this work offers a practical framework for creating emotionally intelligent learning environments. It s a vital resource for educators, developers, and researchers committed to creating psychologically sustainable educational environments.

Emotionally Intelligent Digital Learning explores how AI can transform digital education by supporting both academic success and student well-being. Instead of focusing solely on cognitive performance, this book introduces emotionally aware technologies that recognize student emotions in real time, offer personalized emotional support, and build mental resilience.Through real-world case studies, ranging from virtual empathy training in nursing to tools that reveal emotional manipulation on social media, the authors explore how AI can foster emotional intelligence, empathy, and digital self-awareness.Blending insights from psychology, computer science, and education, this work offers a practical framework for creating emotionally intelligent learning environments. It’s a vital resource for educators, developers, and researchers committed to creating psychologically sustainable educational environments.

Emotionally Intelligent Digital Learning explores how AI can transform digital education by supporting both academic success and student well-being. Instead of focusing solely on cognitive performance, this book introduces emotionally aware technologies that recognize student emotions in real time, offer personalized emotional support, and build mental resilience.Through real-world case studies, ranging from virtual empathy training in nursing to tools that reveal emotional manipulation on social media, the authors explore how AI can foster emotional intelligence, empathy, and digital self-awareness.Blending insights from psychology, computer science, and education, this work offers a practical framework for creating emotionally intelligent learning environments. It s a vital resource for educators, developers, and researchers committed to creating psychologically sustainable educational environments.

This book provides a brief, self-contained introduction to Carleman estimates for three typical second order partial differential equations, namely elliptic, parabolic, and hyperbolic equations, and their typical applications in control, unique continuation, and inverse problems. There are three particularly important and novel features of the book. First, only some basic calculus is needed in order to obtain the main results presented, though some elementary knowledge of functional analysis and partial differential equations will be helpful in understanding them. Second, all Carleman estimates in the book are derived from a fundamental identity for a second order partial differential operator; the only difference is the choice of weight functions. Third, only rather weak smoothness and/or integrability conditions are needed for the coefficients appearing in the equations. Carleman Estimates for Second Order Partial Differential Operators and Applications will be of interestto all researchers in the field.

This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems.A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems.A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems.A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

Building on the success of the first edition, this extensively revised and expanded second edition of Emergencies in Urology sets a new standard in the field. Edited by five internationally recognized experts, this authoritative textbook closes one of the last remaining gaps in urological literature: the systematic management of urgent and emergent clinical scenarios in urology. This edition reflects major advances in diagnostics, surgical techniques, and perioperative management. It includes fully updated chapters on urological trauma, urosepsis, urinary obstruction, oncological emergencies, and intra- and postoperative complications—complemented by new chapters on iatrogenic pathology, undiversion, and contralateral renal autotransplantation. The book also incorporates current insights from reconstructive, pediatric, and transplant urology. A hallmark of this work is the unique combination of didactic algorithms and rich illustrations by acclaimed medical artist Stephan Spitzer, and over 60 real-life case vignettes contributed by leading clinicians from around the world. These personal reports offer invaluable insight into the practical and often challenging decision-making required in emergency situations. Emergencies in Urology is not just a clinical reference—it is an educational tool that bridges theory and practice, experience and innovation. It is essential reading for urologists, emergency physicians, surgeons, anesthesiologists, and all healthcare professionals involved in the acute care of urological patients.

Building on the success of the first edition, this extensively revised and expanded second edition of Emergencies in Urology sets a new standard in the field. Edited by five internationally recognized experts, this authoritative textbook closes one of the last remaining gaps in urological literature: the systematic management of urgent and emergent clinical scenarios in urology. This edition reflects major advances in diagnostics, surgical techniques, and perioperative management. It includes fully updated chapters on urological trauma, urosepsis, urinary obstruction, oncological emergencies, and intra- and postoperative complications—complemented by new chapters on iatrogenic pathology, undiversion, and contralateral renal autotransplantation. The book also incorporates current insights from reconstructive, pediatric, and transplant urology. A hallmark of this work is the unique combination of didactic algorithms and rich illustrations by acclaimed medical artist Stephan Spitzer, and over 60 real-life case vignettes contributed by leading clinicians from around the world. These personal reports offer invaluable insight into the practical and often challenging decision-making required in emergency situations. Emergencies in Urology is not just a clinical reference—it is an educational tool that bridges theory and practice, experience and innovation. It is essential reading for urologists, emergency physicians, surgeons, anesthesiologists, and all healthcare professionals involved in the acute care of urological patients.

This book is an interdisciplinary study of English binominal quantitative constructions based on English-Chinese comparison. Taking three perspectives, i.e. a functional-typological perspective, a cognitive approach, and a corpus-based method, it aims to unveil the hidden categorisation process behind the usage of English binominal quantitative constructions and to reveal the language universal in cognising the concepts of ‘Quantity’ and ‘Quality’. It argues against treating Chinese and English as members of two opposing typological camps concerning quantification modes (‘classifier languages’ versus ‘non-classifier languages’) and advocates to view the two languages as lying within a more extended and inclusive system, viz. a system of quantification and categorisation modes, or a Quantity-Quality continuum.

The classical Pontryagin maximum principle (addressed to deterministic finite dimensional control systems) is one of the three milestones in modern control theory. The corresponding theory is by now well-developed in the deterministic infinite dimensional setting and for the stochastic differential equations. However, very little is known about the same problem but for controlled stochastic (infinite dimensional) evolution equations when the diffusion term contains the control variables and the control domains are allowed to be non-convex. Indeed, it is one of the longstanding unsolved problems in stochastic control theory to establish the Pontryagin type maximum principle for this kind of general control systems: this book aims to give a solution to this problem. This book will be useful for both beginners and experts who are interested in optimal control theory for stochastic evolution equations.

The classical Pontryagin maximum principle (addressed to deterministic finite dimensional control systems) is one of the three milestones in modern control theory. The corresponding theory is by now well-developed in the deterministic infinite dimensional setting and for the stochastic differential equations. However, very little is known about the same problem but for controlled stochastic (infinite dimensional) evolution equations when the diffusion term contains the control variables and the control domains are allowed to be non-convex. Indeed, it is one of the longstanding unsolved problems in stochastic control theory to establish the Pontryagin type maximum principle for this kind of general control systems: this book aims to give a solution to this problem. This book will be useful for both beginners and experts who are interested in optimal control theory for stochastic evolution equations.

This book is a practical guide to the laparoscopic and robotic surgery technique in urology. It includes 34 chapters in three sections, which are adrenal gland, kidney and ureter surgery, bladder and prostate surgery and lympadenectomy. This book covers all parts of laparoscopic and robotic urological surgery, including methods in patient selection, peri-operative management, step-by-step descriptions of specific techniques and complication avoidance. It is accompanied with over 800 illustrations and real-time capture figures. It also includes over 40 surgery videos with online access. Through the combination of texts, pictures and videos, it presents the surgical designing, surgical procedures and surgical techniques in panorama. This book is a good reference book for urologists who interested in these techniques.

This book provides a comprehensive and up-to-date account of the HPLC technology and fingerprints of commonly-used Chinese herbs. It contains HPLC fingerprints of over 40 traditional Chinese medicinal herbs and details of their sources, production and quality control. The book provides a practical review of the techniques, relevant materials, and the particular demands for using HPLC in traditional Chinese medicinal herb applications. It also covers HPLC methods used to analyze the herbs.High-performance liquid chromatography (HPLC) is increasingly used in the field of traditional Chinese medicine for obtaining fingerprints of Chinese medicinal herbs. Advantages such as high speed, high resolution, high sensitivity, stability, accuracy, and automation make it one of the leading techniques used for quality control, standardization of planting, and new drug development in traditional Chinese medicine.To date, no other books on HPLC fingerprints of traditional Chinese medicinal herbs have been published in English. This is the first book in English devoted to providing readers with state-of-the-art information on HPLC applied in the analysis of traditional Chinese medicinal herbs.

This book offers a unified introduction to low-rank Hankel methods for modern spectral signal processing, which are widely used in high-resolution radar/sonar imaging, DOA estimation and array processing, massive MIMO channel estimation, medical and astronomical imaging, and integrated sensing and communication systems. It provides a practical pathway from basic Hankel structures to state-of-the-art algorithms for spectral compressed sensing, blind super-resolution, and joint blind super-resolution and demixing. Focusing on spectrally sparse signals, the book shows how to exploit Hankel matrix and tensor structures to recover continuous-domain frequencies from few, noisy, or nonuniform samples. It explains when convex approaches based on nuclear or atomic norms guarantee exact recovery, and why they become computationally prohibitive in large-scale radar, imaging, and communication systems. Building on this foundation, the text introduces fast nonconvex schemes—projected, vanilla, scaled, and Riemannian gradient methods—that leverage low-rank factorization of Hankel (and vectorized Hankel) matrices with rigorous convergence and sample complexity guarantees. A central theme is handling realistic, “blind” scenarios where point spread functions or channels are unknown, and multi-user mixtures must be demixed before super-resolving fine spectral details. The book systematically treats these challenges, from single-measurement spectral compressed sensing to multi-measurement Hankel tensor completion and integrated sensing-and-communication style joint blind super-resolution and demixing. Throughout, theoretical insights are closely linked to algorithm design and numerical behavior, helping readers understand not only how to implement methods, but when and why they work. This volume targets advanced graduate students, researchers, and R&D engineers in signal processing, applied mathematics, radar and wireless communications, and related areas who need reliable and efficient tools for spectral compressed sensing, blind super-resolution, and demixing in high-dimensional applications.