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Recent development on statistical methods for personalized medicine discovery

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《医学前沿（英文）》 2013年第7卷第1期页码 102-110 doi: 10.1007/s11684-013-0245-7

摘要：

It is well documented that patients can show significant heterogeneous responses to treatments so the best treatment strategies may require adaptation over individuals and time. Recently, a number of new statistical methods have been developed to tackle the important problem of estimating personalized treatment rules using single-stage or multiple-stage clinical data. In this paper, we provide an overview of these methods and list a number of challenges.

关键词： dynamic treatment regimes personalized medicine reinforcement learning Q-learning

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Assessment of temporal and spatial variations in water quality using multivariate statistical methods

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

《环境科学与工程前沿（英文）》 2014年第8卷第6期页码 895-904 doi: 10.1007/s11783-014-0736-z

摘要： This study evaluated the temporal and spatial variations of water quality data sets for the Xin'anjiang River through the use of multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), correlation analysis, and principal component analysis (PCA). The water samples, measured by ten parameters, were collected every month for three years (2008–2010) from eight sampling stations located along the river. The hierarchical CA classified the 12 months into three periods (First, Second and Third Period) and the eight sampling sites into three groups (Groups 1, 2 and 3) based on seasonal differences and various pollution levels caused by physicochemical properties and anthropogenic activities. DA identified three significant parameters (temperature, pH and ) to distinguish temporal groups with close to 76% correct assignment. The DA also discovered five parameters (temperature, electricity conductivity, total nitrogen, chemical oxygen demand and total phosphorus) for spatial variation analysis, with 80.56% correct assignment. The non–parametric correlation coefficient (Spearman R) explained the relationship between the water quality parameters and the basin characteristics, and the GIS made the results visual and direct. The PCA identified four PCs for Groups 1 and 2, and three PCs for Group 3. These PCs captured 68.94%, 67.48% and 70.35% of the total variance of Groups 1, 2 and 3, respectively. Although natural pollution affects the Xin'anjiang River, the main sources of pollution included agricultural activities, industrial waste, and domestic wastewater.

关键词： Xin'anjiang River multivariable statistical analysis temporal variation spatial variation water quality

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Statistical considerations for genomic selection

Huimin KANG, Lei ZHOU, Jianfeng LIU

《农业科学与工程前沿（英文）》 2017年第4卷第3期页码 268-278 doi: 10.15302/J-FASE-2017164

摘要： Genomic selection is becoming increasingly important in animal and plant breeding, and is attracting greater attention for human disease risk prediction. This review covers the most commonly used statistical methods and some extensions of them, i.e., ridge regression and genomic best linear unbiased prediction, Bayesian alphabet, and least absolute shrinkage and selection operator. Then it discusses the measurement of the performance of genomic selection and factors affecting the prediction of performance. Among the measurements of prediction performance, the most important and commonly used measurement is prediction accuracy. In simulation studies where true breeding values are available, accuracy of genomic estimated breeding value can be calculated directly. In real or industrial data studies, either training-testing approach or -fold cross-validation is commonly employed to validate methods. Factors influencing the accuracy of genomic selection include linkage disequilibrium between markers and quantitative trait loci, genetic architecture of the trait, and size and composition of the training population. Genomic selection has been implemented in the breeding programs of dairy cattle, beef cattle, pigs and poultry. Genomic selection in other species has also been intensively researched, and is likely to be implemented in the near future.

关键词： genomic estimated breeding value genomic selection linkage disequilibrium statistical methods

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我国生态文明统计核算方法研究

石庆焱,周晶

《中国工程科学》 2017年第19卷第4期页码 67-73 doi: 10.15302/J-SSCAE-2017.04.011

摘要：

构建生态文明统计核算体系是生态文明建设的基础性工作，可为生态文明建设进程的监测、评估和决策提供可靠的数据支撑。虽然我国目前已有一定的资源环境统计基础，但由于缺少生态文明统计核算的顶层设计，因此无法将这些数据有效整合于统一框架。本文从生态文明建设的实际需求出发，分析了我国在生态文明统计核算中存在的问题，在结合SEEA2012–CF的基础上构建了我国生态文明统计指标体系和核算框架，并就进一步完善我国生态文明统计核算体系提出建议。

关键词：生态文明 SEEA2012–CF 统计体系核算框架自然资源资产负债表环境资产账户

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Factor analysis for the statistical modeling of earthquake-induced landslides

Jeng-Wen LIN, Meng-Hsun HSIEH, Yu-Jen LI

《结构与土木工程前沿（英文）》 2020年第14卷第1期页码 123-126 doi: 10.1007/s11709-019-0582-y

摘要： Earthquake-induced landslides are difficult to assess and predict owing to the inherent unpredictability of earthquakes. In most existing studies, the landslide potential is statistically assessed by collecting and analyzing the data of historical landslide events and earthquake observation records. Unlike rainfall-induced landslides, earthquake-induced landslides cannot be predicted in advance using real-time monitoring systems, and the development of the models for these landslides should instead depend on early earthquake warnings and estimations. Hence, in this study, factor analysis was performed and the frequency distribution method was employed to investigate the potential risk of the landslides caused by earthquakes. Factors such as the slope gradient, lithology (geology), aspect, and elevation were selected and classified as influential factors to facilitate the construction of a landslide database for the area of study.

关键词： earthquake factor analysis slope landslides statistical modeling

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Analysis on the distinguishing features of traditional Chinese therapeutics and related statistical issues

Jingqing Hu, Jie Qiao, Deying Kang, Baoyan Liu

《医学前沿（英文）》 2011年第5卷第2期页码 203-207 doi: 10.1007/s11684-011-0138-6

摘要： Traditional Chinese medicine (TCM) is one of the rarely existing ancient traditional medicines that hold systematic theories as well as preventative and therapeutic methods for diseases in practice. From the 1950s, such research methods as mathematics, statistics, and data mining (DM) have been gradually introduced to TCM studies, making it more scientific. Meanwhile, the distinct features of TCM theories and diagnostic-model have constantly challenged the methodology of statistics. This paper introduces the following scientific features of traditional Chinese therapeutics: 1) its goal is to balance the functions and conditions of human body; 2) it emphasizes on holism and individualization; 3) it stresses the longitudinal regulation and evaluation mode, which is a circle of syndrome diagnosis, treatment and evaluation; 4) the interventions of TCM are abundant, compound and natural; and 5) humanistic thought is everywhere. Some statistical problems are raised based on these features. First, complex statistical methods that can analyze subjective indexes and latent variables, multidimensional and multistage data, non-equilibrium designed studies, and longitudinal data are required. Second, comprehensive evaluation on multiple-target mechanism has been brought in by combination treatment. Third, there is a need to analyze how humanity and related cultural factors may influence the effect of interventions. Thus, promoting implemented studies of statistics as well as carrying out the TCM scientific propositions have become the common expectations of both TCM and modern medicine.

关键词： traditional Chinese therapeutics feature statistic

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Spatial impacts of climate factors on regional agricultural and forestry biomass resources in north-eastern province of China

Wenyan Wang, Wei Ouyang, Fanghua Hao, Yun Luan, Bo Hu

《环境科学与工程前沿（英文）》 2016年第10卷第4期 doi: 10.1007/s11783-016-0864-8

摘要： Dynamic analysis of biomass combined NPP modeling has been adopted. Temperature trends to warming and precipitation has periodic fluctuation. Regional distribution of agricultural and forestry biomass is mutual and divergent. Precipitation is significantly positive correlated with agricultural biomass. Temperature is negative on forestry biomass in Lesser Khingan & northern Changbai. Precipitation plays positive effect on biomass in southwestern Changbai Mountain. The dynamics of agricultural and forestry biomass are highly sensitive to climate change, particularly in high latitude regions. Heilongjiang Province was selected as research area in North-east China. We explored the trend of regional climate warming and distribution feature of biomass resources, and then analyzed on the spatial relationship between climate factors and biomass resources. Net primary productivity (NPP) is one of the key indicators of vegetation productivity, and was simulated as base data to calculate the distribution of agricultural and forestry biomass. The results show that temperatures rose by up to 0.37°C/10a from 1961 to 2013. Spatially, the variation of agricultural biomass per unit area changed from -1.93 to 5.85 t·km ·a during 2000–2013. More than 85% of farmland areas showed a positive relationship between agricultural biomass and precipitation. The results suggest that precipitation exerts an overwhelming climate influence on agricultural biomass. The mean density of forestry biomass varied from 10 to 30 t·km . Temperature had a significant negative effect on forestry biomass in Lesser Khingan and northern Changbai Mountain, because increased temperature leads to decreased Rubisco activity and increased respiration in these areas. Precipitation had a significant positive relationship with forestry biomass in south-western Changbai Mountain, because this area had a warmer climate and stress from insufficient precipitation may induce xylem cavitation. Understanding the effects of climate factors on regional biomass resources is of great significance in improving environmental management and promoting sustainable development of further biomass resource use.

关键词： Biomass resources Net primary productivity (NPP) Climate change Heilongjiang Province China Climate Energy systems/technology Other sustainability (specify) Statistical methods GIS Model flow CFD

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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

《机械工程前沿（英文）》 2010年第5卷第2期页码 149-156 doi: 10.1007/s11465-010-0008-y

摘要： With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.

关键词： statistical process control (SPC) fuzzy adaptive resonance theory (ART) histogram control chart time series analysis

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Application of statistical design for the production of inulinase by

M. DILIPKUMAR, M. RAJASIMMAN, N. RAJAMOHAN

《化学科学与工程前沿（英文）》 2011年第5卷第4期页码 463-470 doi: 10.1007/s11705-011-1112-1

摘要： A Plackett-Burman design was employed for screening 18 nutrient components for the production of inulinase using sp. and pressmud as the substrate via solid-state fermentation (SSF). From the experiments, three nutrients viz. yeast extract, FeSO ·7H O, and NH NO were found to be the most significant components. Hence these three components were selected and optimized using Response Surface Methodology (RSM). The optimum conditions are: yeast extract 0.00274 g/gds, FeSO ·7H O 0.00011 g/gds and NH NO 0.00772 g/gds. The effect of the substrate concentration and initial moisture content were also studied. A substrate concentration of 12 g and an initial moisture content of 65% are optimum for the maximum production of inulinase (89 U/gds).

关键词： inulinase pressmud Response Surface Methodology (RSM) streptomyces sp

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复杂耦合系统的统计能量分析及其应用

盛美萍

《中国工程科学》 2002年第4卷第6期页码 77-84

摘要：

文章综合导纳分析法、经典统计能量分析方法和经典功率流理论的各自优点，提出适合复杂耦合系统的统计能量分析方法，为研究实际机械结构之间的振动传递规律、复杂机械系统的声辐射特性提供理论依据，为实际工程结构的振动隔离、噪声治理提供理论指导。文章首次提出统计能量分析参数必须统一定义，将影响实际机械结构相互之间能量传递的若干要素各自分离，并引入相应的参数分别开展研究。利用理论研究的成果，发展后的统计能量分析首次应用于水下航行器振动和噪声特性分析，预报了水下航行器的振动传递规律和辐射噪声级。理论分析与实验测试结果符合较好。文章指出了水下航行器噪声治理的方向。

关键词：功率流统计能量分析导纳耦合

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Statistical analysis of residential building energy consumption in Tianjin

Jihong LING,Luhui ZHAO,Jincheng XING,Zhiqiang LU

《能源前沿（英文）》 2014年第8卷第4期页码 513-520 doi: 10.1007/s11708-014-0327-5

摘要： To analyze the effect of energy conservation policies on energy consumption of residential buildings, the characteristics of energy consumption and indoor thermal comfort were investigated in detail in Tianjin, China, based on official statistical yearbook and field survey data. A comprehensive survey of 305 households indicates that the mean electricity consumption per household is 3215 kWh/a, in which annual cooling electricity consumption is 344 kWh/a, and the mean natural gas consumption for cooking is 103.2 m /a. Analysis of 3966 households data shows that space heating average intensity of residential buildings designed before 1996 is 133.7 kWh/(m ·a), that of buildings designed between 1996 and 2004 is 117.2 kWh/(m ·a), and that of buildings designed after 2004 is 105.0 kWh/(m ·a). Apparently, enhancing the performance of envelops is effective in reducing space heating intensity. Furthermore, the results of questionnaires show that 18% of the residents feel slightly warm and hot respectively, while 3% feel slightly cold in winter. Therefore, the electricity consumption in summer will rise for meeting indoor thermal comfort.

关键词： energy intensity indoor thermal comfort residential building survey statistical analysis energy conversation

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Development of mix design method based on statistical analysis of different factors for geopolymer concrete

Paramveer SINGH; Kanish KAPOOR

《结构与土木工程前沿（英文）》 2022年第16卷第10期页码 1315-1335 doi: 10.1007/s11709-022-0853-x

摘要： The present study proposes the mix design method of Fly Ash (FA) based geopolymer concrete using Response Surface Methodology (RSM). In this method, different factors, including binder content, alkali/binder ratio, NS/NH ratio (sodium silicate/sodium hydroxide), NH molarity, and water/solids ratio were considered for the mix design of geopolymer concrete. The 2D contour plots were used to setup the mix design method to achieve the target compressive strength. The proposed mix design method of geopolymer concrete is divided into three categories based on curing regime, specifically one ambient curing (25 °C) and two heat curing (60 and 90 °C). The proposed mix design method of geopolymer concrete was validated through experimentation of M30, M50, and M70 concrete mixes at all curing regimes. The observed experimental compressive strength results validate the mix design method by more than 90% of their target strength. Furthermore, the current study concluded that the required compressive strength can be achieved by varying any factor in the mix design. In addition, the factor analysis revealed that the NS/NH ratio significantly affects the compressive strength of geopolymer concrete.

关键词： geopolymer concrete mix design fly ash response surface methodology compressive strength stress−strain

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A review of optimization modeling and solution methods in renewable energy systems

《工程管理前沿（英文）》页码 640-671 doi: 10.1007/s42524-023-0271-3

摘要： The advancement of renewable energy (RE) represents a pivotal strategy in mitigating climate change and advancing energy transition efforts. A current of research pertains to strategies for fostering RE growth. Among the frequently proposed approaches, employing optimization models to facilitate decision-making stands out prominently. Drawing from an extensive dataset comprising 32806 literature entries encompassing the optimization of renewable energy systems (RES) from 1990 to 2023 within the Web of Science database, this study reviews the decision-making optimization problems, models, and solution methods thereof throughout the renewable energy development and utilization chain (REDUC) process. This review also endeavors to structure and assess the contextual landscape of RES optimization modeling research. As evidenced by the literature review, optimization modeling effectively resolves decision-making predicaments spanning RE investment, construction, operation and maintenance, and scheduling. Predominantly, a hybrid model that combines prediction, optimization, simulation, and assessment methodologies emerges as the favored approach for optimizing RES-related decisions. The primary framework prevalent in extant research solutions entails the dissection and linearization of established models, in combination with hybrid analytical strategies and artificial intelligence algorithms. Noteworthy advancements within modeling encompass domains such as uncertainty, multienergy carrier considerations, and the refinement of spatiotemporal resolution. In the realm of algorithmic solutions for RES optimization models, a pronounced focus is anticipated on the convergence of analytical techniques with artificial intelligence-driven optimization. Furthermore, this study serves to facilitate a comprehensive understanding of research trajectories and existing gaps, expediting the identification of pertinent optimization models conducive to enhancing the efficiency of REDUC development endeavors.

关键词： renewable energy system bibliometrics mathematical programming optimization models solution methods

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Analysis of statistical thermodynamic model for binary protein adsorption equilibria on cation exchange

ZHOU Xiaopeng, SU Xueli, SUN Yan

《化学科学与工程前沿（英文）》 2007年第1卷第2期页码 103-112 doi: 10.1007/s11705-007-0020-x

摘要： A study of nonlinear competitive adsorption equilibria of proteins is of fundamental importance in understanding the behavior of preparative chromatographic separation. This work describes the nonlinear binary protein adsorption equilibria on ion exchangers by the statistical thermodynamic (ST) model. The single-component and binary protein adsorption isotherms of bovine hemoglobin (Hb) and bovine serum albumin (BSA) on SP Sepharose FF were determined by batch adsorption experiments in 0.05 mol/L sodium acetate buffer at three pH values (4.5, 5.0 and 5.5) and three NaCl concentrations (0.05, 0.10 and 0.15 mol/L) at pH 5.0. The ST model was found to depict the effects of pH and ionic strength on the single-component equilibria well, with model parameters depending on the pH and ionic strength. Moreover, the ST model gave acceptable fitting to the binary adsorption data with the fitted single-component model parameters, leading to the estimation of the binary ST model parameter. The effects of pH and ionic strength on the model parameters are reasonably interpreted by the electrostatic and thermodynamic theories. Results demonstrate the availability of the ST model for describing nonlinear competitive protein adsorption equilibria in the presence of two proteins.

关键词： fundamental importance single-component equilibria acceptable fitting hemoglobin chromatographic separation

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Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

《机械工程前沿（英文）》 2018年第13卷第1期页码 85-95 doi: 10.1007/s11465-018-0491-0

摘要：

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

关键词： injection molding intelligent methods process parameters optimization