The forecasting efficiency under different selected regions by Pattern Informatics Method and seismic potential estimation in the North-South Seismic Zone

In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.

基于S-R和分解定理的二维几何非线性问题的虚单元法求解

应变-旋转(Strain-Rotation,S-R)和分解定理为分析几何非线性问题提供了合理可靠的理论基础,但用有限元求解时会遇到大变形发生后的网格畸变问题。近年提出的虚单元法(Virtual element method,VEM)适用于一般的多边形网格,因此,该文尝试使用一阶虚单元求解基于S-R和分解定理的二维几何非线性问题,以克服网格畸变的影响。基于重新定义的多项式位移空间基函数,推演获得一阶虚单元分析线弹性力学问题时允许位移空间向多项式位移空间的投影表达式;按照虚单元法双线性格式的计算规则,分析处理基于更新拖带坐标法和势能率原理的增量变分方程;进而建立离散系统方程及其矩阵表达形式,并编制MATLAB求解程序;采用常规多边形网格和畸变网格,应用该文算法分析均布荷载下的悬臂梁和均匀内压下的厚壁圆筒变形。结果与已有文献和ANSYS软件的对比表明:该文算法在两种网格中均可有效执行且具备足够数值精度。总体该文算法为基于S-R和分解定理的二维几何非线性问题求解提供了一种鲁棒方法。

Ⅰ导联R/(R+S)对胸前V3导联移行流出道室性心律失常起源部位的鉴别价值

目的:探索鉴别胸前V3导联移行流出道室性心律失常(OT-VA)起源部位的体表心电图指标。方法:连续选择2017年1月至2022年8月行导管射频消融术的胸前V3导联移行OT-VA患者65例。比较左室流出道起源组(LVOT组)和右室流出道起源组(RVOT组)室性心律失常发作时体表心电图QRS波振幅及相关指标的差异,选择差异有统计学意义的指标,绘制ROC曲线评价所选取指标鉴别OT-VA起源部位的效能。结果:LVOT组11例,RVOT组54例,两组间差异有统计学意义且ROC曲线下面积(AUC)最大的指标为Ⅰ导联R波/(R+S)波振幅比[R/(R+S)],其鉴别OT-VA起源部位的AUC(95%CI)为0.949(0.894~1.000),截断值为0.50。Ⅰ导联R/(R+S)<0.50诊断胸前V3导联移行LVOT起源OT-VA的敏感度、特异度和准确度分别为0.909、0.944和0.938。结论:Ⅰ导联R/(R+S)<0.50可准确鉴别LVOT起源的胸前V3导联移行OT-VA。

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。

R.S.托马斯诗歌中的反田园书写

R.S.托马斯的诗歌展现了威尔士乡村一系列反田园特质,包括几乎绝望的风景、花园里的机器和自然界弱肉强食的暴力法则。这种现实主义的反田园书写反映了托马斯的民族主义情结、反现代主义和生态主义的立场。通过探讨田园与反田园的含义,分析托马斯诗歌中的反田园书写及其现实关怀,有助于挖掘他积极的入世态度和道德情怀。

达人主播直播带货对消费者购买意愿的双路径影响——基于SOR及ELM模型的分析

文章基于SOR模型和ELM模型,研究了达人主播直播带货营销对消费者购买意愿的影响机理。该研究发现,消费者购买意愿通过中心路径和边缘路径被影响,中心路径因素为信息质量和促销激励,而边缘路径因素为达人主播的专业性、知名度和社会临场感。此外,消费者的感知信任和感知价值对其购买意愿具有显著正向影响,并在不同因素之间起中介作用。本研究结果提供了一个包括感知信任和感知价值双路径的中介影响模型框架,为未来研究该领域提供了新的思路和实证基础。

R/S Analysis and its Application in the Forecast of Mine Inflows

In this paper, the status quo and modeling principles of R/S analysis of non-linear theory are introduced and reviewed. Given the hydro-geological conditions of the Wutongzhuang coal mine, Hurst exponents of mine inflow for the main shaft, venti- lating shaft and auxiliary shaft were obtained using R/S analysis, which are 0.772 0, 0.824 7 and 0.905 1 respectively. Since all of the three Hurst exponents are larger than 0.5, it can be concluded that the trend of mine inflow are a long-term as well as persistent problem. Based on the level of duration, the shafts can be listed in decreasing order as the auxiliary shaft, the ventilation shaft and the main shaft, which appears identical with the actual situation of the mine inflow. With R/S analysis, a new method for long-term forecasting of mine inflows is provided.

(1R,2S)-2-氟环丙胺对甲苯磺酸盐合成工艺的改进

研究了(1R,2S)-2-氟环丙胺对甲苯磺酸盐的合成工艺。以丁二烯为原料,经过成环、氧化、还原、拆分等反应,设计合成(1S,2S)-2-氟环丙甲酸,通过考察与优化确定了最佳反应条件;进一步制得目标产物(1R,2S)-2-氟环丙胺对甲苯磺酸盐,产物收率达到75%。

碱促进的(3aS,4R,6aR)-双苄基生物素转化为(3aS,4S,6aR)-双苄基生物素的研究

目的:将生物素关键中体(3aS,4S,6aR)-双苄基生物素合成过程中产生的杂质(3aS,4R,6aR)-双苄基生物素经化学反应转化为产物(3aS,4S,6aR)-双苄基生物素。方法:通过碱催化反应,(3aS,4R,6aR)-双苄基生物素能顺利地转化为(3aS,4S,6aR)-双苄基生物素。结果:以异丙醇为溶剂,甲醇钠为催化剂,(3aS,4R,6aR)-双苄基生物素在25℃下搅拌24 h,以32.5%的收率得到(3aS,4S,6aR)-双苄基生物素。结论:该工艺为生物素工业生产中产生的杂质(3aS,4R,6aR)-双苄基生物素的回收利用提供了一种可行的方法。

阿富汗地震R/S分形特征及地震活动性分析

地震的发生具有非线性特征,分形理论能够刻画地震时空分布特征及其变化过程。本文基于R/S分析方法确定阿富汗主要地震带的分形特征,利用ARIMA模型对兴都—库什山地震带可能发生的年度最大震级进行预测。R/S分析表明,兴都—库什山地震带Hurst指数为0.9125,地震活动记忆周期为8年;苏莱曼山地震带Hurst指数为0.7281,地震活动记忆周期为9年。兴都—库什山和苏莱曼山地震带地震活动的变化趋势与历史变化一致,且兴都—库什山地震带的趋势延续性比苏莱曼山地震带更为显著。ARIMA模型预测结果显示,2022—2026年兴都—库什山地震带可能发生的年度最大震级分别为M_(b)6.2、M_(b)6.1、M_(b)5.8、M_(b)5.8和M_(b)6.1。

The Collaboratory for the Study of Earthquake Predictability in China:Experiment Design and Preliminary Results of CSEP2.0

Since the inaugural international collaboration under the framework of the Collaboratory for the Study of Earthquake Predictability(CSEP)in 2007,numerous forecast models have been developed and operated for earthquake forecasting experiments across CSEP testing centers(Schorlemmer et al.,2018).Over more than a decade,efforts to compare forecasts with observed earthquakes using numerous statistical test methods and insights into earthquake predictability,which have become a highlight of the CSEP platform.

A data assimilation-based forecast model of outer radiation belt electron fluxes

Because radiation belt electrons can pose a potential threat to the safety of satellites orbiting in space,it is of great importance to develop a reliable model that can predict the highly dynamic variations in outer radiation belt electron fluxes.In the present study,we develop a forecast model of radiation belt electron fluxes based on the data assimilation method,in terms of Van Allen Probe measurements combined with three-dimensional radiation belt numerical simulations.Our forecast model can cover the entire outer radiation belt with a high temporal resolution(1 hour)and a spatial resolution of 0.25 L over a wide range of both electron energy(0.1-5.0 MeV)and pitch angle(5°-90°).On the basis of this model,we forecast hourly electron fluxes for the next 1,2,and 3 days during an intense geomagnetic storm and evaluate the corresponding prediction performance.Our model can reasonably predict the stormtime evolution of radiation belt electrons with high prediction efficiency(up to~0.8-1).The best prediction performance is found for~0.3-3 MeV electrons at L=~3.25-4.5,which extends to higher L and lower energies with increasing pitch angle.Our results demonstrate that the forecast model developed can be a powerful tool to predict the spatiotemporal changes in outer radiation belt electron fluxes,and the model has both scientific significance and practical implications.

Factors Limiting the Forecast Skill of the Boreal Summer Intraseasonal Oscillation in a Subseasonal-to-Seasonal Model

In this study,we evaluate the forecast skill of the subseasonal-to-seasonal(S2S)prediction model of the Beijing Climate Center(BCC)for the boreal summer intraseasonal oscillation(BSISO).We also discuss the key factors that inhibit the BSISO forecast skill in this model.Based on the bivariate anomaly correlation coefficient(ACC)of the BSISO index,defined by the first two EOF modes of outgoing longwave radiation and 850-hPa zonal wind anomalies over the Asian monsoon region,we found that the hindcast skill degraded as the lead time increased.The ACC dropped to below 0.5for lead times of 11 days and longer when the predicted BSISO showed weakened strength and insignificant northward propagation.To identify what causes the weakened forecast skill of BSISO at the forecast lead time of 11 days,we diagnosed the main mechanisms responsible for the BSISO northward propagation.The same analysis was also carried out using the observations and the outputs of the four-day forecast lead that successfully predicted the observed northward-propagating BSISO.We found that the lack of northward propagation at the 11-day forecast lead was due to insufficient increases in low-level cyclonic vorticity,moistening and warm temperature anomalies to the north of the convection,which were induced by the interaction between background mean flows and BSISO-related anomalous fields.The BCC S2S model can predict the background monsoon circulations,such as the low-level southerly and the northerly and easterly vertical shears,but has limited capability in forecasting the distributions of circulation and moisture anomalies.

固定化脂肪酶手性拆分(R,S)-1-苯基乙醇研究进展

(R,S)-1-苯基乙醇是药物合成与精细化学品的重要中间体,可经固定化脂肪酶不对称催化获得光学纯1-苯基乙醇。本文分别从脂肪酶类型、溶剂工程、固定化技术三方面综述了国内外固定化脂肪酶手性拆分(R,S)-1-苯基乙醇的研究进展,并指明该领域中亟待解决的关键问题及解决思路,以期为后续固定化脂肪酶应用于手性拆分(R,S)-1-苯基乙醇提供参考。

Verification of an operational ocean circulation-surface wave coupled forecasting system for the China＇s seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.

航天器S4R电源技术在公路零碳中的应用

空间电源S4R控制技术在有效利用光伏阵列,提高电能的高效控制和转换方面,尤其是在高可靠性、模块化、高可扩展性电源供应方面的优点,与高速公路数字转型和智慧升级及“双碳”策略带来的沿线设备电力供应新的需求相匹配。本文介绍了一套将S4R功率调节技术用于高速公路供电的新型拓扑,实现用电点能源自洽,满足数字化、零碳化和智慧升级的需求。

基于R/S分析的BP网络方法预测气井产量

本文利用R/S分析法对气井产量进行分析,提出了历史数据的时间序列和平稳时间序列两种不同表达方式,并利用BP网络方法预测出了气井产量。为验证这种方法的有效性,分别对BP网络与BP神经网络、贝叶斯算法三种方法进行了比较。结果表明,贝叶斯算法获得的预测结果比其他两种方法更准确、更符合实际。贝叶斯算法得到的预测结果与实际值的平均误差分别为0.67%和0.33%,而采用传统BP神经网络得到的预测结果与实际值的平均误差分别为1.71%和0.96%。

基于NAR神经网络和R/S分析法的隧道围岩变形预测分析

为研究隧道围岩变形非线性特点,采用NAR神经网络和R/S分析法,对隧道围岩变形量和变形趋势进行分析。通过NAR神经网络对变形监测样本进行误差分析,认为NAR神经网络对围岩变形短期预测时的误差小精度高。运用R/S分析法对各变形时间序列进行重标极差分析,获得各时序的Hurst指数,分析其与围岩变形趋势的关系,并通过Hurst指数对隧道围岩变形趋势进行判定。结果表明:算例中的断面围岩变形仍然会呈增长趋势,但增长幅度在减小,且水平收敛的趋势性强于拱顶沉降,说明前者受随机扰动影响较小,后期稳定性相对更高。通过运用R/S分析法进行时间序列分析,不仅为围岩变形趋势预判提供了Hurst指数判据,同时也为围岩稳定性分析及治理提供了一种依据。

不同下壁导联室性早搏R/S波比值的慢性心力衰竭患者近期预后随访分析

目的对不同下壁导联室性早搏R/S波比值的慢性心力衰竭患者近期预后随访进行分析。方法选择2020年3月~2022年3月本院收治的93例动态心电图检查存在室性早搏的CHF患者93例。所有患者完善24h动态心电图检查,随访一年。依照近期预后进行分组,将出现急性心肌梗死、恶性心律失常等不良心脏事件纳入预后不良组(n=37),其余未出现心脏不良事件的患者纳入预后良好组(n=56)。比较两组不同下壁导联室性早搏R/S波比值的预后。结果两组在年龄、BMI、吸烟、高血压、糖尿病、LVEF、利尿剂、地高辛方面差异无统计学意义(P>0.05);两组在性别、NYHA分级上差异有统计学意义(P<0.05);预后良好组R/S比值≥1例数比率高于预后不良组,R/S比值<1例数比例低于预后不良组,差异有统计学意义(P<0.05)。Logistic回归分析显示,R/S比值<1与性别、NYHA分级均是CHF患者近期预后不良的独立危险因素(P<0.05)。结论不同下壁导联的室性早搏R/S比值与其预后具有相关性,R/S比值<1是其不良预后的预测因素。

Forecasting Inflation Rate of Zambia Using Holt’s Exponential Smoothing

In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2010 to May 2014. Results show that the ARIMA ((12), 1, 0) is an adequate model which best fits the CPI time series data and is therefore suitable for forecasting CPI and subsequently the inflation rate. However, the choice of the Holt’s exponential smoothing is as good as an ARIMA model considering the smaller deviations in the mean absolute percentage error and mean square error. Moreover, the Holt’s exponential smoothing model is less complicated since you do not require specialised software to implement it as is the case for ARIMA models. The forecasted inflation rate for April and May, 2015 is 7.0 and 6.6 respectively.