Effect of bird density on the decision to join a group in the Sicalis flaveola pelzeni (Passeriformes, Emberizidae)

A change in bird density within a captive flock of Sicalis flaveola pelzeni (Sclater, 1872) affected the decision to join a group. Ruling out inter-individual differences and maintaining constant the size of a food patch, birds were found to fly more often to the food source and spend a longer time in its environs when kept in greater groups.

Biometric and statistical investigations on the cnidoma of the genus Hydra (Cnidaria, Hydrozoa)

This paper deals about the nematocysts like a source of biometric information for comparison between the species Hydra vulgaris Pallas, 1766, Hydra vulgaris pedunculata Deserti et al., 2011 and Hydra pseudoligactis (Hyman, 1931). This biometric tool lets us carry out statistical comparisons and adding these results to the identification of specimens from different classificatory groups. In this particular study, we obtained significant differences between species, individuals of each species and nematocysts type when compared the biometry of its nematocysts. Another result was the variation in of particular nematocysts, like atrichous isorhiza and holotrichous isorhiza for the species H. vulgaris in relation to the column size.

Capillaria spp. eggs in Patagonian archaeological sites: statistical analysis of morphometric data

Discriminant analysis was used to identify eggs of Capillaria spp. at specific level found in organic remains from an archaeological site in Patagonia, Argentina, dated of 6,540 ± 110 years before present. In order to distinguish eggshell morphology 149 eggs were measured and grouped into four arbitrary subsets. The analysis used on egg width and length discriminated them into different morphotypes (Wilks' lambda = 0.381, p < 0.05). The correlation analysis suggests that width was the most important variable to discriminate among the Capillaria spp. egg morphotypes (Pearson coefficient = 0.950, p < 0.05). The study of eggshell patterns, the relative frequency in the sample, and the morphometric data allowed us to correlate the four morphotypes with Capillaria species.

Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.

Quality uncertainty and allocation of decision rights in the European protected designation of origin

The paper considers some issue in the governance of the European Protected Designation of Origin (PDO). The PDO systems are the outcomes of both farmers and consumers expectations and connect the valorisation of the agricultural and rural resources of given territories to the quality of typical products. A critical point in the governance of the PDO systems is represented by the connection between the quality strategies and the uncertainty. The paper argues that the PDO systems can be thought of as strictly coordinated subsystems in which the ex post governance play a critical role in coping with quality uncertainty. The study suggests that the society's inducements given raise to complex organizational systems in which the allocation of decision rights to PDO collective organizations play a major role. The empirical analysis is carried out by examining ten Italian PDO systems in order to identify the decision rights allocated.

Entrepreneurial decision-making using the knightian uncertainty approach

The article discusses the behavioral aspects that affect the entrepreneurs' decision making under the Knightian uncertainty approach. Since the profit arising from entrepreneurial activity represents the reward of an immeasurable and subjective risk, it has been hypothesized that innovative entrepreneurs have excessive optimism and confidence, which leads them to invest in high-risk activities. A behavioral model of decision making under uncertainty is used to test the hypothesis of overconfidence. This model is based on Bayesian inference, which allows us to model the assumption that these entrepreneurs are overconfident. We conclude that, under the hypothesis of overconfidence, these entrepreneurs decide to invest, despite the fact that the expected utility model indicates the contrary. This theoretical finding could explain why there are a large number of business failures in the first years of activity.

The decision of an obese woman to have bariatric surgery: the social phenomenology

Objective To understand the process by which an obese woman decides to have bariatric surgery. Method A qualitative survey with a social phenomenology approach, carried out in 2012, with 12 women, using the phenomenological interview. Results A woman bases the decision to have the surgery on: the inappropriateness of her eating habits; a physical appearance that is incompatible with an appearance that is standardized by society; the social prejudice that she has to live with; the limitations imposed by obesity; and her lack of success with previous attempts to lose weight. Outcomes that she hopes for from the decision to have the surgery include: restoring her health; achieving social inclusion; and entering the labor market. Conclusion This study allows one to reflect that prescriptive actions do not give a satisfactory response to a complexity of the subjective questions involved in the decision to have surgery for obesity. For this, what is called for is a program of work based on an interdisciplinary approach, and training that gives value to the bio-psycho-social aspects involved in a decision in favor of surgical treatment.

Informatics competencies essential to decision making in nursing management

Abstract OBJECTIVE To identify informatics abilities essential to decision making in nursing management. METHOD Survey study with specialist nurses in health informatics and management. An electronic questionnaire was built based on the competencies Information Literacy (five categories; 40 abilities) and Information Management (nine categories; 69 abilities) of the TIGER - Technology Informatics Guiding Education Reform - initiative, with the guiding question: Which informatics abilities are essential to decision making in management? Answers were sorted in a Likert scale, ranging from 1 to 5. Rasch analysis was conducted with the software WINSTEPS ®. Results were presented in logits, with cutoff value zero. RESULTS Thirty-two specialists participated, coming from all regions of Brazil. In the information literacy competency, 18 abilities were considered essential and in Information Management, 38; these were sorted according to their degree of essentiality. CONCLUSION It is believed that the incorporation of these abilities in teaching can support the education of nurse managers and contribute to evidence-based practice, incorporation of information and communication technologies in health and information management.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Decision criteria for optimizing postemergence johnsongrass control in soybean crops in Argentina

Field studies were established in Zavalla and Oliveros, Argentina, during four years in order to optimize Johnsongrass (Sorghum halepense (L.) Pers.) chemical control by means of the thermal calendar model in comparison with other criteria (weed height or days after sowing). The effect of three application dates of postemergence herbicides was determined by visual control, density of tillers originated from rhizome bud regrowth, and from crown and shoot bud regrowth, and soybean yield. Following the thermal calendar model criterion, applications during the second date afforded the best control. Weed height for the first date showed little variability between experiments but was highly variable in the second and third application dates, achieving in some cases values greater than 120 cm. For all years, no significant differences were detected for crop yield between the first and second application dates, and yields were always lower for the third date. The greatest rhizome bud regrowth was observed for the earliest application date and the highest crown and shoot bud regrowth was determined for the last application date. Parameters associated with control efficiency showed the best behaviour for the second date. However, plant height at this moment may interfere with herbicide application and the variability exhibited by this parameter highlights the risk of determining control timing using only one decision criterion.