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A review on statistical models for identifying climate contributions to crop yields

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Journal of Geographical Sciences 2013年第3期23卷 567-576页

作者： SHI Wenjiao TAO Fulu ZHANG Zhao State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Beijing 100875 China Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China

statistical models using historical data on crop yields and weather to calibrate rela- tively simple regression equations have been widely and extensively applied in previous studies, and have provided a common alternative to process-based models, which require extensive input data on cultivar, management, and soil conditions. However, very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields. This paper introduces three main statistical methods, i.e., time-series model, cross-section model and panel model, which have been used to identify such issues in the field of agrometeorology. Generally, research spatial scale could be categorized into two types using statistical models, including site scale and regional scale （e.g. global scale, national scale, provincial scale and county scale）. Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models. The issues include the extent of spatial and temporal scale, non-climatic trend removal, colinearity existing in climate variables and non-consideration of adaptations. Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.

关键词： climate change crop yield influence adaptation statistical model

statistical models for jointly analyzing multiple allometries

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Statistical models for jointly analyzing multiple allometrie...

A New statistical modeling Approach for Survival Analysis of Cancer Patients—Multiple Myeloma Cancer

中国畜牧兽医学会养牛学分会2011年学术研讨会

作者： Huijiang Gao~1,Runqing Yang~2,and Junya Li~1 1.Institute of Animal Science,Chiese Academy of Agricultural Science,100193,People’s Republic of China 2.School of Agriculture and biology,Shanghai Jiaotong University,Shanghai 200240,People’s Republic of China Running Head:Joint allometry scaling model

As reciprocal function of simple allometry equation is the power one,it can also be used to define allometry scaling but whose scalling exponent has an opposite meaning to that of simple allometry *** on this,a joint static allometry scaling model of entire body size on multiple partial body size is established,which can not only simultaneously evaluate allometry scaling of multiple partial body size,but also take into account the correlations among multiple partial body size and facilitate subsequent statistical inference and *** that ontogenetic allometry may be time-dependent, ontogenetic allometry is estimated by jointly analyzing changes of entire and multiple partial body sizes as growth time with multivariate stepwise *** analysis of allometry scaling is suitable for muliple biological traits and functions with same property or comparability,which is illustrated by one example.

关键词： Allometry scaling statistical model Joint analysis

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Open Journal of Applied Sciences 2021年第4期10卷 365-378页

作者： Lohuwa Mamudu Chris P. Tsokos Department of Mathematics and Statistics University of South Florida Tampa USA

Background: The Cox Proportional Hazard (Cox-PH) model has been a popularly used method for survival analysis of cancer data given the survival times as a function of covariates or risk factors. However, it is very seldom to see the assumptions for the application of the Cox-PH model satisfied in most of the research studies, raising questions about the effectiveness, robustness, and accuracy of the model predicting the proportion of survival times. This is because the necessary assumptions in most cases are difficult to satisfy, as well as the assessment of interaction among covariates. Methods: To further improve the therapeutic/treatment strategy for cancer diseases, we proposed a new approach to survival analysis using multiple myeloma (MM) cancer data. We first developed a data-driven nonlinear statistical model that predicts the survival times with 93% accuracy. We then performed a parametric analysis on the predicted survival times to obtain the survival function which is used in estimating the proportion of survival times. Results: The new proposed approach for survival analysis has proved to be more robust and gives better estimates of the proportion of survival than the Cox-PH model. Also, satisfying the proposed model assumptions and finding interactions among risk factors is less difficult compared to the Cox-PH model. The proposed model can predict the real values of the survival times and the identified risk factors are ranked according to the percent of contribution to the survival time. Conclusion: The new proposed nonlinear statistical model approach for survival analysis of cancer diseases is very efficient and provides an improved and innovative strategy for cancer therapeutic/treatment.

关键词： Health Science Multiple Myeloma Cancer Cancer Therapeutic Cox-PH model statistical model Survival Analysis Probability Estimation

Analysis on the Logarithmic model of Relationships

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四川大学学报（工程科学版） 2005年第S1期37卷 71-74页

作者： Peng, Qinge Cao, Shuyou Liu, Xingnian Hang, Er Lab. of Hydraulics and Mountain River Eng. Sichuan Univ. Chengdu 610065 China

The logarithmic model is often used to describe the relationships between *** often gives good statistical ***,in the process of modeling of soil and water conservation,we find out that this“good”model cannot guarantee good *** this paper we make an inquiry into the intrinsic *** is shown that the logarithmic model has the property of enlarging or reducing model errors,and the disadvantages of the logarithmic model are analyzed.

关键词： soil and water conservation statistical model logarithmic model

Experimental and mechanistic study of dispersed micrometer-sized particle resuspension in a square straight duct with rough walls

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Particuology 2023年第12期83卷 101-114页

作者： Qi Sun Suyuan Yu Wei Peng Institute of Nuclear and New Energy Technology Cooperation Innovation Center of Advanced Nuclear Energy TechnologyKey Laboratory of Advanced Reactor Engineering and Safety of Ministry of EducationTsinghua UniversityBeijing100084China Center for Combustion Energy Key Laboratory for Thermal Science and Power Engineering of the Ministry of EducationDepartment of Energy and Power EngineeringTsinghua UniversityBeijing100084China

The resuspension of graphite dust is an important phenomenon in the release of radioactivity and the safety of nuclear reactors during severe *** this study,a visualization experimental platform is constructed to study effects of particle size,flow velocity,and wall roughness on the resuspension characteristics of graphite particles.A statistical model of particle resuspension applicable to monolayer dispersed particles is developed based on the moment equilibrium of the particles and the flow field characteristics,as calculated by the large-eddy simulation *** results show that particle resuspension can be divided into short-and long-term resuspension *** particle resuspension occurs during the short-term *** increases in flow velocity and particle diameter,the aerodynamic or adhesion force acting on the particles increases,and corresponding particle resuspension fraction *** influence of rough walls on particle resuspension is related to both the force on the particles and the arm ratio between the wall morphology and the particle diameter.A comparison with the experimental results demonstrates that the particle resuspension model developed in this study accurately predicts the impact of flow velocity,particle size,and wall roughness on particle resuspension.

关键词： Particle resuspension statistical model Moment equilibrium High temperature gas-cooled reactor(HTGR)

Multiscale study of the dynamic friction coefficient due to asperity plowing

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Friction 2021年第4期9卷 822-839页

作者： Jianqiao HU Hengxu SONG Stefan SANDFELD Xiaoming LIU Yueguang WEI State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100049China Institute for Advanced Simulation IAS-9:Materials Data Science and Informatics Forschungszentrum Juelich GmbHJuelich 52425Germany Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China

A macroscopically nominal flat surface is rough at the nanoscale level and consists of ***,the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity contact pairs under *** this work,we first used molecular dynamics simulations to study the non-adhesive shear between single contact ***,to estimate the friction coefficient of rough surfaces,we implemented the frictional behavior of a single contact pair into a Greenwood-Williamson-type statistical *** employing the present multiscale approach,we used the size,rate,and orientation effects,which originated from nanoscale dislocation plasticity,to determine the dependence of the macroscale friction coefficient on system parameters,such as the surface roughness,separation,loading velocity,and *** model predicts an unconventional dependence of the friction coefficient on the normal contact load,which has been observed in nanoscale frictional ***,this model represents one step toward understanding some of the relevant macroscopic phenomena of surface friction at the nanoscale level.

关键词： multiscale friction asperity plowing dislocation plasticity size/velocity effect crystal orientation statistical model

modeling the density gradient of 3D nanofiber scaffolds fabricated by divergence electrospinning

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Advances in Manufacturing 2021年第3期9卷 414-429页

作者： Muhammad Adib Uz Zaman Dilshan Sooriyaarachchi Ying-Ge Zhou George Z.Tan Dong-Ping Du Department of Industrial Manufacturing and Systems EngineeringTexas Tech UniversityLubbockTXUSA

Following recent insights on structure-cell-function interactions and the critical role of the extracellular matrix(ECM),the latest biofabrication approaches have increasingly focused on designing materials with biomimetic *** electrospinning is a novel fabrication method for three-dimensional(3D)nanofiber *** is introduced to produce 3D nanofiber mats that have numerous applications in regenerative medicine and tissue *** of the most important characteristics of 3D nanofiber mats is the density *** study provides a statistical analysis and response surface modeling framework based on experimental data to evaluate the manner by which the geometric designs of double-bevel collectors influence the fiber density ***,variance of analysis and sensitivity analysis were performed to identify parameters that had significant effects,and a response surface model embedded with seven location indicators was developed to predict the spatial distribution of fiber density for different collector *** was concluded that the collector height,bevel angle,and their interactions were significant factors influencing the density *** study revealed the sensitivity of system configuration and provided an optimization tool for process controllability of microstructure gradients.

关键词： Electrospinning 3D nanofiber scaffold statistical model Design of experiments Response surface method

Quantitative evaluation of urban park cool island factors in mountain city

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Journal of Central South University 2012年第6期19卷 1657-1662页

作者：卢军李春蝶杨永川张歆晖靳鸣 Key Laboratory of The Three Gorges Reservoir Region's Eco-Environment(Chongqing University) Ministry of Education Sichuan Southwest Project Management Consulting Co.Ltd.

Evaluating how park characteristics affect the formation of a park cool island(PCI) is the premise of guiding green parks planning in mountain *** diurnal variation of PCI intensity was achieved,and correlations between PCI intensity and park characteristics such as park area,landscape shape index(LSI),green ratio and altitude were analyzed,using 3 010 temperature and humidity data from measurements in six parks with typical park characteristics in Chongqing,*** results indicate that:1) the main factor determining PCI intensity is park area,which leads to obvious cool island effect when it exceeds 14 hm2;2) there is a negative correlation between PCI intensity and LSI,showing that the rounder the park shape is,the better the cool island effect could be achieved;3) regression analysis of humidity and PCI intensity proves that photosynthesis midday depression(PMD) is an important factor causing the low PCI intensity at 13:00;4) the multivariable linear regression model proposed here could effectively well predict the daily PCI intensity in mountain cities.

关键词： park cool island park characteristics regression analysis photosynthesis midday depression statistical model

Time-Series modeling and Prediction of Global Monthly Absolute Temperature for Environmental Decision Making

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Advances in Atmospheric Sciences 2013年第2期30卷 382-396页

作者： YE Liming YANG Guixia Eric VAN RANST TANG Huajun Key Laboratory of Agri-Informatics Ministry of Agriculture/Institute ofAgricultural Resources and Regional PlanningChinese Academy of Agricultural Sciences Beijing 100081 Department of Geology and Soil Science (WE13) Ghent University Krijgslaan 281 9000 Gent Belgium Chinese Academy of Agricultural Sciences Beijing 100081

A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined （DSC） approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average （SARIMA） models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term （10-year） environmental planning and decision making.

关键词： time series analysis statistical model polynomial trend Fourier method ARIMA climatechange