We have developed a novel route to reduce the dielectric loss of CaCu3Ti4O12 (CCTO) material based on the internal‐barrier‐layer‐capacitance (IBLC) model. By the partial La‐for‐Ca substitution the dielectric loss was suppressed re‐markably while the giant dielectric constant still remains. The sample of Ca0.8La0.2Cu3Ti4O12 exhibits a high dielectric con‐ stant over 3000 and a low dissipation factor below 0.015 at 10 kHz from 180 K to 300 K. The impedance spectroscopy analysis confirms that the decrease of dielectric loss is mainly due to the increase of conductivity in the CCTO grain/subgrain. Our result is expected to be able to promote practical applications. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

This multicenter registry documents satisfactory safety and efficacy profiles, as evidenced by low rates of major adverse cardiac events and stent thrombosis up to 18 months, for the Excel biodegradable polymer-based sirolimus-eluting stent when used with 6 months of dual antiplatelet therapy in a "real-world" setting. (Multi-Center Registry Trial of EXCEL Biodegradable Polymer Drug-Eluting Stent [CREATE]; NCT00331578).

In this single-center experience with complex patients and lesions, the EXCEL stent implantation with 6-month dual antiplatelet treatment proved to markedly reduce the incidence of 24-month ISR and MACE. These preliminary findings require further validation by large scale, randomized trials.

The temperature dependence of the resistivity and magnetoresistance (MR) of quasi-one-dimensional NbSe3 was studied. The sharp increase of the positive MR in the lower charge-density wave (CDW) phase is consistent with previous reports, and the violation of Kohler’s rule is obvious. We found that the MR data can be fitted very well with a modified two-band model, and the temperature dependence of the resulting parameters was discussed. The MR, the effect of magnetic field on the CDW gap, and the thermoelectric power of NbSe3 can be coherently understood within this model.

Background: The evidence of current epidemiological studies investigating the association between serum potassium levels and mortality of acute myocardial infarction (AMI) patients is controversial and inadequate. Design: Systematic review and meta-analysis. Methods: Two researchers independently searched the PubMed, EMBASE and Web of Science databases to identify observational studies published prior to 31 October 2017. Similarly, two researchers separately extracted data and any differences were resolved by discussion. Pooled relative risks and 95% confidence intervals (CIs) were computed with an inverse variance-weighted random-effects model. Heterogeneity among studies was assessed with the I 2 statistic. Results: Seven cohort studies were included for analysis. Compared with the reference group (3.5 to <4.0 mEq/L), the pooled relative risks of mortality were 1.15 (95% CI ¼ 1.00-1.32), 1.09 (95% CI ¼ 0.97-1.24), 1.42 (95% CI ¼ 1.19-1.70) and 1.85 (95% CI ¼ 1.39-2.47) for AMI patients with a potassium level of<3.5, 4.0 to <4.5, 4.5 to <5.0, and 5.0 mEq/L, respectively. For admission and post-admission potassium, although J-shaped associations were also indicated, nonsignificant results were observed for AMI patients with potassium levels of <3.5 mEq/L when compared with the reference group. Notably, in subgroup analyses of study characteristics, stratified by study quality, geographic location, type of outcome, number of cases, type of AMI, and adjustment for potential confounders, the findings were broadly consistent across strata. Conclusions: These findings indicate that both lower (<3.5 mEq/L) and higher (4.5 mEq/L) serum potassium levels are associated with an increased risk of mortality of patients with AMI.

We report the evidence of proton incorporations in a newly-discovered cobalt oxyhydrate superconductor. During the hydration process for Na$_{0.32}$CoO$_{2}$ by the direct reaction with water liquid, it was shown that substantial NaOH was gradually liberated, indicating that H$^{+}$ is incorporated into the hydrated compound. Combined with the thermogravimetric analysis, the chemical composition of the typical sample is Na$_{0.22}$H$_{0.1}$CoO$_{2}\cdot 0.85$H$_{2}$O, which shows bulk superconductivity at 4.4 K.Comment: 9 pages, 4 figure

For the optimal design of electromagnetic devices, it is the most time consuming to obtain the training samples from full wave electromagnetic simulation software, including HFSS, CST, and IE3D. Traditional machine learning methods usually use only labeled samples or unlabeled samples, but in practical problems, labeled samples and unlabeled samples coexist, and the acquisition cost of labeled samples is relatively high. This paper proposes a semisupervised learning Gaussian Process (GP), which combines unlabeled samples to improve the accuracy of the GP model and reduce the number of labeled training samples required. The proposed GP model consists two parts: initial training and self-training. In the process of initial training, a small number of labeled samples obtained by full wave electromagnetic simulation are used for training the initial GP model. Afterwards, the trained GP model is copied to another GP model in the process of self-training, and then the two GP models will update after crosstraining with different unlabeled samples. Using the same test samples for testing and updating, a model with a smaller error will replace another. Repeat the self-training process until a predefined stopping criterion is met. Four different benchmark functions and resonant frequency modeling problems of three different microstrip antennas are used to evaluate the effectiveness of the GP model. The results show that the proposed GP model has a good fitting effectiveness on benchmark functions. For microstrip antennas resonant frequency modeling problems, in the case of using the same labeled samples, its predictive ability is better than that of the traditional supervised GP model.

While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25–75 year-old adults read sentences with high cloze (HC) and low cloze (LC) probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC) was found in several regions, especially the left middle frontal gyrus (MFG) and right inferior frontal gyrus (IFG), which play an important role in semantic integration. Moreover, when accounting for global gray matter volume reduction, the age-cloze correlation in the left MFG and right IFG was absent. The results suggest that brain structural atrophy may disrupt brain response in aging brains, which then show less brain engagement in semantic integration.