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Scientometrics - This study investigates a potential relationship between highly-cited scholarly papers and the number of citations received by other papers with which they share a journal issue.... 相似文献
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Anna Enrico Wenjing Zhang Marie Lund Traulsen Elena Marzia Sala Paola Costamagna Peter Holtappels 《Journal of the European Ceramic Society》2018,38(7):2677-2686
Water-based sol-gel electrospinning is employed to manufacture perovskite oxide La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF) nanofiber cathodes for intermediate-temperature solid oxide fuel cells. LSCF fibrous scaffolds are synthesized through electrospinning of a sol-gel solution employing water as the only solvent. Morphological characterizations demonstrate that the LSCF fibers have highly crystalline structure with uniform elemental distribution. After heat treatment, the average fiber diameter is 250 nm and the porosity of the nanofiber tissue is 37.5 %. The heat treated LSCF nanofibers are applied directly onto a Ce0.9Gd0.1O1.95 (CGO) electrolyte disk to form a symmetrical cell. Electrochemical characterization is carried out through electrochemical impedance spectroscopy (EIS) in the temperature range 550?°C–950?°C, and reproducibility of the electrochemical performance for a series of cells is demonstrated. At 650?°C, the average measured polarization resistance Rp is 1.0 Ω cm2. Measured performance decay is 1 % during the first 33?h of operation at 750?°C, followed by an additional 0.7 % over the subsequent 70?h. 相似文献
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To determine whether there is any correlation between sudden decrease in barometric pressure and onset of labor, a non-experimental, retrospective study at a 948-bed tertiary care hospital was done. Pregnant patients of 36 weeks gestation or more who presented with spontaneous onset of labor during the 48 hours surrounding the 12 occurrences of significant drop in barometric pressure in 1992 were included in the study. Significantly more occurrences of onset of labor were identified in the 24 hours after a drop in barometric pressure than were identified in the 24 hours prior to the drop in barometric pressure (P < 0.05). Therefore, the overall number of labor onsets increased in the 24 hours following a significant drop in barometric pressure. 相似文献
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We determine the exact power of two-prover interactive proof systems introduced by Ben-Or, Goldwasser, Kilian, and Wigderson (1988). In this system, two all-powerful noncommunicating provers convince a randomizing polynomial time verifier in polynomial time that the inputx belongs to the languageL. We show that the class of languages having tow-prover interactive proof systems is nondeterministic exponential time.We also show that to prove membership in languages inEXP, the honest provers need the power ofEXP only.The first part of the proof of the main result extends recent techniques of polynomial extrapolation used in the single prover case by Lund, Fortnow, Karloff, Nisan, and Shamir.The second part is averification scheme for multilinearity of a function in several variables held by an oracle and can be viewed as an independent result onprogram verification. Its proof rests on combinatorial techniques employing a simple isoperimetric inequality for certain graphs: 相似文献
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At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models. 相似文献