Improper ferroelectricity in ultrathin hexagonal ferrites films

Suppression of ferroelectricity in ultrathin films of improper ferroelectric hexagonal ferrites or manganites has been attributed to the effect of interfacial clamping; however, the quantitative understanding and related phenomenological model are still lacking. In this work, we report on the paraelectric-to-ferroelectric phase transition of epitaxial h-ScFeO3 films with different thicknesses through in situ reflection highenergy electron diffraction. Based on the interfacial clamping model and the Landau theory, we show that the thickness-dependence of the ferroelectric Curie temperature can be understood in terms of the characteristic length of an interfacial clamping layer and the bulk Curie temperature. Furthermore, we found that the critical thickness of improper ferroelectricity is proportional to the characteristic length of the interfacial clamping layer. These results reveal the essential role of mechanical clamping from interface on the improper ferroelectricity of hexagonal ferrites or manganites and could serve as the guidance to achieve robust improper ferroelectricity in ultrathin films

Systematic study of elliptic flow parameter in the relativistic nuclear collisions at RHIC and LHC energies

We employed the new issue of a parton and hadron cascade model PACIAE 2.1 to systematically investigate the charged particle elliptic flow parameter $v_2$ in the relativistic nuclear collisions at RHIC and LHC energies. With randomly sampling the transverse momentum $x$ and $y$ components of the particles generated in string fragmentation on the circumference of an ellipse instead of circle originally, the calculated charged particle $v_2(\eta)$ and $v_2(p_T)$ fairly reproduce the corresponding experimental data in the Au+Au/Pb+Pb collisions at $\sqrt{s_{NN}}$=0.2/2.76 TeV. In addition, the charged particle $v_2(\eta)$ and $v_2(p_T)$ in the p+p collisions at $\sqrt s$=7 TeV as well as in the p+Au/p+Pb collisions at $\sqrt{s_{NN}}$=0.2/5.02 TeV are predicted.Comment: 7 pages, 5 figure

MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation

The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentation, has attracted much attention. However, the publicly available COVID-19 training data are limited, easily causing overfitting for traditional deep learning methods that are usually data-hungry with millions of parameters. On the other hand, fast training/testing and low computational cost are also necessary for quick deployment and development of COVID-19 screening systems, but traditional deep learning methods are usually computationally intensive. To address the above problems, we propose MiniSeg, a lightweight deep learning model for efficient COVID-19 segmentation. Compared with traditional segmentation methods, MiniSeg has several significant strengths: i) it only has 83K parameters and is thus not easy to overfit; ii) it has high computational efficiency and is thus convenient for practical deployment; iii) it can be fast retrained by other users using their private COVID-19 data for further improving performance. In addition, we build a comprehensive COVID-19 segmentation benchmark for comparing MiniSeg to traditional methods

A pilot study of aortic hemodynamics before and after thoracic endovascular repair with a double-branched endograft

This work was partially supported by Bolton Medical, Sunrise, Florida, US. The authors declare that although Bolton Medical supported this study, the funding company had no control, input or influence on the study design, data analysis or publications.Peer reviewedPublisher PD

Higher moment singularities explored by the net proton non-statistical fluctuations

We use the non-statistical fluctuation instead of the full one to explore the higher moment singularities of net proton event distributions in the relativistic Au+Au collisions at $\sqrt{s_{NN}}$ from 11.5 to 200 GeV calculated by the parton and hadron cascade model PACIAE. The PACIAE results of mean ($M$), variance ($\sigma^2$), skewness ($S$), and kurtosis ($\kappa$) are consistent with the corresponding STAR data. Non-statistical moments are calculated as the difference between the moments derived from real events and the ones from mixed events, which are constructed by combining particles randomly selected from different real events. An evidence of singularity at $\sqrt{s_{NN}}\sim$ 60 GeV is first seen in the energy dependent non-statistical $S$ and $S\sigma$.Comment: 5 pages,5 figure