"Elegant Moriya is supposed to return to 'hakushi' after his master dies, but he demands another shot at servitude! Reckless Ryuusei lives apart from the family and refuses to use kotodama ... but he's inexplicably drawn in by Moriya's seductive power. Can a flawless kami and a twisted human find a way to come together?"--Page 4 of cover

Tears, kisses, an old paper doll -- these are all that Himi left. Calling out Himi's name so much it seemed his throat would tear open, Genma was able to bring Himi back to life! But the difference between the obstinately blushing Himi that Genma remembers, and the one before his eyes who obediently acquiesces, is irritating. Can a love that was lost come back?

Shoui has long prepared himself for the day when Asari must go away. But does their extraordinary bond go beyond mere tradition? Can a sweet, sacred promise, and shared feelings conjure a true miracle? Ze binds men and dolls in a heartrending dance of loss...and love!

"When a kotodama-sama dies, his or her kami-sama -- a healer made of living paper -- typically chooses to die as well, returning to a blank state as 'hakushi.' But when Himi's master passes away, a deep sense of obligation forces him to choose another path. Instead, Himi becomes kami-sama for his master's estranged son Genma"--Page 4 of cover

Teijin Sakuichi was born in the home of Japan's most prominent plutocrats and Kishi Ryota was born and raised in a ordinary household and lived quite a rough life. They are neighbors and have been friends since kindergarten, elementary and middle school. But, in the winter of their third year of middle school, Sakuichi proposed to Ryota before going to study abroad. Then several years later, after having no contact with Sakuichi, he suddenly appears out of nowhere...Translated by Tracy Wright; Edited by Tracy Wright; Lettered by Tracy Wright

Soft computing is the common name for a certain form of natural information processing that has its original form in biology, especially in the function of human brain. It is a discipline rooted in a group of technologies such as fuzzy logic, neural networks, chaos, genetic algorithms, probabilistic reasoning and learning algorithms. Today, soft computing has become an acknowledged concept; however, for a long time, such components of soft computing have been debated and individually developed.Since its beginning in 1990, the series of IIZUKA conferences has covered various kinds of technologies that constitute soft computing. This series has played a pioneering role in promoting the development of a symbiotic relationship between the various technologies of soft computing.At IIZUKA'98, the 5th International Conference on Soft Computing and Information/Intelligent Systems, new developments and results in this field were introduced and discussed by researchers from academic, governmental and industrial institutions around the world.This volume presents the opening lecture by Prof. Walter J Freeman, the keynote speech by Dr Gen Matsumoto, the plenary lectures by 5 eminent researchers and about 230 carefully selected papers drawn from more than 25 countries. It documents current research and in-depth studies on the fundamental aspects of soft computing and their practical applications.

High-throughput sequencing technologies are widely used to study microbial ecology across species and habitats in order to understand the impacts of microbial communities on host health, metabolism, and the environment. Due to the dynamic nature of microbial communities, longitudinal microbiome analyses play an essential role in these types of investigations. Key questions in microbiome studies aim at identifying specific microbial taxa, enterotypes, genes, or metabolites associated with specific outcomes, as well as potential factors that influence microbial communities. However, the characteristics of microbiome data, such as sparsity and skewedness, combined with the nature of data collection, reflected often as uneven sampling or missing data, make commonly employed statistical approaches to handle repeated measures in longitudinal studies inadequate. Therefore, many researchers have begun to investigate methods that could improve incorporating these features when studying clinical, host, metabolic, or environmental associations with longitudinal microbiome data. In addition to the inferential aspect, it is also becoming apparent that visualization of high dimensional data in a way which is both intelligible and comprehensive is another difficult challenge that microbiome researchers face. Visualization is crucial in both the analysis and understanding of metagenomic data. Researchers must create clear graphic representations that give biological insight without being overly complicated. Thus, this Research Topic seeks to both review and provide novels approaches that are being developed to integrate microbiome data and complex metadata into meaningful mathematical, statistical and computational models. We believe this topic is fundamental to understanding the importance of microbial communities and provides a useful reference for other investigators approaching the field.