Search for new physics via photon polarization of b→sγb \rightarrow s \gamma

We suggest a discriminant analysis of new physics beyond the standard model through a detection of photon polarization in a radiative B meson decay. This analysis is investigated in SUSY SU(5) GUT with right-handed neutrino and left-right symmetric models. New physics search via CP asymmetry in the same process are also evaluated in each model for comparison. We show that new physics can be found via detecting the photon polarization in a parameter space of TeV energy scale.Comment: 20 pages, 8 figures, v2:references added, v3:published versio

Design of continuous-time recurrent neural networks with piecewise-linear activation function for generation of prescribed sequences of bipolar vectors

A recurrent neural network (RNN) can generate a sequence of patterns as the temporal evolution of the output vector. This paper focuses on a continuous-time RNN model with a piecewise-linear activation function that has neither external inputs nor hidden neurons, and studies the problem of finding the parameters of the model so that it generates a given sequence of bipolar vectors. First, a sufficient condition for the model to generate the desired sequence is derived, which is expressed as a system of linear inequalities in the parameters. Next, three approaches to finding solutions of the system of linear inequalities are proposed: One is formulated as a convex quadratic programming problem and others are linear programming problems. Then, two types of sequences of bipolar vectors that can be generated by the model are presented. Finally, the case where the model generates a periodic sequence of bipolar vectors is considered, and a sufficient condition for the trajectory of the state vector to converge to a limit cycle is provided

A novel update rule of HALS algorithm for nonnegative matrix factorization and Zangwill’s global convergence

Nonnegative Matrix Factorization (NMF) has attracted a great deal of attention as an effective technique for dimensionality reduction of large-scale nonnegative data. Given a nonnegative matrix, NMF aims to obtain two low-rank nonnegative factor matrices by solving a constrained optimization problem. The Hierarchical Alternating Least Squares (HALS) algorithm is a well-known and widely-used iterative method for solving such optimization problems. However, the original update rule used in the HALS algorithm is not well defined. In this paper, we propose a novel well-defined update rule of the HALS algorithm, and prove its global convergence in the sense of Zangwill. Unlike conventional globally-convergent update rules, the proposed one allows variables to take the value of zero and hence can obtain sparse factor matrices. We also present two stopping conditions that guarantee the finite termination of the HALS algorithm. The practical usefulness of the proposed update rule is shown through experiments using real-world datasets

Lignin Modification by Termite and Its Symbiotic Protozoa

この論文は国立情報学研究所の学術雑誌公開支援事業により電子化されました

Neoirietriol

The title compound {systematic name: (1R,4S,4aS,7R,8aR)-4-bromo-7-[(1S,3R)-3-bromo-1,2,2-trimethyl­cyclo­pent­yl]-1,4a-dimethyl­deca­hydro­naphthalene-1,7,8a-triol}, C20H34Br2O3, is a neoirieane-type bromo­diterpenoid isolated from Laurencia yonaguniensis Masuda et Abe, species inedita. The absolute stereochemistry was established as (1S,4R,5R,7R,10S,11S,14R). The structure displays inter- and intra­molecular O—H⋯O hydrogen bonding