A thin film of polyvinylidene fluoride-trifluoroethylene (PVDF-TrFE) has good flexibility and simple preparation process. More importantly, compared with PVDF, its piezoelectric β-phase can be easily formed without mechanical stretching. However, its piezoelectricity is relatively lower. Therefore, at present, PVDF-TrFE is always compounded with other kinds of piezoelectric materials to solve this problem. The effect of nano-ZnO doping amount on the sensing characteristics of the piezoelectric films was studied. PVDF-TrFE/nano-ZnO films with different nano-ZnO contents were prepared by spin coating process and packaged. The dispersion of nano-ZnO dopants and the crystallinity of β-phase in piezoelectric films with different nano-ZnO contents were observed by scanning electron microscopy and X-ray diffraction, and the piezoelectric strain constants and dielectric constants were measured, respectively. The effect of different nano-ZnO contents on the output performance of the piezoelectric sensor was obtained by a series of impact experiments. The results show that the piezoelectric strain constant and dielectric constant can be increased by doping nano-ZnO in PVDF-TrFE. Moreover, the doping amount of nano-ZnO in PVDF-TrFE is of great significance for improving the piezoelectric properties of PVDF-TrFE/nano-ZnO thin films. Among the prepared piezoelectric films, the output voltage of PVDF-TrFE/nano-ZnO piezoelectric sensor with 7.5% nano-ZnO doping amount is about 5.5 times that of pure PVDF-TrFE. Thus, the optimal range of the doping amount for nano-ZnO is about 4–10%.

Parallel Krylov Subspace Methods are commonly used for solving large-scale sparse linear systems. Facing the development of extreme scale platforms, the minimization of synchronous global communication becomes critical to obtain good efficiency and scalability. This paper highlights a recent development of a hybrid (unite and conquer) method, which combines three computation algorithms together with asynchronous communication to accelerate the resolution of non-Hermitian linear systems and to improve its fault tolerance and reusability. Experimentation shows that our method has an up to 5× speedup and better scalability than the conventional methods for the resolution on hierarchical clusters with hundreds of nodes.

Iterative linear algebra methods are the important parts of the overall computing time of applications in various fields since decades. Recent research related to social networking, big data, machine learning and artificial intelligence has increased the necessity for non-hermitian solvers associated with much larger sparse matrices and graphs. The analysis of the iterative method behaviors for such problems is complex, and it is necessary to evaluate their convergence to solve extremely large non-Hermitian eigenvalue and linear problems on parallel and/or distributed machines. This convergence depends on the properties of spectra. Then, it is necessary to generate large matrices with known spectra to benchmark the methods. These matrices should be non-Hermitian and non-trivial, with very high dimension. This paper highlights a scalable matrix generator that uses the user-defined spectrum to construct largescale sparse matrices and to ensure their eigenvalues as the given ones with high accuracy. This generator is implemented on CPUs and multi-GPU platforms. Good strong and weak scaling performance is obtained on several supercomputers. We also propose a method to verify its ability to guarantee the given spectra.

Background: S-ketamine (the S-isomer of ketamine) is twice as potent as the racemic mixture of this agent and carries fewer side effects when administered to humans. Information regarding the use of S-ketamine for the prevention of emergence delirium (ED) is limited. Thus, we evaluated the effect of S-ketamine administered at the end of anesthesia on ED in preschool children undergoing tonsillectomy and/or adenoidectomy.Methods: We investigated 108 children aged 3–7 years, who were scheduled for elective tonsillectomy and/or adenoidectomy under general anesthesia. They were randomly assigned to receive either S-ketamine 0.2 mg/kg or an equal volume of normal saline at the end of anesthesia. The primary outcome was the highest score on the pediatric anesthesia ED (PAED) scale during the first 30 min post-surgery. The secondary outcomes included the incidence of ED (defined as a score of ≥ 3 on Aono scale), pain score, time to extubation, and incidences of adverse events. Multivariate analyses were also performed using logistic regression to evaluate the independent factors predictive of ED.Results: The median (interquartile range) PAED score of the S-ketamine group (0 [0, 3]) was significantly lower than that in the control group (1 [0, 7]) (estimate median difference = 0, 95% confidence interval −2 to 0, p = 0.040). Significantly fewer patients in the S-ketamine group had an Aono scale score ≥ 3 (4 [7%] vs. 12 [22%], p = 0.030). Patients in the S-ketamine group also had a lower median pain score than did control subjects (4 [4, 6] vs. 6 [5, 8], p = 0.002). The time to extubation and incidences of adverse events were comparable between the two groups. However, multivariate analyses indicated that except S-ketamine use, pain scores, age and duration of anesthesia were independent factors predictive of ED.Conclusion: S-ketamine (0.2 mg/kg) administered at the end of anesthesia effectively reduced the incidence and severity of ED in preschool children undergoing tonsillectomy and/or adenoidectomy without prolonging the time to extubation or increasing adverse events. However, S-ketamine use was not an independent factor predictive of ED.