Methodology for material property determination

Predicting solid material pyrolysis requires numerous parameters/properties that are time consuming and difficult to measure. Multiobjective optimization techniques have been used to determine these parameters; however, a methodology for the types of tests needed for the optimization and parameters that should be optimized versus measured has not been fully established. This study investigated combinations of testing protocols and parameters for optimization to determine a testing and optimization methodology that results in the accurate parameters. A Shuffled Complex Evolution (SCE) optimization routine was used to determine parameters based on some parameters being known (ie, measured) and others being determined through optimization and different combinations of types of input data. The results indicate that material testing should be done at three different heating rates in a thermogravimetric analyzer (TGA) and at three different heat fluxes in the cone calorimeter. The TGA tests and two cone calorimeter tests are input into the SCE optimization routine to determine the remaining parameters. The third cone calorimeter test is used to validate the parameters determined using the methodology. The method provides parameters within 20% of the actual parameters input into the Fire Dynamics Simulator (FDS) virtual experiment models. This method is applied to Polymethyl methacrylate (PMMA) experimental data to prove effectiveness.     

Ultrastructure of motor nerve terminals in the anterior third of wistar rat tongue

The nerve terminals of intrinsic muscular fibers of the tongue of adult wistar rats was studied by using silver impregnation techniques, transmission electron microscopy (TEM), and high resolution scanning electron microscopy (HRSEM) to observe the nerve fibers and their terminals. Silver impregnation was done according to Winkelman and Schmit, 1957 . For TEM, small blocks were fixed in modified Karnovsky solution, postfixed in 1% buffered osmium tetroxide solution, and embedded in Spurr resin. For HRSEM, the parts were fixed in 2% osmium tetroxide solution with 1/15 M sodium phosphate buffer (pH 7.4) at 4°C for 2 h, according to the technique described by Tanaka, 1989 . Thick myelinated nerve bundles were histologically observed among the muscular fibers. The intrafusal nerve fiber presented a tortuous pathway with punctiform terminal axons in clusters contacting the surface of sarcolemma. Several myelinated nerve fibers involved by collagen fibers of the endoneurium were observed in HRSEM in three-dimensional aspects. The concentric lamellae of the myelin sheath and the axoplasm containing neurofilaments interspersed among the mitochondria were also noted. In TEM, myofibrils, mitochondria, rough endoplasmic reticulum, Golgi's apparatus, and glycogen granules were observed in sarcoplasm. It is also noted that the sarcomeres constituted by myofilaments with their A, I, and H bands and the electron dense Z lines. In areas adjacent to muscular fibers, there were myelinated and unmyelinated nerve fibers involved by endoneurium and perineurium. In the region of the neuromuscular junction, the contact with the sarcolemma of the muscular cell occurs forming several terminal buttons and showing numerous evaginations of the cell membrane. In the terminal button, mitochondria and numerous synaptic vesicles were observed. Microsc. Res. Tech., 2009. © 2009 Wiley-Liss, Inc.     

Synthesis and characterization of carboxymethylated red angico (Anadenanthera macrocarpa) exudate polysaccharide

Red angico is a heteropolysaccharide (arabinogalactan) obtained from Anadenanthera macrocarpa trees. Carboxymethylation of angico gum (AG) with monochloroacetic acid (MCA) in alkaline aqueous medium resulted in samples which were characterized by ¹³C nuclear magnetic resonance spectroscopy and gel permeation chromatography. The effects of reaction parameters, such as alkali concentration, MCA/AG ratio and temperature on the reaction yield and degree of substitution (DS) were investigated. The DS and MCA total efficiency values increase up to 2 h reaction time and then decrease. The DS varied from 0.11 to 1.10 depending on NaOH/MCA/AG ratio and temperature. The highest MCA total efficiency (0.57) was obtained for NaOH/MCA/AG molar ratio equal to 3:1:1, at 70°C. (DS = 0.63, yield = 91.0%). Nuclear magnetic resonance (NMR) and gel permeation chromatography (GPC) analysis shows that polymer degradation was observed in all samples. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 2985–2991, 2007     

Performance Analysis of Network Traffic Predictors in the Cloud

Predicting the inherent traffic behaviour of a network is an essential task, which can be used for various purposes, such as monitoring and managing the network’s infrastructure. However, the recent surge of dynamic environments, such as Internet of Things and Cloud Computing have hampered this task. This means that the traffic on these networks is even more complex, displaying a nonlinear behaviour with specific aperiodic characteristics during daily operation. Traditional network traffic predictors are usually based on large historical data bases which are used to train algorithms. This may not be suitable for these highly volatile environments, where the strength of the force exerted in the interaction between past and current values may change quickly with time. In light of this, a taxonomy for network traffic prediction models, including the review of state of the art, is presented here. In addition, an analysis mechanism, focused on providing a standardized approach for evaluating the best candidate predictor models for these environments, is proposed. These contributions favour the analysis of the efficacy and efficiency of network traffic prediction among several prediction models in terms of accuracy, historical dependency, running time and computational overhead. An evaluation of several prediction mechanisms is performed by assessing the Normalized Mean Square Error and Mean Absolute Percent Error of the values predicted by using traces taken from two real case studies in cloud computing.