The study of the charged top-pion decay processes

In the framework of top-color assisted technicolor(TC2) theory, we study the four decay processes of charged top-pion, i.e., $\Pi^{+}_{t}\to t\bar{b}$, $\Pi^{+}_{t}\to c\bar{b}$, $\Pi^{+}_{t}\to W^{+}\gamma$, $\Pi^{+}_{t}\to W^{+}Z^{0}$, the decay branching ratio of these modes are calculated. The results show that the main decay channels of charged top-pion are the tree level modes: $\Pi_t^+ \to t\bar{b}$ and $\Pi_t^+ \to c\bar{b}$. Light $\Pi_t^+$ is easier to be detected than heavy one at future coliders. So, the study provides us some useful information to search for charged top-pion.Comment: 14 pages, 6 figure

Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach

Even though the volatility spillover effects in global equity markets have been documented extensively, the transmission of illiquidity across national borders has not. In this paper, we propose a multiplicative error model (MEM) for the dynamics of illiquidity. We empirically study the illiquidity and volatility spillover effects in eight developed equity markets during and after the recent financial crisis. We find that equity markets are interdependent, both in terms of volatility and illiquidity. Most markets show an increase in volatility and illiquidity spillover effects during the crisis. Furthermore, we find volatility and illiquidity transmission are highly relevant. Illiquidity is a more important channel than volatility in propagating the shocks in equity markets. Our results show an overall crucial role for illiquidity in US markets in influencing other equity markets' illiquidity and volatility. These findings are of importance for policy makers as well as institutional and private investors

Electrical switching of ferro-rotational order in nano-thick 1T-TaS2_2 crystals

Hysteretic switching of domain states is a salient character of all ferroic materials and the foundation for their multifunctional applications. Ferro-rotational order is emerging as a new type of ferroic order featuring structural rotations, but its controlled switching remains elusive due to its invariance under both time reversal and spatial inversion. Here, we demonstrate electrical switching of ferro-rotational domain states in nanometer-thick 1T-TaS$_2$ crystals in its charge-density-wave phases. Cooling from the high-symmetry phase to the ferro-rotational phase under an external electric field induces domain state switching and domain wall formation, realized in a simple two-terminal configuration using a volt-scale voltage. Although the electric field does not couple with the order due to symmetry mismatch, it drives domain wall propagation to give rise to reversible, durable, and nonvolatile isothermal state switching at room temperature. These results pave the path for manipulation of the ferro-rotational order and its nanoelectronic applications

The productions of the top-pions and top-Higgs associated with the charm quark at the hadron colliders

In the topcolor-assistant technicolor (TC2) model, the typical physical particles, top-pions and top-Higgs, are predicted and the existence of these particles could be regarded as the robust evidence of the model. These particles are accessible at the Tevatron and LHC, and furthermore the flavor-changing(FC) feature of the TC2 model can provide us a unique chance to probe them. In this paper, we study some interesting FC production processes of top-pions and top-Higgs at the Tevatron and LHC, i.e., $c\Pi_{t}^{-}$ and $c\Pi_{t}^{0}(h_{t}^{0})$ productions. We find that the light charged top-pions are not favorable by the Tevatron experiments and the Tevatron has a little capability to probe neutral top-pion and top-Higgs via these FC production processes. At the LHC, however, the cross section can reach the level of $10\sim 100$ pb for $c\Pi_t^-$ production and $10\sim 100$ fb for $c\Pi_t^0(h_t^0)$ production. So one can expect that enough signals could be produced at the LHC experiments. Furthermore, the SM background should be clean due to the FC feature of the processes and the FC decay modes $\Pi_t^-\to b\bar{c}, \Pi_t^0(h_t^0)\to t\bar{c}$ can provide us the typical signal to detect the top-pions and top-Higgs. Therefore, it is hopeful to find the signal of top-pions and top-Higgs with the running of the LHC via these FC processes.Comment: 12 pages, 6 figure

Alterations to the Lung Microbiome in Idiopathic Pulmonary Fibrosis Patients

Lung microbiome ecosystem homeostasis in idiopathic pulmonary fibrosis (IPF) remains uncharacterized. The aims of this study were to identify unique microbial signatures of the lung microbiome and analyze microbial gene function in IPF patients. DNA isolated from BALF samples was obtained for high-throughput gene sequencing. Microbial metagenomic data were used for principal component analysis (PCA) and analyzed at different taxonomic levels. Shotgun metagenomic data were annotated using the KEGG database and were analyzed for functional and metabolic pathways. In this study, 17 IPF patients and 38 healthy subjects (smokers and non-smokers) were recruited. For the PCA, the first and the second principal component explained 16.3 and 13.4% of the overall variability, respectively. The β diversity of microbiome was reduced in the IPF group. Signature of IPF's microbes was enriched of Streptococcus, Pseudobutyrivibrio, and Anaerorhabdus. The translocation of lung microbiome was shown that 32.84% of them were from oral. After analysis of gene function, ABC transporter systems, biofilm formation, and two-component regulatory system were enriched in IPF patients' microbiome. Here we shown the microbiology characteristics in IPF patients. The microbiome may participate in altering internal conditions and involving in generating antibiotic resistance in IPF patients

High-Resolution U-Net: Preserving Image Details for Cultivated Land Extraction

Accurate and efficient extraction of cultivated land data is of great significance for agricultural resource monitoring and national food security. Deep-learning-based classification of remote-sensing images overcomes the two difficulties of traditional learning methods (e.g., support vector machine (SVM), K-nearest neighbors (KNN), and random forest (RF)) when extracting the cultivated land: (1) the limited performance when extracting the same land-cover type with the high intra-class spectral variation, such as cultivated land with both vegetation and non-vegetation cover, and (2) the limited generalization ability for handling a large dataset to apply the model to different locations. However, the “pooling” process in most deep convolutional networks, which attempts to enlarge the sensing field of the kernel by involving the upscale process, leads to significant detail loss in the output, including the edges, gradients, and image texture details. To solve this problem, in this study we proposed a new end-to-end extraction algorithm, a high-resolution U-Net (HRU-Net), to preserve the image details by improving the skip connection structure and the loss function of the original U-Net. The proposed HRU-Net was tested in Xinjiang Province, China to extract the cultivated land from Landsat Thematic Mapper (TM) images. The result showed that the HRU-Net achieved better performance (Acc: 92.81%; kappa: 0.81; F1-score: 0.90) than the U-Net++ (Acc: 91.74%; kappa: 0.79; F1-score: 0.89), the original U-Net (Acc: 89.83%; kappa: 0.74; F1-score: 0.86), and the Random Forest model (Acc: 76.13%; kappa: 0.48; F1-score: 0.69). The robustness of the proposed model for the intra-class spectral variation and the accuracy of the edge details were also compared, and this showed that the HRU-Net obtained more accurate edge details and had less influence from the intra-class spectral variation. The model proposed in this study can be further applied to other land cover types that have more spectral diversity and require more details of extraction

The pricing of unexpected volatility in the currency market

Many recent papers have investigated the role played by volatility in determining the cross-section of currency returns. This paper employs two time-varying factor models: a threshold model and a Markov-switching model to price the excess returns from the currency carry trade. We show that the importance of volatility depends on whether the currency markets are unexpectedly volatile. Volatility innovations during relatively tranquil periods are largely unrewarded in the market, whereas during the unexpected volatile period, this risk, has a substantial impact on currency returns. The empirical results show that the two time-varying factor models fit the data better and generate a smaller pricing error than the linear model, while the Markov-switching model outperforms the threshold factor models not only by generating lower pricing errors but also distinguishes two regimes endogenously and without any predetermined state variables