With the integration of global economy and rapid development of information technology,China's economic and trade exchange will be further strengthened and social economic phenomenon will become more and more comp...With the integration of global economy and rapid development of information technology,China's economic and trade exchange will be further strengthened and social economic phenomenon will become more and more complex. Therefore,understanding fishery statistical systems and making comparative analysis become particularly important for formulating fishery development and economic management policies.Through comparative study on statistical systems,organization,statistical laws and regulations,statistical indicators,and statistical management and methods of different countries,this paper is intended to provide reference for improving China's fishery statistical system and operating mechanism.展开更多
Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment thr...Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.展开更多
This article focuses on the development of the international service trade statistics system.The 1994 General Agreement on Trade in Services(GATS)provided a institutional basis for service trade statistics.The 2002“I...This article focuses on the development of the international service trade statistics system.The 1994 General Agreement on Trade in Services(GATS)provided a institutional basis for service trade statistics.The 2002“International Service Trade Statistics Manual”(MSITS 2002)established the international balance of payments statistics paradigm.The revised MSITS 2010 in 2010 introduced the expanded balance of payments service classification(EBOPS 2010),incorporating foreign affiliate service trade statistics(FATS),and constructing a comprehensive statistics system.The update of MSITS 2010 originated from changes in the global economic environment,technological progress leading to diversified forms of service trade,and the demands of international service trade negotiations.This standard has constructed a multi-level classification system.Since the release of MSITS 2010,many countries have implemented the new statistical framework,but some developing countries face challenges.International organizations and developed countries have provided corresponding support for service trade statistics standards.展开更多
This paper proposes a set of nonparametric statistical tools for analyzing the system resilience of civil structures and infrastructure and its migration upon changes in critical system parameters.The work is founded ...This paper proposes a set of nonparametric statistical tools for analyzing the system resilience of civil structures and infrastructure and its migration upon changes in critical system parameters.The work is founded on the classic theoretic framework that system resilience is defined in multiple dimensions for a constructed system.Consequentially,system resilience can lose its parametric form as a random variable,falling into the realm of nonparametric statistics.With this nonparametric shift,traditional distribution-based statistics are ineffective in characterizing the migration of system resilience due to the variation of system parameters.Three statistical tools are proposed under the nonparametric statistical resilience analysis(npSRA)framework,including nonparametric copula-based sensitivity analysis,two-sample resilience test analysis,and a novel tool for resilience attenuation analysis.To demonstrate the use of this framework,we focus on electric distribution systems,commonly found in many urban,suburban,and rural areas and vulnerable to tropical storms.A novel procedure for considering resourcefulness parameters in the socioeconomic space is proposed.Numerical results reveal the complex sta-tistical relations between the distributions of system resilience,physical aging,and socioeconomic parameters for the power distribution system.The proposed resilience distance computing and resilience attenuation anal-ysis further suggests two proper nonparametric distance metrics,the Earth Moving Distance(EMD)metric and the Cramévon Mises(CVM)metric,for characterizing the migration of system resilience for electric distribution systems.展开更多
This paper is a statistical survey of Southern Hemisphere cold and hot polar cap patches,in relation to the interplanetary magnetic field(IMF)and ionospheric convection geometry.A total of 11,946 patch events were ide...This paper is a statistical survey of Southern Hemisphere cold and hot polar cap patches,in relation to the interplanetary magnetic field(IMF)and ionospheric convection geometry.A total of 11,946 patch events were identified by Defense Meteorological Satellite Program(DMSP)F16 during the years 2011 to 2022.A temperature ratio of ion/electron temperature(T_(i)/T_(e))<0.68 is recommended to define a hot patch in the Southern Hemisphere,otherwise it is defined as a cold patch.The cold and hot patches have different dependencies on IMF clock angle,while their dependencies on IMF cone angle are similar.Both cold and hot patches appear most often on the duskside,and the distribution of cold patches gradually decreases from the dayside to the nightside,while hot patches have a higher occurrence rate near 14 and 21 magnetic local time(MLT).Moreover,we compared the key plasma characteristics of polar cap cold and hot patches in the Southern and Northern Hemispheres.The intensity of the duskside upward field-aligned current of patches in the Southern Hemisphere(SH)is stronger than that in the Northern Hemisphere(SH),which may be due to the discrepancy in conductivities between the two hemispheres,caused by the tilted dipole.In both hemispheres,the downward soft-electron energy flux of the dawnside patches is significantly greater than that of the duskside patches.展开更多
Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.展开更多
Multi-angle statistical analysis of tropical cyclones(TCs)and their distant thermodynamic disturbances over Northwest Pacific from July to September during 2001-2020 was conducted.The results show that TCs could trigg...Multi-angle statistical analysis of tropical cyclones(TCs)and their distant thermodynamic disturbances over Northwest Pacific from July to September during 2001-2020 was conducted.The results show that TCs could trigger distant thermodynamic disturbances,which mainly caused an increase in air pressure and a rise in temperature in northern China.The distant thermodynamic disturbances triggered by TCs differed in spatial distribution and intensity in different months.In the same month,the spatial distribution of such disturbances triggered by high-intensity TCs was consistent with the overall pattern,and there was a significant increase in intensity and area.From the probability of TC activities and the significance test of variance of analysis under different levels of P-J index,it is found that TC activities could stimulate the increase of P-J teleconnection index.There was a significant positive correlation between them,which was accompanied by a step effect.展开更多
To realize dynamic statistical publishing and protection of location-based data privacy,this paper proposes a differential privacy publishing algorithm based on adaptive sampling and grid clustering and adjustment.The...To realize dynamic statistical publishing and protection of location-based data privacy,this paper proposes a differential privacy publishing algorithm based on adaptive sampling and grid clustering and adjustment.The PID control strategy is combined with the difference in data variation to realize the dynamic adjustment of the data publishing intervals.The spatial-temporal correlations of the adjacent snapshots are utilized to design the grid clustering and adjustment algorithm,which facilitates saving the execution time of the publishing process.The budget distribution and budget absorption strategies are improved to form the sliding window-based differential privacy statistical publishing algorithm,which realizes continuous statistical publishing and privacy protection and improves the accuracy of published data.Experiments and analysis on large datasets of actual locations show that the privacy protection algorithm proposed in this paper is superior to other existing algorithms in terms of the accuracy of adaptive sampling time,the availability of published data,and the execution efficiency of data publishing methods.展开更多
This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenari...This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenarios involving Normal,Platykurtic and Skewed distributions over different sample sizes and standard deviation values.In the study,standard deviation ratios were set as 2,3,4,1/2,1/3 and 1/4 and power comparisons were made between small and large sample sizes.For equal sample sizes,small sample sizes of 5,8,10,12,16 and 20 and large sample sizes of 25,50,75 and 100 were used.For different sample sizes,the combinations of(4,16),(8,16),(10,20),(16,4),(16,8)and(20,10)small sample sizes and(10,30),(30,10),(50,75),(50,100),(75,50),(75,100),(100,50)and(100,75)large sample sizes were examined in detail.According to the findings,the power analysis under variance heterogeneity conditions shows that the Siegel-Tukey test has a higher statistical power than the other nonparametric Savage test at small and large sample sizes.In particular,the Siegel-Tukey test was reported to offer higher precision and power under variance heterogeneity,regardless of having equal or different sample sizes.展开更多
Artificial intelligence(AI)is rapidly transforming healthcare and medical education.Strong statistical thinking skills are vital for evaluating and applying AI tools.However,traditional medical statistics education ha...Artificial intelligence(AI)is rapidly transforming healthcare and medical education.Strong statistical thinking skills are vital for evaluating and applying AI tools.However,traditional medical statistics education has not adapted to this demand.This paper first analyzes the connotation and importance of statistical thinking,points out the significant challenges currently faced by medical statistics education,and then proposes strategies such as innovative teaching methods combined with evidence-based medicine,utilizing AI platforms for supplemental teaching,multidisciplinary integration,and strengthening the understanding of the statistical foundations of AI to enhance the statistical thinking abilities of medical professionals.This study emphasizes the importance of cultivating medical statistical thinking in the era of AI to improve the quality of medical education and ensure the safety and effectiveness of future medical services.展开更多
Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex ...Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex web pages.Through ana-lyzing various statistical characteristics of HTML el-ements in web documents,this paper proposes,based on statistical features,an unsupervised web data ex-traction method—traversing the HTML DOM parse tree at first,calculating and generating the statistical matrix of the elements,and then locating data records by clustering method and heuristic rules that reveal in-herent links between the visual characteristics of the data recording areas and the statistical characteristics of the HTML nodes—which is both suitable for data records extraction of single-page and multi-pages,and it has strong generality and needs no training.The ex-periments show that the accuracy and efficiency of this method are equally better than the current data extrac-tion method.展开更多
In this study,the gradients of Total Electron Content(TEC)for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations,time periods within a day,and satellite directions...In this study,the gradients of Total Electron Content(TEC)for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations,time periods within a day,and satellite directions.Annual medians of these gradients for quiet days are computed as templates.The metric distances(L2N)and Symmetric Kullback-Leibler Distances(SKLD)are obtained between the templates and the daily gradient series.The grouped histograms are fitted to the prospective Probability Density Functions(PDF).The method is applied to the Slant Total Electron Content(STEC)estimates from the Turkish National Permanent GPS Network(TNPGN-Active)for 2015.The highest gradients are observed in the east-west axis with a maximum of 25 mm/km during a geomagnetic storm.The maximum differences from the gradient templates occur for neighboring stations within100-130 km distance away from each other,during night hours,and for regions bordering the Black Sea and the Mediterranean in the northeast and southeast of Turkey.The empirical PDFs of the stationpair gradients are predominantly Weibull-distributed.The mean values of Weibull PDFs in all station groups are between 1.2 and 1.8 mm/km,with an increase during noon and afternoon hours.The standard deviations of the gradient PDFs generally increase during night hours.The algorithm will form a basis for quantifying the stochastic variations of the spatial rate of change of TEC trends in midlatitude regions,thus supplementing reliable and accurate regional monitoring of ionospheric variability.展开更多
Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a ...Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.展开更多
Extratropical transition(ET)is one of the last phases of tropical cyclones(TCs)and corresponds to the structural change from a tropical system to an extratropical system characterized by pronounced asymmetric distribu...Extratropical transition(ET)is one of the last phases of tropical cyclones(TCs)and corresponds to the structural change from a tropical system to an extratropical system characterized by pronounced asymmetric distributions of heavy rainfall and strong wind.This study analyzes the statistical characteristics of ET events involving TCs over the western North Pacific(WNP)during 1981–2022.The analysis employs the Cyclone Phase Space(CPS)method to evaluate the accuracy of the fifth-generation reanalysis from the European Centre for Medium-Range Weather Forecasts(ERA5)in identifying ET based on different TC center definitions.Results show that defining the TC center by the minimum sea level pressure yields the most accurate ET identification.Subsequently,the study investigates several characteristics of ET events in the WNP.It is found that TCs undergoing ET(ETTCs)primarily form in the region of 125°–155°E,10°–25°N,with ET typically initiating between 30°–40°N and completing between 35°–50°N.These ETTCs predominantly occur from April to December,with peak activity observed from August to October.Additionally,the average duration of the ET process is 18.5 h,with longer durations observed from August to October,displaying a roughly 6-year cycle.Spatially,ET events with longer durations tend to occur at lower latitudes.Correspondingly,TCs initiating their ET phase at lower latitudes are typically stronger and larger,and they also experience longer ET durations.展开更多
Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome th...Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.展开更多
Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit signifi...Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.展开更多
We perform a time-resolved statistical study of GRB 221009A’s X-ray emission using Swift XRT Photon Counting and Windowed Timing data.After standard reduction(barycentric correction,pile-up,background subtraction via...We perform a time-resolved statistical study of GRB 221009A’s X-ray emission using Swift XRT Photon Counting and Windowed Timing data.After standard reduction(barycentric correction,pile-up,background subtraction via HEASOFT),we extracted light curves for each observational ID and for their aggregation.Countrate histograms were fitted using various statistical distributions;fit quality was assessed by chi-squared and the Bayesian Information Criterion.The first observational segment is best described by a Gaussian distribution(χ^(2)=68.4;BIC=7651.2),and the second by a Poisson distribution(χ^(2)=33.5;BIC=4413.3).When all segments are combined,the lognormal model provides the superior fit(χ^(2)=541.9;BIC=34365.5),indicating that the full data set’s count rates exhibit the skewness expected from a multiplicative process.These findings demonstrate that while individual time intervals conform to discrete or symmetric statistics,the collective emission profile across multiple observations is better captured by a lognormal distribution,consistent with complex,compounded variability in GRB afterglows.展开更多
The ability to accurately simulate the time evolu-tion of quantum systems stands as a cornerstone of modern molecular science.It provides the essential mechanistic bridge between a system’s microscopic structure and ...The ability to accurately simulate the time evolu-tion of quantum systems stands as a cornerstone of modern molecular science.It provides the essential mechanistic bridge between a system’s microscopic structure and its macroscopic function,a challenge first envisioned by Feynman.The central difficulty,and the unifying theme of this Special Topic,is the problem of“complexity”:a multifaceted challenge arising from the interplay of strongly coupled electronic and vibrational degrees of freedom,quantum statistics,and the non-trivial,often non-Markovian,memory effects exerted by a surrounding environment.展开更多
To improve the efficiency of the management of large farms, a digitalized system of economic statistics is designed based on the Internet platform of the digitalized agricultural integrated system of Friendship Farm, ...To improve the efficiency of the management of large farms, a digitalized system of economic statistics is designed based on the Internet platform of the digitalized agricultural integrated system of Friendship Farm, the largest farm in the world. The system can also realize data storage by using the access databank technology. A dynamic website system, based on ASP technology, is used to implement the on-line inquiry of the statistical index of the agricultural economy and the diagrams of the index every year. Furthermore, it can provide the value of comprehensive indicators of farms' economic profits for every year and a trend chart of the comprehensive appraisal of economic development, by using principal component analysis. An early-warning indicator boundary is decided based on the majority principle. The system can realize the farm's terminal data input with effective data-collecting channels and a normative gathering scope and system. This system breaks through the stand-alone database system in agricultural digitalized research to realize the database system in the Internet environment by integrating the existing technologies in China. The system lays a foundation for the further integrated research on the network platform of the digitalized agricultural integrated system in Friendship Farm.展开更多
Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are establishe...Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.展开更多
文摘With the integration of global economy and rapid development of information technology,China's economic and trade exchange will be further strengthened and social economic phenomenon will become more and more complex. Therefore,understanding fishery statistical systems and making comparative analysis become particularly important for formulating fishery development and economic management policies.Through comparative study on statistical systems,organization,statistical laws and regulations,statistical indicators,and statistical management and methods of different countries,this paper is intended to provide reference for improving China's fishery statistical system and operating mechanism.
基金partially supported by the National Key Research and Development Project under Grant 2020YFB1806805Science and Technology on Communication Networks Laboratorysupported by China Scholarship Council.
文摘Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.
基金The interim results of the postdoctoral research project“Research on the Evolution Process of Shenzhen’s High-tech Industry Policies(1980-2022)”(Project Number:6023271023S)at the end of the postdoctoral period of Shenzhen Polytechnic University.Institute of Economic and Social Development(Phase III)Project:6025310002Q.
文摘This article focuses on the development of the international service trade statistics system.The 1994 General Agreement on Trade in Services(GATS)provided a institutional basis for service trade statistics.The 2002“International Service Trade Statistics Manual”(MSITS 2002)established the international balance of payments statistics paradigm.The revised MSITS 2010 in 2010 introduced the expanded balance of payments service classification(EBOPS 2010),incorporating foreign affiliate service trade statistics(FATS),and constructing a comprehensive statistics system.The update of MSITS 2010 originated from changes in the global economic environment,technological progress leading to diversified forms of service trade,and the demands of international service trade negotiations.This standard has constructed a multi-level classification system.Since the release of MSITS 2010,many countries have implemented the new statistical framework,but some developing countries face challenges.International organizations and developed countries have provided corresponding support for service trade statistics standards.
基金supported by the National Science Foundation(NSF)under Award Number IIA-1355406.
文摘This paper proposes a set of nonparametric statistical tools for analyzing the system resilience of civil structures and infrastructure and its migration upon changes in critical system parameters.The work is founded on the classic theoretic framework that system resilience is defined in multiple dimensions for a constructed system.Consequentially,system resilience can lose its parametric form as a random variable,falling into the realm of nonparametric statistics.With this nonparametric shift,traditional distribution-based statistics are ineffective in characterizing the migration of system resilience due to the variation of system parameters.Three statistical tools are proposed under the nonparametric statistical resilience analysis(npSRA)framework,including nonparametric copula-based sensitivity analysis,two-sample resilience test analysis,and a novel tool for resilience attenuation analysis.To demonstrate the use of this framework,we focus on electric distribution systems,commonly found in many urban,suburban,and rural areas and vulnerable to tropical storms.A novel procedure for considering resourcefulness parameters in the socioeconomic space is proposed.Numerical results reveal the complex sta-tistical relations between the distributions of system resilience,physical aging,and socioeconomic parameters for the power distribution system.The proposed resilience distance computing and resilience attenuation anal-ysis further suggests two proper nonparametric distance metrics,the Earth Moving Distance(EMD)metric and the Cramévon Mises(CVM)metric,for characterizing the migration of system resilience for electric distribution systems.
基金supported by the National Natural Science Foundation of China(Grants 42325404,42120104003,42204164,42474219 and U22A2006)the Chinese Meridian Project,the International Partnership Program of Chinese Academy of Sciences(Grant 183311KYSB20200003)+7 种基金Shandong Provincial Natural Science Foundation(Grants ZR2022QD077,ZR2022MD034)the Stable-Support Scientific Project of China Research Institute of Radiowave Propagation(Grant A132312191)the foundation of the National Key Laboratory of Electromagnetic Environment(Grant 6142403180204)the Chongqing Natural Science Foundation(Grants cstc2021ycjh-bgzxm0072,CSTB2023NSCQ-LZX0082)National Program on Key Basic Research Project(Grant 2022173-SD-1)The work in Norway is supported by the Research Council of Norway Grant 326039Work at UCLA has been supported by NSF grant AGS-2055192This research was supported by the International Space Science Institute(ISSI)in Bern and Beijing,through ISSI International Team project#511(Multi-Scale Magnetosphere-Ionosphere-Thermosphere Interaction).
文摘This paper is a statistical survey of Southern Hemisphere cold and hot polar cap patches,in relation to the interplanetary magnetic field(IMF)and ionospheric convection geometry.A total of 11,946 patch events were identified by Defense Meteorological Satellite Program(DMSP)F16 during the years 2011 to 2022.A temperature ratio of ion/electron temperature(T_(i)/T_(e))<0.68 is recommended to define a hot patch in the Southern Hemisphere,otherwise it is defined as a cold patch.The cold and hot patches have different dependencies on IMF clock angle,while their dependencies on IMF cone angle are similar.Both cold and hot patches appear most often on the duskside,and the distribution of cold patches gradually decreases from the dayside to the nightside,while hot patches have a higher occurrence rate near 14 and 21 magnetic local time(MLT).Moreover,we compared the key plasma characteristics of polar cap cold and hot patches in the Southern and Northern Hemispheres.The intensity of the duskside upward field-aligned current of patches in the Southern Hemisphere(SH)is stronger than that in the Northern Hemisphere(SH),which may be due to the discrepancy in conductivities between the two hemispheres,caused by the tilted dipole.In both hemispheres,the downward soft-electron energy flux of the dawnside patches is significantly greater than that of the duskside patches.
基金funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
文摘Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.
基金the National Natural Science Foundation of China(42305011).
文摘Multi-angle statistical analysis of tropical cyclones(TCs)and their distant thermodynamic disturbances over Northwest Pacific from July to September during 2001-2020 was conducted.The results show that TCs could trigger distant thermodynamic disturbances,which mainly caused an increase in air pressure and a rise in temperature in northern China.The distant thermodynamic disturbances triggered by TCs differed in spatial distribution and intensity in different months.In the same month,the spatial distribution of such disturbances triggered by high-intensity TCs was consistent with the overall pattern,and there was a significant increase in intensity and area.From the probability of TC activities and the significance test of variance of analysis under different levels of P-J index,it is found that TC activities could stimulate the increase of P-J teleconnection index.There was a significant positive correlation between them,which was accompanied by a step effect.
基金supported by National Nature Science Foundation of China(No.62361036)Nature Science Foundation of Gansu Province(No.22JR5RA279).
文摘To realize dynamic statistical publishing and protection of location-based data privacy,this paper proposes a differential privacy publishing algorithm based on adaptive sampling and grid clustering and adjustment.The PID control strategy is combined with the difference in data variation to realize the dynamic adjustment of the data publishing intervals.The spatial-temporal correlations of the adjacent snapshots are utilized to design the grid clustering and adjustment algorithm,which facilitates saving the execution time of the publishing process.The budget distribution and budget absorption strategies are improved to form the sliding window-based differential privacy statistical publishing algorithm,which realizes continuous statistical publishing and privacy protection and improves the accuracy of published data.Experiments and analysis on large datasets of actual locations show that the privacy protection algorithm proposed in this paper is superior to other existing algorithms in terms of the accuracy of adaptive sampling time,the availability of published data,and the execution efficiency of data publishing methods.
文摘This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenarios involving Normal,Platykurtic and Skewed distributions over different sample sizes and standard deviation values.In the study,standard deviation ratios were set as 2,3,4,1/2,1/3 and 1/4 and power comparisons were made between small and large sample sizes.For equal sample sizes,small sample sizes of 5,8,10,12,16 and 20 and large sample sizes of 25,50,75 and 100 were used.For different sample sizes,the combinations of(4,16),(8,16),(10,20),(16,4),(16,8)and(20,10)small sample sizes and(10,30),(30,10),(50,75),(50,100),(75,50),(75,100),(100,50)and(100,75)large sample sizes were examined in detail.According to the findings,the power analysis under variance heterogeneity conditions shows that the Siegel-Tukey test has a higher statistical power than the other nonparametric Savage test at small and large sample sizes.In particular,the Siegel-Tukey test was reported to offer higher precision and power under variance heterogeneity,regardless of having equal or different sample sizes.
基金supported by the Doctoral Research Start-up Project of Wannan Medical College(WYRCQD2024019)the Quality Engineering Project of Anhui Provincial Department of Education-the“101 Project”(2023ylyjh046)the“Online and Offline Hybrid Course”Project(2020xsxxkc462).
文摘Artificial intelligence(AI)is rapidly transforming healthcare and medical education.Strong statistical thinking skills are vital for evaluating and applying AI tools.However,traditional medical statistics education has not adapted to this demand.This paper first analyzes the connotation and importance of statistical thinking,points out the significant challenges currently faced by medical statistics education,and then proposes strategies such as innovative teaching methods combined with evidence-based medicine,utilizing AI platforms for supplemental teaching,multidisciplinary integration,and strengthening the understanding of the statistical foundations of AI to enhance the statistical thinking abilities of medical professionals.This study emphasizes the importance of cultivating medical statistical thinking in the era of AI to improve the quality of medical education and ensure the safety and effectiveness of future medical services.
文摘Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex web pages.Through ana-lyzing various statistical characteristics of HTML el-ements in web documents,this paper proposes,based on statistical features,an unsupervised web data ex-traction method—traversing the HTML DOM parse tree at first,calculating and generating the statistical matrix of the elements,and then locating data records by clustering method and heuristic rules that reveal in-herent links between the visual characteristics of the data recording areas and the statistical characteristics of the HTML nodes—which is both suitable for data records extraction of single-page and multi-pages,and it has strong generality and needs no training.The ex-periments show that the accuracy and efficiency of this method are equally better than the current data extrac-tion method.
基金supported by TUBITAK 112E568,114E092,and 115E915 projectsTNPGN-Active RINEX data set is available to the IONOLAB group for the TUBITAK 109E055 project。
文摘In this study,the gradients of Total Electron Content(TEC)for a midlatitude region are estimated and grouped with respect to the distance between neighboring stations,time periods within a day,and satellite directions.Annual medians of these gradients for quiet days are computed as templates.The metric distances(L2N)and Symmetric Kullback-Leibler Distances(SKLD)are obtained between the templates and the daily gradient series.The grouped histograms are fitted to the prospective Probability Density Functions(PDF).The method is applied to the Slant Total Electron Content(STEC)estimates from the Turkish National Permanent GPS Network(TNPGN-Active)for 2015.The highest gradients are observed in the east-west axis with a maximum of 25 mm/km during a geomagnetic storm.The maximum differences from the gradient templates occur for neighboring stations within100-130 km distance away from each other,during night hours,and for regions bordering the Black Sea and the Mediterranean in the northeast and southeast of Turkey.The empirical PDFs of the stationpair gradients are predominantly Weibull-distributed.The mean values of Weibull PDFs in all station groups are between 1.2 and 1.8 mm/km,with an increase during noon and afternoon hours.The standard deviations of the gradient PDFs generally increase during night hours.The algorithm will form a basis for quantifying the stochastic variations of the spatial rate of change of TEC trends in midlatitude regions,thus supplementing reliable and accurate regional monitoring of ionospheric variability.
基金Project(52274096)supported by the National Natural Science Foundation of ChinaProject(WS2023A03)supported by the State Key Laboratory Cultivation Base for Gas Geology and Gas Control,China。
文摘Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.
基金Science and Technology Commission of Shanghai Municipality,China(23DZ1204703)。
文摘Extratropical transition(ET)is one of the last phases of tropical cyclones(TCs)and corresponds to the structural change from a tropical system to an extratropical system characterized by pronounced asymmetric distributions of heavy rainfall and strong wind.This study analyzes the statistical characteristics of ET events involving TCs over the western North Pacific(WNP)during 1981–2022.The analysis employs the Cyclone Phase Space(CPS)method to evaluate the accuracy of the fifth-generation reanalysis from the European Centre for Medium-Range Weather Forecasts(ERA5)in identifying ET based on different TC center definitions.Results show that defining the TC center by the minimum sea level pressure yields the most accurate ET identification.Subsequently,the study investigates several characteristics of ET events in the WNP.It is found that TCs undergoing ET(ETTCs)primarily form in the region of 125°–155°E,10°–25°N,with ET typically initiating between 30°–40°N and completing between 35°–50°N.These ETTCs predominantly occur from April to December,with peak activity observed from August to October.Additionally,the average duration of the ET process is 18.5 h,with longer durations observed from August to October,displaying a roughly 6-year cycle.Spatially,ET events with longer durations tend to occur at lower latitudes.Correspondingly,TCs initiating their ET phase at lower latitudes are typically stronger and larger,and they also experience longer ET durations.
基金partially funded by the National Natural Science Foundation of China(U2142205)the Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)+1 种基金the Special Fund for Forecasters of China Meteorological Administration(CMAYBY2020-094)the Graduate Student Research and Innovation Program of Central South University(2023ZZTS0347)。
文摘Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.
基金Supported by the Laoshan Laboratory(No.LSKJ 202202404)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42000000)+1 种基金the National Natural Science Foundation of China(NSFC)(No.42030410)the Startup Foundation for Introducing Talent of NUIST,and the Jiangsu Innovation Research Group(No.JSSCTD 202346)。
文摘Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.
文摘We perform a time-resolved statistical study of GRB 221009A’s X-ray emission using Swift XRT Photon Counting and Windowed Timing data.After standard reduction(barycentric correction,pile-up,background subtraction via HEASOFT),we extracted light curves for each observational ID and for their aggregation.Countrate histograms were fitted using various statistical distributions;fit quality was assessed by chi-squared and the Bayesian Information Criterion.The first observational segment is best described by a Gaussian distribution(χ^(2)=68.4;BIC=7651.2),and the second by a Poisson distribution(χ^(2)=33.5;BIC=4413.3).When all segments are combined,the lognormal model provides the superior fit(χ^(2)=541.9;BIC=34365.5),indicating that the full data set’s count rates exhibit the skewness expected from a multiplicative process.These findings demonstrate that while individual time intervals conform to discrete or symmetric statistics,the collective emission profile across multiple observations is better captured by a lognormal distribution,consistent with complex,compounded variability in GRB afterglows.
文摘The ability to accurately simulate the time evolu-tion of quantum systems stands as a cornerstone of modern molecular science.It provides the essential mechanistic bridge between a system’s microscopic structure and its macroscopic function,a challenge first envisioned by Feynman.The central difficulty,and the unifying theme of this Special Topic,is the problem of“complexity”:a multifaceted challenge arising from the interplay of strongly coupled electronic and vibrational degrees of freedom,quantum statistics,and the non-trivial,often non-Markovian,memory effects exerted by a surrounding environment.
基金The Key Technologies R& D Program of Heilongjiang Province (No.GB06B601)
文摘To improve the efficiency of the management of large farms, a digitalized system of economic statistics is designed based on the Internet platform of the digitalized agricultural integrated system of Friendship Farm, the largest farm in the world. The system can also realize data storage by using the access databank technology. A dynamic website system, based on ASP technology, is used to implement the on-line inquiry of the statistical index of the agricultural economy and the diagrams of the index every year. Furthermore, it can provide the value of comprehensive indicators of farms' economic profits for every year and a trend chart of the comprehensive appraisal of economic development, by using principal component analysis. An early-warning indicator boundary is decided based on the majority principle. The system can realize the farm's terminal data input with effective data-collecting channels and a normative gathering scope and system. This system breaks through the stand-alone database system in agricultural digitalized research to realize the database system in the Internet environment by integrating the existing technologies in China. The system lays a foundation for the further integrated research on the network platform of the digitalized agricultural integrated system in Friendship Farm.
基金Supported by the National Basic Research Program of China (973 Program) (No. 2010CB428703)Oceanic Science Fund for Young Scholar of SOA (Nos. 2010225, 2010118)+1 种基金Public Science and Technology Research Funds Projects of Ocean of China (Nos. 201005008, 201005009)Open Fund of MOIDAT (No. 201011)
文摘Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.
