Multiple regression analysis of risk factors related to radiation pneumonitis

BACKGROUND Radiation pneumonitis(RP)is a severe complication of thoracic radiotherapy that may lead to dyspnea and lung fibrosis,and negatively affects patients’quality of life.AIM To carry out multiple regression analysis on the influencing factors of radiation pneumonitis.METHODS Records of 234 patients receiving chest radiotherapy in Huzhou Central Hospital(Huzhou,Zhejiang Province,China)from January 2018 to February 2021,and the patients were divided into either a study group or a control group based on the presence of radiation pneumonitis or not.Among them,93 patients with radiation pneumonitis were included in the study group and 141 without radiation pneumonitis were included in the control group.General characteristics,and radiation and imaging examination data of the two groups were collected and compared.Due to the statistical significance observed,multiple regression analysis was performed on age,tumor type,chemotherapy history,forced vital capacity(FVC),forced expiratory volume in the first second(FEV1),carbon monoxide diffusion volume(DLCO),FEV1/FVC ratio,planned target area(PTV),mean lung dose(MLD),total number of radiation fields,percentage of lung tissue in total lung volume(vdose),probability of normal tissue complications(NTCP),and other factors.RESULTS The proportions of patients aged≥60 years and those with the diagnosis of lung cancer and a history of chemotherapy in the study group were higher than those in the control group(P<0.05);FEV1,DLCO,and FEV1/FVC ratio in the study group were lower than those in the control group(P<0.05),while PTV,MLD,total field number,vdose,and NTCP were higher than in the control group(P<0.05).Logistic regression analysis showed that age,lung cancer diagnosis,chemotherapy history,FEV1,FEV1/FVC ratio,PTV,MLD,total number of radiation fields,vdose,and NTCP were risk factors for radiation pneumonitis.CONCLUSION We have identified patient age,type of lung cancer,history of chemotherapy,lung function,and radiotherapy parameters as risk factors for radiation pneumonitis.Comprehensive evaluation and examination should be carried out before radiotherapy to effectively prevent radiation pneumonitis.

Usage as Complementary Correspondence Analysis and Logistic Regression in a Scientific Survey on Self Healing Methods

The aim of this study is to show complementary usage of logistic and correspondence analysis in a research subject to self-healing methodologies. Firstly, the number of the variables is reduced by logistic regression according to relationship between dependent and independent variables and then research carries on searching variables. The relationship among the behaviours of individuals and their demographic characteristics is modelled by logistic regression and shown graphically by correspondence analysis. In application, first of all, the effect of age, sex, marital status, education level, occupation and income level and present health condition, on appreciating self-health, is explained by a model. As a result of that model, it can be said that the effect of age, occupation and present health condition is reasonable. After analysing that model, the relationship between categorical variables (age, sex, occupation, preferred precautions, and worth of personal health) is shown graphically by multiple correspondence analysis.

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.

CFD Analysis and Optimization of Automobile Radiator based on STAR-CCM+

This research talks about the radiator cooling system of the automobile engine,the radiator’ s fluidstructure interaction dynamics based on computational fluid dynamics( CFD) STAR-CCM+ software. The linear regression model of coolant determined by MATLAB software was imported into the user-defined field function of the software,using the standard K-Epsilon turbulence model to analyze temperature,pressure and velocity changes of the coolant in the radiator channel. In order to improve the efficiency of the radiator,it is necessary to analyze the structure of two kinds of heat sinks,and get better heat transfer effect.

Stability of mine ventilation system based on multiple regression analysis

In order to overcome the disadvantages of diagonal connection structures that are complex and for which it is difficult to derive the discriminant of the airflow directions of airways, we have applied a multiple regression method to analyze the effect, of changing the rules of mine airflows, on the stability of a mine ventilation system. The amount of air （ Qj ） is determined for the major airway and an optimum regression equation was derived for Qi as a function of the independent variable （ Ri ）, i.e., the venti- lation resistance between different airways. Therefore, corresponding countermeasures are proposed according to the changes in airflows. The calculated results agree very well with our practical situation, indicating that multiple regression analysis is simple, quick and practical and is therefore an effective method to analyze the stability of mine ventilation systems.

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.

Logistics Regression Analysis between TCM Constitution Types of Patients with Hypertension,Insomnia and ABPM,PSQI

[Objectives]The research aimed to explore the distribution characteristics of TCM constitution types of patients with hypertension and insomnia,and study the clinical characteristics of patients with different constitutions,in order to provide new ideas for the treatment of patients with hypertension and insomnia.[Methods]Cross sectional observation method was used,and 420 patients with hypertension and insomnia were selected.Required information was collected,and the constitution type of traditional Chinese medicine was determined,and relevant data were recorded.SPSS and Logistic regression analysis method were used to explore the correlation between the distribution of TCM constitution types and gender,age,24 h-SBP,24 h-DBP,24 h-BPV,PSQI score,etc.[Results]Among 420 patients,the proportion of gentleness constitution was the most,and others in turn were Qi deficiency constitution>Yang deficiency constitution>phlegm dampness constitution>Qi stagnation constitution>Yin deficiency constitution>blood stasis constitution>damp heat constitution>special constitution.Among male patients,the proportion of gentleness constitution was the most.Among female patients,the proportion of Qi deficiency constitution was the most.In each constitution,the proportion of men and women was different,and the difference in gentleness constitution,Qi deficiency constitution and Yin deficiency constitution had statistical significance(P<0.05).The proportion of gentleness constitution for young and middle-aged patients was the most,while elderly patients with Qi deficiency constitution was the most.There was difference in the distribution of TCM constitution in different age groups,and the difference had statistical significance(P<0.05).Compared with the patients with gentleness constitution,the patients with Qi deficiency constitution,Yang deficiency constitution,Yin deficiency constitution,damp heat constitution,blood stasis constitution and Qi stagnation constitution had different differences in terms of age,24 h-SBP,24 h-DBP,24 h-BPV and PSQI score,and there was statistical significance(P<0.05).Except damp heat constitution,blood stasis constitution and special constitution,other constitutions had certain correlation with age,24 h-SBP,24 h-DBP,24 h-BPV and PSQI score.[Conclusions]TCM constitution types of patients with hypertension and insomnia were dominant by gentleness constitution,Qi deficiency constitution and Yang deficiency constitution.The distribution of TCM constitution in different gender and age groups was different,and different TCM constitution was related to ABPM and PSQI.

Prediction of cavity growth rate during underground coal gasification using multiple regression analysis

During underground coal gasification （UCG）, whereby coal is converted to syngas in situ, a cavity is formed in the coal seam. The cavity growth rate （CGR） or the moving rate of the gasification face is affected by controllable （operation pressure, gasification time, geometry of UCG panel） and uncontrollable （coal seam properties） factors. The CGR is usually predicted by mathematical models and laboratory experiments, which are time consuming, cumbersome and expensive. In this paper, a new simple model for CGR is developed using non-linear regression analysis, based on data from 1 l UCG field trials. The empirical model compares satisfactorily with Perkins model and can reliably predict CGR.

Research on the Effect of Artificial Intelligence Real Estate Forecasting Using Multiple Regression Analysis and Artificial Neural Network: A Case Study of Ghana

To transition from conventional to intelligent real estate, the real estate industry must enhance its embrace of disruptive technology. Even though the real estate auction market has grown in importance in the financial, economic, and investment sectors, few artificial intelligence-based research has tried to predict the auction values of real estate in the past. According to the objectives of this research, artificial intelligence and statistical methods will be used to create forecasting models for real estate auction prices. A multiple regression model and an artificial neural network are used in conjunction with one another to build the forecasting models. For the empirical study, the study utilizes data from Ghana apartment auctions from 2016 to 2020 to anticipate auction prices and evaluate the forecasting accuracy of the various models available at the time. Compared to the conventional Multiple Regression Analysis, using artificial intelligence systems for real estate appraisal is becoming a more viable option (MRA). The Artificial Neural network model exhibits the most outstanding performance, and efficient zonal segmentation based on the auction evaluation price enhances the model’s prediction accuracy even more. There is a statistically significant difference between the two models when it comes to forecasting the values of real estate auctions.

Using Linear Regression Analysis and Defense in Depth to Protect Networks during the Global Corona Pandemic

The purpose of this research was to determine whether the Linear Regression Analysis can be effectively applied to the prioritization of defense-in-depth security tools and procedures to reduce cyber threats during the Global Corona Virus Pandemic. The way this was determined or methods used in this study consisted of scanning 20 peer reviewed Cybersecurity Articles from prominent Cybersecurity Journals for a list of defense in depth measures (tools and procedures) and the threats that those measures were designed to reduce. The methods further involved using the Likert Scale Model to create an ordinal ranking of the measures and threats. The defense in depth tools and procedures were then compared to see whether the Likert scale and Linear Regression Analysis could be effectively applied to prioritize and combine the measures to reduce pandemic related cyber threats. The results of this research reject the H0 null hypothesis that Linear Regression Analysis does not affect the relationship between the prioritization and combining of defense in depth tools and procedures (independent variables) and pandemic related cyber threats (dependent variables).

Study on Fractional Separation and GC-MS Analysis of Flash Coal Tar Pyrolysed at Low Temperatures

The composition of low temperature pyrolysis coal tar has an effect on its further processing and reasomble utlization In this paper, the compeition or coal tars produced from both low temperature pyroysis in a fluidized bed aud flash pyrolysis with solid heat carrier have been investigated by the methch of fractional seperation and Gas Chromatography-Mass Spectrometry (GC-MS)- It is observed that the degree of coalification maceral and secondary reaction temperature (freeboard temperature in a fluidized bed) have some iufluence on the composition of coal tars- The main compoundes are phenol cresols,xylenols, naphthalene, alkylnaphthalenes, antbraceue, phenanthrene,acenaphthylene, fluoren, indene and so

COX MULTIVARIATE REGRESSION ANALYSIS OF RECURRENCE FACTORS FOR COLONIC CARCINOMA

Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma were investigated by univariate and Cox multivariate regression analyses. Ten factors contributed to the rate were analyzed. Results: Dukes stages, obstruction, postoperative chemotherapy as well as the growth manner of the tumor were significantly associated with the recurrence rate of colonic carcinoma (P<0.05) by univariate analysis, while Dukes stages, obstruction, and postoperative chemotherapy were significant factors by the multivariate analysis. Conclusion: Dukes stages, obstruction, and postoperative chemotherapy are independent prognostic factors in the recurrence of colonic carcinoma.

Multiple Regression Analysis of Influencing Factors on Yield of New Sugarcane Variety Yuetang 03-373

[Objectives]The purpose of this study was to provide reference for cultivation and promotion of a new sugarcane variety Yuetang 03-373,on the basis of analyzing and summarizing the characters of the variety.[Methods]Correlation,multiple regression and path analyses were performed for the yield and yield components of Yuetang 03-373.[Results]Correlation analysis shows that cane yield was significantly correlated with millable stalk number,stalk length and stalk diameter,and among them,the correlation with millable stalk number was the strongest.Multiple regression and path analyses show that millable stalk number contributed the most to cane yield,followed by stalk length,and stalk diameter contributed the least.The regression equation of cane yield against the three yield components was y=-2.8713+1.5497x1+5.8990x2-395.4294x3(R=0.9672**).[Conclusions]Millable stalk number and stalk length were the important and major factors for high yield of Yuetang 03-373,indicating that Yuetang 03-373 is a sugarcane variety of millable stalk type.In cultivation,full play should be given to the advantage of Yuetang 03-373 in millable stalk number,as well as stalk length(plant height),in order to achieve the purpose of increasing yield.

The Stochastic Regression Analysis as a Tool in Ecotoxicological QSAR Studies

Correspondence factor analysis(CFA)was used in conjunction with linear regression analysis to examine the structure-activity relationships of 50 benzene derivatives tested on Pimephales promelas.From nine molecular descriptors(numbers of C,H,O,N,Br,Cl,NO_2,OH,and NH_2 included in the molecules),CFA made it possible to define five new independent variables which were introduced in a stepwise regression analysis procedure to describe the acute toxicity(96-h LC_(50))of the aromatic compounds.The model log 1/C=-0.727F_1+1.248F_3+4.052(r=0.918; s=0.270)is more relevant to describe the ecotoxicological behavior of the studied compounds on the fathead minnow than that obtained with principal components(log 1/C=0.151 PC_1 -0.271 PC_2+4.124;r=0.737;s=0.460).The heuristic potency of this particular statistical analysis,which is called stochastic regression analysis,is discussed in detail.1989 Academic Press,Inc.

Logistic Regression Analysis of Influencing Factors on Serum ALT and HCV RNA Changes in Patients with Chronic Hepatitis C

Objective This study was undertaken to investigate the influencing factors on serum ALT level and hepatitis C virus(HCV)RNA titer in chronic hepatitis C(CHC)patients.Methods All patients enrolled into this study were anti-HCV positive.Retrospective tracing method was applied to detect serum ALT level and HCV RNA titer and to collect general information of the patients such as genders,age groups,interferon medication history,infection pathways,height and weight.Then the multi-factor analysis was adopted with the application of binominal logistic regression mode.Results The abnormal rate of ALT level was positively correlated to HCV RNA and gender while negatively correlated to interferon medication history and age group,with Wald value of the 4 factors as 39.604,11.823,18.991 and 7.389,respectively.The positive rate of HCV RNA was negatively correlated to interferon medication history and gender while positively correlated to ALT level,with corresponding Wald value of the 3 factors as81.394,7.618 and 27.562,respectively.Conclusions The normal ALT level in HCV infected patients was associated with viral load,age,gender and interferon medication history,while the normal rate of HCV RNA titer was closely associated with gender,interferon medication history and ALT level.

An Adaptive Design for Six Sigma(ADFSS): a Simulated Annealing and Regression Analysis Embedded Approach

Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into four major phases viz. identify, design, optimize, and validate （IDOV）. And an adaptive design for six sigma （ADFSS） incorporating the traits of artifidai intelligence and statistical techniques is presented. In the identify phase of the ADFSS, fuzzy relation measures between customer attributes （CAs） and engineering characteristics （ECs） as well as fuzzy correlation measures among ECs are determined with the aid of two fuzzy logic controllers （FLCs）. These two measures are then used to establish the cumulative impact factor for ECs. In the next phase （ i. e. design phase）, a transfer function is developed with the aid of robust multiple nonlinear regression analysis. Furthermore, 1this transfer function is optimized with the simulated annealing （ SA ） algorithm in the optimize phase. In the validate phase, t-test is conducted for the validation of the design resulted in earlier phase. Finally, a case study of a hypothetical writing instrument is simulated to test the efficacy of the proposed ADFSS.

DDM regression analysis of the in-situ stress field in a non-linear fault zone

A multivariable regression analysis of the in-situ stress field, which considers the non-linear deformation behavior of faults in practical projects, is presented based on a newly developed three-dimensional displacement discontinuity method （DDM） program. The Bar- ton-Bandis model and the Kulhaway model are adopted as the normal and the tangential deformation model of faults, respectively, where the Mohr-Coulomb failure criterion is satisfied. In practical projects, the values of the mechanical parameters of rock and faults are restricted in a bounded range for in-situ test, and the optimal mechanical parameters are obtained from this range by a loop. Comparing with the traditional finite element method （FEM）, the DDM regression results are more accurate.

Modified scaled distance regression analysis approach for prediction of blast-induced ground vibration in multi-hole blasting

The blast-induced ground vibration prediction using scaled distance regression analysis is one of the most popular methods employed by engineers for many decades. It uses the maximum charge per delay and distance of monitoring as the major factors for predicting the peak particle velocity(PPV). It is established that the PPV is caused by the maximum charge per delay which varies with the distance of monitoring and site geology. While conducting a production blasting, the waves induced by blasting of different holes interfere destructively with each other, which may result in higher PPV than the predicted value with scaled distance regression analysis. This phenomenon of interference/superimposition of waves is not considered while using scaled distance regression analysis. In this paper, an attempt has been made to compare the predicted values of blast-induced ground vibration using multi-hole trial blasting with single-hole blasting in an opencast coal mine under the same geological condition. Further,the modified prediction equation for the multi-hole trial blasting was obtained using single-hole regression analysis. The error between predicted and actual values of multi-hole blast-induced ground vibration was found to be reduced by 8.5%.

Isolated Area Load Forecasting using Linear Regression Analysis: Practical Approach

This paper presents an analysis to forecast the loads of an isolated area where the history of load is not available or the history may not represent the realistic demand of electricity. The analysis is done through linear regression and based on the identification of factors on which electrical load growth depends. To determine the identification factors, areas are selected whose histories of load growth rate known and the load growth deciding factors are similar to those of the isolated area. The proposed analysis is applied to an isolated area of Bangladesh, called Swandip where a past history of electrical load demand is not available and also there is no possibility of connecting the area with the main land grid system.

Approach for improving precision of regression analysis of single-replication fertilization experiments in rice

The field experiment designs with single replication were frequently used for factorial experiments in which the numbers of field plots were limited, but the experimental error was difficult to be estimated. To study a new statistical method for improving precision of regression analysis of such experiments in rice, 84 fertilizer experiments were conducted in 15 provinces of China, including Zhejiang, Jiangsu, Anhui, Hunan, Sichuan, Heilongjiang, etc. Three factors with 14 treatments (N: 0—225kg/ha, P: 0 —112. 5kg/ha, K: 0—150kg/ha) and two replications were employed using approaching optimun design. There were 2352 (84×14×2=2352) Yield deviations (d) between the individual treatment yields and its arithmetic mean. The results indicated that: