Ants obtained from trees of a "Jacareuba" (Calophyllum brasiliense) forest plantation in Central Amazonia by canopy fogging: first results

Canopies of the locally occurring Amazonian tree species Calophyllum brasiliense. Camb. (Guttiferae, height 10 m) were fogged after dawn on the same day at five adjacent localities in a 20-year-old plantation at the Adolpho Ducke Forest Reserve near Manaus/Brazil, using natural pyrethrum (0.5%, 1.0%, 1.5%), Baythroid (0.3%) and diesel oil, respectively. The 1152 ants collected represented 52 species, 17 genera and five subfamilies. The highest number of ant species was obtained with the synthetic pyrethrum Baythroid 0.3% and with natural pyrethrum 1.5%. About 46% of the total ant species were only collected in the first hour after fogging, and 17% only during the second hour, after trees had been heavily shaken. About 73% of the total ant specimens dropped in the first hour. Data on alpha-diversity, eveness and frequency of ants indicated a rapidly decreasing knock-down effect of both the synthetic and natural pyrethrum after application. The ant fauna in the canopy of C. brasiliense is somewhat distinct compared with that of Goupia glabra Aubl. (Celastraceae, height 45 m) from the primary forest of the reserve.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Levels of leaf Herbivory in Amazonian trees from different stages In forest regeneration

Leaves from 120 canopy trees and 60 understory tree saplings growing in primary and secondary forests near Manaus, Brazil, were collected for determination of standing levels of herbivory (percent leaf area lost). Overall, levels of herbivory on leaves of central Amazonian trees were low. About one quarter of the leaves examined (n = 855) had no damage at all. In most other Neotropical sites studied the mean percentage of herbivory was found to vary between 5.7 and 13.1%, whereas in Manaus it was only 3.1%. The data presented here support the contention that levels of herbivore damage are positively related to soil fertility. No significant difference was found in herbivory levels between canopy trees and understory saplings. Also, there was no difference in damage between leaves from pioneer and late successional trees. Field assays of preference, however, revealed that leaves from pioneer trees are more palatable to leaf-cutting ants (Atta laevigata). This effect was dependent upon leaf age, being observed in mature leaves, but not in young leaves. The greater rate of leaf production in secondary forests may be a factor accounting for the greater abundance of leaf-cutting ants in secondary compared to primary forests.

Experimental and numerical approaches for structural assessment in new footbridge designs (SFRSCC–GFPR hybrid structure)

Within the civil engineering field, the use of the Finite Element Method has acquired a significant importance, since numerical simulations have been employed in a broad field, which encloses the design, analysis and prediction of the structural behaviour of constructions and infrastructures. Nevertheless, these mathematical simulations can only be useful if all the mechanical properties of the materials, boundary conditions and damages are properly modelled. Therefore, it is required not only experimental data (static and/or dynamic tests) to provide references parameters, but also robust calibration methods able to model damage or other special structural conditions. The present paper addresses the model calibration of a footbridge bridge tested with static loads and ambient vibrations. Damage assessment was also carried out based on a hybrid numerical procedure, which combines discrete damage functions with sets of piecewise linear damage functions. Results from the model calibration shows that the model reproduces with good accuracy the experimental behaviour of the bridge.

A bayesian approach for NDT data fusion: The Saint Torcato Church case study

This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

Bionomics data for Anopheles (Anopheles) forattinii Wilkerson & Sallum, 1999

Immature and adult stages of Anopheles (Anopheles) forattinii were collected in the Parque Nacional do Jaú, Novo Airão, Amazonas, Brazil. Larvae and pupae were taken from fresh water among floating plant debris inside flooded "igapó" forest. This species may make use of plant debris for passive dispersal throughout its distribution range.

Masonry macro-block analysis

The structural analysis involves the definition of the model and selection of the analysis type. The model should represent the stiffness, the mass and the loads of the structure. The structures can be represented using simplified models, such as the lumped mass models, and advanced models resorting the Finite Element Method (FEM) and Discrete Element Method (DEM). Depending on the characteristics of the structure, different types of analysis can be used such as limit analysis, linear and non-linear static analysis and linear and non-linear dynamic analysis. Unreinforced masonry structures present low tensile strength and the linear analyses seem to not be adequate for assessing their structural behaviour. On the other hand, the static and dynamic non-linear analyses are complex, since they involve large time computational requirements and advanced knowledge of the practitioner. The non-linear analysis requires advanced knowledge on the material properties, analysis tools and interpretation of results. The limit analysis with macro-blocks can be assumed as a more practical method in the estimation of maximum load capacity of structure. Furthermore, the limit analysis require a reduced number of parameters, which is an advantage for the assessment of ancient and historical masonry structures, due to the difficult in obtaining reliable data.

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

The influence of the conservation status and changes in the rainfall regime on forest-savanna mosaic dynamics in Northern Brazilian Amazonia

Coupled carbon/climate models are predicting changes in Amazon carbon and water cycles for the near future, with conversion of forest into savanna-like vegetation. However, empirical data to support these models are still scarce for Amazon. Facing this scenario, we investigated whether conservation status and changes in rainfall regime have influenced the forest-savanna mosaic over 20 years, from 1986 to 2006, in a transitional area in Northern Amazonia. By applying a spectral linear mixture model to a Landsat-5-TM time series, we identified protected savanna enclaves within a strictly protected nature reserve (Maracá Ecological Station - MES) and non-protected forest islands at its outskirts and compared their areas among 1986/1994/2006. The protected savanna enclaves decreased 26% in the 20-years period at an average rate of 0.131 ha year-1, with a greater reduction rate observed during times of higher precipitation, whereas the non-protected forest islands remained stable throughout the period of study, balancing the encroachment of forests into the savanna during humid periods and savannization during reduced rainfall periods. Thus, keeping favorable climate conditions, the MES conservation status would continue to favor the forest encroachment upon savanna, while the non-protected outskirt areas would remain resilient to disturbance regimes. However, if the increases in the frequency of dry periods predicted by climate models for this region are confirmed, future changes in extension and directions of forest limits will be affected, disrupting ecological services as carbon storage and the maintenance of local biodiversity.

Dynamic interface model for masonry walls subjected to high strain rate out-of-plane loads

The present study proposes a dynamic constitutive material interface model that includes non-associated flow rule and high strain rate effects, implemented in the finite element code ABAQUS as a user subroutine. First, the model capability is validated with numerical simulations of unreinforced block work masonry walls subjected to low velocity impact. The results obtained are compared with field test data and good agreement is found. Subsequently, a comprehensive parametric analysis is accomplished with different joint tensile strengths and cohesion, and wall thickness to evaluate the effect of the parameter variations on the impact response of masonry walls.

Reproductive biology of Ameerega trivittata (Anura: Dendrobatidae) in an area of terra firme forest in eastern Amazonia

The reproductive success of tropical amphibians is influenced by factors such as body size and the characteristics of breeding sites. Data on reproductive biology are important for the understanding of population dynamics and the maintenance of species. The objectives of the present study were to examine the abundance of Ameerega trivittata, analyze the use of microhabitats by calling males and the snout-vent length (SVL) of breeding males and females, the number of tadpoles carried by the males and mature oocytes in the females, as well as the relationship between the SVL of the female and both the number and mean size of the mature oocytes found in the ovaries. Three field trips were conducted between January and September, 2009. A total of 31 plots, with a mean area of 2.3 ha, were surveyed, resulting in records of 235 individuals, with a mean density of 3.26 individuals per hectare. Overall, 66.1% of the individuals sighted were located in the leaf litter, while 17.4% were perched on decaying tree trunks on the forest floor, 15.7% on the aerial roots of Cecropia trees, and 0.8% on lianas. Males were observed transporting a mean of 10.8 tadpoles on their backs. A significant correlation was found between the size of the females and the mean diameter of the oocytes. New data were collected on the size of oocytes and no pattern was found in the type of perches used by calling males of the different Ameerega species.

Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

The seasonal diet of Aequidens tetramerus (Cichlidae) in a small forest stream in the Machado River basin, Rondônia, Brazil

Trophic relationships in fish communities are affected by the availability of resources, which in turn is affected by spatial and temporal variations throughout the year. The aims of this study were to characterize the diet of A. tetramerus in a streamlet in the north of Brazil and compare its composition in different hydrological seasons (wet and dry seasons). Collections were performed every two months from October 2011 to September 2012 with the aid of seine nets, hand net and fishing traps in the streamlet located in the Machado River drainage basin in the Rondônia state. Most of the specimens collected were quite small (< 40 mm) and had empty stomachs. Our results showed that A. tetramerus feeds on a wide variety of items of plant origin, such as algae, seeds and leaves, as well as items of animal origin, including bryozoans, crustaceans, fish scales, terrestrial insects and detritus. The data also indicated higher consumption of aquatic insects than other food items, suggesting a primarily insect-based diet. Items of plant and allochthonous origin were consumed more in the wet season than in the dry season, but there were no seasonal differences in the consumption of animal and autochthonous items.