Application of cluster analysis and stepwise regression in predicting the traffic volume of lanes

Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors.

Population Quantity Variations of Oriental Fruit Fly (Bactrocera dorsalis Hendel) on the Basis of Stepwise Regression Analysis

[Objective] The research aimed to study the significant influence factors of the population variations of oriental fruit fly. [Method] Using stepwise regression analysis, the population variations law of oriental fruit fly in Jianshui County of Yunnan province and the meteorological factors that caused its occurrence were analyzed. And the regression model was built. Finally, the regression model was tested on the basis of the data in Jianshui County of Yunnan Province during 2004-2006.[Result] The main meteorological factors that influenced the occurrence of oriental fruit fly were relative humidity, the lowest monthly temperature and rainfall. [Conclusion] This study will provide certain reference for the prediction researches on the time, quantity and occurrence peak of oriental fruit fly.

An optimized protocol for stepwise optimization of real-time RT-PCR analysis

Computational tool-assisted primer design for real-time reverse transcription(RT)PCR(qPCR)analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome.It can lead to false confidence in the quality of the designed primers,which sometimes results in skipping the optimization steps for qPCR.However,the optimization of qPCR parameters plays an essential role in the efficiency,specificity,and sensitivity of each gene’s primers.Here,we proposed an optimized approach to sequentially optimizing primer sequences,annealing temperatures,primer concentrations,and cDNA concentration range for each reference(and target)gene.Our approach started with a sequence-specific primer design that should be based on the single-nucleotide polymorphisms(SNPs)present in all the homologous sequences for each of the reference(and target)genes under study.By combining the efficiency calibrated and standard curve methods with the 2−ΔΔCt method,the standard cDNA concentration curve with a logarithmic scale was obtained for each primer pair for each gene.As a result,an R 2≥0.9999 and the efficiency(E)=100±5% should be achieved for the best primer pair of each gene,which serve as the prerequisite for using the 2^(−ΔΔCt) method for data analysis.We applied our newly developed approach to identify the best reference genes in different tissues and at various inflorescence developmental stages of Tripidium ravennae,an ornamental and biomass grass,and validated their utility under varying abiotic stress conditions.We also applied this approach to test the expression stability of six reference genes in soybean under biotic stress treatment with Xanthomonas axonopodis pv.glycines(Xag).Thus,these case studies demonstrated the effectiveness of our optimized protocol for qPCR analysis.

Multi－variate Stepwise Discriminant Analysis Research Affecting Portal Hypertension＇s Grade Factors of Liver Function

The idtal time for selecting portal hypertension operation is the accurate judgement of the grade of liver function.yet the present criterion in grading liver functicn is controversial.tco pztitnts vith 20 factoxs related to poxttl hypeitersor wexe undergone stepwise discriminant analysis by using SAS software on the IBM/PC computer(significance levtl α=0.05).The results show that ascites degree prothrombin tmie(PT),serum total bilirubin,serum albumin content,main portal vein flow are significant fators.In the light of above variates contributing to grading liver function as to estblish a discriminant eqation,it was found that the total agreement rate between replaceable discimination and original Child-Pugh classification is 86%.A test for agieement was performed between discriminant and original classificaton,showing that the two kinds of classification methods have a good agreement rates (Kppa=0.7856),indicating the discriminant classification is of practica values.

A quantitative analysis on the sources of dune sand in the Hulun Buir Sandy Land:application of stepwise discriminant analysis (SDA) to the granulometric data

Quantitatively determining the sources of dune sand is one of the problems necessarily and urgently to be solved in aeolian landforms and desertification research. Based on the granulometric data of sand materials from the Hulun Buir Sandy Land, the paper employs the stepwise discriminant analysis technique (SDA) for two groups to select the principal factors determining the differences between surface loose sediments. The extent of similarity between two statistical populations can be described quantitatively by three factors such as the number of principal variables, Mahalanobis distance D 2 and confidence level 琢for F-test. Results reveal that: 1) Aeolian dune sand in the region mainly derives from Hailar Formation (Q 3 ), while fluvial sand and palaeosol also supply partially source sand for dunes; and 2) in the vicinity of Cuogang Town and west of the broad valley of the lower reaches of Hailar River, fluvial sand can naturally become principal supplier for dune sand.

Analysis and Evaluation Indicator Selection of Chilling Tolerance of Different Cotton Genotypes

[Objectivc] This study aimed to investigate the chilling tolerance of seedlings of different cotton genotypes and screen appropriate indicators for assess- ing chilling tolerance, to establish reliable mathematical evaluation model for chilling tolerance of cotton, thus providing theoretical basis for breeding and promoting new chilling-tolerant cotton germplasms and large-scale evaluation of chilling tolerance of cotton varieties. [Method] Fifteen cotton varieties （lines） were used as experimental materials. The photosynthetic gas exchange parameters, chlorophyll fluorescence ki- netic parameters, chlorophyll content, relative soluble sugar content, malonaldehyde content, relative proiine content, relative conductivity and other 12 physiological indi- cators of seedling leaves under low temperature treatment （5 ℃, 12 h） and recovery treatment （25 ℃. 24 h） were determined; based on the chilling tolerance coefficient （CTC） of various individual indicators, the comprehensive evaluation of chilling toler- ance was conducled by using principal component analysis, hierarchical cluster anal- ysis and stepwise regression analysis. [Result] The results showed that the 12 indi- vidual physiological indicators could be classified into 7 independent comprehensive components by principal component analysis; 15 cotton varieties （lines） were clus- tered into three categories by using membership function method and hierarchical cluster analysis; the mathematical model for evaluating chilling tolerance of cotton seedlings was established： D =0.275 -0.244Fo1 ＋0.206Fv/Fm1＋0.326g,%-0.056SS ＋ 0.225MDA＋O.O38REC （FF=0.995）, and the evaluation accuracy of the equation was higher than 94.25%,0. Six identification indicators closely related to chilling tolerance were screened, including Fo,, Fv/Fm1, Seedling leaves of cotton varieties （lines） gs2, SS, MDA, and REC. [Conclusion] with high chilling tolerance are less dam- aged under low temperature stress, and are able to maintain relatively high photo- synthetic electron transport capacity and high stomatal conductance after recovery treatment, which is contributed to gas exchange and recovery of photosynthetic ca- pacity. Determination of the six indicators under the same stress condition can be adopted for rapid identification and prediction of the chilling tolerance of other cotton varieties, which provides basis for the breeding, promotion, identification and screen- ing of chilling tolerant germplasms.

Statistical Analysis of Leaf Water Use Efficiency and Physiology Traits of Winter Wheat Under Drought Condition

Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency （WUE） and physiological traits （photosynthesis rate, stomatal conductance, transpiration rate, intercellular CO2 concentration, etc.） of 29 wheat cultivars. The results showed that photosynthesis rate, stomatal conductance, and transpiration rate were the most important leaf WUE parameters under drought condition. Based on the results of statistical analyses, principal component analysis could be the most suitable method to ascertain the relationship between leaf WUE and relative physiological traits. It is reasonable to assume that high leaf WUE wheat could be obtained by selecting breeding materials with high photosynthesis rate, low transpiration rate, and stomatal conductance under dry area.

Impacts of COVID-19 pandemic on urban park visitation:a global analysis

The COVID-19 pandemic has resulted in over 33 million confirmed cases and over 1 million deaths globally,as of 1 October 2020.During the lockdown and restrictions placed on public activities and gatherings,green spaces have become one of the only sources of resilience amidst the coronavirus pandemic,in part because of their positive effects on psychological,physical and social cohesion and spiritual wellness.This study analyzes the impacts of COVID-19 and government response policies to the pandemic on park visitation at global,regional and national levels and assesses the importance of parks during this global pandemic.The data we collected primarily from Google’s Community Mobility Reports and the Oxford Coronavirus Government Response Tracker.The results for most countries included in the analysis show that park visitation has increased since February 16th,2020 compared to visitor numbers prior to the COVID-19 pandemic.Restrictions on social gathering,movement,and the closure of workplace and indoor recreational places,are correlated with more visits to parks.Stay-at-home restrictions and government stringency index are negatively associated with park visits at a global scale.Demand from residents for parks and outdoor green spaces has increased since the outbreak began,and highlights the important role and benefits provided by parks,especially urban and community parks,under the COVID-19 pandemic.We provide recommendations for park managers and other decision-makers in terms of park management and planning during health crises,as well as for park design and development.In particular,parks could be utilized during pandemics to increase the physical and mental health and social well-being of individuals.

乳腺癌术后患者自我形象的Stepwise多元回归分析调查

目的探讨乳腺癌术后患者自我形象水平的影响因素。方法选择我院2018年9月至2019年9月接收的70例乳腺癌术后患者以及同期70例健康女性作为研究对象,应用自我形象量表(BIBCQ)评分,分析乳腺癌术后患者自我形象的相关因素,并采用多元线性回归分析,确定影响患者自我形象的独立因素。结果乳腺癌术后患者自我形象各维度评分明显高于健康女性(P<0.001),Stepwise多元线性回归分析显示,年龄、配偶态度、文化程度、抑郁焦虑是乳腺癌术后自我形象的独立影响因素。结论乳腺癌患者术后自我形象受配偶态度、年龄、文化程度等多种因素影响,临床应针对相关影响因素实施个性化护理服务。

A calibration method of Argo floats based on multiple regression analysis

Argo floats are flee-moving floats that report vertical profiles of salinity, temperature and pressure at regular time intervals. These floats give good measurements of temperature and pressure, but salinity measurements may show significant sensor drifting with time. It is found that sensor drifting with time is not purely linear as presupposed by Wong （2003）. A new method is developed to calibrate conductivity data measured by Argo floats. In this method, Wong＇s objective analysis method was adopted to estimate the background climatological salinity field on potential temperature surfaces from nearby historical data in WOD01. Furthermore, temperature and time factors are taken into account, and stepwise regression was used for a time-varying or temperature-varying slope in potential conductivity space to correct the drifting in these profiling float salinity data. The result shows salinity errors using this method are smaller than that of Wong＇s method, the quantitative and qualitative analysis of the conductivity sensor can be carded out with our method.

New empirical model to evaluate groundwater flow into circular tunnel using multiple regression analysis

There are various analytical, empirical and numerical methods to calculate groundwater inflow into tun- nels excavated in rocky media. Analytical methods have been widely applied in prediction of groundwa- ter inflow to tunnels due to their simplicity and practical base theory. Investigations show that the real amount of water infiltrating into jointed tunnels is much less than calculated amount using analytical methods and obtained results are very dependent on tunnel＇s geometry and environmental situations. In this study, using multiple regression analysis, a new empirical model for estimation of groundwater seepage into circular tunnels was introduced. Our data was acquired from field surveys and laboratory analysis of core samples. New regression variables were defined after perusing single and two variables relationship between groundwater seepage and other variables. Finally, an appropriate model for estima- tion of leakage was obtained using the stepwise algorithm. Statistics like R, R2, R2e and the histogram of residual values in the model represent a good reputation and fitness for this model to estimate the groundwater seepage into tunnels. The new experimental model was used for the test data and results were satisfactory. Therefore, multiple regression analysis is an effective and efficient way to estimate the groundwater seeoage into tunnels.

Influence Factors Analysis to Chlorophyll a of Spring Algal Bloom in Xiangxi Bay of Three Gorges Reservoir

To study the relationship between environmental variables and chlorophyll a of spring algal bloom in Xiangxi Bay of Three Gorges Reservoir, stepwise multiple binomial regression and grey relative analysis methods were adopted. In surveys, 13 stations have been investigated and 143 samples were collected weekly from March 4 to May 13 in 2007. The study shows environmental variables (turbidity, total nitrogen, dissolved oxygen, total phosphates and silicate) are key factors during algal bloom. The grey relative values and their permutation indicated that turbidity was the most important factor and had comprehensive effect on chlorophyll a. The more number of interactive variables is found to be an indication of biochemical activity during spring algal bloom in Xiangxi Bay such as DO×TN, Turb×TP and so on. There was good linear relationship between chlorophyll a and the interaction of DO with TN ( , ).The interac-tion of nutrients (TP×TN, TP×SiO4, TN×SiO4) had significant influence to chlorophyll a and probably determined the inter-specific competition at different nutrient concentrations.

Cancer Gene Extraction Based on Stepwise Regression

With the expansion of the gene expression profile database,in the case of as little as possible to lose information or to retain the most critical information,gene extraction has become a main direction for the scholars.This paper excludes 1561 irrelevant genes through the definition of weighted distance firstly,and then removes 252 redundant genes by Pearson's correlation coefficient.Finally by comparing the two methods,stepwise regression after clustering and only stepwise analysis,we obtain the best combination of 8 genes.

Analysis of the Nucleoside Content of Cordyceps sinensis Using the Stepwise Gradient Elution Technique of Thin-Layer Chromatography

Nucleoside is the main class of active components in Cordyceps sinensis. Thin-layer chromatography (TLC) is one of the most commonly used methods in pharmacopoeias for analyzing chemical components of herbal medicine. Since the isocratic elution method cannot be applied successfully in TLC analysis for separating all the nucleoside components, the stepwise gradient elution has been developed in this work to separate eight nucleoside standards with success. In this way, quantitative analyses of the samples of Cordyceps sinensis were achieved via the pro-posed TLC procedure coupled with the scanning densitometric techniques of CAMAG and TLCQA methods for qualitative and quantitative analysis.

减氮对华北地区麦玉轮作农田土壤N2O排放调控机理

【目的】探究减氮对华北地区麦玉轮作农田土壤N2O排放调控机制。【方法】冬小麦季和夏玉米季均以不施氮为对照(CK),设置2个施氮量,分别为常规施氮量(纯氮300 kg/hm2,N2)、减氮20%(纯氮240 kg/hm2,N1),研究施氮量对麦玉轮作农田土壤性质及N2O排放通量影响,基于逐步回归分析,研究减氮对麦玉轮作农田土壤N2O排放调控机制。【结果】(1)减氮有效降低了N2O排放通量,且夏玉米季N2O排放通量远高于冬小麦季,夏玉米季由施肥引起的N2O排放量较高。(2)冬小麦季N2O排放通量与环境因子逐步回归公式为:N2O排放通量=181.952+1.450×硝态氮+8.401×铵态氮-0.514×电导率;硝态氮、铵态氮会对冬小麦季N2O排放通量产生显著的正向影响,而电导率会对冬小麦季N2O排放通量产生显著的负向影响。(3)夏玉米季N2O排放通量与环境因子逐步回归公式为:N2O排放通量=-354.606+4.592×硝态氮+157.848×铵态氮;硝态氮、铵态氮会对夏玉米季N2O排放通量产生显著的正向影响。【结论】综上可知,适量减氮显著降低夏玉米季N2O累积排放量和增温潜势,应加强夏玉米季农田水肥管理。

石家庄暴雨时空分布特征及灾情评估

基于石家庄市2015—2021年暴雨洪涝灾情资料数据,以及17个国家站及268个区域自动气象站数据,采用气候统计诊断方法分析了石家庄暴雨时空分布的气候特征,并利用灰色关联分析及逐步回归方法,建立了石家庄市暴雨灾情评估及预评估模型.结果表明:①石家庄暴雨频次及强度随时间呈递增趋势,暴雨强度年际变化增大且极端性增强.②石家庄西北部暴雨频次多、强度大,西南部暴雨频次相对较少,但强度最大,其中平山、井陉为大暴雨、特大暴雨高发区,复杂的地理环境使该地区发生暴雨洪涝灾害的风险增加.③由灰色关联分析方法确定的暴雨灾情等级正确率83.33%,能够反映实际暴雨灾情等级,且有利于客观区分同一等级内暴雨灾情大小.④基于气象因子,利用逐步回归方法建立的暴雨灾情评估及预评估模型正确率可达68.75%.

RMAPS模式预报总辐射的3种订正方法应用

为降低光伏功率预测中预报总辐射误差且探讨各类订正方法的适用性,分季节对比分析逐步回归、支持向量机(SVM)和相似误差订正(AnBC)方法对快速更新多尺度分析和预报系统短期预报总辐射的订正效果.结果表明,订正后明显降低了预报误差,一定程度上改善了预报总辐射分布较分散和偏大的情况.酒泉鸿坤光伏电站秋季逐步回归订正效果相对最佳(平均绝对偏差(M_(AE))降低4.56 W/m^(2)),冬季、夏季和春季均是AnBC效果相对最佳(M_(AE)依次降低10.33、12.71、44.27 W/m^(2));敦煌电建汇能光伏电站秋季和冬季均是SVM订正效果相对最佳(M_(AE)分别降低4.73和7.85 W/m^(2)),夏季和春季均是AnBC效果相对最佳(M_(AE)分别降低16.24和34.17 W/m^(2)).两座电站逐小时误差分布显示AnBC效果相对最佳;就各季节相对最佳订正方法而言,订正后春季提高时次百分比最高(酒泉鸿坤为73.88%,电建汇能为77.28%).晴天SVM订正效果最明显,非晴天AnBC效果最明显.

原油集输系统能耗影响因素的综合判定模型

随着油田生产能源需求的不断增长,原油集输系统在能源供应链中所起的作用日渐显著,其能耗所占比重在整体油田生产中也日益增加,而系统能耗又受到多种因素的制约,如何科学合理地分析集输系统能耗影响因素成为油田面临的重要课题。同时,部分因素之间还会存在交叉影响而造成信息重叠,这给准确把握系统能耗主要影响因素带来较大难度。结合集输系统能耗构成特点和生产实际运行状况,综合考虑产液量、含水率、油品黏度等影响集输系统能耗的客观因素,采用改进熵权法、主成分分析法以及多元逐步回归分析法对各项因素的影响程度进行定量描述,根据权重大小进行排序,并将3种方法结合进行综合判定,确定含水率和产液量为影响油田集输系统能耗的主要影响因素,最后针对主要因素变量对系统的相关制约原因进一步深入探究,并提出系统具体降耗措施,以期为原油集输系统节能提效提供理论参考。

呼吸系统感染患者住院费用灰色关联及影响因素分析

目的:分析呼吸系统感染患者住院费用的构成及内、外部影响因素,为公立医院实施DRG付费改革、控制医疗费用、提高医疗服务质量提供参考。方法:收集2021年江苏省某三甲医院呼吸内科呼吸系统感染住院患者579例,提取患者病案基本信息和各项住院费用明细,采用单因素分析、灰色关联分析、多元逐步线性回归分析对呼吸系统感染患者住院费用的内、外部影响因素进行分析。结果:与呼吸系统感染患者住院费用关联度最高,关联序列排前三位的费用:西药费(0.979)、一般医疗服务费(0.969)和实验室诊断费(0.938)。住院天数、年龄、合并症数量和吸烟史对呼吸系统感染患者的住院费用有显著影响。结论:建议定期审查医院各项费用和成本效益,完善临床诊疗规范,进一步加强控制西药费用,减少不必要的医疗服务和实验室检查;同时尝试建立早期出院计划以减少住院天数,积极做好健康宣传,提高民众健康素养。

武都地区初榨橄榄油酚类和脂肪酸组成对油脂氧化稳定性研究

对武都地区的白橄榄(U)、恩帕特雷(E)、奇迹(K)、阿斯(As)、中山24(Z)、云台14(Y)、皮瓜尔(P)、豆果(Arbe)、小苹果(M)、鄂植8(Ez)、阿尔伯萨拉(Arbo)、科拉蒂(C)、莱星(L)、佛奥(F)这14个品种初榨橄榄油的脂肪酸、酚类成分及油脂氧化稳定性进行检测和分析,单因素方差分析表明:品种间多酚和脂肪酸含量及油脂氧化稳定性存在显著性差异(p<0.05)。所有分析样品的脂肪酸组成均符合欧盟特级初榨橄榄油标准,初榨橄榄油中油酸质量分数在(56.12±0.24)%(豆果)和(71.45±0.42)%(科拉蒂)之间,亚油酸质量分数在(5.73±0.06)%(皮瓜尔)和(15.80±0.05)%(阿斯)之间,棕榈酸质量分数在(12.67±0.12)%(科拉蒂)和(18.76±0.04)%(豆果)之间。裂环烯醚萜类是主要的酚类成分,总酚质量分数最高为奇迹,为(471.35±29.34)mg/kg,最低为豆果,仅(165.65±8.08)mg/kg。主成分分析表明:富含橄榄苦苷苷元、女贞子苷元、橄榄裂环烯醚萜、油酸、芹菜素的品种氧化稳定性越高,而富含棕榈酸、亚油酸、酪醇、羟基酪醇、刺激醛的品种氧化稳定性越低。基于芹菜素、橄榄裂环烯醚萜、木犀草素和亚油酸建立的多元线性逐步回归模型可以预测90.70%的油脂氧化稳定性变化(p<0.001)。