REATIVAÇÃO DE VOÇOROCAS EM RESPOSTA A MUDANÇA DE USO PASTORIL PARA PLANTIO DE EUCALIPTO EM VALES DE CABECEIRAS ADJACENTES: MÉDIO VALE DO RIO PARAÍBA DO SUL.

Este estudo busca o entendimento dos processos hidrológicos e erosivos associados ao desenvolvimento de canais incisos do tipo voçoroca, conectadas a expansão da rede de canais no domínio dos vales de cabeceiras de drenagem, em resposta a mudanças de uso do solo decorrente da introdução de plantios de eucalipto em antigas áreas de pastagens

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Magnetizer design based on a quasi-oppositional gravitational search algorithm

The gravitational search algorithm (GSA) is a novel metaheuristics approach inspired by the laws of gravitation and motion. In GSA, a set of agents, called masses, searches the design space to find the optimal solution by simulation of Newtonian laws of gravity and motion. In this paper, a standard and an improved GSA (IGSA) approach based on a quasi-oppositional approach are presented and tested on a magnetic pole design benchmark. Results indicate that the performance of proposed IGSA on the magnetic pole design is better than that of classical GSA. © 1965-2012 IEEE

Economic Load Dispatch Using a Chemotactic Differential Evolution Algorithm

Abstract. This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques. 1

Harmony Search Algorithms in Structural Engineering

Harmony search method is widely applied in structural design optimization since its emergence. These applications have shown that harmony search algorithm is robust, effective and reliable optimization method. Within recent years several enhancements are suggested to improve the performance of the algorithm. Among these Mandavi has presented two versions of harmony search methods. He named these as improved harmony search method and global best harmony search method. Saka and Hasancebi (2009) have suggested adaptive harmony search where the harmony search parameters are adjusted automatically during design iterations. Coelho has proposed improved harmony search method. He suggested an expression for one of the parameters of standard harmony search method. In this chapter, the optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Corporation): The weight of the steel frame is taken as the objective function to be minimized. Seven different structural optimization algorithms are developed each of which are based on one of the above mentioned versions of harmony search method. Three real size steel frames are designed using each of these algorithms. The optimum designs obtained by these techniques are compared and performance of each version is evaluated