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12,343 results on '"Z. Gao"'

1. Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0

Author: Y. Yuan, F. Yu, Z. Chen, X. Li, F. Hou, Y. Gao, Z. Gao, and R. Pang
Subjects: Geology, QE1-996.5
Abstract: The spectral wave model WAM (Cycle 6) is a commonly used code package for ocean wave forecasting. However, it is still a challenge to include it into the long-term Earth system modeling due to the huge computing requirement. In this study, we have successfully developed a GPU-accelerated version of the WAM model that can run all its computing-demanding components on GPUs, with a significant performance increase compared with its original CPU version. The power of GPU computing has been unleashed through substantial efforts of code refactoring, which reduces the computing time of a 7 d global 1/10° wave modeling to only 7.6 min in a single-node server installed with eight NVIDIA A100 GPUs. Speedup comparisons exhibit that running the WAM6 with eight cards can achieve the maximum speedup ratio of 37 over the dual-socket CPU node with two Intel Xeon 6236 CPUs. The study provides an approach to energy-efficient computing for ocean wave modeling. A preliminary evaluation suggests that approximately 90 % of power can be saved.
Published: 2024
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2. Uncertainties in temperature statistics and fluxes determined by sonic anemometers due to wind-induced vibrations of mounting arms

Author: Z. Gao, H. Liu, D. Li, B. Yang, V. Walden, L. Li, and I. Bogoev
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Accurate air temperature measurements are essential in eddy covariance systems, not only for determining sensible heat flux but also for applying density effect corrections (DECs) to water vapor and CO2 fluxes. However, the influence of wind-induced vibrations of mounting structures on temperature fluctuations remains a subject of investigation. This study examines 30 min average temperature variances and fluxes using eddy covariance systems, combining Campbell Scientific sonic anemometers with closely co-located fine-wire thermocouples alongside LI-COR CO2–H2O gas analyzers at multiple heights above a sagebrush ecosystem. The variances of sonic temperature after humidity corrections (Ts) and sensible heat fluxes derived from Ts are underestimated (e.g., by approximately 5 % for temperature variances and 4 % for sensible heat fluxes at 40.2 m, respectively) as compared with those measured by a fine-wire thermocouple (Tc). Spectral analysis illustrates that these underestimated variances and fluxes are caused by the lower energy levels in the Ts spectra than the Tc spectra in the low-frequency range (natural frequency < 0.02 Hz). These underestimated Ts spectra in the low-frequency range become more pronounced with increasing wind speeds, especially when wind speed exceeds 10 m s−1. Moreover, the underestimated temperature variances and fluxes cause overestimated water vapor and CO2 fluxes through DEC. Our analysis suggests that these underestimations when using Ts are likely due to wind-induced vibrations affecting the tower and mounting arms, altering the time of flight of ultrasonic signals along three sonic measurement paths. This study underscores the importance of further investigations to develop corrections for these errors.
Published: 2024
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3. Gap filling of turbulent heat fluxes over rice–wheat rotation croplands using the random forest model

Author: J. Zhang, Z. Duan, S. Zhou, Y. Li, and Z. Gao
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: This study investigated the accuracy of the random forest (RF) model in gap filling the sensible (H) and latent heat (LE) fluxes, by using the observation data collected at a site over rice–wheat rotation croplands in Shouxian County of eastern China from 15 July 2015 to 24 April 2019. Firstly, the variable significance of the machine learning (ML) model's five input variables, including the net radiation (Rn), wind speed (WS), temperature (T), relative humidity (RH), and air pressure (P), was examined, and it was found that Rn accounted for 78 % and 76 % of the total variable significance in H and LE calculating, respectively, showing that it was the most important input variable. Secondly, the RF model's accuracy with the five-variable (Rn, WS, T, RH, P) input combination was evaluated, and the results showed that the RF model could reliably gap fill the H and LE with mean absolute errors (MAEs) of 5.88 and 20.97 W m−2, and root mean square errors (RMSEs) of 10.67 and 29.46 W m−2, respectively. Thirdly, four-variable input combinations were tested, and it was found that the best input combination was (Rn, WS, T, P) by removing RH from the input list, and its MAE values of H and LE were reduced by 12.65 % and 7.12 %, respectively. At last, through the Taylor diagram, H and LE gap-filling accuracies of the RF model, the support vector machine (SVM) model, the k nearest-neighbor (KNN) model, and the gradient boosting decision tree (GBDT) model were intercompared, and the statistical metrics showed that RF was the most accurate for both H and LE gap filling, while the LR and KNN model performed the worst for H and LE gap filling, respectively.
Published: 2023
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4. Forecasting tropical cyclone tracks in the northwestern Pacific based on a deep-learning model

Author: L. Wang, B. Wan, S. Zhou, H. Sun, and Z. Gao
Subjects: Geology, QE1-996.5
Abstract: Tropical cyclones (TCs) are one of the most severe meteorological disasters, making rapid and accurate track forecasts crucial for disaster prevention and mitigation. Because TC tracks are affected by various factors (the steering flow, the thermal structure of the underlying surface, and the atmospheric circulation), their trajectories present highly complex nonlinear behavior. Deep learning has many advantages in simulating nonlinear systems. In this paper, based on deep-learning technology, we explore the movement of TCs in the northwestern Pacific from 1979 to 2021, divided into training (1979–2014), validation (2015–2018), and test sets (2019–2021), and we create 6–72 h TC track forecasts. Only historical trajectory data are used as input for evaluating the forecasts of the following three recurrent neural networks utilized: recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU) models. The GRU approach performed best; to further improve forecast accuracy, a model combining GRU and a convolutional neural network (CNN) called GRU_CNN is proposed to capture the characteristics that vary with time. By adding reanalysis data of the steering flow, sea surface temperatures, and geopotential height around the cyclone, we can extract sufficient information on the historical trajectory features and three-dimensional spatial features. The results show that GRU_CNN outperforms other deep-learning models without CNN layers. Furthermore, by analyzing three additional environmental factors through control experiments, it can be concluded that the historical steering flow of TCs plays a key role, especially for short-term predictions within 24 h, while sea surface temperatures and geopotential height can gradually improve the 24–72 h forecast. The average distance errors at 6 and 12 h are 17.22 and 43.90 km, respectively. Compared with the 6 and 12 h forecast results (27.57 and 59.09 km) of the Central Meteorological Observatory, the model proposed herein is suitable for short-term forecasting of TC tracks.
Published: 2023
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5. Bursting core-localized ellipticity-induced Alfvén eigenmodes driven by energetic electrons during EAST ohmic discharges

Author: P. Su, H. Lan, C. Zhou, J. Bao, A. Liu, X. Zhu, M. Wu, C. Luo, J. Han, J. Wang, H. Liu, T. Zhang, R. Zhou, S. Lin, H. Zhao, Y. Sun, Z. Qiu, N. Chu, T. Tang, Y. Tan, L. Zeng, and Z. Gao
Subjects: ellipticity-induced Alfvén eigenmodes, energetic electrons, wave-particle interaction, EAST tokamak, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: A series of high-frequency ( $400\sim1000{\text{ kHz}}$ ) bursting core-localized Alfvén instabilities have been observed during ohmic discharges in EAST tokamak. The instability trigger favours the discharge conditions of low toroidal magnetic field and low electron density. The toroidal mode numbers are mainly $n = 2\sim3$ and they propagate in the ion diamagnetic drift (co-current) direction. These modes are radially localized in the range of ${\rho _{{\text{tor}}}} = 0.2\sim0.35$ based on Doppler BackScatter measurement. They are identified as ellipticity-induced Alfvén eigenmodes (EAEs) occurring at $q = 1$ rational surfaces by magnetohydrodynamics simulations using the realistic geometry and plasma profiles. The EAEs show regular bursts with ∼10 ms duration along with the mode frequency chirping downwards and upwards rapidly. It is also found that sawtooth events can interrupt the growth and evolution of the EAEs, causing the modes to disappear immediately. Passing energetic electrons (EEs) that move much faster than Alfvén velocity are responsible for the destabilization of these EAEs, which attribute to the fact that the large poloidal and toroidal frequencies mostly cancel each other and satisfy the EAE resonance condition with primary energy exchange. These novel experimental results of the wave-particle interaction between EAEs and EEs are helpful for extrapolating alpha particle physics that are characterized by small orbit width with respect to machine size in future fusion reactors.
Published: 2024
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6. Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)

Author: Z. Gao, Y. Wang, P. Vasilakos, C. E. Ivey, K. Do, and A. G. Russell
Subjects: Geology, QE1-996.5
Abstract: The growing abundance of data is conducive to using numerical methods to relate air quality, meteorology and emissions to address which factors impact pollutant concentrations. Often, it is the extreme values that are of interest for health and regulatory purposes (e.g., the National Ambient Air Quality Standard for ozone uses the annual maximum daily fourth highest 8 h average (MDA8) ozone), though such values are the most challenging to predict using empirical models. We developed four different computational models, including the generalized additive model (GAM), multivariate adaptive regression splines, random forest, and support vector regression, to develop observation-based relationships between the fourth highest MDA8 ozone in the South Coast Air Basin and precursor emissions, meteorological factors and large-scale climate patterns. All models had similar predictive performance, though the GAM showed a relatively higher R2 value (0.96) with a lower root mean square error and mean bias.
Published: 2022
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7. A benchmark dataset of diurnal- and seasonal-scale radiation, heat, and CO2 fluxes in a typical East Asian monsoon region

Author: Z. Duan, Z. Gao, Q. Xu, S. Zhou, K. Qin, and Y. Yang
Subjects: Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract: A benchmark dataset of radiation, heat, and CO2 fluxes is crucial to land–atmosphere interaction research. Due to rapid urbanization and the development of agriculture, the land–atmosphere interaction processes over the Yangtze River Delta (YRD) of China, which is a typical East Asian monsoon region, are becoming various and complex. To understand the effects of various land cover changes on land–atmosphere interactions in this region, a comprehensive long-term (2011–2019) in situ observation campaign, including 30 min resolution meteorological variables (air temperature, humidity, pressure, wind speed, and wind direction), surface radiative flux, turbulent heat flux, and CO2 flux, was conducted at four sites with two typical surface types (i.e., croplands and suburbs) in the YRD. Analysis of the dataset showed that all four radiation components, latent heat flux, sensible heat flux, soil heat flux, and CO2 flux varied seasonally and diurnally at the four sites. Surface energy fluxes exhibited great differences among the four sites. On an annual basis, for the two cropland sites, the dominant consumer of net radiation was latent heat flux. For the two suburban sites, in contrast, latent heating dominated from April to November, whereas sensible heating dominated during the other months. Our present work provides convincing evidence that the dataset has potential for multiple research fields, including studying land–atmosphere interactions, improving boundary layer parameterization schemes, evaluating remote sensing algorithms, validating carbon flux modeling and inversion, and developing climate models for typical East Asian monsoon regions. The dataset is publicly available at https://doi.org/10.5281/zenodo.6552301 (Duan et al., 2022).
Published: 2022
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8. BIO-INSPIRED MULTIPLE SCALES PLACE RECOGNITION FOR ELECTRIC SUBSTATIONS

Author: G. Wen, F. Zhou, H. Zhang, H. Pan, J. Cao, Z. Gao, Y. Liu, Z. Sun, and L. Pei
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: We could get many helpful information and results from satellite remote sensing images and aerial images, including disaster monitoring, grid hidden danger identification, and electricity consumption management. In the recent years, novel computer vision and deep neural network have got a lot of attention in many fields because of mimicking mammalian cognitive mechanism as much as possible. With the in-depth of mammalian cognitive and motor mechanisms research, people trend to adopt these reliable and efficient methods for power grid management and maintenance.For utilizing computing resources and improving analysing efficiency flexibly, we propose an assessing and verification framework based on bio-inspired perception and understanding, which summarizes the most appropriate image scale in the electric facilities place recognition. The proposed framework consists of different scenes aerial images datasets, several electric facilities place recognition methods, and credible evaluating methods mimicking mammals. Firstly, we gather satellite remote images and aerial images of sufficient electric power facilities in the United States via Google Earth and other public datasets. Then, several typical place recognition methods are adopted to testing recognition ability of multi-scale perception results, like SAD, NetVLAD, and GIST descriptor. To get more reliable result, multi-units and multi-scenes experiments are implemented roundly. After all experiments and evaluations, we could get that the most appropriate image scale is 1000 m size and the highest recognition accuracy of electric power facilities location is 500 m. Conclusion in our article shows the recommended perception form and scale closest to human cognition in the power grid management and maintenance.
Published: 2022
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9. Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset

Author: H. Omidvar, T. Sun, S. Grimmond, D. Bilesbach, A. Black, J. Chen, Z. Duan, Z. Gao, H. Iwata, and J. P. McFadden
Subjects: Geology, QE1-996.5
Abstract: To compare the impact of surface–atmosphere exchanges from rural and urban areas, fully vegetated areas (e.g. deciduous trees, evergreen trees and grass) commonly found adjacent to cities need to be modelled. Here we provide a general workflow to derive parameters for SUEWS (Surface Urban Energy and Water Balance Scheme), including those associated with vegetation phenology (via leaf area index, LAI), heat storage and surface conductance. As expected, attribution analysis of bias in SUEWS-modelled QE finds that surface conductance (gs) plays the dominant role; hence there is a need for more estimates of surface conductance parameters. The workflow is applied at 38 FLUXNET sites. The derived parameters vary between sites with the same plant functional type (PFT), demonstrating the challenge of using a single set of parameters for a PFT. SUEWS skill at simulating monthly and hourly latent heat flux (QE) is examined using the site-specific derived parameters, with the default NOAH surface conductance parameters (Chen et al., 1996). Overall evaluation for 2 years has similar metrics for both configurations: median hit rate between 0.6 and 0.7, median mean absolute error less than 25 W m−2, and median mean bias error ∼ 5 W m−2. Performance differences are more evident at monthly and hourly scales, with larger mean bias error (monthly: ∼ 40 W m−2; hourly ∼ 30 W m−2) results using the NOAH-surface conductance parameters, suggesting that they should be used with caution. Assessment of sites with contrasting QE performance demonstrates how critical capturing the LAI dynamics is to the SUEWS prediction skills of gs and QE. Generally gs is poorest in cooler periods (more pronounced at night, when underestimated by ∼ 3 mm s−1). Given the global LAI data availability and the workflow provided in this study, any site to be simulated should benefit.
Published: 2022
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10. Reproducing Arctic springtime tropospheric ozone and mercury depletion events in an outdoor mesocosm sea ice facility

Author: Z. Gao, N.-X. Geilfus, A. Saiz-Lopez, and F. Wang
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: The episodic buildup of gas-phase reactive bromine species over sea ice and snowpack in the springtime Arctic plays an important role in boundary layer processes, causing annual concurrent depletion of ozone and gaseous elemental mercury (GEM) during polar sunrise. Extensive studies have shown that these phenomena, known as bromine explosion events (BEEs), ozone depletion events (ODEs), and mercury depletion events (MDEs) are all triggered by reactive bromine species that are photochemically activated from bromide via multi-phase reactions under freezing air temperatures. However, major knowledge gaps exist in both fundamental cryo-photochemical processes causing these events and meteorological conditions that may affect their timing and magnitude. Here, we report an outdoor mesocosm study in which we successfully reproduced ODEs and MDEs at the Sea-ice Environmental Research Facility (SERF) in Winnipeg, Canada. By monitoring ozone and GEM concentrations inside large acrylic tubes over bromide-enriched artificial seawater during sea ice freeze-and-melt cycles, we observed mid-day photochemical ozone and GEM loss in winter in the in-tube boundary layer air immediately above the sea ice surface in a pattern that is characteristic of BEE-induced ODEs and MDEs in the Arctic. The importance of UV radiation and the presence of a condensed phase (experimental sea ice or snow) in causing such reactions were demonstrated by comparing ozone and GEM concentrations between the UV-transmitting and UV-blocking acrylic tubes under different air temperatures. The ability of reproducing BEE-induced photochemical phenomena in a mesocosm in a non-polar region provides a new approach to systematically studying the cryo-photochemical processes and meteorological conditions leading to BEEs, ODEs, and MDEs in the Arctic, their role in biogeochemical cycles across the ocean–sea ice–atmosphere interface, and their sensitivities to climate change.
Published: 2022
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11. A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations

Author: S. Chen, Y. Yang, F. Deng, Y. Zhang, D. Liu, C. Liu, and Z. Gao
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high-spatial-resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. Firstly, the observed environmental parameters, e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF), around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 ∘C. Then, the spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the decreasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high spatial and temporal resolution (30 m and 1 h) CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.
Published: 2022
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12. Estimating vertical wind power density using tower observation and empirical models over varied desert steppe terrain in northern China

Author: S. Zhou, Y. Yang, Z. Gao, X. Xi, Z. Duan, and Y. Li
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: A complex and varied terrain has a great impact on the distribution of wind energy resources, resulting in uncertainty in accurately assessing wind energy resources. In this study, three wind speed distributions of kernel, Weibull, and Rayleigh type for estimating average wind power density were first compared by using meteorological tower data from 2018 to 2020 under varied desert steppe terrain contexts in northern China. Then three key parameters of scale factor (c) and shape factor (k) from the Weibull model and surface roughness (z0) were investigated for estimating wind energy resource. The results show that the Weibull distribution is the most suitable wind speed distribution over that terrain. The scale factor (c) in the Weibull distribution model increases with an increase in height, exhibiting an obvious form of power function, while there were two different forms for the relationship between the shape factor (k) and height: i.e., the reciprocal of the quadratic function and the logarithmic function, respectively. The estimated roughness length (z0) varied with the withering period, the growing period, and the lush period, which can be represented by the estimated median value in each period. The maximum and minimum values of surface roughness length over the whole period are 0.15 and 0.12 m, respectively. The power-law model and the logarithmic model are used to estimate the average power density values at six specific heights, which show greater differences in autumn and winter, and smaller differences in spring and summer. The gradient of the increase in average power density values with height is largest in autumn and winter, and smallest in spring and summer. Our findings suggest that dynamic changes in three key parameters (c, k, and z0) should be accurately considered for estimating wind energy resources under varied desert steppe terrain contexts.
Published: 2022
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13. Technical note: Uncertainties in eddy covariance CO2 fluxes in a semiarid sagebrush ecosystem caused by gap-filling approaches

Author: J. Yao, Z. Gao, J. Huang, H. Liu, and G. Wang
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Gap-filling eddy covariance CO2 fluxes is challenging at dryland sites due to small CO2 fluxes. Here, four machine learning (ML) algorithms including artificial neural network (ANN), k-nearest neighbors (KNNs), random forest (RF), and support vector machine (SVM) are employed and evaluated for gap-filling CO2 fluxes over a semiarid sagebrush ecosystem with different lengths of artificial gaps. The ANN and RF algorithms outperform the KNN and SVM in filling gaps ranging from hours to days, with the RF being more time efficient than the ANN. Performances of the ANN and RF are largely degraded for extremely long gaps of 2 months. In addition, our results suggest that there is no need to fill the daytime and nighttime net ecosystem exchange (NEE) gaps separately when using the ANN and RF. With the ANN and RF, the gap-filling-induced uncertainties in the annual NEE at this site are estimated to be within 16 g C m−2, whereas the uncertainties by the KNN and SVM can be as large as 27 g C m−2. To better fill extremely long gaps of a few months, we test a two-layer gap-filling framework based on the RF. With this framework, the model performance is improved significantly, especially for the nighttime data. Therefore, this approach provides an alternative in filling extremely long gaps to characterize annual carbon budgets and interannual variability in dryland ecosystems.
Published: 2021
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14. Reflection of low-frequency fast magnetosonic waves at the local two-ion cutoff frequency: observation in the plasmasphere

Author: G. Wang, M. Wu, S. Xiao, I. Zhelavskaya, Y. Shprits, Y. Chen, Z. Zou, Z. Gao, W. Yi, and T. Zhang
Subjects: Science, Physics, QC1-999, Geophysics. Cosmic physics, QC801-809
Abstract: We investigate the reflection of low-harmonic fast magnetosonic (MS) waves at the local two-ion cutoff frequency (fcutHe+). By comparing the wave signals of the two Van Allen Probes satellites, a distinct boundary where wave energies cannot penetrate inward are found in the time–frequency domain. The boundary is identified as the time series of local fcutHe+. For a certain frequency, there exists a spatial interface formed by fcutHe+, where the incident waves should be reflected. The waves with small incident angles are more likely to penetrate the thin layer where the group velocity reduces significantly and then slow down in a period of several to tens of seconds before the reflection process complete. The cutoff reflection scenario can explain the intense outward waves observed by probe A. These results of MS reflection at fcutHe+ may help to predict the global distribution of MS waves and promote the understanding of wave–particle dynamics in the radiation belt.
Published: 2021
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15. Large-scale synoptic drivers of co-occurring summertime ozone and PM2.5 pollution in eastern China

Author: L. Zong, Y. Yang, M. Gao, H. Wang, P. Wang, H. Zhang, L. Wang, G. Ning, C. Liu, Y. Li, and Z. Gao
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Surface ozone (O3) pollution during summer (June–August) over eastern China has become more severe in recent years, resulting in a co-occurrence of surface O3 and PM2.5 (particulate matter with aerodynamic diameters ≤ 2.5 µm in the air) pollution. However, the mechanisms regarding how the synoptic weather pattern (SWP) might influence this compound pollution remain unclear. In this study, we applied the T-mode principal component analysis (T-PCA) method to objectively classify the occurrence of four SWPs over eastern China, based on the geopotential heights at 500 hPa during summer (2015–2018). These four SWPs over eastern China were closely related to the western Pacific subtropical high (WPSH), exhibiting significant intra-seasonal and interannual variations. Based on ground-level air quality observations, remarkable spatial and temporal disparities of surface O3 and PM2.5 pollution were also found under the four SWPs. In particular, there were two SWPs that were sensitive to compound pollution (Type 1 and Type 2). Type 1 was characterized by a stable WPSH ridge with its axis at about 22∘ N and the rain belt located south of the Yangtze River Delta (YRD); Type 2 also exhibited WPSH dominance (ridge axis at ∼ 25∘ N) but with the rain belt (over the YRD) at a higher latitude compared to Type 1. In general, SWPs have played an important role as driving factors of surface O3–PM2.5 compound pollution in a regional context. Our findings demonstrate the important role played by SWPs in driving regional surface O3–PM2.5 compound pollution, in addition to the large quantities of emissions, and may also provide insights into the regional co-occurring high levels of both PM2.5 and O3 via the effects of certain meteorological factors.
Published: 2021
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16. Integrated simulation analysis of the HL-2M high-parameter hybrid scenario

Author: Y. Zhong, G. Yang, X. Gong, P. Yu, Q. Tan, Q. Huang, P. Zheng, L. Yin, T. Yang, Z. Gao, Z. Wang, and M. Xu
Subjects: OMFIT, impurity concentration, pedestal density, HL-2M, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: On the basis of the OMFIT integrated simulation platform and the parameters of the HL-2M device, a hybrid scenario with a typical safety factor q profile is simulated using the joint injection method of neutral beam and electron cyclotron wave with a normalized toroidal beta ( β _N ) of 2.39. At the same time, by analyzing the effect of impurity concentration ( Z _eff ) and pedestal density ( n _e,ped ) on confinement, a higher parameters hybrid scenario is obtained, with β _N reaching 3.118. The research results indicate that the turbulent stabilization effect caused by Z _eff gradually decreases from strong to weak with the increase of Z _eff , whereas the radiation power loss increases linearly as Z _eff increases. Consequently, there exists an optimal Z _eff value for optimal confinement. In addition, it is found that the optimal Z _eff value decreases with the increase of n _e,ped . The research results are crucial for the HL-2M device to accomplish the 1 MA advanced scenario discharge target, and they serve as a reference for future impurity seeding experiments.
Published: 2023
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17. NEW SOLAR-INDUCED CHLOROPHYLL FLUORESCENCE RETRIEVAL ALGORITHM BASED ON TANSAT SATELLITE DATA

Author: Y. Zhou, X. Lu, Y. Huang, Z. Gao, and Y. Zheng
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Solar-induced chlorophyll fluorescence (SIF) is an indicator of plant photosynthesis which could be detected by satellite. However，some existing algorithms are easily affected by the inaccuracy of satellite data which will causing deviation in the retrieval of SIF. To avoid "outliers" with inaccuracy affecting the retrieval results, a random sample consensus algorithm (RANSAC) was introduced to retrieve SIF in this paper. The results show that the chlorophyll fluorescence value obtained by this method is consistent with the OCO-2 SIF product (R2 = 0.81), and also consistent with the MODIS vegetation index (R2 = 0.87 with NDVI, R2 = 0.85 with EVI). Compared with the existing SIF products (OCO-2 SIF), the SIF retrieved in this paper was better in spatial details and outlier distribution.
Published: 2020
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18. Observation of X(2370) and search for X(2120) in $$J/\psi \rightarrow \gamma K{\bar{K}} \eta '$$ J/ψ→γKK¯η′

Author: M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, M. Alekseev, A. Amoroso, Q. An, Anita, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. Chai, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, J. C. Chen, M. L. Chen, S. J. Chen, Y. B. Chen, W. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, Z. L. Dou, S. X. Du, J. Z. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Fu, X. L. Gao, Y. Gao, Y. G. Gao, Z. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, S. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, J. S. Huang, X. T. Huang, X. Z. Huang, N. Huesken, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, D. P. Jin, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. S. Lange, P. Larin, L. Lavezzi, H. Leithoff, T. Lenz, C. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. B. Li, H. J. Li, J. C. Li, J. W. Li, Ke Li, L. K. Li, Lei Li, P. L. Li, P. R. Li, Q. Y. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, X. N. Li, Z. B. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, D. X. Lin, Y. J. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, D. Y. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, L. Y. Liu, Q. Liu, S. B. Liu, T. Liu, X. Liu, X. Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, Y. F. Long, X. C. Lou, H. J. Lu, J. D. Lu, J. G. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, X. N. Ma, X. X. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, J. Min, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, C. Morales Morales, N. Yu. Muchnoi, H. Muramatsu, A. Mustafa, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, M. Papenbrock, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, C. F. Qiao, N. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, M. Richter, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, M. Savrié, Y. Schelhaas, C. Schnier, K. Schoenning, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. Y. Sheng, X. Shi, X. D Shi, J. J. Song, Q. Q. Song, X. Y. Song, S. Sosio, C. Sowa, S. Spataro, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, Y. J. Sun, Y. K Sun, Y. Z. Sun, Z. J. Sun, Z. T. Sun, Y. X. Tan, C. J. Tang, G. Y. Tang, X. Tang, V. Thoren, B. Tsednee, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, K. Wang, L. L. Wang, L. S. Wang, M. Wang, M. Z. Wang, Meng Wang, P. L. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. G. Wang, Z. Y. Wang, Zongyuan Wang, T. Weber, D. H. Wei, P. Weidenkaff, F. Weidner, H. W. Wen, S. P. Wen, U. Wiedner, G. Wilkinson, M. Wolke, L. H. Wu, L. J. Wu, Z. Wu, L. Xia, S. Y. Xiao, Y. J. Xiao, Z. J. Xiao, Y. G. Xie, Y. H. Xie, T. Y. Xing, X. A. Xiong, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. X. Yang, L. Yang, R. X. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, J. S. Yu, T. Yu, C. Z. Yuan, X. Q. Yuan, Y. Yuan, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, B. Y. Zhang, C. C. Zhang, D. H. Zhang, H. H. Zhang, H. Y. Zhang, J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, K. Zhang, L. Zhang, Lei Zhang, S. F. Zhang, T. J. Zhang, X. Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Yu Zhang, Z. H. Zhang, Z. P. Zhang, Z. Y. Zhang, G. Zhao, J. W. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, T. C. Zhao, Y. B. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, L. Zhou, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, X. L. Zhu, Y. C. Zhu, Y. S. Zhu, Z. A. Zhu, J. Zhuang, B. S. Zou, and J. H. Zou
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Using a sample of $$1.31\times 10^{9} ~J/\psi $$ 1.31×109J/ψ events collected with the BESIII detector, we perform a study of $$J/\psi \rightarrow \gamma K{\bar{K}}\eta '$$ J/ψ→γKK¯η′ . X(2370) is observed in the $$K{\bar{K}}\eta '$$ KK¯η′ invariant-mass distribution with a statistical significance of $$8.3\sigma $$ 8.3σ . Its resonance parameters are measured to be $$M=2341.6\pm 6.5 \, \text {(stat.)} \pm 5.7 \, \text {(syst.)}~ \hbox {MeV}/c^{2}$$ M=2341.6±6.5(stat.)±5.7(syst.)MeV/c2 and $$\Gamma = 117\pm 10 \, \text {(stat.)}\pm 8 \, \text {(syst.)}~\hbox {MeV}$$ Γ=117±10(stat.)±8(syst.)MeV . The product branching fractions for $$J/\psi \rightarrow \gamma X(2370),X(2370)\rightarrow K^{+}K^{-}\eta '$$ J/ψ→γX(2370),X(2370)→K+K-η′ and $$J/\psi \rightarrow \gamma X(2370),X(2370)\rightarrow K_{S}^{0}K_{S}^{0}\eta '$$ J/ψ→γX(2370),X(2370)→KS0KS0η′ are determined to be $$(1.79\pm 0.23\, \text {(stat.)}\pm 0.65\,\text {(syst.)})\times 10^{-5}$$ (1.79±0.23(stat.)±0.65(syst.))×10-5 and $$(1.18\pm 0.32\, \text {(stat.)}\pm 0.39\, \text {(syst.)})\times 10^{-5}$$ (1.18±0.32(stat.)±0.39(syst.))×10-5 , respectively. No evident signal for X(2120) is observed in the $$K{\bar{K}}\eta '$$ KK¯η′ invariant-mass distribution. The upper limits for the product branching fractions of $${\mathcal {B}}(J/\psi \rightarrow \gamma X(2120)\rightarrow \gamma K^{+} K^{-} \eta ')$$ B(J/ψ→γX(2120)→γK+K-η′) and $${\mathcal {B}}(J/\psi \rightarrow \gamma X(2120)\rightarrow \gamma K_{S}^{0} K_{S}^{0} \eta ')$$ B(J/ψ→γX(2120)→γKS0KS0η′) are determined to be $$1.49\times 10^{-5}$$ 1.49×10-5 and $$6.38\times 10^{-6}$$ 6.38×10-6 at the 90% confidence level, respectively.
Published: 2020
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19. VEHICLE DETECTION IN REMOTE SENSING IMAGES USING DEEP NEURAL NETWORKS AND MULTI-TASK LEARNING

Author: M. Cao, H. Ji, Z. Gao, and T. Mei
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Vehicle detection in remote sensing image has been attracting remarkable attention over past years for its applications in traffic, security, military, and surveillance fields. Due to the stunning success of deep learning techniques in object detection community, we consider to utilize CNNs for vehicle detection task in remote sensing image. Specifically, we take advantage of deep residual network, multi-scale feature fusion, hard example mining and homography augmentation to realize vehicle detection, which almost integrates all the advanced techniques in deep learning community. Furthermore, we simultaneously address super-resolution (SR) and detection problems of low-resolution (LR) image in an end-to-end manner. In consideration of the absence of paired low-/highresolution data which are generally time-consuming and cumbersome to collect, we leverage generative adversarial network (GAN) for unsupervised SR. Detection loss is back-propagated to SR generator to boost detection performance. We conduct experiments on representative benchmark datasets and demonstrate that our model yields significant improvements over state-of-the-art methods in deep learning and remote sensing areas.
Published: 2020
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20. A COARSE-TO-FINE BAND REGISTRATION FRAMEWORK FOR MULTI/HYPERSPECTRAL REMOTE SENSING IMAGES CONSIDERING CLOUD INFLUENCE

Author: X. Zhao, Z. Gao, W. Sun, and F. Wen
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Band registration is one of the most critical steps in the production of multi/hyperspectral images and determines the accuracy of applications directly. Because of the characteristics of imaging devices in some multi/hyperspectral satellites, there may be a time difference between bands during push-broom imaging, which leads to displacements of moving clouds with respect to the ground. And a large number of feature points may gather around cloud contours due to the high contrast and rich texture, resulting in building a transformation more suitable for moving clouds and making ground objects ghosted and blurred. This brings a big challenge for registration methods based on feature extraction and matching. In this paper, we propose a novel coarse-to-fine band registration framework for multi/hyperspectral images containing moving clouds. In the coarse registration stage, a cloud mask is generated by grayscale stretching, morphology and other operations. Based on this mask, a coarse matching of cloud-free regions is performed to eliminate large misalignment between bands. In the refinement stage, low-rank analysis and RASL (Robust Alignment by Sparse and Low-rank decomposition) are used to optimize the rank of coarse results to achieve fine registration between bands. After experiments on a total of 102 images (83 cloudy images and 19 cloud-free images with all 32 bands) from Zhuhai-1 hyperspectral satellite, our method can achieve a registration accuracy of 0.6 pixels in cloudy images, 0.41 pixels in cloud-free images, which is enough for subsequent applications.
Published: 2020
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21. Aerosol vertical mass flux measurements during heavy aerosol pollution episodes at a rural site and an urban site in the Beijing area of the North China Plain

Author: R. Yuan, X. Zhang, H. Liu, Y. Gui, B. Shao, X. Tao, Y. Wang, J. Zhong, Y. Li, and Z. Gao
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Due to excessive anthropogenic emissions, heavy aerosol pollution episodes (HPEs) often occur during winter in the Beijing–Tianjin–Hebei (BTH) area of the North China Plain. Extensive observational studies have been carried out to understand the causes of HPEs; however, few measurements of vertical aerosol fluxes exist, despite them being the key to understanding vertical aerosol mixing, specifically during weak turbulence stages in HPEs. In the winter of 2016 and the spring of 2017 aerosol vertical mass fluxes were measured by combining large aperture scintillometer (LAS) observations, surface PM2.5 and PM10 mass concentrations, and meteorological observations, including temperature, relative humidity (RH), and visibility, at a rural site in Gucheng (GC), Hebei Province, and an urban site at the Chinese Academy of Meteorological Sciences (CAMS) in Beijing located 100 km to the northeast. These are based on the light propagation theory and surface-layer similarity theory. The near-ground aerosol mass flux was generally lower in winter than in spring and weaker in rural GC than in urban Beijing. This finding provides direct observational evidence for a weakened turbulence intensity and low vertical aerosol fluxes in winter and polluted areas such as GC. The HPEs included a transport stage (TS), an accumulative stage (AS), and a removal stage (RS). During the HPEs from 25 to 31 January 2017, in Beijing, the mean mass flux decreased by 51 % from 0.0049 mg m−2 s−1 in RSs to 0.0024 mg m−2 s−1 in the TSs. During the ASs, the mean mass flux decreased further to 0.00087 mg m−2 s−1, accounting for approximately one-third of the flux in the TSs. A similar reduction from the TSs to ASs was observed in the HPE from 16 to 22 December 2016 in GC. It can be seen that from the TS to the AS, the aerosol vertical turbulent flux decreased, but the aerosol particle concentration within the surface layer increased, and it is inferred that in addition to the contribution of regional transport from upwind areas during the TS, suppression of vertical turbulence mixing confining aerosols to a shallow boundary layer increased accumulation.
Published: 2019
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22. PB1950: MASS CYTOMETRY ANALYSIS IDENTIFIES T CELL IMMUNE SIGNATURE FOR APLASTIC ANEMIA AND PREDICTS RESPONSE TO CYCLOSPORINE

Author: L. Zhang, J. Mao, Y. Lian, Q. Liang, H. Pan, Z. Gao, W. Li, J. Zhao, L. Fang, Y. Chu, W. Yuan, and J. Shi
Subjects: Diseases of the blood and blood-forming organs, RC633-647.5
Published: 2022
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23. POS-551 INTRAOPERATIVE PLASMA (1-84) PTH LEVELS ARE BETTER THAN INTACT PTH FOR ASSESSING THE SUCCESS OF PARATHYROIDECTOMY IN UREMIC HYPERPARATHYROIDISM PATIENTS

Author: F. Xu, W. Ren, Y. Huang, M. Zeng, L. Zhang, H. Qian, Y. Cui, W. Zhou, Z. Gao, H. Huang, H. Chen, C. Liu, C. Xing, X. Zha, and N. Wang
Subjects: Diseases of the genitourinary system. Urology, RC870-923
Published: 2021
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24. DESIGNING AND CONSTRUCTION OF THE SPECTRAL LIBRARY FOR TYPICAL PIGMENTS USED IN CHINESE PAINTINGS

Author: S. Lyu, Y. Liu, M. Hou, Z. Gao, X. Yang, and M. Gu
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Suffered from the environmental changes and human’s influence, Chinese paintings are facing a worrying situation in documentation, which leads urgent into establishing digital archives to realize the permanent preservation of its surface information. Non-destructive identification of pigment types using hyperspectral techniques is the key to ensure the colour restoration scientifically. At present, one commonly used method for spectral identification is to calculate the similarities between unknown spectra and standard spectra in spectral library. The purpose of this study is to establish a spectral library of typical pigments specifically for the information preservation and pigment types identification on surface of Chinese paintings. The main works of the research are: (1) collecting the standard spectra in laboratory and the pigment spectra on surface of real cultural relics as the data source of the spectral library; (2) adding the expert knowledge of traditional pigments and normative descriptions of spectra measurement as part of the spectral library; and (3) constructing the spectral library website with the Browser/Server structure, and by using MySQL database for storage, SSM framework for background building and JSP page for displaying. The significance of the design and construction of the Typical Pigments of Chinese Paintings (TPCP) spectral library is not only to establish a standard spectral library for pigment types identification, but also a digital archive of pigment information on the surface of real cultural relics, to achieve permanent preservation, and provide spectral data sources and pigment information references for conservation workers and researchers in related fields for further research.
Published: 2019
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25. Vertical observations of the atmospheric boundary layer structure over Beijing urban area during air pollution episodes

Author: L. Wang, J. Liu, Z. Gao, Y. Li, M. Huang, S. Fan, X. Zhang, Y. Yang, S. Miao, H. Zou, Y. Sun, Y. Chen, and T. Yang
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: We investigated the interactions between the air pollutants and the structure of the urban boundary layer (UBL) over Beijing by using the data mainly obtained from the 325 m meteorological tower and a Doppler wind lidar during 1–4 December 2016. Results showed that the pollution episodes in this period could be characterized by low surface pressure, high relative humidity, weak wind, and temperature inversion. Compared with a clean daytime episode that took place on 1 December, results also showed that the attenuation ratio of downward shortwave radiation was about 5 %, 24 % and 63 % in afternoon hours (from 12:00 to 14:00 local standard time, LST) on 2–4 December, respectively, while for the net radiation (Rn) attenuation ratio at the 140 m level of the 325 m tower was 3 %, 27 % and 68 %. The large reduction in Rn on 4 December was not only the result of the aerosols, but also clouds. Based on analysis of the surface energy balance at the 140 m level, we found that the sensible heat flux was remarkably diminished during daytime on polluted days and even negative after sunrise (about 07:20 LST) till 14:00 LST on 4 December. We also found that heat storage in the urban surface layer played an important role in the exchange of the sensible heat flux. Owing to the advantages of the wind lidar having superior spatial and temporal resolution, the vertical velocity variance could capture the evolution of the UBL well. It clearly showed that vertical mixing was negatively related to the concentrating of pollutants, and that vertical mixing would also be weakened by a certain quantity of pollutants, and then in turn worsened the pollution further. Compared to the clean daytime on 1 December, the maximums of the boundary layer height (BLH) decreased about 44 % and 56 % on 2–3 December, when the average PM2.5 (PM1) concentrations in afternoon hours (from 12:00 to 14:00 LST) were 44 (48) µg m−3 and 150 (120) µg m−3. Part of these reductions of the BLH was also contributed by the effect of the heat storage in the urban canopy.
Published: 2019
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26. Measurement of the phase between strong and electromagnetic amplitudes of J/ψ decays

Author: M. Ablikim, M.N. Achasov, S. Ahmed, M. Albrecht, A. Amoroso, F.F. An, Q. An, Y. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, P.L. Chen, S.J. Chen, X.R. Chen, Y.B. Chen, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, S. Fegan, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Y.G. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, S. Gu, Y.T. Gu, A.Q. Guo, L.B. Guo, R.P. Guo, Y.P. Guo, Z. Haddadi, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Z.L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, Y. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, T. Khan, A. Khoukaz, P. Kiese, R. Kliemt, L. Koch, O.B. Kolcu, B. Kopf, M. Kornicer, M. Kuemmel, M. Kuessner, M. Kuhlmann, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, L. Lavezzi, S. Leiber, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, K.J. Li, Kang Li, Ke Li, Lei Li, P.L. Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.M. Liu, Huanhuan Liu, Huihui Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, Ke Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Z.A. Liu, Zhiqing Liu, Y.F. Long, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, Z.X. Meng, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, G. Morello, N.Yu. Muchnoi, H. Muramatsu, A. Mustafa, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, M. Papenbrock, P. Patteri, M. Pelizaeus, J. Pellegrino, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, A. Pitka, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Richter, M. Ripka, M. Rolo, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, J.J. Song, W.M. Song, X.Y. Song, S. Sosio, C. Sowa, S. Spataro, G.X. Sun, J.F. Sun, L. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.K. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, G.Y. Tang, X. Tang, I. Tapan, M. Tiemens, B. Tsednee, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, Dan Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, Meng Wang, P. Wang, P.L. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, Zongyuan Wang, T. Weber, D.H. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, X. Xia, Y. Xia, D. Xiao, H. Xiao, Y.J. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, X.A. Xiong, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.H. Yang, Y.X. Yang, Yifan Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y.H. Zhang, Y.T. Zhang, Yang Zhang, Yao Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, Y.X. Zhou, J. Zhu, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, B.S. Zou, and J.H. Zou
Subjects: Physics, QC1-999
Abstract: Using 16 energy points of e+e− annihilation data collected in the vicinity of the J/ψ resonance with the BESIII detector and with a total integrated luminosity of around 100pb−1, we study the relative phase between the strong and electromagnetic amplitudes of J/ψ decays. The relative phase between J/ψ electromagnetic decay and the continuum process (e+e− annihilation without the J/ψ resonance) is confirmed to be zero by studying the cross section lineshape of μ+μ− production. The relative phase between J/ψ strong and electromagnetic decays is then measured to be (84.9±3.6)∘ or (−84.7±3.1)∘ for the 2(π+π−)π0 final state by investigating the interference pattern between the J/ψ decay and the continuum process. This is the first measurement of the relative phase between J/ψ strong and electromagnetic decays into a multihadron final state using the lineshape of the production cross section. We also study the production lineshape of the multihadron final state ηπ+π− with η→π+π−π0, which provides additional information about the phase between the J/ψ electromagnetic decay amplitude and the continuum process. Additionally, the branching fraction of J/ψ→2(π+π−)π0 is measured to be (4.73±0.44)% or (4.85±0.45)%, and the branching fraction of J/ψ→ηπ+π− is measured to be (3.78±0.68)×10−4. Both of them are consistent with the world average values. The quoted uncertainties include both statistical and systematic uncertainties, which are mainly caused by the low statistics. Keywords: Phase, Strong amplitude, Electromagnetic amplitude, J/ψ decay, BESIII
Published: 2019
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27. The two-way feedback mechanism between unfavorable meteorological conditions and cumulative aerosol pollution in various haze regions of China

Author: J. Zhong, X. Zhang, Y. Wang, J. Wang, X. Shen, H. Zhang, T. Wang, Z. Xie, C. Liu, T. Zhao, J. Sun, S. Fan, Z. Gao, Y. Li, and L. Wang
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Accompanied by unfavorable meteorological conditions with stable stratification in various haze regions of China, persistent heavy aerosol pollution episodes (HPEs) lasting more than 3 consecutive days frequently occur, particularly in winter. In the North China Plain (NCP), explosive growth of fine particulate matter smaller than 2.5 µm in diameter (PM2.5), which occurs during some HPES, is dominated by a two-way feedback mechanism between more unfavorable meteorological conditions and cumulative aerosol pollution. However, the existence of a two-way feedback mechanism such as this in other key haze regions in China is uncertain; these regions include the Guanzhong Plain (GZP), the Yangtze River Delta (YRD) region, the Two Lakes Basin (TLB; a large outflow basin connected to Hubei Province and Hunan Province), the Pearl River Delta (PRD) region, the Sichuan Basin (SB), and the Northeast China Plain (NeCP). In this study, using surface PM2.5 and radiation observations, radiosonde observations, and reanalysis data, we observed the existence of a two-way feedback mechanism in the six abovementioned regions. In the SB, this two-way feedback mechanism is weak due to the suppression of cloudy mid-upper layers. In the more polluted NCP, the GZP, and the NeCP, the feedback is more striking than that in the YRD, the TLB, and the PRD. In these regions, the feedback of worsened meteorological conditions on PM2.5 explains 60 %–70 % of the increase in PM2.5 during the cumulative stages (CSs). For each region, the low-level cooling bias becomes increasingly substantial with increasing aerosol pollution and a closer distance to the ground surface. With PM2.5 mass concentrations greater than 400 µg m−3, the near-ground bias exceeded −4 ∘C in Beijing and reached up to approximately −4 ∘C in Xi'an; this result was caused by accumulated aerosol mass to some extent. In addition to the increase in PM2.5 caused by the two-way feedback, these regions also suffer from the regional transport of pollutants, including inter-regional transport in the GZP, trans-regional transport from the NCP to the YRD and the TLB, and southwesterly transport in the NeCP.
Published: 2019
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28. Evaluating the performance of two surface layer schemes for the momentum and heat exchange processes during severe haze pollution in Jing-Jin-Ji in eastern China

Author: Y. Peng, H. Wang, Y. Li, C. Liu, T. Zhao, X. Zhang, Z. Gao, T. Jiang, H. Che, and M. Zhang
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: The turbulent flux parameterization schemes in the surface layer are crucial for air pollution modeling. There have been some deficiencies in the prediction of air pollutants by atmosphere chemical models, which is closely related to the uncertainties of the momentum and sensible heat fluxes calculated in the surface layer. The differences between two surface layer schemes (Li and MM5 schemes) were discussed, and the performances of two schemes were mainly evaluated based on the observed momentum and sensible heat fluxes during a heavy haze episode in Jing-Jin-Ji in eastern China. The results showed that the aerodynamic roughness length z0m and the thermal roughness length z0h played major roles in the flux calculation. Compared with the Li scheme, ignoring the difference between z0m and z0h in the MM5 scheme induced a great error in the calculation of the sensible heat flux (e.g., the error was 54 % at Gucheng station). Besides the roughness length, the algorithm for the surface turbulent flux as well as the roughness sublayer also resulted in certain errors in the MM5 scheme. In addition, magnitudes of z0m and z0h have significant influence on the two schemes. The large z0m and z0m∕z0h in megacities with a rough surface (e.g., Beijing) resulted in much larger differences of momentum and sensible heat fluxes between Li and MM5, compared with the small z0m and z0m∕z0h in suburban areas with a smooth surface (e.g., Gucheng). The Li scheme could better characterize the evolution of atmospheric stratification than the MM5 scheme in general, especially for the transition stage from unstable to stable atmospheric stratification, corresponding to the PM2.5 accumulation. The biases of momentum and sensible heat fluxes from Li were lower, about 38 % and 43 %, respectively, than those from MM5 during this stage. This study indicates the superiority of the Li scheme in describing regional atmospheric stratification and an improved possibility of severe haze prediction in Jing-Jin-Ji in eastern China by coupling it into atmosphere chemical models.
Published: 2018
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29. Study of e+e− → D+D−π+π− at center-of-mass energies from 4.36 to 4.60GeV

Author: M. Ablikim, M.N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, M. Alekseev, A. Amoroso, F.F. An, Q. An, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino Balossino, Y. Ban, K. Begzsuren, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Biernat, J. Bloms, I. Boyko, R.A. Briere, H. Cai, X. Cai, A. Calcaterra, G.F. Cao, N. Cao, S.A. Cetin, J. Chai, J.F. Chang, W.L. Chang, G. Chelkov, D.Y. Chen, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S.J. Chen, Y.B. Chen, W. Cheng, G. Cibinetto, F. Cossio, X.F. Cui, H.L. Dai, J.P. Dai, X.C. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, J.Z. Fan, J. Fang, S.S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, M. Fritsch, C.D. Fu, Y. Fu, Q. Gao, X.L. Gao, Y. Gao, Y.G. Gao, Z. Gao, B. Garillon, I. Garzia, E.M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, L.M. Gu, M.H. Gu, S. Gu, Y.T. Gu, A.Q. Guo, L.B. Guo, R.P. Guo, Y.P. Guo, A. Guskov, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, M. Himmelreich, Y.R. Hou, Z.L. Hou, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, N. Huesken, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, H.L. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X.S. Kang, R. Kappert, M. Kavatsyuk, B.C. Ke, I.K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O.B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. Kurth, M.G. Kurth, W. Kühn, J.S. Lange, P. Larin, L. Lavezzi, H. Leithoff, T. Lenz, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, J.W. Li, Ke Li, L.K. Li, Lei Li, P.L. Li, P.R. Li, Q.Y. Li, W.D. Li, W.G. Li, X.H. Li, X.L. Li, X.N. Li, X.Q. Li, Z.B. Li, Z.Y. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, L.Z. Liao, J. Libby, C.X. Lin, D.X. Lin, Y.J. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, D.Y. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.M. Liu, Huanhuan Liu, Huihui Liu, J.B. Liu, J.Y. Liu, K.Y. Liu, Ke Liu, L.D. Liu, L.Y. Liu, Q. Liu, S.B. Liu, T. Liu, X. Liu, X.Y. Liu, Y.B. Liu, Z.A. Liu, Zhiqing Liu, Y.F. Long, X.C. Lou, H.J. Lu, J.D. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, P.W. Luo, T. Luo, X.L. Luo, S. Lusso, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, X.N. Ma, X.X. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q.A. Malik, A. Mangoni, Y.J. Mao, Z.P. Mao, S. Marcello, Z.X. Meng, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, A. Mustafa, S. Nakhoul, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, M. Papenbrock, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, A. Pitka, R. Poling, V. Prasad, M. Qi, T.Y. Qi, S. Qian, C.F. Qiao, N. Qin, X.P. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, S.Q. Qu, K.H. Rashid, C.F. Redmer, M. Richter, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, M. Savrié, K. Schoenning, W. Shan, X.Y. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, X. Shi, X.D. Shi, J.J. Song, Q.Q. Song, X.Y. Song, S. Sosio, C. Sowa, S. Spataro, F.F. Sui, G.X. Sun, J.F. Sun, L. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.K. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, Y.T. Tan, C.J. Tang, G.Y. Tang, X. Tang, V. Thoren, B. Tsednee, I. Uman, B. Wang, B.L. Wang, C.W. Wang, D.Y. Wang, H.H. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, M.Z. Wang, Meng Wang, P.L. Wang, R.M. Wang, W.P. Wang, X. Wang, X.F. Wang, X.L. Wang, Y. Wang, Y.F. Wang, Z. Wang, Z.G. Wang, Z.Y. Wang, Zongyuan Wang, T. Weber, D.H. Wei, P. Weidenkaff, H.W. Wen, S.P. Wen, U. Wiedner, G. Wilkinson, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, Y. Xia, S.Y. Xiao, Y.J. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, T.Y. Xing, X.A. Xiong, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, W. Xu, X.P. Xu, F. Yan, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, R.X. Yang, S.L. Yang, Y.H. Yang, Y.X. Yang, Yifan Yang, Z.Q. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, X.Q. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.F. Zhang, T.J. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.T. Zhang, Yang Zhang, Yao Zhang, Yi Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, Y. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, L.P. Zhou, Q. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, Xiaoyu Zhou, Xu Zhou, A.N. Zhu, J. Zhu, K. Zhu, K.J. Zhu, S.H. Zhu, W.J. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, B.S. Zou, and J.H. Zou
Subjects: Physics, QC1-999
Abstract: We report a study of the e+e−→D+D−π+π− process using e+e− collision data samples with an integrated luminosity of 2.5fb−1 at center-of-mass energies from 4.36 to 4.60GeV, collected with the BESIII detector at the BEPCII storage ring. The D1(2420)+ is observed in the D+π+π− mass spectrum. The mass and width of the D1(2420)+ are measured to be (2427.2±1.0stat.±1.2syst.)MeV/c2 and (23.2±2.3stat.±2.3syst.)MeV, respectively. In addition, the Born cross sections of the e+e−→D1(2420)+D−+c.c.→D+D−π+π− and e+e−→ψ(3770)π+π−→D+D−π+π− processes are measured as a function of the center-of-mass energy.
Published: 2020
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30. Prevalence of Helicobacter pylori infection in a third-tier Chinese city: relationship with gender, age, birth-year and survey years

Author: W. Hong, H. Tang, X. Dong, S. Hu, Y. Yan, Z. Basharat, V. Zimmer, L. Tzivian, M. Leja, Z. Gao, A. Sharma, V. Tsukanov, and W. Geng
Subjects: epidemiology, prevalence, helicobacter pylori, regression, china, single-center study., Diseases of the digestive system. Gastroenterology, RC799-869, Medicine (General), R5-920
Abstract: Objective: This study aims to investigate the prevalence of Helicobacter Pylori (H.pylori) infection and its relation with gender, age, birth-year, and survey years. Patients and Methods: We conducted a cross-sectional study on subjects that had undergone healthy checkups for H. pylori infection in a university hospital in mainland China between January 2013 and December 2017. The relationship between age, birth-year, and survey years and prevalence of H. pylori infection was investigated by Joinpoint regression analysis. Results: A total of 53,260 subjects were enrolled in this study. The overall prevalence of H. pylori infection was 48.4%. H. pylori infection prevalence was higher in females than in men. In subjects with age younger than 36 years, a greater increase in age was associated with an increased prevalence of H. pylori infection, reaching a peak at 36 years of age. In subjects with age older than 36 years, the prevalence of H. pylori infection did not change significantly with age. As to birth-year, the prevalence of H. pylori in subjects born between 1923 and 1980 did not significantly change with birth-year. It was followed by a rapid decline in those born between 1980 and 2004. Age-standardized H. pylori infection prevalence was marginally higher in women than in men (44.5% vs. 43.5%, p = 0.025). The observed age-adjusted prevalence of H. pylori infection decreased with survey year from 53.0% in 2013 to 39.5% in 2017. Conclusions: The prevalence of H. pylori infection was relatively high in this cohort of patients and decreased from 2013 to 2017, and it changes according to gender, age, and birth-year.
Published: 2019
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31. Measurement of branching fractions for D meson decaying into ϕ meson and a pseudoscalar meson

Author: M. Ablikim, M.N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, M. Alekseev, A. Amoroso, F.F. An, Q. An, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Biernat, J. Bloms, I. Boyko, R.A. Briere, H. Cai, X. Cai, A. Calcaterra, G.F. Cao, N. Cao, S.A. Cetin, J. Chai, J.F. Chang, W.L. Chang, G. Chelkov, D.Y. Chen, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S.J. Chen, Y.B. Chen, W. Cheng, G. Cibinetto, F. Cossio, X.F. Cui, H.L. Dai, J.P. Dai, X.C. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, J.Z. Fan, J. Fang, S.S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, M. Fritsch, C.D. Fu, Y. Fu, Q. Gao, X.L. Gao, Y. Gao, Y.G. Gao, Z. Gao, B. Garillon, I. Garzia, E.M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, L.M. Gu, M.H. Gu, S. Gu, Y.T. Gu, A.Q. Guo, L.B. Guo, R.P. Guo, Y.P. Guo, A. Guskov, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, M. Himmelreich, Y.R. Hou, Z.L. Hou, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, N. Huesken, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, H.L. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X.S. Kang, R. Kappert, M. Kavatsyuk, B.C. Ke, I.K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O.B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. Kurth, M.G. Kurth, W. Kühn, J.S. Lange, P. Larin, L. Lavezzi, H. Leithoff, T. Lenz, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, J.W. Li, Ke Li, L.K. Li, Lei Li, P.L. Li, P.R. Li, Q.Y. Li, W.D. Li, W.G. Li, X.H. Li, X.L. Li, X.N. Li, Z.B. Li, Z.Y. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, L.Z. Liao, J. Libby, C.X. Lin, D.X. Lin, Y.J. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, D.Y. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.M. Liu, Huanhuan Liu, Huihui Liu, J.B. Liu, J.Y. Liu, K. Liu, K.Y. Liu, Ke Liu, L.Y. Liu, Q. Liu, S.B. Liu, T. Liu, X. Liu, X.Y. Liu, Y.B. Liu, Z.A. Liu, Zhiqing Liu, Y.F. Long, X.C. Lou, H.J. Lu, J.D. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, P.W. Luo, T. Luo, X.L. Luo, S. Lusso, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, X.N. Ma, X.X. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q.A. Malik, A. Mangoni, Y.J. Mao, Z.P. Mao, S. Marcello, Z.X. Meng, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, A. Mustafa, S. Nakhoul, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, M. Papenbrock, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, A. Pitka, R. Poling, V. Prasad, H.R. Qi, M. Qi, T.Y. Qi, S. Qian, C.F. Qiao, N. Qin, X.P. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, S.Q. Qu, K.H. Rashid, K. Ravindran, C.F. Redmer, M. Richter, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, M. Savrié, Y. Schelhaas, K. Schoenning, W. Shan, X.Y. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, X. Shi, X.D Shi, J.J. Song, Q.Q. Song, X.Y. Song, S. Sosio, C. Sowa, S. Spataro, F.F. Sui, G.X. Sun, J.F. Sun, L. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.K Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, Y.T Tan, C.J. Tang, G.Y. Tang, X. Tang, V. Thoren, B. Tsednee, I. Uman, B. Wang, B.L. Wang, C.W. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, M.Z. Wang, Meng Wang, P.L. Wang, R.M. Wang, W.P. Wang, X. Wang, X.F. Wang, X.L. Wang, Y. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.Y. Wang, Zongyuan Wang, T. Weber, D.H. Wei, P. Weidenkaff, F. Weidner, H.W. Wen, S.P. Wen, U. Wiedner, G. Wilkinson, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, Y. Xia, S.Y. Xiao, Y.J. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, T.Y. Xing, X.A. Xiong, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, W. Xu, X.P. Xu, F. Yan, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, R.X. Yang, S.L. Yang, Y.H. Yang, Y.X. Yang, Yifan Yang, Z.Q. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, T. Yu, C.Z. Yuan, X.Q. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.F. Zhang, T.J. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.T. Zhang, Yang Zhang, Yao Zhang, Yi Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, Y. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, L.P. Zhou, Q. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, Xiaoyu Zhou, Xu Zhou, A.N. Zhu, J. Zhu, K. Zhu, K.J. Zhu, S.H. Zhu, W.J. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, B.S. Zou, and J.H. Zou
Subjects: Physics, QC1-999
Abstract: The four decay modes D0→ϕπ0, D0→ϕη, D+→ϕπ+, and D+→ϕK+ are studied by using a data sample taken at the centre-of-mass energy s=3.773 GeV with the BESIII detector, corresponding to an integrated luminosity of 2.93 fb−1. The branching fractions of the first three decay modes are measured to be B(D0→ϕπ0)=(1.168±0.028±0.028)×10−3, B(D0→ϕη)=(1.81±0.46±0.06)×10−4, and B(D+→ϕπ+)=(5.70±0.05±0.13)×10−3, respectively, where the first uncertainties are statistical and the second are systematic. In addition, the upper limit of the branching fraction for D+→ϕK+ is given to be 2.1×10−5 at the 90% confidence level. The ratio of B(D0→ϕπ0) to B(D+→ϕπ+) is calculated to be (20.49±0.50±0.45)%, which is consistent with the theoretical prediction based on isospin symmetry between these two decay modes. Keywords: BESIII, D meson, Hadronic decays, Branching fractions
Published: 2019
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32. Measurement of singly Cabibbo-suppressed decays D0 → π0π0π0, π0π0η, π0ηη and ηηη

Author: M. Ablikim, M.N. Achasov, S. Ahmed, M. Albrecht, A. Amoroso, F.F. An, Q. An, J.Z. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, P.L. Chen, S.J. Chen, X.R. Chen, Y.B. Chen, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J. Fang, S.S. Fang, Y. Fang, R. Farinelli, L. Fava, S. Fegan, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Y.G. Gao, Z. Gao, B. Garillon, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, A.Q. Guo, R.P. Guo, Y.P. Guo, Z. Haddadi, S. Han, X.Q. Hao, F.A. Harris, K.L. He, X.Q. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, H.M. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Z.L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, Y. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, T. Khan, A. Khoukaz, P. Kiese, R. Kliemt, L. Koch, O.B. Kolcu, B. Kopf, M. Kornicer, M. Kuemmel, M. Kuessner, M. Kuhlmann, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, L. Lavezzi, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K.J. Li, Kang Li, Ke Li, Lei Li, P.L. Li, P.R. Li, Q.Y. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.M. Liu, Huanhuan Liu, Huihui Liu, J.B. Liu, J.Y. Liu, K. Liu, K.Y. Liu, Ke Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Z.A. Liu, Zhiqing Liu, Y.F. Long, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, Z.X. Meng, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, A. Mustafa, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, M. Papenbrock, P. Patteri, M. Pelizaeus, J. Pellegrino, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, A. Pitka, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Richter, M. Ripka, M. Rolo, G. Rong, Ch. Rosner, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, J.J. Song, W.M. Song, X.Y. Song, S. Sosio, C. Sowa, S. Spataro, G.X. Sun, J.F. Sun, L. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.K. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, G.Y. Tang, X. Tang, I. Tapan, M. Tiemens, B. Tsednee, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, Dan Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, Meng Wang, P. Wang, P.L. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.Y. Wang, Zongyuan Wang, T. Weber, D.H. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, Y. Xia, D. Xiao, H. Xiao, Y.J. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, X.A. Xiong, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.H. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y.H. Zhang, Y.T. Zhang, Yang Zhang, Yao Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, J. Zhu, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, B.S. Zou, and J.H. Zou
Subjects: Physics, QC1-999
Abstract: Using a data sample of e+e− collision data corresponding to an integrated luminosity of 2.93 fb−1 collected with the BESIII detector at a center-of-mass energy of s=3.773GeV, we search for the singly Cabibbo-suppressed decays D0→π0π0π0, π0π0η, π0ηη and ηηη using the double tag method. The absolute branching fractions are measured to be B(D0→π0π0π0)=(2.0±0.4±0.3)×10−4, B(D0→π0π0η)=(3.8±1.1±0.7)×10−4 and B(D0→π0ηη)=(7.3±1.6±1.5)×10−4 with the statistical significances of 4.8σ, 3.8σ and 5.5σ, respectively, where the first uncertainties are statistical and the second ones systematic. No significant signal of D0→ηηη is found, and the upper limit on its decay branching fraction is set to be B(D0→ηηη)
Published: 2018
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33. CLASSIFICATION AND RECOGNITION OF TOMB INFORMATION IN HYPERSPECTRAL IMAGE

Author: M. Gu, S. Lyu, M. Hou, S. Ma, Z. Gao, S. Bai, and P. Zhou
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.
Published: 2018
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34. INFORMATION EXTRACTION IN TOMB PIT USING HYPERSPECTRAL DATA

Author: X. Yang, M. Hou, S. Lyu, S. Ma, Z. Gao, S. Bai, M. Gu, and Y. Liu
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.
Published: 2018
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35. Structural integrity investigation for RPV with various cooling water levels under pressurized melting pool

Author: J. Mao, Y. Liu, S. Bao, L. Luo, Z. Lu, and Z. Gao
Subjects: Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract: The strategy denoted as in-vessel retention (IVR) is widely used in severe accident (SA) management by most advanced nuclear power plants. The essence of IVR mitigation is to provide long-term external water cooling in maintaining the reactor pressure vessel (RPV) integrity. Actually, the traditional IVR concept assumed that RPV was fully submerged into the water flooding, and the melting pool was depressurized during the SA. The above assumptions weren't seriously challenged until the occurrence of Fukushima accident on 2011, suggesting the structural behavior had not been appropriately assessed. Therefore, the paper tries to address the structure-related issue on determining whether RPV safety can be maintained or not with the effect of various water levels and internal pressures created from core meltdown accident. In achieving it, the RPV structural behaviors are numerically investigated in terms of several field parameters, such as temperature, deformation, stress, plastic strain, creep strain, and total damage. Due to the presence of high temperature melt on the inside and water cooling on the outside, the RPV failure is governed by the failure mechanisms of creep, thermal-plasticity and plasticity. The creep and plastic damages are interacted with each other, which further accelerate the failure process. Through detailed investigation, it is found that the internal pressure as well as water levels plays an important role in determining the RPV failure time, mode and site.
Published: 2018
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36. Dark photon search in the mass range between 1.5 and 3.4 GeV/c2

Author: M. Ablikim, M.N. Achasov, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, H.Y. Chen, J.C. Chen, M.L. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, S.X. Du, P.F. Duan, E.E. Eren, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.Y. Gao, Y. Gao, Z. Gao, I. Garzia, C. Geng, K. Goetzen, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, Y.L. Han, X.Q. Hao, F.A. Harris, K.L. He, Z.Y. He, T. Held, Y.K. Heng, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.M. Huang, G.S. Huang, H.P. Huang, J.S. Huang, X.T. Huang, Y. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.L. Jiang, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, W. Kuehn, A. Kupsc, J.S. Lange, M. Lara, P. Larin, C. Leng, C. Li, C.H. Li, Cheng Li, D.M. Li, F. Li, G. Li, H.B. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.M. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B.J. Liu, C.X. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, X.X. Liu, Y.B. Liu, Z.A. Liu, Zhiqiang Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, R.Q. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, M. Lv, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, F.E. Maas, M. Maggiora, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, K. Moriya, N.Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, Y.N. Pu, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Y. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, H.L. Ren, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, V. Santoro, A. Sarantsev, M. Savrié, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, M. Ullrich, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, S.G. Wang, W. Wang, X.F. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, Z. Wu, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y. Yang, Y.X. Yang, H. Ye, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, H.W. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.H. Zhang, X.Y. Zhang, Y. Zhang, Y.N. Zhang, Y.H. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, Li Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Dark photon search, Initial state radiation, BESIII, Physics, QC1-999
Abstract: Using a data set of 2.93 fb−1 taken at a center-of-mass energy s=3.773 GeV with the BESIII detector at the BEPCII collider, we perform a search for an extra U(1) gauge boson, also denoted as a dark photon. We examine the initial state radiation reactions e+e−→e+e−γISR and e+e−→μ+μ−γISR for this search, where the dark photon would appear as an enhancement in the invariant mass distribution of the leptonic pairs. We observe no obvious enhancement in the mass range between 1.5 and 3.4 GeV/c2 and set a 90% confidence level upper limit on the mixing strength of the dark photon and the Standard Model photon. We obtain a competitive limit in the tested mass range.
Published: 2017
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37. Measurement of cross sections of the interactions e+e−→ϕϕω and e+e−→ϕϕϕ at center-of-mass energies from 4.008 to 4.600 GeV

Author: M. Ablikim, M.N. Achasov, S. Ahmed, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, R.P. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Z.L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Y.B. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Y.Y. Liu, Z.A. Liu, Zhiqing Liu, H. Loehner, Y.F. Long, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, G. Morello, N.Yu. Muchnoi, H. Muramatsu, P. Musiol, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, W. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, Zongyuan Wang, T. Weber, D.H. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.N. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: e+e− annihilation, Triple quarkonia, Cross section, Physics, QC1-999
Abstract: Using data samples collected with the BESIII detector at the BEPCII collider at six center-of-mass energies between 4.008 and 4.600 GeV, we observe the processes e+e−→ϕϕω and e+e−→ϕϕϕ. The Born cross sections are measured and the ratio of the cross sections σ(e+e−→ϕϕω)/σ(e+e−→ϕϕϕ) is estimated to be 1.75±0.22±0.19 averaged over six energy points, where the first uncertainty is statistical and the second is systematic. The results represent first measurements of these interactions.
Published: 2017
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38. Observation of the decay Λc+→Σ−π+π+π0

Author: M. Ablikim, M.N. Achasov, S. Ahmed, M. Albrecht, A. Amoroso, F.F. An, Q. An, J.Z. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S.J. Chen, X.R. Chen, Y.B. Chen, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, O. Dorjkhaidav, Z.L. Dou, S.X. Du, P.F. Duan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, S. Fegan, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Y.G. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, S. Gu, Y.T. Gu, A.Q. Guo, L.B. Guo, R.P. Guo, Y.P. Guo, Z. Haddadi, S. Han, X.Q. Hao, F.A. Harris, K.L. He, X.Q. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Z.L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, T. Khan, P. Kiese, R. Kliemt, L. Koch, O.B. Kolcu, B. Kopf, M. Kornicer, M. Kuemmel, M. Kuhlmann, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, L. Lavezzi, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.L. Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, Ke Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Y.Y. Liu, Z.A. Liu, Zhiqing Liu, Y.F. Long, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, G. Morello, N.Yu. Muchnoi, H. Muramatsu, P. Musiol, A. Mustafa, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, J. Pellegrino, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, J.J. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Richter, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, J.J. Song, X.Y. Song, S. Sosio, C. Sowa, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.K. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, G.Y. Tang, X. Tang, I. Tapan, M. Tiemens, B.T. Tsednee, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, Dan Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, W.P. Wang, X.F. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, Y. Xia, D. Xiao, H. Xiao, Y.J. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, X.A. Xiong, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.H. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, Y.X. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Branching fraction, Charmed baryon, Weak decays, e+e− annihilation, BESIII, Physics, QC1-999
Abstract: We report the first observation of the decay Λc+→Σ−π+π+π0, based on data obtained in e+e− annihilations with an integrated luminosity of 567 pb−1 at s=4.6 GeV. The data were collected with the BESIII detector at the BEPCII storage rings. The absolute branching fraction B(Λc+→Σ−π+π+π0) is determined to be (2.11±0.33(stat.)±0.14(syst.))%. In addition, an improved measurement of B(Λ+c→Σ−π+π+) is determined as (1.81±0.17(stat.)±0.09(syst.))%.
Published: 2017
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39. Measurements of cross section of e+e−→pp¯π0 at center-of-mass energies between 4.008 and 4.600 GeV

Author: M. Ablikim, M.N. Achasov, S. Ahmed, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, O. Fedorov, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, R.P. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Y. Huang, Z.L. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Y.B. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Y.Y. Liu, Z.A. Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, P. Musiol, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, M. Shi, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, S.G. Wang, W. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.N. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Physics, QC1-999
Abstract: Based on e+e− annihilation data samples collected with the BESIII detector at the BEPCII collider at 13 center-of-mass energies from 4.008 to 4.600 GeV, measurements of the Born cross section of e+e−→pp¯π0 are performed. No significant resonant structure is observed in the measured energy dependence of the cross section. The upper limit on the Born cross section of e+e−→Y(4260)→pp¯π0 at the 90% C.L. is determined to be 0.01 pb. The upper limit on the ratio of the branching fractions B(Y(4260)→pp¯π0)B(Y(4260)→π+π−J/ψ) at the 90% C.L. is determined to be 0.02%. Keywords: Hadrons, Cross section measurements, Y(4260)
Published: 2017
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40. RESEARCH ON THE APPLICATION OF RAPID SURVEYING AND MAPPING FOR LARGE SCARE TOPOGRAPHIC MAP BY UAV AERIAL PHOTOGRAPHY SYSTEM

Author: Z. Gao, Y. Song, C. Li, F. Zeng, and F. Wang
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.
Published: 2017
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41. Study of J/ψ and ψ(3686)→Σ(1385)0Σ¯(1385)0 and Ξ0Ξ¯0

Author: M. Ablikim, M.N. Achasov, S. Ahmed, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, R.P. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Z.L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Y.B. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Y.Y. Liu, Z.A. Liu, Zhiqing Liu, H. Loehner, Y.F. Long, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, G. Morello, N.Yu. Muchnoi, H. Muramatsu, P. Musiol, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, W. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Y.H. Xie, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.N. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Charmonium, Branching fraction, Angular distribution, Physics, QC1-999
Abstract: We study the decays of J/ψ and ψ(3686) to the final states Σ(1385)0Σ¯(1385)0 and Ξ0Ξ¯0 based on a single baryon tag method using data samples of (1310.6±7.0)×106 J/ψ and (447.9±2.9)×106 ψ(3686) events collected with the BESIII detector at the BEPCII collider. The decays to Σ(1385)0Σ¯(1385)0 are observed for the first time. The measured branching fractions of J/ψ and ψ(3686) to Ξ0Ξ¯0 are in good agreement with, and much more precise than, the previously published results. The angular parameters for these decays are also measured for the first time. The measured angular decay parameter for J/ψ→Σ(1385)0Σ¯(1385)0, α=−0.64±0.03±0.10, is found to be negative, different to the other decay processes in this measurement. In addition, the “12% rule” and isospin symmetry in the decays of J/ψ and ψ(3686) to ΞΞ¯ and Σ(1385)Σ¯(1385) are tested.
Published: 2017
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42. Measurement of the absolute branching fraction for Λc+→Λμ+νμ

Author: M. Ablikim, M.N. Achasov, S. Ahmed, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, O. Bakina, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, R.P. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Z.L. Huang, T. Hussain, W. Ikegami Andersson, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, L. Lavezzi, H. Leithoff, C. Leng, C. Li, Li Cheng, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K. Li, Lei. Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Y.B. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, Q.J. Liu, S.B. Liu, X. Liu, Y.B. Liu, Y.Y. Liu, Z.A. Liu, Z.Q. Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, G. Mezzadri, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, P. Musiol, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, W. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Xie Yuehong, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, Z.Y. You, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.N. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Λc+, Semi-leptonic decay, Absolute branching fraction, BESIII, Physics, QC1-999
Abstract: We report the first measurement of the absolute branching fraction for Λc+→Λμ+νμ. This measurement is based on a sample of e+e− annihilation data produced at a center-of-mass energy s=4.6 GeV, collected with the BESIII detector at the BEPCII storage rings. The sample corresponds to an integrated luminosity of 567 pb−1. The branching fraction is determined to be B(Λc+→Λμ+νμ)=(3.49±0.46(stat)±0.27(syst))%. In addition, we calculate the ratio B(Λc+→Λμ+νμ)/B(Λc+→Λe+νe) to be 0.96±0.16(stat)±0.04(syst).
Published: 2017
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43. Measurements of the branching fractions for D+→KS0KS0K+, KS0KS0π+ and D0→KS0KS0, KS0KS0KS0

Author: M. Ablikim, M.N. Achasov, S. Ahmed, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, N. Berger, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J. Chai, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, J.C. Chen, M.L. Chen, S. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, O. Fedorov, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, R.P. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, F.H. Heinsius, T. Held, Y.K. Heng, T. Holtmann, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, X.Z. Huang, Y. Huang, Z.L. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, A. Kupsc, W. Kühn, J.S. Lange, M. Lara, P. Larin, H. Leithoff, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, H.J. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.N. Li, X.Q. Li, Y.B. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Y.Y. Liu, Z.A. Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, M.M. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, G. Mezzadri, J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, P. Musiol, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, A. Sarantsev, M. Savrié, C. Schnier, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, M. Shi, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, X.H. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, S.G. Wang, W. Wang, W.P. Wang, X.F. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, L.J. Wu, Z. Wu, L. Xia, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, J.J. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.Q. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.N. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: BESIII, D0 and D+ mesons, Hadronic decays, Branching fractions, Physics, QC1-999
Abstract: By analyzing 2.93fb−1 of data taken at the ψ(3770) resonance peak with the BESIII detector, we measure the branching fractions for the hadronic decays D+→KS0KS0K+, D+→KS0KS0π+, D0→KS0KS0 and D0→KS0KS0KS0. They are determined to be B(D+→KS0KS0K+)=(2.54±0.05stat.±0.12sys.)×10−3, B(D+→KS0KS0π+)=(2.70±0.05stat.±0.12sys.)×10−3, B(D0→KS0KS0)=(1.67±0.11stat.±0.11sys.)×10−4 and B(D0→KS0KS0KS0)=(7.21±0.33stat.±0.44sys.)×10−4, where the second one is measured for the first time and the others are measured with significantly improved precision over the previous measurements.
Published: 2017
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44. The lignin synthesis related genes and lodging resistance of Fagopyrum esculentum

Author: D. Hu, X. B. Liu, H. Z. She, Z. Gao, R. W. Ruan, D. Q. Wu, and Z. L. Yi
Subjects: common buckwheat, enzyme activities, gene expression, Biology (General), QH301-705.5, Plant ecology, QK900-989
Abstract: Lignin is closely related to the lodging resistance of common buckwheat (Fagopyrum esculentum Moench.). However, the characteristics of lignin synthesis related genes have not yet been reported. We investigated the lignin biosynthesis gene expression, activities of related enzymes, and accumulation of lignin monomers during branching stage, bloom stage, and milky ripe stage by real-time quantitative PCR, UVspectrophotometry, and gas chromatography-mass spectrometry in the 2nd internode of three common buckwheat cultivars with different lodging resistance. The results showed that lignin content and the activity of phenylalanine ammonia lyase (PAL), 4-coumarate: CoA ligase (4CL), cinnamyl alcohol dehydrogenase (CAD) and peroxidase (POD) were closely related to the lodging resistance of common buckwheat. Further, we studied gene expression of cinnamate 4-hydroxylase (C4H), caffeoyl-CoA O-methyltransferase (CCoAOMT), ferulate 5-hydroxylase (F5H), cinnamoyl-CoA reductase (CCR), and caffeic acid O-methyltransferase (COMT). The lignin biosynthesis genes were divided into three classes according to their expression pattern: 1) expression firstly increasing and then descending (PAL, 4CL, CAD, C4H, CCoAOMT, F5H, and CCR), 2) expression remaining constant during maturation (C3H), and 3) expression decreasing with maturation (COMT). The present study provides preliminary insights into the expression of lignin biosynthesis genes in common buckwheat, laying a foundation for further understanding the lignin biosynthesis.
Published: 2017
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45. Measurement of the leptonic decay width of J/ψ using initial state radiation

Author: M. Ablikim, M.N. Achasov, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, H.Y. Chen, J.C. Chen, M.L. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, S.X. Du, P.F. Duan, E.E. Eren, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.Y. Gao, Y. Gao, Z. Gao, I. Garzia, C. Geng, K. Goetzen, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, Y.L. Han, X.Q. Hao, F.A. Harris, K.L. He, Z.Y. He, T. Held, Y.K. Heng, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.M. Huang, G.S. Huang, H.P. Huang, J.S. Huang, X.T. Huang, Y. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.L. Jiang, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, W. Kuehn, A. Kupsc, J.S. Lange, M. Lara, P. Larin, C. Leng, C. Li, C.H. Li, Cheng Li, D.M. Li, F. Li, G. Li, H.B. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.M. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B.J. Liu, C.X. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, X.X. Liu, Y.B. Liu, Z.A. Liu, Zhiqiang Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, R.Q. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, M. Lv, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, F.E. Maas, M. Maggiora, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, K. Moriya, N.Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, Y.N. Pu, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Y. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, H.L. Ren, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, V. Santoro, A. Sarantsev, M. Savrié, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, M. Ullrich, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, S.G. Wang, W. Wang, X.F. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, Z. Wu, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y. Yang, Y.X. Yang, H. Ye, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, H.W. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.H. Zhang, X.Y. Zhang, Y. Zhang, Y.N. Zhang, Y.H. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, Li Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: J/ψ resonance, Electronic width, Initial state radiation, BESIII, Physics, QC1-999
Abstract: Using a data set of 2.93 fb−1 taken at a center-of-mass energy of s=3.773 GeV with the BESIII detector at the BEPCII collider, we measure the process e+e−→J/ψγ→μ+μ−γ and determine the product of the branching fraction and the electronic width Bμμ⋅Γee=(333.4±2.5stat±4.4sys) eV. Using the earlier-published BESIII result for Bμμ=(5.973±0.007stat±0.037sys)%, we derive the J/ψ electronic width Γee=(5.58±0.05stat±0.08sys) keV.
Published: 2016
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46. Spectral Induced Polarization of Biochar in Variably Saturated Soil

Author: Z. Gao, F.-H. Haegel, O. Esser, E. Zimmermann, H. Vereecken, and J.A. Huisman
Subjects: Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract: Biochar is considered a promising soil amendment, but an effective method to detect and characterize the spatial distribution and temporal dynamics of biochar in soil is still missing. The aim of this study is to investigate the ability of the spectral induced polarization (SIP) method for the noninvasive detection of biochar in unsaturated sandy media. In particular, a pure sand and two sand–biochar mixtures with 1 and 2% biochar made from pine ( spp.) wood by pyrolysis at 800°C were investigated. The measured SIP spectra as a function of saturation were interpreted by fitting a Cole–Cole model to the low-frequency part of the SIP measurements. The porous nature of the biochar particles strongly affected the SIP response of the partially saturated sand–biochar mixtures. Due to the high residual water content of the biochar in a dry background, the relationship between bulk electrical conductivity and water saturation was nonlinear in a log–log representation. This nonlinear behavior could adequately be explained with a dielectric mixing model that considered the drainage of the biochar particles. Both the measured phase and chargeability of the sand–biochar mixtures showed a complex dependence on water saturation. This was attributed to the decrease in polarization strength of the biochar particles with desaturation and the simultaneous increase in phase of the sand background. Overall, the results of this study suggest that field SIP measurements may be a promising tool for the characterization and monitoring of biochar amendments to agricultural soils.
Published: 2019
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47. Measurement of the e+e−→π+π− cross section between 600 and 900 MeV using initial state radiation

Author: M. Ablikim, M.N. Achasov, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, H.Y. Chen, J.C. Chen, M.L. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, S.X. Du, P.F. Duan, E.E. Eren, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.Y. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, X.Q. He, T. Held, Y.K. Heng, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.M. Huang, G.S. Huang, J.S. Huang, X.T. Huang, Y. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, W. Kühn, A. Kupsc, J.S. Lange, M. Lara, P. Larin, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.M. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B.J. Liu, C.X. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Z.A. Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, F.E. Maas, M. Maggiora, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, K. Moriya, N.Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, V. Santoro, A. Sarantsev, M. Savrié, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, M.R. Shepherd, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, M. Ullrich, I. Uman, G.S. Varner, B. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, S.G. Wang, W. Wang, X.F. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, Z. Wu, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, L. Xu, Q.J. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, X.Y. Zhang, Y. Zhang, Y.N. Zhang, Y.H. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Hadronic cross section, Muon anomaly, Initial state radiation, Pion form factor, BESIII, Physics, QC1-999
Abstract: We extract the e+e−→π+π− cross section in the energy range between 600 and 900 MeV, exploiting the method of initial state radiation. A data set with an integrated luminosity of 2.93 fb−1 taken at a center-of-mass energy of 3.773 GeV with the BESIII detector at the BEPCII collider is used. The cross section is measured with a systematic uncertainty of 0.9%. We extract the pion form factor |Fπ|2 as well as the contribution of the measured cross section to the leading-order hadronic vacuum polarization contribution to (g−2)μ. We find this value to be aμππ,LO(600–900MeV)=(368.2±2.5stat±3.3sys)⋅10−10, which is between the corresponding values using the BaBar or KLOE data.
Published: 2016
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48. Measurement of the branching fraction for ψ(3770)→γχc0

Author: M. Ablikim, M.N. Achasov, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, H.Y. Chen, J.C. Chen, M.L. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, Z.L. Dou, S.X. Du, P.F. Duan, E.E. Eren, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, R. Farinelli, L. Fava, O. Fedorov, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.L. Gao, X.Y. Gao, Y. Gao, Z. Gao, I. Garzia, K. Goetzen, L. Gong, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, X.Q. Hao, F.A. Harris, K.L. He, T. Held, Y.K. Heng, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.S. Huang, J.S. Huang, X.T. Huang, Y. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.W. Jiang, X.S. Jiang, X.Y. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, P. Kiese, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, W. Kuehn, A. Kupsc, J.S. Lange, M. Lara, P. Larin, C. Leng, C. Li, Cheng Li, D.M. Li, F. Li, F.Y. Li, G. Li, H.B. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, Q.Y. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.M. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B.J. Liu, C.X. Liu, D. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.B. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, Y.B. Liu, Z.A. Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, Q.M. Ma, T. Ma, X.N. Ma, X.Y. Ma, Y.M. Ma, F.E. Maas, M. Maggiora, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, N.Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, Y. Pan, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, V. Prasad, H.R. Qi, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, M. Ripka, G. Rong, Ch. Rosner, X.D. Ruan, V. Santoro, A. Sarantsev, M. Savrié, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, M. Ullrich, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, S.G. Wang, W. Wang, W.P. Wang, X.F. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, Z. Wu, L. Xia, L.G. Xia, Y. Xia, D. Xiao, H. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.J. Yang, H.X. Yang, L. Yang, Y.X. Yang, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, Z. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.N. Zhang, Y.T. Zhang, Yu Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, S.H. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: Physics, QC1-999
Abstract: By analyzing a data set of 2.92 fb−1 of e+e− collision data taken at s=3.773 GeV and 106.41×106 ψ(3686) decays taken at s=3.686 GeV with the BESIII detector at the BEPCII collider, we measure the branching fraction and the partial decay width for ψ(3770)→γχc0 to be B(ψ(3770)→γχc0)=(6.88±0.28±0.67)×10−3 and Γ[ψ(3770)→γχc0]=(187±8±19) keV, respectively. These are the most precise measurements to date.
Published: 2016
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49. An improved limit for Γee of X(3872) and Γee measurement of ψ(3686)

Author: M. Ablikim, M.N. Achasov, X.C. Ai, O. Albayrak, M. Albrecht, D.J. Ambrose, A. Amoroso, F.F. An, Q. An, J.Z. Bai, R. Baldini Ferroli, Y. Ban, D.W. Bennett, J.V. Bennett, M. Bertani, D. Bettoni, J.M. Bian, F. Bianchi, E. Boger, O. Bondarenko, I. Boyko, R.A. Briere, H. Cai, X. Cai, O. Cakir, A. Calcaterra, G.F. Cao, S.A. Cetin, J.F. Chang, G. Chelkov, G. Chen, H.S. Chen, H.Y. Chen, J.C. Chen, M.L. Chen, S.J. Chen, X. Chen, X.R. Chen, Y.B. Chen, H.P. Cheng, X.K. Chu, G. Cibinetto, D. Cronin-Hennessy, H.L. Dai, J.P. Dai, A. Dbeyssi, D. Dedovich, Z.Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L.Y. Dong, M.Y. Dong, S.X. Du, P.F. Duan, J.Z. Fan, J. Fang, S.S. Fang, X. Fang, Y. Fang, L. Fava, F. Feldbauer, G. Felici, C.Q. Feng, E. Fioravanti, M. Fritsch, C.D. Fu, Q. Gao, X.Y. Gao, Y. Gao, Z. Gao, I. Garzia, C. Geng, K. Goetzen, W.X. Gong, W. Gradl, M. Greco, M.H. Gu, Y.T. Gu, Y.H. Guan, A.Q. Guo, L.B. Guo, Y. Guo, Y.P. Guo, Z. Haddadi, A. Hafner, S. Han, Y.L. Han, X.Q. Hao, F.A. Harris, K.L. He, Z.Y. He, T. Held, Y.K. Heng, Z.L. Hou, C. Hu, H.M. Hu, J.F. Hu, T. Hu, Y. Hu, G.M. Huang, G.S. Huang, H.P. Huang, J.S. Huang, X.T. Huang, Y. Huang, T. Hussain, Q. Ji, Q.P. Ji, X.B. Ji, X.L. Ji, L.L. Jiang, L.W. Jiang, X.S. Jiang, J.B. Jiao, Z. Jiao, D.P. Jin, S. Jin, T. Johansson, A. Julin, N. Kalantar-Nayestanaki, X.L. Kang, X.S. Kang, M. Kavatsyuk, B.C. Ke, R. Kliemt, B. Kloss, O.B. Kolcu, B. Kopf, M. Kornicer, W. Kühn, A. Kupsc, W. Lai, J.S. Lange, M. Lara, P. Larin, C. Leng, C.H. Li, Cheng Li, D.M. Li, F. Li, G. Li, H.B. Li, J.C. Li, Jin Li, K. Li, Lei Li, P.R. Li, T. Li, W.D. Li, W.G. Li, X.L. Li, X.M. Li, X.N. Li, X.Q. Li, Z.B. Li, H. Liang, Y.F. Liang, Y.T. Liang, G.R. Liao, D.X. Lin, B.J. Liu, C.X. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.H. Liu, H.M. Liu, J. Liu, J.P. Liu, J.Y. Liu, K. Liu, K.Y. Liu, L.D. Liu, P.L. Liu, Q. Liu, S.B. Liu, X. Liu, X.X. Liu, Y.B. Liu, Z.A. Liu, Zhiqiang Liu, Zhiqing Liu, H. Loehner, X.C. Lou, H.J. Lu, J.G. Lu, R.Q. Lu, Y. Lu, Y.P. Lu, C.L. Luo, M.X. Luo, T. Luo, X.L. Luo, M. Lv, X.R. Lyu, F.C. Ma, H.L. Ma, L.L. Ma, Q.M. Ma, S. Ma, T. Ma, X.N. Ma, X.Y. Ma, F.E. Maas, M. Maggiora, Q.A. Malik, Y.J. Mao, Z.P. Mao, S. Marcello, J.G. Messchendorp, J. Min, T.J. Min, R.E. Mitchell, X.H. Mo, Y.J. Mo, C. Morales Morales, K. Moriya, N.Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I.B. Nikolaev, Z. Ning, S. Nisar, S.L. Niu, X.Y. Niu, S.L. Olsen, Q. Ouyang, S. Pacetti, P. Patteri, M. Pelizaeus, H.P. Peng, K. Peters, J. Pettersson, J.L. Ping, R.G. Ping, R. Poling, Y.N. Pu, M. Qi, S. Qian, C.F. Qiao, L.Q. Qin, N. Qin, X.S. Qin, Y. Qin, Z.H. Qin, J.F. Qiu, K.H. Rashid, C.F. Redmer, H.L. Ren, M. Ripka, G. Rong, X.D. Ruan, V. Santoro, A. Sarantsev, M. Savrié, K. Schoenning, S. Schumann, W. Shan, M. Shao, C.P. Shen, P.X. Shen, X.Y. Shen, H.Y. Sheng, W.M. Song, X.Y. Song, S. Sosio, S. Spataro, G.X. Sun, J.F. Sun, S.S. Sun, Y.J. Sun, Y.Z. Sun, Z.J. Sun, Z.T. Sun, C.J. Tang, X. Tang, I. Tapan, E.H. Thorndike, M. Tiemens, D. Toth, M. Ullrich, I. Uman, G.S. Varner, B. Wang, B.L. Wang, D. Wang, D.Y. Wang, K. Wang, L.L. Wang, L.S. Wang, M. Wang, P. Wang, P.L. Wang, Q.J. Wang, S.G. Wang, W. Wang, X.F. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.G. Wang, Z.H. Wang, Z.Y. Wang, T. Weber, D.H. Wei, J.B. Wei, P. Weidenkaff, S.P. Wen, U. Wiedner, M. Wolke, L.H. Wu, Z. Wu, L.G. Xia, Y. Xia, D. Xiao, Z.J. Xiao, Y.G. Xie, Q.L. Xiu, G.F. Xu, L. Xu, Q.J. Xu, Q.N. Xu, X.P. Xu, L. Yan, W.B. Yan, W.C. Yan, Y.H. Yan, H.X. Yang, L. Yang, Y. Yang, Y.X. Yang, H. Ye, M. Ye, M.H. Ye, J.H. Yin, B.X. Yu, C.X. Yu, H.W. Yu, J.S. Yu, C.Z. Yuan, W.L. Yuan, Y. Yuan, A. Yuncu, A.A. Zafar, A. Zallo, Y. Zeng, B.X. Zhang, B.Y. Zhang, C. Zhang, C.C. Zhang, D.H. Zhang, H.H. Zhang, H.Y. Zhang, J.J. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, K. Zhang, L. Zhang, S.H. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.T. Zhang, Z.H. Zhang, Z.P. Zhang, Z.Y. Zhang, G. Zhao, J.W. Zhao, J.Y. Zhao, J.Z. Zhao, Lei Zhao, Ling Zhao, M.G. Zhao, Q. Zhao, Q.W. Zhao, S.J. Zhao, T.C. Zhao, Y.B. Zhao, Z.G. Zhao, A. Zhemchugov, B. Zheng, J.P. Zheng, W.J. Zheng, Y.H. Zheng, B. Zhong, L. Zhou, Li Zhou, X. Zhou, X.K. Zhou, X.R. Zhou, X.Y. Zhou, K. Zhu, K.J. Zhu, S. Zhu, X.L. Zhu, Y.C. Zhu, Y.S. Zhu, Z.A. Zhu, J. Zhuang, L. Zotti, B.S. Zou, and J.H. Zou
Subjects: X(3872), ψ(3686), Γee, Charmonium spectroscopy, BESIII, Physics, QC1-999
Abstract: Using the data sets taken at center-of-mass energies above 4 GeV by the BESIII detector at the BEPCII storage ring, we search for the reaction e+e−→γISRX(3872)→γISRπ+π−J/ψ via the Initial State Radiation technique. The production of a resonance with quantum numbers JPC=1++ such as the X(3872) via single photon e+e− annihilation is forbidden, but is allowed by a next-to-leading order box diagram. We do not observe a significant signal of X(3872), and therefore give an upper limit for the electronic width times the branching fraction ΓeeX(3872)B(X(3872)→π+π−J/ψ)
Published: 2015
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50. Highly Sensitive Ratiometric Fluorescent Probe for the Detection of Mercury Ions

Author: Y. Yue, Z. Gao, L. Chen, R. Su, W. Qi, and Z. He
Subjects: Chemical engineering, TP155-156, Computer engineering. Computer hardware, TK7885-7895
Abstract: An effective dual-emission fluorescent probe combining gold nanoclusters (AuNCs) and carbon dots (CDs) was fabricated for the detection of mercury ions (Hg2+). CDs doped into silica nanoparticles exhibited a reference fluorescence signal, while the outer AuNCs layer stabilized by bovine serum albumin (BSA) was extremely sensitive to Hg2+. This probe selectively detected Hg2+ in a good linear range from 0.43 to 39 μM and a detection limit (signal-to-noise ratio is 3) of 81 nM. The increase in the Hg2+ concentration was accompanied by the colour change from reddish violet to blue. This method exhibited several advantages of facile preparation and operation and high selectivity and sensitivity. This dual-emission fluorescent probe has significant potential for the ‘‘naked eye’’ detection of Hg2+.
Published: 2017
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