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.

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.

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.

Investigations on the relationship among the porosity,permeability and pore throat size of transition zone samples in carbonate reservoirs using multiple regression analysis,artificial neural network and adaptive neuro-fuzzy interface system

Finding an accurate method for estimating permeability aside from well logs has been a difficult task for many years.The most commonly used methods targeted towards regression technique to understand the correlation between pore throat radii,porosity and permeability are Winland and Pittman equation approaches.While these methods are very common among petrophysicists,they do not give a good prediction in certain cases.Consequently,this paper investigates the relationship among porosity,permeability,and pore throat radii using three methods such as multiple regression analysis,artificial neural network(ANN),and adaptive neuro-fuzzy inference system(ANFIS)for application in transition zone permeability modeling.Firstly,a comprehensive mercury injection capillary pressure(MICP)test was conducted using 228 transition zone carbonate core samples from a field located in the Middle-East region.Multiple regression analysis was later performed to estimate the permeability using pore throat and porosity measurement.For the ANN,a two-layer feed-forward neural network with sigmoid hidden neurons and a linear output neuron was used.The technique involves training,validation,and testing of input/output data.However,for the ANFIS method,a hybrid optimization consisting of least-square and backpropagation gradient descent methods with a subtractive clustering technique was used.The ANFIS combines both the artificial neural network and fuzzy logic inference system(FIS)for the training,validation,and testing of input/output data.The results show that the best correlation for the multiple regression technique is achieved for pore throat radii with 35%mercury saturation(R35).However,for both the ANN and ANFIS techniques,pore throat radii with 55%mercury saturation(R55)gives the best result.Both the ANN and ANFIS are later found to be more effective and efficient and thus recommended as compared with the multiple regression technique commonly used in the industry.

Predicting urbanization level by main element analysis and multiple linear regression---taking Xiantao district in Hubei Province as an example

In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and lastly predict its urbanization level

Suggestion of advanced regression model on friction angle of fault gouge in South Korea

Although friction characteristics of fault gouge are important to understand reactivation of fault,behavior of earthquake,and mechanism of slope failure,analysis results of fault gouge have low accuracy mostly than those of soils or rocks due to its high heterogeneity and low strength.Therefore,to improve the accuracy of analysis results,we conducted simple regression analysis and structural equation model analysis and selected major influential factors of friction characteristics among many factors,and then we deduced advanced regression model with the highest coefficient of determination(R^(2)) via multiple regression analysis.Whereas most coefficients of determination in simple regression analysis are below0.3-0.4,coefficient of determination in multiple regression analysis is remarkably large as 0.657.

An empirical analysis on community residents' perception and major influencing factors of rural tourism development

With the rapid development of rural tourism in China,community residents,as important stakeholders in the development of rural tourism,their perceptions and attitudes directly affect the sustainable and healthy development of local rural tourism.Taking the community residents of Xiaogucheng Village in Hangzhou as the research object,using the methods of field interviews and questionnaires,a multiple regression model was established to conduct an empirical analysis on the perception and main factors affecting the development of rural tourism of community residents.The results show that the development of rural tourism in villages with better economic development is not as popular as expected;Where community residents have made ideological progress and are willing to participate in tourism development,the development effect of rural tourism is remarkable;In addition,community residents also hope that their personal abilities can be combined with rural tourism for common development;The destruction of community environment has a slight impact on the development of rural tourism,which shows that the attention is not enough.Finally,based on the analysis conclusion,it provides new ideas and inspiration for the sustainable development of rural tourism:improving the community residents’participation in rural tourism system,establishing the guidance mechanism of community residents’tourism vocational education,and consolidating the achievements of community ecological environment management.

Education Investment Fixed Asset Investment and Regional Economic Development Differences--Empirical analysis based on Chinese

In this article,it discusses the di£ferences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment.Based on the provincial data of 31 provinces from 1999 to 2017 released by National Bureau of Statistics,it expends the Cobb-Douglas model and Lucas model,and analyses the data with multiple linear regression models.From the study,it finds that compared with investment in fixed assets,investment in education has a larger role in promoting economic development,which is more obvious in the underdeveloped central and western regions and rural areas.However,at the same time it needs to note that the positive effects of education investment will be restricted by the economic structure and policy environment,and education expenditure policies should also be implemented in accordance with time and local conditions.

中国8省市50岁及以上人群卫生保健服务满意度与生活质量的关联研究

目的探讨50岁及以上人群卫生保健服务满意度和生活质量之间的关系。方法利用世界卫生组织(World Health Organization,WHO)全球老龄化与成人健康研究中国项目基线调查资料,选取我国8个省/直辖市15050名50岁及以上的中老年人,使用全球老龄化与成人健康研究问卷和WHO生活质量量表8项简化版评估卫生保健服务满意度和生活质量,并获取社会人口学及慢性病患病情况等信息,使用多元线性回归模型分析两者之间的关系并按居住地、性别和年龄组进行分层分析。结果研究共纳入研究对象13408人,平均年龄为(63.86±10.24)岁,对本市(区)提供的卫生保健服务感到非常满意的占4.16%,感到满意的占58.90%,感到一般的占30.81%,感到不满意的占5.69%,感到非常不满意的占0.44%。研究对象生活质量得分为(40.25±15.56)分,多元线性回归分析显示研究对象的卫生保健服务满意度越高,生活质量越好(P<0.001)。在分层分析中,该关联在不同居住地区、不同性别以及不同年龄组中均有统计学意义(P<0.001)。结论50岁及以上的人群中,较高的卫生保健服务满意度和较高的生活质量相关。

Experimental Study on Anchoring Physical Properties of Different Anchoring Lengths Coupled with Temperature and Pressure

Aiming at deep roadway anchorage solids, laboratory similar model tests were used to reveal the mechanical properties of anchorage solids with different anchorage lengths under the coupling effect of temperature and pressure, and SPSS statistical analysis software was used to conduct linear regression analysis of the ultimate anchorage force obtained from the tests. The results show that: through multiple linear regression analysis, the influence degree of temperature and pressure coupling on the ultimate anchorage force is arranged in order of anchoring length > surrounding rock strength > temperature > side pressure coefficient, and the linear regression equation of the model is obtained. Compared with the linear regression equation of simulation results, the model has a high explanatory ability.

Climatic envelope of evergreen sclerophyllous oaks and their present distribution in the eastern Himalaya and Hengduan Mountains

Evergreen sclerophyllous oaks （the E.S. oaks, Quercus section Heterobalanus） are the dominant species of the local ecosystem in the eastern Himalaya and the Hengduan Mountains, southwest China. In this study, we document the climatic envelope of the seven E.S. oak species and examine the relationships between climate and their distribution. This was done using a principal components analysis （PCA） and multiple regression analysis （MRA） of nine climatic indices. The main climatic envelope of the E.S. oaks were： mean temperature of the warmest month （MTW）= 12.0-19.5℃, warmth index （WI） = 33.2-88.9℃ month, annual biotemperature （BT）=-6.9- -0.3 ℃, coldness index （CI）=-30.4- -10.1 ℃ month, mean temperature of the coldest month （MTC）=-3.7-3.0℃ and annual precipitation （AP）=701-897 mm at the lower limits; and MTW=8.3-16.1℃, WI=15.7-59.1℃ month, BT=3.6-8.9℃, CI=-55.4-19.3℃ month, MTC=8.3-16.1 ℃ and AP=610-811 mm at the upper limits. The climatic range of the E.S. oaks is wide and includes two climatic zones, the cool-temperature zone and the subpolar zone. The PCA and MRA results suggest that the thermal climate plays a major role and precipitation plays a secondary role in controlling the large-scale distribution of the E.S. oaks, except Quercus monimotricha. In thermal regimes, BT and/or MTW are most important for both lower and upper limits of the E.S. oaks. Furthermore, our results indicate that the upper distribution limits of the E.S. oaks are less determined by low temperatures and their duration （CI） than by other factors.

Family empowerment and quality of life of parents raising children with Developmental Disabilities in 78 Japanese families

Objectives: The families of these children experience distress both at the time of diagnosis and afterward.A top priority is to understand family empowerment,family function,and family members' quality of life (QoL) and to effectively support these families in Japan.The objective of this study was to assess the actual conditions of families living with children having DDs and to explore the factors associated with family empowerment and parents' QoL.Methods: We surveyed ninety-three parents (78 mothers,15 fathers) from 78 families which lived with children with DDs in the capital region of Japan.We assessed two main outcomes using the Japanese versions of the following instruments: Family Empowerment Scale (FES),World Health Organization Quality of Life 26 (WHOQOL26),and other six outcomes.Correlation and multiple regression analyses were conducted.Results: No medication,cooperation with child rearing,assistance from a developmental support center,solved problems related to child rearing,and higher scores in Problem Solving contributed to higher FES scores.Higher WHOQOL26 scores were related to being a full-time housewife,higher self-esteem,no developmental support,a broad emotional support network,higher scores in Problem Solving and Role Function,and lower scores in Affective Reaction and General Function.Conclusions: We revealed that family empowerment and QoL of parents rearing children with DDs in Japan were affected by various subscales of family function and other family attributes.Effective interventions for improving family empowerment and QoL should be researched in the future.

Shear Flow Dispersion Under Wave and Current

The longitudinal dispersion of solute in open channel flow with short period progressive waves is investigated. The waves induce second order drift velocity in the direction of propagation and enhance the mixing process in concurrent direction. The 1-D wave-period-averaged dispersion equation is derived and an expression for the wave-current induced longitudinal dispersion coefficient （WCLDC） is propased based on Fiscber＇ s expression （1979） for dispersion in unidirectional flow. The result shows that the effect of waves on dispersion is mainly due to the cross-sectional variation of the drift velocity. Furthermore, to obtain a more practical expression of the WCLDC, the longitudinal dispersion coefficient due to Seo and Cheong （1998） is modified to incluee the effect of drift velocity. Laboratory experiments have been conducted to verify the propased expression. The experimental results, together with dimensional analysis, show that tbe wave effect can be reflected by the ratio between the wave amplitude and wave period. A comparative study between the cases with and without waves demonstrates that the magnitude of the longitudinal dispersion coefficient is increased nnder the presence of waves.

Carbon stock and sink economic values of forest ecosystem in the forest industry region of Heilongjiang Province, China

The values of forest carbon stock (CSV) and carbon sink (COV) are important topics in the global carbon cycle. We quantitatively analyzed the factors affecting changes in both for forest ecosystem in 2000−2015. With multiple linear stepwise regression analysis, we obtained the factors that had a significant impact on changes of CSV and COV, and then the impacts of these variables on CSV and COV were used for further quantitative analysis using the vector autoregressive model. Our results indicated that both stand age and afforestation area positively affect CSV and COV;however, the forest enterprise gross output value negatively affects CSV. Stand age has the largest long-term cumulative impact on CSV and COV, reaching 40.4% and 9.8%, respectively. The impact of enterprise gross output value and afforestation area on CSV and COV is the smallest, reaching 4.0% and 0.3%, respectively.

Contributing Factors for Delays during the Morning Commute Hours and the Impact of the Spread of COVID-19 for Metropolitan Train Lines in Japan

The present study aims to conduct 2 types of statistical analysis to reveal the impact of the spread of COVID-19 on train delays by comparing the potential contributing factors before, during and after the outbreak of the virus in the metropolitan train lines in Japan. First of all, the result of the present study clearly revealed the changes in contributing factors for train delays caused by the spread of COVID-19. Specifically, the contributing factors for train delays changed due to the decrease of passengers by the effect of the outbreak of the virus. Additionally, though large terminal stations were considered to be a major contributing factor in causing and increasing train delays in the past, this was not the case after the spread of COVID-19. Therefore, under such conditions, it is more effective to make improvements in small to medium stations and tracks rather than terminal stations. Furthermore, as the decrease in passengers also decreased train delays in commuter lines going to the suburbs due to the spread of COVID-19, the contributing factor for such lines is the excessive number of passengers. Therefore, as for countermeasures for train delays after the effects of COVID-19, it is necessary to disperse passengers in order to avoid passengers concentrating in the same time zones and train lines.

Function of Palm Fiber in Stabilization of Alluvial Clayey Soil in Yangtze River Estuary

Palm fiber is one of the favorable materials used in stabilization of soft soil in geotechnical engineering projects in recent years due to its nature of sustainability,no harm to the environment,biodegradability,availability and costeffectiveness in the context of widespread appeal from the world for returning to nature and protecting the earth our homestead.This paper is aimed at exploring the mechanical performance of Shanghai clayey soil reinforced with palm fiber.The unconfined compressive tests are carried out on samples treated with palm fibers of different lengths and contents,and the unconfined compressive strength(UCS),ductility rate(DR),secant modulus(SM),energy absorption capacity(EAC)and failure pattern(FP)of the reinforced and unreinforced samples have been analyzed with regard to their relationship with palm fiber contents and lengths.Then multiple regression,grey correlation and general correlation relationship analysis are applied to the resultant test data so as to obtain the mathematical and statistical equation of related soil indexes.It has been concluded from the analysis that the unconfined compressive strength,ductility and energy absorption capacity of reinforced soil will increase with the increase in content and length of palm fiber,which are maximized when palm fiber content and length are 0.4%and 15 mm,respectively.On the contrary,the secant modulus of reinforced soil decreases considerably with content and length of palm fiber as a whole.Additionally,the failure pattern also changes from brittle to ductile gradually with the content and length of palm fiber.The data provided by the analysis of reinforced soil can be referred to and used for the related geotechnical engineering in the future.And the mathematical model obtained from the statistical regression is significantly meaningful because it can be used to predict the soil performance without the need for doing the additional tests,with saving in cost and time.What’s more,the application of palm fiber to soft soil is completely in accordance to the concept of sustainable development and environment protection.

Laboratory study and predictive modeling for thaw subsidence in deep permafrost

Oil wells on the North Slope of Alaska pass through deep deposits of permafrost. The heat transferred during their operation causes localized thawing, resulting in ground subsidence adjacent to the well casings. This subsidence has a damaging effect, causing the casings to compress, deform, and potentially fail. This paper presents the results of a laboratory study of the thaw consolidation strain of deep permafrost and its predictive modeling. Tests were performed to determine strains due to thaw and post-thaw loading, as well as soil index properties. Results, together with data from an earlier testing program, were used to produce empirical models for predicting strains and ground subsidence. Four distinct strain cases were analyzed with three models by multiple regression analyses, and the best-fitting model was selected for each case. Models were further compared in a ground subsidence prediction using a shared subsurface profile. Laboratory results indicate that strains due to thaw and post-thaw testing in deep core permafrost are insensitive to depth and are more strongly influenced by stress redistributions and the presence of ice lenses and inclusions. Modeling results show that the most statistically valid and useful models were those constructed using moisture content, porosity, and degree of saturation. The applicability of these models was validated by comparison with results from Finite Element modeling.

Effects of Tidal Channels and Roads on Landscape Dynamic Distribution in the Yellow River Delta, China

Landscape characters in estuarine regions generally controlled by tidal regimes and human activities like road construction.In this work,tidal channels and road construction in the Yellow River Delta(YRD)were extracted by visual interpretation methods so as to decipher impacts of tidal channel development and road construction on landscape patch change during 1989–2016.Spatial distribution history of three wetlands,which covered by Phragmites australis(freshwater marsh,FM),Suaeda salsa(salt marsh,SM),and mudflats(MD)were also established.Results indicated that tidal channel,number,frequency,and fractal dimension were all the maximum in 2003,and the minimum in 1998,respectively.Road length,number,and density showed increasing trend during 1989–2016.MD were the predominant landscape type,followed by FM and SM during 1989-2016.Principal component analysis implied two extracted factors,F1 and F2,which could represent 91.93% of the total variations.F1 mainly proxied tidal channel development,while F2 represented road construction.A multiple linear regression analysis showed positive effects of both F1 and F2 on FM patch numbers and negative impacts on SM patch areaes with R^2 values of 0.416 and 0.599,respectively.Tidal channels were negatively related to MD patch numbers,while roads were positively related to that.In any case,road construction showed larger impacts on landscape type shifting than that of tidal channel development in the YRD.

Rapid Non-destructive Detection for Molds Colony of Paddy Rice Based on Near Infrared Spectroscopy

Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.

Spatiotemporal Characteristics of Wetlands Ecosystem in the Niger Delta Region

Wetlands are classified as essential and valuable components of the ecosystem. Wetlands are significant for ecosystem services such as nutrient cycles, soil formation and water treatment. Nearly half of the world’s wetlands have vanished in the last century because of anthropogenic activities, agricultural land use, and urban development, one of such places that are faced with the challenges of sustainability is the wetland habitats. This study aimed at assessing the spatial temporal characteristics of wetlands ecosystem in the Niger Delta Region of Nigeria from 1986-2016. The secondary data include raw satellite imageries obtained from the archive of the United States Geological Survey and Earth Explorer. The data set includes a notable period of four years landsat images for, 1986, 1996, 2006 and 2016. The maps were projected using Universal Transverse Mercator (UTM) projection system and datum WGS 84 of zone 32. Satellite images of the study area were acquired from the United States Geological Survey (USGS). The USGS uses the LandSat5 Thematic Mapper (TM) Landsat7 Thematic Mapper, Enhanced Thematic Mapper (ETM+), Thermal Infrared Sensor (TIRS) and Landsa8 Operational Land Imager (OLI) to generate high resolution images that are useful for this type of study. The satellite imageries were also analyzed using GIS and Remote Sensing techniques by computing of Normalized Differential Vegetation Index (NDVI) values for the entire study area by conversion of spectral reflectance values into NDVI values. The satellite images covering the area were acquired and analyzed using ArcGIS10.6. A total area of 25,053.93 (km2) was delineated in the study area. After processing the imagery, five land use/land cover (LULC) classes were developed in ArcGIS environment, such as Built-up area, Fallow land, Vegetation, Wetland and Waterbody. This study concludes that changes in wetland landscape patterns will produce profound impacts in urban areas where there are rapid anthropogenic activities. Anova table showed a huge significant relationship between time and vegetation decrease across the study area at 0.027 which is less than 0.05 significance level. Wetlands warming and drying will cause the shrinking and reduction of wetland in sizes from accelerated wetland degradation. Therefore, there is an interaction and mutual influence between dynamic changes of wetland landscape patterns and other land use classes.