Jian Ma – författare

Silicon (Si) plays a significant role in the resistance of plants to multiple stresses including biotic and abiotic stresses. Silicon is also the only element that does not damage plants when accumulated in excess. However, the contribution of Si to plant growth has been largely ignored due to its universal existence in the earth's crust. From numerous intensive studies on Si, initiated in Japan about 80 years ago, Japanese scientists realized that Si was important for the healthy growth of rice and for stability of rice production. In a worldwide first, silicon was recognized as a valuable fertilizer in Japan. The beneficial effects of Si on rice growth in particular, are largely attributable to the characteristics of a silica gel that is accumulated on the epidermal tissues in rice. These effects are expressed most clearly under high-density cultivation systems with heavy applications of nitrogen. Si is therefore recognized now as an ''agronomically essential element'' in Japan.

Recently, Si has become globally important because it generates resistance in many plants to diseases and pests, and may contribute to reduced rates of application of pesticides and fungicides. Silicon is also now considered as an environment-friendly element. The achievements of Si research in Japan are introduced in this book, in relation to soils, fertilizers and plant nutrition.

This book constitutes the proceedings of the 28th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2024, held in Cambridge, MA, USA, during April 29–May 2, 2024.The 57 full papers included in this book were carefully reviewed and selected from 352 submissions. They were organized in topical sections as follows: theoretical and foundational algorithm contributions and more applied directions that engage with new technologies and intriguing biological questions.

This book constitutes the proceedings of the 28th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2024, held in Cambridge, MA, USA, during April 29–May 2, 2024. The 57 full papers included in this book were carefully reviewed and selected from 352 submissions.

This is the first book illustrating China’s forest carbon projects. It includes an analysis of the policy and future development trends of China’s forest carbon market and showcases the country’s most representative forest carbon projects. Accordingly, it offers a valuable resource for all policymakers and researchers interested in forest carbon, as well as project developers and engineers involved in forest carbon projects.

This monograph introduces readers to new theories and methods applying cognitive computing and geometric space transformation to the field of fault diagnosis and prognostics. It summarizes the basic concepts and technical aspects of fault diagnosis and prognostics technology. Existing bottleneck problems are examined, and the advantages of applying cognitive computing and geometric space transformation are explained. In turn, the book highlights fault diagnosis, prognostic, and health assessment technologies based on cognitive computing methods, including deep learning, transfer learning, visual cognition, and compressed sensing. Lastly, it covers technologies based on differential geometry, space transformation, and pattern recognition.