Gentiopicrin exerts anticancer effect on human colon cancer cells via caspase-dependent apoptosis, cell cycle arrest, and inhibition of cell migration and invasion

Purpose: To investigate the anticancer effect of gentiopicrin on human colon cancer (HT-295) cells, and its effects on caspase-mediated cellular apoptosis, cell cycle, cell migration and cell invasion. Methods: MTT assay and clonogenic assay were used to study the effect of gentiopicrin on cell viability and cancer colony formation, respectively, while the apoptotic effects of gentiopicrin were determined using fluorescence microscopy and Western blotting. The effect of gentiopicrin on cell cycle was evaluated by flow cytometry, while Transwell assay was used to study its effects on cell migration and invasion. Results: Gentiopicrin exerted potent and dose-dependent suppression of cell proliferation and colony formation, and produced pro-apoptotic effects on HT-295 colon cancer cells. Treatment of HT-295 cells with gentiopicrin resulted in up-regulated expressions of caspase-3, caspase-8, caspase-9 and Bax, while Bcl-2 expression was downregulated. Moreover, gentiopicrin dose-dependently induced cell cycle arrest in HT-295 cells at the G2/M phase, and inhibited cell migration and invasion. Conclusion: Gentiopicrin exerts potent anticancer effects on human colon cancer cells via cell apoptosis and G2/M phase cell cycle arrest. In addition, it suppressed the migration and invasion of HT-295 cells. These findings provide useful basis for further in vivo research of gentiopicrin on colon cancer

The source localization technique based on improved functional beamforming using a virtual array

Beamforming have become a popular technique to identify sound source. The most common application is conventional beamforming, but it has low resolution and requires a large number of microphones at low frequency. To overcome this problem, an improved functional beamforming method based on “virtual array” and the relative spectral matrix is introduced. Firstly, the relative complex pressures of the sound field can be acquired by “virtual array” with one scanning microphone and a fixed reference microphone. Thereby, a relative spectral matrix of the relative complex pressures measured can be obtained. Then the improved functional beamforming method with order v is developed based on the relative spectral matrix. And the resolution of the improved method can be modified by increased the number of order v. but it also can be improved by changing virtual microphones. This property allows widening the scope of this interesting beamforming method

Feasibility investigation of direct laser cutting process of metal foam with high pore density

To avoid damage to the pore structure of metal foam, a laser cutting process for efficiently and directly cutting metal foam into regular shapes is proposed. After analyzing the proposed laser cutting process, its effects when applied to three different types of metal material (copper, ferroalloy, and nickel) and two levels of pore density, namely 90 and 110 pores per inch (PPI), were investigated. The results show that metal foam with a good surface quality can be obtained without damaging the pore structure by using the proposed laser cutting process. Of the three metal types considered, the highest material removal rate (MRR) and material oxidation rate (MOR) were observed for ferroalloy foam. Of the two pore densities, metal foam of 90 PPI showed a larger material removal rate than metal foam of 110 PPI. The MRR and MOR increased with an increase in the laser output power and decrease in the scanning speed. Using a central composite experimental design method, optimized processing parameters of 26 W laser output power and 475 mm/s scanning speed were adopted to cut the metal foam with a high pore density

Three-dimensional Reconstruction of Coronal Mass Ejections by CORAR Technique through Different Stereoscopic Angle of STEREO Twin Spacecraft

Recently, we developed the Correlation-Aided Reconstruction (CORAR) method to reconstruct solar wind inhomogeneous structures, or transients, using dual-view white-light images (Li et al. 2020; Li et al. 2018). This method is proved to be useful for studying the morphological and dynamical properties of transients like blobs and coronal mass ejection (CME), but the accuracy of reconstruction may be affected by the separation angle between the two spacecraft (Lyu et al. 2020). Based on the dual-view CME events from the Heliospheric Imager CME Join Catalogue (HIJoinCAT) in the HELCATS (Heliospheric Cataloguing, Analysis and Techniques Service) project, we study the quality of the CME reconstruction by the CORAR method under different STEREO stereoscopic angles. We find that when the separation angle of spacecraft is around 150{\deg}, most CME events can be well reconstructed. If the collinear effect is considered, the optimal separation angle should locate between 120{\deg} and 150{\deg}. Compared with the CME direction given in the Heliospheric Imager Geometrical Catalogue (HIGeoCAT) from HELCATS, the CME parameters obtained by the CORAR method are reasonable. However, the CORAR-obtained directions have deviations towards the meridian plane in longitude, and towards the equatorial plane in latitude. An empirical formula is proposed to correct these deviations. This study provides the basis for the spacecraft configuration of our recently proposed Solar Ring mission concept (Wang et al. 2020b).Comment: 18 pages, 9 figure

One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning

Hyperspectral anomaly detection (HAD) involves identifying the targets that deviate spectrally from their surroundings, without prior knowledge. Recently, deep learning based methods have become the mainstream HAD methods, due to their powerful spatial-spectral feature extraction ability. However, the current deep detection models are optimized to complete a proxy task (two-step paradigm), such as background reconstruction or generation, rather than achieving anomaly detection directly. This leads to suboptimal results and poor transferability, which means that the deep model is trained and tested on the same image. In this paper, an unsupervised transferred direct detection (TDD) model is proposed, which is optimized directly for the anomaly detection task (one-step paradigm) and has transferability. Specially, the TDD model is optimized to identify the spectral deviation relationship according to the anomaly definition. Compared to learning the specific background distribution as most models do, the spectral deviation relationship is universal for different images and guarantees the model transferability. To train the TDD model in an unsupervised manner, an anomaly sample simulation strategy is proposed to generate numerous pairs of anomaly samples. Furthermore, a global self-attention module and a local self-attention module are designed to help the model focus on the "spectrally deviating" relationship. The TDD model was validated on four public HAD datasets. The results show that the proposed TDD model can successfully overcome the limitation of traditional model training and testing on a single image, and the model has a powerful detection ability and excellent transferability

Unraveling the Thermodynamic Enigma between Fast and Slow Coronal Mass Ejections

Coronal Mass Ejections (CMEs) are the most energetic expulsions of magnetized plasma from the Sun that play a crucial role in space weather dynamics. This study investigates the diverse kinematics and thermodynamic evolution of two CMEs (CME1: 2011 September 24 and CME2: 2018 August 20) at coronal heights where thermodynamic measurements are limited. The peak 3D propagation speed of CME1 is high (1,885 km/s) with two-phase expansion (rapid and nearly constant), while the peak 3D propagation speed of CME2 is slow (420 km/s) with only a gradual expansion. We estimate the distance-dependent variations in the polytropic index, heating rate, temperature, and internal forces implementing the revised FRIS model, taking inputs of 3D kinematics estimated from the GCS model. We find CME1 exhibiting heat-release during its early-rapid acceleration decrease and jumps to the heat-absorption state during its constant acceleration phase. In contrast to CME1, CME2 shows a gradual transition from the near-adiabatic to the heat-absorption state during its gradually increasing acceleration. Our analysis reveals that although both CMEs show differential heating, they experience heat-absorption during their later propagation phases, approaching the isothermal state. The faster CME1 achieves an adiabatic state followed by an isothermal state at smaller distances from the Sun than the slower CME2. We also find that the expansion of CMEs is primarily influenced by centrifugal and thermal pressure forces, with the Lorentz force impeding expansion. Multi-wavelength observations of flux-ropes at source regions support the FRIS model-derived findings at initially observed lower coronal heights.Comment: 23 pages, 9 figures, accepted for publication in The Astrophysical Journal (ApJ

Nonlinear Hall effect and scaling law in Sb-doped topological insulator MnBi4Te7

Nonlinear Hall effect (NLHE), as a new member of Hall effect family, has been realized in many materials, attracting a great deal of attention. Here, we report the observation of NLHE in magnetic topological insulator Sb-doped MnBi4Te7 flakes. The NLHE generation efficiency can reach up to 0.06 V^-1, which is comparable to that observed in MnBi2Te4. Differently, the NLHE can survive up to 200 K, much larger than the magnetic transition temperature. We further study the scaling behavior of the NLHE with longitudinal conductivity. The linear relationship with opposite slope when temperature is below and above the magnetic transition temperature is uncovered. It reveals that the NLHE originates from skew scattering. Our work provides a platform to search NLHE with larger generation efficiency at higher temperatures

Performance optimization and lightweight design of floating raft vibration isolation system based on RBF-PSO algorithm

ObjectiveTo address the challenges of heavy workload and long iterative cycles in the lightweight design of floating raft vibration isolation system in engineering applications, this study proposes a lightweight design method based on RBF-PSO multi-objective optimization algorithm. Method Taking the plate-frame floating raft vibration isolation system as the research object, a finite element model was established using ANSYS APDL. The vibration isolation performance and impact resistance were evaluated through numerical simulation. Experimental tests were conducted to assess the vibration isolation performance of the floating raft. The accuracy of the numerical simulation was validated by comparing it with the experimental results. A full finite difference method was employed to analyze the parameter sensitivity of the floating raft vibration isolation system. Appropriate design variables were selected based on the sensitivity analysis. The lightweight design of the floating raft vibration isolation system was carried out using the RBF-PSO multi-objective optimization algorithm. Results The results show that after optimization, the mass of the raft is 63.03 kg. Compared with the original design, the weight of the lightweight raft is reduced by 31.92%. The vibration isolation performance of the floating raft system improves by 2.48 dB. The impact resistance of the equipment is also improved. The discrepancy between the optimized result obtained by the RBF-PSO algorithm and the numerical simulation calculation is less than 1%. Conclusion Therefore, the RBF-PSO multi-objective optimization algorithm can be effectively applied to the lightweight design of the floating raft vibration isolation system

Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction

Online lane graph construction is a promising but challenging task in autonomous driving. Previous methods usually model the lane graph at the pixel or piece level, and recover the lane graph by pixel-wise or piece-wise connection, which breaks down the continuity of the lane. Human drivers focus on and drive along the continuous and complete paths instead of considering lane pieces. Autonomous vehicles also require path-specific guidance from lane graph for trajectory planning. We argue that the path, which indicates the traffic flow, is the primitive of the lane graph. Motivated by this, we propose to model the lane graph in a novel path-wise manner, which well preserves the continuity of the lane and encodes traffic information for planning. We present a path-based online lane graph construction method, termed LaneGAP, which end-to-end learns the path and recovers the lane graph via a Path2Graph algorithm. We qualitatively and quantitatively demonstrate the superiority of LaneGAP over conventional pixel-based and piece-based methods on challenging nuScenes and Argoverse2 datasets. Abundant visualizations show LaneGAP can cope with diverse traffic conditions. Code and models will be released at \url{https://github.com/hustvl/LaneGAP} for facilitating future research