Trait contributions to fish community assembly emerge from trophic interactions in an individual-based model

Community ecology seeks to understand and predict the characteristics of communities that can develop under different environmental conditions, but most theory has been built on analytical models that are limited in the diversity of species traits that can be considered simultaneously. We address that limitation with an individual-based model to simulate assembly of fish communities characterized by life history and trophic interactions with multiple physiological tradeoffs as constraints on species performance. Simulation experiments were carried out to evaluate the distribution of 6 life history and 4 feeding traits along gradients of resource productivity and prey accessibility. These experiments revealed that traits differ greatly in importance for species sorting along the gradients. Body growth rate emerged as a key factor distinguishing community types and defining patterns of community stability and coexistence, followed by egg size and maximum body size. Dominance by fast-growing, relatively large, and fecund species occurred more frequently in cases where functional responses were saturated (i.e. high productivity and/or prey accessibility). Such dominance was associated with large biomass fluctuations and priority effects, which prevented richness from increasing with productivity and may have limited selection on secondary traits, such as spawning strategies and relative size at maturation. Our results illustrate that the distribution of species traits and the consequences for community dynamics are intimately linked and strictly dependent on how the benefits and costs of these traits are balanced across different conditions. © 2012 Elsevier B.V.

Modelling polymers with side chains: MEH-PPV and P3HT

Modelling polymers with side chains is always a challenge once the degrees of freedom are very high. In this study, we present a successful methodology to model poly[2-methoxy-5-(2′-ethyl-hexyloxy)-p-phenylenevinylene] (MEH-PPV) and poly[3-hexylthiophene] (P3HT) in solutions, taking into account the influence of side chains on the polymer conformation. Molecular dynamics and semi-empirical quantum mechanical methods were used for structure optimisation and evaluation of optical properties. The methodology allows to describe structural and optical characteristics of the polymers in a satisfactory way, as well as to evaluate some usual simplifications adopted for modelling these systems. Effective conjugation lengths of 8-14.6 and 21 monomers were obtained for MEH-PPV and P3HT, respectively, in accordance with experimental findings. In addition, anti/syn conformations of these polymers could be predicted based on intrinsic interactions of the lateral branches. © 2013 Copyright Taylor and Francis Group, LLC.

Parametric VaR with goodness-of-fit tests based on EDF statistics for extreme returns

Parametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.

Nonlinear formulation based on FEM, Mazars damage criterion and Fick's law applied to failure assessment of reinforced concrete structures subjected to chloride ingress and reinforcements corrosion

Structural durability is an important design criterion, which must be assessed for every type of structure. In this regard, especial attention must be addressed to the durability of reinforced concrete (RC) structures. When RC structures are located in aggressive environments, its durability is strongly reduced by physical/chemical/mechanical processes that trigger the corrosion of reinforcements. Among these processes, the diffusion of chlorides is recognized as one of major responsible of corrosion phenomenon start. To accurate modelling the corrosion of reinforcements and to assess the durability of RC structures, a mechanical model that accounts realistically for both concrete and steel mechanical behaviour must be considered. In this context, this study presents a numerical nonlinear formulation based on the finite element method applied to structural analysis of RC structures subjected to chloride penetration and reinforcements corrosion. The physical nonlinearity of concrete is described by Mazars damage model whereas for reinforcements elastoplastic criteria are adopted. The steel loss along time due to corrosion is modelled using an empirical approach presented in literature and the chloride concentration growth along structural cover is represented by Fick's law. The proposed model is applied to analysis of bended structures. The results obtained by the proposed numerical approach are compared to responses available in literature in order to illustrate the evolution of structural resistant load after corrosion start. (C) 2014 Elsevier Ltd. All rights reserved.

Modelling the maximum potential of nitrogen deposition and requirements of lysine for broilers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelling of the nitrogen deposition and dietary lysine requirements of Redbro broilers

The aim of this study was to determine the coefficients of the Goettingen model for Redbro birds and estimate the digestible lysine requirements. To determine the model parameters, three nitrogen balance trials were performed in Periods I (14-28 days), II (42-56 days) and III (70-84 days), using 42 birds per trial. The birds were individually housed and subjected to six diets with increasing levels of nitrogen, with lysine as the limiting amino acid (deficient by 20% in relation to other amino acids). Dietary nitrogen concentrations were 8, 16, 24, 32, 40 and 48 g/kg. A control diet was added to confirm lysine as the first limiting amino acid. Nitrogen balance trials were divided into 5 days of adaptation and two periods of excreta collection, each one of 5 days. The response of the birds to a control diet confirmed that lysine was the first limiting amino acid. The adjustment of the exponential functions between nitrogen retention or excretion and nitrogen intake allowed estimation of parameters of the Goettingen model. The maximum potential for nitrogen retention was 3276, 2585 and 2603 mg/BWkg0.67.day, nitrogen maintenance requirement was 225, 135 and 122 mg/BWkg0.67.day and efficiency of nitrogen utilisation was 313 x 10(-6), 406 x 10(-6) and 415 x 10(-6) in the phases of 14-28, 42-56 and 70-84 days. The digestible lysine intake for Periods I, II and III, based on 60% of the maximum potential for nitrogen retention, was 711, 989 and 1272 mg/day (1.225%, 1.137% and 1.09% of lysine in the diet for a daily feed intake of 58, 87 and 117 g/day), respectively.

Implementing new northernmost records to modelling the distribution of Hypsiboas caingua (Anura: Hylidae) in South America

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatial modelling and prediction on river networks: up model, down model or hybrid?

Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Modified constraint-induced movement therapy and modified forced-use therapy for stroke patients are both effective to promote balance and gait improvements

Background: Previous studies show that chronic hemiparetic patients after stroke, presents inabilities to perform movements in paretic hemibody. This inability is induced by positive reinforcement of unsuccessful attempts, a concept called learned non-use. Forced use therapy (FUT) and constraint induced movement therapy (CIMT) were developed with the goal of reversing the learned non-use. These approaches have been proposed for the rehabilitation of the paretic upper limb (PUL). It is unknown what would be the possible effects of these approaches in the rehabilitation of gait and balance. Objectives: To evaluate the effect of Modified FUT (mFUT) and Modified CIMT (mCIMT) on the gait and balance during four weeks of treatment and 3 months follow-up. Methods: This study included thirty-seven hemiparetic post-stroke subjects that were randomly allocated into two groups based on the treatment protocol. The non-paretic UL was immobilized for a period of 23 hours per day, five days a week. Participants were evaluated at Baseline, 1st, 2nd, 3rd and 4th weeks, and three months after randomization. For the evaluation we used: The Stroke Impact Scale (SIS), Berg Balance Scale (BBS) and Fugl-Meyer Motor Assessment (FM). Gait was analyzed by the 10-meter walk test (T10) and Timed Up & Go test (TUG). Results: Both groups revealed a better health status (SIS), better balance, better use of lower limb (BBS and FM) and greater speed in gait (T10 and TUG), during the weeks of treatment and months of follow-up, compared to the baseline. Conclusion: The results show mFUT and mCIMT are effective in the rehabilitation of balance and gait. Trial Registration ACTRN12611000411943.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

Improving Planting Stocks for the Brazilian Atlantic Forest Restoration through Community-Based Seed Harvesting Strategies

High-diversity reforestation can help jumpstart tropical forest restoration, but obtaining viable seedlings is a major constraint: if nurseries do not offer them, it is hard to plant all the species one would like. From 2007 to 2009, we investigated five different seed acquisition strategies employed by a well-established tree nursery in southeastern Brazil, namely (1) in-house seed harvesters; (2) hiring a professional harvester; (3) amateur seed harvesters; or (4) a seed production cooperative, as well as (5) participating in a seed exchange program. In addition, we evaluated two strategies not dependent on seeds: harvesting seedlings from native tree species found regenerating under Eucalyptus plantations, and in a native forest remnant. A total of 344 native tree and shrub species were collected as seeds or seedlings, including 2,465 seed lots. Among these, a subset of 120 species was obtained through seed harvesting in each year. Overall, combining several strategies for obtaining planting stocks was an effective way to increase species richness, representation of some functional groups (dispersal syndromes, planting group, and shade tolerance), and genetic diversity of seedlings produced in forest tree nurseries. Such outcomes are greatly desirable to support high-diversity reforestation as part of tropical forest restoration. In addition, community-based seed harvesting strategies fostered greater socioeconomic integration of traditional communities in restoration projects and programs, which is an important bottleneck for the advance of ecological restoration, especially in developing countries. Finally, we discuss some of the limitations of the various strategies for obtaining planting stocks and the way forward for their improvement.

Modelling shared attention through relational reinforcement learning

Shared attention is a type of communication very important among human beings. It is sometimes reserved for the more complex form of communication being constituted by a sequence of four steps: mutual gaze, gaze following, imperative pointing and declarative pointing. Some approaches have been proposed in Human-Robot Interaction area to solve part of shared attention process, that is, the most of works proposed try to solve the first two steps. Models based on temporal difference, neural networks, probabilistic and reinforcement learning are methods used in several works. In this article, we are presenting a robotic architecture that provides a robot or agent, the capacity of learning mutual gaze, gaze following and declarative pointing using a robotic head interacting with a caregiver. Three learning methods have been incorporated to this architecture and a comparison of their performance has been done to find the most adequate to be used in real experiment. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human in a controlled environment. The experimental results show that the robotic head is able to produce appropriate behavior and to learn from sociable interaction.

Ligand- and Structure-Based Drug Design Strategies and PPAR delta/alpha Selectivity

Peroxisome-proliferator-activated receptors are a class of nuclear receptors with three subtypes: a, ? and d. Their main function is regulating gene transcription related to lipid and carbohydrate metabolism. Currently, there are no peroxisome-proliferator-activated receptors d drugs being marketed. In this work, we studied a data set of 70 compounds with a and d activity. Three partial least square models were created, and molecular docking studies were performed to understand the main reasons for peroxisome-proliferator-activated receptors d selectivity. The obtained results showed that some molecular descriptors (log P, hydration energy, steric and polar properties) are related to the main interactions that can direct ligands to a particular peroxisome-proliferator-activated receptors subtype.

A comparison of deterministic, reliability-based and risk-based structural optimization under uncertainty

In this paper, the effects of uncertainty and expected costs of failure on optimum structural design are investigated, by comparing three distinct formulations of structural optimization problems. Deterministic Design Optimization (DDO) allows one the find the shape or configuration of a structure that is optimum in terms of mechanics, but the formulation grossly neglects parameter uncertainty and its effects on structural safety. Reliability-based Design Optimization (RBDO) has emerged as an alternative to properly model the safety-under-uncertainty part of the problem. With RBDO, one can ensure that a minimum (and measurable) level of safety is achieved by the optimum structure. However, results are dependent on the failure probabilities used as constraints in the analysis. Risk optimization (RO) increases the scope of the problem by addressing the compromising goals of economy and safety. This is accomplished by quantifying the monetary consequences of failure, as well as the costs associated with construction, operation and maintenance. RO yields the optimum topology and the optimum point of balance between economy and safety. Results are compared for some example problems. The broader RO solution is found first, and optimum results are used as constraints in DDO and RBDO. Results show that even when optimum safety coefficients are used as constraints in DDO, the formulation leads to configurations which respect these design constraints, reduce manufacturing costs but increase total expected costs (including expected costs of failure). When (optimum) system failure probability is used as a constraint in RBDO, this solution also reduces manufacturing costs but by increasing total expected costs. This happens when the costs associated with different failure modes are distinct. Hence, a general equivalence between the formulations cannot be established. Optimum structural design considering expected costs of failure cannot be controlled solely by safety factors nor by failure probability constraints, but will depend on actual structural configuration. (c) 2011 Elsevier Ltd. All rights reserved.