Challenges in QCD matter physics - The Compressed Baryonic Matter experiment at FAIR

Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 (sqrt(s_NN) = 2.7 - 4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials (mu_B > 500 MeV), effects of chiral symmetry, and the equation-of-state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2022, in the context of the worldwide efforts to explore high-density QCD matter.Comment: 15 pages, 11 figures. Published in European Physical Journal

Efficient Ferrite-Based Perovskite Anode for Solid Oxide Fuel Cells with A-Site and B-Site Co-exsolution

Exsolution of A-site and/or B-site dopants has been widely used to improve the electroactivity and coking resistance of the perovskite anode for solid oxide fuel cells (SOFCs). Here, an A-site and B-site co-exsolved Ba0.3Sr0.7Fe0.9Mn0.1O3−δ (BSFM) perovskite is employed as the anode material of SOFCs. X-ray diffraction results confirm that the cubic BSFM perovskite shows reasonable structure stability in hydrogen, although metallic Fe and SrO exsolve from the provskite lattice. Scanning electron microscopy results find that a whisker-like species grows from the perovskite in addition to the exsolution of Fe nanoparticles. It is verified by transmission electron microscopy−energy-dispersive X-ray spectroscopy that the whisker is composed of BaO and SrO. The surface enrichment of Ba and Sr elements is also proven by X-ray photoelectron spectroscopy. The peak power densities of a single cell with the BSFM anode are 538 and 364 mW cm−2 at 800 and 750 °C in hydrogen, respectively, while the polarization resistances of them are 0.18 and 0.28 Ω cm2 at the same conditions, respectively. The cell operates stably for over 60 h in hydrogen with a current density of 0.2 A cm−2 . However, the BSFM anode shows sluggish activity for methane oxidation. With the addition of Ni to the BSFM anode, its activity for methane oxidation is remarkably improved, and the peak power density increases from 84 mW cm−2 for the BSFM anode to 194 mW cm−2 for the Ni−BSFM anode at 800 °C in methane. The Ni−BSFM anode also exhibits excellent stability in methane and works stably for over 70 h with a current density of 0.2 A cm−2

C-RISE: A Post-Hoc Interpretation Method of Black-Box Models for SAR ATR

The integration of deep learning methods, especially Convolutional Neural Networks (CNN), and Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has been widely deployed in the field of radar signal processing. Nevertheless, these methods are frequently regarded as black-box models due to the limited visual interpretation of their internal feature representation and parameter organization. In this paper, we propose an innovative approach named C-RISE, which builds upon the RISE algorithm to provide a post-hoc interpretation technique for black-box models used in SAR Images Target Recognition. C-RISE generates saliency maps that effectively visualize the significance of each pixel. Our algorithm outperforms RISE by clustering masks that capture similar fusion features into distinct groups, enabling more appropriate weight distribution and increased focus on the target area. Furthermore, we employ Gaussian blur to process the masked area, preserving the original image structure with optimal consistency and integrity. C-RISE has been extensively evaluated through experiments, and the results demonstrate superior performance over other interpretation methods based on perturbation when applied to neural networks for SAR image target recognition. Furthermore, our approach is highly robust and transferable compared to other interpretable algorithms, including white-box methods

Yangyin Qingre Huoxue Method in Traditional Chinese Medicine Ameliorates Atherosclerosis in ApoE−/− Mice Suffering from High-Fat Diet and HSP65 Aggression

Atherosclerosis (AS) is a complicated arterial disease resulting from abnormal lipid deposition and inflammatory injury, which is attributed to Yin deficiency, accumulation of heat materials, and stasis of blood flow in Traditional Chinese Medicine (TCM) theory. Thus, according to TCM theory, the method of nourishing Yin (Yangyin), clearing away heat (Qingre), and promoting blood circulation (Huoxue) is a reasonable strategy, which has achieved remarkable clinical efficacy in the treatment of AS, but the mechanisms remain to be known. In this study, we evaluated the effects of Yangyin Qingre Huoxue Prescription (YQHP) on AS in ApoE-/- mice suffering from a high-fat diet and heat shock protein (HSP65) attack. YQHP regulated levels of blood lipids and inflammation-linked cytokines as well as Th17/Treg ratio in peripheral blood. Suppressed IL-6-p-STAT3 signaling and restored IL-2-p-STAT5 signaling in the presence of YQHP may partake in the regulation of Th17 and Treg differentiation. Moreover, YQHP modulated transcriptional levels of costimulator CD80 in aortas as well corresponding to the downregulation of GM-CSF in serum and CD3 expression in CD4+ T cells, which might indicate the potential of YQHP to regulate antigen presenting cells. All these effects eventually promoted the improvement of atherosclerotic lesions. In addition, YQHP promoted less monocyte infiltration in the liver and lower levels of AST, ALT, and AKP production than simvastatin. Conclusively, lipid-regulating and anti-inflammatory functions mediated by YQHP with lower hepatotoxicity than simvastatin hindered the progression of HSP65 aggravated AS in ApoE-/- mice, indicating the effectiveness of Yangyin Qingre Huoxue Method in the treatment of AS

Flowability prediction of recycled α-hemihydrate gypsum for 3D powder printing under combined effects of different glidants using response surface methodology

In this study, a high-value-added recycled α-hemihydrate gypsum (α-RHG) generated from WGP using the atmospheric pressure hydrothermal method (APHM) was utilized to manufacture a 3D printed material. The univariate and combined effects of affordable and high-performance glidants, including hydrophobic nano-silica (HNS) and soluble starch (SS), on the flowability of α-RHG were evaluated experimentally and modelled. The results revealed that the flowability of α-RHG can be enhanced by the proper univariate addition of HNS (e.g., <1.0 wt%) or SS (e.g., <3.0 wt%). In addition, the experimental and modelling results based on central composite design (CCD) using response surface methodology have consistently demonstrated that the optimal flowability of α-RHG can be achieved by incorporating an optimum combined addition of 1.0 wt% HNS and 3.0 wt% SS. Finally, a 3D printed sample with a flow rate of 3.16 g/s using the modified α-RHG powder with optimum addition of HNS and SS was successfully produced

Behavior of Salmonella Typhimurium on Fresh Strawberries Under Different Storage Temperatures and Wash Treatments

Fresh strawberries are one of the most popular fruits in China and are vulnerable to microbial contamination. In this study, the behavior of Salmonella Typhimurium on fresh strawberries stored at refrigeration and room temperatures, as well as the effectiveness of mild heat wash treatments at 47, 50, and 53°C on bacterial survival was investigated. The modified Gompertz, Huang, log-linear, and Weibull models were used to fit bacterial growth and survival curves under different treatments. A secondary model based on linear regression was developed to describe the effect of washing temperature on the kinetic parameters of S. Typhimurium survival derived from the Weibull model. During 72 h storage, S. Typhimurium on fresh strawberries stored at 4°C was reduced by 1.35 log CFU/g and growth of 5.64 log CFU/g was observed when strawberries were stored at 25°C. Bacterial reductions of 1.22 ± 0.15, 1.92 ± 0.06, 2.27 ± 0.07 log CFU/g were obtained when washing was carried out at 47, 50 and 53°C for 240 s, respectively. The wash temperature was an important parameter for bacterial inactivation and bacterial populations declined significantly in conjunction with washing time (p &lt; 0.05). Warm wash treatments lead the visible color changes of strawberries, showing a slightly darker appearance while acceptable. The goodness-of-fit indices indicated that the log-linear model provided a satisfactory fit to describe the bacterial survival at 4°C. According to the smaller Akaike information criterion (AIC) value, the modified Gompertz model performed slightly better than the Huang model in describing bacterial growth at 25°C. The high adj-R2 (≥0.90) and small RMSE (≤0.22) indicated the Weibull model better described bacterial behavior under mild heat treatments. We found a close linear relationship between wash temperatures and ln k and ln n. These models were validated by independent experimental data and the values of the bias and accuracy factors fell into the acceptable range

Tribological Behaviors of Inconel 718&ndash;Tungsten Carbide Friction Pair with Sulfur Additive Lubrication

This work investigated the lubricating and anti-wear properties of several sulfur additives for a nickel-based superalloy&ndash;tungsten carbide friction pair. Compared with PAO40 without any active chemical compounds, the three kinds of sulfur additives could decrease the friction coefficient from 0.2 to 0.1 and the wear volume by 90%. Sulfurized fatty acid ester had the best performance under high temperature and heavy load with COF below 0.1 and the smallest wear volume. Furthermore, the lubricating mechanism was investigated by XPS. The physical adsorptive film and the tribochemical film together enhanced the friction-reducing and anti-wear performances of the lubricants. This effective lubricant for Inconel 718 can be applied to the machining of nickel-based alloy