The Nonlinear Spatial Damping Rate in QGP

The derivative expansion method has been used to solve the semiclassical kinetic equations of quark-gluon plasma (QGP). The nonlinear spatial damping rate, the imaginary part of the wave vector, for the longitudinal secondary color waves in the long wavelength limit has been calculated numerically.Comment: 11 page

A Squeeze-and-Excitation and Transformer based Cross-task System for Environmental Sound Recognition

Environmental sound recognition (ESR) is an emerging research topic in audio pattern recognition. Many tasks are presented to resort to computational systems for ESR in real-life applications. However, current systems are usually designed for individual tasks, and are not robust and applicable to other tasks. Cross-task systems, which promote unified knowledge modeling across various tasks, have not been thoroughly investigated. In this paper, we propose a cross-task system for three different tasks of ESR: acoustic scene classification, urban sound tagging, and anomalous sound detection. An architecture named SE-Trans is presented that uses attention mechanism-based Squeeze-and-Excitation and Transformer encoder modules to learn channel-wise relationship and temporal dependencies of the acoustic features. FMix is employed as the data augmentation method that improves the performance of ESR. Evaluations for the three tasks are conducted on the recent databases of DCASE challenges. The experimental results show that the proposed cross-task system achieves state-of-the-art performance on all tasks. Further analysis demonstrates that the proposed cross-task system can effectively utilize acoustic knowledge across different ESR tasks

SSDPT: Self-Supervised Dual-Path Transformer for Anomalous Sound Detection in Machine Condition Monitoring

Anomalous sound detection for machine condition monitoring has great potential in the development of Industry 4.0. However, these anomalous sounds of machines are usually unavailable in normal conditions. Therefore, the models employed have to learn acoustic representations with normal sounds for training, and detect anomalous sounds while testing. In this article, we propose a self-supervised dual-path Transformer (SSDPT) network to detect anomalous sounds in machine monitoring. The SSDPT network splits the acoustic features into segments and employs several DPT blocks for time and frequency modeling. DPT blocks use attention modules to alternately model the interactive information about the frequency and temporal components of the segmented acoustic features. To address the problem of lack of anomalous sound, we adopt a self-supervised learning approach to train the network with normal sound. Specifically, this approach randomly masks and reconstructs the acoustic features, and jointly classifies machine identity information to improve the performance of anomalous sound detection. We evaluated our method on the DCASE2021 task2 dataset. The experimental results show that the SSDPT network achieves a significant increase in the harmonic mean AUC score, in comparison to present state-of-the-art methods of anomalous sound detection

Two-stage Autoencoder Neural Network for 3D Speech Enhancement

3D speech enhancement has attracted much attention in recent years with the development of augmented reality technology. Traditional denoising convolutional autoencoders have limitations in extracting dynamic voice information. In this paper, we propose a two-stage autoencoder neural network for 3D speech enhancement. We incorporate a dual-path recurrent neural network block into the convolutional autoencoder to iteratively apply time-domain and frequency-domain modeling in an alternate fashion. And an attention mechanism for fusing the high-dimension features is proposed. We also introduce a loss function to simultaneously optimize the network in the time-frequency and time domains. Experimental results show that our system outperforms the state-of-the-art systems on the dataset of ICASSP L3DAS23 challenge.Comment: 5 pages,5 figure

Separate DOD and DOA Estimation for Bistatic MIMO Radar

A novel MUSIC-type algorithm is derived in this paper for the direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic MIMO radar. Through rearranging the received signal matrix, we illustrate that the DOD and the DOA can be separately estimated. Compared with conventional MUSIC-type algorithms, the proposed separate MUSIC algorithm can avoid the interference between DOD and DOA estimations effectively. Therefore, it is expected to give a better angle estimation performance and have a much lower computational complexity. Meanwhile, we demonstrate that our method is also effective for coherent targets in MIMO radar. Simulation results verify the efficiency of the proposed method, particularly when the signal-to-noise ratio (SNR) is low and/or the number of snapshots is small

Three-dimensional correlated-fermion phase separation from analysis of the geometric mean of the individual susceptibilities

A quasi-Gaussian approximation scheme is formulated to study the strongly correlated imbalanced fermions thermodynamics, where the mean-field theory is not applicable. The non-Gaussian correlation effects are understood to be captured by the statistical geometric mean of the individual susceptibilities. In the three-dimensional unitary fermions ground state, an {\em universal} non-linear scaling transformation relates the physical chemical potentials with the individual Fermi kinetic energies. For the partial polarization phase separation to full polarization, the calculated critical polarization ratio is $P_C={[1-(1-\xi)^{6/5}]}/{[1+(1-\xi)^{6/5}]}\doteq 0.34$. The $\xi=4/9$ defines the ratio of the symmetric ground state energy density to that of the ideal fermion gas.Comment: Minor changes with typos correcte

Comparison of the efficacy and safety of 10 glucagon-like peptide-1 receptor agonists as add-on to metformin in patients with type 2 diabetes: a systematic review

PurposeThis study aimed to perform a network meta-analysis to objectively evaluate the efficacy and safety of 10 Glucagon-like peptide-1 receptor agonists (GLP-1RAs) in combination with metformin that is approved for use worldwide in patients with type 2 diabetes and to provide evidence-based support and reference for the selection of clinical treatment.MethodsThree databases (PubMed, Embase, and Cochrane Library) were searched from their respective inception until September 30, 2022. Only randomized controlled trials comparing the efficacy and safety of GLP-1RAs for treating type 2 diabetes (T2D) were included. The 10 GLP-1RAs are exenatide (including exenatide twice daily and once weekly), liraglutide, lixisenatide, dulaglutide, PEX168, semaglutide (subcutaneous and oral semaglutide), tirzepatide and albiglutide.Results34 RCTs with 10 GLP-1RAs and 12993 patients were included in the Network Meta-Analysis (NMA). According to the NMA, tirzepatide 15 mg, semaglutide 1.0 mg, PEX168-200μg, oral semaglutide 14 and dulaglutide 1.5 mg reduced HbA1c by -2.23%, -1.57%, -1.12%, -1.10%, -1.09% and body weight by -11.33 kg, -5.99 kg, +0.40 kg, -3.95 kg, -1.87 kg, respectively. There was no significant difference in the rate of adverse events for tirzepatide 15 mg, oral-semaglutide 14 mg, and semaglutide 1.0 mg. PEX168-200μg, tirzepatide 15mg, and oral semaglutide 14mg had Surface Under the Cumulative Ranking (SUCRA) values greater than placebo, and only tirzepatide 15mg and oral semaglutide 14mg were significantly different from placebo in the rate of serious adverse events. All GLP-1RA did not lead to increased incidence of hypoglycemia. Albiglutide 30mg and semaglutide 1.0mg significantly differed from placebo in Adverse Event (AE) withdrawal. Finally, the sensitivity analysis and publication bias analysis results indicate that the study results are reliable.ConclusionThis study’s results showed that GLP-1RAs were effective in lowering HbA1c and reducing body weight without increased incidence of hypoglycemic reactions. In addition, this study may provide reference and evidence-based medical evidence for clinicians to select GLP-1RAs in patients with T2D and high body mass index (BMI). Based on the NMA results, tirzepatide 15mg and semaglutide 1.0mg may be preferred

A ROP GTPase-Dependent Auxin Signaling Pathway Regulates the Subcellular Distribution of PIN2 in Arabidopsis Roots

SummaryPIN-FORMED (PIN) protein-mediated auxin polar transport is critically important for development, pattern formation, and morphogenesis in plants. Auxin has been implicated in the regulation of polar auxin transport by inhibiting PIN endocytosis [1, 2], but how auxin regulates this process is poorly understood. Our genetic screen identified the Arabidopsis SPIKE1 (SPK1) gene whose loss-of-function mutations increased lateral root density and retarded gravitropic responses, as do pin2 knockout mutations [3]. SPK1 belongs to the conserved DHR2-Dock family of Rho guanine nucleotide exchange factors [4–6]. The spk1 mutations induced PIN2 internalization that was not suppressed by auxin, as did the loss-of-function mutations for Rho-like GTPase from Plants 6 (ROP6)-GTPase or its effector RIC1. Furthermore, SPK1 was required for auxin induction of ROP6 activation. Our results have established a Rho GTPase-based auxin signaling pathway that maintains PIN2 polar distribution to the plasma membrane via inhibition of its internalization in Arabidopsis roots. Our findings provide new insights into signaling mechanisms that underlie the regulation of the dynamic trafficking of PINs required for long-distance auxin transport and that link auxin signaling to PIN-mediated pattern formation and morphogenesis

Lymphatic impairment leads to pulmonary tertiary lymphoid organ formation and alveolar damage

The lung is a specialized barrier organ that must tightly regulate interstitial fluid clearance and prevent infection in order to maintain effective gas exchange. Lymphatic vessels are important for these functions in other organs, but their roles in the lung have not been fully defined. In the present study, we addressed how the lymphatic vasculature participates in lung homeostasis. Studies using mice carrying a lymphatic reporter allele revealeded that, in contrast to other organs, lung lymphatic collecting vessels lack smooth muscle cells entirely, suggesting that forward lymph flow is highly dependent on movement and changes in pressure associated with respiration. Functional studies using CLEC2-deficient mice in which lymph flow is impaired due to loss of lympho-venous hemostasis or using inducible lung-specific ablation of lymphatic endothelial cells in a lung transplant model revealeded that loss of lymphatic function leads to an inflammatory state characterized by the formation of tertiary lymphoid organs (TLOs). In addition, impaired lymphatic flow in mice resulteds in hypoxia and features of lung injury that resemble emphysema. These findings reveal both a lung-specific mechanism of lymphatic physiology and a lung-specific consequence of lymphatic dysfunction that may contribute to chronic lung diseases that arise in association with TLO formation