Solos das áreas-piloto do projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), município de Benjamin Constant, Estado do Amazonas.

2005

Hibridização genômica in situ em triticeae: um enfoque metodológico.

2009

Avaliação participativa do manejo de agroecossistemas e capacitação em agroecologia utilizando indicadores de sustentabilidade de determinação rápida e fácil.

2006

Avaliação de plantas com potencial inseticida no controle da Vaquinha-do-feijoeiro (Cerotoma tingomarianus Bechyné).

Através deste trabalho, avaliou-se a atividade inseticida de extratos aquosos e alcoólicos de várias partes de plantas de 13 espécies vegetais, exóticas e nativas da Amazônia brasileira, em adultos de Cerotoma tingomarianus.

Mal do caroço.

Como evitar Como tratar.

Manejo de pragas em hortaliças durante a transição agroecológica.

2013

Potencialidades da pimenta-de-macaco (Piper aduncum L.): características gerais e resultados de pesquisa.

A diversidade da flora brasileira, em especial a da Região Amazônica, apresenta um imenso potencial para a produção de compostos secundários de plantas, que têm sido demandados continuamente pela indústria nas últimas décadas, devido ao incremento da utilização de produtos naturais na agropecuária. Estima-se que existam 500 mil espécies de plantas no mundo, sendo .16% delas encontradas na florésta amazônica. No entanto, a pesquisa de substâncias ativas derivadas de plantas no Brasil ainda é muito incipiente. Mesmo considerando os incrementos significativos da pesquisa nas últimas duas décadas, há, evidentemente, uma grande lacuna de conhecimento da nossa flora a ser preenchida. A partir da década de 90 a Embrapa Acre vem intensificando atividades de pesquisa no sentido de viabilizar a utilização de recursos não-madeireiros das florestas do Acre. Destacam-se dentre eles, produtos promissores oriundos de piperáceas, como o óleo essencial rico em safrol, produzido a partir da biomassa da Piper hispidinervum e, mais recentemente, o óleo essencial de P. aduncum com altos teores de dilapiol. P. aduncum é uma espécie de planta que vem apresentando um crescente interesse, principalmente quanto à extração em escala industrial do seu óleo essencial. A elaboração deste documento tem como finalidade contribuir para o conhecimento da potencialidade do emprego dessa planta na elaboração de produtos para o controle de pragas de interesse agropecuário e utilização na medicina humana.

Cultivares de alho para agricultura orgânica.

2014

An Active Pattern Recognition Architecture for Mobile Robots

An active, attentionally-modulated recognition architecture is proposed for object recognition and scene analysis. The proposed architecture forms part of navigation and trajectory planning modules for mobile robots. Key characteristics of the system include movement planning and execution based on environmental factors and internal goal definitions. Real-time implementation of the system is based on space-variant representation of the visual field, as well as an optimal visual processing scheme utilizing separate and parallel channels for the extraction of boundaries and stimulus qualities. A spatial and temporal grouping module (VWM) allows for scene scanning, multi-object segmentation, and featural/object priming. VWM is used to modulate a tn~ectory formation module capable of redirecting the focus of spatial attention. Finally, an object recognition module based on adaptive resonance theory is interfaced through VWM to the visual processing module. The system is capable of using information from different modalities to disambiguate sensory input.

Learning Temporal Contexts and Priming-Preparation Modes for Pattern Recognition

The system presented here is based on neurophysiological and electrophysiological data. It computes three types of increasingly integrated temporal and probability contexts, in a bottom-up mode. To each of these contexts corresponds an increasingly specific top-down priming effect on lower processing stages, mostly pattern recognition and discrimination. Contextual learning of time intervals, events' temporal order or sequential dependencies and events' prior probability results from the delivery of large stimuli sequences. This learning gives rise to emergent properties which closely match the experimental data.

Cerebellar Learning in an Opponent Motor Controller for Adaptive Load Compensation and Synergy Formation

This paper shows how a minimal neural network model of the cerebellum may be embedded within a sensory-neuro-muscular control system that mimics known anatomy and physiology. With this embedding, cerebellar learning promotes load compensation while also allowing both coactivation and reciprocal inhibition of sets of antagonist muscles. In particular, we show how synaptic long term depression guided by feedback from muscle stretch receptors can lead to trans-cerebellar gain changes that are load-compensating. It is argued that the same processes help to adaptively discover multi-joint synergies. Simulations of rapid single joint rotations under load illustrates design feasibility and stability.

A Fast BCS/FCS Algorithm for Image Segmentation

A fast and efficient segmentation algorithm based on the Boundary Contour System/Feature Contour System (BCS/FCS) of Grossberg and Mingolla [3] is presented. This implementation is based on the FFT algorithm and the parallelism of the system.

Navite: A Neural Network System For Sensory-Based Robot Navigation

A neural network system, NAVITE, for incremental trajectory generation and obstacle avoidance is presented. Unlike other approaches, the system is effective in unstructured environments. Multimodal inforrnation from visual and range data is used for obstacle detection and to eliminate uncertainty in the measurements. Optimal paths are computed without explicitly optimizing cost functions, therefore reducing computational expenses. Simulations of a planar mobile robot (including the dynamic characteristics of the plant) in obstacle-free and object avoidance trajectories are presented. The system can be extended to incorporate global map information into the local decision-making process.

How Spinal Neural Networks Reduce Discrepancies between Motor Intention and Motor Realization

This paper attempts a rational, step-by-step reconstruction of many aspects of the mammalian neural circuitry known to be involved in the spinal cord's regulation of opposing muscles acting on skeletal segments. Mathematical analyses and local circuit simulations based on neural membrane equations are used to clarify the behavioral function of five fundamental cell types, their complex connectivities, and their physiological actions. These cell types are: α-MNs, γ-MNs, IaINs, IbINs, and Renshaw cells. It is shown that many of the complexities of spinal circuitry are necessary to ensure near invariant realization of motor intentions when descending signals of two basic types independently vary over large ranges of magnitude and rate of change. Because these two types of signal afford independent control, or Factorization, of muscle LEngth and muscle TEnsion, our construction was named the FLETE model (Bullock and Grossberg, 1988b, 1989). The present paper significantly extends the range of experimental data encompassed by this evolving model.

An Integrated Neural Network-Event-Related Potentials Model of Temporal and Probability Context Effects on Event Categorization

We present a neural network that adapts and integrates several preexisting or new modules to categorize events in short term memory (STM), encode temporal order in working memory, evaluate timing and probability context in medium and long term memory. The model shows how processed contextual information modulates event recognition and categorization, focal attention and incentive motivation. The model is based on a compendium of Event Related Potentials (ERPs) and behavioral results either collected by the authors or compiled from the classical ERP literature. Its hallmark is, at the functional level, the interplay of memory registers endowed with widely different dynamical ranges, and at the structural level, the attempt to relate the different modules to known anatomical structures.