1,721,087 research outputs found

    Molecular cloning and sequence analysis of the cDNAs for pituitary glycoprotein hormone α subunits from two species of Synbranchiformes, Monopterus albus and Ophisternon bengalense

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    No information is available regarding the cDNA nucleotide and protein sequences of pituitary glycoprotein hormone α subunits (PGH α) from fish of the order Synbranchiformes. For better understanding of phylogenetic diversity and evolution of PGH α in fish, we have cloned cDNAs for PGH α subunits from swamp eels, Monopterus albus and Ophisternon bengalense, two members of the order Synbranchiformes, suborder Synbranchoidei, family Synbranchidae. The PGH α subunit cDNA was cloned by reverse transcription and polymerase chain reaction amplification from total pituitary RNA. The full length PGH α cDNA was obtained using 5’- and 3’- rapid amplification of cDNA ends (RACE). The PGH α of these two species possessed 354 bp of coding region, which encoding a protein of 117 amino acids consisting of a putative signal peptide of 23 amino acids and a mature peptide of 94 amino acids. The amino acid sequence identity of PGH α between the two species is 93.8 %. All 10 cysteine residues, forming 5 disulfide linkage, and 2 putative N-linked glycosylation sites are conserved in the PGH α subunits of the two species. Three proline residues, presumably responsible for changing the backbone directions of the protein structure, are conserved as well. Phylogenetic analysis of PGH α subunits based on their amino acid sequences revealed that the percent identities of the swamp eels are highest (92.5 %) with fishes of Perciformes, intermediate with Pleuronectiformes (82.5 %) and Cyprinodontiformes (72.2 %), and lowest with Salmoniformes, Cypriniformes, Siluriformes, Anguilliformes, Acipenseriformes and Ceratodontiformes (56.7 % - 65.1 %)

    Microstructural changes during superplastic deformation of Fe-24Cr-7Ni-3Mo-0.14N duplex stainless steel

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    The superplasticity of Fe-24Cr-7Ni-3Mo-0.14N duplex stainless steel after solution treatment at 1350 degrees C followed by 90% cold rolling was investigated at 850 degrees C with a strain rate ranging from 10(-3) to 10(-1) s(-1). The microstructure of duplex stainless steel consists of matrix gamma phase having low angle boundaries and sigma phase as second phase particles before the deformation at 850 degrees C. The constituent phases in the duplex stainless steel were found to be changed following alpha --> alpha + gamma --> alpha + gamma + sigma --> gamma + sigma through phase transformation during the deformation at 850 degrees C. A maximum elongation of 750% was obtained at 850 degrees C with strain rate of 3.16 x 10(-3) s(-1). The low angle grain boundaries were changed into high angle grain boundaries by dynamic recrystallization of gamma phase at an early stage of deformation. The dislocation density within matrix gamma grains was low and a significant strain-induced grain growth was observed during the deformation. The misorientation angles between the neighboring gamma grains increased with increasing strain; thus the low angle grain boundaries were transformed into high angle grain boundaries suitable for sliding by the dynamic recrystallization during the deformation. The grain boundary sliding assisted by dynamic recrystallization is considered a controlling mechanism for superplastic deformation at 850 degrees C. (C) 1999 Elsevier Science S.A. All rights reserved

    Directional Wigner distribution for order analysis in rotating/reciprocating machines

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    A signal processing technique for rotation-related transient signals from a rotating or reciprocating machine is proposed to characterise its instantaneous planar motion. It essentially utilises the directional Wigner distributions (dWDs) defined for the forward and backward pass analytic signals. It is shown that the auto- and cross-dWDs in the angle-order domain are much better in concentration of signal terms and reduction of interference terms than those conventionally defined in the time-frequency domain, particularly when the rotational speed variation is significant during acquisition of the signals. (C) 1999 Academic Press

    A chart re-estimation algorithm for a probabilistic recursive transition network

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    A Probabilistic Recursive Transition Network is an elevated version of a Recursive Transition Network used to model and process context-free languages in stochastic parameters. We present a re-estimation algorithm for training probabilistic parameters, and show how efficiently it can be implemented using charts. The complexity of the Outside algorithm we present is O(N(4)G(3)) where N is the input size and G is the number of states. This complexity cart be significantly overcome when the redundant computations are avoided. Experiments on the Penn tree corpus show that re-estimation can be done more efficiently with charts

    Monte Carlo simulation of anisotropic grain growth in liquid phase sintering

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    One of the key techniques in modern engineering ceramic system is microstructural control of anisotropic grain growth because grain orientation and shape proved to have an influence on mechanic, dielectric and electric behavior of ceramics. But until now, computer simulation for grain growth has not sufficiently addressed to this subject. The reason is that simulation algorithm was laborious because it has to contain mass transfer through liquid phase and especially anisotropic grain growth has to be considered based on interfacial properties in real system. The goal of present study is simulation of anisotropic grain growth in liquid phase by Q-states model. To give anisotropic inherency to grains, constraint on mobility to specific boundaries was applied. For comparison, we measured grain size distribution and deduced grain growth kinetics from relationship between average grain size and time. As a result, the grain size distribution functions become broader and the peak height decreases as the anisotropy is increased. The growth exponent 0.67 and 0.47 found by linear fitting have slightly different values in comparison with work of Grest et al. but similar is trend to the decrease of exponent with anisotropy

    Visualization study of the vortex behavior and fluid layer formation of a periodically pulsating jet under a ceiling

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    The vortex behavior and thickness of the nozzle fluid layer of pulsating jets under a ceiling are studied using the laser-assisted visualization technique. The vortex formation characteristics of jets pulsating at different frequencies are compared with those of continuously issuing jets to investigate the effects of the pulsating frequency on the thicknesses of the nozzle fluid layers under a ceiling. To identify similarities between the features of pulsating isothermal jets and periodically pulsating pool fires, the frequencies of the pulsating jets are determined using the results obtained from previous pool fire studies. The formation and propagation characteristics of vortices in pulsating jets are investigated, along with the effects of the pulsation frequency on the thickness of the nozzle fluid layer. The size of the first primary vortex generated decreases as the pulsation frequency of the jet increases. The thickness of the nozzle fluid layer of pulsating jets is larger than that of continuously issuing jet, although the first primary vortex is smaller. The thickness of the nozzle fluid layer increases with decreasing pulsation frequency in jets with the same Reynolds number. The results of this study show the possibility that the ceiling jet behavior including the thickness of the smoke layer induced by a pulsating real fire plume can be strongly related to the pulsation frequency of the plume.This work was supported by the Korea Science and Technology Foundation through the Combustion Engineering Research Center(CERC) at the Korea Advanced Institute of Science and Technology

    Phenomena and mechanism on superplasticity of duplex stainless steels

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    The superplasticity of Fe-24Cr-7Ni-3Mo-0.14N duplex stainless steel after being solution treated at 1350 degrees C followed by 90% cold rolling was investigated at 850 degrees C with a strain rate ranging from 10(-3)-10(-1)s(-1). The microstructure of duplex stainless steel consists of a matrix gamma phase having low angle grain boundaries and a sigma phase as second phase particles before the deformation at 850 degrees C. It is well known that the constituent phases in duplex stainless steel is changed following alpha-->alpha+gamma-->alpha+gamma+sigma-->gamma+sigma through phase transformation during deformation at 850 degrees C. The final microstructure of duplex stainless steel consisted of 70 vol.% of gamma and 30 vol.% of the sigma phase. A maximum elongation of 750% was obtained at 850 degrees C with a strain rate of 3.16x10(-3)s(-1). The dislocation density within matrix gamma grains was low and a significant strain-induced grain growth was observed during the deformation. The misorientation angles between the neighboring gamma grains increased as the strain increased, thus the low angle grain boundaries were transformed into high angle grain boundaries suitable for sliding by dynamic recrystallization during the deformation at 850 degrees C. The grain boundary sliding assisted by dynamic recrystallization is considered to be a controlling mechanism for superplastic deformation at 850 degrees C

    The directional Wigner distribution and its applications

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    A new signal processing technique, the directional Wigner distribution (dWD), is presented to characterize the instantaneous planar motion of a measurement point in a structure from its transient complex-valued vibration signal. It is proven that the auto-dWD essentially tracks the shape and directivity of the instantaneous planar motion, whereas the phase of the cross-dWD indicates its inclination angle. Finally, the technique is successfully applied to two practical cases: a rotor during run-up and an automobile engine during crank-on/idling/engine-off. (C) 1998 Academic Press
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