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ABSTRACT: To evaluate the effects of co-administration of inactivated avian influenza H9N2 virus and adjuvants in waterfowls, 10-d-old ducks were immunized intranasally with inactivated avian influenza virus (IAIV) combined with CpG DNA and sodium cholate. Immunoglobulin A and IgG antibody levels in throat and tracheal tissues increased significantly, as did specific IgA and IgG antibody levels in the serum after intranasal immunization with IAIV combined with CpG DNA and sodium cholate, compared with immunization with IAIV only. Furthermore, enhanced hemagglutination inhibition titers were also detected in serum samples taken between the third and seventh weeks after immunization with IAIV and both adjuvants compared with IAIV alone. The expression of IL-2 and IL-6 in tracheal and lung tissues increased significantly in the early period after booster immunization. However, the enhancement induced by a single adjuvant was insignificant, and no significant change was detected in the antibody titers or cytokine levels between the ducks that received IAIV alone or saline. In the viral challenge study, prior administration of both CpG DNA and sodium cholate with IAIV reduced the viral titers in the oropharynx and cloaca swabs. Our study suggests that the combination of CpG DNA and sodium cholate could be beneficial to immunization with inactivated H9N2 virus by enhancing the local and systemic immune responses.
Poultry Science 05/2012; 91(5):1074-80. · 1.73 Impact Factor
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ABSTRACT: This paper presents a novel application of neural network modeling
in the optimization of sensor locations for the measurement of flue gas
flow in industrial ducts and stacks. The proposed neural network model
has been validated with an experiment based upon a case-study power
plant. The results have shown that the optimized sensor location can be
easily determined with this model. The industry can directly benefit
from the improvement of measurement accuracy of the flue gas flow in the
optimized sensor location and the reduction of manual measurement
operation with Pitot tube
IEEE Transactions on Instrumentation and Measurement 05/2000; · 1.21 Impact Factor
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WISE 2000, Proceedings of the First International Conference on Web Information Systems Engineering, Volume I (Main Program), Hong Kong, China, June 19-21, 2000; 01/2000
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ABSTRACT: Burrs are often difficult to detect and measure because of their
intrinsic variability in shape and dimension. No automotive standard had
been established about their acceptable dimensions and measurement
techniques for sheet steel products. For the automotive industry, even
burrs of the size of 100 μm are perceived as damaging because of
their dramatic impact upon panel corrosion resistance and assembly
performance. It is critical to measure burrs during panel manufacture in
order to control the process. The characterization of the typical burr
produced has been carried out employing 3D measurements with a surface
profilometer and a SEM. This analysis has shown a typical triangular
burr shape and some characteristic dimensions. A contact method and two
laser-triangulation systems have been developed. The instrument accuracy
was analyzed, based upon a full factorial experimentation over a set of
typical panels edges
Instrumentation and Measurement Technology Conference, 1999. IMTC/99. Proceedings of the 16th IEEE; 02/1999
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ABSTRACT: This paper presents a novel application of neural network
modelling in the optimisation of sensor locations for measurement of
flue gas flow in industrial ducts and stacks. The neural network model
has been validated with experiment based upon a case-study power plant.
The results have shown that the optimised sensor location can be
determined using this model. The measurement accuracy of the flue gas
flow can be significantly improved in the optimised sensor location,
resulting in a possible reduction in the manual operation
Instrumentation and Measurement Technology Conference, 1999. IMTC/99. Proceedings of the 16th IEEE; 02/1999
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ABSTRACT: This paper discusses the modelling of the flue gas flow in industrial ducts and stacks using artificial neural networks (ANNs). Based upon the individual velocity and other operating conditions, an ANN model has been developed for the measurement of the volume flow rate. The model has been validated by the experiment using a case-study power plant. The results have shown that the model can largely compensate for the non-representativeness of a sampling location and, as a result, the measurement accuracy of the flue gas flow can be significantly improved
Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE; 06/1998
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ABSTRACT: Blood resistivity is an important quantity which value influences the results of various methods used in the study of heart and circulation. In this paper, the relationship between blood resistivity and velocity of blood flow was evaluated and analyzed based upon a probe using six-ring electrodes and a circulatory model. The experimental results indicated that the change in blood resistivity was only ±1.1% when the velocity of blood flow changed from 2.83 cm/s to 40 cm/s and it rose to 23% when the velocity was lower than 2.83 cm/s
Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE; 06/1998
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ABSTRACT: This paper discusses the dynamic error characteristics of touch trigger probes used with coordinate measuring machines. During the investigation, a number of important parameters have been identified, including measurement speed, probe longitude, approach distance, probe latitude, stylus length/stylus tip diameter, probe orientation, operating mode (scanning and non-scanning), scan pitch, pre-load spring force (gauging force), probe type and the surface approach angle. This paper presents the detailed experimental design and the results obtained from the systematic experiments. These results have led to some useful recommendations for the reduction of the probe dynamic errors. Some of these recommendations included the selection of the optimum measurement speed, the setting of the pre-load spring force and the choice of the probe type
Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE; 06/1998
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ABSTRACT: This paper presents a fiber optic sensor system, artificial neural
networks (fast back-propagation) are employed for the data processing.
The use of the neural networks makes it possible for the sensor to be
used both for surface roughness and displacement measurement at the same
time. The results indicate 100% correct surface classification for ten
different surfaces (different materials, different manufacturing
methods, and different surface roughnesses) and displacement errors less
then ±5 μm. The actual accuracy was restricted by the
calibration machine. A measuring range of ±0.8 mm for the
displacement measurement was achieved
IEEE Transactions on Instrumentation and Measurement 09/1997; · 1.21 Impact Factor
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ABSTRACT: This paper presents a general object-oriented model for
measurement systems. The limitations of the conventional
function-oriented models are examined in the light of the generalised
concept of measurement and its theoretical framework proposed previously
by the author. The proposed model identifies five classes of objects,
i.e. measured object, measuring instrument, reference standard, human
observer and operating environment. Each of them is characterised by its
own attributes and operations or functions at three levels, i.e.
internal, operational and environmental. The interactions between them
are also modelled including the coupling between the measured object and
the measuring instrument, the human-instrument interface, the
calibration and the interference. Together with the generalised concept
of measurement and its philosophical framework, it serves as a practical
tool for description, analysis and design, and, in particular, for
computer aided analysis and design of a measuring system. It will find
applications in instrumentation engineering and measurement education
and research
Instrumentation and Measurement Technology Conference, 1997. IMTC/97. Proceedings. 'Sensing, Processing, Networking'., IEEE; 06/1997
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ABSTRACT: This paper presents a fibre optic sensor system. Artificial neural
networks using fast backpropagation are employed for the data
processing. The use of the neural networks makes it possible for the
sensor to be used both for surface roughness and displacement
measurement at the same time. The results indicate 100% correct surface
classification for ten different surfaces (different materials,
different manufacturing methods and different surface roughnesses) and
displacement errors less then ±5 μm. The actual accuracy was
restricted by the calibration machine. A measuring range of ±0.8
mm for the displacement measurement were achieved
Instrumentation and Measurement Technology Conference, 1996. IMTC-96. Conference Proceedings. 'Quality Measurements: The Indispensable Bridge between Theory and Reality'., IEEE; 02/1996
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ABSTRACT: Without surface pretreatment or applying additional interlayer, diamond films have been directly synthesized on an Fe–25Cr–5Al steel substrate by a hot filament chemical vapor deposition method from an H2-1vol.% CH4 gas mixture. Due to an effective removal of intermediate graphite phase from the diamond–steel interface, the coated diamond films were continuous and adherent well to the steel substrate. Aligned conical diamond structures were also achieved on this steel substrate by negatively biasing the substrate holder and inducing a glow discharge. The deposition behavior of carbon on Fe–Cr–Ni steel substrate was different. A graphite-rich carbon film incorporated with diamond particles grew in the absence of biasing, then aligned carbon nanotube bundles were formed in the presence of negative biasing and glow discharge. The different deposition behavior of carbon on the two kinds of steel substrates was addressed in terms of the effect of their chemical compositions.Research Highlights► Without surface pre-treatment or buffer layer, a selective synthesis of diamond or CNTs is directly realized on steel substrates. ► Alloying element Al shows a unique role in growing adherent diamond nanostructures directly on steels. ► The films and the underlying steel substrates are characterized by synchrotron XAS to reveal the fundamental growth mechanism.
Diamond and Related Materials. 20(2):187-190.
