115 resultados para Pre-tensioning Structural Design


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We present results from a systematic numerical study of structural properties of an unforced, incompressible, homogeneous, and isotropic three-dimensional turbulent fluid with an initial energy spectrum that develops a cascade of kinetic energy to large wave numbers. The results are compared with those from a recently studied set of power-law initial energy spectra [C. Kalelkar and R. Pandit, Phys. Rev. E 69, 046304 (2004)] which do not exhibit such a cascade. Differences are exhibited in plots of vorticity isosurfaces, the temporal evolution of the kinetic energy-dissipation rate, and the rates of production of the mean enstrophy along the principal axes of the strain-rate tensor. A crossover between "non-cascade-type" and "cascade-type" behavior is shown numerically for a specific set of initial energy spectra.

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The use of stereochemically constrained amino acids permits the design of short peptides as models for protein secondary structures. Amino acid residues that are restrained to a limited range of backbone torsion angles (ϕ-ψ) may be used as folding nuclei in the design of helices and β-hairpins. α-Amino-isobutyric acid (Aib) and related Cαα dialkylated residues are strong promoters of helix formation, as exemplified by a large body of experimentally determined structures of helical peptides. DPro-Xxx sequences strongly favor type II’ turn conformations, which serve to nucleate registered β-hairpin formation. Appropriately positioned DPro-Xxx segments may be used to nucleate the formation of multistranded antiparallel β-sheet structures. Mixed (α/β) secondary structures can be generated by linking rigid modules of helices and β-hairpins. The approach of using stereochemically constrained residues promotes folding by limiting the local structural space at specific residues. Several aspects of secondary structure design are outlined in this chapter, along with commonly used methods of spectroscopic characterization.

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Purpose: A number of proteome studies have been performed recently to identify pheromone-related protein expression and their molecular function using genetically modified rodents' urine. However, no such studies have used Indian commensal rodents; interestingly, in a previous investigation, we confirmed the presence of volatile molecules in commensal rodents urine and these molecules seem to be actively involved in pheromonal communication. Therefore, the present study aims to identify the major urinary protein [MUP] present in commensal rat urine, which will help us to understand the protein's expression pattern and intrinsic properties among the rodents globally. Experimental Design: Initially, the total urinary proteins were separated by 1-D and 2-D electrophoresis and then subsequently analyzed by Matrix Assisted Laser Desorption Ionization-Time of Flight and Mass Spectrometer (MALDI-TOF/MS). Furthermore, they were then fragmented with the aid of a Tandem Mass Spectrometer (TOF/TOF) and the identified sequences aligned and confirmed using similarity with the deduced primary structures of members of the lipocalin superfamily.Results: The SDS-PAGE protein profiles showed distinct proteins with molecular masses of 15, 22.4, 25, 28, 42, 50, 55, 68, and 91 kDa. Of these proteins, the 22.4 kDa protein was considered to be target candidate. When 2D electrophoresis was carried out, about similar to 50 spots were detected with different masses and various pI ranges. The 22.4 kDa protein was found to have a pI of about 4.9. This 22.4 kDa protein spot was digested and subjected to mass spectrometry; it was identified as rat MUP. The fragmented peptides from the rat MUP at 935, 1026, 1192, and 1303 m/z were further fragmented with the aid of MS/MS and generated de novo sequence and this confirmed this protein to be the MUP present in the urine of commensal rats.Conclusion: The present investigation confirms the presence of MUP with a molecular mass of 22.4 kDa in the urine of commensal rats. This protein may be involved in the binding of volatile molecules and opens up a discussion about how volatile and non-volatile molecules in the commensal rats' urine may contribute chemo-communication.

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Nocardia sp. quantitatively converts salannin 1 and 3-de-O-acetylsalannin 2 (C-seco limonoids) into 3-deacetoxy-1-de[(E)-2-methylbut-2-enoyloxy]salannin-1-en-3-one 10, a novel and potentially bioactive compound with an alpha,beta-unsaturated ketone moiety in ring `A'. In order to establish the sequence of events involved in this transformation and the structural specificity of this bacterial system, several new derivatives of salannin 1 have been prepared. These studies have indicated that the transformation is initiated by deacetylation at C-3, followed by oxidation of the secondary hydroxy group to 3-keto, which appears to facilitate the elimination of the tigloyloxy/acetoxy group at C-1 with the formation of an olefinic linkage between C-1 and C-2. The organism very efficiently transforms some of the derivatives of salannin into their corresponding compounds possessing an enone systemin ring `A', an essential pre-requisite for various biological activities. Some of the C-seco limonoids prepared in the present study, viz. 10, 1,2-didehydro-1,3-dideoxy-3-oxosalannic acid 18, 3-deacetoxy-1-de[(E)-2-methylbut-2-enoyloxy]-20,21,22,23-tetrahydrosal annin-1-en-3-one 15 and 1,2-didehydro-1,3-dideoxy-3-oxosalannol 23 were hitherto not known.

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The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.

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A completely automated temperature-programmed reaction (TPR) system for carrying out gas-solid catalytic reactions under atmospheric flow conditions is fabricated to study CO and hydrocarbon oxidation, and NO reduction. The system consists of an all-stainless steel UHV system, quadrupole mass spectrometer SX200 (VG Scientific), a tubular furnace and micro-reactor, a temperature controller, a versatile gas handling system, and a data acquisition and analysis system. The performance of the system has been tested under standard experimental conditions for CO oxidation over well-characterized Ce1-x-y(La/Y)(y)O2-delta catalysts. Testing of 3-way catalysis with CO, NO and C2H2 to convert to CO2, N-2 and H2O is done with this catalyst which shows complete removal of pollutants below 325 degrees C. Fixed oxide-ion defects in Pt substituted Ce1-y(La/Y)(y)O2-y/2 show higher catalytic activity than Pt ion-substituted CeO2

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The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

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The use of fractional-factorial methods in the optimization of porous-carbon electrode structure is discussed with respect to weight-loss of carbon during gas treatment, weight and mixing time of binder, compaction temperature, time and pressure, and pressure of feed gas. The experimental optimization of an air electrode in alkaline solution is described.

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Thirteen host guest compounds of 3,5-dihydroxybenzoic acid (DHBA) have been structurally characterized. Water molecules occupy the peripheries of a hexagonal void, created with DHBA molecules, and act as ``hooks'' to connect the guest molecules with the host-framework via hydrogen bonding. The ``water hook'' is an OH group acting as a donor. Consequently, the guest molecules were chosen so that they contain good hydrogen bond acceptor functionalities. A number of multicomponent hydrates were isolated with stoichiometries (DHBA)(x)(H2O). (guest),. Of these, compounds with the following as guests were obtained as crystals that were good enough for single crystal work: ethyl acetate (EtOAc), diethyl oxalate, dimethyl oxalate, di(n-propyl) oxalate, diethyl malonate, diethyl succinate, chloroacetonitrile, N,N-dimethyl formamide (DMF), acetone, dimethyl sulfoxide (DMSO), 1-propanol, and 2-butanol. From 2-butanol, a hemihydrate, (DHBA)(2)(H2O), was also obtained concomitantly. Further to guest stabilization, water acts as a good mediator of effective crystal packing and also determines the topology of the host framework. En the present series of compounds, the role of water is wide ranging, and it is not easy to classify it specifically as a host or as a guest.

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A completely automated temperature-programmed reaction (TPR) system for carrying out gas-solid catalytic reactions under atmospheric flow conditions is fabricated to study CO and hydrocarbon oxidation, and NO reduction. The system consists of an all-stainless steel UHV system, quadrupole mass spectrometer SX200 (VG Scientific), a tubular furnace and micro-reactor, a temperature controller, a versatile gas handling system, and a data acquisition and analysis system. The performance of the system has been tested under standard experimental conditions for CO oxidation over well-characterized Ce1-x-y(La/Y)(y)O2-delta catalysts. Testing of 3-way catalysis with CO, NO and C2H2 to convert to CO2, N-2 and H2O is done with this catalyst which shows complete removal of pollutants below 325 degrees C. Fixed oxide-ion defects in Pt substituted Ce1-y(La/Y)(y)O2-y/2 show higher catalytic activity than Pt ion-substituted CeO2.

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The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

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Life cycle assessment (LCA) is used to estimate a product's environmental impact. Using LCA during the earlier stages of design may produce erroneous results since information available on the product's lifecycle is typically incomplete at these stages. The resulting uncertainty must be accounted for in the decision-making process. This paper proposes a method for estimating the environmental impact of a product's life cycle and the associated degree of uncertainty of that impact using information generated during the design process. Total impact is estimated based on aggregation of individual product life cycle processes impacts. Uncertainty estimation is based on assessing the mismatch between the information required and the information available about the product life cycle in each uncertainty category, as well as their integration. The method is evaluated using pre-defined scenarios with varying uncertainty. DOI: 10.1115/1.4002163]

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An ultraviolet photoelectron spectrometer for the study of van der Waals molecules has been designed and fabricated indigenously. The spectrometer consists of an HeI discharge lamp, a molecular beam sample inlet system, an electrostatic lens, a 180-degrees hemispherical electrostatic analyser and a channeltron detector. Performance of the spectrometer is illustrated with an example.