This book emphasizes and presents the latest information on eco-physiology and biochemistry of cyanobacteria with special emphasis on their biodiversity, molecular mechanisms of some important biological processes and survival mechanisms under myriad of environmental conditions as well as bioremediation. Cyanobacteria are the most dominant prokaryotic floras on the Earth's surface, and are of great importance in terms of ecological, economical and evolutionary perspectives. They are oldest groups of photosynthetic autotrophs, which create oxygenic atmosphere for the development and sustainability of ecosystems with different life forms. The book presents an integrative approach to their possible biotechnological application in the field of bio-energy and various aspects of biochemistry, biophysics and structural biology of photosynthesis. The various chapters describe the different applications of cyanobacteria as bio-energy sources and in phycoremediation. The contents incorporated in this book can be used as a textbook by undergraduate and post-graduate students, teachers, and researchers in the most interesting fields of physicochemical ecology and biochemistry of cyanobacteria.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.