A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

Appropriate choice of aggregation operators in fuzzy decision support systems

Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision that are ever present in decision support and expert systems in many areas. The choice of aggregation operators is crucial to the behavior of the system that is intended to mimic human decision making. This paper discusses how aggregation operators can be selected and adjusted to fit empirical data—a series of test cases. Both parametric and nonparametric regression are considered and compared. A practical application of the proposed methods to electronic implementation of clinical guidelines is presented

Improving the performance of equalization in communication systems

In this paper, research on exploring the potential of several popular equalization techniques while overcoming their disadvantages has been conducted. First, extensive literature survey on equalization is conducted. The focus has been placed on several popular linear equalization algorithm such as the conventional least-mean-square (LMS) algorithm, the recursive least squares (RLS) algorithm, the fi1tered-X LMS algorithm and their development. The approach in analysing the performance of the filtered-X LMS Algorithm, a heuristic method based on linear time-invariant operator theory is provided to analyse the robust perfonnance of the filtered-X structure. It indicates that the extra filter could enhance the stability margin of the corresponding non filtered X structure. To overcome the slow convergence problem while keeping the simplicity of the LMS based algorithms, an H2 optimal initialization is proposed.

Methods of construction of OWA operators from data

This paper investigates the problem of obtaining the weights of the ordered weighted aggregation (OWA) operators from observations. The problem is formulated as a restricted least squares and uniform approximation problems. We take full advantage of the linearity of the problem. In the former case, a well known technique of non-negative least squares is used. In a case of uniform approximation, we employ a recently developed cutting angle method of global optimisation. Both presented methods give results superior to earlier approaches, and do not require complicated nonlinear constructions. Additional restrictions, such as degree of orness of the operator, can be easily introduced

A new method for locating the global optimum : application of the cutting angle method to molecular structure prediction

Many problems in chemistry depend on the ability to identify the global minimum or maximum of a function. Examples include applications in chemometrics, optimization of reaction or operating conditions, and non-linear least-squares analysis. This paper presents the results of the application of a new method of deterministic global optimization, called the cutting angle method (CAM), as applied to the prediction of molecular geometries. CAM is shown to be competitive with other global optimization techniques for several benchmark molecular conformation problem. CAM is a general method that can also be applied to other computational problems involving global minima, global maxima or finding the roots of nonlinear equations.

Application of fast and robust equalization in communication technology

In this paper, the authors explore the potential of several popular equalization techniques while overcoming their disadvantages. First, extensive literature survey on equalization is conducted. The focus is on popular linear equalization algorithms such as the conventional least-mean-square (LMS) algorithm , The recursive least-squares (RLS) algorithm, the filtered-X LMS algorithm and their development. To overcome the slow convergence problem while keeping the simplicity of the LMS based algorithms, an H2 optimal initialization is proposed.

Institutional ownership and firm performance: evidence from Finland

This paper investigates the relationship between different classes of institutional investors and firm performance. Using industry level data from Finland, which is characterized by various institutional investors who own multiple ownership stakes in different firms across a broad spectrum of industries, the paper exhibits two novelties. First, unlike previous studies which treated institutional investors as a monolithic group, we segment them in classes. Second, we recognize the joint determination of firm performance and institutional ownership. We account for this issue in the context of a system of equations, using three stage least squares methodology. The empirical results suggest a significant two-way feedback between firm performance and institutional equity ownership. However, this effect is not symmetric. We find that institutional investors with likely investment and business ties with firms have adverse (negative) effect on firm performance and the impact is very significant in comparison to the negative effect of firm performance on institutional ownership.

The effect of osteoporotic vertebral fracture of predicted spinal loads in vivo

he aetiology of osteoporotic vertebral fractures is multi-factorial, and cannot be explained solely by low bone mass. After sustaining an initial vertebral fracture, the risk of subsequent fracture increases greatly. Examination of physiologic loads imposed on vertebral bodies may help to explain a mechanism underlying this fracture cascade. This study tested the hypothesis that model-derived segmental vertebral loading is greater in individuals who have sustained an osteoporotic vertebral fracture compared to those with osteoporosis and no history of fracture. Flexion moments, and compression and shear loads were calculated from T2 to L5 in 12 participants with fractures (66.4 ± 6.4 years, 162.2 ± 5.1 cm, 69.1 ± 11.2 kg) and 19 without fractures (62.9 ± 7.9 years, 158.3 ± 4.4 cm, 59.3 ± 8.9 kg) while standing. Static analysis was used to solve gravitational loads while muscle-derived forces were calculated using a detailed trunk muscle model driven by optimization with a cost function set to minimise muscle fatigue. Least squares regression was used to derive polynomial functions to describe normalised load profiles. Regression co-efficients were compared between groups to examine differences in loading profiles. Loading at the fractured level, and at one level above and below, were also compared between groups. The fracture group had significantly greater normalised compression (p = 0.0008) and shear force (p < 0.0001) profiles and a trend for a greater flexion moment profile. At the level of fracture, a significantly greater flexion moment (p = 0.001) and shear force (p < 0.001) was observed in the fracture group. A greater flexion moment (p = 0.003) and compression force (p = 0.007) one level below the fracture, and a greater flexion moment (p = 0.002) and shear force (p = 0.002) one level above the fracture was observed in the fracture group. The differences observed in multi-level spinal loading between the groups may explain a mechanism for increased risk of subsequent vertebral fractures. Interventions aimed at restoring vertebral morphology or reduce thoracic curvature may assist in normalising spine load profiles.

The effects of clustered data on standard error estimates in covariance structure analysis : a field data application

Purpose – The purpose of this article is to present an empirical analysis of complex sample data with regard to the biasing effect of non-independence of observations on standard error parameter estimates. Using field data structured in the form of repeated measurements it is to be shown, in a two-factor confirmatory factor analysis model, how the bias in SE can be derived when the non-independence is ignored.

Design/methodology/approach – Three estimation procedures are compared: normal asymptotic theory (maximum likelihood); non-parametric standard error estimation (naïve bootstrap); and sandwich (robust covariance matrix) estimation (pseudo-maximum likelihood).

Findings – The study reveals that, when using either normal asymptotic theory or non-parametric standard error estimation, the SE bias produced by the non-independence of observations can be noteworthy.

Research limitations/implications – Considering the methodological constraints in employing field data, the three analyses examined must be interpreted independently and as a result taxonomic generalisations are limited. However, the study still provides “case study” evidence suggesting the existence of the relationship between non-independence of observations and standard error bias estimates.

Originality/value – Given the increasing popularity of structural equation models in the social sciences and in particular in the marketing discipline, the paper provides a theoretical and practical insight into how to treat repeated measures and clustered data in general, adding to previous methodological research. Some conclusions and suggestions for researchers who make use of partial least squares modelling are also drawn.

Position estimation and tracking of an autonomous mobile sensor using received signal strength

In this paper, an algorithm for approximating the path of a moving autonomous mobile sensor with an unknown position location using Received Signal Strength (RSS) measurements is proposed. Using a Least Squares (LS) estimation method as an input, a Maximum-Likelihood (ML) approach is used to determine the location of the unknown mobile sensor. For the mobile sensor case, as the sensor changes position the characteristics of the RSS measurements also change; therefore the proposed method adapts the RSS measurement model by dynamically changing the pass loss value alpha to aid in position estimation. Secondly, a Recursive Least-Squares (RLS) algorithm is used to estimate the path of a moving mobile sensor using the Maximum-Likelihood position estimation as an input. The performance of the proposed algorithm is evaluated via simulation and it is shown that this method can accurately determine the position of the mobile sensor, and can efficiently track the position of the mobile sensor during motion.

The cost of granting executive stock options with strike prices adjusted by the cost of capital

Purpose – The purpose of this paper is to estimate the cost of granting executive stocks with strike prices adjusted by the cost of capital.

Design/methodology/approach – In the paper a Monte Carlo simulation approach developed in Longstaff and Schwartz is used in conjunction with the subjective valuation model developed in Ingersoll to value these executive stock options that are subject to performance hurdles.

Findings – The paper finds that standard European Black-Scholes-Merton option values overstate the true cost to the firm of granting these executive stock options. The option values also decrease with a higher dividend yield, a higher performance hurdle, a longer vesting period, and a shorter maturity.

Research limitations/implications – While the study in the paper is limited to the valuation of executive options, the methodology can be used to study incentive effects of executive stock options that have a performance hurdle.

Practical implications – The approach used in this paper to estimate the cost of granting executive stock options is a clear improvement over standard European option pricing approaches that often result in biased estimates.

Originality/value – This paper presents a first attempt to integrate the Ingersoll utility-theoretic model and the Longstaff and Schwartz least squares Monte Carlo algorithm to estimate the subjective value and the objective cost of executive stock options with a performance hurdle. This valuation approach will be useful in the study of other types of executive compensation.

A generalized data windowing scheme for adaptive conjugate gradient algorithms

The performance of the modified adaptive conjugate gradient (CG) algorithms based on the iterative CG method for adaptive filtering is highly related to the ways of estimating the correlation matrix and the cross-correlation vector. The existing approaches of implementing the CG algorithms using the data windows of exponential form or sliding form result in either loss of convergence or increase in misadjustment. This paper presents and analyzes a new approach to the implementation of the CG algorithms for adaptive filtering by using a generalized data windowing scheme. For the new modified CG algorithms, we show that the convergence speed is accelerated, the misadjustment and tracking capability comparable to those of the recursive least squares (RLS) algorithm are achieved. Computer simulations demonstrated in the framework of linear system modeling problem show the improvements of the new modifications.

On institutional ownership and firm performance : a disaggregated view

We study the relationship between institutional ownership and firm performance in Finland. A systems approach is employed to investigate the potential two-way causality between firm performance and ownership structure. Three-stage least squares estimation technique is used to solve for the systems. The evidence suggests an endogeneity problem between firm performance and institutional ownership. However, the magnitude of the problem differs with respect to the concentration of ownership measure used. Our results show that a more equal distribution of the voting power among the largest institutional stakeholder may exert positive effects on firm performance. We also find a significant difference relating to firm performances and equity ownerships between the two classes of institutional investor. Consistent with the ownership structure in Finland, we find that a simple ownership concentration index does not influence firm performance.

Impact of electronic data interchange in the Australian automotive industry

Information technology continues to play an increasingly significant role in the development of firms competing in the vast array of markets from those classified as global markets, such as the automotive industry, to the smaller nationally-based markets such as retailing. An objective of electronic commerce is to assist organisations to remain competitive and gain entry to markets which were previously unattainable. This study focuses on the organisational impact of one form of electronic commerce (electronic data interchange) on the component sector of the Australian automotive industry and examines the extent to which trading partner relationships have been affected. The research investigates the extent to which the integration of electronic data interchange (EDI) with an organisation’s internal application system may facilitate specific net benefits. The automotive industry became the first Australian industry to cooperatively adopt EDI. Research to date has not adequately examined the organisational impact of the nature and extent of net benefits gained from EDI adoption. To achieve the objective of assessing EDI net benefits, a conceptual model was developed. The model proposed that the level of EDI net benefits expected is influenced by the size of the organisation and the concentration of trade achieved within the industry via intervening links through (a) the level of senior management commitment and (b) the extent of system integration. Nine empirically testable research propositions are derived from the model, each testing the relationship between model constructs. Data was collected from 114 component suppliers to Ford Australia in 1992 and 1994 using a repeated cross-sectional longitudinal design. Structural equation modelling using partial least squares was adopted in the analysis of the data. A pure longitudinal model together with 12 case studies of selected component manufacturers supplemented the research design. The results of the research showed that the proposed conceptual model is a good description of the data. In particular, net benefits obtained from EDI adoption are directly determined by the size of the organisation, and the extent to which firms integrate EDI into their internal application systems. The level of net benefits is only indirectly influenced by the level of senior management commitment to the EDI project through (a) management commitment’s direct effect on integration, and (b) the direct effect the volume of trade a supplier achieves with the automotive industry on senior management commitment and system integration. The major benefits organisations experienced from EDI were enhanced productivity, clerical staff savings, improved data accuracy, enhanced customer service and reduced administration costs. The research showed that few suppliers gained inventory savings from EDI, a frequently claimed benefit from EDI adoption. Evidence of small improvements in product quality emerged from the results. In summary, this research attempts to make two primary contributions to knowledge, first in providing a method by which net benefits from electronic commerce can be measured within an industry adopting electronic trading, and second, by providing organisations with the knowledge of the specific net benefits organisations could expect from EDI adoption, together with the four major factors affecting these benefits. The research concludes with possible directions for future research, in particular an assessment of the impact of incorporating financial EDI into electronic trading.

Fourier transform infrared microspectroscopy as a tool to identify macroalgal propagules

Understanding of macroalgal dispersal has been hindered by the difficulty in identifying propagules. Different carrageenans typically occur in gametophytes and tetrasporophytes of the red algal family Gigartinaceae, and we may expect that carpospores and tetraspores also differ in composition of carrageenans. Using Fourier transform infrared (FT-IR) microspectroscopy, we tested the model that differences in carrageenans and other cellular constituents between nuclear phases should allow us to discriminate carpospores and tetraspores of Chondrus verrucosus Mikami. Spectral data suggest that carposporophytes isolated from the pericarp and female gametophytes contained κ-carrageenan, whereas tetrasporophytes contained λ-carrageenan. However, both carpospores and tetraspores exhibited absorbances in wave bands characteristic of κ-,ι-, and λ-carrageenans. Carpospores contained more proteins and may be more photosynthetically active than tetraspores, which contained more lipid reserves. We draw analogies to planktotrophic and lecithotrophic larvae. These differences in cellular chemistry allowed reliable discrimination of spores, but pretreatment of spectral data affected the accuracy of classification. The best classification of spores was achieved with extended multiplicative signal correction (EMSC) pretreatment using partial least squares discrimination analysis, with correct classification of 86% of carpospores and 83% of tetraspores. Classification may be further improved by using synchrotron FT-IR microspectroscopy because of its inherently higher signal-to-noise ratio compared with microspectroscopy using conventional sources of IR. This study demonstrates that FT-IR microspectroscopy and bioinformatics are useful tools to advance our understanding of algal dispersal ecology through discrimination of morphologically similar propagules both within and potentially between species.