Tokyo Institute of Technology

About: Tokyo Institute of Technology is a education organization based out in Tokyo, Tôkyô, Japan. It is known for research contribution in the topics: Thin film & Catalysis. The organization has 46775 authors who have published 101656 publications receiving 2357893 citations. The organization is also known as: Tokyo Tech & Tokodai.

Mechanistic insights into photodegradation of organic dyes using heterostructure photocatalysts

Abstract: Due to its low cost, environmentally friendly process, and lack of secondary contamination, the photodegradation of dyes is regarded as a promising technology for industrial wastewater treatment. This technology demonstrates the light-enhanced generation of charge carriers and reactive radicals that non-selectively degrade various organic dyes into water, CO2, and other organic compounds via direct photodegradation or a sensitization-mediated degradation process. The overall efficiency of the photocatalysis system is closely dependent upon operational parameters that govern the adsorption and photodegradation of dye molecules, including the initial dye concentration, pH of the solution, temperature of the reaction medium, and light intensity. Additionally, the charge-carrier properties of the photocatalyst strongly affect the generation of reactive species in the heterogeneous photodegradation and thereby dictate the photodegradation efficiency. Herein, this comprehensive review discusses the pseudo kinetics and mechanisms of the photodegradation reactions. The operational factors affecting the photodegradation of either cationic or anionic dye molecules, as well as the charge-carrier properties of the photocatalyst, are also fully explored. By further analyzing past works to clarify key active species for photodegradation reactions and optimal conditions, this review provides helpful guidelines that can be applied to foster the development of efficient photodegradation systems.

Fermi Observations of GRB 090902B: A Distinct Spectral Component in the Prompt and Delayed Emission

Abstract: We report on the observation of the bright, long gamma-ray burst (GRB), GRB 090902B, by the Gamma-ray Burst Monitor (GBM) and Large Area Telescope (LAT) instruments on-board the Fermi observatory. ...

12-oxo-phytodienoic acid triggers expression of a distinct set of genes and plays a role in wound-induced gene expression in Arabidopsis.

Abstract: Jasmonic acid (JA) and methyl jasmonate (MeJA), collectively known as JAs, regulate diverse physiological processes in plants, including the response to wounding. Recent reports suggest that a cyclopentenone precursor of JA, 12-oxo-phytodienoic acid (OPDA), can also induce gene expression. However, little is known about the physiological significance of OPDA-dependent gene expression. We used microarray analysis of approximately 21,500 Arabidopsis (Arabidopsis thaliana) genes to compare responses to JA, MeJA, and OPDA treatment. Although many genes responded identically to both OPDA and JAs, we identified a set of genes (OPDA-specific response genes [ORGs]) that specifically responded to OPDA but not to JAs. ORGs primarily encoded signaling components, transcription factors, and stress response-related genes. One-half of the ORGs were induced by wounding. Analysis using mutants deficient in the biosynthesis of JAs revealed that OPDA functions as a signaling molecule in the wounding response. Unlike signaling via JAs, OPDA signaling was CORONATINE INSENSITIVE 1 independent. These results indicate that an OPDA signaling pathway functions independently of JA/MeJA signaling and is required for the wounding response in Arabidopsis.

A widely applicable Bayesian information criterion

Abstract: A statistical model or a learning machine is called regular if the map taking a parameter to a probability distribution is one-to-one and if its Fisher information matrix is always positive definite. If otherwise, it is called singular. In regular statistical models, the Bayes free energy, which is defined by the minus logarithm of Bayes marginal likelihood, can be asymptotically approximated by the Schwarz Bayes information criterion (BIC), whereas in singular models such approximation does not hold. Recently, it was proved that the Bayes free energy of a singular model is asymptotically given by a generalized formula using a birational invariant, the real log canonical threshold (RLCT), instead of half the number of parameters in BIC. Theoretical values of RLCTs in several statistical models are now being discovered based on algebraic geometrical methodology. However, it has been difficult to estimate the Bayes free energy using only training samples, because an RLCT depends on an unknown true distribution. In the present paper, we define a widely applicable Bayesian information criterion (WBIC) by the average log likelihood function over the posterior distribution with the inverse temperature 1/log n, where n is the number of training samples. We mathematically prove that WBIC has the same asymptotic expansion as the Bayes free energy, even if a statistical model is singular for or unrealizable by a statistical model. Since WBIC can be numerically calculated without any information about a true distribution, it is a generalized version of BIC onto singular statistical models.

Nb2O5·nH2O as a heterogeneous catalyst with water-tolerant Lewis acid sites.

Abstract: Niobic acid, Nb(2)O(5)·nH(2)O, has been studied as a heterogeneous Lewis acid catalyst. NbO(4) tetrahedra, Lewis acid sites, on Nb(2)O(5)·nH(2)O surface immediately form NbO(4)-H(2)O adducts in the presence of water. However, a part of the adducts can still function as effective Lewis acid sites, catalyzing the allylation of benzaldehyde with tetraallyl tin and the conversion of glucose into 5-(hydroxymethyl)furfural in water.