Network connectance and autonomy analyses of the photosynthetic apparatus in tropical tree species from different successional groups under contrasting irradiance conditions

Biological systems are complex dynamical systems whose relationships with environment have strong implications on their regulation and survival. From the interactions between plant and environment can emerge a quite complex network of plant responses rarely observed through classical analytical approaches. The objective of this current study was to test the hypothesis that photosynthetic responses of different tree species to increasing irradiance are related to changes in network connectances of gas exchange and photochemical apparatus, and alterations in plant autonomy in relation to the environment. The heat dissipative capacity through daily changes in leaf temperature was also evaluated. It indicated that the early successional species (Citharexylum myrianthum Cham. and Rhamnidium elaeocarpum Reiss.) were more efficient as dissipative structures than the late successional one (Cariniana legalis (Mart.) Kuntze), suggesting that the parameter deltaT (T ºCair - T ºCleaf) could be a simple tool in order to help the classification of successional classes of tropical trees. Our results indicated a pattern of network responses and autonomy changes under high irradiance. Considering the maintenance of daily CO2 assimilation, the tolerant species (C. myrianthum and R. elaeocarpum) to high irradiance trended to maintain stable the level of gas exchange network connectance and to increase the autonomy in relation to the environment. On the other hand, the late successional species (C. legalis) trended to lose autonomy, decreasing the network connectance of gas exchange. All species showed lower autonomy and higher network connectance of the photochemical apparatus under high irradiance.

The brain decade in debate: I. Neurobiology of learning and memory

This article is a transcription of an electronic symposium in which some active researchers were invited by the Brazilian Society for Neuroscience and Behavior (SBNeC) to discuss the last decade's advances in neurobiology of learning and memory. The way different parts of the brain are recruited during the storage of different kinds of memory (e.g., short-term vs long-term memory, declarative vs procedural memory) and even the property of these divisions were discussed. It was pointed out that the brain does not really store memories, but stores traces of information that are later used to create memories, not always expressing a completely veridical picture of the past experienced reality. To perform this process different parts of the brain act as important nodes of the neural network that encode, store and retrieve the information that will be used to create memories. Some of the brain regions are recognizably active during the activation of short-term working memory (e.g., prefrontal cortex), or the storage of information retrieved as long-term explicit memories (e.g., hippocampus and related cortical areas) or the modulation of the storage of memories related to emotional events (e.g., amygdala). This does not mean that there is a separate neural structure completely supporting the storage of each kind of memory but means that these memories critically depend on the functioning of these neural structures. The current view is that there is no sense in talking about hippocampus-based or amygdala-based memory since this implies that there is a one-to-one correspondence. The present question to be solved is how systems interact in memory. The pertinence of attributing a critical role to cellular processes like synaptic tagging and protein kinase A activation to explain the memory storage processes at the cellular level was also discussed.

Rheological and structural evaluations of commercial italian salad dressings

The emulsion stability, composition, structure and rheology of four different commercial italian salad dressings manufactured with traditional and light formulations were evaluated. According to the results, the fat content ranged from 8% (w/w) (light) to 34% (w/w) (traditional), the carbohydrate concentration varied between 3.8% (w/w) (traditional) and 14.4% (w/w) (light) and the pH was between 3.6-3.9 for all samples. The microscopic and stability analyses showed that the only stable salad dressing was a light sample, which had the smallest droplet size when compared with the other samples. With respect to the rheological behaviour, all the salad dressings were characterized as thixotropic and shear thinning fluids. However, the stable dressing showed an overshoot at relatively low shear rates. This distinct rheological behavior being explained by the differences in its composition, particularly the presence of a maltodextrin network.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

Biomassa residual para remoção de íons uranilo

Activities related to nuclear industry, production of phosphoric acid and hospitals have generated considerable volumes of radioactive waste containing uranyl ions. Banana pith was characterized by Scanning Electron Microscopy and Fourier Transform Infrared Spectroscopy and was investigated as a biosorbent for uranyl ions from nitric solutions by batch experiments. Influences of adsorbent size, kinetics and equilibrium adsorption were studied. The biosorption of the uranyl ions followed pseudo-second-order kinetics. The adsorption isotherm data were closely fitted to the Freundlich equation.