Toward a systems understanding of plant–microbe interactions

Plants are closely associated with microorganisms including pathogens and mutualists that influence plant fitness. Molecular genetic approaches have uncovered a number of signaling components from both plants and microbes and their mode of actions. However, signaling pathways are highly interconnected and influenced by diverse sets of environmental factors. Therefore, it is important to have systems views in order to understand the true nature of plant–microbe interactions. Indeed, systems biology approaches have revealed previously overlooked or misinterpreted properties of the plant immune signaling network. Experimental reconstruction of biological networks using exhaustive combinatorial perturbations is particularly powerful to elucidate network structure and properties and relationships among network components. Recent advances in metagenomics of microbial communities associated with plants further point to the importance of systems approaches and open a research area of microbial community reconstruction. In this review, we highlight the importance of a systems understanding of plant–microbe interactions, with a special emphasis on reconstruction strategies

Online monitoring system and data management for KamLAND

In January 22, 2002, KamLAND started the data-taking. The KamLAND detector is a complicated system which consists of liquid scintillator, buffer oil, spherical balloon and so on. In order to maintain the detector safety, we constructed monitoring system which collect detector status information such as balloon weight, liquid scintillator oil level and so on. In addition, we constructed continuous Rn monitoring system for the $^7$Be solar neutrino detection. The KamLAND monitoring system consists of various network, LON, 1-Wire, and TCP/IP, and these are indispensable for continuous experimental data acquisition.Comment: Submitted to Nucl.Instrum.Meth.

Heterogeneity Induced Order in Globally Coupled Chaotic Systems

Collective behavior is studied in globally coupled maps with distributed nonlinearity. It is shown that the heterogeneity enhances regularity in the collective dynamics. Low-dimensional quasiperiodic motion is often found for the mean-field, even if each element shows chaotic dynamics. The mechanism of this order is due to the formation of an internal bifurcation structure, and the self-consistent dynamics between the structures and the mean-field. Keywords: Globally Coupled Map with heterogeneity, Collective behaviorComment: 11 pages (Revtex) + 4 figures (PostScript,tar+gzip