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Abstract: Estimating the prediction error of classifiers induced by supervised learning algorithms is important not only to predict its future error, but also to choose a classifier from a given set (model selection). If the goal is to estimate the prediction error of a particular classifier, the desired estimator should have low bias and low variance. However, if the goal is the model selection, in order to make fair comparisons the chosen estimator should have low variance assuming that the bias term is independent from the considered classifier. This paper follows the analysis proposed in [1] about the statistical properties of k-fold cross-validation estimators and extends it to the most popular error estimators: resubstitution, holdout, repeated holdout, simple bootstrap and 0.632 bootstrap estimators, without and with stratification. We present a general framework to analyze the decomposition of the variance of different error estimators considering the nature of the variance (irreducible/reducible variance) and the different sources of sensitivity (internal/external sensitivity). An extensive empirical study has been performed for the previously mentioned estimators with naive Bayes and C4.5 classifiers over training sets obtained from assorted probability distributions. The empirical analysis consists of decomposing the variances following the proposed framework and checking the independence assumption between the bias and the considered classifier. Based on the obtained results, we propose the most appropriate error estimations for model selection under different experimental conditions. [Copyright &y& Elsevier]

Aim: The calibration area (CA) corresponds to the geographic region used by different algorithms that estimate the species' environmental preferences and delimit its geographic distribution. This study intended to identify, test and compare current literature's most commonly employed approaches and methods for CA creation, highlighting the differences with the accessible area (M), a frequently misapplied concept. Location: Global. Taxon: Arthropods, amphibians, reptiles, birds and mammals. Methods: We conducted a literature review and analysed 129 recent articles on species distribution that use correlative models to identify the methods used to establish the CA and their frequency. We also evaluated seven of the most widely used methods for 31 species from different taxa. Results: We found that the most frequently used methods in literature corresponded to biogeographic entities (BE). Moreover, according to our evaluation, those methods that seek to establish the CA through the accessible area approach (including BE and 'grinnell') were the best evaluated. Finally, we highlight the advantages and disadvantages of the analysed methods in selecting CA. Main Conclusions: Although we cannot fail to recognize the usefulness and validity of the different methods to establish CAs, we suggest calibrating ecological niche and species distribution models in light of explicit a priori hypotheses regarding the extent of accessible areas (M) as a delimitation of the CA, which theoretically includes the species' dispersal ability and its barriers. We recommend using the BE method, which is simple to establish and highly operational. [ABSTRACT FROM AUTHOR]

Harvest efficiency is one of the main factors that define productivity of a grassland. In Lotus species, productive response has not been studied in function of the amount of intercepted light. This study was conducted in the Colegio de Postgraduados, Montecillo, Texcoco, Mexico, in the 2014-2015 and 2015-2016 crop cycles with the objective of determining the production of L. corniculatus in function of the percentage (90, 95 and 100%) of light intercepted (LI) and a fixed cutting (CF) defined seasonally. The hypothesis was that higher production of forage would be obtained with 95% LI. The experimental design was random blocks in divided plots, and the treatments were LI and CF with three replications. Annual yield of forage showed differences among treatments only in the second year. Forage yield of CF was lower (22 844 kg MS ha-1) than the average with 90, 95 and 100% LI (32 173 kg MS ha-1). Seasonal yield was higher in spring (10 461 kg MS ha-1) relative to the fall and winter average (5750 kg MS ha-1). Weeds contributed (4%) to annual yield and leaves (58%) in spring with 95% LI. With 95 and 100% LI greater heights (23 cm) were recorded, and in CF the heights were lower (19 cm) in both years. Of the seasons, taller plants (24 cm) grew in the spring and shorter plants in autumn and winter (19 cm). In the second year, there was a higher mean annual leaf:stem ratio in CF (2.8:1), mainly in autumn (3.3:1). The best productive performance of L. corniculatus was with 90, 95 and 100% LI. The highest contribution of leaf was with 95% LI, mainly in spring. In conclusion, although there were not differences between the percentages of intercepted light, at 95% the largest amount of leaf was produced, and thus we consider it to be the best management strategy. Nevertheless, because it is a species recently characterized in Mexico, it is necessary to conduct more research in different environment types. [ABSTRACT FROM AUTHOR]

Under an electric field, spherical conducting particles in a dielectric liquid assemble into a dendritic tree in order to dissipate charge. Several topological measures characterize such networks, including degree distributions, Strahler numbers, and total external pathlengths. Here, scaling laws relating these measures to the number of nodes in the system are presented and shown to match diffusion limited aggregation (DLA) structures. Experimental bifurcation and stream-length ratios in this easily reproducible laboratory experiment are found to agree with DLA simulations and Horton's laws for river networks. Certain scaling relations in transportation networks are known to originate from general features of networks. Here we find the experimental structures share properties with hydrological drainage networks. [ABSTRACT FROM AUTHOR]

Piper eriopodon is one of the Piper species found in the Sierra Nevada de Santa Marta, and the species has been reported with different compositions of their essential oils (EO). In this study, the volatile fractions/essential oil (by HS-SPME/SDE/MWHD-GC–MS/1H-NMR) of different parts from the plant were characterized, and assessments of the in vitro bio-properties of the leaf EO were conducted. The results indicated the following: (i) in the volatile fractions were β-caryophyllene (~23%)/myrcene (~20%) (inflorescences) and β-caryophyllene (~43%)/β-selinene (~20%) (leaves) using HS-SPME; myrcene (~31%)/β-pinene (~23%) (inflorescences), gibbilimbol B (~60%) (fruits) and gibbilimbol B (~46%)/β-caryophyllene (~11%) (leaves) through SDE; (ii) leaf EO contained gibbilimbol B (~72%), confirmed with 1H-NMR; (iii) the cytotoxic values (µg/mL) in erythrocytes/lymphocytes/Hep-2 were HC50: 115 ± 3 (eryth.), LC50: 71 ± 4 (lymph.) and LC50: 33 ± 2 (cell-line); (iv) the antibacterial susceptibilities (ϕ inh. zone, mm; 4–16 µg EO) were 22.5 ± 0.4–97 ± 4 (Staphylococcus aureus), 23 ± 2–77 ± 4 (Escherichia coli) and 17 ± 1–48 ± 3 (Listeria monocytogenes); (v) the TAA value was 2249 ± 130 mmol Trolox®/kg; (vi) the IC50 value was 13±1 µg/mL (AChE) with 20 ± 0–37 ± 6% repellency (2–4 h, Sitophilus zeamais). Thus, the EO of P. eriopodon leaves from northern Colombia could be a promising species for sustainable exploitation in the future due to its outstanding bioactivities. [ABSTRACT FROM AUTHOR]

An abstract of the article "Interaction of gypsum with As(V)-bearing aqueous solutions: Surface precipitation of guerinite, saifeldite, and Ca2NaH(AsO4)2·6H2O, a synthetic arsenate," by Manuel Prieto, Laura Torre, and Santiago García-Granda is presented.

Objective: Evaluate the effects of i) dehulling of lupine seed on chemical composition and apparent metabolizable energy (AME) and ii) soybean meal substitution by dehulled lupine seed in broiler diets with enzymes on productive performance, size of digestive organs and welfare-related variables. Methods: Experiment 1, chemical composition and AME were determined in whole and dehulled lupine seed. Experiment 2, two hundred eighty-eight one-day-old male Ross 308 broilers were used. The experimental diets were maize-soybean meal (MS), MS with enzymes (MSE) and maize-dehulled lupine seed with enzymes (MLE). Diets were assigned to the experimental units under a completely randomized design (eight replicates per diet). The body weight (BW) gain, feed intake, feed conversion, digestive organ weights, gait score, latency to lie down and valgus/varus angulation were evaluated. Results: The dehulling process increased protein (25.0% to 31.1%), AME (5.9 to 8.8 MJ/kg) and amino acid contents. The BW gain of broilers fed the MLE diet was similar (p>0.05) to that of those fed the MS diet, but lower than that of those fed the MSE diet. Feed intake of broilers fed the MLE diet was higher (p<0.05) than that of those fed the MS diet and similar (p>0.05) to those fed the MSE diet. Feed conversion of broilers fed the MLE diet was 8.0% and 8.7% higher (p<0.05) than that of those fed the MS and MSE diets, respectively. Broilers fed the MLE diet had the highest (p<0.05) relative proventriculus and gizzard weights, but had poor welfare-related variables. Conclusion: It is possible to substitute soybean meal by dehulled lupine seed with enzymes in broiler diets, obtaining similar BW gains in broilers fed the MLE and MS diets; however, a higher feed intake is required. Additionally, the MLE diet reduced welfare-related variables. [ABSTRACT FROM AUTHOR]

Growth, biomass yield, fiber content and lodging resistance were studied, during a six month growth period, for eight varieties of Cenchrus purpureus , intended as energy crop, in Veracruz, Mexico. Then, only yield at day 182 was assessed for two additional years. The varieties were: CT115 (CT), African Cane (AC), Taiwan (TAI), King Grass (KG), Vruckwona (VRU), Roxo (RX), OM22 (OM) and Cameroon (CAM). Local weather is warm and sub-humid, historical data for monthly average temperature and annual rainfall were 25.8 °C and 1142 mm, respectively. Height, diameter and light interception were measured monthly from day 65–185. At day 185, biomass yield and tiller density were measured. Number of lying tillers was counted to estimate lodging resistance. Cellulose and hemicellulose content were estimated in leaf and stem. No differences were found for dry matter yield or stem yield at day 185 in the first year. Regarding the next two years, TAI yielded above CT, OM or ROX. Average dry matter yield was higher in the second year than in the establishment cycle (38.6 vs 21.1 Mg ha −1 ), but decreased in the third year (32.2 Mg ha −1 ). In both stem and whole plant, AC and KG showed higher hemicellulose content than RX, OM or CT; while AC and VRU had higher cellulose than RX in stem, or than CT in the whole plant. Furthermore, varieties AC, KG, VRU and TAI were resistant to lodging and had a higher fiber content, so they are recommended as energetic crops. [ABSTRACT FROM AUTHOR]

Abstract: A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of ‘state-of-the-art’ uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs. [Copyright &y& Elsevier]