On the Relationship between Climatic Variables and Pressure Systems over Saudi Arabia in the Winter Season

The synoptic circulation over Saudi Arabia is complicated and frequently governed by the effect of large-scale pressure systems. In this work, we used NCEP–NCAR global data to illustrate the relationship between climatic variables and the main pressure systems that affect the weather and climate of Saudi Arabia, and also to investigate the influence of these pressure systems on surface air temperature（SAT） and rainfall over the region in the winter season. It was found that there are two primary patterns of pressure that influence the weather and climate of Saudi Arabia. The first occurs in cases of a strengthening Subtropical High（Sub H）, a weakening Siberian High（Sib H）, a deepening of the Icelandic Low（Ice L）, or a weakening of the Sudanese Low（Sud L）. During this pattern, the Sub H combines with the Sib H and an obvious increase of sea level pressure（SLP） occurs over southern European, the Mediterranean, North Africa, and the Middle East. This belt of high pressure prevents interaction between midlatitude and extratropical systems, which leads to a decrease in the SAT,relative humidity（RH） and rainfall over Saudi Arabia. The second pattern occurs in association with a weakening of the Sub H, a strengthening of the Sib H, a weakening of the Ice L, or a deepening of the Sud L. The pattern arising in this case leads to an interaction between two different air masses： the first（cold moist） air mass is associated with the Mediterranean depression travelling from west to east, while the second（warm moist） air mass is associated with the northward oscillation of the Sud L and its inverted V-shape trough. The interaction between these two air masses increases the SAT, RH and the probability of rainfall over Saudi Arabia, especially over the northwest and northeast regions.

THE CAUCHY INTEGRAL OF MANY COMPLEX VARIABLES PASSIVE OPERATORS AND MULTIDIMENSIONAL DISPERSION RELATIONS

This note illustrates the multidimensional dispersion relations that connect the real and imaginary parts of the matrixwhere z(p)) is the boundary value of the impedance

Effect of Correlation Level on the Use of Auxiliary Variable in Double Sampling for Regression Estimation

While an auxiliary information in double sampling increases the precision of an estimate and solves the problem of bias caused by non-response in sample survey, the question is that, does the level of correlation between the auxiliary information x and the study variable y ease in the accomplishment of the objectives of using double sampling? In this research, investigation was conducted through empirical study to ascertain the importance of correlation level between the auxiliary variable and the study variable to maximally accomplish the importance of auxiliary variable(s) in double sampling. Based on the Statistics criteria employed, which are minimum variance, coefficient of variation and relative efficiency, it was established that the higher the correlation level between the study and auxiliary variable(s) is, the better the estimator is.

Lie symmetry and the generalized Hojman conserved quantity of Nielsen equations for a variable mass holonomic system of relative motion

Lie symmetry and the generalized Hojman conserved quantity of Nielsen equations for a variable mass holonomic system of relative motion are studied. The determining equation of Lie symmetry of Nielsen equations for a variable mass holonomic system of relative motion under the infinitesimal transformations of groups is given. The expression of generalized Hojman conserved quantity deduced directly from Lie symmetry for a variable mass holonomic system of relative motion is obtained. An example is given to illustrate the application of the results.

Mei symmetry and Mei conserved quantity of Appell equations for a variable mass holonomic system of relative motion

Mei symmetry and Mei conserved quantity of Appell equations for a variable mass holonomic system of relative motion are studied.The definition and criterion of the Mei symmetry of Appell equations for a variable mass holonomic system of relative motion under the infinitesimal transformations of groups are given.The structural equation of Mei symmetry of Appell equations and the expression of Mei conserved quantity deduced directly from Mei symmetry for a variable mass holonomic system of relative motion are gained.Finally,an example is given to illustrate the application of the results.

Batch process monitoring based on WGNPE–GSVDD related and independent variables

In many batch processes, there are related or independence relationships among process variables. The traditional monitoring method usually carries out a single statistical model according to the related or independent method, and in the feature extraction there is not fully taken into account the characterization of fault information, it will make the process monitoring ineffective, so a fault monitoring method based on WGNPE(weighted global neighborhood preserving embedding)–GSVDD(greedy support vector data description) related and independent variables is proposed. First, mutual information method is used to separate the related variables and independent variables. Secondly, WGNPE method is used to extract the local and global structures of the related variables in batch process and highlight the fault information, GSVDD method is used to extract the process information of the independent variables quickly and effectively. Finally, the statistical monitoring model is established to achieve process monitoring based on WGNPE and GSVDD. The effectiveness of the proposed method was verified by the penicillin fermentation process.

Presence of circulating tumor cells is associated with metabolic-related variables in postoperative patients with early-stage breast cancer

Objective：Although circulating tumor cells（CTCs）have been well-established as promising prognostic biomarkers in both early breast cancer and metastatic settings,little is known regarding the prognostic relevance of CTCs in the long-term postoperative monitoring of patients with non-metastatic breast cancer（non-MBC）.In this study,we investigated the associations of CTCs with clinicopathological features and metabolic-related variables,such as obesity and hyperglycemia.Methods：In this retrospective study,we recruited 264 patients with postoperative stage Ⅰ–Ⅲ breast cancer at Guangdong General Hospital from January 2009 to December 2015.The prevalence and number of CTCs were assessed using the Cell Search System at a median time of 19.0 months[interquartile range（IQR）,7.8–33.0]after surgery.The CTC assay results were correlated with the clinicopathological features and metabolic-related variables.A multivariate logistic regression analysis was performed to further determine the independent predictors of CTCs.Results：CTCs were detected in 10.6%of all patients.The positive rate of CTCs in patients with infiltrating ductal carcinoma was lower than that in patients with other pathological types（9.0%vs.28.6%,P=0.020）.More importantly,the presence of CTCs was correlated with blood glucose level（P=0.015）and high-density lipoprotein level（P=0.030）.The multivariate logistic regression analysis showed that the pathological type[odds ratio（OR）：1.757,95%CI：1.021–3.023;P=0.042]and blood glucose level（OR：1.218,95%CI：1.014–1.465;P=0.035）were independent predictors of the presence of CTCs.Conclusions：This study revealed potential associations between CTCs and metabolic-related factors in Chinese patients with non-MBC and supports the hypothesis that metabolic dysfunction in breast cancer patients might influence the biological activity of metastatic breast cancer,leading to a higher prevalence of CTCs.

Assessment on Agricultural Drought Risk Based on Variable Fuzzy Sets Model

Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was estab-lished according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respec-tively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combi-nation weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the as-sessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.

Nonlinear combined forecasting model based on fuzzy adaptive variable weight and its application

In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system,a new nonlinear fuzzy adaptive variable weight combined forecasting model was established by using conceptions of the relative error,the change tendency of the forecasted object,gray basic weight and adaptive control coefficient on the basis of the method of fuzzy variable weight.Based on Visual Basic 6.0 platform,a fuzzy adaptive variable weight combined forecasting and management system was developed.The application results reveal that the forecasting precisions from the new nonlinear combined forecasting model are higher than those of other single combined forecasting models and the combined forecasting and management system is very powerful tool for the required decision in complex industry system.

APPROACH FOR LAYOUT OPTIMIZATION OF TRUSS STRUCTURES WITH DISCRETE VARIABLES UNDER DYNAMIC STRESS, DISPLACEMENT AND STABILITY CONSTRAINTS

A mathematical model was developed for layout optimization of truss structures with discrete variables subjected to dynamic stress, dynamic displacement and dynamic stability constraints. By using the quasi-static method, the mathematical model of structure optimization under dynamic stress, dynamic displacement and dynamic stability constraints were transformed into one subjected to static stress, displacement and stability constraints. The optimization procedures include two levels, i.e., the topology optimization and the shape optimization. In each level, the comprehensive algorithm was used and the relative difference quotients of two kinds of variables were used to search the optimum solution. A comparison between the optimum results of model with stability constraints and the optimum results of model without stability constraint was given. And that shows the stability constraints have a great effect on the optimum solutions.

New Refinement Relations of Z Specifications for Multiple Viewpoints Oriented Requirements Method

In this paper we develop several new refinement relations of Z for multiple viewpoints oriented requirements method (MVORM). The original motivation is that we found the standard Z refinement relation is not adequate or correct when considering specifications that have temporal relationships of operations. The concept of temporal state variables is introduced into Z. Then new implementation relations are defined and new refinement relations are deduced, mainly for temporal state variables to process temporal relationships of operations. We use state transition systems to abstract the temporal state transitions. A simple example is used to show the procedures of MVORM. Finally some directions of further work are forwarded.

Towards an Algebraic Theory of Orthogonal Polynomials in Several Variables

In this paper, we review on a general theory of orthogonal polynomials in several variables (O.P.S.V) in which we present two different approaches for the three-term recurrence relation. We draw attention to the fact that it is possible to take advantage of the orthogonal projection approach of the three-term recurrence relation towards the development of the algebraic theory of O.P.S.V.

On the Extension of the Three-Term Recurrence Relation to Probabilities Distributions without Moments

In this paper, we extend the three-term recurrence relation for orthogonal polynomials associated with a probability distribution having a finite moment of all orders to a class of orthogonal functions associated with an infinitely divisible probability distribution µ?having a finite moments of order less or equal to four. An explicit expression of these functions will be given in term of the Lévy-Khintchine function of the measure?µ.

The Equation of the Universe (According to the Theory of Relation)

A new equation is found in which the concept of matter-space-time is mathematically connected;gravitation and electromagnetism are also bound by space-time. A mechanism is described showing how velocity, time, distance, matter, and energy are correlated. We are led to ascertain that gravity and electricity are two distinct manifestations of a single underlying process: electro-gravitation. The force of gravitation arises of electromagnetism—inherently much stronger—divided by the cosmological space-time. The radius of space-time belongs to the family of electromagnetic waves: the wavelength is the radius (1026 m) of the universe and the period (1017 s) is its cosmological age. For the first time, the cosmological time, considered as a real physical object, is integrated into a “cosmological equation” which makes coherent what we know regarding the time (its origin, its flow …), the matter, and space. It sets up a mathematical model allowing us to interpret dark energy (or cosmological constant) as being both “negative” and “tired” energy. After an introduction with a brief history of unifications and the presentation of two roughly equal ratios arising out from Dirac’s large-number hypotheses which relate to the ratio of electric force to gravitational force and the ratio of the age of the universe to the atomic time unit associated with atomic processes, we present in §2 this new equation of quantum cosmology which operates the reconciliation between the macrocosm and the microcosm. In §3 and §4, we discuss the irreversible cosmological time resulting from the equation, as well as the role of the mass (heavy) relative to the gravitational constant G. In §5 we discuss the links that the equation establishes between gravitation (structure of condensation) and electromagnetism (structure of expansion), between relativity and quantum theory. We apply the formula to Planck’s time. We speak of the new essential variable? ?, and briefly of a new principle, the principle of compensation. In §6 we discuss the negative energy solutions banned by physics, and we deplore that half of the universe escapes us. We present the electro-gravitation in §7, from the equation which represents a super hydrogen atom. In § 8 we show that the global mass (gravitational) is variable: it increases during the expansion while the mass of the elementary particles decreases. In §9 we approach the spontaneous symmetry breaking;when it occurs, the arrows of the equation are momentarily reversed: such a mechanism would apply to the Allais effect, also mentioned in §6.4. §10 and §11 deal with the energy linked by the equation to matter through expansive space-time. The equation transforms electromagnetic kinetic energy into a gravitational mass, considered as a potential energy. Entropy increases according to the arrow of time towards the future. In §12 we discuss of the prevailing theory of inflation. We note the similarity between the proclaimed acceleration of current expansion and inflation. Physicists have interpreted the positive cosmological constant in terms of vacuum energy which would be 10120 times higher than the dark energy density deduced from the astronomical measurements. However, the high theoretical value of the vacuum energy (and the cosmological constant) has no observable pending in the cosmos. In §13 we suggest that these several orders of magnitude difference problem are solved by the theory of relation, which indicates a deceleration of the expansion. Finally, in § 14, we close by speaking of a model of cyclic universe and about the object of this paper, a dynamic equation that allows to build a quantum cosmology.

Estimation of Population Variance Using the Coefficient of Kurtosis and Median of an Auxiliary Variable under Simple Random Sampling

In this study we have proposed a modified ratio type estimator for population variance of the study variable y under simple random sampling without replacement making use of coefficient of kurtosis and median of an auxiliary variable x. The estimator’s properties have been derived up to first order of Taylor’s series expansion. The efficiency conditions derived theoretically under which the proposed estimator performs better than existing estimators. Empirical studies have been done using real populations to demonstrate the performance of the developed estimator in comparison with the existing estimators. The proposed estimator as illustrated by the empirical studies performs better than the existing estimators under some specified conditions i.e. it has the smallest Mean Squared Error and the highest Percentage Relative Efficiency. The developed estimator therefore is suitable to be applied to situations in which the variable of interest has a positive correlation with the auxiliary variable.

Cultural Variables and International Business

By analyzing a set of dynamic variables of culture, this paper reaches the conclusion that there is a link between successful global business and cultural awareness and sensitivity.

Experimental test of error-disturbance uncertainty relation with continuous variables

The uncertainty relation is one of the fundamental principles in quantum mechanics and plays an important role in quantum information science. We experimentally test the error-disturbance uncertainty relation(EDR) with continuous variables for Gaussian states. Two incompatible continuous-variable observables, amplitude and phase quadratures of an optical mode, are measured simultaneously using a heterodyne measurement system.The EDR values with continuous variables for coherent, squeezed, and thermal states are verified experimentally.Our experimental results demonstrate that Heisenberg’s EDR with continuous variables is violated, while Ozawa’s and Branciard’s EDRs with continuous variables are validated.

Subjective Well-Being among Empty-Nest Elderly and Its Related Factors:Taking Guangdong Province as an Example

Objective:To explore the the status of happiness and social support of empty nesters in Guangdong Province and analyze the relationship between the above two variables.Method:Totally 1148 empty nesters(776 males,734 females)from 5 cities in Guangdong province are selected by stratified random sampling and conducted with Memorial University of Newfoundland Scale of Happiness(MUNSH),Social Support Rating Scale(SSRS),Mini-Mental State Examination(MMSE)and a self-edited questionnaire on the general information.Results:The total score of MUNSH is(10.20±6.37).The total score and the scores of the 3 dimensions of objective support,subject support,the use of support in SSRS are(30.79±5.51),(9.24±2.37),(19.38±4.95)and(9.22±2.15)respectively.Multiple variable linear regression show that are positively associated with the total scores of MUNSH(B=.227,.115,.098,.158,.082,respectively,P<.05).was negatively associated with total score of MUNSH(B=-.097,P<.05).Conclusion:It suggests that the sort of leisure,gender,progress rank,family characteristics,such as family economic condition and father’s career may be related factors of undergraduates life satisfaction.

Clustering Categorical Data Based on Within-Cluster Relative Mean Difference

The clustering on categorical variables has received intensive attention. In dataset with categorical features, some features show the superior performance on clustering procedure. In this paper, we propose a simple method to find such distinctive features by comparing pooled within-cluster mean relative difference and then partition the data upon such features and give subspace of the subgroups. The applications on zoo data and soybean data illustrate the performance of the proposed method.

Modeling personalized head-related impulse response using support vector regression

A new customization approach based on support vector regression （SVR） is proposed to obtain individual headrelated impulse response （HRIR） without complex measurement and special equipment. Principal component analysis （PCA） is first applied to obtain a few principal components and corresponding weight vectors correlated with individual anthropometric parameters. Then the weight vectors act as output of the nonlinear regression model. Some measured anthropometric parameters are selected as input of the model according to the correlation coefficients between the parameters and the weight vectors. After the regression model is learned from the training data, the individual HRIR can be predicted based on the measured anthropometric parameters. Compared with a back-propagation neural network （BPNN） for nonlinear regression, better generalization and prediction performance for small training samples can be obtained using the proposed PCA-SVR algorithm.