Fluid flow induced calcium response in bone cell network

In our previous work, bone cell networks with controlled spacing and functional intercellular gap junctions had been successfully established by using microcontact printing and self assembled monolayers technologies [Guo, X. E., E. Takai, X. Jiang, Q. Xu, G. M. Whitesides, J. T. Yardley, C. T. Hung, E. M. Chow, T. Hantschel, and K. D. Costa. Mol. Cell. Biomech. 3:95-107, 2006]. The present study investigated the calcium response and the underlying signaling pathways in patterned bone cell networks exposed to a steady fluid flow. The glass slides with cell networks were separated into eight groups for treatment with specific pharmacological agents that inhibit pathways significant in bone cell calcium signaling. The calcium transients of the network were recorded and quantitatively evaluated with a set of network parameters. The results showed that 18 alpha-GA (gap junction blocker), suramin (ATP inhibitor), and thapsigargin (depleting intracellular calcium stores) significantly reduced the occurrence of multiple calcium peaks, which were visually obvious in the untreated group. The number of responsive peaks also decreased slightly yet significantly when either the COX-2/PGE(2) or the NOS/nitric oxide pathway was disrupted. Different from all other groups, cells treated with 18 alpha-GA maintained a high concentration of intracellular calcium following the first peak. In the absence of calcium in the culture medium, the intracellular calcium concentration decreased slowly with fluid flow without any calcium transients observed. These findings have identified important factors in the flow mediated calcium signaling of bone cells within a patterned network.

Neural network retrieval of ocean surface parameters from SSM/I data

A new algorithm based on the multiparameter neural network is proposed to retrieve wind speed (WS), sea surface temperature (SST), sea surface air temperature, and relative humidity ( RH) simultaneously over the global oceans from Special Sensor Microwave Imager (SSM/I) observations. The retrieved geophysical parameters are used to estimate the surface latent heat flux and sensible heat flux using a bulk method over the global oceans. The neural network is trained and validated with the matchups of SSM/I overpasses and National Data Buoy Center buoys under both clear and cloudy weather conditions. In addition, the data acquired by the 85.5-GHz channels of SSM/I are used as the input variables of the neural network to improve its performance. The root-mean-square (rms) errors between the estimated WS, SST, sea surface air temperature, and RH from SSM/I observations and the buoy measurements are 1.48 m s(-1), 1.54 degrees C, 1.47 degrees C, and 7.85, respectively. The rms errors between the estimated latent and sensible heat fluxes from SSM/I observations and the Xisha Island ( in the South China Sea) measurements are 3.21 and 30.54 W m(-2), whereas those between the SSM/ I estimates and the buoy data are 4.9 and 37.85 W m(-2), respectively. Both of these errors ( those for WS, SST, and sea surface air temperature, in particular) are smaller than those by previous retrieval algorithms of SSM/ I observations over the global oceans. Unlike previous methods, the present algorithm is capable of producing near-real-time estimates of surface latent and sensible heat fluxes for the global oceans from SSM/I data.

Parameters Inversion of Fluid-Saturated Porous Media Based on Neural Networks

The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.

Three-Dimensional Network Model And Its Parameter Calibration

A material model, whose framework is parallel spring-bundles oriented in 3-D space, is proposed. Based on a discussion of the discrete schemes and optimum discretization of the solid angles, a 3-D network cell consisted of one-dimensional components is developed with its geometrical and physical parameters calibrated. It is proved that the 3-D network model is able to exactly simulate materials with arbitrary Poisson ratio from 0 to 1/2, breaking through the limit that the previous models in the literature are only suitable for materials with Poisson ratio from 0 to 1/3. A simplified model is also proposed to realize high computation accuracy within low computation cost. Examples demonstrate that the 3-D network model has particular superiority in the simulation of short-fiber reinforced composites.

Electric characteristics of pseudo-spark during breakdown phase

An analysis of the time-dependent resistive voltage and power deposition during the breakdown phase of pseudo-spark is presented. The voltage and current were measured by specially designed low-inductance capacitive voltage divider and current measuring resistor. The measured waveforms of voltage and current are digitized and processed by a computer program to remove the inductive component, so as to obtain resistive voltage and power deposition. The influence of pressure, cathode geometry and charging voltage of storage capacitors on the electrical properties in the breakdown phase are investigated. The results suggest that the breakdown phase of pseudo-spark consists of three stages. The first stage is mainly hollow cathode discharge. In the second stage, field-enhanced thermionic emission takes place, resulting in a fast voltage drop and sharp rise of discharge current. The third stage of discharge depends simply on the parameters of the discharge circuit.

Electric and magnetic losses and gains in determining the sign of refractive index

Within the framework of classic electromagnetic theories, we have studied the sign of refractive index of optical medias with the emphases on the roles of the electric and magnetic losses and gains. Starting from the Maxwell equations for an isotropic and homogeneous media, we have derived the general form of the complex refractive index and its relation with the complex electric permittivity and magnetic permeability, i.e. n = root epsilon mu, in which the intrinsic electric and magnetic losses and gains are included as the imaginary parts of the complex permittivity and permeability, respectively, as epsilon = epsilon(r) + i(epsilon i) and mu = mu(r) + i mu(i). The electric and magnetic losses are present in all passive materials, which correspond, respectively, to the positive imaginary permittivity and permeability epsilon(i) > 0 and mu(i) > 0. The electric and magnetic gains are present in materials where external pumping sources enable the light to be amplified instead of attenuated, which correspond, respectively, to the negative imaginary permittivity and permeability epsilon(i) < 0 and mu(i) < 0. We have analyzed and determined uniquely the sign of the refractive index, for all possible combinations of the four parameters epsilon(r), mu(r), epsilon(i), and mu(i), in light of the relativistic causality. A causal solution requires that the wave impedance be positive Re {Z} > 0. We illustrate the results for all cases in tables of the sign of refractive index. One of the most important messages from the sign tables is that, apart from the well-known case where simultaneously epsilon < 0 and mu < 0, there are other possibilities for the refractive index to be negative n < 0, for example, for epsilon(r) < 0, mu(r) > 0, epsilon(i) > 0, and mu(i) > 0, the refractive index is negative n < 0 provided mu(i)/epsilon(i) > mu(r)/vertical bar epsilon(r)vertical bar. (c) 2006 Elsevier B.V. All rights reserved.

Effect of network modifiers on spectroscopic properties of erbium-doped phosphate glasses

The integrated absorption cross section Sigma(abs), I peak emission cross section sigma(cmi), Judd-Ofeld intensity parameters Omega(iota) ( t = 2,4,6), and spontaneous emission probability A(R) of Er3+ ions were determined for Erbium doped alkali and alkaline earth phosphate glasses. It is found the compositional dependence of sigma(emi) 5 almost similar to that of Sigma(abs), which is determined by the sum, of Omega(1) (3 Omega(2) + 10 Omega(4) + 21 Omega(6)). In addition, the compositional dependence of Omega(1) was studied in these glass systems. As a result, compared with. Omega(4) and Omega(6) the Omega(2) has a stronger compositional dependence on the ionic radius and content of modifers. The covalency of Er-O bonds in phosphate glass is weaker than that in silicate glass, germanate glass, aluminate glass, and tellurate glass, since Omega(6) of phosphate glass is relatively large. A(R) is affected by the covalency of the Er3+ ion sites and corresponds to the Omega(6) value.

Effect of bismuth oxide on the thermal stability and Judd-Ofelt parameters of Er 3(+)/Yb3(+) co-doped aluminophosphate glasses

The Er3+/Yb3+ co-doped glasses with compositions of xBi(2)O(3)-(65-x)P2O5-4Yb(2)O(3)-11Al(2)O(3)-5BaO-15Na(2)O (where x = 0, 2.5, 5, 7.5 and 10 mol%) were prepared using the normal melt quench technique. The optical absorption spectra of the glasses were recorded in the wavelength range 300-1700 nm. The effect of Bi2O3 content on the thermal stability and absorption spectra of glasses was investigated. In addition, the Judd-Ofelt parameters and oscillator strengths were calculated by employing Judd-Ofelt theory. It was observed that the positions of the fundamental absorption edge and cut-off wavelength shifted towards red as the content of Bi2O3 increased. However, there were no red shifts found both in the peak wavelength and in the center of mass wavelength of all absorption bands with Bi2O3 content increasing. The results of Judd-Ofelt theory analysis showed that Judd-Ofelt parameters Omega(t), (t = 2, 4, 6) changed sharply when Bi2O3 concentration exceeded 5 mol%. The variation trends of experimental oscillator strength were similar with those of Judd-Ofelt parameters as function of Bi2O3 concentrations. Moreover, differential scanning calorimetry experiments showed that the increases of Bi2O3 content weakened the network structure and then lowered the thermal stability of the glasses. The spontaneous emission probability A(rad), branching ratio beta and the radiative lifetime tau(rad) were also calculated and analyzed. The stimulated emission cross-section of Er3+ was calculated according to the McCumber theory. It was found that the stimulated emission cross-section of Er3+ was monotonically increases with Bi2O3 content increasing. (C) 2006 Elsevier B.V. All rights reserved.

Forecasting Daily Chlorophyll a Concentration during the Spring Phytoplankton Bloom Period in Xiangxi Bay of the Three-Gorges Reservoir by Means of a Recurrent Artificial Neural Network

A recurrent artificial neural network was used for 0-and 7-days-ahead forecasting of daily spring phytoplankton bloom dynamics in Xiangxi Bay of Three-Gorges Reservoir with meteorological, hydrological, and limnological parameters as input variables. Daily data from the depth of 0.5 m was used to train the model, and data from the depth of 2.0 m was used to validate the calibrated model. The trained model achieved reasonable accuracy in predicting the daily dynamics of chlorophyll a both in 0-and 7-days-ahead forecasting. In 0-day-ahead forecasting, the R-2 values of observed and predicted data were 0.85 for training and 0.89 for validating. In 7-days-ahead forecasting, the R-2 values of training and validating were 0.68 and 0.66, respectively. Sensitivity analysis indicated that most ecological relationships between chlorophyll a and input environmental variables in 0-and 7-days-ahead models were reasonable. In the 0-day model, Secchi depth, water temperature, and dissolved silicate were the most important factors influencing the daily dynamics of chlorophyll a. And in 7-days-ahead predicting model, chlorophyll a was sensitive to most environmental variables except water level, DO, and NH3N.

High-frequency characterization of packaging network in to-can photodiode modules

A simple method for analyzing the effects of TO packaging network on the high-frequency response of photodiode modules is presented. This method is established based on the relations of the scattering parameters of the packaging network, photodiode chip, and module. It is shown that the results obtained by this method agree well with those obtained by the conventional comparison method. The proposed method is much more convenient since only the electrical domain measurements are required. (C) 2008 Wiley Periodicals, Inc.

Characterization of parasitics from scattering parameters of laser diode

A novel method for characterizing the parasitics of parasitic network is proposed based on the relations between the scattering parameters of a semiconductor laser chip and laser diode. Experiments are designed and performed using our method. The analysis results are in good agreement with the measurements. Furthermore, how the parasitics change with the parasitic element values are investigated. The method only needs reflection coefficient of laser diode to be measured, which is simple because of the developed electrical-domain measurement techniques. 2007 Wiley Periodicals, Inc.

Extraction of intrinsic response from S-parameters of laser diodes

We describe a new method for extracting the intrinsic response of a laser diode from S-parameters measured using a calibrated vector network analyzer. The experimental results obtained using the new method are compared with those obtained using the optical modulation method and the frequency response subtraction method. Good agreement has been obtained, confirming the new method validity and accuracy. The new method has the advantages of obtaining the intrinsic characteristics of a laser diode with conventional measurements using a network analyzer.