STABILITY OF TIME-PERIODIC TRAVELING FRONTS IN BISTABLE REACTION-ADVECTION-DIFFUSION EQUATIONS

This paper is concerned with the global exponential stability of time periodic traveling fronts of reaction-advection-diffusion equations with time periodic bistable nonlinearity in infinite cylinders. It is well known that such traveling fronts exist and are asymptotically stable. In this paper, we further show that such fronts are globally exponentially stable. The main difficulty is to construct appropriate supersolutions and subsolutions.

Characteristics of Water Environment in Regions of Zhaling and Eling Lakes near Waterhead of Yellow River

Conditions of the water environment in the region of the Zhaling and Eling lakes, which are located in the frozen earth zone on the Qingzang plateau, are unique. The equilibrium of the water quantity of the two lakes is maladjustment under the condition of a dry and cold climate in which evaporation is greater than precipitation. The Zhaling and Eling lakes have been atrophying, leaving three lake terraces and star studded lagoons around the two lakes since Holocene. When these lagoons were separated from the original lakes, they became cut lake basins, and were transformed from fresh water lakes into salt water lakes, salt lakes or salt playas owing to strong evaporation. This kind of evolutionary process will continue in the future.

Convenient Way of Extend Linear Expenditure System Modeling without Regression

Extend Linear Expenditure System model is a collection of multiple linear models, and modeling is a clearly tedious process. The innovation of this paper is trying to find a simple way of ELES modeling, which means, in order to omit the modeling process one by one, we try to use Excel functionality to create a model workplace. As long as you replace the original sample data in the workspace, you can get the results you want.

Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023?

In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter.In this report,as shown in the multi-model ensemble mean(MME)prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences,a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months,which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection,thus serving to modulate the winter climate in East Asia and North America.Despite some uncertainty due to unpredictable internal atmospheric variability,the global mean surface temperature(GMST)in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend.Specifically,the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter,and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991.Moreover,the necessary early warnings are still reliable in the timely updated mediumterm numerical weather forecasts and sub-seasonal-to-seasonal prediction.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature(CMST) Dataset

According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.

基于时空综合分型的El Niňo事件对中国东部降水的影响差异

基于1961—2022年中国高分辨率降水格点资料、合成分析和经验正交函数分解方法,揭示了时空综合分型得到的生命史较长-异常中心位置偏东的低频-东部(LF-EP)型和生命史较短-异常中心位置偏西的准两年-中部(QB-CP)型El Niňo事件对中国东部降水的不同影响。结果表明,LF-EP型事件对降水的影响显著且稳定:自发展年秋季到衰减年夏季长达近4个季节,长江以南区域降水持续地显著偏多,且异常雨带中心自衰减年春季起逐步北抬。QB-CP型事件发生时降水异常特征变化更加复杂多变:发展年夏秋季其空间分布与LF-EP型事件中的特征大致相反,长江以南区域降水整体偏少,冬季开始长江以南逐渐有正异常降水出现,且春季以后异常雨带表现出逐渐南退特征,至衰减年夏季发展为华北-长江中下游-华南地区降水异常“正-负-正”分布。进一步通过比较不同类型事件中大尺度水汽输送的差异探讨了其影响不同的可能机制,发现由海温异常纬向位置差异导致的西太平洋区域大气环流直接响应以及衍生模态响应差异是造成中国东部降水异常空间分布特征差异的重要原因。同时,两类时空事件持续性和转相时间的差异也会使得对降水影响的时间尺度出现差别。

河北省城乡居民消费结构变动研究——基于ELES模型的实证分析

基于ELES模型,对2013-2021年河北省城乡居民消费结构变动情况进行了研究.从边际消费倾向可以看出,随着生活水平的提高,河北省城乡居民的消费逐渐从“温饱型”向“小康型”转变.消费结构变动度分析显示,除个别年份外,居民消费结构整体变动不大,相对较稳定.通过分析消费结构熵数发现,河北省城乡居民整体消费质量较高,但是消费结构升级速度相对较慢.根据分析结果,提出了增加居民收入、优化消费环境、拓展新型消费、坚持推进城乡融合发展、提高农村居民的社会保障水平等建议.

两类厄尔尼诺事件对次年山东夏季降水的影响研究

厄尔尼诺(El Nino)事件可根据海温极大值中心分为东部型El Nino和中部型El Nino。本研究通过观测资料研究了1979-2020年两类El Nino事件对次年山东夏季(6-8月)季节平均和月平均降水异常的影响。结果显示,中部型El Nino次年夏季西北太平洋反气旋较气候态偏北,进而增强东亚夏季风,使得山东夏季平均降水偏多。伴随着反气旋在季节内的北移,降水正异常在晚夏(8月)最为显著,而东部型El Nino次年夏季反气旋较气候态偏南偏弱。同期日本列岛地区由于东亚-太平洋遥相关负位相的出现产生异常气旋,山东地区受气旋西侧干冷北风控制,夏季降水偏少。由于气旋强度在季节内逐渐降低,所以山东干旱在初夏(6月)最显著。这些结果可以为未来山东夏季降水季节预测提供重要参考。

Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

Mafic and felsic magmatism in the Wadi Kalalat area, South Eastern Desert, Egypt: mineralogy, geochemistry and geodynamic evolution during the Neoproterozoic in the Nubian Shield

In the south Eastern Desert of Egypt,two contrasting types of magmatism(mafic and felsic) are recorded in the Wadi Kalalat area,and form the Gabal El Motaghiarat and Gabal Batuga intrusions,respectively.The two intrusions post-dates ophiolitic and arc associations represented by serpentinite and metagabbro-diorite,respectively.The mafic intrusion has a basal ultramafic member represented by fresh peridotite,which is followed upward by olivine gabbro and anorthositic or leucogabbro.This mafic intrusion pertains to the Alaskan-type mafic-ultramafic intrusions in the Arabian-Nubian Shield(ANS)being of tholeiitic nature and emplaced in a typical arc setting.On the other hand,the Gabal Batuga intrusion comprises three varieties of fresh A-type granites of high K-calc alkaline nature,which is peraluminous and garnetbearing in parts.A narrow thermal aureole in the olivine gabbro of the mafic intrusion was developed due to the intrusion of the Batuga granites.This results in the development of a hornfelsic melagabbro variety in which the composition changed from tholeiitic to a calc-alkaline composition due to the addition of S_(i)O_(2),Al_(2)O_(3),alkalis,lithosphile elements(LILEs) such as Rb(70 ppm) and Y(28 ppm) from the felsic intrusion.Outside the thermal aureole,Rb amounts 2-8 ppm and Y lies in the range <2-6ppm.It is believed that the Gabal Batuga felsic intrusion started to emplace during the waning stage of an arc system,with transition from the pre-collisional(i.e.,arc setting) to post-collisional and within plate settings.Magma from which the Gabal Batuga granites were fractionated is high-K calc-alkaline giving rise to a typical post-collisional A-type granite(A_(2)-subtype) indicating an origin from an underplating crustal source.Accordingly,it is stressed here that the younger granites in the ANS are not exclusively post-collisional and within-plate but most likely they started to develop before closure of the arc system.The possible source(s) of mafic magmas that resulted in the formation of the two intrusions are discussed.Mineralogical and geochemical data of the post-intrusion dykes(mafic and felsic) suggest typical active continental rift/within-plate settings.

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

Geochemistry, mineral paragenesis and geothermal conditions of oreforming fluids from the Ain El Bey Cu–Fe deposit: potential occurrence of native gold and precious metal traces (North African orogenic belt, Northern Tunisia)

The Ain El Bey abandoned mine, in North-West Tunisia, fits into the geodynamic context of the European and African plate boundary. Ore deposit corresponds to veins and breccia of multiphase Cu–Fe-rich mineralization related to various hydrothermal fluid circulations. Petromineralogical studies indicate a rich mineral paragenesis with a minimum of seven mineralization phases and, at least, six pyrite generations. As is also the case for galena and native silver, native gold is observed for the first time as inclusion in quartz which opens up, thus, new perspectives for prospecting and evaluating the potential for noble metals associated with the mineralization. Scanning Electron Microscope--Energy Dispersive Spectroscopy and Transmission electron microscopy analyses show, in addition, a large incorporation of trace elements, including Ag and Au, in mineral structures such as fahlores(tetrahedrite-tennantite) and chalcopyrite ones. The mineral/mineral associations, used as geothermometers, gave estimated temperatures for the mineralizing fluids varying from 254 to 330 ℃ for phase Ⅲ, from 254 to 350 ℃ for phase Ⅳ, and from 200 to 300 ℃ for phases Ⅴ and Ⅵ. The seventh and last identified mineralization phase, marked by a deposit of native gold, reflects a drop in the mineralizing fluid’s temperature(< 200 ℃) compatible with boiling conditions. Such results open up perspectives for the development of precious metal research and the revaluation of the Cu–Fe ore deposit at the Ain El Bey abandoned mine, as well as at the surrounding areas fitting in the geodynamic framework of the Africa-Europe plate boundary.

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.

面向产线AI质检的少样本评测方法研究和验证

随着工业4.0时代的到来,制造业与人工智能的深度融合已成为了业界的重要发展趋势,工业质检是其中的重要突破口,但目前业界缺乏对工业质检产品进行评估的标准方法,各质检产品的性能往往不透明,不利于优化迭代及规模推广。针对上述问题,提出了一种面向工业界产线应用需求的AI工业质检算法评测方法,可在工业领域样本数量少且不均衡的情况下,面向产线落地应用需求,对AI工业质检产品及其竞品进行对标评估。该评测方法通过交叉验证法构建数据集,从而避免数据集规模小且不均衡导致的评测结果波动较大的问题,通过灰盒测试法避免数据集来源单一导致的评测结果不客观问题,并根据产线实际生产需求制定相关评估指标,可真实反映产线应用场景下质检产品检测性能。将上述方法应用于光伏电池片EL检测产品的对标评测中进行验证,结果表明该评测方法具备可行性,且能客观反映各产品的真实性能。最后,基于对评测结果的分析对比,为AI工业质检产品的优化提供了一些建议。

Circulation Pattern Controls of Summer Temperature Anomalies in Southern Africa

This study investigates the relationship between circulation patterns and austral summer temperature anomalies in southern Africa. The results show that the formation of continental lows tends to increase the thickness of the lower atmosphere. Further, the distinct variabilities of high and low pressure under the circulation types, influence air mass advection from the adjacent oceans, as well as atmospheric stability over land. Stronger anticyclonic circulation at the western branch of the Mascarene high-pressure system enhances the low-level cold air advection by southeast winds,decreases the thickness, and lowers the temperature over a majority of the land in southern Africa. Conversely, a weaker Mascarene High, coupled with enhanced cyclonic activity in the southwest Indian Ocean increases low-level warm air advection and increases temperature anomalies over vast regions in southern Africa. The ridging of a closed South Atlantic anticyclone at the southern coast of southern Africa results in colder temperatures near the tip of southern Africa due to enhanced low-level cold air advection by southeast winds. However, when the ridge is weak and westerly winds dominate the southern coast of southern Africa, these areas experience temperature increases. The northward track of the Southern Hemisphere mid-latitude cyclone, which can be linked to the negative Southern Annular Mode, reduces the temperature in the southwestern part of southern Africa. Also, during the analysis period, El Ni?o was associated with temperature increases over the central parts of southern Africa;while the positive Indian Ocean dipole was linked to a temperature increase over the northeastern, northwestern, and southwestern parts of southern Africa.

El Niño事件发展期对中国东部夏季极端降水的影响

利用1961−2020年的再分析资料和中国台站观测降水数据集,研究了东部型El Niño事件发展期夏季对中国夏季极端降水的影响.结果表明,东部型El Niño在发展期夏季对中国极端降水的影响主要表现在中国东部地区,造成华北和江南地区极端降水减少,江淮地区极端降水显著增多.进一步分析其中的物理过程发现,当东部型El Niño事件处于发展期夏季时,赤道东太平洋出现显著的海表面温度(sea surface temperature,SST)暖异常,西太平洋区域表现为冷异常,导致反气旋性环流异常.同时,西北太平洋区域存在SST暖异常,对应气旋性环流异常.异常的SST分布激发了“正-负-正(+−+)”的东亚-太平洋型(East Asia-Pacific,EAP)波列异常,对应着“负-正-负(−+−)”的降水配置.在2个异常环流的交汇处有显著的辐合上升运动,为江淮地区带去了充足的水汽.而华北地区主要受到反气旋性环流和蒙古高压的共同控制,并受到来自高纬度地区的异常西北风影响,存在显著的辐散下沉运动,降水的动力条件不足.并且,在东部型El Niño事件发展期夏季,西太平洋副热带高压位置异常偏东,不利于江南地区降水的发生及水汽的输送,进一步造成江南地区极端降水减少.以上结果显示东部型El Niño事件在其发展期夏季对中国极端降水存在重要的影响,为区域极端气候预测提供了理论依据.

碎石桩加固风积沙地基液化规律及频响特征试验研究

为解决我国铁路线路不可避免地穿越风积沙河谷地区遇到的地基液化问题,通过振动台试验探究了碎石桩加固风积沙地层的液化规律及频响特征。研究结果表明,在EL Centro地震波作用下:(1)碎石桩能有效抵抗风积沙地基沉降,大幅度增强其抗液化能力,尤其是地基中部(3/5桩长),并且能将液化易发部位从中部转移到浅层,有利于对液化场地采取加固措施;(2)碎石桩充当优良的排水路径,能弱化桩间土的剪胀剪缩循环活动性,使孔压保持稳态增长;(3)通过相关性分析发现,当地震烈度过高时,碎石桩的排水效果会达到极限,地基深处的部分孔隙水将从桩间土渗流至地表,导致路径上孔压增长的相互影响性显著增强;(4)碎石桩加固后的风积沙地基在低频段(0~10 Hz)的响应集中且最为强烈,在高频域(25~30 Hz)的响应具有高程放大效应,而液化的地层会弱化地基原有的能量传递效果;(5)通过希尔波特谱可知,随着地震波从下往上传播,碎石桩地基的响应主频段会向高频(≥22 Hz)扩展与迁移,而发生液化的土层具有高频过滤作用。

Impacts of central-Pacific El Niño and physical drivers on eastern Pacific bigeye tuna

Bigeye tuna Thunnus obesus is an important migratory species that forages deeply,and El Niño events highly influence its distribution in the eastern Pacific Ocean.While sea surface temperature is widely recognized as the main factor affecting bigeye tuna(BET)distribution during El Niño events,the roles of different types of El Niño and subsurface oceanic signals,such as ocean heat content and mixed layer depth,remain unclear.We conducted A spatial-temporal analysis to investigate the relationship among BET distribution,El Niño events,and the underlying oceanic signals to address this knowledge gap.We used monthly purse seine fisheries data of BET in the eastern tropical Pacific Ocean(ETPO)from 1994 to 2012 and extracted the central-Pacific El Niño(CPEN)indices based on Niño 3 and Niño 4indexes.Furthermore,we employed Explainable Artificial Intelligence(XAI)models to identify the main patterns and feature importance of the six environmental variables and used information flow analysis to determine the causality between the selected factors and BET distribution.Finally,we analyzed Argo datasets to calculate the vertical,horizontal,and zonal mean temperature differences during CPEN and normal years to clarify the oceanic thermodynamic structure differences between the two types of years.Our findings reveal that BET distribution during the CPEN years is mainly driven by advection feedback of subsurface warmer thermal signals and vertically warmer habitats in the CPEN domain area,especially in high-yield fishing areas.The high frequency of CPEN events will likely lead to the westward shift of fisheries centers.

SHEL:a semantically enhanced hardware-friendly entity linking method

With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.