Improvement of 6–15 Day Precipitation Forecasts Using a Time-Lagged Ensemble Method

A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs,all at the same forecast valid time.This lagged average forecast （LAF） method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean.Our analyses of the Equitable Threat Score,the Hanssen and Kuipers Score,and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d-1 and 5 mm d-1 in many regions of China,and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members.In particular,significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40％-50％ in the summer season; these regions include northeastern and central to southern China,and the southeastem Tibetan Plateau.

阿尔茨海默病中免疫检查位点LAG3的研究

目的:探讨免疫检查位点基因LAG3在阿尔茨海默病(AD)中的作用和意义。方法:对GEO(https://www.ncbi.nlm.nih.gov/geo/)数据库中AD患者脑组织测序数据集GSE48350和血液测序数据集GSE140829进行分析,采用CIBERSORT计算脑组织中的免疫细胞评分,并观察LAG3的表达量变化;使用人源Aβ1-42淀粉样蛋白诱导小鼠海马神经元细胞系HT22作为AD细胞模型,RT-PCR检测LAG3的表达量变化。通过GSEA分析研究与LAG3直接相关的通路,String网站构建PPI网络,发现与LAG3相互作用的基因,最后通过KEGG和GO分析这些基因的生物学功能。结果:AD患者脑组织中免疫细胞与健康人存在较大差异,AD患者脑组织和血液中LAG3水平均高于健康人,AD细胞模型中LAG3的表达量也增高。结论:AD脑组织中免疫细胞构成与健康人存在差异,AD脑组织中未激活的记忆CD4^(+)T细胞和单核细胞的比例较高,激活的NK细胞偏低,且免疫检查位点LAG3的表达量增高,其可能与CD4细胞有关,也与免疫细胞的活化和调节存在联系。

Lagged climatic effects on carbon fluxes over three grassland ecosystems in China

Aims The plasticity of ecosystem responses could buffer and post-pone the effects of climates on ecosystem carbon fluxes,but this lagged effect is often ignored.In this study,we used carbon flux data collected from three typical grassland ecosystems in China,including a temperate semiarid steppe in Inner mongolia(Neimeng site,Nm),an alpine shrub-meadow in Qinghai(Haibei site,Hb)and an alpine meadow steppe in Tibet(Dangxiong site,DX),to examine the time lagged effects of environmental factors on CO_(2) exchange.Methods Eddy covariance data were collected from three typical Chinese grasslands.In linking carbon fluxes with climatic factors,we used their averages or cumulative values within each 12-month period and we called them‘yearly’statistics in this study.To investigate the lagged effects of the climatic factors on the car-bon fluxes,the climatic‘yearly’statistics were kept still and the‘yearly’statistics of the carbon fluxes were shifted backward 1 month at a time.Important Findingssoil moisture and precipitation was the main factor driving the annual variations of carbon fluxes at the alpine Hb and DX,respectively,while the Nm site was under a synthetic impact of each climatic factor.The time lagged effect analysis showed that temperature had several months,even half a year lag effects on Co2 exchange at the three studied sites,while moisture’s effects were mostly exhibited as an immediate manner,except at Nm.In general,the lagged climatic effects were relatively weak for the alpine ecosystem.our results implied that it might be months or even 1 year before the variations of ecosystem carbon fluxes are adjusted to the current climate,so such lag effects could be resistant to more frequent climate extremes and should be a critical component to be considered in evaluating ecosystem stability.an improved knowledge on the lag effects could advance our understanding on the driving mechanisms of climate change effects on ecosystem carbon fluxes.

INVESTIGATION OF LAGGED CORRELATION BETWEEN THE TEMPERATURE OF CHINA AND THE GLOBAL OUTGOING LONGWAVE RADIATION IN 1974-1985

1-12 month lagged correlations between winter temperatures at 22 stations in China and the global dis- tribution of the Outgoing Longwave Radiation(OLR)are investigated.The basic results are:(1)The monthly averaged temperatures of Dec.,Jan.and Feb.of China are correlated to the global distribution of OLR of Oct.,Nov.and Dec.,respectively.It is consistent with the response period(about 50 days)of 500 hPa geopotential height field in extratropical latitudes to the thermal forcing in tropical latitudes,and also consis- tent with the Walker cell of a 40-60 day oscillation.(2)There is a significant positive correlation between the winter temperature of the most part of China and the OLR in the Gulf of Mexico.It shows that when the thermal forcing of the Gulf of Mexico is stronger,the excited barotropic instability of westerlies in northern Atlantic could influence the East Asian circulation and cause the temperature of China to be below normal. (3)The temperature around the Tibetan(Xizang)Plateau is negatively correlated to the OLR in western equa- torial Pacific,showing that when the Walker cell is stronger,the local Hadley cell in Southeast Asia is stronger and it causes the temperature around the Tibetan Plateau to be higher than normal.

三阴性乳腺癌免疫及靶向治疗研究进展

三阴性乳腺癌(TNBC)占所有乳腺癌的15%~20%。与其他亚型相比,TNBC患者的临床病程进展迅速、发病年龄早、远处复发更快、内脏转移更常见,且其相关治疗往往仅限于化疗,预后较差。因此,为患者制定最佳的治疗策略对于减轻TNBC造成的疾病负担至关重要。目前发现了多种潜在的可用药物靶点,“精准治疗”“分类而治”正在改变TNBC的临床实践,新的治疗领域的发展为突破TNBC治疗难点带来了希望。本文对近年来TNBC的全身治疗选择,包括免疫治疗和靶向治疗进行了综述。

GNSS接收机晶振频率稳定度仿真分析

针对全球卫星导航系统(GNSS)提供的高精度定位、导航及授时(PNT)服务以精密测量的传输时间为基础,然而GNSS接收机中普遍采用的频率源为稳定度较差的晶振的问题,提出一种对GNSS接收机晶振频率稳定度进行分析和建模的方法:根据GNSS接收机晶振频率稳定度受随机频率误差及老化率的影响的原理,给出晶振随机频率误差及老化率的数学模型;并根据不同随机频率误差成分仿真相应的各项晶振随机频率误差序列;同时基于LAG1自相关法辨识不同时期主导的随机频率误差类型,定性分析其对晶振频率稳定度的影响。实验结果表明,提出的方法可为GNSS接收机晶振设计及频率稳定度能评估提供参考。

Shear behaviour of a rock bridge sandwiched between incipient joints under the influence of hydraulic pressures

The rock bridges sandwiched in incipiently jointed rock mass were considered as barriers that block the fluid seepage,and provide certain shear strength reservation.For better revealing the influence of hydraulic pressure on the failure behaviour of rock bridges,direct shear tests were carried out through a newly proposed method on rock samples that contain two parallel incipient joints.By developing the gypsum-silicone pad coupling samples,a conventional triaxial test system was qualified to implement direct shear tests with satisfied sealing capability.The results showed that the rock bridges could be failed through the tensile failure,shear failure and mixed failure mechanism.The hydraulic pressure would facilitate the tensile failure mechanism and induce rougher fracture surfaces;while the normal stress would facilitate the shear failure mechanism and induce less rough fracture.The hydraulic pressure reduced the global shear strength of the rock block through reducing the efficient normal stress applied on the rock bridge area,which was highly dependent on the joint persistence,k.Moreover,because of the iterating occurrence of the hydraulic pressure lag with the fracture propagation,the rock bridge failure stage in the shear stress-shear displacement curves displayed a fluctuation trend.

Impact of the Urban Heat Island Effect on Ozone Pollution in Chengdu City,China

With the advancement of urbanization,the urban heat island effect and ozone pollution have become hot issues in urban research.The urban heat island effect can impact ozone conversion,but its mechanism of action is unclear.In this study,the effects of the urban heat island effect on ozone concentration in Chengdu City,China,were investigated by comparing the ozone concentration under different heat island levels with ozone data from March 2020 to February 2021 and the temperature and wind field data of ERA5-Land during the same period.The results showed that:1)regarding the distribution characteristics,the ozone concentration in Chengdu presented a‘high in summer and low in winter’distribution.The ozone concentration in summer(189.54µg/m^(3))was nearly twice that in winter(91.99µg/m^(3)),and the ozone diurnal variation presented a‘single peak and single valley’distribution,with a peak at 16:00.2)For the characteristics of the heat island effect,the heat island intensity in Chengdu was obviously higher in spring than in other seasons,and the diurnal variation showed a‘single peak and single valley’distribution,with the peak and trough values appearing at 9:00 and 17:00,respectively.Spatially,the eastern part of Chengdu was a heat island,while the western and northwestern parts were mostly cold island.3)The correlation analysis between heat island intensity and ozone concentration showed a significant positive correlation but with a 7–8 h time lag.Ambient air temperature was not the main factor affecting ozone concentration.The heat island effect impacts the ozone concentration in two ways:changing the local heat budget to promote ozone generation and forming local urban wind,which promotes ozone diffusion or accumulation and forms different areas of low and high ozone values.

Influence of asymmetric tidal mixing on sediment dynamics in a partially mixed estuary

To investigate the influence of asymmetric tidal mixing(ATM) on sediment dynamics in tidal estuaries, we developed a vertically one-dimensional idealized analytical model, in which the M_2 tidal flow, residual flow and suspended sediment concentration(SSC) are described. Model solutions are obtained in terms of tidallyaveraged, and tidally-varying components(M_2 and M_4) of both hydrodynamics and sediment dynamics. The effect of ATM was considered with a time-varying eddy viscosity and time-varying eddy diffusivity of SSC. For the first time, an analytical solution for SSC variation driven by varying diffusivity could be derived. The model was applied to York River Estuary, where higher(or lower) eddy diffusivity was observed during flood(or ebb) in a previous study. The model results agreed well with the observation in both hydrodynamics and sediment dynamics. The vertical sediment distribution under the influence of ATM was analyzed in terms of the phase lag of the M_2 component of SSC relative to tidal flow. The phase lag increases significantly in estuaries with typical ATM(higher diffusivity during flood and lower diffusivity during ebb) for the case of seaward-directed net bottom shear stress(e.g., strong river discharge). In contrary, the phase lag is reduced by ATM, if the tidally-averaged bottom shear stress is landward(e.g., strong horizontal density gradient). The dynamics of sediment transport was analyzed as a function of ATM phase lag to identify the time of highest sediment diffusivity, as well as a function of the residual flow, to evaluate the relative importance of seaward and landward residual flows. In estuaries with relative strong fresh water discharge or weak tidal forcing(in case of flood season or neap tide), the near bottom SSC could be higher during ebb than during flood, since the bottom shear stress is higher during ebb due to seaward residual flow. However, landward net sediment transport can be expected in these estuaries in case of a typical ATM, because higher diffusivity causes higher SSC and landward transport during the flood period, while both SSC and seaward transport could be lower during ebb. On the contrary, seaward sediment transport can be expected in estuaries with landward tidally mean bottom shear stress in case of a reverse ATM,where sediment diffusivity is higher during the ebb.

Blockchain technology‑based FinTech banking sector involvement using adaptive neuro‑fuzzy‑based K‑nearest neighbors algorithm

The study aims to investigate the financial technology(FinTech)factors influencing Chinese banking performance.Financial expectations and global realities may be changed by FinTech’s multidimensional scope,which is lacking in the traditional financial sector.The use of technology to automate financial services is becoming more important for economic organizations and industries because the digital age has seen a period of transition in terms of consumers and personalization.The future of FinTech will be shaped by technologies like the Internet of Things,blockchain,and artificial intelligence.The involvement of these platforms in financial services is a major concern for global business growth.FinTech is becoming more popular with customers because of such benefits.FinTech has driven a fundamental change within the financial services industry,placing the client at the center of everything.Protection has become a primary focus since data are a component of FinTech transactions.The task of consolidating research reports for consensus is very manual,as there is no standardized format.Although existing research has proposed certain methods,they have certain drawbacks in FinTech payment systems(including cryptocurrencies),credit markets(including peer-to-peer lending),and insurance systems.This paper implements blockchainbased financial technology for the banking sector to overcome these transition issues.In this study,we have proposed an adaptive neuro-fuzzy-based K-nearest neighbors’algorithm.The chaotic improved foraging optimization algorithm is used to optimize the proposed method.The rolling window autoregressive lag modeling approach analyzes FinTech growth.The proposed algorithm is compared with existing approaches to demonstrate its efficiency.The findings showed that it achieved 91%accuracy,90%privacy,96%robustness,and 25%cyber-risk performance.Compared with traditional approaches,the recommended strategy will be more convenient,safe,and effective in the transition period.

FOLMS-AMDCNet:an automatic recognition scheme for multiple-antenna OFDM systems

The existing recognition algorithms of space-time block code(STBC)for multi-antenna(MA)orthogonal frequencydivision multiplexing(OFDM)systems use feature extraction and hypothesis testing to identify the signal types in a complex communication environment.However,owing to the restrictions on the prior information and channel conditions,these existing algorithms cannot perform well under strong interference and noncooperative communication conditions.To overcome these defects,this study introduces deep learning into the STBCOFDM signal recognition field and proposes a recognition method based on the fourth-order lag moment spectrum(FOLMS)and attention-guided multi-scale dilated convolution network(AMDCNet).The fourth-order lag moment vectors of the received signals are calculated,and vectors are stitched to form two-dimensional FOLMS,which is used as the input of the deep learning-based model.Then,the multi-scale dilated convolution is used to extract the details of images at different scales,and a convolutional block attention module(CBAM)is introduced to construct the attention-guided multi-scale dilated convolution module(AMDCM)to make the network be more focused on the target area and obtian the multi-scale guided features.Finally,the concatenate fusion,residual block and fully-connected layers are applied to acquire the STBC-OFDM signal types.Simulation experiments show that the average recognition probability of the proposed method at−12 dB is higher than 98%.Compared with the existing algorithms,the recognition performance of the proposed method is significantly improved and has good adaptability to environments with strong disturbances.In addition,the proposed deep learning-based model can directly identify the pre-processed FOLMS samples without a priori information on channel and noise,which is more suitable for non-cooperative communication systems than the existing algorithms.

Economic complexity and environmental sustainability in eastern European economies:Evidence from novel Fourier approach

Globally,economies have become complex and new technologies have transformed and facilitated the modernization of economies.In the previous literature,economic complexity approach has become one of the popular tools in the development and innovation studies of economic geography.Researchers have found that green technology and eco-innovation approaches should be used to decisively reduce the effects of carbon emissions on the environment.However,debates about the impact of economic complexity on environment remain unsettled since some emerging production technologies have far-reaching pollution effects.This study explored the impacts of economic complexity on environmental sustainability in Turkey using the novel Fourier-based approaches,namely:Fourier Augmented Dickey-Fuller(FADF)and Fourier Autoregressive-Distributed Lag(FARDL)models.The Fourier-based approaches indicated that all variables(economic complexity index(ECI),GDP,energy consumption,and CO_(2)emission(CO_(2)E))are cointegrated in the long run.Additionally,the FARDL model implied that(i)in the long run,the effect of ECI(as a proxy for economic complexity),GDP(as a proxy for economic growth),and energy consumption on CO_(2)E(as a proxy for environmental quality)are important;(ii)economic complexity decreases environmental degradation in Turkey;and(iii)economic growth and energy consumption negatively affect environmental quality.The results also showed that economic complexity could be used as a policy tool to tackle environmental degradation.The findings also revealed that the fossil fuelbased economy will continue to expand and undermine Turkey’s efforts to meet its net zero emission target by 2053.Therefore,policy-makers should take actions and establish diversified economic,environmental,and energy strategies.For policy insights,the Turkish governments can use the combination of tax exemptions and technical support systems to support knowledge creation and the diffusion of environmentally friendly technologies The governments can also impose strict environmental regulations on the knowledge development phases.

Study of Construction Techniques and Hygro-Thermal Behavior of a Vernacular Earth Building in a Humid Tropical Climate

This study analyzes the know-how of local communities, to draw on techniques that make contemporary buildings more energy efficient. The impluvium hut in the locality of Enampore, Casamance, Southern Senegal, served as the object of study. The hut, including several rooms, is entirely built with earthen walls, earthen floor, earthen ceiling, covered by a double straw roof and its central courtyard. A room noted (L) and a semi-opened living space were chosen as spaces for hygro-thermal experimentation. The hottest average temperature obtained respectively in the room (L) and in the living space is 25.5˚C and 27˚C when outside is about 34˚C. The thermal amplitude inside room (L) is 0.88˚C, in semi-opened living space, is 2.6˚C and outside is 9.5˚C. With these results we can say that room (L) undergoes very low temperature variations and that there is no need to air-condition in the enclosure. The thermal amplitude makes it possible to see the influence of the earthen walls on the interior temperature and its regularity compared to the fluctuation of the external temperature. The thermal inertia of the building walls was characterized using also the time lag and the decrement factor. They was respectively 7.0 H and 0.093 for the room (L). With this result we can say that this material has a high thermal inertia. For humidity, it is high around 78.5% in the room (L), 66.0% at the semi-open living room, when it is 59.0% outside. Through this study, it is possible that the revalorization of vernacular architecture can be an alternative to reduce the energy consumption of buildings.

Predicting Wavelet-Transformed Stock Prices Using a Vanishing Gradient Resilient Optimized Gated Recurrent Unit with a Time Lag

The development of accurate prediction models continues to be highly beneficial in myriad disciplines. Deep learning models have performed well in stock price prediction and give high accuracy. However, these models are largely affected by the vanishing gradient problem escalated by some activation functions. This study proposes the use of the Vanishing Gradient Resilient Optimized Gated Recurrent Unit (OGRU) model with a scaled mean Approximation Coefficient (AC) time lag which should counter slow convergence, vanishing gradient and large error metrics. This study employed the Rectified Linear Unit (ReLU), Hyperbolic Tangent (Tanh), Sigmoid and Exponential Linear Unit (ELU) activation functions. Real-life datasets including the daily Apple and 5-minute Netflix closing stock prices were used, and they were decomposed using the Stationary Wavelet Transform (SWT). The decomposed series formed a decomposed data model which was compared to an undecomposed data model with similar hyperparameters and different default lags. The Apple daily dataset performed well with a Default_1 lag, using an undecomposed data model and the ReLU, attaining 0.01312, 0.00854 and 3.67 minutes for RMSE, MAE and runtime. The Netflix data performed best with the MeanAC_42 lag, using decomposed data model and the ELU achieving 0.00620, 0.00487 and 3.01 minutes for the same metrics.

The winners of International Woolmark Prize and Karl Lagerfeld Award were announced

Lagos Space Programme from Nigeria and Denmark’s A.ROEGE HOVE have been announced the winners of the 2023 International Woolmark Prize and Karl Lagerfeld Award for In­novation,respectively,at a special event held in Paris.BYBORRE is also celebrating after being recognised as the Supply Chain Award recipient.

几种水溶性破乳剂在原油破乳中的应用

对几种水溶性破乳剂在原油破乳中的应用进行了研究、结果表明，在水溶性破乳剂的破乳过程中，亲水环境有利于原油破乳．

基于ICP的硅高深宽比沟槽刻蚀技术

介绍了电感耦合等离子体(ICP)刻蚀技术的基本概念。结合英国STS公司的STS multiplex ICP system刻蚀机,介绍了刻蚀机原理及刻蚀过程。对硅深槽刻蚀技术进行了分析,对其中Footing效应、Lag效应和侧壁光滑问题提出了优化方案,最后在实验的基础上得出了能够刻蚀出高质量硅深沟槽的刻蚀参数。

利用海洋磁力梯度数据重建总场的方法研究

通过分析影响磁力梯度仪的4大误差因素,认为地质信号主要分布在低频率段里,时变信号主要出现在中间频率段里,系统噪音主要出现在高频率段里,据此推断算法相应的定性行为。用正交相关函数法,计算了主从传感器之间的LAG值的范围。利用TVSA剖面积分法用于重建总场的研究,并把研究方法直接应用到了海上磁力梯度测线的重建总场中,恢复的结果显示方法是可行的。

原油破乳剂LAG847的应用研究

原油破乳剂 LAG847由含硅破乳剂与普通破乳剂复配制得。研究了 LAG847破乳剂在中原油田采油一厂文一联改换密闭流程中的应用情况 ,结果表明 ,LAG847的性能达到了密闭流程所要求的三相分离器出口原油 w( H2 O) <30 % 。

视觉掩蔽可基于知觉到的客体位置

利用flash-lag效应分离视觉掩蔽中客体的物理位置和知觉位置,以探讨掩蔽效应是否基于知觉到的客体位置。实验中掩蔽刺激做圆周运动,到某一位置时,目标刺激短时呈现,要求被试判断目标刺激(缺角菱形)的缺角方向。通过操作目标呈现时二者之间的相对位置,发现当二者物理位置不重合而知觉位置重合时掩蔽效应最大。该结果表明,视觉掩蔽可基于知觉到的客体位置。