李良枝研究 -民族的アイデンティティを超えて-

早大学位記番号:新7915早稲田大

Enhanced Precision Time Synchronization for Wireless Sensor Networks

Time synchronization in wireless sensor networks (WSNs) is a fundamental issue for the coordination of distributed entities and events. Nondeterministic latency, which may decrease the accuracy and precision of time synchronization can occur at any point in the network layers. Specially, random back-off by channel contention leads to a large uncertainty. In order to reduce the large nondeterministic uncertainty from channel contention, we propose an enhanced precision time synchronization protocol in this paper. The proposed method reduces the traffic needed for the synchronization procedure by selectively forwarding the packet. Furthermore, the time difference between sensor nodes increases as time advances because of the use of a clock source with a cheap crystal oscillator. In addition, we provide a means to maintain accurate time by adopting hardware-assisted time stamp and drift correction. Experiments are conducted to evaluate the performance of the proposed method, for which sensor nodes are designed and implemented. According to the evaluation results, the performance of the proposed method is better than that of a traditional time synchronization protocol

Sustained, Photocatalytic CO₂ Reduction to CH₄ in a Continuous Flow Reactor by Earth-Abundant Materials: Reduced Titania-Cu₂O Z-Scheme Heterostructures

Photocatalytic conversion of CO₂ and water vapor to hydrocarbon fuels is a promising approach for storing solar energy while reducing greenhouse gas emissions. However, still certain issues including low product yields, limited photocatalyst stability and relatively high cost have hampered practical implementation of this technology. In the present work, a unique strategy is adopted to synthesize a stable, and inexpensive photocatalyst comprised of earth-abundant materials: a reduced titania-Cu₂O Z-scheme heterostructure. Under illumination for 6 h, the optimized reduced titania-Cu₂O photocatalyst enables 0.13 % photoreduction of highly diluted CO₂ with water vapors to 462nmol g⁻¹ of CH₄ while showing excellent stability over seven testing cycles (42 h). Our studies show the Z-scheme inhibits Cu₂O photocorrosion, while its synergistic effects with reduced titania result in sustained CH₄ formation in a continuous flow photoreactor. To the best of our knowledge stability exhibited by the reduced titania-Cu₂O Z-scheme is the highest for any Cu-based photocatalyst

CO_2, water, and sunlight to hydrocarbon fuels: a sustained sunlight to fuel (Joule-to-Joule) photoconversion efficiency of 1%

If we wish to sustain our terrestrial ecosphere as we know it, then reducing the concentration of atmospheric CO_2 is of critical importance. An ideal pathway for achieving this would be the use of sunlight to recycle CO_2, in combination with water, into hydrocarbon fuels compatible with our current energy infrastructure. However, while the concept is intriguing such a technology has not been viable due to the vanishingly small CO_2-to-fuel photoconversion efficiencies achieved. Herein we report a photocatalyst, reduced blue-titania sensitized with bimetallic Cu–Pt nanoparticles that generates a substantial amount of both methane and ethane by CO_2 photoreduction under artificial sunlight (AM1.5): over a 6 h period 3.0 mmol g^(−1) methane and 0.15 mmol g^(−1) ethane are obtained (on an area normalized basis 0.244 mol m^(−2) methane and 0.012 mol m^(−2) ethane), while no H_2 nor CO is detected. This activity (6 h) translates into a sustained Joule (sunlight) to Joule (fuel) photoconversion efficiency of 1%, with an apparent quantum efficiency of φ = 86%. The time-dependent photoconversion efficiency over 0.5 h intervals yields a maximum value of 3.3% (φ = 92%). Isotopic tracer experiments confirm the hydrocarbon products originate from CO_2 and water

Lactobacillus sakei suppresses collagen-induced arthritis and modulates the differentiation of T helper 17 cells and regulatory B cells

Abstract Background To evaluate the immunomodulatory effect of Lactobacillus sakei in a mouse model of rheumatoid arthritis (RA) and in human immune cells. Methods We evaluated whether L. sakei reduced the severity of collagen-induced arthritis (CIA) and modulated interleukin (IL)-17 and IL-10 levels, as well as whether it affected the differentiation of CD4+ T cells and regulatory B cells. We evaluated osteoclastogenesis after culturing bone marrow-derived mononuclear cells with L. sakei. Results The differentiation of T helper 17 cells and the serum level of IL-17 were suppressed by L. sakei in both human peripheral blood mononuclear cells and mouse splenocytes. The serum level of IL-10 was significantly increased in the L. sakei-treated group, whereas the regulatory T cell population was unchanged. The population of regulatory B cells significantly increased the in L. sakei-treated group. Oral administration of L. sakei reduced the arthritis incidence and score in mice with CIA. Finally, osteoclastogenesis and the mRNA levels of osteoclast-related genes were suppressed in the L. sakei-treated group. Conclusion L. sakei exerted an anti-inflammatory effect in an animal model of RA, regulated Th17 and regulatory B cell differentiation, and suppressed osteoclastogenesis. Our findings suggest that L. sakei has therapeutic potential for RA

Practical Particulate Matter Sensing and Accurate Calibration System Using Low-Cost Commercial Sensors

Air pollution is a social problem, because the harmful suspended materials can cause diseases and deaths to humans. Specifically, particulate matters (PM), a form of air pollution, can contribute to cardiovascular morbidity and lung diseases. Nowadays, humans are exposed to PM pollution everywhere because it occurs in both indoor and outdoor environments. To purify or ventilate polluted air, one need to accurately monitor the ambient air quality. Therefore, this study proposed a practical particulate matter sensing and accurate calibration system using low-cost commercial sensors. The proposed system basically uses noisy and inaccurate PM sensors to measure the ambient air pollution. This paper mainly deals with three types of error caused in the light scattering method: short-term noise, part-to-part variation, and temperature and humidity interferences. We propose a simple short-term noise reduction method to correct measurement errors, an auto-fitting calibration for part-to-part repeatability to pinpoint the baseline of the signal that affects the performance of the system, and a temperature and humidity compensation method. This paper also contains the experiment setup and performance evaluation to prove the superiority of the proposed methods. Based on the evaluation of the performance of the proposed system, part-to-part repeatability was less than 2 μg/m3 and the standard deviation was approximately 1.1 μg/m3 in the air. When the proposed approaches are used for other optical sensors, it can result in better performance