海拔和坡向对唐古拉山土壤胞外酶活性的影响

土壤胞外酶够将大分子有机质分解成可以被微生物利用的小分子化合物,在土壤有机质分解与转化过程中起着重要的作用。因此,土壤中酶促反应往往成为陆地生态系统中土壤有机质分解的限速步骤。然而,土壤酶活性的地理分布格局,尤其是其随着不同海拔和坡向的分布特征和驱动机制,仍不明确。为探讨土壤胞外酶的空间分布特征及影响因素,我们沿海拔梯度(2980—5120 m)在青藏高原唐古拉山的南北坡选取了6个样点,测定了参与碳、氮、磷循环的6种水解酶的活性和土壤理化性质,并结合植被和气象数据进行分析。结果显示,随海拔梯度的升高,年均温度(MAT)、土壤碳氮比(C:N)降低,年均降水量(MAP)、紫外线辐射(UV)、归一化植被指数(NDVI)、土壤碳含量(TC)、土壤氮含量(TN)升高;南坡的MAP、UV、NDVI、TC、TN显著高于北坡,而C∶N显著低于北坡。不同类型的土壤胞外酶对海拔和坡向的响应不同,碳获取酶α-葡萄糖苷酶(AG)、β-葡萄糖苷酶(BG)、β-木糖苷酶(BX),以及氮获取酶N-乙酰-氨基葡萄糖苷酶(NAG)活性均随海拔梯度的升高而升高,且都在南坡显著高于北坡;磷获取酶酸性磷酸酶(AP)和氮获取酶亮氨酸氨基肽酶(LAP)活性在不同海拔和坡向的分布上并没有显著差异。模型平均和相对重要性分析表明,NDVI、RB和TC是驱动碳获取酶(AG、BG、BX)活性随海拔梯度和坡向分布格局的主要因子;NDVI是驱动参与氮获取酶(NAG)活性变化的主要因子。我们的研究结果表明,不同海拔和坡向上植被和土壤特征的差异驱动了土壤胞外酶活性的空间分布,从而可能对碳循环和养分循环产生不同的影响,为预测土壤胞外酶的空间地理格局提供了科学依据

中国脑血管病临床管理指南（第2版）（节选）——第3章 脑血管病高危人群管理 Chinese Stroke Association Guidelines for Clinical Management of Cerebrovascular Diseases (Second Edition) (Except) ——Chapter Three Management of Patients at Hige-risk of Cerebrovascular Diseases

针对脑血管病的危险因素积极进行早期干预管理是减少脑血管病危害最有效的方法。本章节介绍脑血管病高危人群管理的推荐意见，包括对不可干预和可干预血管危险因素的控制，阿司匹林在缺血性卒中一级预防中的应用以及首次卒中风险评估等方面。 Abstract: Early intervention to manage the risk factors of cerebrovascular disease is the most effective way to reduce the harm of cerebrovascular diseases. This chapter presents recommendations for the management of populations at high risk for cerebrovascular disease, including control of non-interventionable and interventionable vascular risk factors, the use of aspirin in the primary prevention of ischaemic stroke, and the risk assessment of first-time stroke

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies