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The Jiangmen Underground Neutrino Observatory (JUNO) is a state-of-the-art liquid scintillator-based neutrino physics experiment under construction in South China. To reduce the background from external radioactivities, a water Cherenkov detector composed of 35 kton ultra-pure water and 2,400 20-inch photomultiplier tubes is developed. Even after specialized treatment, ultra-pure water still contains trace levels of radioactive elements that can contribute to the detector background. Among which 222Rn is particularly significant. To address this, an online radon removal system based on the JUNO prototype has been developed. By integrating micro-bubble generators to enhance degasser's radon removal efficiency, the radon concentration in water can be reduced to 1 mBq/m3 level, meeting the stringent requirements of JUNO. Additionally, a highly sensitive online radon concentration measurement system capable of detecting concentrations ∼ 1 mBq/m 3 has been developed to monitor the radon concentration in water. In this paper, the details regarding both systems will be presented. [ABSTRACT FROM AUTHOR]

Anthropogenic activities alter the underlying surface conditions and arrangements of landscape features in a drainage basin, interfering with the pollutant (e.g., dissolved nitrogen, phosphorus) transport network configuration and altering the hydrological response. Assessing the impact of anthropogenic activities on hydrological connectivity for natural-artificial catchment is critical to understand the hydrological-driven ecosystem processes, services and biodiversity. However, quantifying this impact at catchment scale remains challenging. In this study, a new framework was proposed to quantify the impact of anthropogenic activities on hydrological connectivity combined with graph theory and network analysis. This framework was exemplified in a natural-artificial catchment of the Yangtze River basin of China. Based on remote sensing and field-investigated data, three transport networks were constructed, including natural transport network (N1), ditch–road transport network (N2), and terrace–dominated transport network (N3), which reflected the different human intervention. The results showed that human intervention improved the connectivity of the nodes and enhanced the complexity of the catchment transport network structure. Anthropogenic activities significantly decreased the hydrological structural connectivity of the catchment. In particular, compared with the N1 network, the critical nodes for hydrological connectivity which were judged by connectivity indexes were reduced by 92.94% and 95.29% in the N2 and N3 network, respectively. Furthermore, the ditch–road construction had a greater impact than terraces in decreasing hydrological structural connectivity at catchment scale. This framework has proven effective in quantifying the hydrological connectivity analysis under different human intervention at the catchment scale and facilitates the improvement of catchment management strategies. • A new framework was proposed to identify catchment hydrological connectivity. • Graph theory combined with network analysis were integrated into the framework. • Three transport networks were constructed to exemplify the framework. • Ditches, roads, and terraces significantly decreased hydrological connectivity. [ABSTRACT FROM AUTHOR]

[Display omitted] • Machine learning approaches quantified the effects of hydrological and landscape metrics on water quality. • Impacts of hydrological and landscape metrics on water quality varied with hydrological regulations. • Landscape composition exhibited the largest impact on water quality during the FDPs. • Landscape configuration had the largest impact on water quality during the WSPs. Dam construction and reservoir operation altered the landscape and hydrological process of reservoir bays, affecting reservoir water quality. However, many landscape and hydrological connectivity metrics are highly correlated and may introduce redundancies and misleading results when use conventional multivariate regression techniques. Knowledge concerning the pure effects of landscape and hydrological connectivity metrics are crucial for understanding nonpoint pollution processes and guiding water quality protection strategies in reservoirs. Based on water quality monitoring data for six years (2015–2020) from 66 reservoir bays of the Danjiangkou Reservoir in China during both flood discharge periods (FDPs) and water storage periods (WSPs), machine learning approaches (boosted regression trees and random forest) were conducted to decipher the effects of hydrological connectivity and landscape characteristics on water quality. The results showed that landscape composition, landscape configuration, and topography had the combined importance of 46.69%, 31.48%, and 10.14% on the overall water quality changes during the FDPs, respectively. However, landscape configuration was the largest importance factor controlling overall water quality for the WSPs with the combined importance of 38.57%. For the FDPs, the top two importance variables of overall water quality variation were the proportions of shrub and agricultural land in the reservoir bay. For the WSPs, the top two importance variables were flow length and index of connectivity. For specific water quality parameters, the highest importance factor controlling the variation in total nitrogen, total phosphorus, ammonia nitrogen, nitrate and chlorophyll a were landscape configuration, while the landscape composition had the highest importance on the variation in permanganate index, suggesting landscape characteristics affected water quality with specific responses to distinct water quality parameters. These findings emphasize the distinct roles of landscape and hydrological characteristics on water quality and provide important information for the efficient formulation of water quality protection strategies in reservoirs. [ABSTRACT FROM AUTHOR]

Background: The role of endovascular therapy for acute stroke with a large infarction has not been extensively studied in differing populations., Methods: We conducted a multicenter, prospective, open-label, randomized trial in China involving patients with acute large-vessel occlusion in the anterior circulation and an Alberta Stroke Program Early Computed Tomography Score of 3 to 5 (range, 0 to 10, with lower values indicating larger infarction) or an infarct-core volume of 70 to 100 ml. Patients were randomly assigned in a 1:1 ratio within 24 hours from the time they were last known to be well to undergo endovascular therapy and receive medical management or to receive medical management alone. The primary outcome was the score on the modified Rankin scale at 90 days (scores range from 0 to 6, with higher scores indicating greater disability), and the primary objective was to determine whether a shift in the distribution of the scores on the modified Rankin scale at 90 days had occurred between the two groups. Secondary outcomes included scores of 0 to 2 and 0 to 3 on the modified Rankin scale. The primary safety outcome was symptomatic intracranial hemorrhage within 48 hours after randomization., Results: A total of 456 patients were enrolled; 231 were assigned to the endovascular-therapy group and 225 to the medical-management group. Approximately 28% of the patients in both groups received intravenous thrombolysis. The trial was stopped early owing to the efficacy of endovascular therapy after the second interim analysis. At 90 days, a shift in the distribution of scores on the modified Rankin scale toward better outcomes was observed in favor of endovascular therapy over medical management alone (generalized odds ratio, 1.37; 95% confidence interval, 1.11 to 1.69; P = 0.004). Symptomatic intracranial hemorrhage occurred in 14 of 230 patients (6.1%) in the endovascular-therapy group and in 6 of 225 patients (2.7%) in the medical-management group; any intracranial hemorrhage occurred in 113 (49.1%) and 39 (17.3%), respectively. Results for the secondary outcomes generally supported those of the primary analysis., Conclusions: In a trial conducted in China, patients with large cerebral infarctions had better outcomes with endovascular therapy administered within 24 hours than with medical management alone but had more intracranial hemorrhages. (Funded by Covidien Healthcare International Trading [Shanghai] and others; ANGEL-ASPECT ClinicalTrials.gov number, NCT04551664.)., (Copyright © 2023 Massachusetts Medical Society.)