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

Molecular Dynamics Simulation Insights into Rejuvenating Aged Asphalt with Waste Soybean Oil and Polymers

This study utilized molecular dynamics simulations to assess the rejuvenation of aged asphalt (AA) with waste soybean oil (WSO) and functionalized SBS polymers, focusing on: 1) constructing and validating models for virgin asphalt (VA), AA, and composite rejuvenated asphalt with WSO and polymers; 2) analyzing diffusion effects and binding abilities in these rejuvenated models; 3) evaluating interface binding and diffusion behaviors in composite rejuvenated models. The addition of functionalized SBS molecules and WSO improved the diffusion rates of various components within these models. Specifically, functionalized linear-SBS (LSBS) molecules demonstrated superior diffusion performance compared to star-SBS (SSBS) molecules. Incorporating WSO and polymers into the AA model increased the occupied volume of all rejuvenated models. The free volume fraction (FFV) in rejuvenated asphalt models exceeded that in AA at 433 K, suggesting that the inclusion of WSO and polymers enhances molecular mobility. As temperature increased, the interaction energy between polymers and asphalt components decreased. LSBS molecules exhibited stronger interactions with asphalt components than SSBS molecules, whose interaction energy was significantly enhanced by hydrogenation treatment. In rejuvenated-rejuvenated asphalt models, the interface interaction energy was higher than in VA–VA models, suggesting improved interface stability. However, diffusion rates of various components in rejuvenated-rejuvenated asphalt models were lower than those in VA–VA models

Amplicon sequencing reveals different microbial communities between growing and non-growing seasons in the soils of Pinus armandi forestland in Shennongjia, China

Soil microbial communities are susceptible to climate change due to seasonal alternation. To explore the effects of seasonal variation on soil nutrients and microorganisms, we sequenced the 16S rDNA and 18S rDNA genes of the distinct regions (16S V3-V4, 18S V4) to precisely identify the soil microbial communities in the growing season (Par_S) and non-growing season (Par_W) in Pinus armandi forestland, in Shennongjia forest region, China. Eight chemical properties of the soil samples were also determined to elucidate the correlations between the microbial communities and soil characteristics. In Par_S, we identified 36 phyla 348 genera of bacteria, and 58 phyla 197 genera fungi. Par_W’s corresponding values were 39 phyla 471 genera and 59 phyla 259 genera, respectively. Par_S owned more abundant bacterial communities than Par_W. The relative abundance of most bacteria and fungi differed significantly between Par_S and Par_W.  Most of the top 35 abundant bacterial genera and fungal genera were enriched in Par_S and Par_W, respectively. The soil properties differed significantly between Par_S and Par_W. They were significantly correlated with the variations in the relative abundance of the top 10 bacterial and fungal genera in both Par_S and Par_W. Rokubacteriales and RB41 were dominant among Par_S’s top 10 bacterial genera, and were related to the RR of the soil. Sphingomonas was dominant among Par_W’s top 10 bacterial genera. Magnoliophyta, Haplotaxida and Acari were dominant among Par_S’s top 10 fungal genera, and were related to RR, TK, HN, TP and AP. Archaeorhizomyces was dominant among Par_W’s top 10 bacterial genera. For the top 10 abundant bacterial genera in Par_S, the relative abundance of Nitrospira was negatively correlated with the contents of TN and AK, and MND1 was negatively correlated with SOM. Regarding the top 10 abundant bacterial genera in Par_W, SBR1031 was positively correlated with TP and AP, and MND1 was positively correlated with AP. Regarding the top 10 abundant fungal genera in Par_S, only Acari had a positive correlation with TK

CFD-Based Analysis of Wedges Water Entry under Impact Loads

1053-1056The impact on a falling wedge upon water entry is numerically investigated in this paper. After verified by experimental data, the numerical framework is applied for parametric studies on wedges of different drop heights and different deadrise angles to reveal the interaction behaviour between the wedge and water during impact. Pressure distribution on the wedge surface during the water entry shows that the pressure peak moves up along the surface as impact time increases. It is found that the force peak decrease with the increase of drop height and decrease of deadrise angle of the wedge. The peak positions move positively along the timeline as the increase of deadrise angle while the peak force appears just in a small impact time range for a wedge

Not All Metrics Are Guilty: Improving NLG Evaluation with LLM Paraphrasing

Most research about natural language generation (NLG) relies on evaluation benchmarks with limited references for a sample, which may result in poor correlations with human judgements. The underlying reason is that one semantic meaning can actually be expressed in different forms, and the evaluation with a single or few references may not accurately reflect the quality of the model's hypotheses. To address this issue, this paper presents a novel method, named Para-Ref, to enhance existing evaluation benchmarks by enriching the number of references. We leverage large language models (LLMs) to paraphrase a single reference into multiple high-quality ones in diverse expressions. Experimental results on representative NLG tasks of machine translation, text summarization, and image caption demonstrate that our method can effectively improve the correlation with human evaluation for sixteen automatic evaluation metrics by +7.82% in ratio. We release the code and data at https://github.com/RUCAIBox/Para-Ref

Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models

Large language models (LLMs) demonstrate remarkable multilingual capabilities without being pre-trained on specially curated multilingual parallel corpora. It remains a challenging problem to explain the underlying mechanisms by which LLMs process multilingual texts. In this paper, we delve into the composition of Transformer architectures in LLMs to pinpoint language-specific regions. Specially, we propose a novel detection method, language activation probability entropy (LAPE), to identify language-specific neurons within LLMs. Based on LAPE, we conduct comprehensive experiments on several representative LLMs, such as LLaMA-2, BLOOM, and Mistral. Our findings indicate that LLMs' proficiency in processing a particular language is predominantly due to a small subset of neurons, primarily situated in the models' top and bottom layers. Furthermore, we showcase the feasibility to "steer" the output language of LLMs by selectively activating or deactivating language-specific neurons. Our research provides important evidence to the understanding and exploration of the multilingual capabilities of LLMs.Comment: Accepted by ACL 202

Semi-classical solutions of perturbed elliptic system with general superlinear nonlinearity

Abstract This paper is concerned with the following perturbed elliptic system: − ε 2 △ u + V ( x ) u = W v ( x , u , v ) , x ∈ R N , − ε 2 △ v + V ( x ) v = W u ( x , u , v ) , x ∈ R N , u , v ∈ H 1 ( R N ) , where V ∈ C ( R N , R ) and W ∈ C 1 ( R N × R 2 , R ) . Under some mild conditions on the potential V and nonlinearity W, we establish the existence of nontrivial semi-classical solutions via variational methods, provided that 0 &lt; ε ≤ ε 0 , where the bound ε 0 is formulated in terms of N, V, and W. MSC: 35J10, 35J20.</jats:p

Pyramiding stacking of multigenes (PSM): a simple, flexible and efficient multigene stacking system based on Gibson assembly and gateway cloning

Genetic engineering of complex metabolic pathways and multiple traits often requires the introduction of multiple genes. The construction of plasmids carrying multiple DNA fragments plays a vital role in these processes. In this study, the Gibson assembly and Gateway cloning combined Pyramiding Stacking of Multigenes (PSM) system was developed to assemble multiple transgenes into a single T-DNA. Combining the advantages of Gibson assembly and Gateway cloning, the PSM system uses an inverted pyramid stacking route and allows fast, flexible and efficient stacking of multiple genes into a binary vector. The PSM system contains two modular designed entry vectors (each containing two different attL sites and two selectable markers) and one Gateway-compatible destination vector (containing four attR sites and two negative selection markers). The target genes are primarily assembled into the entry vectors via two parallel rounds of Gibson assembly reactions. Then, the cargos in the entry constructs are integrated into the destination vector via a single tube Gateway LR reaction. To demonstrate PSM’s capabilities, four and nine gene expression cassettes were respectively assembled into the destination vector to generate two binary expression vectors. The transgenic analysis of these constructs in Arabidopsis demonstrated the reliability of the constructs generated by PSM. Due to its flexibility, simplicity and versatility, PSM has great potential for genetic engineering, synthetic biology and the improvement of multiple traits