Manifold-Aware Deep Clustering: Maximizing Angles between Embedding Vectors Based on Regular Simplex

This paper presents a new deep clustering (DC) method called manifold-aware DC (M-DC) that can enhance hyperspace utilization more effectively than the original DC. The original DC has a limitation in that a pair of two speakers has to be embedded having an orthogonal relationship due to its use of the one-hot vector-based loss function, while our method derives a unique loss function aimed at maximizing the target angle in the hyperspace based on the nature of a regular simplex. Our proposed loss imposes a higher penalty than the original DC when the speaker is assigned incorrectly. The change from DC to M-DC can be easily achieved by rewriting just one term in the loss function of DC, without any other modifications to the network architecture or model parameters. As such, our method has high practicability because it does not affect the original inference part. The experimental results show that the proposed method improves the performances of the original DC and its expansion method.Comment: Accepted by Interspeech 202

Metabolic design of Escherichia coli for muconic acid production

Adipic acid(AA) is a versatile bulk chemical to be used for raw materials such as nylon 6,6. Currently, AA biosynthesis from bio-resources have received a lot of attention in recent years as environment-friendly and renewable AA production process. Muconic acid(MA), also known as 2,4-hexadienedioic acid, is expected as a biosynthesis precursor of AA. There are Several studies on MA biosynthesis using Escherichia coli introduced foreign genes. In those studies, MA is synthesized from intermediate products of shikimate pathway. However, the production volume is not sufficient and it is a hindrance to industrialization. In this study, we aimed to the high efficiency biosynthesis of MA using metabolic designed Escherichia coli. First, we designed the metabolism to increase the accumulation of phosphoenolpyruvic acid (PEP), which is one of the starting materials of the shikimate pathway. Next, we determined the optimal MA synthetic pathway branched from the shikimate pathway. Specifically, we examined three types of MA production pathway with PEP accumulation strain as parent and selected the pathway with the highest MA production. Finally, we examined efficient production of MA using fusion proteins. Shikimate pathway protein and MA production pathway protein were combined to direct carbon flux into MA production

Exploring the circumstellar environment of Tycho's supernova remnant--I. The hydrodynamic evolution of the shock

Among Type Ia supernova remnants (SNRs), Tycho's SNR has been considered as a typical object from the viewpoints of its spectroscopic, morphological and environmental properties. A recent reanalysis of Chandra data shows that its forward shock is experiencing a substantial deceleration since around 2007, which suggests recent shock interactions with a dense medium as a consequence of the cavity-wall environment inside a molecular cloud. Such a non-uniform environment can be linked back to the nature and activities of its progenitor. In this study, we perform hydrodynamic simulations to characterize Tycho's cavity-wall environment using the latest multi-epoch proper motion measurements of the forward shock. A range of parameters for the environment is explored in the hydrodynamic models to fit with the observation data for each azimuthal region. Our results show that a wind-like cavity with $\rho(r)\propto r^{-2}$ reconciles with the latest data better than a uniform medium with a constant density. In addition, our best-fit model favors an anisotropic wind with an azimuthally varying wind parameter. The overall result indicates a mass-loss rate which is unusually high for the conventional single-degenerate explosion scenario.Comment: 13 pages, 9 figures, 1 table, accepted for publication in Ap

Exploring the Circumstellar Environment of Tycho's Supernova Remnant. I. The Hydrodynamic Evolution of the Shock

Among Type Ia supernova remnants (SNRs), Tycho's SNR has been considered as a typical object from the viewpoints of its spectroscopic, morphological, and environmental properties. A recent reanalysis of Chandra data showed that its forward shock is experiencing a substantial deceleration since around 2007, which suggests recent shock interactions with a dense medium as a consequence of a cavity-wall environment inside a molecular cloud. Such a nonuniform environment can be linked back to the nature and activities of its progenitor. In this study, we perform hydrodynamic simulations to characterize Tycho's cavity-wall environment using the latest multiepoch proper motion measurements of the forward shock. A range of parameters for the environment is explored in the hydrodynamic models to fit with the observational data for each azimuthal region. Our results show that a wind-like cavity with ρ(r) ∝ r⁻² reconciles with the latest data better than a uniform medium with a constant density. In addition, our best-fit model favors an anisotropic wind with an azimuthally varying wind parameter. The overall result indicates a mass-loss rate which is unusually high for the conventional single-degenerate explosion scenario