广义可加模型共曲线性及其在空气污染问题研究中的应用

目的:针对大气污染与健康关系研究中拟合广义 可加模型时的共曲线性现象进行研究并试图减小其影响. 方法:采用非参数条件自助抽样法来估计模型系数及其可信 区间.结果:实例数据分析可见自助法得到的结果较好. 结论:非参数条件自助抽样法是克服广义可加模型中共曲线 性影响的有益尝试.

圆形分布在结核病发病季节性分布特征中的应用

本文应用圆形分布的原理和方法,对井陉县1986～1992年结核发病高峰时点进行了初步分析。发病高峰时点为6月9日。P<0.001,表明结核病的发病高峰是很明显的。发病高峰期为2月10日～10月6日,说明季节性不明显。但发病高峰时点出现在春夏季节的有6年,占85.7％。提示本县结核病以春夏季流行为主。

胃癌419例临床X线分析

目的为了提高对胃癌X线诊断水平.方法回顾性分析我院1980/1999年确诊的419例胃癌(胃底贲门癌137例,胃窦癌152例,胃体癌91例,胃角癌15例,全胃癌13例,残胃癌11例),结合临床表现,手术所见,病理活检对内镜与钡餐检查进行比较,并分析胃钡餐检查误、漏诊原因.结果经胃钡餐造影检出胃癌298例,与病理符合率71.12%,误、漏诊121例(28.88%).X线钡餐与主要表现为:①癌肿区粘膜皱襞紊乱、中断、破坏;②胃壁增厚,僵硬,蠕动,扩张度消失;③不规则充盈缺损及癌性龛影.204例同时进行内镜检查,检出胃癌167例,检出率81.86%结论内镜检查明显优于胃钡餐造影检查,尤其对早期胃癌诊断更显示其优越性.提出在行胃钡餐检查时,双对比法与传统法密切结合,是避免胃钡餐检查误。

Spatial Variability of Soil Organic Carbon in a Watershed on the Loess Plateau

Soil organic carbon (SOC) has great impacts on global warming, land degradation and food security. Classic statistical and geostatistical methods were used to characterize and compare the spatial heterogeneity of SOC and related factors, such as topography, soil type and land use, in the Liudaogou watershed on the Loess Plateau of North China. SOC concentrations followed a log-normal distribution with an arithmetic and geometric means of 23.4 and 21.3 g kg-1, respectively, were moderately variable (CV = 75.9%), and demonstrated a moderate spatial dependence according to the nugget ratio (34.7%). The experimental variogram of SOC was best-fitted by a spherical model, after the spatial outliers had been detected and subsequently eliminated. Lower SOC concentrations were associated with higher elevations. Warp soils and farmland had the highest SOC concentrations, while aeolian sand soil and shrublands had the lowest SOC values. The geostatistical characteristics of SOC for the different soil and land use types were different. These patterns were closely related to the spatial structure of topography, and soil and land use types.

Modified Method for Estimating Organic Carbon Density in Discontinuous Karst Soil Using Ground-Penetrating Radar and Geostatistics

The conventional method which assumes the soil distribution is continuous was unsuitable for estimating soil organic carbon density(SOCD) in Karst areas because of its discontinuous soil distribution. The accurate estimation of SOCD in Karst areas is essential for carbon sequestration assessment in China. In this study, a modified method,which considers the vertical proportion of soil area in the profile when calculating the SOCD, was developed to estimate the SOCD in a typical Karst peak-cluster depression area in southwest China. In the modified method, ground-penetrating radar(GPR) technology was used to detect the distribution and thickness of soil. The accuracy of the method was confirmed through comparison with the data obtained using a validation method, in which the soil thickness was measured by excavation. In comparison with the conventional method and average-soil-depth method,the SOCD estimated using the GPR method showed the minimum relative error with respect to that obtained using the validation method. At a regional scale, the average SOCDs at depths of 0-20 cm and 0-100 cm, which were interpolated by ordinary kriging,were 1.49(ranging from 0.03-5.65) and 2.26(0.09-11.60) kgm-2based on GPR method in our study area(covering 393.6 hm2), respectively. Therefore, the modified method can be applied on the accurate estimation of SOCD in discontinuous soil areas such as Karst regions.

Mirizzi Syndrome: Our Experience with 27 Cases in PUMC Hospital

Objective To retrospectively evaluate the diagnosis and treatment of Mirizzi syndrome （MS）. Methods Patients who received elective or emergency cholecystectomies in our center during 23 years were retrospectively evaluated. The data reviewed included demography, clinical presentations, diagnostic methods, surgical procedures, postoperative complications, and follow-up.

Spatial Variability of Soil Organic Carbon in Different Hillslope Positions in Toshan Area, Golestan Province, Iran: Geostatistical Approaches

Accessibility to organic carbon(OC) budget is required for sustainable agricultural development and ecosystem preservation and restoration. Using geostatistical models to describe and demonstrate the spatial variability of soil organic carbon(SOC) will lead to a greater understanding of this dynamics. The aim of this paper is to present the relationships between the spatial variability of SOC and the topographic features by using geostatistical methods on a loess mountain-slope in Toshan region, Golestan Province, northern Iran. Hence, 234 soil samples were collected in a regular grid that covered different parts of the slope. The results showed that such factors as silt, clay, saturated moisture content, mean weighted diameter(MWD) and bulk density were all correlated to the OC content in different slope positions, and the spatial variability of SOC more to slope positions and elevations. The coefficient of variation(CV) indicated that the variability of SOC was moderate in different slope positions and for the mountain-slope as a whole. However, the higher variability of SOC(CV = 45.6%) was shown in the back-slope positions. Also, the ordinary cokriging method for clay as covariant gave better results in evaluating SOC for the whole slope with the RMSE value 0.2552 in comparison with the kriging and the inverse distance weighted(IDW) methods. The interpolation map of OC for the slope under investigation showed lowering SOC concentrations versus increasing elevation and slope gradient. The spatial correlation ratio was different between various slope positions and related to the topographic texture.

An efficient latent variable optimization approach with stochastic constraints for complex industrial process

For complex chemical processes,process optimization is usually performed on causal models from first principle models.When the mechanism models cannot be obtained easily,restricted model built by process data is used for dynamic process optimization.A new strategy is proposed for complex process optimization,in which latent variables are used as decision variables and statistics is used to describe constraints.As the constraint condition will be more complex by projecting the original variable to latent space,Hotelling T^2 statistics is introduced for constraint formulation in latent space.In this way,the constraint is simplified when the optimization is solved in low-dimensional space of latent variable.The validity of the methodology is illustrated in pH-level optimal control process and practical polypropylene grade transition process.

Statistical approach for the culture conditions optimization of magnetotactic bacteria for magnetic cells production

The culture of Magnetospirillum magneticum WM-1 depends on several control factors that have great effect on the magnetic cells concentration. Investigation into the optimal culture conditions needs a large number of experiments So it is desirable to minimize the number of experiments and maximize the information gained from them. The orthogonal design of experiments and mathematical statistical method are considered as effective methods to optimize the culture condition of magnetotactic bacteria WMol for high magnetic cells concentration. The effects of the four factors, such as pH value of medium, oxygen concentration of gas phase in the serum bottle, C：C （mtartaric acid： m=succinic acid） ratio and NaNO3 concentration, are simultaneously investigated by only sixteen experiments through the orthogonal design L16（44） method. The optimal culture condition is obtained. At the optimal culture condition （ pH 7.0, an oxygen concentration 4.0%, C：C （mtartaric acid： m=succinic acid） ratio 1：2 and NaNO3 100 mg 1^-1）, the magnetic cells concentration is promoted tO 6.5×10^7 cells ml^-1, approximately 8.3% higher than that under the initial conditions. The pH value of medium is a very important factor for magnetic cells concentration. It can be Proved that the orthogonal design of experiment is of 90% confidence. Ferric iron uptake follows MichaelisoMenten kinetics with a Km of 2.5 pM and a Vmax of 0.83 min^-1.

Clinical Significance of CENP-H Expression in Uterine Cervical Cancer

Objective This work aims to investigate the expression pattern and clinicopathologic significance of centromere protein H(CENP-H) in uterine cervical cancer(UCC). Methods The level of CENP-H expression in the paraffin sections of 62 UCC cases was determined by the SP immunohistochemical method,with complete clinicopathologic data in all cases.Statistical analysis was conducted to evaluate the prognostic and diagnostic significance of CENP-H using SPSS13.0 software package. Results Immunohistochemical assay showed strong CENP-H expression in 61.29% (38/62) of the paraffin-embedded cervical cancer tissues.Statistical analysis revealed a strong correlation between the CENP-H expression and the clinical classification(P=0.038) of the cervical carcinoma.The expression increased with rise of the stages.The analysis of Cox proportional hazards regression model suggested that CENP-H expression(P=0.002) and tumor stage(P=0.001) were independent prognostic markers for the survival of UCC patients.The survival analysis showed that the survival rate was significantly lower in patients with high expression of CENP-H than in those with low expression of CENP-H(P=0.001). Conclusions CENP-H is likely to be a valuable marker for carcinogenesis and progression of UCC.It might be used as the important diagnostic and prognostic marker for cervical carcinoma patients,especially for those at early stage.

Existence Results of Abstract Impulsive Integrodifferential Systems with Measure of Non-compactness

In this Paper, we study the existence of solutions for the nonlocal integrodifferential equations with interval impulse and measure of non compactness by using M6nch - fixed point theorem. Finally, an example is given to illustrate our main result.

Forecasting Financial Distress of Chinese High-tech Manufacturing Companies Based on a Hybrid Model of GA-SVM

Owing to the radical changing of Chinese economy, it is essential to build an effective financial distress prediction model. In this paper, we present a genetic algorithm （GA） approach for optimizing parameters of support vector machine （SVM）. We validate the proposed model on datasets of Chinese high-tech manufacturing industry. Experimental results reveal that the proposed GAo SVM model can compare to and even outperform other exiting classifiers. Compared to grid-search algorithm, the proposed GA-based takes less time to optimize SVM parameter without degrading the prediction accuracy of SVM.

Authentication based on feature of hand-written signature

The typical features of the coordinate and the curvature as well as the recorded time information were analyzed in the hand-written signatures.In the hand-written signature process 10 biometric features were summarized:the amount of zero speed in direction x and direction y,the amount of zero acceleration in direction x and direction y,the total time of the hand-written signatures,the total distance of the pen traveling in the hand-written process,the frequency for lifting the pen,the time for lifting the pen,the amount of the pressure higher or lower than the threshold values.The formulae of biometric features extraction were summarized.The Gauss function was used to draw the typical information from the above-mentioned biometric features,with which to establish the hidden Markov mode and to train it.The frame of double authentication was proposed by combing the signature with the digital signature.Web service technology was applied in the system to ensure the security of data transmission.The training practice indicates that the hand-written signature verification can satisfy the needs from the office automation systems.

A study on effects of different instruction models in military English teaching

SPSS statistical analysis system is used to examine the teaching effects of three different instruction models which are commonly used in military English teaching. Of the three models, interactive teaching model has shown to have advantage over the other two, the situational teaching model and the task-based Instruction model. It is concluded that it is beneficial to improve teaching effects in military English teaching if the teacher can stimulate students to involve themselves more in class. To do so, it is necessary to strike a balance between the learners＇ language input and output so as to ensure that the input knowledge be consolidated and digested through practice in output.

Improved Crude Oil Price Forecasting With Statistical Learning Methods

Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.

Reduction in the Water Level of Lake Victoria and Its Implications on Livelihoods in Rwanjaba Lakeshore Community,Uganda

This paper examines the livelihood challenges experienced in Rwanjaba Lakeshore Community during the period of low water level in Lake Victoria between 2004 and 2007 and identifies the livelihood coping strategies that were adopted to address them.A total of 55 households were randomly sampled and the data collection methods included household questionnaires and participant observations.The data were analyzed using the Statistical Package for Social Science(SPSS) and the results presented with the help of descriptive statistics.The livelihood challenges experienced during the low lake water level included fish shortage(34.5%),household food scarcity(23.6%),sex for fish(18.2%),family breakdown(12.7%),increased theft(7.2%) and accidents due to the exposed rocks in the lake(3.6%).The livelihood coping strategies adopted to redress the challenges included causal labour(32.7%),maize roasting(23.6%),sand mining(18.2%),selling of snacks(12.7%),selling household property(9.1%) and resorting shop and market credits(3.6%).The paper proposes a number of recommendations for improving the livelihood of the community ranging from policy reforms to the diversification of activities.

Diagnosing Student Learning Problems in Object Oriented Programming

Students often face difficulties while taking basic programming courses due to several factors. In response, research has presented subjective assessments for diagnosing learning problems to improve the teaching of programming in higher education. In this paper, the authors propose an Object Oriented conceptual map model and organize this approach into three levels： constructing a Concept Effect Propagation Table, constructing Test Item-Concept Relationships and diagnosing Student Learning Problems with Matrix Composition. The authors＇ work is a modification of the approaches of Chert and Bai as well as Chu et al., as the authors use statistical methods, rather than fuzzy sets, for the authors＇ analysis. This paper includes a statistical summary, which has been tested on a small sample of students in King Abdulaziz University, Jeddah, Saudi Arabia, illustrating the learning problems in an Object Oriented course. The experimental results have demonstrated that this approach might aid learning and teaching in an effective way.

A Task-driven Medical Teaching Design under the Guidance of B-learning

A new challenge has been brought by the rapid development of information technology to medical teaching, and the teaching reform of the medical education in China should be deepened for attaining a development. The core of deepening medical teaching reform is to break the traditional teaching model （i.e. giving a lecture）, and create a better classroom teaching situation by making full use of the modern teaching methods. In B-learning, the effective combination of the traditional teaching method＇ s advantages with the E-learning in a pure technical environment is advocated. In the task-driven teaching, a teaching design is made by students in a real or simulated real environment. In this paper, the effective combination of B-learning with the task-driven teaching model is introduced, so that the better teaching effect is achieved.

Differences inthe Level of Social Status of Male and Female Folk Dancers

The research was conducted in order to determine differences in the social status structure of male and female performers of folk dances. For the purpose of determining the social status structure of male and female dancers, 103 male and 145 female dancers aged 18-28 actively engaged in folk dancing were tested. For the assessment of social status, only one model that allows for true scientific approach to studying the structure of stratification dimensions has been made so far. The model was constructed by Saksida and later served as a basis for many studies conducted by other authors as well （Saksida, Caserman, Petrovic, Momirovic, and Hosek）. Designed as a phenomenological model, it has undergone several changes over time, but it is still suitable for studying social change. The INST2 questionnaire modified by Boli, Popovic, Hosek, Momirovic, and Savic （SSMIN） was applied in this study. All the data obtained in this research were processed at the Multidisciplinary Research Center of the Faculty of Sport and Physical Education, University of Pristina, through the system of data processing programs designed by D. Popovic and K Momirovic. To determine differences between the groups, a method of discriminant analysis was applied.

Position and Perspective of Statistics in Sociology

The paper first gives a brief overview of the use of statistical methods in sociology in order to show the continuity and importance of these methods in the development of sociology as a science. Therefore, education of sociologists requires, among other things, training in statistical methods applicable in data processing and analysis in sociological research. Then the research continues with a comparative analysis of the curricula of undergraduate academic studies of sociology, and especially the presence of statistics teaching in them, in the Republic of Serbia and the neighbouring countries. Different programs of the Department of Sociology of the Faculty of Philosophy in Novi Sad are analyzed together with the results of the students＇ evaluations for the academic years 2007/2008 and 2009/2010.