Large-eddy Simulation of Near-field Dynamics in a Particle-laden Round Turbulent Jet

AbstractThis article investigates the near-field dynamics in a particle-laden round turbulent jet in a large-eddy simulation (LES). A point-force two-way coupling model is adopted in the simulation to reveal the particle modulation of turbulence. The particles mainly excite the initial instability of the jet and bring about the earlier breakup of vortex rings in the near-field. The flow fluctuating intensity either in the axial or in the radial directions is hence increased by particles. The article also describes the mean velocity modulated by particles. The changing statistical velocity induced by particle modulation implies the effects of modulation of the local flow structures. This study is expected to be useful to the control of two-phase turbulent jets

Fast Numerical Solutions of Gas-Particle Two-Phase Vacuum Plumes

The free molecule point source and Simons models coupled to the particle Lagrangian trajectory model are employed, respectively, to establish the fast solving method for gas-particle two-phase vacuum plumes. Density, velocity and temperature distributions of gas phase, and velocity and temperature of particles are solved to present the flow properties of two-phase plumes. The method based on free molecule point source model predicts the velocity and temperature distributions of vacuum plumes more reasonably and accurately than the Simons model. Comparisons of different drag coefficients show that Loth's drag formula can calculate exactly particle initial acceleration process for high Rer and Mr two-phase flows. The response characteristics of particles along their motion paths are further analyzed. Smaller particles can easily reach momentum equilibrium, while larger ones accelerate very difficultly. The thermal response is more relaxed than momentum response for different particle sizes. The present study is guidable to consider the effects of two-phase plumes on spacecraft in engineering

Key clinical studies on changing clinical practice of advanced breast cancer in 2022

With the improvement of comprehensive treatment of breast cancer and the continuous development of anti-tumor drugs, the survival time of breast cancer patients, especially advanced breast cancer, has been further extended. In recent years, the treatment of advanced breast cancer has ushered an era of fine classification and precise tiered therapy. In 2022, many breakthroughs have been made in the field of advanced breast cancer research. With changes in the treatment of each subtype, some treatment schemes affecting clinical practice have been incorporated into treatment guidelines. The treatment for hormone-receptor-positive advanced breast cancer focuses on patients who have failed treatment with cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors. Novel anti-human epidermal growth factor receptor 2 (HER2) antibody-drug conjugates (ADC) in advanced HER2 positive breast cancer are the focus of research. More research evidence is needed for immunotherapy in advanced triple-negative breast cancer (TNBC), and the treatment with ADC targeting Trop-2 has been effective. Treatment with ADC in HER2-low breast cancer are changing clinical practice. In this article, we summarized the research progress of different types of advanced breast cancer in this year, in order to better guide the individualized treatment and improve the prognosis of advanced breast cancer patients

The spectrum of low-pTp_{T} J/ψJ/\psi in heavy ion collisions in a fractal description

Transverse momentum spectrum of particles in hadron gas are affected by flow, quantum and strong interaction effects. Previously, most models focus on only one of the three effects but ignore others. The unconsidered effects are taken into the fitted parameters. In this paper, we study the three effects together from a new fractal angle by physical calculation instead of data fitting. Near the critical temperature, the three effects induce $J/\psi$ and neighboring meson to form a two-meson structure. We set up a two-particle fractal (TPF) model to describe this structure. We propose that under the three effects, $J/\psi$-$\pi$ two-meson state, $J/\psi$ and $\pi$ two-quark states form a self-similarity structure. With evolution, the two-meson structure disintegrate. We introduce an influencing factor $q_{fqs}$ to describe the flow, quantum and strong interaction effects and an escort factor $q_2$ to describe the binding force and the three effects. By solving the probability and entropy equations, we obtain the values of $q_{fqs}$ and $q_2$ at different collision energies and centrality classes. By substituting the value of $q_{fqs}$ into distribution function, we obtain the transverse momentum spectrum of low-$p_T$ $J/\psi$ and find it in good agreement with experimental data. We also analyze the evolution of $q_{fqs}$ with the temperature. It is found that $q_{fqs}$ is larger than 1. This is because the three effects decrease the number of microstates. We also find $q_{fqs}$ decreases with decreasing the temperature. This is consistent with the fact that with the system expansion, the influence of the three effects decrease.Comment: 9 pages, 3 figure

3D Cinemagraphy from a Single Image

We present 3D Cinemagraphy, a new technique that marries 2D image animation with 3D photography. Given a single still image as input, our goal is to generate a video that contains both visual content animation and camera motion. We empirically find that naively combining existing 2D image animation and 3D photography methods leads to obvious artifacts or inconsistent animation. Our key insight is that representing and animating the scene in 3D space offers a natural solution to this task. To this end, we first convert the input image into feature-based layered depth images using predicted depth values, followed by unprojecting them to a feature point cloud. To animate the scene, we perform motion estimation and lift the 2D motion into the 3D scene flow. Finally, to resolve the problem of hole emergence as points move forward, we propose to bidirectionally displace the point cloud as per the scene flow and synthesize novel views by separately projecting them into target image planes and blending the results. Extensive experiments demonstrate the effectiveness of our method. A user study is also conducted to validate the compelling rendering results of our method.Comment: Accepted by CVPR 2023. Project page: https://xingyi-li.github.io/3d-cinemagraphy

Flexibly-oriented double Cdc45-MCM-GINS intermediates during eukaryotic replicative helicase maturation

The core of the eukaryotic helicase MCM is loaded as an inactive double hexamer (DH). How it is assembled into two active Cdc45-MCM-GINS (CMG) helicases remains elusive. Here, we report that at the onset of S phase, both Cdc45 and GINS are loaded as dimers onto MCM DH, resulting in formation of double CMG (d-CMG). As S phase proceeds, d-CMGs gradually mature into two single CMG-centered replisome progression complexes (RPCs). Mass spectra reveal that RPA and DNA Pol α/primase co-purify exclusively with RPCs, but not with d-CMGs. Consistently, d-CMGs are not able to catalyze either the unwinding or de novo DNA synthesis, while RPCs can do both. Using single-particle electron microscopy, we have obtained 2D class averages of d-CMGs. Compared to MCM DHs, they display heterogeneous, flexibly orientated and partially loosened conformations with changed interfaces. The dumbbell-shaped d-CMGs are mediated by Ctf4, while other types of d-CMGs are independent of Ctf4. These data suggest CMG dimers as bona fide intermediates during MCM maturation, providing an additional quality control for symmetric origin activation and bidirectional replication

PIT: Optimization of Dynamic Sparse Deep Learning Models via Permutation Invariant Transformation

Dynamic sparsity, where the sparsity patterns are unknown until runtime, poses a significant challenge to deep learning. The state-of-the-art sparsity-aware deep learning solutions are restricted to pre-defined, static sparsity patterns due to significant overheads associated with preprocessing. Efficient execution of dynamic sparse computation often faces the misalignment between the GPU-friendly tile configuration for efficient execution and the sparsity-aware tile shape that minimizes coverage wastes (non-zero values in tensor). In this paper, we propose PIT, a deep-learning compiler for dynamic sparsity. PIT proposes a novel tiling mechanism that leverages Permutation Invariant Transformation (PIT), a mathematically proven property, to transform multiple sparsely located micro-tiles into a GPU-efficient dense tile without changing the computation results, thus achieving both high GPU utilization and low coverage waste. Given a model, PIT first finds feasible PIT rules for all its operators and generates efficient GPU kernels accordingly. At runtime, with the novel SRead and SWrite primitives, PIT rules can be executed extremely fast to support dynamic sparsity in an online manner. Extensive evaluation on diverse models shows that PIT can accelerate dynamic sparsity computation by up to 5.9x (average 2.43x) over state-of-the-art compilers

Synthesis and antiviral activities of a novel class of thioflavone and flavonoid analogues

AbstractA novel class of thioflavone and flavonoid derivatives has been prepared and their antiviral activities against enterovirus 71 (EV71) and the coxsackievirus B3 (CVB3) and B6 (CVB6) were evaluated. Compounds 7d and 9b showed potent antiviral activities against EV71 with IC50 values of 8.27 and 5.48μM, respectively. Compound 7f, which has been synthesized for the first time in this work, showed the highest level of inhibitory activity against both CVB3 and CVB6 with an IC50 value of 0.62 and 0.87μM. Compounds 4b, 7a, 9c and 9e also showed strong inhibitory activities against both the CVB3 and CVB6 at low concentrations (IC50=1.42−7.15μM), whereas compounds 4d, 7c, 7e and 7g showed strong activity against CVB6 (IC50=2.91–3.77μM) together with low levels of activity against CVB3. Compound 7d exhibited stronger inhibitory activity against CVB3 (IC50=6.44μM) than CVB6 (IC50>8.29μM). The thioflavone derivatives 7a, 7c, 7d, 7e, 7f and 7g, represent a new class of lead compounds for the development of novel antiviral agents

Wafer-Size and Single-Crystal MoSe_2 Atomically Thin Films Grown on GaN Substrate for Light Emission and Harvesting

Two-dimensional (2D) atomic-layered semiconductors are important for next-generation electronics and optoelectronics. Here, we designed the growth of an MoSe_2 atomic layer on a lattice-matched GaN semiconductor substrate. The results demonstrated that the MoSe_2 films were less than three atomic layers thick and were single crystalline of MoSe_2 over the entire GaN substrate. The ultrathin MoSe_2/GaN heterojunction diode demonstrated ∼850 nm light emission and could also be used in photovoltaic applications