The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

Estudi de l'evolució i distribució de Rhynchophorus ferrugineus. Bloc 1: Anàlisi de l'evolució a Catalunya i determinació d'un model lineal generalitzat mixte

El morrut de les palmeres, R. ferrugineus, està actualment considerat com la plaga més perjudicial de les palmeres ja que la seva infestació produeix, de forma comuna, la seva mort. Des de la seva instal·lació en els països de la conca mediterrània, en els últims anys, són milers les palmeres que han mort degut a la plaga. La ràpida dispersió que s’ha produït de l’insecte així com la difícil detecció en els períodes primerencs de les infestacions fa que el R. ferrugineus posi en perill ecosistemes naturals de palmeres així com hàbitats rurals i urbans amb un ús ornamental d’aquestes plantes. És necessari desenvolupar estudis que permetin un millor coneixement del comportament d’aquest insecte així com, aquelles característiques intrínseques de la palmeres i variables externes que afavoreixen la instauració del coleòpter i, per tant, noves metodologies pel seu control.

Estudi de l'evolució i distribució de Rhynchophorus ferrugineus. Bloc 2: Aplicació d'un model lineal generalitzat mixte a les localitats de Matadepera i Tossa de Mar

El morrut de les palmeres, R. ferrugineus, està actualment considerat com la plaga més perjudicial de les palmeres ja que la seva infestació produeix, de forma comuna, la seva mort. Des de la seva instal·lació en els països de la conca mediterrània, en els últims anys, són milers les palmeres que han mort degut a la plaga. La ràpida dispersió que s’ha produït de l’insecte així com la difícil detecció en els períodes primerencs de les infestacions fa que el R. ferrugineus posi en perill ecosistemes naturals de palmeres així com hàbitats rurals i urbans amb un ús ornamental d’aquestes plantes. És necessari desenvolupar estudis que permetin un millor coneixement del comportament d’aquest insecte així com, aquelles característiques intrínseques de la palmeres i variables externes que afavoreixen la instauració del coleòpter i, per tant, noves metodologies pel seu control.

Inferring epidemic contact structure from phylogenetic trees.

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.

What matters for predicting spatial distributions of trees: techniques, data, or species' characteristics?

Data characteristics and species traits are expected to influence the accuracy with which species' distributions can be modeled and predicted. We compare 10 modeling techniques in terms of predictive power and sensitivity to location error, change in map resolution, and sample size, and assess whether some species traits can explain variation in model performance. We focused on 30 native tree species in Switzerland and used presence-only data to model current distribution, which we evaluated against independent presence-absence data. While there are important differences between the predictive performance of modeling methods, the variance in model performance is greater among species than among techniques. Within the range of data perturbations in this study, some extrinsic parameters of data affect model performance more than others: location error and sample size reduced performance of many techniques, whereas grain had little effect on most techniques. No technique can rescue species that are difficult to predict. The predictive power of species-distribution models can partly be predicted from a series of species characteristics and traits based on growth rate, elevational distribution range, and maximum elevation. Slow-growing species or species with narrow and specialized niches tend to be better modeled. The Swiss presence-only tree data produce models that are reliable enough to be useful in planning and management applications.

Optimization strategies for fast detection of positive selection on phylogenetic trees.

MOTIVATION: The detection of positive selection is widely used to study gene and genome evolution, but its application remains limited by the high computational cost of existing implementations. We present a series of computational optimizations for more efficient estimation of the likelihood function on large-scale phylogenetic problems. We illustrate our approach using the branch-site model of codon evolution. RESULTS: We introduce novel optimization techniques that substantially outperform both CodeML from the PAML package and our previously optimized sequential version SlimCodeML. These techniques can also be applied to other likelihood-based phylogeny software. Our implementation scales well for large numbers of codons and/or species. It can therefore analyse substantially larger datasets than CodeML. We evaluated FastCodeML on different platforms and measured average sequential speedups of FastCodeML (single-threaded) versus CodeML of up to 5.8, average speedups of FastCodeML (multi-threaded) versus CodeML on a single node (shared memory) of up to 36.9 for 12 CPU cores, and average speedups of the distributed FastCodeML versus CodeML of up to 170.9 on eight nodes (96 CPU cores in total).Availability and implementation: ftp://ftp.vital-it.ch/tools/FastCodeML/. CONTACT: selectome@unil.ch or nicolas.salamin@unil.ch.

Stratification of the severity of critically ill patients with classification trees

Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

Annonaceae substitution rates: a codon model perspective

The Annonaceae includes cultivated species of economic interest and represents an important source of information for better understanding the evolution of tropical rainforests. In phylogenetic analyses of DNA sequence data that are used to address evolutionary questions, it is imperative to use appropriate statistical models. Annonaceae are cases in point: Two sister clades, the subfamilies Annonoideae and Malmeoideae, contain the majority of Annonaceae species diversity. The Annonoideae generally show a greater degree of sequence divergence compared to the Malmeoideae, resulting in stark differences in branch lengths in phylogenetic trees. Uncertainty in how to interpret and analyse these differences has led to inconsistent results when estimating the ages of clades in Annonaceae using molecular dating techniques. We ask whether these differences may be attributed to inappropriate modelling assumptions in the phylogenetic analyses. Specifically, we test for (clade-specific) differences in rates of non-synonymous and synonymous substitutions. A high ratio of nonsynonymous to synonymous substitutions may lead to similarity of DNA sequences due to convergence instead of common ancestry, and as a result confound phylogenetic analyses. We use a dataset of three chloroplast genes (rbcL, matK, ndhF) for 129 species representative of the family. We find that differences in branch lengths between major clades are not attributable to different rates of non-synonymous and synonymous substitutions. The differences in evolutionary rate between the major clades of Annonaceae pose a challenge for current molecular dating techniques that should be seen as a warning for the interpretation of such results in other organisms.

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Measurement and simulation of solar radiation availability in relation to the growth of coffee plants in an agroforestry system with rubber trees

Solar radiation is an important factor for plant growth, being its availability to understory crops strongly modified by trees in an Agroforestry System (AFS). Coffee trees (Coffea arabica - cv. Obatã IAC 1669-20) were planted at a 3.4 x 0.9 m spacing inside and aside rows of monocrops of 12 year-old rubber trees (Hevea spp.), in Piracicaba-SP, Brazil (22º42'30" S, 47º38'00" W - altitude: 546m). One-year-old coffee plants exposed to 25; 30; 35; 40; 45; 80; 90; 95 and 100% of the total solar radiation were evaluated according to its biophysical parameters of solar radiation interception and capture. The Goudriaan (1977) adapted by Bernardes et al. (1998) model for radiation attenuation fit well to the measured data. Coffee plants tolerate a decrease in solar radiation availability to 50% without undergoing a reduction on growth and LAI, which was approximately 2m².m-2 under this condition. Further reductions on the availability of solar radiation caused a reduction in LAI (1.5m².m-2), thus poor land cover and solar radiation interception, resulting in growth reduction.

ALLOMETRIC MODELS FOR ESTIMATING ABOVEGROUND BIOMASS AND BIOMASS ALLOCATION OF CAPIXINGUI TREES (Croton floribundus Spreng.) IN AN AGRISILVICULTURAL SYSTEM

ABSTRACT The objective of this study was to select allometric models to estimate total and pooled aboveground biomass of 4.5-year-old capixingui trees established in an agrisilvicultural system. Aboveground biomass distribution of capixingui was also evaluated. Single- (diameter at breast height [DBH] or crown diameter or stem diameter as the independent variable) and double-entry (DBH or crown diameter or stem diameter and total height as independent variables) models were studied. The estimated total biomass was 17.3 t.ha-1, corresponding to 86.6 kg per tree. All models showed a good fit to the data (R2ad > 0.85) for bole, branches, and total biomass. DBH-based models presented the best residual distribution. Model lnW = b0 + b1* lnDBH can be recommended for aboveground biomass estimation. Lower coefficients were obtained for leaves (R2ad > 82%). Biomass distribution followed the order: bole>branches>leaves. Bole biomass percentage decreased with increasing DBH of the trees, whereas branch biomass increased.

Influence of thermal treatment of wood on the aroma of a sugar cane spirit (cachaça) model-solution

The aging process of alcoholic beverages is generally conducted in wood barrels made with species from Quercus sp. Due to the high cost and the lack of viability of commercial production of these trees in Brazil, there is demand for new alternatives to using other native species and the incorporation of new technologies that enable greater competitiveness of sugar cane spirit aged in Brazilian wood. The drying of wood, the thermal treatment applied to it, and manufacturing techniques are important tools in defining the sensory quality of alcoholic beverages after being placed in contact with the barrels. In the thermal treatment, several compounds are changed by the application of heat to the wood and various studies show the compounds are modified, different aromas are developed, there is change in color, and beverages achieve even more pleasant taste, when compared to non-treated woods. This study evaluated the existence of significant differences between hydro-alcoholic solutions of sugar cane spirits elaborated from different species of thermo-treated and non-treated wood in terms of aroma. An acceptance test was applied to evaluate the solutions preferred by tasters under specific test conditions.

Suppression of long-branch attraction artefacts in the animal phylogeny using a site-heterogeneous model

Affiliation: Département de Biochimie, Université de Montréal

A GIS-based empirical model for vegetation prediction in Lefka Ori, Crete

The aim of the study was to establish and verify a predictive vegetation model for plant community distribution in the alti-Mediterranean zone of the Lefka Ori massif, western Crete. Based on previous work three variables were identified as significant determinants of plant community distribution, namely altitude, slope angle and geomorphic landform. The response of four community types against these variables was tested using classification trees analysis in order to model community type occurrence. V-fold cross-validation plots were used to determine the length of the best fitting tree. The final 9node tree selected, classified correctly 92.5% of the samples. The results were used to provide decision rules for the construction of a spatial model for each community type. The model was implemented within a Geographical Information System (GIS) to predict the distribution of each community type in the study site. The evaluation of the model in the field using an error matrix gave an overall accuracy of 71%. The user's accuracy was higher for the Crepis-Cirsium (100%) and Telephium-Herniaria community type (66.7%) and relatively lower for the Peucedanum-Alyssum and Dianthus-Lomelosia community types (63.2% and 62.5%, respectively). Misclassification and field validation points to the need for improved geomorphological mapping and suggests the presence of transitional communities between existing community types.