终末期肾病维持性血液透析患者透析时血压变异性的影响因素分析

目的探讨终末期肾病维持性血液透析患者透析时血压变异性(BPV)的影响因素。方法选取福建卫生职业技术学院附属省级机关医院2016年5月—2017年6月收治的行规律血液透析患者60例,根据血压变异系数均值将患者分为高收缩压变异性组30例和低收缩压变异性组30例;高舒张压变异性组30例和低舒张压变异性组30例。将透析中收缩压与舒张压BPV值作为因变量,以患者的年龄、透析龄、体质指数(BMI)、透析间期体质量增长率、脱水量、透析前收缩压、尿素清除指数、清蛋白、血红蛋白、血脂水平(总胆固醇)、血清钙、磷、甲状旁腺激素等为自变量进行多元性回归分析。结果年龄、透析前收缩压、透析间期体质量增长率是透析中收缩压BPV的独立危险因素并呈正相关(P<0.05),血红蛋白是收缩压BPV的独立危险因素并呈负相关(P<0.05)。透析间期体质量增长率、脱水量是舒张压BPV的独立危险因素并呈正相关(P<0.05)。结论患者的年龄、透析间期体质量增长率、透析前收缩压、血红蛋白、脱水量为终末期肾病维持性血液透析患者透析时BPV的独立危险因素。

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.

Correlation and path analysis of morphological and weight traits in marine gastropod Glossaulax reiniana

Using correlation and path analysis, the genetic correlation between weight traits and morphological traits was determined in the marine gastropod Glossaulax reiniana. A total of 100 G. reiniana individuals from a wild population were used. Shell width （X1）, shell height （X2）, umbo-callus height （X3）, body width （X4）, operculum length （X5）, operculum width （X6）, body weight （Y1） and soft-tissue weight （Y2） were measured, and the correlation coefficient matrix calculated. Morphological traits were used as independent variables and weight traits as dependent variables for path coefficient analysis. Path coefficients, correlation indices and determination coefficients were also determined. Results indicate that the correlation coefficients associated with each morphological and weight trait were all highly significant （P〈0.01）. After deleting redundant independent variables, the following optimum multiple regression equations were obtained using stepwise multiple regression analysis： Y1=-29.317＋0.362X2＋0.349X4＋ 1.190）（5 for body weight; and Y2=-17.292＋0.166X1＋0.171X2＋0.703X5, for soft-tissue weight. Operculum height had the highest positive direct correlation with both body weight and soft-tissue weight, which was in accordance with the test results obtained from determinate coefficient analysis. The indication of high genetic correlations between weight traits and morphological traits will provide valuable information for G. reiniana breeding programs.

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.

Theoretical analysis of thermoviscoelastic contact between friction lining and wire rope in mine friction hoists

Serious accidents of mine hoists caused by high-speed sliding between friction lining and wire rope are often seen in coal mines.In order to solve this problem,we analyzed the contact characteristics between friction lining and wire rope.Then we carried out a dynamic mechanical analysis(DMA) to explain the change in mechanical properties of the friction lining as function of temperature and load frequency and found that temperature has a stronger effect on the mechanical properties than the frequency.We used multiple regression analysis to obtain the thermoviscoelastic constitutive relations of the friction lining.As well we derived the analytic solution for the thermoviscoelastic contact radius and pressure by combining the theory of viscoelastic contact mechanics with thermoviscoelastic constitutive relations.

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

Spatial Variability of Soil Carbon to Nitrogen Ratio and Its Driving Factors in Ili River Valley,Xinjiang,Northwest China

Soil carbon to nitrogen(C/N) ratio is one of the most important variables reflecting soil quality and ecological function,and an indicator for assessing carbon and nitrogen nutrition balance of soils.Its variation reflects the carbon and nitrogen cycling of soils.In order to explore the spatial variability of soil C/N ratio and its controlling factors of the Ili River valley in Xinjiang Uygur Autonomous Region,Northwest China,the traditional statistical methods,including correlation analysis,geostatistic alanalys and multiple regression analysis were used.The statistical results showed that the soil C/N ratio varied from 7.00 to 23.11,with a mean value of 10.92,and the coefficient of variation was 31.3%.Correlation analysis showed that longitude,altitude,precipitation,soil water,organic carbon,and total nitrogen were positively correlated with the soil C/N ratio(P < 0.01),whereas negative correlations were found between the soil C/N ratio and latitude,temperature,soil bulk density and soil p H.Ordinary Cokriging interpolation showed that r and ME were 0.73 and 0.57,respectively,indicating that the prediction accuracy was high.The spatial autocorrelation of the soil C/N ratio was 6.4 km,and the nugget effect of the soil C/N ratio was 10% with a patchy distribution,in which the area with high value(12.00–20.41) accounted for 22.6% of the total area.Land uses changed the soil C/N ratio with the order of cultivated land > grass land > forest land > garden.Multiple regression analysis showed that geographical and climatic factors,and soil physical and chemical properties could independently explain 26.8%and 55.4% of the spatial features of soil C/N ratio,while human activities could independently explain 5.4% of the spatial features only.The spatial distribution of soil C/N ratio in the study has important reference value for managing soil carbon and nitrogen,and for improving ecological function to similar regions.

Estimation of reservoir porosity using probabilistic neural network and seismic attributes

Porosity is one of the most important properties of oil and gas reservoirs. The porosity data that come from well log are only available at well points. It is necessary to use other method to estimate reservoir porosity.Seismic data contain abundant lithological information. Because there are inherent correlations between reservoir property and seismic data,it is possible to estimate reservoir porosity by using seismic data and attributes.Probabilistic neural network is a powerful tool to extract mathematical relation between two data sets. It has been used to extract the mathematical relation between porosity and seismic attributes. Firstly,a seismic impedance volume is calculated by seismic inversion. Secondly,several appropriate seismic attributes are extracted by using multi-regression analysis. Then a probabilistic neural network model is trained to obtain a mathematical relation between porosity and seismic attributes. Finally,this trained probabilistic neural network model is implemented to calculate a porosity data volume. This methodology could be utilized to find advantageous areas at the early stage of exploration. It is also helpful for the establishment of a reservoir model at the stage of reservoir development.

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.

Newspaper Visibility of Members of Parliament in Kenya

This research investigates variables that predicted news coverage of 212 members of parliament （MPs） in Kenya by four national newspapers in 2009. The 10 variables examined are： ordinary MP, cabinet minister, powerful ministry, parliamentary committee chairmanship, seniority, big tribe identity, major party affiliation, presidential ambition, commenting on contentious issues, and criticizing government. Findings indicate that commenting on contentious issues, criticizing government, cabinet minister, ordinary MP, powerful ministry, and seniority significantly predicted visibility of the parliamentarians in newspaper news. However, a multiple regression analysis shows that the strongest predictors are commenting on contentious issues, cabinet minister, criticizing government, and big tribe identity. While commenting on controversial issues was the strongest predictor, major party identification and committee leadership were found not to predict MPs＇ visibility.

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.

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.