The effect of grazing intensity and the presence of a forage legume on nitrogen dynamics in Brachiaria pastures in the Atlantic forest region of the south of Bahia, Brazil

It has been shown that with careful grazing management and addition of Pand K, but not N, fertilisers Brachiaria pastures are ableto maintain sustainable live weight gains over many years. However, standardon-farm practice, which generally involves high stocking rates, leads after afew years to pasture decline due mainly to N deficiency for grass regrowth. Togenerate an understanding of the mechanism of pasture decline and possiblemanagement options to mitigate this process, a study was performed in theAtlantic forest region of the south of Bahia state to study the N dynamics inpastures of Brachiaria humidicola subject to threedifferent stocking rates of beef cattle, with and without the presence of theforage legume Desmodium ovalifolium. Despite the fact thatthe C:N ratio of the deposited litter was high (60 to 70) the rate ofdecomposition was very rapid (k –0.07 gg^–1 day^–1) and annual rates of Nturnover through the litter pathway were between 105 and 170 kg Nha^–1 year^–1. In the grass-onlypasturesas stocking rate increased from 2 to 3 head ha^–1, N recycledinthe litter decreased by 11%, but a further increase to 4 headha^–1 decreased N recycling by 30% suggesting thatbeyonda certain critical level higher grazing stocking rates would lead to pasturedecline if there was no N addition. High stocking rates decreased theproportionof the legume in the sward, but at all rates the concentration of N in both thegreen and dead grass in the forage on offer and in the litter was higher in themixed sward. The presence of the legume caused a decrease in the C:N ratio ofthe microbial biomass while both soil N mineralisation and nitrificationincreased. This increased rate of turnover of the microbial biomass and thecontribution of N₂ fixation to the legume resulted in largeincreasesin the N recycled via litter deposition ranging from 42 to 155 kg Nha^–1 year^–1.     

Distributed Latency-Energy Minimization and interference avoidance in TDMA Wireless Sensor Networks

This paper presents Latency-Energy Minimization Medium Access (LEMMA), a new TDMA-based MAC protocol for Wireless Sensor Networks (WSNs), specially suited to extend the lifetime of networks supporting alarm-driven, delay-sensitive applications characterized by convergecast traffic patterns and sporadic traffic generation. Its cascading time-slot assignment scheme conciliates low end-to-end latency with a low duty-cycle, while supporting multi-sink WSN topologies. Unlike most of the current solutions, LEMMA’s time-slot allocation protocol makes decisions based on the interference actually experienced by the nodes, instead of following the simple but potentially ineffective n-hop approach. Simulation results are presented to demonstrate the ineffectiveness of the n-hop time-slot allocation in comparison with LEMMA, as well as to evaluate the performance of LEMMA against L-MAC, T-MAC and Low Power Listening. The results show that under the target scenario conditions, LEMMA presents lower interference between assigned time-slots and lower end-to-end latency, while matching its best contender in terms of energy-efficiency.     

Transmission power and data rate aware routing on wireless networks

Wireless networks can vary both the transmission power and modulation of links. Existing routing protocols do not take transmission power control (TPC) and modulation adaptation (also known as rate adaptation – RA) into account at the same time, even though the performance of wireless networks can be significantly improved when routing algorithms use link characteristics to build their routes. This article proposes and evaluates extensions to routing protocols to cope with TPC and RA. The enhancements can be applied to any link state or distance vector routing protocols. An evaluation considering node density, node mobility and link error show that TPC- and RA-aware routing algorithms improve the average latency and the end-to-end throughput, while consuming less energy than traditional protocols.     

Compact yet efficient hardware implementation of artificial neural networks with customized topology

There are several neural network implementations using either software, hardware-based or a hardware/software co-design. This work proposes a hardware architecture to implement an artificial neural network (ANN), whose topology is the multilayer perceptron (MLP). In this paper, we explore the parallelism of neural networks and allow on-the-fly changes of the number of inputs, number of layers and number of neurons per layer of the net. This reconfigurability characteristic permits that any application of ANNs may be implemented using the proposed hardware. In order to reduce the processing time that is spent in arithmetic computation, a real number is represented using a fraction of integers. In this way, the arithmetic is limited to integer operations, performed by fast combinational circuits. A simple state machine is required to control sums and products of fractions. Sigmoid is used as the activation function in the proposed implementation. It is approximated by polynomials, whose underlying computation requires only sums and products. A theorem is introduced and proven so as to cover the arithmetic strategy of the computation of the activation function. Thus, the arithmetic circuitry used to implement the neuron weighted sum is reused for computing the sigmoid. This resource sharing decreased drastically the total area of the system. After modeling and simulation for functionality validation, the proposed architecture synthesized using reconfigurable hardware. The results are promising.     

Preference-based multi-objective evolutionary algorithms for power-aware application mapping on NoC platforms

Network-on-chip (NoC) are considered the next generation of communication infrastructure in embedded systems. In the platform-based design methodology, an application is implemented by a set of collaborative intellectual property (IP) blocks. The selection of the most suited set of IPs as well as their physical mapping onto the NoC infrastructure to implement efficiently the application at hand are two hard combinatorial problems that occur during the synthesis process of Noc-based embedded system implementation. In this paper, we propose an innovative preference-based multi-objective evolutionary methodology to perform the assignment and mapping stages. We use one of the well-known and efficient multi-objective evolutionary algorithms NSGA-II and microGA as a kernel. The optimization processes of assignment and mapping are both driven by the minimization of the required silicon area and imposed execution time of the application, considering that the decision maker’s preference is a pre-specified value of the overall power consumption of the implementation.     

Lennard-Jones Viscosities in Wide Ranges of Temperature and Density: Fast Calculations Using a Steady–State Periodic Perturbation Method

A method for fast calculation of viscosity from molecular dynamics simulation is revisited. The method consists of using a steady-state periodic perturbation. A methodology to choose the amplitude of the external perturbation, which is one of the major practical issues in the original technique of Gosling et al. [Mol. Phys. 26: 1475 (1973)] is proposed. The amplitude of the perturbation required for fast caculations and the viscosity values for wide ranges of temperature and density of the Lennard-Jones (LJ) model fluid are reported. The viscosity results are in agreement with recent LJ viscosity calculations. Additionally, the simulations demonstrate that the proposed approach is suitable to efficiently generate viscosity data of good quality.     

The interplay of electronic structure,molecular orientation and charge transport in organic semiconductors: Poly(thiophene) and poly(bithiophene)

Ultrathin films of poly(thiophene) (PT) and poly(bithiophene) (PBT) were prepared by electrochemical route using ionic liquid (BFEE) as medium and electrolyte. Distinct morphologies and electrical properties were observed in these materials. To evaluate its response in photovoltaics, these films were used as active layer in bilayer geometry solar cells with the electron acceptor molecule C₆₀. The best performance was observed for PT films. In order to probe the differences in molecular dynamics and structural order, ultrafast electron dynamics in the low-femtosecond regime was evaluated by resonant Auger spectroscopy using the core–hole clock method at the sulfur K absorption edge. Electron delocalization times for the different polymeric films were derived as a function of the excitation energy. Photoabsorption measurements were conducted and molecular orientation derived. These results corroborated with the morphology found for these films and thus the performance of PT and PBT in the devices, and with the proposed conduction mechanism.     

Nonwoven Ni–NiO/carbon fibers for electrochemical water oxidation

The development of technologically efficient anodes for water oxidation is crucial to improve hydrogen production via water splitting. Electrodes based on metallic active sites dispersed in carbon matrices have been shown to be an attractive way to attain this goal. However, challenges remain to prevent catalyst agglomeration that otherwise can result in a decrease of performance over time.In this work, we report an alternative and efficient method to produce nickel-nickel oxide nanoparticles-embedded in carbon nanofibers (Ni–NiO/C), by the solution blow spinning (SBS) process. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses show the carbon nanofibrillar matrix as a robust support, with well-dispersed nickel nanoparticles on the surface. The responses of the linear scanning voltammetry, cyclic voltammetry and electrochemical impedance spectroscopy demonstrate how a small fraction of nickel on the fiber surface (≈1.2–5.3%) is enough to promote substantial improvement in performance (η = 278 and 309 mV vs RHE for 10 mA cm^?2) and a significant turnover frequency (TOF) values of 1.38 (η = 278) and 1.30 s^?1 (η = 309). These promising results are correlated with a large amount of Ni³⁺ present on the fiber surfaces, as identified by X-ray Photoelectron Spectroscopy (XPS). This work provides a low-cost and rapid preparation technique that can be extended for the manufacture of a wide variety of electrodes based on metals supported on carbon nanofibers.