Incidence and recurrence of acute otitis media in Taiwan's pediatric population

OBJECTIVE: To report the incidence and recurrence of acute otitis media (AOM) in Taiwan's pediatric population. METHODS: Information from children (aged <= 12 years) with a diagnosis of AOM was retrieved from the 2006 National Healthcare Insurance claims database. We calculated the cumulative incidence rate and the incidence density rate of recurrent AOM within one year after the initial diagnosis in 2006. We used a multivariate logistic regression model to assess the predictors for recurrence of AOM. RESULTS: The annual incidence rate of AOM was estimated to be 64.5 cases per 1,000 children. The overall one-year cumulative incidence rate of recurrence was 33.1%, and the incidence density rate was 33.5 cases per 100 personyears, with the highest figure (41.2 cases per 100 person-years) noted for children aged 0-2 years. Recurrence was significantly associated with age, gender, place of treatment, and physician specialty. CONCLUSION: AOM remains a major threat to children's health in Taiwan. Male children and very young children require more aggressive preventive strategies to reduce the risk of recurrence

ワークショップ イゲンゴ カンキョウ ニ オイテ ニホン キンダイ ショウセツ ヲ ヨム ダザイ オサム オウゴン フウケイ ヲ レイ ニ チュウゴクゴ ハンタイジ

異言語環境において日本近代小説を読む　太宰治『黄金風景』を例

Efficient Fuzzy C-Means Architecture for Image Segmentation

This paper presents a novel VLSI architecture for image segmentation. The architecture is based on the fuzzy c-means algorithm with spatial constraint for reducing the misclassification rate. In the architecture, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. In addition, an efficient pipelined circuit is used for the updating process for accelerating the computational speed. Experimental results show that the the proposed circuit is an effective alternative for real-time image segmentation with low area cost and low misclassification rate

太宰治『黄金风景』

太宰治『黄金風景』Translations Chinese(Traditional) 繁体中

Mechanistic study on uptake and transport of pharmaceuticals in lettuce from water

The dissemination of pharmaceuticals in agroecosystems originating from land application of animal manure/sewage sludge and irrigation with treated wastewater in agricultural production has raised concern about the accumulation of pharmaceuticals in food products. The pathways of pharmaceutical entries via plant roots, transport to upper fractions, and the factors influencing these processes have yet been systematically elucidated, thus impeding the development of effective measures to mitigate pharmaceutical contamination in food crops. In this study, lettuce uptake of thirteen commonly used pharmaceuticals was investigated using a hydroponic experimental setting. Pharmaceutical sorption by lettuce roots was measured in order to evaluate the influence on pharmaceutical transport from roots to shoots. Small-sized pharmaceuticals e.g., caffeine and carbamazepine with molecular weight (MW) 12.0 L g−1) and demonstrated a reduced transport to shoots. Large-sized pharmaceuticals (e.g. MW >400 g mol−1) including lincomycin, monensin sodium, and tylosin could be excluded from cell membranes, resulting in the predominant accumulation in lettuce roots. Large-sized oxytetracycline existed as zwitterionic species that could slowly enter lettuce roots; however, the relatively strong interaction with lettuce roots limits its transport to shoots. The mass balance analysis revealed that acetaminophen, β-estradiol, carbadox, estrone and triclosan were readily metabolized in lettuce with >90% loss during 144-h exposure period. A scheme was proposed to describe pharmaceutical uptake and transport in plant, which could reasonably elucidate many literature-reported results. Molecular size, reactivity and ionic speciation of pharmaceuticals, as well as plant physiology, collectively determine their uptake, transport and accumulation in plants

The Implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for Global Dust Forecasting at NOAA NCEP

The NOAA National Centers for Environmental Prediction (NCEP) implemented the NOAA Environmental Modeling System (NEMS) Global Forecast System (GFS) Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5-day dust forecasts at 1deg x 1deg resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders, as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered

Cobalt doped LaSrTiO3-delta as an anode catalyst: effect of Co nanoparticle precipitation on SOFCs operating on H2S-containing hydrogen

NSERC; National Nature Science Foundation of China [51072021]; China Scholarship CouncilThis article compares the effects of Co doping on phase structures and stability of lanthanum strontium titanate (LST) anodes and electrochemical measurements in solid oxide fuel cells (SOFCs) employing H2S-containing H-2 as fuel. The Co-doped LST (LSCT) with a perovskite structure was synthesized via a solid state approach, achieving excellent phase purity and refined particle size. The catalytic activity and electrochemical performance are significantly improved by introducing Co. A maximum power density of 300 mW cm(-2) was achieved at 900 degrees C with 5000 ppm H2S-H-2 in a fuel cell having a 300 mu m thick YSZ electrolyte. Trace amounts of metallic Co nanoparticles with sizes typically no larger than 10 nm in diameter were detected on the LSCT surface after reduction in H-2 at 900 degrees C. The nano-sized Co clusters could reduce the anode polarization resistance, as well as improve the cell performance, compared with undoped LST anodes. The LSCT anode catalyst was electrochemically stable in 5000 ppm H2S-H-2 during the test time at high operating temperature. The LSCT anode catalyst also had relatively high redox stability in reversible oxidation-reduction cycles

A review of high impact weather for aviation meteorology

This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems. Severe weather can disrupt aviation operations on the ground or in-flight. The most important parameters related to aviation meteorology are wind and turbulence, fog visibility, aerosol/ash loading, ceiling, rain and snow amount and rates, icing, ice microphysical parameters, convection and precipitation intensity, microbursts, hail, and lightning. Measurements of these parameters are functions of sensor response times and measurement thresholds in extreme weather conditions. In addition to these, airport environments can also play an important role leading to intensification of extreme weather conditions or high impact weather events, e.g., anthropogenic ice fog. To observe meteorological parameters, new remote sensing platforms, namely wind LIDAR, sodars, radars, and geostationary satellites, and in situ instruments at the surface and in the atmosphere, as well as aircraft and Unmanned Aerial Vehicles mounted sensors, are becoming more common. At smaller time and space scales (e.g., < 1 km), meteorological forecasts from NWP models need to be continuously improved for accurate physical parameterizations. Aviation weather forecasts also need to be developed to provide detailed information that represents both deterministic and statistical approaches. In this review, we present available resources and issues for aviation meteorology and evaluate them for required improvements related to measurements, nowcasting, forecasting, and climate change, and emphasize future challenges