研究者・留学生向け英文メールニュース 「Tokyo Tech Bulletin No. 69」を配信

A fully-connected annealer extendable to a multi-chip system and featuring a multi-policy mechanism has been designed by Tokyo Tech researchers to solve a broad class of combinatorial optimization (CO) problems relevant to real-world scenarios quickly and efficiently.

New insights gained by scientists at Tokyo Tech have clarified the relationship between ACE2, ALA, and the production of heme, which could pave the way to anti-viral drugs to cure COVID-19.

Tin-vacancy (Sn-V) centers in diamond have the potential to function as quantum nodes in quantum networks to transmit information. However, they pose limitations while showing optical properties to generate quantum entanglement. Tokyo Tech researchers have now overcome this challenge.

CycPeptMPDB, a novel database--created by Tokyo Tech researchers--focused on the membrane permeability of cyclic peptides, could accelerate the development of drugs based on these promising compounds. Thanks to its search and visualization capabilities, CycPeptMPDB could pave the way to new computational and machine learning methods for screening and designing drugs with cyclic peptides.

Visible-light-driven single transition metal catalysts are ideal for photoreactions. Their potential has finally been fully harnessed by researchers from Tokyo Tech, who developed a catalyst with reduced substrate dependence and increased visible light-harvesting ability.

Applying hydrostatic pressure as an external stimulus, Tokyo Tech and Keio University researchers demonstrate a new way to regulate singlet fission (SF), a process in which two electrons are generated from a single photon, in chromophores, opening doors to the design of SF-based materials with enhanced (photo)energy conversion.

Penguins generate centripetal force when turning by pointing their belly inwards and moving their wings asymmetrically, as shown by scientists at Tokyo Tech. Their findings shed light on the previously unknown mechanisms that these birds rely on to perform their underwater turns by a single wingbeat, paving the way to a more comprehensive knowledge of their swimming maneuvers.

Engineers at Tokyo Tech have demonstrated a simple computational approach for supporting the classification performance of neural networks operating on sensor time series. The proposed technique involves feeding the recorded signal as an external forcing into an elementary non-linear dynamical system, and providing its temporal responses to this disturbance to the neural network alongside the original data.

A comparison of the genomes of methane-producing microorganisms (i.e., methanogens), reveals that temperature adaptation might not be genomically encoded, but rather enforced through protein regulation and finer scale adaptations in amino acids.