Correlations of flow harmonics in 2.76A TeV Pb--Pb collisions

Using the event-by-event viscous hydrodynamics VISH2+1 with MC-Glauber, MC-KLN, and AMPT initial conditions, we investigate the correlations of flow harmonics, including the symmetric cumulants $SC^{v}(m, n)$, the normalized symmetric cumulants $NSC(m, n)$, and the Pearson correlation coefficients $C(v_{m}^{2}, v_{n}^{2})$ in 2.76A TeV Pb--Pb collisions. We find $SC^{v}(m, n)$ is sensitive to both initial conditions and the specific shear viscosity $\eta/s$. A comparison with the recent ALICE data show that our hydrodynamic calculations can qualitatively describe the data of $SC^{v}(3, 2)$ and $SC^{v}(4, 2)$ for various initial conditions, which demonstrate that $v_2$, $v_4$ are correlated and $v_2$, $v_3$ are anti-correlated. Meanwhile, the predicted symmetric cumulants $SC^{v}(5, 2)$, $SC^{v}(5, 3)$, and $SC^{v}(4, 3)$ reveal that $v_2$ and $v_5$, $v_3$ and $v_5$ are correlated, $v_3$ and $v_4$ are anti-correlated in most centrality classes. We also find $NSC^{v}(3, 2)$ and $C(v_{3}^{2}, v_{2}^{2})$, which are insensitive to $\eta/s$, are mainly determined by corresponding $NSC^{\varepsilon}(3, 2)$ and $C(\varepsilon_{3}^{2}, \varepsilon_{2}^{2})$ correlators from the initial state. In contrast, other $NSC^{v}(m, n)$ and $C(v_{m}^{2}, v_{n}^{2})$ correlators are influenced by both initial conditions and $\eta/s$, which illustrates the non-linear mode couplings in higher flow harmonics with $n \geq 4$.Comment: 10 pages, 7 figure

Investigating the correlations of flow harmonics in 2.76A TeV Pb--Pb collisions

This proceeding briefly summarizes our recent investigations on the correlations of flow harmonics in 2.76A TeV Pb--Pb collisions with viscous hydrodynamics {\tt VISH2+1}. We calculated both the symmetric cumulants $SC^{v}(m, n)$ and the normalized symmetric cumulants $NSC^{v}(m, n)$, and found $v_{2}$ and $v_{4}$, $v_{2}$ and $v_{5}$, $v_{3}$ and $v_{5}$ are correlated, $v_{2}$ and $v_{3}$, $v_{3}$ and $v_{4}$ are anti-correlated. We also found $NSC^{v}(3, 2)$ are insensitive to the QGP viscosity, which are mainly determined by the initial conditions.Comment: SQM2016 proceeding, 4pages, 2 figure

Zinc-Dependent Oligomerization of Thermus thermophilus Trigger Factor Chaperone

Metal ions often play important roles in biological processes. Thermus thermophilus trigger factor (TtTF) is a zinc-dependent molecular chaperone where Zn2+ has been shown to enhance its folding-arrest activity. However, the mechanisms of how Zn2+ binds to TtTF and how Zn2+ affects the activity of TtTF are yet to be elucidated. As a first step in understanding the mechanism, we performed in vitro biophysical experiments on TtTF to investigate the zinc-binding site on TtTF and unveil how Zn2+ alters the physical properties of TtTF, including secondary structure, thermal stability, and oligomeric state. Our results showed that TtTF binds Zn2+ in a 1:1 ratio, and all three domains of TtTF are involved in zinc-binding. We found that Zn2+ does not affect the thermal stability of TtTF, whereas it does induce partial structural change and promote the oligomerization of TtTF. Given that the folding-arrest activity of Escherichia coli TF (EcTF) is regulated by its oligomerization, our results imply that TtTF exploits Zn2+ to modulate its oligomeric state to regulate the activity.Thermus thermophilus trigger factor (TtTF) is a zinc-dependent molecular chaperone whose folding-arrest activity is regulated by Zn2+. However, little is known about the mechanism of zinc-dependent regulation of the TtTF activity. Here we exploit in vitro biophysical experiments to investigate zinc-binding, the oligomeric state, the secondary structure, and the thermal stability of TtTF in the absence and presence of Zn2+. The data show that full-length TtTF binds Zn2+, but the isolated domains and tandem domains of TtTF do not bind to Zn2+. Furthermore, circular dichroism (CD) and nuclear magnetic resonance (NMR) spectra suggested that Zn2+-binding induces the partial structural changes of TtTF, and size exclusion chromatography-multi-angle light scattering (SEC-MALS) showed that Zn2+ promotes TtTF oligomerization. Given the previous work showing that the activity regulation of E. coli trigger factor is accompanied by oligomerization, the Data suggest that TtTF exploits zinc ions to induce the structural change coupled with the oligomerization to assemble the client-binding site, thereby effectively preventing proteins from misfolding in the thermal environment

Fine-Tuning Pre-Trained Language Models Effectively by Optimizing Subnetworks Adaptively

Large-scale pre-trained language models have achieved impressive results on a wide range of downstream tasks recently. However, fine-tuning an extremely large-scale pre-trained language model on limited target datasets is often plagued by overfitting and representation degradation. In this paper, we propose a Dynamic Parameter Selection (DPS) algorithm for the large-scale pre-trained models during fine-tuning, which adaptively selects a more promising subnetwork to perform staging updates based on gradients of back-propagation. Experiments on the GLUE benchmark show that DPS outperforms previous fine-tuning methods in terms of overall performance and stability, and consistently achieves better results with variable pre-trained language models. In addition, DPS brings a large magnitude of improvement in out-of-domain transferring experiments and low-resource scenarios, which shows that it can maintain stable general contextual features and reduce the representation collapse. We release our code at https://github.com/ZhangHaojie077/DPSComment: NeurIPS 202

Operating characteristics study of a dual-opposed free-piston Stirling generator

Dual-opposed Free-piston Stirling generators (dual-opposed FPSGs) offer advantages of reduced vibration and increased power density, making them promising candidates for space and distributed energy applications. So far, operational characteristics of the dual-opposed FPSG have yet to be completely understood. This study focuses on a 3 kW dual-opposed FPSG prototype designed to integrate heat pipes. Through computational fluid dynamics and thermoacoustic analysis, a novel hot end heat exchanger with evenly-distributed heat pipe bore was discovered to deliver 12 kW heating power with a gas–solid temperature difference of 21 K. Subsequently effort combined thermoacoustically-based calculations with experiments to investigate the impact of two electrical connection methods of linear alternators on FPSG performance. Experimental results validated the numerical model, showing heat-to-electricity efficiency deviations within 5 % under different electrical connection modes. The FPSG consistently achieved its rated power in both series and parallel connection modes, exhibiting a thermal-to-electric efficiency of 25.2 %. Notably, the series connection mode demonstrates superior sensitivity and consistency compared to parallel connection. Further experiments revealed that charge pressure, load resistance and external capacitance all exerts limited impact on the consistency, while external capacitance significantly influenced acoustic impedance. This resulted in an enhancement in both hot-end wall temperature and heat-to-electricity efficiency, while minimizing power piston displacement and damping temperature when resonating with the inductance

JNK pathway promotes hepatocyte apoptosis by inhibiting Bcl-2 and upregulating expressions of Bim, caspase-3 and caspase-9 after cardiopulmonary bypass

Purpose: To study the effect of Jun N-terminal kinase (JNK) signaling pathway on hepatocyte apoptosis in vivo and in vitro, and to elucidate the mechanism of action. Methods: TdT-mediated dUTP Nick-End Labeling (TUNEL) method was used to determine apoptosis in control and cardiopulmonary bypass (CPB) groups at 0, 3 and 6 hours after rat surgery. The expressions of JNK and p-c-Jun in liver tissues at 0, 3 and 6 h after surgery, and the levels of p-c-Jun, Bcl-2 and Bim following overexpression of JNK, were determined using Western blot assay. Human liver cell line HL-7702 was cultured and transfected with over-expressed JNK plasmid and empty plasmid. Proliferation of HL-7702 cells after JNK over-expression was assessed by Cell Counting Kit-8 (CCK-8), while quantitative real-time polymerase chain reaction (RT-qPCR) was employed to evaluate mRNA expression levels of caspase-3 and caspase-9 mRNA after JNK over-expression. Apoptosis of the cells was determined by flow cytometry (FC) after JNK over-expression. Results: FC results showed that the number of apoptotic hepatocytes increased after JNK overexpression in hepatocytes while TUNEL assay results demonstrated that hepatocyte apoptosis increased in CPB group, when compared to control group; furthermore, the number of apoptotic cells gradually increased within 6 h after surgery. The expressions of JNK and p-c-Jun were higher in CPB group than in control group, and increased gradually in both groups within 6 h after surgery. Overexpression of JNK decreased the proliferation of hepatocytes, and also lowered protein expression levels of p-c-Jun and Bim; on the other hand, the protein expression levels of Bcl-2 fell, while mRNA expression levels of caspase-3 and caspase-9 mRNA increased. Conclusion: JNK pathway promotes hepatocyte apoptosis after cardiopulmonary bypass by inhibiting Bcl-2 pathway and promoting the expressions of Bim caspase-3 and caspase-9. Keywords: Cardiopulmonary bypass, Apoptosis, JNK pathway, Bim, caspase-3 and caspase-

A Dataset And Benchmark Of Underwater Object Detection For Robot Picking

Underwater object detection for robot picking has attracted a lot of interest. However, it is still an unsolved problem due to several challenges. We take steps towards making it more realistic by addressing the following challenges. Firstly, the currently available datasets basically lack the test set annotations, causing researchers must compare their method with other SOTAs on a self-divided test set (from the training set). Training other methods lead to an increase in workload and different researchers divide different datasets, resulting there is no unified benchmark to compare the performance of different algorithms. Secondly, these datasets also have other shortcomings, e.g., too many similar images or incomplete labels. Towards these challenges we introduce a dataset, Detecting Underwater Objects (DUO), and a corresponding benchmark, based on the collection and re-annotation of all relevant datasets. DUO contains a collection of diverse underwater images with more rational annotations. The corresponding benchmark provides indicators of both efficiency and accuracy of SOTAs (under the MMDtection framework) for academic research and industrial applications, where JETSON AGX XAVIER is used to assess detector speed to simulate the robot-embedded environment

Numerical simulation analysis of PELE penetrating target plates with different thicknesses

PELE (Penetrator with Enhanced Later Effect) is a new type of ammunition, which does not need to be filled with explosives and fuses, but has the function of armor piercing projectile and grenade at the same time. The numerical simulation of a 60 mm diameter PELE penetrating target was investigated. The results show that in the process of the target plate becoming thicker, the transverse effect first increases and then weakens, and the optimal target plate thickness range is 4-6 cm; the properties of the core material have an important influence on the transverse effect of PELE; with the increase of the core radius, the radial velocity of the fragments after PELE penetrating the target first increases, then decreases and then increases, and the optimal core radius is 2-2.6 cm

Learned Point Cloud Geometry Compression

This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a.k.a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep neural networks (DNN) based variational autoencoders (VAE). In our approach, PCG is first voxelized, scaled and partitioned into non-overlapped 3D cubes, which is then fed into stacked 3D convolutions for compact latent feature and hyperprior generation. Hyperpriors are used to improve the conditional probability modeling of latent features. A weighted binary cross-entropy (WBCE) loss is applied in training while an adaptive thresholding is used in inference to remove unnecessary voxels and reduce the distortion. Objectively, our method exceeds the geometry-based point cloud compression (G-PCC) algorithm standardized by well-known Moving Picture Experts Group (MPEG) with a significant performance margin, e.g., at least 60% BD-Rate (Bjontegaard Delta Rate) gains, using common test datasets. Subjectively, our method has presented better visual quality with smoother surface reconstruction and appealing details, in comparison to all existing MPEG standard compliant PCC methods. Our method requires about 2.5MB parameters in total, which is a fairly small size for practical implementation, even on embedded platform. Additional ablation studies analyze a variety of aspects (e.g., cube size, kernels, etc) to explore the application potentials of our learned-PCGC.Comment: 13 page