New BPS Solitons in 2+1 Dimensional Noncommutative CP^1 Model

Investigating the solitons in the non-commutative $CP^{1}$ model, we have found a new set of BPS solitons which does not have counterparts in the commutative model.Comment: 8 pages, LaTeX2e, references added, improvements to discussions, Version to be published in JHE

Sclerite formation in the hydrothermal-vent “scaly-foot” gastropod — possible control of iron sulfide biomineralization by the animal

A gastropod from a deep-sea hydrothermal field at the Rodriguez triple junction, Indian Ocean, has scale-shaped structures, called sclerites, mineralized with iron sulfides on its foot. No other organisms are known to produce a skeleton consisting of iron sulfides. To investigate whether iron sulfide mineralization is mediated by the gastropod for the function of the sclerites, we performed a detailed physical and chemical characterization. Nanostructural characterization of the iron sulfide sclerites reveals that the iron sulfide minerals pyrite (FeS2) and greigite (Fe3S4) form with unique crystal habits inside and outside of the organic matrix, respectively. The magnetic properties of the sclerites, which are mostly consistent with those predicted from their nanostructual features, are not optimized for magnetoreception and instead support use of the magnetic minerals as structural elements. The mechanical performance of the sclerites is superior to that of other biominerals used in the vent environment for predation as well as protection from predation. These characteristics, as well as the co-occurrence of brachyuran crabs, support the inference that the mineralization of iron sulfides might be controlled by the gastropod to harden the sclerites for protection from predators. Sulfur and iron isotopic analyses indicate that sulfur and iron in the sclerites originate from hydrothermal fluids rather than from bacterial metabolites, and that iron supply is unlikely to be regulated by the gastropod for iron sulfide mineralization. We propose that the gastropod may control iron sulfide mineralization by modulating the internal concentrations of reduced sulfur compounds

Sulphur-isotopic composition of the deep-sea mussel Bathymodiolus marisindicus from currently active hydrothermal vents in the Indian Ocean

Sulphur-isotopic composition of soft tissues from bathymodiolus marisindicus collected from hydrothermal vents in the indian ocean was reported. the [delta]34s values of the soft tissues (+3[similar]+5‰ vs cañyon diablo troilite) were nearly identical to those from the associated hydrothermal fluid and chimney sulphides (+5 to +8‰), but were significantly different from that of the common seawater sulphate (+21‰), which suggested that the endosymbiotic bacteria used sulphide in the fluid as an energy source. transmission electron microscopic observation of the endosymbionts also suggested that the symbiont is a thioautotroph. bathymodiolus species, which depend on either sulphide or methane oxidation, or both, have a worldwide distribution. bathymodiolus marisindicus from the indian ocean has a close relationship with congeners in the pacific ocean as evidenced by form of symbiosis. biogeography and migration of the genus bathymodiolus based on the relevant data are briefly discussed.</p

Evolution of 3-9 Mo Stars for Z=0.001 - 0.03 and Metallicity Effects on Type Ia Supernovae

Recent observations have revealed that Type Ia supernovae (SNe Ia) are not perfect standard candles but show some variations in their absolute magnitudes, light curve shapes, and spectra. The C/O ratio in the SNe Ia progenitors (C-O white dwarfs) may be related to this variation. In this work, we systematically investigate the effects of stellar mass (M) and metallicity (Z) on the C/O ratio and its distribution in the C-O white dwarfs by calculating stellar evolution from the main-sequence through the end of the second dredge-up for M=3-9 Mo and Z=0.001-0.03. We find that the total carbon mass fraction just before SN Ia explosion varies in the range 0.36 -- 0.5. We also calculate the metallicity dependence of the main-sequence-mass range of the SN Ia progenitor white dwarfs. Our results show that the maximum main-sequence mass to form C-O white dwarfs decreases significantly toward lower metallicity, and the number of SN Ia progenitors may be underestimated if metallicity effectis neglected. We discuss the implications of these results on the variation of SNe Ia, determination of cosmological parameters, luminosity function of white dwarfs, and the galactic chemical evolution.Comment: Added references and corrected typos. To appear in the Astrophysical Journal 1999 March 10 issu

Association of Serotonin2c Receptor Polymorphisms With Antipsychotic Drug Response in Schizophrenia

There is conflicting evidence for the association between genetic polymorphisms in the serotonin (5-HT)2C receptor (HTR2C) and response to antipsychotic drugs (APD) in schizophrenic patients. We tested the association between the HTR2C polymorphisms, Cys23Ser, −759C/T, and −697G/C, and response to APDs (mainly clozapine) in a 6 month prospective study in 171 patients with schizophrenia. Ser23 was significantly associated with treatment response (positive symptoms, X2 = 7.540, p = 0.01; negative symptoms, X2 = 4.796, p = 0.03) in male patients only. A −759C-Ser23 haplotype was similar associated with positive (X2 = 6.648, p = 0.01) and negative (X2 = 6.702, p = 0.01) symptom improvement. Logistic regression, after controlling for covariates, also showed significant haplotypic associations. A meta-analysis of six studies for Ser23 and treatment response showed an overall odds ratio of 2.00 (95%CI, 1.38–2.91, p = 0.0003) or 1.94 (95%CI, 1.27–2.99, p = 0.0024) under fixed or random effect models. These results provide additional evidence that HTR2C polymorphisms are associated with treatment response to APD with HTR2C antagonism or inverse agonism, in male schizophrenic patients

Explainable AI for Ship Collision Avoidance: Decoding Decision-Making Processes and Behavioral Intentions

This study developed an explainable AI for ship collision avoidance. Initially, a critic network composed of sub-task critic networks was proposed to individually evaluate each sub-task in collision avoidance to clarify the AI decision-making processes involved. Additionally, an attempt was made to discern behavioral intentions through a Q-value analysis and an Attention mechanism. The former focused on interpreting intentions by examining the increment of the Q-value resulting from AI actions, while the latter incorporated the significance of other ships in the decision-making process for collision avoidance into the learning objective. AI's behavioral intentions in collision avoidance were visualized by combining the perceived collision danger with the degree of attention to other ships. The proposed method was evaluated through a numerical experiment. The developed AI was confirmed to be able to safely avoid collisions under various congestion levels, and AI's decision-making process was rendered comprehensible to humans. The proposed method not only facilitates the understanding of DRL-based controllers/systems in the ship collision avoidance task but also extends to any task comprising sub-tasks.Comment: 24 pases and 15 figures. If you need the program, please contuct u

Reliability Quantification of Deep Reinforcement Learning-based Control

Reliability quantification of deep reinforcement learning (DRL)-based control is a significant challenge for the practical application of artificial intelligence (AI) in safety-critical systems. This study proposes a method for quantifying the reliability of DRL-based control. First, an existing method, random noise distillation, was applied to the reliability evaluation to clarify the issues to be solved. Second, a novel method for reliability quantification was proposed to solve these issues. The reliability is quantified using two neural networks: reference and evaluator. They have the same structure with the same initial parameters. The outputs of the two networks were the same before training. During training, the evaluator network parameters were updated to maximize the difference between the reference and evaluator networks for trained data. Thus, the reliability of the DRL-based control for a state can be evaluated based on the difference in output between the two networks. The proposed method was applied to DQN-based control as an example of a simple task, and its effectiveness was demonstrated. Finally, the proposed method was applied to the problem of switching trained models depending on the state. Con-sequently, the performance of the DRL-based control was improved by switching the trained models according to their reliability.Comment: 18 pages and 17 figure