Search

This study systematically investigates the effects of high-power continuous wave laser (CWL) treatment on the mechanical behavior and failure mechanisms of SM400A steel, comparing these outcomes with those of untreated specimens. The findings reveal that while CWL treatment enhances surface hardness, it has minimal impact on the strength of thick structural steel components. However, excessive laser energy density leads to surface defects and softening of the microstructure, adversely affecting the material's toughness. This results in a reduction in elongation at fracture, transitioning the failure mode from ductile to brittle. The study concludes that to ensure the safe use of laser-treated structures, the laser energy density should be carefully controlled not to exceed 3000 J/cm2.

The growth of network-connected devices has led to an exponential increase in data generation, creating significant challenges for efficient data analysis. This data is generated continuously, creating a dynamic flow known as a data stream. The characteristics of a data stream may change dynamically, and this change is known as concept drift. Consequently, a method for handling data streams must efficiently reduce their volume while dynamically adapting to these changing characteristics. This article proposes a simple online vector quantization method for concept drift. The proposed method identifies and replaces units with low win probability through remove-birth updating, thus achieving a rapid adaptation to concept drift. Furthermore, the results of this study show that the proposed method can generate minimal dead units even in the presence of concept drift. This study also suggests that some metrics calculated from the proposed method will be helpful for drift detection.

Planetary protection is a guiding principle aiming to prevent microbial contamination of the solar system by spacecraft (forward contamination) and extraterrestrial contamination of the Earth (backward contamination). Bioburden reduction on spacecraft, including cruise and landing systems, is required to prevent microbial contamination from Earth during space exploration missions. Several sterilization methods are available; however, selecting appropriate methods is essential to eliminate a broad spectrum of microorganisms without damaging spacecraft components during manufacturing and assembly. Here, we compared the effects of different bioburden reduction techniques, including dry heat, UV light, isopropyl alcohol (IPA), hydrogen peroxide (H2O2), vaporized hydrogen peroxide (VHP), and oxygen and argon plasma on microorganisms with different resistance capacities. These microorganisms included Bacillus atrophaeus spores and Aspergillus niger spores, Deinococcus radiodurans, and Brevundimonas diminuta, all important microorganisms for considering planetary protection. Bacillus atrophaeus spores showed the highest resistance to dry heat but could be reliably sterilized (i.e., under detection limit) through extended time or increased temperature. Aspergillus niger spores and D. radiodurans were highly resistant to UV light. Seventy percent of IPA and 7.5% of H2O2 treatments effectively sterilized D. radiodurans and B. diminuta but showed no immediate bactericidal effect against B. atrophaeus spores. IPA immediately sterilized A. niger spores, but H2O2 did not. During VHP treatment under reduced pressure, viable B. atrophaeus spores and A. niger spores were quickly reduced by approximately two log orders. Oxygen plasma sterilized D. radiodurans but did not eliminate B. atrophaeus spores. In contrast, argon plasma sterilized B. atrophaeus but not D. radiodurans. Therefore, dry heat could be used for heat-resistant component bioburden reduction, and VHP or plasma for non-heat-resistant components in bulk bioburden reduction. Furthermore, IPA, H2O2, or UV could be used for additional surface bioburden reduction during assembly and testing. The systemic comparison of sterilization efficiencies under identical experimental conditions in this study provides basic criteria for determining which sterilization techniques should be selected during bioburden reduction for forward planetary protection.

Artificial intelligence (AI) has achieved superhuman performance in board games such as Go, chess, and Othello (Reversi). In other words, the AI system surpasses the level of a strong human expert player in such games. In this context, it is difficult for a human player to enjoy playing the games with the AI. To keep human players entertained and immersed in a game, the AI is required to dynamically balance its skill with that of the human player. To address this issue, we propose AlphaDDA, an AlphaZero-based AI with dynamic difficulty adjustment (DDA). AlphaDDA consists of a deep neural network (DNN) and a Monte Carlo tree search, as in AlphaZero. AlphaDDA learns and plays a game the same way as AlphaZero, but can change its skills. AlphaDDA estimates the value of the game state from only the board state using the DNN. AlphaDDA changes a parameter dominantly controlling its skills according to the estimated value. Consequently, AlphaDDA adjusts its skills according to a game state. AlphaDDA can adjust its skill using only the state of a game without any prior knowledge regarding an opponent. In this study, AlphaDDA plays Connect4, Othello, and 6x6 Othello with other AI agents. Other AI agents are AlphaZero, Monte Carlo tree search, the minimax algorithm, and a random player. This study shows that AlphaDDA can balance its skill with that of the other AI agents, except for a random player. AlphaDDA can weaken itself according to the estimated value. However, AlphaDDA beats the random player because AlphaDDA is stronger than a random player even if AlphaDDA weakens itself to the limit. The DDA ability of AlphaDDA is based on an accurate estimation of the value from the state of a game. We believe that the AlphaDDA approach for DDA can be used for any game AI system if the DNN can accurately estimate the value of the game state and we know a parameter controlling the skills of the AI system.

Spectral clustering (SC) is one of the most popular clustering methods and often outperforms traditional clustering methods. SC uses the eigenvectors of a Laplacian matrix calculated from a similarity matrix of a dataset. SC has serious drawbacks: the significant increases in the time complexity derived from the computation of eigenvectors and the memory space complexity to store the similarity matrix. To address the issues, I develop a new approximate spectral clustering using the network generated by growing neural gas (GNG), called ASC with GNG in this study. ASC with GNG uses not only reference vectors for vector quantization but also the topology of the network for extraction of the topological relationship between data points in a dataset. ASC with GNG calculates the similarity matrix from both the reference vectors and the topology of the network generated by GNG. Using the network generated from a dataset by GNG, ASC with GNG achieves to reduce the computational and space complexities and improve clustering quality. In this study, I demonstrate that ASC with GNG effectively reduces the computational time. Moreover, this study shows that ASC with GNG provides equal to or better clustering performance than SC.

Direct observation of the lithiation and de-lithiation in lithium batteries on the component and microstructural scale is still difficult. This work presents recent advances in MeV ion-beam analysis, enabling quantitative contact-free analysis of the spatially-resolved lithium content and state-of-charge (SoC) in all-solid-state lithium batteries via 3 MeV proton-based characteristic x-ray and gamma-ray emission analysis. The analysis is demonstrated on cross-sections of ceramic and polymer all-solid-state cells with LLZO and MEEP/LIBOB solid electrolytes. Different SoC are measured ex-situ and one polymer-based operando cell is charged at 333 K during analysis. The data unambiguously show the migration of lithium upon charging. Quantitative lithium concentrations are obtained by taking the physical and material aspects of the mixed cathodes into account. This quantitative lithium determination as a function of SoC gives insight into irreversible degradation phenomena of all-solid-state batteries during the first cycles and locations of immobile lithium. The determined SoC matches the electrochemical characterization within uncertainties. The presented analysis method thus opens up a completely new access to the state-of-charge of battery cells not depending on electrochemical measurements. Automated beam scanning and data-analysis algorithms enable a 2D quantitative Li and SoC mapping on the µm-scale, not accessible with other methods.

The aim of this study was to assess the effect of tadalafil (0.5, 2.5, and 10 mg/kg per day) on the progression of pulmonary arterial hypertension (PAH) in early treatment and on the survival rate in late treatment on the monocrotaline (MCT)-induced PAH rat model. Tadalafil was administered once daily to rats for 3 weeks from the day of MCT-injection or 21 days after the injection. With early treatment, tadalafil at 10 mg/kg per day prevented the development of PAH by maintaining mean pulmonary artery pressure within the normal range and attenuated right ventricular hypertrophy. With late treatment, tadalafil tended to increase the partial pressure of oxygen in arterial blood and dose-dependently improved the survival rate by 55%, 60%, and 70% at 0.5, 2.5, and 10 mg/kg per day, respectively, versus 40% in the MCT-control group. Both early and late treatments with tadalafil were associated with elevated lung cyclic guanosine monophosphate (cGMP). These results suggest that tadalafil relaxes pulmonary arteries by elevating cGMP in lungs and extend survival time by improving pulmonary hemodynamics even when treatment occurs in the late phase of PAH. Thus, it is expected that tadalafil may be an effective, once-daily treatment option in humans with PAH. Keywords:: tadalafil, phosphodiesterase 5 (PDE5) inhibitor, pulmonary artery hypertension (PAH), monocrotaline (MCT), survival

This paper reports the development of a 10Ah lithium-ion pouch battery cell using stainless-steel laminated film as the casing material for JAXA's SLIM lunar lander. By selecting the pouch format, the mass ratio of the case and electrode terminals is significantly reduced, which is superior to conventional space batteries using prismatic metal cases. A high specific energy of approximately 130Wh/kg was achieved. In addition, unlike standard batteries using aluminumlaminated film, the battery developed during this study deforms little when subjected to a vacuum. It can thus be mounted on a spacecraft with a simple, lightweight bracket, contributing to higher specific energy as a module. This paper reports the results of environment tests for the SLIM mission and the basic electrical characteristics of the battery. [ABSTRACT FROM AUTHOR]