スタンダールと『アルマンス』 : キュリアル伯夫人をめぐって

加藤美雄教授退職記念

[3]He melting curves in high magnetic fields

Thesis (Ph. D. in Science)--University of Tsukuba, (B), no. 1752, 2001.6.30Includes bibliographical references"[3]" is superscrip

Roles for HLA and KIR polymorphisms in natural killer cell repertoire selection and modulation of effector function

Interactions between killer cell immunoglobulin-like receptors (KIRs) and human leukocyte antigen (HLA) class I ligands regulate the development and response of human natural killer (NK) cells. Natural selection drove an allele-level group A KIR haplotype and the HLA-C1 ligand to unusually high frequency in the Japanese, who provide a particularly informative population for investigating the mechanisms by which KIR and HLA polymorphism influence NK cell repertoire and function. HLA class I ligands increase the frequencies of NK cells expressing cognate KIR, an effect modified by gene dose, KIR polymorphism, and the presence of other cognate ligand–receptor pairs. The five common Japanese KIR3DLI allotypes have distinguishable inhibitory capacity, frequency of cellular expression, and level of cell surface expression as measured by antibody binding. Although KIR haplotypes encoding 3DL1*001 or 3DL1*005, the strongest inhibitors, have no activating KIR, the dominant haplotype encodes a moderate inhibitor, 3DL1*01502, plus functional forms of the activating receptors 2DL4 and 2DS4. In the population, certain combinations of KIR and HLA class I ligand are overrepresented or underrepresented in women, but not men, and thus influence female fitness and survival. These findings show how KIR–HLA interactions shape the genetic and phenotypic KIR repertoires for both individual humans and the population

Phase autoencoder for limit-cycle oscillators

We present a phase autoencoder that encodes the asymptotic phase of a limit-cycle oscillator, a fundamental quantity characterizing its synchronization dynamics. This autoencoder is trained in such a way that its latent variables directly represent the asymptotic phase of the oscillator. The trained autoencoder can perform two functions without relying on the mathematical model of the oscillator: first, it can evaluate the asymptotic phase and phase sensitivity function of the oscillator; second, it can reconstruct the oscillator state on the limit cycle in the original space from the phase value as an input. Using several examples of limit-cycle oscillators, we demonstrate that the asymptotic phase and phase sensitivity function can be estimated only from time-series data by the trained autoencoder. We also present a simple method for globally synchronizing two oscillators as an application of the trained autoencoder.Comment: 12 pages, 16 figure