F-wave heavy-light meson spectroscopy in QCD sum rules and heavy quark effective theory

We study the F-wave c_bar s heavy meson doublets (2+,3+) and (3+,4+). They have large orbital excitations L=3, and may be good challenges (tests) for theoretical studies. To study them we use the method of QCD sum rule in the framework of heavy quark effective theory. Their masses are predicted to be m_{(2+,3+)} = (3.45 \pm 0.25, 3.50 \pm 0.26) GeV and m_{(3+,4+)} = (3.20 \pm 0.22, 3.26 \pm 0.23) GeV, with mass splittings Delta m_{(2+,3+)} = m_{3+} - m_{2+} = 0.046 \pm 0.030 GeV and Delta m_{(3+,4+)} = 0.053 \pm 0.044 GeV, respectively. We note that this is a pioneering work and these results are provisional.Comment: 10 pages, 8 figures, 3 tables, accepted by PR

Information-Theoretic Measure of Genuine Multi-Qubit Entanglement

We consider pure quantum states of N qubits and study the genuine N-qubit entanglement that is shared among all the N qubits. We introduce an information-theoretic measure of genuine N-qubit entanglement based on bipartite partitions. When N is an even number, this measure is presented in a simple formula, which depends only on the purities of the partially reduced density matrices. It can be easily computed theoretically and measured experimentally. When N is an odd number, the measure can also be obtained in principle.Comment: 5 pages, 2 figure

ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models

Data-to-text generation is challenging due to the great variety of the input data in terms of domains (e.g., finance vs sports) or schemata (e.g., diverse predicates). Recent end-to-end neural methods thus require substantial training examples to learn to disambiguate and describe the data. Yet, real-world data-to-text problems often suffer from various data-scarce issues: one may have access to only a handful of or no training examples, and/or have to rely on examples in a different domain or schema. To fill this gap, we propose Any-Shot Data-to-Text (ASDOT), a new approach flexibly applicable to diverse settings by making efficient use of any given (or no) examples. ASDOT consists of two steps, data disambiguation and sentence fusion, both of which are amenable to be solved with off-the-shelf pretrained language models (LMs) with optional finetuning. In the data disambiguation stage, we employ the prompted GPT-3 model to understand possibly ambiguous triples from the input data and convert each into a short sentence with reduced ambiguity. The sentence fusion stage then uses an LM like T5 to fuse all the resulting sentences into a coherent paragraph as the final description. We evaluate extensively on various datasets in different scenarios, including the zero-/few-/full-shot settings, and generalization to unseen predicates and out-of-domain data. Experimental results show that ASDOT consistently achieves significant improvement over baselines, e.g., a 30.81 BLEU gain on the DART dataset under the zero-shot setting.Comment: Findings of EMNLP 202

Solubility prediction of weak electrolyte mixtures

International audienceThe solubility of materials is a thermodynamic variable that depends on their chemical composition and with temperature. Solubility is also affected by the pH, by the presence of additional species in the solution, and by the use of different solvents. On electrolyte, the calculation of solubility requires that the mean ionic activity coefficient be known along with a thermodynamic solubility product

Proteomic differences between developmental stages of Toxoplasma gondii revealed by iTRAQ-based quantitative proteomics

Toxoplasma gondii has a complex two-host life-cycle between intermediate host and definitive host. Understanding proteomic variations across the life-cycle stages of T. gondii may improve the understanding of molecular adaption mechanism of T. gondii across life-cycle stages, and should have implications for the development of new treatment and prevention interventions against T. gondii infection. Here, we utilized LC–MS/MS coupled with iTRAQ labeling technology to identify differentially expressed proteins (DEPs) specific to tachyzoite (T), bradyzoites-containing cyst (C) and sporulated oocyst (O) stages of the cyst-forming T. gondii Prugniuad (Pru) strain. A total of 6285 proteins were identified in the three developmental stages of T. gondii. Our analysis also revealed 875, 656, and 538 DEPs in O vs. T, T vs. C, and C vs. O, respectively. The up- and down-regulated proteins were analyzed by Gene Ontology enrichment, KEGG pathway and STRING analyses. Some virulence-related factors and ribosomal proteins exhibited distinct expression patterns across the life-cycle stages. The virulence factors expressed in sporulated oocysts and the number of up-regulated virulence factors in the cyst stage were about twice as many as in tachyzoites. Of the 79 ribosomal proteins identified in T. gondii, the number of up-regulated ribosomal proteins was 33 and 46 in sporulated oocysts and cysts, respectively, compared with tachyzoites. These results support the hypothesis that oocyst and cystic stages are able to adapt to adverse environmental conditions and selection pressures induced by the host’s immune response, respectively. These findings have important implications for understanding of the developmental biology of T. gondii, which may facilitate the discovery of novel therapeutic targets to better control toxoplasmosis

Association between Life’s simple 7 and rheumatoid arthritis in adult Americans: data from the National Health and nutrition examination survey

ObjectiveThe study aimed to investigate the relationship between Life’s Simple 7 (LS7) and the risk of rheumatoid arthritis (RA) in adult Americans.MethodsA total of 17,532 participants were included in this study. The association between LS7 and the risk of RA was assessed using a weighted logistic regression model, with odds ratios (ORs) and 95% confidence intervals (CIs) calculated. Moreover, the nonlinear relationship was further characterized through smooth curve fitting (SCF) and weighted generalized additive model (GAM) analysis.ResultsAfter adjusting for all covariates, the weighted logistic regression model demonstrated that the LS7 was negatively correlated with the risk of RA. Compared to quintile 1 of LS7, the OR between the risk of RA and quartile 4 of LS7 (LS7.Q4) was 0.261 (95% CI, 0.203, 0.337) in males under 50 years old, while in females of the same age group, the OR was 0.183 (95% CI, 0.142, 0.234). For females aged between 50 and 70 years old, the OR between the risk of RA and LS7.Q4 was 0.313 (95% CI, 0.264, 0.371). In females aged 70 years or older, the OR between the risk of RA and LS7.Q4 was 0.632 (95% CI, 0.486, 0.822).ConclusionThis finding suggested the healthy lifestyle behaviors represented by LS7 have a negative association with RA. However, further prospective studies are needed to verify the causal relationship in the results