Centrifugal Model Tests on the Settlement of Railway Embankment on Deep,Completely Decomposed Granite Soil

Settlement control of high-speed railways is a key technology in embankment engineering. In order to reveal the engineering characteristics of the deep, completely decomposed granite soil in the Hainan East Ring Railway, four groups of centrifuge model tests were conducted. We studied the settlement properties, under the embankment action, of untreated subsoil, subsoil treated by dynamic compaction, and subsoil reinforced with cement-mixed piles. In particular, we examined the relationship between settlement and time, including the settlement during and after construction. The results show that the Weibull model can describe the relationship between embankment settlement and time well, and that the post-construction settlements of the subsoil meet the requirements of the relevant code. Among the two foundation treatment measures, dynamic compaction is more effective than reinforcement with cement-mixed piles. The tested pressure on the contact surface between embankment and subsoil was obviously different from the commonly used calculated values.

The Seasonal Climatic Simulation of 9000 Years before Present by Using the IAP Atmospheric General Circulation Model

The seasonal cycle of the climate of 9000 years before present was simulated with the IAP two-level atmospheric general circulation model. The incoming solar radiation was specified from the orbital parameters for 9000 years ago. The boundary conditions of that time were prescribed to the present value because of the small differences between the two. The change in radiation makes temperature to be higher in summer and lower in winter over large areas of the land; and the increased temperature contrast between the land and the ocean strengthens the summer monsoon circulation and increases the precipitation over there. The asymmetry of temperature change between the Northern Hemisphere and the Southern Hemisphere and between summer and winter still exists, which agrees with that get from the previous perpetual experiments.

Global Climate Internal Variability in a 2000-year Control Simulation with Community Earth System Model(CESM)

Using the low-resolution(T31, equivalent to 3.75°× 3.75°) version of the Community Earth System Model(CESM) from the National Center for Atmospheric Research(NCAR), a global climate simulation was carried out with fixed external forcing factors(1850 Common Era.(C.E.) conditions) for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the El Nio-Southern Oscillation(ENSO), the Atlantic Multi-decadal Oscillation(AMO), the Pacific Decadal Oscillation(PDO), and the North Atlantic Oscillation(NAO), were compared with reanalysis datasets to evaluate the model performance. The results are as follows: 1) CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2) climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3) the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3–8 years variability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natural variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.

Streamflow Decomposition Based Integrated ANN Model

The prediction of riverflows requires the understanding of rainfall-runoff process which is highly nonlinear, dynamic and complex in nature. In this research streamflow decomposition based integrated ANN (SD-ANN) model is developed to improve the efficacy rather than using a single ANN model for the flow hydrograph. The streamflows are decomposed into two states namely 1) the rise state and 2) the fall state. The rainfall-runoff data obtained from the Kolar River basin is used to test the efficacy of the proposed model when compared to feed-forward ANN model (FF-ANN). The results obtained in this study indicate that the proposed SD-ANN model outperforms the single ANN model in terms of both the statistical indices and the prediction of high flows.

Prediction on Cold Chain Logistics Demand of Urban Residents in Jiangsu Province during the Twelfth Five-Year Plan Period——Based on Estimates of GM(1,1) Model

This paper takes the total yield of products that need refrigerated transport as the impact factors of transport aggregate of cold chain logistics,such as meat,aquatic products,quick-frozen noodle,fruits,vegetables,dairy,and medicine.Through selecting the consumption data of urban residents on transported products via cold chain in Jiangsu Province from 2005 to 2000 as sample,this paper establishes grey prediction model GM(1,1) of cold chain logistics demand and uses DPS7.05 software for test,to predict the cold chain logistics demand of urban residents in Jiangsu Province during the Twelfth Five-Year Plan period.The results show that in the period 2010-2015,the cold chain logistics demand of urban residents in Jiangsu Province is 1 151.589 1,1 185.136 6,1 219.661 3,1 255.191 8,1 291.757 3,1 329.388 1 t respectively;in the period 2005-2010,the cold chain logistics demand of urban residents in Jiangsu Province increases at annual growth rate of 3.9%;in the period 2011-2015,the growth rate declines to some extent,increasing slowly at rate of 2.9%.

A Structural Overview through GR(s) Models Characteristics for Better Yearly Runoff Simulation

In rainfall-runoff modelling, a monthly timescale and an annual one are sufficient for the management of deductions. However, to simulate the flow at a large time-step (annual), we generally precede the use of a model working for a finer time-step (daily) while aggregating the desired outputs. The finest time-steps are considered, apriori, as the most performant. By passing from one time-step to another, and in order to work in the desired time-step (annual) and calculate the potential gains or loss, this article proposed a comparative study between the aggregation method of outputs of a modal working at a finer time step, and a method in which we use a conceived model from the beginning. To ensure this comparative and empirical approach, the choice has been focused on (GRs) models to a daily time-step (GR4J), monthly time step (GR2M) and annual time step (GR1A). The modelling platform used is the same for all three models taking into account the specificities of each one: the same data sample, the same optimization method, and the same function criterion are used during the construction of these models. Due to the moving between these time steps, results show that the best way to simulate the annual flow is to use an appropriate and designed modal initially conceived to this time step. Indeed, this simulation seems to be less effective when using a model at a finer time-step (daily).

The estimation of yearly probability gain for seismic statistical model

Based on the calculation method of information gain in the stochastic process presented by Vere-Jones, the rela tion between information gain and probability gain is studied, which is very common in earthquake prediction, and the yearly probability gain for seismic statistical model is proposed. The method is applied to the non stationary Poisson model with whole-process exponential increase and stress release model. In addition, the prediction method of stress release model is obtained based on the inverse function simulation method of stochastic variable.

Remote forcing of Indian Ocean warming on Northwest Pacific during El Nio decaying years:a FOAM model approach

This paper attempts to analyze in detail the remote influence of the Indian Ocean Basin warming on the Northwest Pacific(NWP) during the year of decaying El Ni o.Observation data and the Fast Ocean- Atmosphere coupled Model 1.5 were used to investigate the triggering conditions under which the remote influence is formed between the positive sea surface temperature(SST) anomaly in the North Indian Ocean and the Anomalous Northwest Pacific anticyclone(ANWPA).Our research show that it is only when there is a contributory background wind field over the Indian Ocean,i.e.,when the Indian Summer Monsoon(ISM) reaches its peak,that the warmer SST anomaly in the North Indian Ocean incites significant easterly wind anomalies in the lower atmosphere of the Indo-West tropical Pacific.This then produces the remote influence on the ANWPA.Therefore,the SST anomaly in the North Indian Ocean might interfere with the prediction of the East Asia Summer Monsoon in the year of decaying El Ni o.Both the sustaining effect of local negative SST anomalies in the NWP,and the remote effect of positive SST anomalies in the North Indian Ocean on the ANWPA,should be considered in further research.

A spatiotemporal 3D convolutional neural network model for ENSO predictions: A test case for the 2020/21 La Niña conditions

2020–22年间热带太平洋经历了持续性多年的拉尼娜事件,多数耦合模式都难以准确预测其演变过程,这为厄尔尼诺-南方涛动(ENSO)的实时预测带来了很大的挑战.同时,目前学术界对此次持续性双拉尼娜事件的发展仍缺乏合理的物理解释,其所涉及的物理过程和机制有待于进一步分析.本研究利用再分析数据产品分析了热带东南太平洋东南风异常及其引起的次表层海温异常在此次热带太平洋海表温度(SST)异常演变中的作用,并构建了一个时空分离(Time-Space)的三维(3D)卷积神经网络模型(TS-3DCNN)对此次双拉尼娜事件进行实时预测和过程分析.通过将TS-3DCNN与中国科学院海洋研究所(IOCAS)中等复杂程度海气耦合模式(IOCAS ICM)的预测结果对比,表明TS-3DCNN模型对2020–22年双重拉尼娜现象的预测能力与IOCAS ICM相当,二者均能够从2021年初的初始场开始较好地预测2021年末El Niño3.4区SST的演变.此外,基于TS-3DCNN和IOCAS ICM的敏感性试验也验证了赤道外风场异常和次表层海温异常在2021年末赤道中东太平洋海表二次变冷过程中的关键作用.未来将神经网络与动力模式模式间的有效结合,进一步发展神经网络与物理过程相结合的混合建模是进一步提高ENSO事件预测能力的有效途径.

基于Word2Vec和LDA主题模型的中国省级五年规划“文化政策”文本研究

运用Word2Vec和LDA相结合的主题模型分析技术,对我国31个省份三个时期五年规划文本中文化政策部分进行主题识别,从时间和空间两个维度进行“文化政策”主题挖掘和演化分析。研究发现,“文化政策”主题在发展趋势、重点转移、政策导向、技术应用等方面随时间推移呈现不同演化趋势;四大区域受经济发展水平、文化资源禀赋、政策导向影响,在企业角色强调程度、地区特色旅游发展以及国家级项目和竞争力方面存在地域差异。

Proposed Wave Momentum Source for Generating the 22-Year Solar Cycle

For the 22-year solar cycle oscillation there is no external time dependent source. A nonlinear oscillation, the solar cycle must be generated internally, and Babcock-Leighton models apply an artificial nonlinear source term that can simulate the observations—which leaves open the question of the actual source mechanism for the solar cycle. Addressing this question, we propose to take guidance from the wave mechanism that generates the 2-year Quasi-biennial Oscillation (QBO) in the Earth atmosphere. Upward propagating gravity waves, eastward and westward, deposit momentum to generate the observed zonal wind oscillation. On the Sun, helioseismology has provided a thorough understanding of the acoustic p-waves, which propagate down into the convective envelope guided by the increasing temperature and related propagation velocity. Near the tachocline with low turbulent viscosity, the waves propagating eastward and westward can produce an axisymmetric 22-year oscillation of the zonal flow velocities that can generate the magnetic solar dynamo. Following the Earth model, waves in opposite directions can generate in the Sun wind and magnetic field oscillations in opposite directions, the proposition of a potential solar cycle mechanism.

湘赣流域旅游产业效率的时空演化与比较——基于“十二五”和“十三五”时期的数据

旅游效率是衡量旅游业高质量发展的重要指标之一。通过建立五个要素层、六个指标的投入体系和两个要素层、四个指标的产出体系,运用DEA-MI模型,探讨赣江流域和湘江流域在“十二五”和“十三五”时期旅游业的时空变化,可以为流域旅游效率的发展提供参考。在时序演进上,两江流域旅游效率呈“M”型走向趋势;“十二五”时期赣江流域依靠优势资源取胜,“十三五”时期湘江流域依靠“头部文化”转败为胜;其中技术水平的发展速度是影响旅游业发展的主导因素。在空间分布上,两江流域标准差椭圆始终呈现“东北—西南”方向;赣江流域的空间格局变动主要体现在“十三五”时期,湘江流域则主要集中在“十二五”时期;长、潭、永包围圈的发展模式是湘江流域旅游业成功的关键。

40岁以上人群缺血性脑卒中风险现况调查及预测模型的构建

目的调查1623例>40岁人群缺血性脑卒中(CIS)风险现况,并构建预测模型,旨在为有效预防CIS提供科学依据。方法2015年1月至2020年1月,采用随机抽样法抽取>40岁1623例作为调查对象,进行脑卒中问卷调查、体格检查和实验室检查,根据是否患有CIS分组,比较两组临床资料,通过logistic多因素回归模型分析诱发CIS的危险因素,绘制受试者工作特征(ROC)曲线分析logistic回归模型对>40岁人群发生CIS的预测价值。结果1623例>40岁人中79例确诊CIS,患病率为4.87%。患病组和未患病组年龄、高血压、糖尿病、血脂异常、卒中家族史及血清硫氧还蛋白(Trx)、甘露糖结合凝集素相关丝氨酸蛋白酶3(MASP-3)、甘露聚糖结合凝集素(MBL)水平差异有统计学意义(P<0.05)。年龄(≥60岁)、高血压、糖尿病、血脂异常、脑卒中家族史、Trx>9.10μg·L^(-1)为CIS的危险因素,MASP-3>450.40μg·L^(-1)、MBL>25.31μg·L^(-1)为CIS的保护因素(P<0.05)。年龄、高血压、糖尿病、血脂异常、脑卒中家族史、Trx、MASP-3、MBL联合预测CIS的曲线下面积(AUC)为0.831,预测敏感度为91.36%,特异度为78.52%。结论>40岁人群CIS发生风险较高,主要与年龄、高血压、糖尿病、血脂异常、卒中家族史及血清Trx、MASP-3、MBL水平等因素有关。

1990-2019年中国归因于高体质指数的2型糖尿病疾病负担分析与预测研究

背景中国的糖尿病患者数位居全球首位。近年来糖尿病患病率和死亡率不断上升,威胁人们健康水平,给我国人民群众带来沉重负担。随着肥胖患病率不断上升,预计糖尿病疾病负担将持续上升,糖尿病已成为我国不容忽视的公共卫生问题。目的描述和分析1990—2019年中国归因于高BMI的2型糖尿病疾病负担状况及其变化趋势,预测2020—2024年中国归因于高BMI的2型糖尿病疾病负担状况,旨在为中国2型糖尿病科学防控提供依据。方法于2023年5月,从2019年全球疾病负担(GBD 2019)中提取1990—2019年中国2型糖尿病伤残调整寿命年(DALYs)、DALYs率、标化DALYs率、死亡人数、死亡率及标化死亡率等疾病负担指标的数据,采用联结点回归模型通过年度变化百分比(APC)和平均年度变化百分比(AAPC)分析其变化趋势。基于1990—2016年数据(训练集),构建归因于高BMI的2型糖尿病DALYs率和死亡率的自回归移动平均(ARIMA)模型,利用2017—2019年数据(测试集)进行模型评价。用预测值与实际值得到的相对误差、模型的平均绝对误差(MAE)、平均绝对百分比误差(MAPE)、均方误差(MASE)及均方根误差(RMSE)判断模型预测效果,选择最佳模型预测2020—2024年中国归因于高BMI的2型糖尿病疾病负担。结果1990—2019年:疾病负担整体呈上升趋势(标化DALYs率AAPC=2.85%,标化死亡率AAPC=2.32%,均P<0.05),标化DALYs率从80.21/10万增至181.54/10万,标化死亡率从1.25/10万增至2.39/10万;男性和女性的标化DALYs率和标化死亡率均呈快速上升趋势,与1990年相比,2019年男性标化DALYs率增长了173%,女性增长了89%,男性标化死亡率增长了146%,女性增长了58%;DALYs率和死亡率随年龄增加明显增加,DALYs率在30岁后迅速增加,高峰基本维持在65~69岁(1990年337.47/10万,2019年711.09/10万)和70~74岁年龄组(1990年323.64/10万,2019年730.47/10万),人群死亡率在45岁后迅速增加,高峰维持在95岁以上(1990年12.78/10万,2019年33.29/10万);与全球相比,我国归因于高BMI的2型糖尿病的DALYs率和死亡率整体增速均较高。在1990—2019年中均有4个时间拐点,标化DALYs率和标化死亡率分别在2000—2004年和1996—2004年增速最快。经ARIMA模型预测得到2020—2024年中国归因于高BMI的2型糖尿病标化DALYs率和标化死亡率均呈持续上升趋势,到2024年分别达到205.142/10万(95%CI=189.775/10万~220.508/10万)和2.621/10万(95%CI=2.343/10万~2.900/10万)。结论我国归因于高BMI的2型糖尿病的疾病负担总体呈上升趋势,表现为由伤残导致的疾病负担与死亡人数升高,且增速高于全球。我国男性归因于高BMI的2型糖尿病的疾病负担逐渐高于女性,归因于高BMI的2型糖尿病的DALYs率和死亡率有年轻化趋势,ARIMA模型显示归因于高BMI的2型糖尿病的疾病负担预计将持续上升。为减轻2型糖尿病疾病负担,应该对重点人群(男性、中老年人群)加强健康教育,以提高对糖尿病防治的知晓度,可以通过提倡健康饮食和生活习惯加强体质量管理。

海河流域盛夏降水预测模型的研发和适用性分析

海河流域初夏(6月)和盛夏(7~8月)的降水有显著的年代际变化差异,尤其在2002年之后,海河流域初夏和盛夏的年代际变化特征相反,因此有必要分别针对夏季不同阶段建立预测模型。本文基于年际增量的思想,寻找影响海河流域盛夏降水异常的预测因子,以突出年际变化异常的影响信号。前冬欧亚中高纬度关键区域海平面气压指数SLPI(Sea Level Pressure Index)、6月热带中东太平洋海温Niño3指数以及表征厄尔尼诺—南方涛动现象(El Niño–Southern Oscillation,简称ENSO)演变速度的Niño3指数在6月与1月之差的年际增量作为三个关键预测因子,建立回归方程。进一步利用多模式的2022年6月Niño3指数的预报结果代入预测模型,对海河流域2022年盛夏降水进行预报试验。相对各动力气候模式3月起报的盛夏降水异常预测,基于年际增量的回归模型对海河流域盛夏降水异常拟合和回报的准确率更高,尤其是降水显著偏多年份,预测技巧更突出。进一步对预报偏差较大的年份复盘归因发现,前冬海平面气压指数对冬季风和夏季风转换关系的描述可能受到后期春夏热带太平洋和印度洋海温异常演变的干扰。当前冬海平面气压指数预示的后期海温演变与实际海温演变信号差异较大时,需关注动力模式对临近热带海温尤其是热带印度洋海表温度距平的预报以及海温变化对海河流域盛夏降水的可能影响。

基于GWO-Prophet的商品销售预测研究

零售企业的各项经营活动都离不开商品的销售情况,对商品的销售预测为企业制定生产计划与经营决策等活动提供重要的依据。针对企业销售额预测中销售额时间序列受外界条件影响大,预测精度低等问题,论文提出了一种基于GWO-Prophet的商品销售预测方法。基于某零售企业2015年-2018年销售额数据,通过Prophet模型将高维的销售额数据分别构建对应趋势项、季节项、节假日项、残差项的低维时序特征分量,分别用这些低维特征分量进行拟合后通过加法模型累加来预测未来一年的销售额数据;通过灰狼寻优算法(GWO)对Prophet模型参数进行智能寻优,防止模型陷入局部最优从而提高模型的精确度,通过灰狼寻优算法优化后的Prophet模型能更好地拟合突变点,季节项,节假日项等外界因素对销售额的影响。以MAE、MAPE和RMSE作为模型评估的指标,结果表明,基于GWO-Prophet模型的预测精度不仅优于单一的Prophet模型,还优于其他如ARIMA、SARIMA、LSTM对比模型。

基于PMC指数模型的知识产权政策评价研究

随着创新驱动发展战略深入实施,知识产权对国家治理体系现代化和高质量发展的作用日益凸显,完备科学的知识产权政策评价模型,有助于现行政策体系优化和未来政策制定。本文选取中央及省、自治区、直辖市出台的29个知识产权“十四五”规划政策,基于扎根理论和PMC指数模型,构建知识产权“十四五”规划政策评价模型,测算各政策文本的PMC指数并绘制PMC曲线图,从政策评价等级、四大地区政策、城市群政策等多个视角进行对比分析。研究表明:中国知识产权“十四五”规划政策体系整体质量良好,部分政策存在政策视野受限、政策覆盖面不足等问题,对新发展背景下知识产权发展的需求回应力度不足。基于此,提出强化政策协同性、健全政策评估体系、构建多主体参与机制等对策建议。

0~3岁婴幼儿家长托育服务需求现状及优化策略——基于Kano模型的分析

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