Influence of confined water on the limit support pressure of tunnel face in weakly water-rich strata

In the process of shield tunneling through soft soil layers,the presence of confined water ahead poses a significant threat to the stability of the tunnel face.Therefore,it is crucial to consider the impact of confined water on the limit support pressure of the tunnel face.This study employed the finite element method(FEM)to analyze the limit support pressure of shield tunnel face instability within a pressurized water-containing layer.Subsequently,a multiple linear regression approach was applied to derive a concise solution formula for the limit support pressure,incorporating various influencing factors.The analysis yields the following conclusions:1)The influence of confined water on the instability mode of the tunnel face in soft soil layers makes the displacement response of the strata not significant when the face is unstable;2)The limit support pressure increases approximately linearly with the pressure head,shield tunnel diameter,and tunnel burial depth.And inversely proportional to the thickness of the impermeable layer,soil cohesion and internal friction angle;3)Through an engineering case study analysis,the results align well with those obtained from traditional theoretical methods,thereby validating the rationality of the equations proposed in this paper.Furthermore,the proposed equations overcome the limitation of traditional theoretical approaches considering the influence of changes in impermeable layer thickness.It can accurately depict the dynamic variation in the required limit support pressure to maintain the stability of the tunnel face during shield tunneling,thus better reflecting engineering reality.

影响深圳市GDP增长的因素分析

对1979年到2006年深圳市的GDP与实际利用外资额、工业增加值、净出口和社会消费品零售总额的有关统计数据进行多元线性回归分析和自回归分析.结果表明:影响深圳市GDP增长的主要因素是工业增加值、社会消费品零售总额和净出口,而实际利用外资额只是次要因素.这结果可为深圳市制订经济发展计划提供决策参考.

Burner effects on melting process of regenerative aluminum melting furnace

According to the features of melting process of regenerative aluminum melting furnaces, a three-dimensional mathematical model with user-developed melting model, burner reversing and burning capacity model was established. The numerical simulation of melting process of a regenerative aluminum melting furnace was presented using hybrid programming method of FLUENT UDF and FLUENT scheme based on the heat balance test. Burner effects on melting process of aluminum melting furnaces were investigated by taking optimization regulations into account. The change rules of melting time on influence factors are achieved. Melting time decreases with swirl number, vertical angle of burner, air preheated temperature or natural gas flow; melting time firstly decreases with horizontal angle between burners or air-fuel ratio, then increases; melting time increases with the height of burner.

Exploration of the spatial pattern of urban residential land use with geographically weighted regression technique: a case study of Nanjing,China

As the traditional methods and technical means cannot meet the quantitative research needs of the urban land use patterns, quantitative research methods for the urban land use pattern are established via the GIS （geographic information system ） technique combined with the related theories and models. Taking the city of Nanjing as an example, a spatial database of urban land use and other environmental and socio-economic data is constructed. A multiple linear regression model is developed to determine the statistically significant factors affecting the residential land use distributions. To explain the spatial variations of urban land use patterns, the geographically weighted regression （GWR） is employed to establish spatial associations between these significant factors and the distribution of urban residential land use. The results demonstrate that the GWR can provide an effective approach to the exploration of the urban land use spatial patterns and also provide useful spatial information for planning residential development and other types of urban land use.

Prediction Model of Secondary Substances in Anthocyanins Synthesis of Purple Corn

The aim of this study was to assay the polyphenols,flavonoid,polyphenol oxidase and phenylalnine ammonialyase which were relative to the anthocyanins synthesis of purple corn. The optimization of multiple linear regression model of anthocyanins synthesis was y=4.383 86-0.205 45x1＋5.479 638x2＋0.195 575x4. According to standard partial regression coefficient testing,the result indicated that polyphenols content was negatively correlated with anthocyanins and the relative influence to anthocyanins synthesis was-42.7%; flavonoid content and activity of polyphenol oxidase were positively correlated with anthocyanins of purple corn and the relative influence to anthocyanins synthesis were 71.45% and 73.32% respectively. There was no positive correlation between the activity of phenylalnine ammonialyase and anthocyanins of purple corn. The establishment of multiple linear regression model of anthocyanins synthesis was to provide theory foundation of producing anthocyanins in laboratory.

Prediction of Demand and Tendency of the Book Market in China

The prediction model of the demand of the book market in China from the quantitative angle is established,and the total demand of the books for years from 2002 to 2004 is predicted.The effects of the gross domestic product,household consumption,price and population on the demand of books are also analyzed.In the end,it is summarized that the acceleration of the development of Chinese book industry,the refinement of the books,the innovation of the advertisement,the series of the structure and the steady increase of the price will become the remarkable characteristics of the book market.

Study on QSAR of Taxol and its Derivatives Based on Stepwise Multivariate Linear Regression Analysis

Abstract Using the method of stepwise multivariate linear regression (SMLR), the quantitative structure activity relationships (QSAR) of two isomeric series of taxol and its derivatives have been studied. It was found that the molar refractivity of the C3′substituent of the C13 side chain has significant correlation with its activity. We deduce that structural changes in the C3′substituents may be critical to the anticancer function. It would be useful to the design and synthesis of taxol like compounds with improved activities.

Isotopic composition of precipitation over Arid Northwestern China and its implications for the water vapor origin

In order to reveal the characteristics and climatic controls on the stable isotopic composition of precipitation over Arid Northwestern China, eight stations have been selected from Chinese Network of Isotopes in Precipitation(CHNIP).During the year 2005 and 2006, monthly precipitation samples have been collected and analyzed for the composition of δD and δ18O.The established local meteoric water line δD=7.42δ18O+1.38, based on the 95 obtained monthly composite samples, could be treated as isotopic input function across the region.The deviations of slope and intercept from the Global Meteoric Water Line indicated the specific regional meteorological conditions.The monthly δ18O values were characterized by a positive correlation with surface air temperature(δ18O(‰) =0.33 T(℃)-13.12).The amount effect visualized during summer period(δ18O(‰) =-0.04P(mm)-3.44) though not appeared at a whole yearly-scale.Spatial distributions of δ18O have properly portrayed the atmospheric circulation background in each month over Arid Northwestern China.The quan-titative simulation of δ18O, which involved a Rayleigh fractionation and a kinetic fractionation, demonstrated that the latter one was the dominating function of condensation of raindrops.Furthermore, the raindrop suffered a re-evaporation during falling processes, and the precipitation vapor might have been mixed with a quantity of local recycled water vapor.Multiple linear regression equations and a δ18O-T relation have been gained by using meteorological parameters and δ18O data to evaluate physical controls on the long-term data.The established δ18O-T relation, which has been based on the present-day precipitation, could be considered as a first step of quantitatively reconstructing the historical environmental climate.

Using Path Analysis to Identify the Influence of Climatic Factors on Spring Peak Flow Dominated by Snowmelt in an Alpine Watershed

Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.

Prediction of Soil Depth from Digital Terrain Data by Integrating Statistical and Visual Approaches

Information about the spatial distribution of soil attributes is indispensable for many land resource management applications; however, the ability of soil maps to supply such information for modern modeling tools is questionable. The objectives of this study were to investigate the possibility of predicting soil depth using some terrain attributes derived from digital elevation models （DEMs） with geographic information systems （GIS） and to suggest an approach to predict other soil attributes. Soil depth was determined at 652 field observations over the A1-Muwaqqar Watershed （70 km2） in Jordan. Terrain attributes derived from 30-m resolution DEMs were utilized to predict soil depth. The results indicated that the use of multiple linear regression models within small watershed subdivisions enabled the prediction of soil depth with a difference of 50 cm for 77% of the field observations. The spatial distribution of the predicted soil depth was visually coincided and had good correlations with the spatial distribution of the classes amalgamating three terrain attributes, slope steepness, slope shape, and compound topographic index. These suggested that the modeling of soil-landscape relationships within small watershed subdivisions using the three terrain attributes was a promising approach to predict other soil attributes.

Quantitative evaluation of urban park cool island factors in mountain city

Evaluating how park characteristics affect the formation of a park cool island(PCI) is the premise of guiding green parks planning in mountain cities.The diurnal variation of PCI intensity was achieved,and correlations between PCI intensity and park characteristics such as park area,landscape shape index(LSI),green ratio and altitude were analyzed,using 3 010 temperature and humidity data from measurements in six parks with typical park characteristics in Chongqing,China.The results indicate that:1) the main factor determining PCI intensity is park area,which leads to obvious cool island effect when it exceeds 14 hm2;2) there is a negative correlation between PCI intensity and LSI,showing that the rounder the park shape is,the better the cool island effect could be achieved;3) regression analysis of humidity and PCI intensity proves that photosynthesis midday depression(PMD) is an important factor causing the low PCI intensity at 13:00;4) the multivariable linear regression model proposed here could effectively well predict the daily PCI intensity in mountain cities.

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.

Damage alarming for bridge expansion joints using novelty detection technique based on long-term monitoring data

Damage alarming and safety evaluation using long-term monitoring data is an area of significant research activity for long-span bridges. In order to extend the research in this field, the damage alarming technique for bridge expansion joints based on long-term monitoring data was developed. The effects of environmental factors on the expansion joint displacement were analyzed. Multiple linear regression models were obtained to describe the correlation between displacements and the dominant environmental factors. The damage alarming index was defined based on the multiple regression models. At last, the X-bar control chart was utilized to detect the abnormal change of the displacements. Analysis results reveal that temperature and traffic condition are the dominant environmental factors to influence the displacement. When the confidence level of X-bar control chart is set to be 0.003, the false-positive indications of damage can be avoided. The damage sensitivity analysis shows that the proper X-bar control chart can detect 0.1 cm damage-induced change of the expansion joint displacement. It is reasonably believed that the proposed technique is robust against false-positive indication of damage and suitable to alarm the possible future damage of the expansion joints.

Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.

Support pressure assessment for deep buried railway tunnels using BQ-index

Estimation of support pressure is extremely important to the support system design and the construction safety of tunnels.At present,there are many methods for the estimation of support pressure based on different rock mass classification systems,such as Q system,GSI system and RMR system.However,various rock mass classification systems are based on different tunnel geologic conditions in various regions.Therefore,each rock mass classification system has a certain regionality.In China,the BQ-Inex(BQ system)has been widely used in the field of rock engineering ever since its development.Unfortunately,there is still no estimation method of support pressure with BQ-index as parameters.Based on the field test data from 54 tunnels in China,a new empirical method considering BQ-Inex,tunnel span and rock weight is proposed to estimate the support pressure using multiple nonlinear regression analysis methods.And then the significance and necessity of support pressure estimation method for the safety of tunnel construction in China is explained through the comparison and analysis with the existing internationally widely used support pressure estimation methods of RMR system,Q system and GSI system.Finally,the empirical method of estimating the support pressure based on BQ-index was applied to designing the support system in the China’s high-speed railway tunnel—Zhengwan high-speed railway and the rationality of this method has been verified through the data of field test.

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.

Impact of Regional Development on Carbon Emission: Empirical Evidence Across Countries

Global warming is recently an urgent issue worldwide. The increase of carbon emissions induced by human economic activi- ties has become a major driving force behind global climate change. Thus, as a matter of social responsibility, reasonable carbon con- straints should be implemented to ensure environmental security and sustainable development for every country. Based on a summary of studies that examined the relationship between carbon emissions and regional development, this paper shows that human activity-led carbon emission is caused by the combination of several influencing factors, including population size, income level, and technical pro- gress. Thus, a quantitative model derived from IPAT-ImPACT-Kaya series and STIRPAT models was established. Empirical analysis using multivariate nonlinear regression demonstrated that the origins of growing global carbon emission included the increasing influ- encing elasticity of the population size and the declining negative effect of technical progress. Meanwhile, in context of classification of country groups at different income levels, according to the comparison of fluctuating patterns of the influencing elasticity, technical progress was found as the main factor influencing carbon emission levels in high-income countries, and population size might he the controlling factor in middle-income countries. However, for low-income countries, the nonlinear relationship between carbon emission and its influencing factors was not significant, whereas population growth was identified as an important potential driving force in future carbon emissions. This study can therefore provide a reference for the formulation of policies on carbon constraints, especially to de- velop more efficient carbon mitigating policies for countries at different income levels.

A Quantitative Structure Property Relationship for Prediction of Flash Point of Alkanes Using Molecular Connectivity Indices

Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecular structure without any experimental effort, they provide a simple and straightforward method for property prediction. In this work the flash point of alkanes was modeled by a set of molecular connectivity indices （Х）, modified molecular connectivity indices （ ^mХ^v ） and valance molecular connectivity indices （ ^mХ^v ）, with ^mХ^v calculated using the hydrogen perturbation. A stepwise Multiple Linear Regression （MLR） method was used to select the best indices. The predicted flash points are in good agreement with the experimental data, with the average absolute deviation 4.3 K.

Pyrolysis Characteristics and Kinetics of Methyl Oleate Based on TG-FTIR Method

The thermal decomposition characteristics of methyl oleate were preliminarily investigated under nitrogen atmo-sphere by a thermogravimetric analyzer when the ester was heated at a heating rate of 10℃/min from room temperature to 600℃. Furthermore, the pyrolytic and kinetic characteristics of methyl oleate were intensively studied at different heating rates. The gaseous species obtained during thermal decomposition were also identiifed by the TG-FTIR coupling analysis. The results showed that the pyrolysis of methyl oleate proceeded in three stages, viz. the drying stage, the main pyrolysis stage and the residual pyrolysis stage. The initial decomposition temperature, the maximum weight loss temperature, the peak decomposition temperature and the rate of maximum weight loss of methyl oleate increased with the increasing heating rates. Gaseous CO, CO2 and H2O were the typical decomposition products from pyrolysis of methyl oleate. In addition, a kinetic model for thermal decomposition of methyl oleate was built up based on the experimental results using the Coats-Redfern integral method and the multiplelinear regression method. The activation energy, the preexponential factor, the reaction order and the kinetic equation for thermal decomposition of methyl oleate were obtained. Comparison of the experimental data with the calculated ones and analysis of statistical errors of pyrolysis ratios demonstrated that the kinetic model was reliable for studying the pyrolysis of methyl oleate. Finally, the kinetic compensation effect between the preexponential factors and the activation energy in the pyrolysis of methyl oleate was also conifrmed.