Federal University of Pernambuco

About: Federal University of Pernambuco is a education organization based out in Recife, Brazil. It is known for research contribution in the topics: Population & Context (language use). The organization has 22973 authors who have published 35124 publications receiving 426579 citations.

Biogeochemical cycling in terrestrial ecosystems of the Caatinga Biome

Abstract: The biogeochemical cycles of C, N, P and water, the impacts of land use in the stocks and flows of these elements and how they can affect the structure and functioning of Caatinga were reviewed. About half of this biome is still covered by native secondary vegetation. Soils are deficient in nutrients, especially N and P. Average concentrations of total soil P and C in the top layer (0-20 cm) are 196 mg kg-1 and 9.3 g kg-1, corresponding to C stocks around 23 Mg ha-1. Aboveground biomass of native vegetation varies from 30 to 50 Mg ha-1, and average root biomass from 3 to 12 Mg ha-1. Average annual productivities and biomass accumulation in different land use systems vary from 1 to 7 Mg ha-1 year-1. Biological atmospheric N2 fixation is estimated to vary from 3 to 11 kg N ha-1 year-1and 21 to 26 kg N ha-1 year-1 in mature and secondary Caatinga, respectively. The main processes responsible for nutrient and water losses are fire, soil erosion, runoff and harvest of crops and animal products. Projected climate changes in the future point to higher temperatures and rainfall decreases. In face of the high intrinsic variability, actions to increase sustainability should improve resilience and stability of the ecosystems. Land use systems based on perennial species, as opposed to annual species, may be more stable and resilient, thus more adequate to face future potential increases in climate variability. Long-term studies to investigate the potential of the native biodiversity or adapted exotic species to design sustainable land use systems should be encouraged.

Diapause and quiescence: dormancy mechanisms that contribute to the geographical expansion of mosquitoes and their evolutionary success

Abstract: Mosquitoes are insects belonging to the order Diptera and family Culicidae. They are distributed worldwide and include approximately 3500 species, of which about 300 have medical and veterinary importance. The evolutionary success of mosquitoes, in both tropical and temperate regions, is due to the various survival strategies these insects have developed throughout their life histories. Of the many adaptive mechanisms, diapause and quiescence, two different types of dormancy, likely contribute to the establishment, maintenance and spread of natural mosquito populations. This review seeks to objectively and coherently describe the terms diapause and quiescence, which can be confused in the literature because the phenotypic effects of these mechanisms are often similar.

Finite-state Markov modeling of correlated Rician-fading channels

Abstract: Stochastic properties of the binary channel that describe the successes and failures of the transmission of a modulated signal over a time-correlated flat-fading channel are considered for investigation. This analysis is employed to develop Kth-order Markov models for such a burst channel. The order of the Markov model that generates accurate analytical models is estimated for a broad range of fading environments. The parameterization and accuracy of an important class of hidden Markov models, known as the Gilbert-Elliott channel (GEC), are also investigated. Fading rates are identified in which the Kth-order Markov model and the GEC model approximate the fading channel with similar accuracy. The latter model is useful for approximating slowly fading processes, since it provides a more compact parameterization.

Multi-Agent Patrolling with Reinforcement Learning

Abstract: Patrolling tasks can be encountered in a variety of real-world domains, ranging from computer network administration and surveillance to computer wargame simulations. It is a complex multi-agent task, which usually requires agents to coordinate their decision-making in order to achieve optimal performance of the group as a whole. In this paper, we show how the patrolling task can be modeled as a reinforcement learning (RL) problem, allowing continuous and automatic adaptation of the agentsý strategies to their environment. We demonstrate that an efficient cooperative behavior can be achieved by using RL methods, such as Q-Learning, to train individual agents. The proposed approach is totally distributed, which makes it computationally efficient. The empirical evaluation proves the effectiveness of our approach, as the results obtained are substantially better than the results available so far on this domain.

Diffusive magnonic spin transport in antiferromagnetic insulators

Abstract: It has been shown recently that a layer of the antiferromagnetic insulator (AFI) NiO can be used to transport spin current between a ferromagnet (FM) and a nonmagnetic metal (NM). In the experiments one uses the microwave-driven ferromagnetic resonance in a FM layer to produce a spin pumped spin current that flows through an AFI layer and reaches a NM layer where it is converted into a charge current by means of the inverse spin Hall effect. Here we present a theory for the spin transport in an AFI that relies on the spin current carried by the diffusion of thermal antiferromagnetic magnons. The theory explains quite well the measured dependence of the voltage in the NM layer on the thickness of the NiO layer.