149 resultados para Functional displays
Resumo:
Metallic and other type of coatings on fiber Bragg grating (FBG) sensors alter their sensitivity with thermal and mechanical stress while protecting the fragile optical fiber in harsh sensing surroundings. The behavior of the coated materials is unique in their response to thermal and mechanical stress depending on the thickness and the mode of coating. The thermal stress during the coating affects the temperature sensitivity of FBG sensors. We have explored the thermal response of FBGs coated with Al and Pb to an average thickness of 80 nm using flash evaporation technique where the FBG sensor is mounted in a region at room temperature in an evacuated chamber having a pressure of 10(6) Torr which will minimize any thermal stress during the coating process. The coating thickness is chosen in the nanometer region with the aim to study thermal behavior of nanocoatings and their effect on FBG sensitivity. The sensitivity of FBGs is evaluated from the wavelengths recorded using an optical sensing interrogator sm 130 (Micron Optics) from room temperature to 300 degrees C both during heating and cooling. It is observed that the sensitivity of the metal coated fibers is better than the reference FBG with no coating for the entire range of temperature. For a coating thickness of 80 nm, Al coated FBG is more sensitive than the one coated with Pb up to 170 degrees C and it reverses at higher temperatures. This point is identified as a reversible phase transition in Pb monolayers as the 2-dimensional aspects of the metal layers are dominant in the nanocoatings of Pb. On cooling, the phase transition reverses and the FBGs return to the original state and for repeated cycles of heating and cooling the same pattern is observed. Thus the FBG functions as a sensor of the phase transitions of the coatings also. (C) 2012 Elsevier Inc. All rights reserved.
Resumo:
Diaminopropionate ammonia lyase (DAPAL) is a pyridoxal-5'phosphate (PLP)-dependent enzyme that catalyzes the conversion of diaminopropionate (DAP) to pyruvate and ammonia and plays an important role in cell metabolism. We have investigated the role of the ygeX gene of Escherichia coli K-12 and its ortholog, STM1002, in Salmonella enterica serovar Typhimurium LT2, presumed to encode DAPAL, in the growth kinetics of the bacteria. While Salmonella Typhimurium LT2 could grow on DL-DAP as a sole carbon source, the wild-type E. coli K-12 strain exhibited only marginal growth on DL-DAP, suggesting that DAPAL is functional in S. Typhimurium. The expression of ygeX in E. coli was low as detected by reverse transcriptase PCR (RT-PCR), consistent with the poor growth of E. coli on DL-DAP. Strains of S. Typhimurium and E. coli with STM1002 and ygeX, respectively, deleted showed loss of growth on DL-DAP, confirming that STM1002 (ygeX) is the locus encoding DAPAL. Interestingly, the presence of DL-DAP caused a growth inhibition of the wild-type E. coli strain as well as the knockout strains of S. Typhimurium and E. coli in minimal glucose/glycerol medium. Inhibition by DL-DAP was rescued by transforming the strains with plasmids containing the STM1002 (ygeX) gene encoding DAPAL or supplementing the medium with Casamino Acids. Growth restoration studies using media lacking specific amino acid supplements suggested that growth inhibition by DL-DAP in the absence of DAPAL is associated with auxotrophy related to the inhibition of the enzymes involved in the biosynthetic pathways of pyruvate and aspartate and the amino acids derived from them.
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A combination of ab initio and classical Monte Carlo simulations is used to investigate the effects of functional groups on methane binding. Using Moller-Plesset (MP2) calculations, we obtain the binding energies for benzene functionalized with NH2, OH, CH3, COOH, and H2PO3 and identify the methane binding sites. In all cases, the preferred binding sites are located above the benzene plane in the vicinity of the benzene carbon atom attached to the functional group. Functional groups enhance methane binding relative to benzene (-6.39 kJ/mol), with the largest enhancement observed for H2PO3 (-8.37 kJ/mol) followed by COOH and CH3 (-7.77 kJ/mol). Adsorption isotherms are obtained for edge-functionalized bilayer graphene nanoribbons using grand canonical Monte Carlo simulations with a five-site methane model. Adsorbed excess and heats of adsorption for pressures up to 40 bar and 298 K are obtained with functional group concentrations ranging from 3.125 to 6.25 mol 96 for graphene edges functionalized with OH, NH2, and COOH. The functional groups are found to act as preferred adsorption sites, and in the case of COOH the local methane density in the vicinity of the functional group is found to exceed that of bare graphene. The largest enhancement of 44.5% in the methane excess adsorbed is observed for COOH-functionalized nanoribbons when compared to H terminated ribbons. The corresponding enhancements for OH- and NH2-functionalized ribbons are 10.5% and 3.7%, respectively. The excess adsorption across functional groups reflects the trends observed in the binding energies from MP2 calculations. Our study reveals that specific site functionalization can have a significant effect on the local adsorption characteristics and can be used as a design strategy to tailor materials with enhanced methane storage capacity.
Resumo:
Narayanan R, Johnston D. Functional maps within a single neuron. J Neurophysiol 108: 2343-2351, 2012. First published August 29, 2012; doi:10.1152/jn.00530.2012.-The presence and plasticity of dendritic ion channels are well established. However, the literature is divided on what specific roles these dendritic ion channels play in neuronal information processing, and there is no consensus on why neuronal dendrites should express diverse ion channels with different expression profiles. In this review, we present a case for viewing dendritic information processing through the lens of the sensory map literature, where functional gradients within neurons are considered as maps on the neuronal topograph. Under such a framework, drawing analogies from the sensory map literature, we postulate that the formation of intraneuronal functional maps is driven by the twin objectives of efficiently encoding inputs that impinge along different dendritic locations and of retaining homeostasis in the face of changes that are required in the coding process. In arriving at this postulate, we relate intraneuronal map physiology to the vast literature on sensory maps and argue that such a metaphorical association provides a fresh conceptual framework for analyzing and understanding single-neuron information encoding. We also describe instances where the metaphor presents specific directions for research on intraneuronal maps, derived from analogous pursuits in the sensory map literature. We suggest that this perspective offers a thesis for why neurons should express and alter ion channels in their dendrites and provides a framework under which active dendrites could be related to neural coding, learning theory, and homeostasis.
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The vaporization characteristics of pendant droplets of various chemical compositions (like conventional fuels, alternative fuels and nanosuspensions) subjected to convective heating in a laminar air jet have been analyzed. Different heating conditions were achieved by controlling the air temperature and velocity fields around the droplet. A hybrid timescale has been proposed which incorporates the effects of latent heat of vaporization, saturation vapor pressure and thermal diffusivity. This timescale in essence encapsulates the different parameters that influence the droplet vaporization rate. The analysis further permits the evaluation of the effect of various parameters such as surrounding temperature, Reynolds number, far-field vapor presence, impurity content and agglomeration dynamics (nanosuspensions) in the droplet. Flow visualization has been carried out to understand the role of internal recirculation on the vaporization rate. The visualization indicates the presence of a single vortex cell within the droplet on account of the rotation and oscillation of the droplet due to aerodynamic load. External heating induced agglomeration in nanofluids leads to morphological changes during the vaporization process. These morphological changes and alteration in vaporization behavior have been assessed using high speed imaging of the diameter regression and Scanning Electron Microscopy images of the resultant precipitate. (C) 2012 Elsevier Ltd. All rights reserved.
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The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.
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Glycosyl hydrolase family 1 beta-glucosidases are important enzymes that serve many diverse functions in plants including defense, whereby hydrolyzing the defensive compounds such as hydroxynitrile glucosides. A hydroxynitrile glucoside cleaving beta-glucosidase gene (Llbglu1) was isolated from Leucaena leucocephala, cloned into pET-28a (+) and expressed in E. coli BL21 (DE3) cells. The recombinant enzyme was purified by Ni-NTA affinity chromatography. The optimal temperature and pH for this beta-glucosidase were found to be 45 A degrees C and 4.8, respectively. The purified Llbglu1 enzyme hydrolyzed the synthetic glycosides, pNPGlucoside (pNPGlc) and pNPGalactoside (pNPGal). Also, the enzyme hydrolyzed amygdalin, a hydroxynitrile glycoside and a few of the tested flavonoid and isoflavonoid glucosides. The kinetic parameters K (m) and V (max) were found to be 38.59 mu M and 0.8237 mu M/mg/min for pNPGlc, whereas for pNPGal the values were observed as 1845 mu M and 0.1037 mu M/mg/min. In the present study, a three dimensional (3D) model of the Llbglu1 was built by MODELLER software to find out the substrate binding sites and the quality of the model was examined using the program PROCHEK. Docking studies indicated that conserved active site residues are Glu 199, Glu 413, His 153, Asn 198, Val 270, Asn 340, and Trp 462. Docking of rhodiocyanoside A with the modeled Llbglu1 resulted in a binding with free energy change (Delta G) of -5.52 kcal/mol on which basis rhodiocyanoside A could be considered as a potential substrate.
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Peptidase N (PepN), the sole M1 family member in Escherichia coli, displays broad substrate specificity and modulates stress responses: it lowers resistance to sodium salicylate (NaSal)-induced stress but is required during nutritional downshift and high temperature (NDHT) stress. The expression of PepN does not significantly change during different growth phases in LB or NaSal-induced stress; however, PepN amounts are lower during NDHT stress. To gain mechanistic insights on the roles of catalytic activity of PepN in modulating these two stress responses, alanine mutants of PepN replacing E264 (GAMEN motif) and E298 (HEXXH motif) were generated. There are no major structural changes between purified wild type (WT) and mutant proteins, which are catalytically inactive. Importantly, growth profiles of Delta pepN upon expression of WT or mutant proteins demonstrated the importance of catalytic activity during NDHT but not NaSal-induced stress. Further fluorescamine reactivity studies demonstrated that the catalytic activity of PepN is required to generate higher intracellular amounts of free N-terminal amino acids; consequently, the lower growth of Delta pepN during NDHT stress increases with high amounts of casamino acids. Together, this study sheds insights on the expression and functional roles of the catalytic activity of PepN during adaptation to NDHT stress. (C) 2012 Elsevier GmbH. All rights reserved.
Resumo:
We consider the problem of optimal routing in a multi-stage network of queues with constraints on queue lengths. We develop three algorithms for probabilistic routing for this problem using only the total end-to-end delays. These algorithms use the smoothed functional (SF) approach to optimize the routing probabilities. In our model all the queues are assumed to have constraints on the average queue length. We also propose a novel quasi-Newton based SF algorithm. Policies like Join Shortest Queue or Least Work Left work only for unconstrained routing. Besides assuming knowledge of the queue length at all the queues. If the only information available is the expected end-to-end delay as with our case such policies cannot be used. We also give simulation results showing the performance of the SF algorithms for this problem.
Resumo:
Density functional theory (DFT) calculations are being performed to investigate the geometric, vibrational, and electronic properties of the chlorogenic acid isomer 3-CQA (1R,3R,4S,5R)-3-{(2E)-3-(3,4-dihydroxyphenyl)prop-2-enoyl]oxy}-1,4, 5-trihydroxycyclohexanecarboxylic acid), a major phenolic compound in coffee. DFT calculations with the 6-311G(d,p) basis set produce very good results. The electrostatic potential mapped onto an isodensity surface has been obtained. A natural bond orbital analysis (NBO) has been performed in order to study intramolecular bonding, interactions among bonds, and delocalization of unpaired electrons. HOMO-LUMO studies give insights into the interaction of the molecule with other species. The calculated HOMO and LUMO energies indicate that a charge transfer occurs within the molecule. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Supramolecular chemistry is an emerging tool for devising materials that can perform specified functions. The self-assembly of facially amphiphilic bile acid molecules has been extensively utilized for the development of functional soft materials. Supramolecular hydrogels derived from the bile acid backbone act as useful templates for the intercalation of multiple components. Based on this, synthesis of gel-nanoparticle hybrid materials, photoluminescent coating materials, development of a new enzyme assay technique, etc. were achieved in the author's laboratory. The present account highlights some of these achievements.
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The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.
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It is increasingly being recognized that resting state brain connectivity derived from functional magnetic resonance imaging (fMRI) data is an important marker of brain function both in healthy and clinical populations. Though linear correlation has been extensively used to characterize brain connectivity, it is limited to detecting first order dependencies. In this study, we propose a framework where in phase synchronization (PS) between brain regions is characterized using a new metric ``correlation between probabilities of recurrence'' (CPR) and subsequent graph-theoretic analysis of the ensuing networks. We applied this method to resting state fMRI data obtained from human subjects with and without administration of propofol anesthetic. Our results showed decreased PS during anesthesia and a biologically more plausible community structure using CPR rather than linear correlation. We conclude that CPR provides an attractive nonparametric method for modeling interactions in brain networks as compared to standard correlation for obtaining physiologically meaningful insights about brain function.
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Introduction: Cytochromes P450 (P450) and associated monooxygenases are a family of heme proteins involved in metabolism of endogenous compounds (arachidonic acid, eicosanoids and prostaglandins) as also xenobiotics including drugs and environmental chemicals. Liver is the major organ involved in P450-mediated metabolism and hepatic enzymes have been characterized. Extrahepatic organs, such as lung, kidney and brain have the capability for biotransformation through P450 enzymes. Brain, including human brain, expresses P450 enzymes that metabolize xenobiotics and endogenous compounds. Areas covered: An overview of P450-mediated metabolism in brain is presented focusing on distinct differences seen in expression of P450 enzymes, generation of unique P450 enzymes in brain through alternate splicing and their consequences in terms of metabolism of psychoactive drugs and inflammatory prompts, such as leukotrienes, thus modulating inflammatory response. Expert opinion: The brain possesses unique P450s that metabolize drugs and endogenous compounds through pathways that are markedly different from that seen in liver indicating that extrapolation directly from liver to brain is not appropriate. It is therefore necessary to characterize the unique brain P450s and their ability to metabolize xenobiotics and endogenous compounds to better understand the functions of this important class of enzymes in brain, especially human brain.
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Helicobacter pylori is a Gram-negative bacterium that colonizes human stomach and causes gastric inflammation. The species is naturally competent and displays remarkable diversity. The presence of a large number of restriction-modification (R-M) systems in this bacterium creates a barrier against natural transformation by foreign DNA. Yet, mechanisms that protect incoming double-stranded DNA (dsDNA) from restriction enzymes are not well understood. A DNA-binding protein, DNA Processing Protein A (DprA) has been shown to facilitate natural transformation of several Gram-positive and Gram-negative bacteria by protecting incoming single-stranded DNA (ssDNA) and promoting RecA loading on it. However, in this study, we report that H. pylori DprA (HpDprA) binds not only ssDNA but also dsDNA thereby conferring protection to both from various exo-nucleases and Type II restriction enzymes. Here, we observed a stimulatory role of HpDprA in DNA methylation through physical interaction with methyltransferases. Thus, HpDprA displayed dual functional interaction with H. pylori R-M systems by not only inhibiting the restriction enzymes but also stimulating methyltransferases. These results indicate that HpDprA could be one of the factors that modulate the R-M barrier during inter-strain natural transformation in H. pylori.