国际大通道沿线云南城市经济势能测算研究

依据现代城市发展规律,基于城市圈域经济理论和方法,运用因子分析和多元线性回归等多种方法,对国际大通道沿线云南城市经济势能进行测算,为云南省委、省政府规划大通道建设与城市经济发展的战略决策提供参考,并为城市圈域经济理论进一步由定性分析朝定量分析作有益的探索。

Comprehensive evaluation of water-inrush risk from coal floors

Lower groups of coal seams are presently being mined from water-inrush from coal floors in order to have safe production in the Yanzhou coal mining area. We need to evaluate the risk in the lower groups of coal seams in mines. Based on a systematic collection of hydrogeological data and some data from mined working faces in these lower groups, we evaluated the factors affecting water-inrush from coal floors of the area by a method of dimensionless analysis. We obtained the order of the factors affecting water-inrush from coal floors and recalculated data on depths of destroyed floors by multiple linear regression analysis and obtained new empirical formulas. We also analyzed the water-inrush coefficient of mined working faces of the lower groups of coal seams and improved the evaluation standard of the water-inrush coefficient method. Finally, we made a comprehensive evaluation of water-inrush risks from coal floors by using the water-inrush coefficient method and a fuzzy clustering method. The evaluation results provide a solid foundation for preventing and controlling the damage caused by water of an Ordovician limestone aquifer in the lower group of coal seams in the mines of Yanzhou. It provides also important guidelines for lower groups of coal seams in other coal mines.

Comparison of very-high-frequency ultrasound assessment of radial arterial wall layers after first and repeated transradial coronary procedures

Background Transradial coronary procedure （TRP） traumatizes the radial artery （RA）, especially resulting in changes to arterial wall morphology. This study explored the significance of the early onset of traumatic effects to wall layers of the RA following the first TRP （FTRP） and repeat TRP （RTRP） using very-high-frequency ultrabiomicroscopy （VHFUBM）. Methods A total of 1431 patients that re- ceived TRP were divided into the FTRP group that comprised 781 patients and the RTRP group that comprised 650 patients depending on the number of procedures. Two-dimensional RA images were acquired by 30-55 MHz ultrasound one day before and one day after the pro- cedure. Results After TRP, the incidence of intimal tears, medial dissections and external elastic lamina fracture were greater in the RTRP （P 〈 0.001）. The RTRP group showed significantly thicker intimal thickness （IT）, media thickness （MT）, adventitia thickness and all complex layer thicknesses as compared with the FTRP group （P 〈 0.001）. Conclusions Multivariate linear regression analysis discovered that repeated TRP and other observations were independent predictors of increased IT in post-operative RA. VHFUBM provides an approach to study structural and histopathological injury in the wall layers of RA which showed increased trauma to the RA following RTRP.

Synthesis,algal inhibition activities and QSAR studies of novel gramine compounds containing ester functional groups

2,5,6-Tribromo-l-methylgramine （TBG）, isolated from bryozoan Zoobotryon pellucidum was shown to be very efficient in preventing recruitment of larval settlement. In order to improve the compatibility of TBG and its analogues with other ingredients in antifouling paints, structural modification of TBG was focused mainly on halogen substitution and N-substitution. Two halogen-substitute gramines and their derivatives which contain ester functional groups at N-position of gramines were synthesized. Algal inhibition activities of the synthesized compounds against algae Nitzschia cIosterium were evaluated and the Median Effective Concentration （EC50） range was 1.06-6.74 lag ml^-1. Compounds that had a long chain ester group exhibited extremely high antifouling activity. Quantitive Structure Activity Relationship （QSAR） studies with multiple linear regression analysis were applied to fred correlation between different calculated molecular descriptors and biological activity of the synthesized compounds. The results show that the toxicity （log （I/EC50）） is correlated well with the partition coefficient log P. Thus, these products have potential function as antifouling agents.

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.

Relationships between Soil Depth and Terrain Attributes in a Semi Arid Hilly Region in Western Iran

Soil depth generally varies in mountainous regions in rather complex ways.Conventional soil survey methods for evaluating the soil depth in mountainous and hilly regions require a lot of time,effort and consequently relatively large budget to perform.This study was conducted to explore the relationships between soil depth and topographic attributes in a hilly region in western Iran.For this,one hundred sampling points were selected using randomly stratified methodology,and considering all geomorphic surfaces including summit,shoulder,backslope,footslope and toeslope;and soil depth was actually measured.Eleven primary and secondary topographic attributes were derived from the digital elevation model(DEM) at the study area.The result of multiple linear regression indicated that slope,wetness index,catchment area and sediment transport index,which were included in the model,could explain about 76 % of total variability in soil depth at the selected site.This proposed approach may be applicable to other hilly regions in the semi-arid areas at a larger scale.

Resistin might not be a risk factor for carotid artery atherosclerosis in elderly Chinese males

Objective To investigate the correlation between the serum resistin level and carotid artery atherosclerosis in elderly Chinese males. Methods The study enrolled 235 elderly Chinese males [median age 76 （range 60-97） years] scheduled for ultrasound examination of carotid artery plaque and determination of carotid artery intima-media thickness （CIMT）. They were divided into carotid atherosclerotic plaque （CAP） and carotid atherosclerotic plaque-free （CAP-free） groups according to the ultrasound results. Their clinical profiles were col-lected, and the serum resistin and other blood biochemistry levels were determined.Results The CAP group was older and had a thicker mean CIMT than the CAP-free group. However, there was no difference in the serum resistin level between the groups. CIMT was positively correlated with age （r = 0.299,P〈 0.001）. The serum resistin level was not correlated with CIMT, even after controlling for age. Multiple linear regression analysis revealed that age （β = 0.001,P〈 0.001） and body mass index （β = 0.002,P= 0.015） were significantly and posi-tively correlated with the mean CIMT. Only age [odds ratio （OR）： 1.159; 95% confidence interval （CI）： 1.078-1.183,P〈 0.001] was associ-ated with the presence of carotid artery atherosclerotic plaque. The serum resistin level was not correlated with the mean CIMT or associated with the presence of carotid artery atherosclerotic plaque.Conclusion The results suggest that resistin might not be a risk factor for atherosclerosis in elderly Chinese males.

Soft sensor design for hydrodesulfurization process using support vector regression based on WT and PCA

A novel method for developing a reliable data driven soft sensor to improve the prediction accuracy of sulfur content in hydrodesulfurization(HDS) process was proposed. Therefore, an integrated approach using support vector regression(SVR) based on wavelet transform(WT) and principal component analysis(PCA) was used. Experimental data from the HDS setup were employed to validate the proposed model. The results reveal that the integrated WT-PCA with SVR model was able to increase the prediction accuracy of SVR model. Implementation of the proposed model delivers the best satisfactory predicting performance(EAARE=0.058 and R2=0.97) in comparison with SVR. The obtained results indicate that the proposed model is more reliable and more precise than the multiple linear regression(MLR), SVR and PCA-SVR.

Structure-Activity Relationships in the Chelation Activity by Derivatives of 1,2-Dithiole-3-Thiones

The structure and electronic properties of a series of biologically active dithiolethiones （1） have been calculated using semi-empirical. Multi-linear regression analysis suggests that there is a reasonable correlation between the experimental activity of the derivatives against chelation activity and calculated properties such as the HOMO energies, molar refractivity, dipole moments and experimental partition coefficient. From the derived QSAR equations the 3-Methylthio-4p-Tolyle-1,2-Dithiolylium accompanying ion （CH3SO4） and 4-para-tolyl-1,2-dithiole-3-thione （2b and 2） are predicted to show the highest activity against chelation activity, while 3-Methylthio-5p-methoxy phenyl-1,2-Dithiolylium accompanying ion （I-） （3a） is predicted to be the least active in line with the experimental results.

Biomass estimation of Shorea robusta with principal component analysis of satellite data

Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.

Thermal performance of a single U-tube ground heat exchanger:A parametric study

In this research,the thermal performance of a single U-tube vertical ground heat exchanger is evaluated numerically as a function of the most influential flow parameters,namely,the soil porosity,volumetric heat capacity,and thermal conductivity of the backfill material,inlet volume flow rate,and inlet fluid temperature.The results are discussed in terms of the variations of the heat exchange rate,the effective thermal resistance,and the effectiveness of the ground heat exchanger.They show that the inlet volume flow rate,inlet fluid temperature,and backfill material thermal conductivity have significant effects on the thermal performance of the ground heat exchanger,such that by decreasing the inlet volume flow rate and increasing the backfill material thermal conductivity and inlet fluid temperature,the outlet fluid temperature decreases considerably.On the contrary,the soil porosity and backfill material volumetric heat capacity have negligible effects on the studied ground heat exchanger’s thermal performance.The lowest inlet fluid temperature reaches a the maximum effective thermal resistance of borehole and soil,and consequently the minimum heat transfer rate and effectiveness.Also,multilinear regression analyses are performed to determine the most feasible models able to predict the thermal properties of the single U-tube ground heat exchanger.

Shock Tube Measurement of Ethylene Ignition Delay Time and Molecular Collision Theory Analysis

In this study, 75% and 96% argon diluent conditions were selected to determine the ig- nition delay time of stoichiometric mixture of C2Ha/O2/Ar within a range of pressures （1.3-：3.0 arm） and temperatures （1092-1743 K）. Results showed a logarithmic linear rela- tionship of the ignition delay time with the reciprocal of temperatures. Under both two diluent conditions, ignition delay time decreased with increased temperature. By multiple linear regression analysis, the ignition delay correlation was deduced. According to this correlation, the calculated ignition delay time in 96% diluent was found to be nearly five times that in 75% diluent. To explain this discrepancy, the hard-sphere collision theory was adopted, and the collision numbers of ethylene to oxygen were calculated. The total collision numbers of ethylene to oxygen were 5.99×10^30 s^-1cm^-3 in 75% diluent and 1.53×10^29 s^-1cm^-3 in 96% diluent （about 40 times that in 75% diluent）. According to the discrepancy between ignition delay time and collision numbers, viz. 5 times corresponds to 40 times, the steric factor can

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

Evaluation of Self Management Behavior of Chronic Kidney Disease Patients

CKD （chronic kidney disease） is a progressive disease. If it is left untreated, it can eventually result in end stage renal failure and necessitate dialysis or kidney transplantation. There is no cure for CKD; instead a great deal of self management over time is essential. The purpose is to evaluate self management behaviour of patients at different stages of CKD. A total of 300 CKD patients were recruited in this cross sectional study from March to July 2015 at nephrology clinic of a tertiary care setting using convenience sampling. Self management behaviour score was determined using in Partners in Health scale and was then compared at different stages of CKD. Demographic and clinical factors contributing to self management behaviour were determined. Results： There was a significant difference in age （p 〈 0.001）, gender （p 〈 0.001）, education level （p 〈 0.001）, marital status （p 〈 0.001）, duration of illness （p 〈 0.001） and number of co-morbidities （p 〈 0.001） among CKD stages. A significant difference in self management behaviour mean score was found among CKD stages （p 〈 0.001）. Post hoc analysis showed self management behaviour mean score for Stage Ⅰ （mean ± SD： 77.81 ± 9.41） was significantly higher than Stage Ⅳ （mean ± SD： 70.53 ± 13.91） and Stage Ⅴ （mean ± SD： 69.54 ± 12.31）. Self management behaviour mean score for Stage Ⅱ （mean ± SD： 78.46 ± 10.01） was significantly higher than Stage Ⅳ and Stage Ⅴ. Multiple linear regression revealed education level （p 〈 0.001） and number of co-morbidities （p = 0.01） as significant predictors of self management behaviour. It can be concluded that special attention should be focused on patients at late stage of CKD, especially those with diabetic nephropathy; low education level and multiple co-morbidities to improve self management behaviour.

New Indoor Accelerated Weathering Condition for Approximating Molecular Weight Distribution of Outdoor-Exposed LDPE

LDPE （low-density polyethylene） photo degraded through various accelerated weathering tests has the molecular weight distribution curves unlike that through outdoor exposure. The authors therefore developed new weathering test condition based on the existing accelerated weathering test using a xenon arc lamp. Samples of LDPE were photo degraded using various accelerated weathering test conditions and outdoor exposure. The physical properties and chemical structures of the photo degraded samples were studied through a tensile test, infrared spectroscopy, and gel chromatography. The authors found that the molecular weight distribution curve of a sample photo degraded using a xenon lamp at a higher BPT （black panel temperature） （73 ~C） was more similar to that of an outdoor-exposed sample than that of a sample photo degraded at the standard BPT （63 ~C）. It is considered that higher temperature accelerates radical recombination, consequently recreating molecular enlargement similar to the outdoor-exposed sample. Multiple regression analysis using newly introduced Mp （peak-top molecular weight） and Mw （weight-average molecular weight） as explanatory variables was conducted, which successfully enabled the authors to provide a simple explanation for the decrease in polymer tensile strength.

Some Practical Issues Related to Univariate Regression Analysis Prior to Multivariate Regression Analysis in Randomized Controlled Clinical Trials

Often many variables have to be analyzed for their importance in terms of significant contribution and predictability in medical research. One of the possible analytical tools may be the Multiple Linear Regression Analysis. However, research papers usually report both univariate and multivariate regression analyses of the data. The biostatistician sometimes faces practical difficulties while selecting the independent variables for logical inclusion in the multivariate analysis. The selection criteria for inclusion of a variable in the multivariate regression is that the variable at the univariate level should have a regression coefficient with p 〈 0.20. However, there is a chance that an independent variable with p 〉 0.20 at univariate regression may become significant in the multivariate regression analysis and vice versa, provided the above criteria is not strictly adhered to. We undertook both univariate and multivariate linear regression analyses on data from two multi-centric clinical trials. We recommend that there is no need to restrict the p value of 〈= 0.20. Because of high speed computer and availability of statistical software, the desired results could be achieved by considering all relevant independent variables in multivariate regression analysis.

Study On the Influencing Factors of Energy-Saving and Environmental Protection Industries in Shanghai

By using principal component analysis, this paper selected some appropriate influencing indicators, and constructed multiple linear regression models to predict the development of energy-saving environmental protection industry（ESEPl） in Shanghai. The Influencing Factors can be categorized into comprehensive economic factors and environmental factors, and GDP of the second industries and the total industries GDP in comprehensive economic factors have the strongest correlation, while in the environmental index factors, the total discharge of waste water has the strongest correlation. On the basis of influencing factors study, the regression model shows that by the end of 2020, the industry investment will reach 89.788 billion RMB, which proves that the development of ESEPI in Shanghai would grow continuously and dramatically.

Do Satisfaction and Loyalty Have a Linear Relationship？ Effect of the Education Level on Arts Participation

This paper aims to explore the relationship between perceived satisfaction and loyalty of Spanish arts participants. Evidence suggests that customer satisfaction plays a key role in an organization＇s ability to maintain a relationship with its customers. We examined the link between satisfaction and loyalty within a theoretical framework based on an empirical study in which data from more than 14,000 respondents were obtained. This data allowed us to evaluate the arts consumer from an attitudinal and behavioral perspective looking at their interests, satisfaction level, frequency of attendance, and compare it using the participant＇s education level. A descriptive statistical analysis using ANOVA （analysis of variance）, correlation, partial correlation, and multiple regression provided evidence that, in the context of experiencing an arts show, satisfaction does not have any impact on loyalty but education level plays a significant role in people＇s interest and loyalty.

Source Apportionment of Heavy Metals in Soils Using Multivariate Statistics and Geostatistics

The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.

In-Situ Differentiation of Acidic and Non-Acidic Tundra via Portable X-ray Fluorescence (PXRF) Spectrometry

Frozen soils or those with permafrost cover large areas of the earth's surface and support unique vegetative ecosystems. Plants growing in such harsh conditions have adapted to small niches, which allow them to survive. In northern Alaska, USA, both moist acidic and non-acidic tundra occur, yet determination of frozen soil p Hs currently requires thawing of the soil so that electrometric pH methods can be utilized. Contrariwise, a portable X-ray fluorescence(PXRF) spectrometer was used in this study to assess elemental abundances and relate those characteristics to soil pH through predictive multiple linear regressions. Two operational modes, Soil Mode and Geochem Mode, were utilized to scan frozen soils in-situ and under laboratory conditions, respectively, after soil samples were dried and ground. Results showed that lab scanning produced optimal results with adjusted coefficient of determination(R^2) of 0.88 and 0.33 and root mean squared errors(RMSEs) of 0.87 and 0.34 between elemental data and lab-determined pH for Soil Mode and Geochem Mode, respectively. Even though the presence of ice attenuated fluoresced radiation under field conditions, adjusted R^2 and RMSEs between the datasets still provided reasonable model generalization(e.g., 0.73 and 0.49 for field Geochem Mode). Principal component analysis qualitatively separated multiple sampling sites based on elemental data provided by PXRF, reflecting differences in the chemical composition of the soils studied. Summarily, PXRF can be used for in-situ determination of soil pH in arctic environments without the need for sample modification and thawing. Furthermore, use of PXRF for determination of soil pH may provide higher sample throughput than traditional eletrometric-based methods, while generating elemental data useful for the prediction of multiple soil parameters.