23 research outputs found

    Detection of Recurrence by 18F-FDG PET in Patients with Endometrial Cancer Showing No Evidence of Disease

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    This study assessed the feasibility of F-18-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) in the post-therapy surveillance for patients with endometrial cancer showing no evidence of disease (NED). From April 1997 to June 2007, 127 patients with endometrial cancer showing NED were performed 18F-FDG PET scan. The feasibility of 18F-FDG PET for the early detection of recurrence in patients with endometrial cancer was evaluated retrospectively. Of the 127 patients, 32 patients showed positive lesions on 18F-FDG PET scan. Nineteen (19/127 cases, 15%) of them were confirmed to have a recurrence clinically or histologically. The sensitivity, specificity and positive and negative predictive value of 18F-FDG PET for detecting recurrences in patients with endometrial cancer were 100%, 88%, 59% and 100%, respectively. In conclusion, 18F-FDG PET may be a useful method for the post-therapy surveillance in patients with endometrial cancer

    Limitations in representation of physical processes preven successful simulation of PM2.5 during KORUS-AQ

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    High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements

    Characterization, sources and reactivity of volatile organic compounds (VOCs) in Seoul and surrounding regions during KORUS-AQ

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    The Korea-United States Air Quality Study (KORUS-AQ) took place in spring 2016 to better understand air pollution in Korea. In support of KORUS-AQ, 2554 whole air samples (WAS) were collected aboard the NASA DC-8 research aircraft and analyzed for 82 C₁–C₁₀ volatile organic compounds (VOCs) using multi-column gas chromatography. Together with fast-response measurements from other groups, the air samples were used to characterize the VOC composition in Seoul and surrounding regions, determine which VOCs are major ozone precursors in Seoul, and identify the sources of these reactive VOCs. (1) The WAS VOCs showed distinct signatures depending on their source origins. Air collected over Seoul had abundant ethane, propane, toluene and n-butane while plumes from the Daesan petrochemical complex were rich in ethene, C₂–C₆ alkanes and benzene. Carbonyl sulfide (COS), CFC-113, CFC-114, carbon tetrachloride (CCl₄) and 1,2-dichloroethane were good tracers of air originating from China. CFC-11 was also elevated in air from China but was surprisingly more elevated in air over Seoul. (2) Methanol, isoprene, toluene, xylenes and ethene were strong individual contributors to OH reactivity in Seoul. However methanol contributed less to ozone formation based on photochemical box modeling, which better accounts for radical chemistry. (3) Positive Matrix Factorization (PMF) and other techniques indicated a mix of VOC source influences in Seoul, including solvents, traffic, biogenic, and long-range transport. The solvent and traffic sources were roughly equal using PMF, and the solvents source was stronger in the KORUS-AQ emission inventory. Based on PMF, ethene and propene were primarily associated with traffic, and toluene, ethylbenzene and xylenes with solvents, especially non-paint solvents for toluene and paint solvents for ethylbenzene and xylenes. This suggests that VOC control strategies in Seoul could continue to target vehicle exhaust and paint solvents, with additional regulations to limit the VOC content in a variety of non-paint solvents

    Characterization, sources and reactivity of volatile organic compounds (VOCs) in Seoul and surrounding regions during KORUS-AQ

    Get PDF
    The Korea-United States Air Quality Study (KORUS-AQ) took place in spring 2016 to better understand air pollution in Korea. In support of KORUS-AQ, 2554 whole air samples (WAS) were collected aboard the NASA DC-8 research aircraft and analyzed for 82 C₁–C₁₀ volatile organic compounds (VOCs) using multi-column gas chromatography. Together with fast-response measurements from other groups, the air samples were used to characterize the VOC composition in Seoul and surrounding regions, determine which VOCs are major ozone precursors in Seoul, and identify the sources of these reactive VOCs. (1) The WAS VOCs showed distinct signatures depending on their source origins. Air collected over Seoul had abundant ethane, propane, toluene and n-butane while plumes from the Daesan petrochemical complex were rich in ethene, C₂–C₆ alkanes and benzene. Carbonyl sulfide (COS), CFC-113, CFC-114, carbon tetrachloride (CCl₄) and 1,2-dichloroethane were good tracers of air originating from China. CFC-11 was also elevated in air from China but was surprisingly more elevated in air over Seoul. (2) Methanol, isoprene, toluene, xylenes and ethene were strong individual contributors to OH reactivity in Seoul. However methanol contributed less to ozone formation based on photochemical box modeling, which better accounts for radical chemistry. (3) Positive Matrix Factorization (PMF) and other techniques indicated a mix of VOC source influences in Seoul, including solvents, traffic, biogenic, and long-range transport. The solvent and traffic sources were roughly equal using PMF, and the solvents source was stronger in the KORUS-AQ emission inventory. Based on PMF, ethene and propene were primarily associated with traffic, and toluene, ethylbenzene and xylenes with solvents, especially non-paint solvents for toluene and paint solvents for ethylbenzene and xylenes. This suggests that VOC control strategies in Seoul could continue to target vehicle exhaust and paint solvents, with additional regulations to limit the VOC content in a variety of non-paint solvents

    OH reactivity in urban and suburban regions in Seoul, South Korea – an East Asian megacity in a rapid transition

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    South Korea has recently achieved developed country status with the second largest megacity in the world, the Seoul Metropolitan Area (SMA). This study provides insights into future changes in air quality for rapidly emerging megacities in the East Asian region. We present total OH reactivity observations in the SMA conducted at an urban Seoul site (May-June, 2015) and a suburban forest site (Sep, 2015). The total OH reactivity in an urban site during the daytime was observed at similar levels (∼15 s(-1)) to those previously reported from other East Asian megacity studies. Trace gas observations indicate that OH reactivity is largely accounted for by NOX (∼50%) followed by volatile organic compounds (VOCs) (∼35%). Isoprene accounts for a substantial fraction of OH reactivity among the comprehensive VOC observational dataset (25-47%). In general, observed total OH reactivity can be accounted for by the observed trace gas dataset. However, observed total OH reactivity in the suburban forest area cannot be largely accounted for (∼70%) by the trace gas measurements. The importance of biogenic VOC (BVOCs) emissions and oxidations used to evaluate the impacts of East Asian megacity outflows for the regional air quality and climate contexts are highlighted in this study

    High temperature torsion behavior of austenitic high Mn steels

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    Effective Modeling on Learning Ballet Online

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    After COVID-19, face-to-face learning was changed to online learning. However, very few effective online learning methods were available regarding physical education. Therefore, this study aimed to examine the modeling effects on learning ballet movement in the online system. We aimed to find effective modeling presentations based on objective information, expert assessments, and a kinematic approach. The study included 36 individuals who were divided into an expert modeling group, a self-modeling group, and controls. Participants performed 60 trials of Pas de basque in the acquisition phase and 10 trials without a demonstration video after 24 h. 10 min later, the reversed Pas de basque was conducted for the retention test. All groups showed improved performance after the acquisition phase, which indicated that the modeling presentation was effective despite adopting an online learning system. However, higher expert scores and more accurate joint movements were shown in the expert modeling group compared to the other groups. Therefore, expert modeling seems to be the most effective method for learning high-difficulty tasks with jumps and turns
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