Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.

This book constitutes the refereed conference proceedings of the 6th International Symposium on Emerging Technologies for Education, SETE 2021, held in Zhuhai, China in November 2021. 35 full papers were accepted together with 8 short papers out of 58 submissions. The papers focus on the following subjects: Emerging Technologies for Education, Digital Technology, Creativity, and Education; Education Technology (Edtech) and ICT for Education; Education + AI; Adaptive Learning, Emotion and Behaviour Recognition and Understanding in Education; as well as papers from the International Symposium on User Modeling and Language Learning (UMLL2021) and the International Workshop on Educational Technology for Language Learning (ETLL 2021).

Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.

The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows: Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.

The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows: Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.

The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows: Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.

The study of vertebrate embryonic development became a separate science in the early 1800s thanks to advances in microscopy. Embryologists collected and dissected specimens from chicken, frogs, turtles, fish, mice as well as humans, observed and documented the anatomy and physiology. These largely observatory work produced many of the important concepts in modern developmental biology, such as germ layers (von Baer, 1828), the theory of natural selection (Darwin, 1859), and the Organizer (Spemann and Mangold, 1934). After World War II, especially after the demonstration of DNA as the genetic material and advancement in recombinant DNA technology, the focus of studies shifted to the cellular, molecular and genetic processes of development, the mechanisms of regulation, and the basis for developmental defects and diseases. In recent years, advancements in stem cell biology and gene editing technology ushered vertebrate embryology into a new era as scientists use the tools and paradigms of embryonic development to tackle diseases of all ages, bridging the embryo and the adult. There is a vast body of research on vertebrate embryology, enough to fill a whole library. It is not the goal of this book to provide a comprehensive picture. Rather, I draw an extremely simplified sketch, a "tasting menu", of current research topics. The book is organized into five sections. Section 1 illustrates a number of major research questions on the three developmental stages - cleavage, gastrulation, and organogenesis. Section 2 presents the frontiers in the study of genetic and epigenetic regulation: the role of genetic interactions, chromatin-based regulation, and non-coding RNAs. Section 3 describes the current research and application of stem cells. Section 4 introduces the role of genetic and environmental factors in developmental defects. Finally, Section 5 highlights the exciting new field of gene editing, using TALENs and CRISPR/Cas9 technologies as two examples.

Genetic diversity, or the variety of genes within a species, plays important roles in phenotypic diversity and the species' ability to adapt to environments. Studies of genetic diversity mainly focus on two areas. The first area is concerned with understanding and characterizing genetic diversity in humans, animals, plants, and microbes. The second focus area is exploiting genetic diversity for the purposes of medicine, agriculture, and conservation. To help readers appreciate the wide range of research questions on genetic diversity and how molecular approaches are utilized to address these questions, this book is organized into three chapters to showcase selected studies of genetic diversity in humans, animals and plants, and microbes, respectively. The post-genomic era provides powerful tools for the studies of genetic diversity. For example, as of 2016, the single nucleotide polymorphism (SNP) database maintained by the National Center for Biotechnology Information (NCBI) lists ~150 million SNPs. The huge amount of available genomic information greatly facilitates genome-wide association studies (GWAS). GWAS has been applied to the studies of various human diseases including cancer, heart diseases and diabetes. In agriculture, GWAS is used to identify genomic regions associated with desirable breeding traits in cattle or agronomic traits in plants. Thanks to the advancement in sequencing technology, it has become feasible and increasingly routine to sequence multi-gene panels, exomes, and whole genomes. These approaches are being widely used for the investigation of genetic variants-of-interest as well as genetic diagnosis. Gene panels offer a quick way to interrogate a panel of genes that are known to be associated with a specific disease or condition. Compared to sequencing of gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS) cost more for each sample but generate much larger amount of data such that the cost per variant is significantly less. By interrogating millions of variants per genome, WES/WGS can be very powerful in identify new variants that are associated with diseases, disease risks, or prognosis. Another important technological development is gene editing technology. Genetic diversity in plants and animals provide the raw material for crop and livestock breeders, respectively. Gene editing technology greatly enhances the efficiency of breeding by allowing breeders to create transgenic elite lines and manipulate multiple loci simultaneously.