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"Treasureville" - eine beschauliche Kleinstadt mit brisanten gesellschaftlichen Strukturen. Val ist inmitten eines Bandenkampfes und weiss so gar nichts über die Hintergründe, die ihre Familie dabei spielt. Ein harmloser Jungenstreich bringt sie und ihre Freunde in Gefahr. Nur die Flucht kann sie retten. Aber wohin bringt sie Ben, ihr Beschützer? Und weshalb meldet sich ihre Familie nicht? Val ist voller Fragen - sie bleibt aber zunächst ohne Antworten.
Offers a comprehensive overview of cell culture engineering, providing insight into cell engineering, systems biology approaches and processing technology In Cell Culture Engineering: Recombinant Protein Production, editors Gyun Min Lee and Helene Faustrup Kildegaard assemble top class authors to present expert coverage of topics such as: cell line development for therapeutic protein production; development of a transient gene expression upstream platform; and CHO synthetic biology. They provide readers with everything they need to know about enhancing product and bioprocess attributes using genome-scale models of CHO metabolism; omics data and mammalian systems biotechnology; perfusion cult...
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical sy...
This volume explores the latest engineering methods of mammalian cells that are useful for controlling the performance of engineered mammalian cells for future cell-based therapeutics and for better understanding of complex biological systems. The chapters in this book are organized into five parts. Part One described methods to engineer mammalian cells to sense biologically relevant inputs, such as cell contacts and soluble proteins. Part Two looks at techniques to engineer mammalian cells to sense artificial inputs, such as light and ultrasound. Part Three provides cutting-edge CRISPR-Cas-based methods to carry out highly multiplexed genome editing and spatiotemporally controlled genome ed...
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated lear...
Since the German edition of this book, the topic of risk has experienced even greater attention, not only in the world of science but also in other fields, such as economics and politics. Therefore, many new publications have evolved. To keep with the idea of an encyclopedia for the topic of risk, this book has been completely reworked. Not only are many updated examples included in chapter “Risks and disasters” but also new chapters have been introduced, such as the chapter “Indetermination and risk”. This new chapter was developed since the question “Is it possible for risks to be completely eliminated, and if not why?” has become a major point of c- cern. Therefore, especially...
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
The poetics of intertextuality proposed in this book, based mainly on semiotics, elucidates factors determining the socio-historically elusive border between general intertextuality and citationality, and explores modes of intertextual representation.
The medical MRI community is by far the largest user of diffusion NMR techniques and this book captures the current surge of methods and provides a primary source to aid adoption in this field. There is a trend to adapting the more advanced diffusion encoding sequences developed by NMR researchers within the fields of porous media, chemical engineering, and colloid science to medical research. Recently published papers indicate great potential for improved diagnosis of the numerous pathological conditions associated with changes of tissue microstructure that are invisible to conventional diffusion MRI. This book disseminates these recent developments to the wider community of MRI researchers and clinicians. The chapters cover the theoretical basis, hardware and pulse sequences, data analysis and validation, and recent applications aimed at promoting further growth in the field. This is a fast moving field and chapters are written by key MRI scientists that have contributed to the successful translation of the advanced diffusion NMR methods to the context of medical MRI, from global locations.
In order to adapt to the ever-increasing demands of telecommunication needs, today’s network operators are implementing 100 Gb/s per dense wavelength division multiplexing (DWDM) channel transmission. At those data rates, the performance of fiberoptic communication systems is degraded significantly due to intra- and inter-channel fiber nonlinearities, polarization-mode dispersion (PMD), and chromatic dispersion. In order to deal with those channel impairments, novel advanced techniques in modulation and detection, coding and signal processing are needed. This unique book represents a coherent and comprehensive introduction to the fundamentals of optical communications, signal processing and coding for optical channels. It is the first to integrate the fundamentals of coding theory with the fundamentals of optical communication.