Asymmetric page split generalized index search trees for formal concept analysis

Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

Substitution of crude cell wall for neutral detergent fibre in the equations of the Cornell Net Carbohydrate and Protein System that predict carbohydrate fractions: application to sunflower (Helianthus annulus L.)

Prediction of carbohydrate fractions using equations from the Cornell Net Carbohydrate and Protein System (CNCPS) is a valuable tool to assess the nutritional value of forages. In this paper these carbohydrate fractions were predicted using data from three sunflower (Helianthus annuus L.) cultivars, fresh or as silage. The CNCPS equations for fractions B(2) and C include measurement of ash and protein-free neutral detergent fibre (NDF) as one of their components. However, NDF lacks pectin and other non-starch polysaccharides that are found in the cell wall (CW) matrix, so this work compared the use of a crude CW preparation instead of NDF in the CNCPS equations. There were no differences in the estimates of fractions B, and C when CW replaced NDF; however there were differences in fractions A and B2. Some of the CNCPS equations could be simplified when using CW instead of NDF Notably, lignin could be expressed as a proportion of DM, rather than on the basis of ash and protein-free NDF, when predicting CNCPS fraction C. The CNCPS fraction B(1) (starch + pectin) values were lower than pectin determined through wet chemistty. This finding, along with the results obtained by the substitution of CW for NDF in the CNCPS equations, suggests that pectin was not part of fraction B(1) but present in fraction A. We suggest that pectin and other non-starch polysaccharides that are dissolved by the neutral detergent solution be allocated to a specific fraction (B2) and that another fraction (B(3)) be adopted for the digestible cell wall carbohydrates.

Decay chain differential equations: Solution through matrix algebra

A matricial method to solve the decay chain differential equations system is presented. The quantity of each nuclide in the chain at a time t may be evaluated by analytical expressions obtained in a simple way using recurrence relations. This method may be applied to problems of radioactive buildup and decay and can be easily implemented computationally. (C) 2009 Elsevier B.V. All rights reserved.

Detection of Herpesviruses and Periodontal Pathogens in Subgingival Plaque of Patients With Chronic Periodontitis, Generalized Aggressive Periodontitis, or Gingivitis

Background: Herpesviruses may be related to the etiology of aggressive periodontitis (AgP) and chronic periodontitis (CP) by triggering periodontal destruction or by increasing the risk for bacterial infection. This case-control study evaluated the presence of herpes simplex virus type 1 (HSV-1), Epstein-Barr virus type 1 (EBV-1), human cytomegalovirus (HCMV), Aggregatibacter actinomycetemcomitans (previously Actinobacillus actinomycetemcomitans), Porphyromonas gingivalis, Prevotella intermedia, and Tannerella forsythia (previously T. forsythensis) in patients with generalized AgP (AgP group), CP (CP group), or gingivitis (G group) and in healthy individuals (C group). Methods: Subgingival plaque samples were collected with paper points from 30 patients in each group. The nested polymerase chain reaction (PCR) method was used to detect HSV-1, EBV-1, and HCMV. Bacteria were identified by 16S rRNA-based PCR. Results: HSV-1, HCMV, and EBV-1 were detected in 86.7%, 46.7%, and 33.3% of the AgP group, respectively; in 40.0%, 50.0%, and 46.7% of the CP group, respectively; in 53.3%, 40.0%, and 20.0% of the G group, respectively; and in 20.0%, 56.7%, and 0.0% of the C group, respectively. A. actinomycetemcomitans was detected significantly more often in the AgP group compared to the other groups (P<0.005). P. gingivalis and T. forsythia were identified more frequently in AgP and CP groups, and AgP, CP, and G groups had higher frequencies of P. intermedia compared to the C group. Conclusion: In Brazilian patients, HSV-1 and EBV-1, rather than HCMV, were more frequently associated with CP and AgP. J Periodontol 2008;79:2313-2321.

Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.

The composite Euler method for stiff stochastic differential equations

In this paper we present the composite Euler method for the strong solution of stochastic differential equations driven by d-dimensional Wiener processes. This method is a combination of the semi-implicit Euler method and the implicit Euler method. At each step either the semi-implicit Euler method or the implicit Euler method is used in order to obtain better stability properties. We give criteria for selecting the semi-implicit Euler method or the implicit Euler method. For the linear test equation, the convergence properties of the composite Euler method depend on the criteria for selecting the methods. Numerical results suggest that the convergence properties of the composite Euler method applied to nonlinear SDEs is the same as those applied to linear equations. The stability properties of the composite Euler method are shown to be far superior to those of the Euler methods, and numerical results show that the composite Euler method is a very promising method. (C) 2001 Elsevier Science B.V. All rights reserved.

A flux ratio theorem for multicomponent linear diffusion equations

Ussing [1] considered the steady flux of a single chemical component diffusing through a membrane under the influence of chemical potentials and derived from his linear model, an expression for the ratio of this flux and that of the complementary experiment in which the boundary conditions were interchanged. Here, an extension of Ussing's flux ratio theorem is obtained for n chemically interacting components governed by a linear system of diffusion-migration equations that may also incorporate linear temporary trapping reactions. The determinants of the output flux matrices for complementary experiments are shown to satisfy an Ussing flux ratio formula for steady state conditions of the same form as for the well-known one-component case. (C) 2000 Elsevier Science Ltd. All rights reserved.

Implicit Taylor methods for stiff stochastic differential equations

In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

Three-point boundary value problems for second-order, ordinary, differential equations

We establish existence results for solutions to three-point boundary value problems for nonlinear, second-order, ordinary differential equations with nonlinear boundary conditions. (C) 2001 Elsevier Science Ltd. All rights reserved.

Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.