Thermodynamic scaling theory for the two-impurity Anderson model

We present results of a study of the two-impurity Anderson model using a thermodynamic scaling theory developed recently. The model is characterized by the Coulomb energy U, the orbital energy epsilond, the d-level width Gamma, and the separation between impurities R. If Gamma<<−epsilond<over a restricted range of kFR. In this case impurity-impurity interactions can be substantial. The other interesting case is when the impurities have a ''fluctuating valence'' with the singlet lying lower in energy, i.e., epsilond>~Gamma. Here we find that the single-impurity physics dominates the low-temperature behavior, and impurity-impurity interactions are perturbative. The qualitative features of the temperature-dependent susceptibility are discussed. Journal of Applied Physics is copyrighted by The American Institute of Physics.

Molecular Pathways of Disturbed Sleep and Depression: Studies on Adenosine and Gene Expression Patterns

Background: Adenosine is a potent sleep-promoting substance, and one of its targets is the basal forebrain. Fairly little is known about its mechanism of action in the basal forebrain and about the receptor subtype mediating its regulating effects on sleep homeostasis. Homeostatic deficiency might be one of the causes of the profoundly disturbed sleep pattern in major depressive disorder, which could explain the reduced amounts of delta-activity-rich stages 3 and 4. Since major depression has a relatively high heritability, and on the other hand adenosine regulates sleep homeostasis and might also be involved in mood modulation, adenosine-related genes should be considered for their possible contribution to a predisposition for depression and disturbed sleep in humans. Depression is a complex disorder likely involving the abnormal functioning of several genes. Novel target genes which could serve as the possible common substrates for depression and comorbid disturbed sleep should be identified. In this way specific brain areas related to sleep regulation should be studied by using animal model of depression which represents more homogenous phenotype as compared to humans. It is also important to study these brain areas during the development of depressive-like features to understand how early changes could facilitate pathophysiological changes in depression. Aims and methods: We aimed to find out whether, in the basal forebrain, adenosine induces recovery non-rapid eye movement (NREM) sleep after prolonged waking through the A1 or/and A2A receptor subtype. A1 and A2A receptor antagonists were perfused into the rat basal forebrain during 3 h of sleep deprivation, and the amount of NREM sleep and delta power during recovery NREM sleep were analyzed. We then explored whether polymorphisms in genes related to the metabolism, transport and signaling of adenosine could predispose to depression accompanied by signs of disturbed sleep. DNA from 1423 individuals representative of the Finnish population and including controls and cases with depression, depression accompanied by early morning awakenings and depression accompanied by fatigue, was used in the study to investigate the possible association between polymorphisms from adenosine-related genes and cases. Finally to find common molecular substrates of depression and disturbed sleep, gene expression changes were investigated in specific brain areas in the rat clomipramine model of depression. We focused on the basal forebrain of 3-week old clomipramine-treated rats which develop depressive-like symptoms later in adulthood and on the hypothalamus of adult female clomipramine-treated rats. Results: Blocking of the A1 receptor during sleep deprivation resulted in a reduction of the recovery NREM sleep amount and delta power, whereas A2A receptor antagonism had no effect. Polymorphisms in adenosine-related genes SLC29A3 (equilibrative nucleoside transporter type 3) in women and SLC28A1 (concentrative nucleoside transporter type 1) in men associated with depression alone as well as when accompanied by early morning awakenings and fatigue. In Study III the basal forebrain of postnatal rats treated with clomipramine displayed disturbances in gamma-aminobutyric acid (GABA) receptor type A signaling, in synaptic transmission and possible epigenetic changes. CREB1 was identified as a common transcription denominator which also mediates epigenetic regulation. In the hypothalamus the major changes included the expression of genes in GABA-A receptor pathway, K+ channel-related, glutamatergic and mitochondrial genes, as well as an overexpression of genes related to RNA and mRNA processing. Conclusions: Adenosine plays an important role in sleep homeostasis by promoting recovery NREM sleep via the A1 receptor subtype in the basal forebrain. Also adenosine levels might contribute to the risk of depression with disturbed sleep, since the genes encoding nucleoside transporters showed the strongest associations with depression alone and when accompanied by signs of disturbed sleep in both women and men. Sleep and mood abnormalities in major depressive disorder could be a consequence of multiple changes at the transcriptional level, GABA-A receptor signaling and synaptic transmission in sleep-related basal forebrain and the hypothalamus.

New molecular strategies for prevention of fibroproliferative vascular disease : An experimental approach to restenosis

Vascular intimal hyperplasia is a major complication following angioplasty. The hallmark feature of this disorder is accumulation of dedifferentiated smooth muscle cells (SMCs) to the luminal side of the injured artery, cellular proliferation, migration, and synthesis of extracellular matrix. This finally results in intimal hyperplasia, which is currently considered an untreatable condition. According to current knowledge, a major part of neointimal cells derive from circulating precursor cells. This has outdated the traditional in vitro cell culture methods of studying neointimal cell migration and proliferation using cultured medial SMCs. Somatostatin and some of its analogs with different selectivity for the five somatostatin receptors (sst1 through sst5) have been shown to have vasculoprotective properties in animal studies. However, clinical trials using analogs selective for sst2/sst3/sst5 to prevent restenosis after percutaneous transluminal coronary angioplasty (PTCA) have failed to show any major benefits. Sirolimus is a cell cycle inhibitor that has been suggested to act synergistically with the protein-tyrosine kinase inhibitor imatinib to inhibit intimal hyperplasia in rat already at well-tolerated submaximal oral doses. The mechanisms behind this synergy and its long-term efficacy are not known. The aim of this study was to set up an ex vivo vascular explant culture model to measure neointimal cell activity without excluding the participation of circulating progenitor cells. Furthermore, two novel potential vasculoprotective treatment strategies were evaluated in detail in rat models of intimal hyperplasia and in the ex vivo explant model: sst1/sst4-selective somatostatin receptor analogs and combination treatment with sirolimus and imatinib. This study shows how whole vessel explants can be used to study the kinetics of neointimal cells and their progenitors, and to evaluate the anti-migratory and anti-proliferative properties of potential vasculoprotective compounds. It also shows how the influx of neointimal progenitor cells occurs already during the first days after vascular injury, how the contribution of cell migration is more important in the injury response than cell proliferation, and how the adventitia actively contribute in vascular repair. The vasculoprotective effect of somatostatin is mediated preferentially through sst4, and through inhibition of cell migration rather than of proliferation, which may explain why sst2/sst3/sst5-selective analogs have failed in clinical trials. Furthermore, a brief early oral treatment with the combination of sirolimus and imatinib at submaximal doses results in long-term synergistic suppression of intimal hyperplasia. The synergy is a result of inhibition of post-operative thrombocytosis and leukocytosis, inhibition of neointimal cell migration to the injury-site, and maintenance of cell integrity by inhibition of apoptosis and SMC dedifferentiation. In conclusion, the influx of progenitor cells already during the first days after injury and the high neointimal cell migratory activity underlines the importance of early therapeutic intervention with anti-migratory compounds to prevent neointimal hyperplasia. Sst4-selective analogs and the combination therapy with sirolimus and imatinib represent potential targets for the development of such vasculoprotective therapies.

Molecular Interactions Underlying Neuronal Ceroid Lipofuscinoses CLN1 and CLN5

Disorders resulting from degenerative changes in the nervous system are progressive and incurable. Both environmental and inherited factors affect neuron function, and neurodegenerative diseases are often the sum of both factors. The cellular events leading to neuronal death are still mostly unknown. Monogenic diseases can offer a model for studying the mechanisms of neurodegeneration. Neuronal ceroid lipofuscinoses, or NCLs, are a group of monogenic, recessively inherited diseases affecting mostly children. NCLs cause severe and specific loss of neurons in the central nervous system, resulting in the deterioration of motor and mental skills and leading to premature death. In this thesis, the focus has been on two forms of NCL, the infantile NCL (INCL, CLN1) and the Finnish variant of late infantile NCL (vLINCLFin, CLN5). INCL is caused by mutations in the CLN1 gene encoding for the PPT1 (palmitoyl protein thioesterase 1) enzyme. PPT1 removes a palmitate moiety from proteins in experimental conditions, but its substrates in vivo are not known. In the Finnish variant of late infantile NCL (vLINCLFin), the CLN5 gene is defective, but the function of the encoded CLN5 has remained unknown. The aim of this thesis was to elucidate the disease mechanisms of these two NCL diseases by focusing on the molecular interactions of the defective proteins. In this work, the first interaction partner for PPT1, the mitochondrial F1-ATP synthase, was described. This protein has been linked to HDL metabolism in addition to its well-known role in the mitochondrial energy production. The connection between PPT1 and the F1-ATP synthase was studied utilizing the INCL-disease model, the genetically modified Ppt1-deficient mice. The levels of F1-ATP synthase subunits were increased on the surface of Ppt1-deficient neurons when compared to controls. We also detected several changes in lipid metabolism both at the cellular and systemic levels in Ppt1-deficient mice when compared to controls. The interactions between different NCL proteins were also elucidated. We were able to detect novel interactions between CLN5 and other NCL proteins, and to replicate the previously reported interactions. Some of the novel interactions influenced the intracellular trafficking of the proteins. The multiple interactions between CLN5 and other NCL proteins suggest a connection between the NCL subtypes at the cellular level. The main results of this thesis elicit information about the neuronal function of PPT1. The connection between INCL and neuronal lipid metabolism introduces a new perspective to this rather poorly characterized subject. The evidence of the interactions between NCL proteins provides the basis for future research trying to untangle the NCL disease mechanisms and to develop strategies for therapies.

Management of multi-scale forest resource data over time

During the last decades there has been a global shift in forest management from a focus solely on timber management to ecosystem management that endorses all aspects of forest functions: ecological, economic and social. This has resulted in a shift in paradigm from sustained yield to sustained diversity of values, goods and benefits obtained at the same time, introducing new temporal and spatial scales into forest resource management. The purpose of the present dissertation was to develop methods that would enable spatial and temporal scales to be introduced into the storage, processing, access and utilization of forest resource data. The methods developed are based on a conceptual view of a forest as a hierarchically nested collection of objects that can have a dynamically changing set of attributes. The temporal aspect of the methods consists of lifetime management for the objects and their attributes and of a temporal succession linking the objects together. Development of the forest resource data processing method concentrated on the extensibility and configurability of the data content and model calculations, allowing for a diverse set of processing operations to be executed using the same framework. The contribution of this dissertation to the utilisation of multi-scale forest resource data lies in the development of a reference data generation method to support forest inventory methods in approaching single-tree resolution.

Evaluation of super-heated steam vacuum drying viability and development of a predictive drying model for four Australian hardwood species.

The results of drying trials show that vacuum drying produces material of the same or better quality than is currently being produced by conventional methods within 41 to 66 % of the drying time, depending on the species. Economic analysis indicates positive or negative results depending on the species and the size of drying operation. Definite economic benefits exist by vacuum drying over conventional drying for all operation sizes, in terms of drying quality, time and economic viability, for E. marginata and E. pilularis. The same applies for vacuum drying C. citriodora and E. obliqua in larger drying operations (kiln capacity 50 m3 or above), but not for smaller operations at this stage. Further schedule refinement has the ability to reduce drying times further and may improve the vacuum drying viability of the latter species in smaller operations.

A Modified Heffron-Phillip's Model for The Design of Power System Stabilizers

In this paper a modified Heffron-Phillip's (K-constant) model is derived for the design of power system stabilizers. A knowledge of external system parameters, such as equivalent infinite bus voltage and external impedances or their equivalent estimated values is required for designing a conventional power system stabilizer. In the proposed method, information available at the secondary bus of the step-up transformer is used to set up a modified Heffron-Phillip's (ModHP) model. The PSS design based on this model utilizes signals available within the generating station. The efficacy of the proposed design technique and the performance of the stabilizer has been evaluated over a range of operating and system conditions. The simulation results have shown that the performance of the proposed stabilizer is comparable to that could be obtained by conventional design but without the need for the estimation and computation of external system parameters. The proposed design is thus well suited for practical applications to power system stabilization, including possibly the multi-machine applications where accurate system information is not readily available.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

The cost-effectiveness of the MobileMums intervention to increase physical activity among mothers with young children: A Markov model informed by a randomised controlled trial

Objectives: To determine the cost-effectiveness of the MobileMums intervention. MobileMums is a 12-week programme which assists mothers with young children to be more physically active, primarily through the use of personalised SMS text-messages. Design: A cost-effectiveness analysis using a Markov model to estimate and compare the costs and consequences of MobileMums and usual care. Setting: This study considers the cost-effectiveness of MobileMums in Queensland, Australia. Participants: A hypothetical cohort of over 36 000 women with a child under 1 year old is considered. These women are expected to be eligible and willing to participate in the intervention in Queensland, Australia. Data sources: The model was informed by the effectiveness results from a 9-month two-arm community-based randomised controlled trial undertaken in 2011 and registered retrospectively with the Australian Clinical Trials Registry (ACTRN12611000481976). Baseline characteristics for the model cohort, treatment effects and resource utilisation were all informed by this trial. Main outcome measures: The incremental cost per quality-adjusted life year (QALY) of MobileMums compared with usual care. Results: The intervention is estimated to lead to an increase of 131 QALYs for an additional cost to the health system of 1.1 million Australian dollars (AUD). The expected incremental cost-effectiveness ratio for MobileMums is 8608 AUD per QALY gained. MobileMums has a 98% probability of being cost-effective at a cost-effectiveness threshold of 64 000 AUD. Varying modelling assumptions has little effect on this result. Conclusions: At a cost-effectiveness threshold of 64 000 AUD, MobileMums would likely be a cost-effective use of healthcare resources in Queensland, Australia. Trial registration number: Australian Clinical Trials Registry; ACTRN12611000481976.

Foodborne Yersinia : Identification and Molecular Epidemiology of Isolates from Human Infections

Yersinia enterocolitica and Yersinia pseudotuberculosis are among the major enteropathogenic bacteria causing infections in humans in many industrialized countries. In Finland, Y. pseudotuberculosis has caused 10 outbreaks among humans during 1997-2008. Some of these outbreaks have been very extensive involving over 400 cases; mainly children attending schools and day-care. Y. enterocolitica, on the contrary, has caused mainly a large number of sporadic human infections in Finland. Y. pseudotuberculosis is widespread in nature, causing infections in a variety of domestic and wild animals. Foodborne transmission of human infections has long been suspected, however, attempts to trace the pathogen have been unsuccessful before this study that epidemiologically linked Y. pseudotuberculosis to a specific food item. Furthermore, due to modern food distribution systems, foodborne outbreaks usually involve many geographically separate infection clusters difficult to identify as part of the same outbreak. Among pathogenic Y. enterocolitica, the global predominance of one genetically homogeneous type (bioserotype 4/O:3) is a challenge to the development of genetic typing methods discriminatory enough for epidemiological purposes, for example, for tracing back to the sources of infections. Furthermore, the diagnostics of Y. enterocolitica infections is hampered because clinical laboratories easily misidentify some other members of the Yersinia species (Y. enterocolitica–like species) as Y. enterocolitica. This results in misleading information on the prevalence and clinical significance of various Yersinia isolates. The aim of this study was to develop and optimize molecular typing methods to be used in epidemiological investigations of Y. enterocolitica and Y. pseudotuberculosis, particularly in active surveillance and outbreak investigations of Y. pseudotuberculosis isolates. The aim was also to develop a simplified set of phenotypic tests that could be used in routine diagnostic laboratories for the correct identification of Y. enterocolitica and Y. enterocolitica –like species. A PFGE method designed here for typing of Y. pseudotuberculosis was efficient in linking the geographically dispersed and apparently unrelated Y. pseudotuberculosis infections as parts of the same outbreak. It proved to be useful in active laboratory-based surveillance of Y. pseudotuberculosis outbreaks. Throughout the study period, information about the diversity of genotypes among outbreak and non-outbreak related strains of human origin was obtained. Also, to our knowledge, this was the first study to epidemiologically link a Y. pseudotuberculosis outbreak of human illnesses to a specific food item, iceberg lettuce. A novel epidemiological typing method based on the use of a repeated genomic region (YeO:3RS) as a probe was developed for the detection and differentiation between strains of Y. enterocolitica subspecies palearctica. This method was able to increase the discrimination in a set of 106 previously PFGE typed Finnish Y. enterocolitica bioserotype 4/O:3 strains among which two main PFGE genotypes had prevailed. The developed simplified method was a more reliable tool than the commercially available biochemical test kits for differentiation between Y. enterocolitica and Y. enterocolitica –like species. In Finland, the methods developed for Y. enterocolitica and Y. pseudotuberculosis have been used to improve the identification protocols and in subsequent outbreak investigations.

Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model

Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period.

Stochastic model for simulating maize yield

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment. © 2012 American Society of Agricultural and Biological Engineers.

A review of the application of molecular genetics for fisheries management and conservation of sharks and rays

Since the first investigation 25 years ago, the application of genetic tools to address ecological and evolutionary questions in elasmobranch studies has greatly expanded. Major developments in genetic theory as well as in the availability, cost effectiveness and resolution of genetic markers were instrumental for particularly rapid progress over the last 10 years. Genetic studies of elasmobranchs are of direct importance and have application to fisheries management and conservation issues such as the definition of management units and identification of species from fins. In the future, increased application of the most recent and emerging technologies will enable accelerated genetic data production and the development of new markers at reduced costs, paving the way for a paradigm shift from gene to genome-scale research, and more focus on adaptive rather than just neutral variation. Current literature is reviewed in six fields of elasmobranch molecular genetics relevant to fisheries and conservation management (species identification, phylogeography, philopatry, genetic effective population size, molecular evolutionary rate and emerging methods). Where possible, examples from the Indo-Pacific region, which has been underrepresented in previous reviews, are emphasized within a global perspective. (C) 2012 The Authors Journal of Fish Biology (C) 2012 The Fisheries Society of the British Isles

Prediction of breeding values for average fruit weight in mango using a multivariate individual mixed model

Mango is an important horticultural fruit crop and breeding is a key strategy to improve ongoing sustainability. Knowledge of breeding values of potential parents is important for maximising progress from breeding. This study successfully employed a mixed linear model methods incorporating a pedigree to predict breeding values for average fruit weight from highly unbalanced data for genotypes planted over three field trials and assessed over several harvest seasons. Average fruit weight was found to be under strong additive genetic control. There was high correlation between hybrids propagated as seedlings and hybrids propagated as scions grafted onto rootstocks. Estimates of additive genetic correlation among trials ranged from 0.69 to 0.88 with correlations among harvest seasons within trials greater than 0.96. These results suggest that progress from selection for broad adaptation can be achieved, particularly as no repeatable environmental factor that could be used to predict G x E could be identified. Predicted breeding values for 35 known cultivars are presented for use in ongoing breeding programs.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.