Generalized parton distributions of Δ\Delta resonance in a diquark spectator approach

The generalized parton distributions (GPDs) for the spin-3/2 $\Delta^+$ resonance are studied numerically by using a diquark spectator approach. Our results show that symmetric constraints from time reversal on GPDs are satisfied. The axial vector form factors of the system are also provided and compared with the lattice QCD calculation. Furthermore, the structure functions are obtained from GPDs in the forward limit. The evolution of structure functions to the scales up to 4 GeV are carried out as predictions for the possible lattice QCD calculations

Mechanical structure of a spin-1 particle

We investigate the mechanical structure of a spin-1 particle. Introducing three different frameworks, i.e., the three-dimensional (3D) Breit frame, the two-dimensional (2D) Breit frame, and the 2D infinite momentum frame (equivalently the two-dimensional Drell-Yan frame), we scrutinize the 2D and 3D energy-momentum tensor (EMT) distributions in these frames. We first derive the EMT distributions in the 2D Breit frame by performing the Abel transformation. The mass distribution in the 2D Breit frame contains an additional monopole contribution induced geometrically. The pressure distribution in the 2D Breit frame also gets an induced monopole structure. When the Lorentz boost is carried out, the mass distribution in the 2D infinite-momentum frame acquires the induced dipole term. Similarly, we also have the induced dipole contributions to the pressure and shear-force densities. We visualize the 2D mass distributions when the spin-1 particle is polarized along the $x$- and $z$-axes. We observe that the 2D mass distribution in the infinite momentum frame exhibit clearly the induced dipole structure when the spin-1 particle is polarized along the $x$-axis. We also discuss the strong force fields inside a polarized spin-1 particle.Comment: 28 pages and 9 figure

Teaching Text-to-Image Models to Communicate in Dialog

A picture is worth a thousand words, thus, it is crucial for conversational agents to understand, perceive, and effectively respond with pictures. However, we find that directly employing conventional image generation techniques is inadequate for conversational agents to produce image responses effectively. In this paper, we focus on the innovative dialog-to-image generation task, where the model synthesizes a high-resolution image aligned with the given dialog context as a response. To tackle this problem, we design a tailored fine-tuning approach on the top of state-of-the-art text-to-image generation models to fully exploit the structural and semantic features in dialog context during image generation. Concretely, we linearize the dialog context with specific indicators to maintain the dialog structure, and employ in-domain data to alleviate the style mismatch between dialog-to-image and conventional image generation tasks. Empirical results on PhotoChat and MMDialog Corpus show that our approach brings consistent and remarkable improvement with 3 state-of-the-art pre-trained text-to-image generation backbones.Comment: Work in progres

Random Silicon Sampling: Simulating Human Sub-Population Opinion Using a Large Language Model Based on Group-Level Demographic Information

Large language models exhibit societal biases associated with demographic information, including race, gender, and others. Endowing such language models with personalities based on demographic data can enable generating opinions that align with those of humans. Building on this idea, we propose "random silicon sampling," a method to emulate the opinions of the human population sub-group. Our study analyzed 1) a language model that generates the survey responses that correspond with a human group based solely on its demographic distribution and 2) the applicability of our methodology across various demographic subgroups and thematic questions. Through random silicon sampling and using only group-level demographic information, we discovered that language models can generate response distributions that are remarkably similar to the actual U.S. public opinion polls. Moreover, we found that the replicability of language models varies depending on the demographic group and topic of the question, and this can be attributed to inherent societal biases in the models. Our findings demonstrate the feasibility of mirroring a group's opinion using only demographic distribution and elucidate the effect of social biases in language models on such simulations.Comment: 25 pages, 4 figures, 19 Table

Role of C4 carbon fixation in Ulva prolifera, the macroalga responsible for the world's largest green tides

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Liu, D., Ma, Q., Valiela, I., Anderson, D. M., Keesing, J. K., Gao, K., Zhen, Y., Sun, X., & Wang, Y. Role of C4 carbon fixation in Ulva prolifera, the macroalga responsible for the world's largest green tides. Communications Biology, 3(1), (2020): 494, doi:10.1038/s42003-020-01225-4.Most marine algae preferentially assimilate CO2 via the Calvin-Benson Cycle (C3) and catalyze HCO3− dehydration via carbonic anhydrase (CA) as a CO2-compensatory mechanism, but certain species utilize the Hatch-Slack Cycle (C4) to enhance photosynthesis. The occurrence and importance of the C4 pathway remains uncertain, however. Here, we demonstrate that carbon fixation in Ulva prolifera, a species responsible for massive green tides, involves a combination of C3 and C4 pathways, and a CA-supported HCO3− mechanism. Analysis of CA and key C3 and C4 enzymes, and subsequent analysis of δ13C photosynthetic products showed that the species assimilates CO2 predominately via the C3 pathway, uses HCO3− via the CA mechanism at low CO2 levels, and takes advantage of high irradiance using the C4 pathway. This active and multi-faceted carbon acquisition strategy is advantageous for the formation of massive blooms, as thick floating mats are subject to intense surface irradiance and CO2 limitation.This work was supported by the State Key Project of Research and Development Plan, Ministry of Science and Technology of the Peopleʼs Republic of China (2016YFC1402106). Support for D.M.A. provided by the Woods Hole Oceanographic Institution—Ocean University of China Cooperative Research Initiative. We thank Dr. Juntian Xu, Jing Ma, Ying Li, and Chenglong Ji for assisting culture experiments and sample analysis

The pathological and therapeutic roles of mesenchymal stem cells in preeclampsia

Mesenchymal stem cells (MSCs) have made progress in the treatment of ischemic and inflammatory diseases. Preeclampsia (PE) is characterized by placenta ischemic and inflammatory injury. Our paper summarized the new role of MSCs in PE pathology and its potency in PE therapy and analyzed its current limitations. Intravenously administered MSCs dominantly distributed in perinatal tissues. There may be additional advantages to using MSCs-based therapies for reproductive disorders. It will provide new ideas for future research in this field

Modeling and analysis of energy distribution networks using switched differential systems

It is a pleasure to dedicate this contribution to Prof. Arjan van der Schaft on the occasion of his 60th birthday. We study the dynamics of energy distribution networks consisting of switching power converters and multiple (dis-)connectable modules. We use parsimonious models that deal effectively with the variant complexity of the network and the inherent switching phenomena induced by power converters. We also present the solution to instability problems caused by devices with negative impedance characteristics such as constant power loads. Elements of the behavioral system theory such as linear differential behaviors and quadratic differential forms are crucial in our analysis