Different El Niño Flavors and Associated Atmospheric Teleconnections as Simulated in a Hybrid Coupled Model

A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.

Dynamical Predictability of Leading Interannual Variability Modes of the Asian-Australian Monsoon in Climate Models

The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide.Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences,especially for the second mode.The first AAM mode,from various seasonal sequences,coincides with the El Niño phase transition in the eastern-central Pacific.The second mode,initialized from boreal summer and autumn,leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring.Our findings hint that ENSO,as an early signal,is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes.Still,the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features.The multimodel ensemble(MME)mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features.The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes.The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.

基于O-AMAS的翻转课堂在临床药理学教学中的探索

临床药理学是连接药学与临床医学间的重要基础课程。文章通过对临床医学专业连续两届参加本课程学习的本科生分别进行传统的授课方式(对照组)以及翻转课堂模式(研究组)的教学,并展开比较研究。结果表明,研究组学生的理论考试总成绩为明显高于对照组。两组学生对基础知识掌握并无明显差异,但在病例分析综合应用上,研究组学生的得分显著优于对照组。通过匿名的问卷调研,研究组学生具有更好的学习体验感,新教学方式取得了较好的教学效果。

基于S-O-R模型的视觉营销对消费者购买意愿的影响研究——以红色文创网店为例

为提高红色文创网店的点击转化率,文章从消费者视角出发,研究影响消费者购买意愿的视觉因素。基于S-O-R模型理论,构建红色文创网店视觉营销对消费者购买意愿因素的理论模型。利用S-O-R模型分析了红色文创网店视觉营销中的商品形象、界面形象以及品牌视觉形象对顾客感知价值及顾客购买意向的影响。通过设计量表和调查问卷进行实证研究,并结合结构方程模型加以论证,得出品牌视觉形象和界面形象是影响消费者购买意愿的关键因素,为设计师和红色文创品牌进行网店设计提供了一定的理论参考和建议。

稻麦复种模式下氮肥与稻秸互作对小麦产量和N_(2)O排放影响及推荐施肥研究

优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入下小麦产量和N_(2)O排放变化的文献,运用随机森林建模,定量分析氮肥和秸秆还田对小麦产量和N_(2)O排放的影响,并结合情景设置进行了特定地点的小麦产量和N_(2)O排放模拟,同时评估了碳排放强度(CEE)和净生态系统经济效益(NEEB)。结果表明,建立的区域尺度小麦产量与N_(2)O排放对氮秸互作响应的随机森林模型,验证结果R^(2)分别为0.66和0.65,RMSE分别为0.70和1.11。结果表明施氮量和土壤有机质是影响小麦产量和N_(2)O排放的重要因素。综合来看,达到最大产量所需的氮肥量为208~212 kg hm^(-2),达到最小CEE所需的氮肥量为113~130 kg hm^(-2),达到最高的NEEB所需的氮肥量为202~205 kg hm^(-2),其中在6.75 t hm^(-2)的秸秆投入下施用202 kg hm^(-2)的氮肥可以获得最高的生态收益1.37万元。优化氮肥和秸秆投入具备减少作物碳排放强度并获得最大净生态环境效益的潜力。

FOUNDATION OF NUCLEAR ALGEBRAIC MODELS

Based upon Tomonoga-Rowe's many body theory, we find that the algebraic models, including IBM and FDSM are simplest extension of Rowe-Rosensteel's sp(3R).Dynkin-Gruber's subalgebra embedding method is applied to find an appropriate algebra and it's reduction chains conforming to physical requirement. The separated cases sp(6) and so(8) now appear as two branches stemming from the same root D6-O(12). Transitional ease between sp(6) and so(8) is inherently include.

表面粗糙度对橡塑O形圈往复密封性能的影响

建立三维确定性混合润滑数值仿真模型,该模型采用统一Reynolds方程系统法,耦合了固体力学分析、流体力学分析和接触力学分析;生成非高斯粗糙表面,基于混合润滑模型研究表面粗糙度、自相关长度比值和纹理方向对橡塑O形圈往复密封摩擦力、泄漏率、平均膜厚和接触面积比等密封性能的影响规律。研究表明:低速时随着表面粗糙度的增大,润滑区接触面积比增大,引起摩擦因数增大,平均膜厚先增大后减小,临界接触面积比约为40%;在混合润滑状态时,对于横向纹理粗糙表面,存在合适的自相关长度比值使得密封的摩擦因数和接触面积比最低;当纹理方向θ=π/10时,摩擦因数最小。

海洋环流模式的并行I/O优化研究

极端气象日益加剧,严重影响人类的生产生活。如何有效应对未来极端环境变化,更关乎国际竞争。因此,发展高精度高分辨率的地球系统模式推动气候变化研究至关重要。随着模式精度和分辨率的不断提高,I/O性能已成为制约模式计算效率和可扩展性的瓶颈。选取典型的海洋环流模式LICOM3作为研究对象,基于天河HPC系统,详细测试和分析了模式的I/O逻辑过程,发现在3K进程规模下I/O可占整体运行时间一半以上,是限制模式计算性能的关键因素。为此,设计并实现了主要输出过程的MPI-IO并行优化方案,显著提升了模式运行效率,基本解决了模式I/O瓶颈。测试结果表明,MPI-IO并行优化方案将输出时间占比从48.58%降到2.44%,将输出带宽提升到6.21 GB/s,约是原程序的14倍。此外,进一步分析了影响并行I/O性能的因素,以期为相关工作提供参考和指导。

低比例甲醇掺混下氨/甲醇燃烧的化学机制和N_(2)O生成分析

为探究氨燃料减少温室气体(GHG)排放的效益,克服氨点火能量较高、层流火焰速度较慢的缺点,使用Chemkin构建化学反应器网格(CRN)仿真模型对低比例甲醇(0~10%)与氨掺混燃烧进行组分演化、产物生成速率和敏感性分析,利用化学反应动力学,分析N_(2)O生成和还原机理。结果表明:纯氨燃烧在当量比为1.1~1.2时,可同时降低NO、未燃NH_(3)和N_(2)O的排放,较纯甲醇燃烧可减少70%以上的温室气体排放;当量比超过0.9时,氨燃烧的GHG排放始终低于纯甲醇燃烧。加入甲醇能有效控制N_(2)O生成,进一步降低GHG排放。在富燃条件下,甲醇的添加促进了H的生成,使N_(2)O消耗增加;在贫燃条件下,甲醇的增强抑制了NH的生产,使N_(2)O生成降低。另外,提高压力和温度也能有效降低温室气体排放。

O-AMAS有效教学模型在“健康评估”课程中的应用与评价

目的:探索O-AMAS有效教学模型在“健康评估”课程中的应用并评价效果。方法:选取大理大学2020、2021级护理专业学生为研究对象,按教学模式分为对照组和实验组,对照组采用传统教学模式教学,实验组采用O-AMAS有效教学模型进行课程教学设计,比较2组学生的评判性思维能力、自主学习能力、学生随堂测验和师生互评结果。结果:实验组学生的评判性思维能力、自主学习能力、学生评教、教师评学及随堂测验得分均显著高于观察组(P<0.001)。结论:将O-AMAS模型融入“健康评估”的课程设计,可以提升教学质量和师生满意度,培养学生自主学习能力和评判性思维能力,O-AMAS教学模型可推广至其他课程教学。

Cake models applied to evaluate the fouling mechanism in separation of anionic polyacrylamide using modified PVDF ultrafiltration membranes

In the present study,nano-sized TiO2 /Al2O3 modified PVDF membranes (MM) were fabricated and utilized for anionic polyacrylamide ( APAM) separation. The results showed that,compared with PVDF membrane (OM) ,the contact angle of MM decreases from 83. 64° to 67. 42°,which indicates the increase of the hydrophilicity of MM. The relative flux (RF) decline curve of this ultrafiltration of APAM in water with time shows an obvious two stage properties. The cake filtration models were used to predict the performance of different time over the complete range of filtration times. All the four cake models could simulate this UF process to a certain extent,and the suitability of the two kinds of membranes was: cake filtration > intermediate pore blocking > standard pore blocking > complete pore blocking models. However,they became more and more unsuited to this process with time extending. Surface and cross-sectional morphology of membrane was investigated by SEM to make an advanced certificate of this UF mechanism.

基于DNDC模型的红壤旱坡花生地N_(2)O排放模拟研究

为探究DNDC模型在红壤旱坡地N_(2)O排放模拟的适用性,以赣北红壤旱坡花生地为研究对象,设置常规耕作和轻简化免耕2种处理,连续3年(2019—2021年)采用静态箱-气相色谱法开展N_(2)O排放的田间原位观测试验,研究不同耕作处理下N_(2)O排放特征及DNDC模型模拟效果。结果表明:DNDC模型对不同耕作处理下0~10 cm土壤温度(相关系数r为0.86~0.87)和作物产量(r为0.90)的模拟效果较好。该模型能较好地模拟花生季因施肥和降雨引起的N_(2)O排放波动变化,也能较好地模拟常规耕作下土壤N_(2)O排放峰,但会在一定程度上低估轻简化免耕的N_(2)O排放峰和排放总量,且模型对16 mm以下的降雨响应较小。土壤pH值、施肥量对红壤旱坡花生地N_(2)O排放的影响最大,降雨量、土壤有机碳含量和粘粒含量也是影响N_(2)O排放的重要因子。模型模拟2019年不同施肥量下N_(2)O排放总量与花生产量发现,氮肥施用量不能低于76.54 kg/hm^(2),也不宜超过106.78 kg/hm^(2)。研究结果可为红壤坡耕地作物种植优化、农业温室气体减排等提供理论依据。

某型飞机舱盖关键元件O形密封圈气密性分析

对某飞机舱盖作动筒异常弹出进行分析,原因是油液中的气体导致油液体积弹性模量变小,可压缩性增强,易发生弹出现象。基于IFAS模型得到含气量与油液体积弹性模量的关系。座舱盖液压操纵系统密封区域均采用O形密封圈进行密封,但由于关键元件粗糙表面特征的存在构成气体泄漏通道,导致座舱盖液压操纵系统中混入气体。因此提出了一种基于Roth模型的泄漏率计算方法,将O形密封圈与金属粗糙表面之间的接触关系,看作弹性金属光滑表面和刚性金属粗糙表面之间的接触关系,对金属粗糙度表面轮廓三角峰均一化排列,从而将泄漏路径定义为梯形通道。基于有限元软件ABAQUS计算密封圈的密封性能系数,分析了表面粗糙度及偏载情况对气体泄漏率的影响;最后通过ANSYS仿真分析与理论结果进行对比。该工作对高精密的密封结构加工设计有着重要指导意义。

Analysis models and methods on the network storage system I/O performance

Network storage provides high scalability, availability and flexibility for storage systems, and is widely applied to many fields. Particularly, I/O performance is of great significance. Its application is wide and expanding rapidly. I/O performance has already become the bottleneck of the whole performance of computer systems for a long time, and under the condition of the present computer technology, I/O performance optimization method looks especially important. In the paper, I/O performance model was analyzed based on the combination of quasi birth, death process and queuing model, and then solved the model. A number of important related performance indicators and the relationship between them were given. By the way of example, this method can show the I/O performance more accurately. Finally, we got some useful conclusions, which may be used to evaluate network storage performance, and are the basis of confirming I/O scheduling strategy.

基于混合Logit模型的仙女山国家森林公园游客行为的影响因素研究

研究森林公园的游客行为特征及影响因素,有助于促进当地的旅游发展,推动经济可持续增长,为森林公园的高质量发展提供研究基础。以仙女山国家森林公园为例,通过实地调查获取游客的社会经济特征、态度量表及行为特征,运用S-O-R框架构建森林公园游客的行为特征分析框架,利用MIMIC模型拟合行为特征分析框架,引入混合Logit模型探索社会经济特征和态度变量对游客行为的影响。结果表明:(1)仙女山国家森林公园以市内游客为主,多以陪伴家人、休闲度假为主要动机。(2)研究证实了构建的行为分析框架对森林公园游客的行为具有解释效力。(3)各变量对旅游行为的影响依次为主体认知(-0.278)>主体选择(-0.160)>旅游地条件(0.204)>主体感受(0.373)。

Estimating the Yield Loss of Winter Wheat from Drought in the United States Southern Plains Region as Influenced by El Niño-Southern Oscillation (ENSO)

Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.

O-U模型下基于HARA效用的最优投资–再保险策略问题

研究了O-U(Ornstein-Uhlenbeck)风险模型下最大化双曲绝对风险(Hyperbolic Abso-lute Risk Aversion,HARA)效用的最优投资–再保险问题。允许保险人购买比例再保险,且可投资于一种无风险资产和一种风险资产,其瞬间收益率由能够反映市场的牛市和熊市特征的O-U过程刻画。在保险人终端财富的HARA效用期望最大化的目标下,利用随机动态规划原理,首先建立了Hamilton-Jacobi-Bellman(HJB)方程。其次,由于HARA效用函数的复杂结构导致常规方法难以求解HJB方程,利用勒让德对偶变换将HJB方程转化为易于求解的对偶HJB方程。通过构造对偶HJB方程解的形式及变量变换,得到了最优再保险–投资策略的解析式。最后通过数值计算分析了参数对最优结果的影响。

基于改进G-O模型的软件可靠性测试方法

为克服传统G-O(Goel-Okumoto)软件可靠性模型中缺陷发现率过于简化处理的局限性,提出了一种以更精准的方式描述缺陷发现率随时间实际变化的模型。改进模型不同于常规假设将其视为恒定或单调的函数,并考虑了测试人员的学习和排错能力的进步,以及软件固有的缺陷发现率随时间递减的趋势,从而假设缺陷发现率呈现先上升后下降的动态变化趋势。通过在两组公开的软件缺陷检测数据集上的应用,并与多种经典的模型进行了对比验证,验证了模型的有效性。实验结果表明,改进后的G-O模型在拟合能力和预测能力方面都显示出优异的性能,证明其在软件可靠性评估中的适用性和优越性。

基于物理模型与统计分析的作动器活动密封O形圈磨损预测研究

在实际服役环境中,飞机发生的总故障的40%是由于密封泄漏造成的,其密封性能的优劣直接影响产品的功能、性能和使用可靠性。然而,飞机上缺乏对密封圈的磨损监测,导致密封圈健康状态难以评估。针对这一问题,本研究提出了一种基于物理模型与统计分析的活动密封O形圈磨损预测方法,首先对密封圈的磨损进行了机理分析和参数测定;其次,采用Abaqus有限元软件模拟研究了密封圈的运动过程,得到密封圈的接触应力;然后,对舵机每个架次的累计行程进行统计分析,得到行程的概率统计曲线,结合Holm-Archard磨损模型得到磨损体积的概率分布曲线;最后,结合时间与行程的关系,建立了磨损体积与时间之间的数学模型。采用多个样本进行验证,结果表明,实际磨损体积在预测密度函数的3σ范围内的概率为95.83%,证明本研究建立的模型能够有较大概率预测活动密封的O形圈的体积磨损情况。

智慧医疗背景下“O+O”模式在糖尿病肾病病人居家护理中的应用

目的:探究智慧医疗背景下的“O+O(offline+online)”模式在糖尿病肾病(DN)病人居家护理中的应用效果。方法:选取2022年5月—2023年5月于我院接受居家护理的120例DN病人为研究对象,采用随机双盲法将其分为对照组(n=60)和观察组(n=60),对照组病人实施常规居家护理,观察组病人实施“O+O”模式下的居家护理;干预前及干预后3、6、12个月比较两组病人的管理依从性、实验室指标、生活质量及护理满意度。结果:干预后观察组病人空腹血糖、餐后2 h血糖、糖化血红蛋白(HbAlc)、尿蛋白定量(U-TP)、血压较对照组病人降低,依从性及生活质量、护理满意度较对照组升高,差异均有统计学意义(P<0.05)。结论:“O+O”模式能够提高DN病人居家护理依从性,有助于DN病人血糖、HbA1c、血压、U-TP的控制,且能提高DN病人生活质量及护理满意度。