Comparing Near-infrared Conventional Diffuse Reflectance Spectroscopy And Hyperspectral Imaging For Determination Of The Bulk Properties Of Solid Samples By Multivariate Regression: Determination Of Mooney Viscosity And Plasticity Indices Of Natural Rubber.

Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

Learning processes and the neural analysis of conditioning

Classical and operant conditioning principles, such as the behavioral discrepancy-derived assumption that reinforcement always selects antecedent stimulus and response relations, have been studied at the neural level, mainly by observing the strengthening of neuronal responses or synaptic connections. A review of the literature on the neural basis of behavior provided extensive scientific data that indicate a synthesis between the two conditioning processes based mainly on stimulus control in learning tasks. The resulting analysis revealed the following aspects. Dopamine acts as a behavioral discrepancy signal in the midbrain pathway of positive reinforcement, leading toward the nucleus accumbens. Dopamine modulates both types of conditioning in the Aplysia mollusk and in mammals. In vivo and in vitro mollusk preparations show convergence of both types of conditioning in the same motor neuron. Frontal cortical neurons are involved in behavioral discrimination in reversal and extinction procedures, and these neurons preferentially deliver glutamate through conditioned stimulus or discriminative stimulus pathways. Discriminative neural responses can reliably precede operant movements and can also be common to stimuli that share complex symbolic relations. The present article discusses convergent and divergent points between conditioning paradigms at the neural level of analysis to advance our knowledge on reinforcement.

PARTITIONED ANALYSIS FOR DIMENSIONALLY-HETEROGENEOUS HYDRAULIC NETWORKS

In this work an iterative strategy is developed to tackle the problem of coupling dimensionally-heterogeneous models in the context of fluid mechanics. The procedure proposed here makes use of a reinterpretation of the original problem as a nonlinear interface problem for which classical nonlinear solvers can be applied. Strong coupling of the partitions is achieved while dealing with different codes for each partition, each code in black-box mode. The main application for which this procedure is envisaged arises when modeling hydraulic networks in which complex and simple subsystems are treated using detailed and simplified models, correspondingly. The potentialities and the performance of the strategy are assessed through several examples involving transient flows and complex network configurations.

A simple method for non-linear analysis of steel fiber reinforced concrete

This paper proposes a physical non-linear formulation to deal with steel fiber reinforced concrete by the finite element method. The proposed formulation allows the consideration of short or long fibers placed arbitrarily inside a continuum domain (matrix). The most important feature of the formulation is that no additional degree of freedom is introduced in the pre-existent finite element numerical system to consider any distribution or quantity of fiber inclusions. In other words, the size of the system of equations used to solve a non-reinforced medium is the same as the one used to solve the reinforced counterpart. Another important characteristic of the formulation is the reduced work required by the user to introduce reinforcements, avoiding ""rebar"" elements, node by node geometrical definitions or even complex mesh generation. Bounded connection between long fibers and continuum is considered, for short fibers a simplified approach is proposed to consider splitting. Non-associative plasticity is adopted for the continuum and one dimensional plasticity is adopted to model fibers. Examples are presented in order to show the capabilities of the formulation.

GENERALIZED FINITE ELEMENT METHOD FOR NONLINEAR THREE-DIMENSIONAL ANALYSIS OF SOLIDS

The Generalized Finite Element Method (GFEM) is employed in this paper for the numerical analysis of three-dimensional solids tinder nonlinear behavior. A brief summary of the GFEM as well as a description of the formulation of the hexahedral element based oil the proposed enrichment strategy are initially presented. Next, in order to introduce the nonlinear analysis of solids, two constitutive models are briefly reviewed: Lemaitre`s model, in which damage and plasticity are coupled, and Mazars`s damage model suitable for concrete tinder increased loading. Both models are employed in the framework of a nonlocal approach to ensure solution objectivity. In the numerical analyses carried out, a selective enrichment of approximation at regions of concern in the domain (mainly those with high strain and damage gradients) is exploited. Such a possibility makes the three-dimensional analysis less expensive and practicable since re-meshing resources, characteristic of h-adaptivity, can be minimized. Moreover, a combination of three-dimensional analysis and the selective enrichment presents a valuable good tool for a better description of both damage and plastic strain scatterings.

Long-Term Astroglial Reaction and Neuronal Plasticity in the Subcortical Visual Pathways After a Complete Ablation of Telencephalon in Pigeons (Columba livia)

This paper analyzes the astroglial and neuronal responses in subtelencephalic structures, following a bilateral ablation of the telencephalon in the Columba livia pigeons. Control birds received a sham operation. Four months later the birds were sacrificed and their brains processed for glial fribillary acid protein (GFAP) and neurofilament immunohistochemistry, markers for astrocytes and neurons, respectively. Computer-assisted image analysis was employed for quantification of the immunoreactive labeling in the nucleus rotundus (N.Rt) and the optic tectum (OT) of the birds. An increased number of GFAP immunoreactive astrocytes were found in several subregions of the N.Rt (p .001), as well as in layers 1, 2cd, 3, and 6 of the OT (p .001) of the lesioned animals. Neurofilament immunoreactivity decreased massively in the entire N.Rt of the lesioned birds; however, remaining neurons with healthy aspect showing large cytoplasm and ramified branches were detected mainly in the periphery of the nucleus. In view of the recently described paracrine neurotrophic properties of the activated astrocytes, the data of the present study may suggest a long-lasting neuroglial interaction in regions of the lesioned bird brain far from injury. Such events may trigger neuronal plasticity in remaining brain structures that may lead spontaneous behavior recovery as the one promoted here even after a massive injury.

Qualitative analysis of hippocampal plastic changes in rats with epilepsy supplemented with oral omega-3 fatty acids

Studies have provided evidence of the important effects of omega-3 fatty acid on the brain in neurological conditions, including epilepsy. Previous data have indicated that omega-3 fatty acids lead to prevention of status epilepticus-associated neuropathological changes in the hippocampal formation of rats with epilepsy. Omega-3 fatty acid supplementation has resulted in extensive preservation of GABAergic cells in animals with epilepsy. This study investigated the interplay of these effects with neurogenesis and brain-derived neurotrophic factor (BDNF). The results clearly showed a positive effect of long-term omega-3 fatty acid supplementation on brain plasticity in animals with epilepsy. Enhanced hippocampal neurogenesis and BDNF levels and preservation of interneurons expressing parvalbumin were observed. Parvalbumin-positive cells were identified as surviving instead of newly formed cells. Additional investigations are needed to determine the electrophysiological properties of the newly formed cells and to clarify whether the effects of omega-3 fatty acids on brain plasticity are accompanied by functional gain in animals with epilepsy. (C) 2009 Elsevier Inc. All rights reserved.

Plasticity of Opioid Receptors in the Female Periaqueductal Gray: Multiparity-Induced Increase in the Activity of Genes Encoding for Mu and Kappa Receptors and a Post-Translational Decrease in Delta Receptor Expression

The periaqueductal gray (PAG) has been reported as a potential site for opioid regulation of behavioral selection. Opioid-mediated behavioral and physiological responses differ between nulliparous and multiparous females. This study addresses the effects of multiple reproductive experiences on mu-, kappa- and delta-opioid receptor (Oprm1, Oprk1, and Oprd1 respectively) gene activity and mu, kappa and delta protein expression (MOR, KOR and DOR respectively) in the PAG of the female rats. This was done by evaluating the opioid gene expression using real-time (RT-PCR) and quantification of each protein receptor by Western blot analysis. The RT-PCR results show that multiple reproductive experiences increase Oprm1 and Oprk1 gene expression. Western blot analysis revealed increased MOR and KOR while DOR protein was decreased in multiparous animals. Taken together, these data suggest that multiple reproductive experiences influence both gene activity and opioid receptor expression in the PAG. Post-translational mechanisms seem particularly relevant for DOR expression. Thus, opioid transmission in the PAG might be modulated by different mechanisms of multiparity-induced plasticity according to the opioid receptor type.

Invertebrate D2 type dopamine receptor exhibits age-based plasticity of expression in the mushroom bodies of the honeybee brain

We have isolated a cDNA clone from the honeybee brain encoding a dopamine receptor, AmDop2, which is positively coupled to adenylyl cyclase. The transmembrane domains of this receptor are 88% identical to the orthologous Drosophila D2 dopamine receptor, DmDop2, though phylogenetic analysis and sequence homology both indicate that invertebrate and vertebrate D2 receptors are quite distinct. In situ hybridization to mRNA in whole-mount preparations of honeybee brains reveals gene expression in the mushroom bodies, a primary site of associative learning. Furthermore, two anatomically distinct cell types in the mushroom bodies exhibit differential regulation of AmDop2 expression. In all nonreproductive females (worker caste) and reproductive males (drones) the receptor gene is strongly and constitutively expressed in all mushroom body interneurons with small cell bodies. In contrast, the large cell-bodied interneurons exhibit dramatic plasticity of AmDop2 gene expression. In newly emerged worker bees (cell-cleaning specialists) and newly emerged drones, no AmDop2 transcript is observed in the large interneurons whereas this transcript is abundant in these cells in the oldest worker bees (resource foragers) and older drones. Differentiation of the mushroom body interneurons into two distinct classes (i.e., plastic or nonplastic with respect to AmDop2 gene expression) indicates that this receptor contributes to the differential regulation of distinct neural circuits. Moreover, the plasticity of expression observed in the large cells implicates this receptor in the behavioral maturation of the bee.

Automated image analysis of lung branching morphogenesis

Regulating mechanisms of branchingmorphogenesis of fetal lung rat explants have been an essential tool formolecular research.This work presents a new methodology to accurately quantify the epithelial, outer contour, and peripheral airway buds of lung explants during cellular development frommicroscopic images. Methods.Theouter contour was defined using an adaptive and multiscale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelium was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds was counted as the skeleton branched ends from a skeletonized image of the lung inner epithelia. Results. The time for lung branching morphometric analysis was reduced in 98% in contrast to themanualmethod. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Nonsignificant differences were found between the automatic and manual results in all culture days. Conclusions. The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lighting characteristics and allowing a reliable comparison between different researchers.

Nanocomposites: the contribution of multiscale modelling to improve the dispersion levels

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Why are offspring born larger when it is colder? Phenotypic plasticity for offspring size in the cladoceran Simocephalus vetulus (Müller)

It has been predicted on theorerical grounds (Sibly & Calow, 1983; Taylor & Williams, 1984) that optimal offspring size should be highly sensitive to juvenile growth and survival rates. To test such models, genetically-identical individuals of Simicephalus vetulus were reared at different temperatures and monitored for offspring size and juvenile growth rate. As adult size correlates negatively with temperature, an analysis of covariance was performed to separate the effects of temperature and maternal size. The result is that offspring size indeed correlates negatively with juvenile growth rate. Comparisons are made with field observation of several authors on seasonal variation of offspring size and alternative explanations are discussed. It is concluded that present experiments support the prediction of the theoretical models.

Analysis of a finite volume element method for the Stokes problem

In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.

A protocol for preparing GFP-labeled neurons previously imaged in vivo and in slice preparations for light and electron microscopic analysis.

In vivo imaging of green fluorescent protein (GFP)-labeled neurons in the intact brain is being used increasingly to study neuronal plasticity. However, interpreting the observed changes as modifications in neuronal connectivity needs information about synapses. We show here that axons and dendrites of GFP-labeled neurons imaged previously in the live mouse or in slice preparations using 2-photon laser microscopy can be analyzed using light and electron microscopy, allowing morphological reconstruction of the synapses both on the imaged neurons, as well as those in the surrounding neuropil. We describe how, over a 2-day period, the imaged tissue is fixed, sliced and immuno-labeled to localize the neurons of interest. Once embedded in epoxy resin, the entire neuron can then be drawn in three dimensions (3D) for detailed morphological analysis using light microscopy. Specific dendrites and axons can be further serially thin sectioned, imaged in the electron microscope (EM) and then the ultrastructure analyzed on the serial images.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.