Dynamic microscopic structures and dielectric response in the cubic-to-tetragonal phase transition for BaTiO3 studied by first-principles molecular dynamics simulation

The dynamic structures of the cubic and tetragonal phase in BaTiO3 and its dielectric response above the cubic-to-tetragonal phase transition temperature (Tp) are studied by first-principles molecular dynamics (MD) simulation. It's shown that the phase transition is due to the condensation of one of the transverse correlations. Calculation of the phonon properties for both the cubic and tetragonal phase shows a saturation of the soft mode frequency near 60 cm-1 near Tp and advocates its order-disorder nature. Our first-principles calculation leads directly to a two modes feature of the dielectric function above Tp [Phys. Rev. B 28, 6097 (1983)], which well explains the long time controversies between experiments and theories

Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation

We aim at segmenting small organs (e.g., the pancreas) from abdominal CT scans. As the target often occupies a relatively small region in the input image, deep neural networks can be easily confused by the complex and variable background. To alleviate this, researchers proposed a coarse-to-fine approach, which used prediction from the first (coarse) stage to indicate a smaller input region for the second (fine) stage. Despite its effectiveness, this algorithm dealt with two stages individually, which lacked optimizing a global energy function, and limited its ability to incorporate multi-stage visual cues. Missing contextual information led to unsatisfying convergence in iterations, and that the fine stage sometimes produced even lower segmentation accuracy than the coarse stage. This paper presents a Recurrent Saliency Transformation Network. The key innovation is a saliency transformation module, which repeatedly converts the segmentation probability map from the previous iteration as spatial weights and applies these weights to the current iteration. This brings us two-fold benefits. In training, it allows joint optimization over the deep networks dealing with different input scales. In testing, it propagates multi-stage visual information throughout iterations to improve segmentation accuracy. Experiments in the NIH pancreas segmentation dataset demonstrate the state-of-the-art accuracy, which outperforms the previous best by an average of over 2%. Much higher accuracies are also reported on several small organs in a larger dataset collected by ourselves. In addition, our approach enjoys better convergence properties, making it more efficient and reliable in practice.Comment: Accepted to CVPR 2018 (10 pages, 6 figures

Factor Structure of a Multidimensional Gender Identity Scale in a Sample of Chinese Elementary School Children

This study examined the factor structure of a scale based on the four-dimensional gender identity model (Egan and Perry, 2001) in 726 Chinese elementary school students. Exploratory factor analyses suggested a three-factor model, two of which corresponded to “Felt Pressure” and “Intergroup Bias” in the original model. The third factor “Gender Compatibility” appeared to be a combination of “Gender Typicality” and “Gender Contentment” in the original model. Follow-up confirmatory factor analysis (CFA) indicated that, relative to the initial four-factor structure, the three-factor model fits the current Chinese sample better. These results are discussed in light of cross-cultural similarities and differences in development of gender identity

Quantitative Analysis of Heroin and its Metabolites in vivo

This study investigated heroin and its metabolites in vivo in the rat by using a high-performance liquid chromatography-tandem mass spectrometry (GC-MS) method

AMP kinase promotes Bcl6 expression in both mouse and human T cells

The transcription factor Bcl6 is a master regulator of follicular helper T (TFH) cells, and understanding the signaling pathway that induces Bcl6 and TFH cell differentiation is therefore critical. IL-2 produced during T cell activation inhibits Bcl6 expression but how TFH cells evade IL-2 inhibition is not completely understood. Here we show that Bcl6 is highly up-regulated in activated CD4 T cells following glucose deprivation (GD), and this pathway is insensitive to inhibition by IL-2. Similar to GD, the glucose analog 2-deoxyglucose (2DG) inhibits glycolysis, and 2DG induced Bcl6 expression in activated CD4 T cells. The metabolic sensor AMP kinase (AMPK) is activated when glycolysis is decreased, and the induction of Bcl6 by GD was inhibited by the AMPK antagonist compound C. Additionally, activation of AMPK by the drug AICAR caused Bcl6 up-regulation in activated CD4 T cells. When mice were immunized with KLH using AICAR as an adjuvant, there was a strong TFH–dependent enhancement of KLH-specific antibody (Ab) responses, and higher Bcl6 expression in TFH cells in vivo. Activation of AMPK strongly induced BCL6 and the up-regulation of TFH cell marker expression by human CD4 T cells. Our data reveal a major new pathway for TFH cell differentiation, conserved by both mouse and human T cells. Mature TFH cells are reported to have a lower metabolic state compared to TH1 cells. Our data indicates that decreased metabolism may be deterministic for TFH cell differentiation, and not simply a result of TFH cell differentiation

A Study of the Effect of Doughnut Chart Parameters on Proportion Estimation Accuracy

Pie and doughnut charts nicely convey the part–whole relationship and they have become the most recognizable chart types for representing proportions in business and data statistics. Many experiments have been carried out to study human perception of the pie chart, while the corresponding aspects of the doughnut chart have seldom been tested, even though the doughnut chart and the pie chart share several similarities. In this paper, we report on a series of experiments in which we explored the effect of a few fundamental design parameters of doughnut charts, and additional visual cues, on the accuracy of such charts for proportion estimates. Since mobile devices are becoming the primary devices for casual reading, we performed all our experiments on such device. Moreover, the screen size of mobile devices is limited and it is therefore important to know how such size constraint affects the proportion accuracy. For this reason, in our first experiment we tested the chart size and we found that it has no significant effect on proportion accuracy. In our second experiment, we focused on the effect of the doughnut chart inner radius and we found that the proportion accuracy is insensitive to the inner radius, except the case of the thinnest doughnut chart. In the third experiment, we studied the effect of visual cues and found that marking the centre of the doughnut chart or adding tick marks at 25% intervals improves the proportion accuracy. Based on the results of the three experiments, we discuss the design of doughnut charts and offer suggestions for improving the accuracy of proportion estimates