Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Genetic and economic analysis of a targeted marker-assisted wheat breeding strategy

The advent of molecular markers as a tool to aid selection has provided plant breeders with the opportunity to rapidly deliver superior genetic solutions to problems in agricultural production systems. However, a major constraint to the implementation of marker-assisted selection (MAS) in pragmatic breeding programs in the past has been the perceived high relative cost of MAS compared to conventional phenotypic selection. In this paper, computer simulation was used to design a genetically effective and economically efficient marker-assisted breeding strategy aimed at a specific outcome. Under investigation was a strategy involving the integration of both restricted backcrossing and doubled haploid (DH) technology. The point at which molecular markers are applied in a selection strategy can be critical to the effectiveness and cost efficiency of that strategy. The application of molecular markers was considered at three phases in the strategy: allele enrichment in the BC1F1 population, gene selection at the haploid stage and the selection for recurrent parent background of DHs prior to field testing. Overall, incorporating MAS at all three stages was the most effective, in terms of delivering a high frequency of desired outcomes and at combining the selected favourable rust resistance, end use quality and grain yield alleles. However, when costs were included in the model the combination of MAS at the BC1F1 and haploid stage was identified as the optimal strategy. A detailed economic analysis showed that incorporation of marker selection at these two stages not only increased genetic gain over the phenotypic alternative but actually reduced the over all cost by 40%.

Does pharmacogenomics provide an ethical challenge to the utilisation of cost-effectiveness analysis by public health systems?

Pharmacogenomics promotes an understanding of the genetic basis for differences in efficacy or toxicity of drugs in different individuals. Implementation of the outcomes of pharmacogenomic research into clinical practice presents a number of difficulties for healthcare. This paper aims to highlight one of the Unique ethical challenges which pharmacogenomics presents for the utilisation of cost-effectiveness analysis by public health systems. This paper contends that pharmacogenomics provides a challenge to fundamental principles which underlie most systems for deciding which drugs should be publicly subsidised. Pharmacogenomics brings into focus the conflict between equality and utility in the context of using cost-effectiveness analysis to aid distribution of a limited national drug budget.

An implementation of genetic algorithms as a basis for a trading system on the foreign exchange market

Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process is very helpful. In this paper, we try to create such a system with a genetic algorithm engine to emulate trader behaviour on the foreign exchange market and to find the most profitable trading strategy.

Mutation analysis to verify feature matrices for isolating errors in simulation models

Software simulation models are computer programs that need to be verified and debugged like any other software. In previous work, a method for error isolation in simulation models has been proposed. The method relies on a set of feature matrices that can be used to determine which part of the model implementation is responsible for deviations in the output of the model. Currrently these feature matrices have to be generated by hand from the model implementation, which is a tedious and error-prone task. In this paper, a method based on mutation analysis, as well as prototype tool support for the verification of the manually generated feature matrices is presented. The application of the method and tool to a model for wastewater treatment shows that the feature matrices can be verified effectively using a minimal number of mutants.

Critical feature analysis of a radiotherapy machine

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An `assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code.

Spectroscopic analysis of terrestrial analogues for the interpretation of surface composition of rocky bodies in the solar system. Effects of mineral mixing and particle size. Applications to moon, mars and implications for mercury.

Among the Solar System’s bodies, Moon, Mercury and Mars are at present, or have been in the recent years, object of space missions aimed, among other topics, also at improving our knowledge about surface composition. Between the techniques to detect planet’s mineralogical composition, both from remote and close range platforms, visible and near-infrared reflectance (VNIR) spectroscopy is a powerful tool, because crystal field absorption bands are related to particular transitional metals in well-defined crystal structures, e.g., Fe2+ in M1 and M2 sites of olivine or pyroxene (Burns, 1993). Thanks to the improvements in the spectrometers onboard the recent missions, a more detailed interpretation of the planetary surfaces can now be delineated. However, quantitative interpretation of planetary surface mineralogy could not always be a simple task. In fact, several factors such as the mineral chemistry, the presence of different minerals that absorb in a narrow spectral range, the regolith with a variable particle size range, the space weathering, the atmosphere composition etc., act in unpredictable ways on the reflectance spectra on a planetary surface (Serventi et al., 2014). One method for the interpretation of reflectance spectra of unknown materials involves the study of a number of spectra acquired in the laboratory under different conditions, such as different mineral abundances or different particle sizes, in order to derive empirical trends. This is the methodology that has been followed in this PhD thesis: the single factors previously listed have been analyzed, creating, in the laboratory, a set of terrestrial analogues with well-defined composition and size. The aim of this work is to provide new tools and criteria to improve the knowledge of the composition of planetary surfaces. In particular, mixtures composed with different content and chemistry of plagioclase and mafic minerals have been spectroscopically analyzed at different particle sizes and with different mineral relative percentages. The reflectance spectra of each mixture have been analyzed both qualitatively (using the software ORIGIN®) and quantitatively applying the Modified Gaussian Model (MGM, Sunshine et al., 1990) algorithm. In particular, the spectral parameter variations of each absorption band have been evaluated versus the volumetric FeO% content in the PL phase and versus the PL modal abundance. This delineated calibration curves of composition vs. spectral parameters and allow implementation of spectral libraries. Furthermore, the trends derived from terrestrial analogues here analyzed and from analogues in the literature have been applied for the interpretation of hyperspectral images of both plagioclase-rich (Moon) and plagioclase-poor (Mars) bodies.

The precursors and impacts of BSR on AMT acquisition and implementation

This paper reports on the results of research into the connections between transaction attributes and buyer-supplier relationships (BSRs) in advanced manufacturing technology (AMT) acquisition and implementation. The investigation began by examining the impact of the different patterns of BSR on the performance of the AMT acquisition. In understanding the phenomena, the study drew upon and integrated the literature of transaction cost economics theory, BSRs, and AMT, and used this as the basis for a theoretical framework and hypotheses development. This framework was then empirically tested using data that were gathered through a questionnaire survey with 147 companies and analyzed using a structural equation modeling technique. The results of the analysis indicated that the higher the level of technological specificity and uncertainty, the more firms are likely to engage in a stronger relationship with technology suppliers. However, the complexity of the technology being implemented was associated with BSR only indirectly through its association with the level of uncertainty (which has a direct impact upon BSR). The analysis also provided strong support for the premise that developing strong BSR could lead to an improved performance in acquiring and implementing AMT. The implications of the study are offered for both the academic and practitioner audience.

Integrated approach to project feasibility analysis:a case study

Feasibility studies of industrial projects consist of multiple analyses carried out sequentially. This is time consuming and each analysis screens out alternatives based solely on the merits of that analysis. In cross-country petroleum pipeline project selection, market analysis determines throughput requirement and supply and demand points. Technical analysis identifies technological options and alternatives for pipe-line routes. Economic and financial analysis derive the least-cost option. The impact assessment addresses environmental issues. The impact assessment often suggests alternative sites, routes, technologies, and/or implementation methodology, necessitating revision of technical and financial analysis. This report suggests an integrated approach to feasibility analysis presented as a case application of a cross-country petroleum pipeline project in India.

Risk based decision support system for effective implementation of projects

Conventional project management techniques are not always sufficient to ensure time, cost and quality achievement of large-scale construction projects due to complexity in planning, design and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in government policies and regulations, unforeseen inflation, underestimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk management throughout the project's life cycle. However, the effectiveness of risk management depends on the technique through which the effects of risk factors are analysed/quantified. This study proposes the Analytic Hierarchy Process (AHP), a multiple attribute decision making technique, as a tool for risk analysis because it can handle subjective as well as objective factors in a decision model that are conflicting in nature. This provides a decision support system (DSS) to project management for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and a competitive business environment. The whole methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Managing healthcare quality using logical framework analysis

Purpose - The purpose of this paper is to develop an integrated quality management model that identifies problems, suggests solutions, develops a framework for implementation and helps to evaluate dynamically healthcare service performance. Design/methodology/approach - This study used the logical framework analysis (LFA) to improve the performance of healthcare service processes. LFA has three major steps - problems identification, solution derivation, and formation of a planning matrix for implementation. LFA has been applied in a case-study environment to three acute healthcare services (Operating Room utilisation, Accident and Emergency, and Intensive Care) in order to demonstrate its effectiveness. Findings - The paper finds that LFA is an effective method of quality management of hospital-based healthcare services. Research limitations/implications - This study shows LFA application in three service processes in one hospital. This very limited population sample needs to be extended. Practical implications - The proposed model can be implemented in hospital-based healthcare services in order to improve performance. It may also be applied to other services. Originality/value - Quality improvement in healthcare services is a complex and multi-dimensional task. Although various quality management tools are routinely deployed for identifying quality issues in healthcare delivery, they are not without flaws. There is an absence of an integrated approach, which can identify and analyse issues, provide solutions to resolve those issues, develop a project management framework to implement those solutions. This study introduces an integrated and uniform quality management tool for healthcare services. © Emerald Group Publishing Limited.

An empirical investigation of the UK stock market response to the implementation of SSAP 20

This study presents an empirical investigation of the UK stock market response to the im-plementation of the UK Statement of Standard Accounting Practice (SSAP) No. 20 “Foreign Cur-rency Translation” (issued in April 1983). Such an empirical investigation has not yet been under-taken for the UK. Our results show that the stock market generally appeared to have anticipatedthe implementation of SSAP 20. For the aggregate set of adopters, we found a positive stock mar-ket response in the official year of adoption, reflecting the appreciation of the income-stabilisingeffects of the standard. This paper also presents a cross-sectional analysis that tests for a relation-ship between the stock returns and the accounting measures of those firms that adopted SSAP 20.We found a significant relation between the stock returns and the related accounting measures inthe actual adoption period of the aggregate set of adopters. This study generally focuses on theinterpretation of the financial impacts of the various accounting choices of firms within their fi-nancial and economic environments.

Time complexity and convergence analysis of domain theoretic Picard method

We present an implementation of the domain-theoretic Picard method for solving initial value problems (IVPs) introduced by Edalat and Pattinson [1]. Compared to Edalat and Pattinson's implementation, our algorithm uses a more efficient arithmetic based on an arbitrary precision floating-point library. Despite the additional overestimations due to floating-point rounding, we obtain a similar bound on the convergence rate of the produced approximations. Moreover, our convergence analysis is detailed enough to allow a static optimisation in the growth of the precision used in successive Picard iterations. Such optimisation greatly improves the efficiency of the solving process. Although a similar optimisation could be performed dynamically without our analysis, a static one gives us a significant advantage: we are able to predict the time it will take the solver to obtain an approximation of a certain (arbitrarily high) quality.

Has DRG payment influenced the technical efficiency and productivity of diagnostic technologies in Portuguese public hospitals? An empirical analysis using parametric and non‐parametric methods

The use of Diagnosis Related Groups (DRG) as a mechanism for hospital financing is a currently debated topic in Portugal. The DRG system was scheduled to be initiated by the Health Ministry of Portugal on January 1, 1990 as an instrument for the allocation of public hospital budgets funded by the National Health Service (NHS), and as a method of payment for other third party payers (e.g., Public Employees (ADSE), private insurers, etc.). Based on experience from other countries such as the United States, it was expected that implementation of this system would result in more efficient hospital resource utilisation and a more equitable distribution of hospital budgets. However, in order to minimise the potentially adverse financial impact on hospitals, the Portuguese Health Ministry decided to gradually phase in the use of the DRG system for budget allocation by using blended hospitalspecific and national DRG casemix rates. Since implementation in 1990, the percentage of each hospitals budget based on hospital specific costs was to decrease, while the percentage based on DRG casemix was to increase. This was scheduled to continue until 1995 when the plan called for allocating yearly budgets on a 50% national and 50% hospitalspecific cost basis. While all other nonNHS third party payers are currently paying based on DRGs, the adoption of DRG casemix as a National Health Service budget setting tool has been slower than anticipated. There is now some argument in both the political and academic communities as to the appropriateness of DRGs as a budget setting criterion as well as to their impact on hospital efficiency in Portugal. This paper uses a twostage procedure to assess the impact of actual DRG payment on the productivity (through its components, i.e., technological change and technical efficiency change) of diagnostic technology in Portuguese hospitals during the years 1992–1994, using both parametric and nonparametric frontier models. We find evidence that the DRG payment system does appear to have had a positive impact on productivity and technical efficiency of some commonly employed diagnostic technologies in Portugal during this time span.