3,280 research outputs found
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
Speech-Driven 3D Face Animation with Composite and Regional Facial Movements
Speech-driven 3D face animation poses significant challenges due to the
intricacy and variability inherent in human facial movements. This paper
emphasizes the importance of considering both the composite and regional
natures of facial movements in speech-driven 3D face animation. The composite
nature pertains to how speech-independent factors globally modulate
speech-driven facial movements along the temporal dimension. Meanwhile, the
regional nature alludes to the notion that facial movements are not globally
correlated but are actuated by local musculature along the spatial dimension.
It is thus indispensable to incorporate both natures for engendering vivid
animation. To address the composite nature, we introduce an adaptive modulation
module that employs arbitrary facial movements to dynamically adjust
speech-driven facial movements across frames on a global scale. To accommodate
the regional nature, our approach ensures that each constituent of the facial
features for every frame focuses on the local spatial movements of 3D faces.
Moreover, we present a non-autoregressive backbone for translating audio to 3D
facial movements, which maintains high-frequency nuances of facial movements
and facilitates efficient inference. Comprehensive experiments and user studies
demonstrate that our method surpasses contemporary state-of-the-art approaches
both qualitatively and quantitatively.Comment: Accepted by MM 2023, 9 pages, 7 figures. arXiv admin note: text
overlap with arXiv:2303.0979
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
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