A method to investigate the shrinkage stress developed by resin-composites bonded to a single flat surface

Objectives. To purpose a method for predicting the shrinkage stress development in the adhesive layer of resin-composite cylinders that shrink bonded to a single flat surface, by measuring the deflection of a glass coverslip caused by the shrinkage of the bonded cylinders. The correlation between the volume of the bonded resin-composite and the stress-peak was also investigated. Methods. A glass coverslip deflection caused by the shrinkage of a bonded resin-composite cylinder (diameter: d = 8 mm, 4 mm, or 2 mm, height: h = 4 mm, 2 mm, 1 mm, or 0.5 mm) was measured, and the same set-up was simulated by finite element analysis (3D-FEA). Stresses generated in the adhesive layer were plotted versus two geometric variables of the resin-composite cylinder (C-Factor and volume) to verify the existence of correlations between them and stresses. Results. The FEA models were validated. A significant correlation (p < 0.01, Pearson's test) between the stress-peak and the coverslip deflection when the resin-composites were grouped by diameter was found for diameters of 2 and 4 mm. The stress-peak of the whole set of data showed a logarithmic correlation with the bonded resin-composite volume (p < 0.001, Pearson's test), but did not correlate with the C-Factor. Significance. The described method should be considered for standardizing the stress generated by the shrinkage of resin-composite blocks bonded to a single flat surface. (C) 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Terbium(III) and dysprosium(III) 8-connected 3D networks containing 2,5-thiophenedicarboxylate anion: Crystal structures and photoluminescence studies

Two novel coordination polymers with the formula {[Ln(2)(2,5-tdc)(3)(dmso)(2)].H2O}(n) (Ln = Tb(III) for (1) and Dy(III) for (2)), (2,5-tdc(2-) = 2,5-thiophenedicarboxylate and dmso = dimethylsulfoxide) have been synthesized by the diffusion method and characterized by thermal analysis, vibrational spectroscopy and single crystal X-ray diffraction analysis. Structure analysis reveals that 2,5-tdc(2-) play a versatile role toward different lanthanide ions to form three-dimensional metal-organic frameworks (MOFs) in which the lanthanides ions are heptacoordinated. Photophysical properties were studied using excitation and emission spectra, where the photoluminescence data show the high emission intensity of the characteristic transitions D-5(4 ->) F-7(J) (J= 6, 5, 4 and 3) for (1) and (F9/2 -> HJ)-F-4-H-6 (J = 15/2, 13/2 and 11/2) for (2), indicating that 2,5-tdc(2-) is a good sensitizer. (C) 2012 Elsevier Ltd. All rights reserved.

Ethanol and Water Adsorption on Close-Packed 3d, 4d, and 5d Transition-Metal Surfaces: A Density Functional Theory Investigation with van der Waals Correction

Nowadays, there is a great interest in the economic success of direct ethanol fuel cells; however, our atomistic understanding of the designing of stable and low-cost catalysts for the steam reforming of ethanol is still far from satisfactory, in particular due to the large number of undesirable intermediates. In this study, we will report a first-principles investigation of the adsorption properties of ethanol and water at low coverage on close-packed transition-metal (TM) surfaces, namely, Fe(110), Co(0001), Ni(111), Cu(111), Ru(0001), Rh(111), Pd(111), Ag(111), Os(0001), Ir(111), Pt(111), and Au(111), employing density functional theory (DFT) calculations. We employed the generalized gradient approximation with the formulation proposed by Perdew, Burke, and Erzenholf (PBE) to the exchange correlation functional and the empirical correction proposed by S. Grimme (DFT+D3) for the van der Waals correction. We found that both adsorbates binds preferentially near or on the on top sites of the TM surfaces through the 0 atoms. The PBE adsorption energies of ethanol and water decreases almost linearly with the increased occupation of the 4d and 5d d-band, while there is a deviation for the 3d systems. The van der Waals correction affects the linear behavior and increases the adsorption energy for both adsorbates, which is expected as the van der Waals energy due to the correlation effects is strongly underestimated by DFT-PBE for weak interacting systems. The geometric parameters for water/TM are not affected by the van der Waals correction, i.e., both DFT and DFT+D3 yield an almost parallel orientation for water on the TM surfaces; however, DFT+D3 changes drastically the ethanol orientation. For example, DFT yields an almost perpendicular orientation of the C-C bond to the TM surface, while the C-C bond is almost parallel to the surface using DFT +D3 for all systems, except for ethanol/Fe(110). Thus, the van der Waals correction decreases the distance of the C atoms to the TM surfaces, which might contribute to break the C-C bond. The work function decreases upon the adsorption of ethanol and water, and both follow the same trends, however, with different magnitude (larger for ethanol/TM) due to the weak binding of water to the surface. The electron density increases mainly in the region between the topmost layer and the adsorbates, which explains the reduction of the substrate work function.

Analog circuit synthesis performing fast Pareto frontier exploration and analysis through 3D graphs

This paper presents a technique for performing analog design synthesis at circuit level providing feedback to the designer through the exploration of the Pareto frontier. A modified simulated annealing which is able to perform crossover with past anchor points when a local minimum is found which is used as the optimization algorithm on the initial synthesis procedure. After all specifications are met, the algorithm searches for the extreme points of the Pareto frontier in order to obtain a non-exhaustive exploration of the Pareto front. Finally, multi-objective particle swarm optimization is used to spread the results and to find a more accurate frontier. Piecewise linear functions are used as single-objective cost functions to produce a smooth and equal convergence of all measurements to the desired specifications during the composition of the aggregate objective function. To verify the presented technique two circuits were designed, which are: a Miller amplifier with 96 dB Voltage gain, 15.48 MHz unity gain frequency, slew rate of 19.2 V/mu s with a current supply of 385.15 mu A, and a complementary folded cascode with 104.25 dB Voltage gain, 18.15 MHz of unity gain frequency and a slew rate of 13.370 MV/mu s. These circuits were synthesized using a 0.35 mu m technology. The results show that the method provides a fast approach for good solutions using the modified SA and further good Pareto front exploration through its connection to the particle swarm optimization algorithm.