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

Study on wheel-rail interaction based on rail roughness

Environmental vibration and noise pollution caused by the operation of subway is a hot topic of concern at home and abroad. There is a need to research dynamic interaction between trains and track in order to solve environmental vibration and noise pollution caused by the operation of train. As an excitation source of the train vibration, rail surface roughness has significant impact on the wheel-rail interaction. In order to study the effect of rail roughness on the wheel-rail vibration load, the wheel-rail interaction model is established based on excitation of rail surface roughness in this paper. The effect of rail roughness on train vibration load is calculated by this model according to the measured rail roughness data in Beijing subway in the MATLAB program. Wheel-rail force in the most adverse situations is also calculated. The property of wheel-rail force under different conditions such as track forms, driving speed and curve radius is also analyzed in this paper

RNA-seq-based digital gene expression analysis reveals modification of host defense responses by rice stripe virus during disease symptom development in Arabidopsis

DEGs involved in protein phosphorylation at 14 dpi. (XLSX 52 kb

Higgs boson pair production process e+e−→ZHHe^+e^-\to ZHH in the littlest Higgs model at the ILC

The physics prospect at future linear $e^{+}e^{-}$ colliders for the study of the Higgs triple self-coupling via the process of $e^{+}e^{-}\to ZHH$ is investigated. In this paper, we calculate the contribution of the new particles predicted by the littlest Higgs model to the cross sections of this process in the future high energy $e^{+}e^{-}$ collider($ILC$). The results show that, in the favorable parameter spaces preferred by the electroweak precision, the deviation of the total cross sections from its $SM$ value varies from a few percent to tens percent, which may be detected at the future $ILC$ experiments with $\sqrt{s}$=500GeV.Comment: 13 pages,4 figure

Adjusting the dose of traditional drugs combined with immunotherapy: reshaping the immune microenvironment in lung cancer

Immunotherapy is currently the most promising clinical treatment for lung cancer, not only revolutionizing second-line therapy but now also approved for first-line treatment. However, its clinical efficiency is not high and not all patients benefit from it. Thus, finding the best combination strategy to expand anti-PD-1/PD-L1-based immunotherapy is now a hot research topic. The conventional use of chemotherapeutic drugs and targeted drugs inevitably leads to resistance, toxic side effects and other problems. Recent research, however, suggests that by adjusting the dosage of drugs and blocking the activation of mutational mechanisms that depend on acquired resistance, it is possible to reduce toxic side effects, activate immune cells, and reshape the immune microenvironment of lung cancer. Here, we discuss the effects of different chemotherapeutic drugs and targeted drugs on the immune microenvironment. We explore the effects of adjusting the dosing sequence and timing, and the mechanisms of such responses, and show how the effectiveness and reliability of combined immunotherapy provide improved treatment outcomes

Towards a deep-learning-based framework of sentinel-2 imagery for automated active fire detection

This paper proposes an automated active fire detection framework using Sentinel-2 imagery. The framework is made up of three basic parts including data collection and preprocessing, deep-learning-based active fire detection, and final product generation modules. The active fire detection module is developed on a specifically designed dual-domain channel-position attention (DCPA)+HRNetV2 model and a dataset with semi-manually annotated active fire samples is constructed over wildfires that commenced on the east coast of Australia and the west coast of the United States in 2019-2020 for the training process. This dataset can be used as a benchmark for other deep-learning-based algorithms to improve active fire detection accuracy. The performance of active fire detection is evaluated regarding the detection accuracy of deep-learning-based models and the processing efficiency of the whole framework. Results indicate that the DCPA and HRNetV2 combination surpasses DeepLabV3 and HRNetV2 models for active fire detection. In addition, the automated framework can deliver active fire detection results of Sentinel-2 inputs with coverage of about 12,000 km(2) (including data download) in less than 6 min, where average intersections over union (IoUs) of 70.4% and 71.9% were achieved in tests over Australia and the United States, respectively. Concepts in this framework can be further applied to other remote sensing sensors with data acquisitions in SWIR-NIR-Red ranges and can serve as a powerful tool to deal with large volumes of high-resolution data used in future fire monitoring systems and as a cost-efficient resource in support of governments and fire service agencies that need timely, optimized firefighting plans

Modeling realistic multiphase flows using a non-orthogonal multiple-relaxation-time lattice Boltzmann method

In this paper, we develop a three-dimensional multiple-relaxation-time lattice Boltzmann method (MRT-LBM) based on a set of non-orthogonal basis vectors. Compared with the classical MRT-LBM based on a set of orthogonal basis vectors, the present non-orthogonal MRT-LBM simplifies the transformation between the discrete velocity space and the moment space, and exhibits better portability across different lattices. The proposed method is then extended to multiphase flows at large density ratio with tunable surface tension, and its numerical stability and accuracy are well demonstrated by some benchmark cases. Using the proposed method, a practical case of a fuel droplet impacting on a dry surface at high Reynolds and Weber numbers is simulated and the evolution of the spreading film diameter agrees well with the experimental data. Furthermore, another realistic case of a droplet impacting on a super-hydrophobic wall with a cylindrical obstacle is reproduced, which confirms the experimental finding of Liu \textit{et al.} [``Symmetry breaking in drop bouncing on curved surfaces," Nature communications 6, 10034 (2015)] that the contact time is minimized when the cylinder radius is comparable with the droplet cylinder.Comment: 19 pages, 11 figure