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"Xu, Yong"
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Xu Yong - Hutong
Xu Yong's black-and-white images dating from 1989 bear witness to the rise and fall, the heyday and the decline, of the Hutongs - against the backdrop of the rapid societal change in China that followed the end of the Qing Dynasty.
BOOK
Ultra-high frequency gravitational waves from scattering, Bremsstrahlung and decay during reheating
A
bstract
We investigate ultra-high frequency gravitational waves (GWs) from gravitons generated during inflationary reheating. Specifically, we study inflaton scattering with its decay product, where the couplings involved in this 2 → 2 scattering are the same as those in the 1 → 3 graviton Bremsstrahlung process. We compute the graviton production rate via such 2 → 2 scattering. Additionally, we compare the resulting GW spectrum with that from Bremsstrahlung as well as that from pure 2 → 2 inflaton scatterings. For completeness, the GW spectrum from graviton pair production through one-loop induced 1 → 2 inflaton decay is also analyzed. With a systematic comparison among the four sources of GWs, we find that 2 → 2 inflaton scattering with its decay product can dominate over Bremsstrahlung if the reheating temperature is larger than the inflaton mass. Pure inflaton 2 → 2 scattering is typically subdominant compared to Bremsstrahlung except in the high-frequency tail. The contribution from one-loop induced 1 → 2 inflaton decay is shown to be suppressed compared to Bremsstrahlung and pure inflaton 2 → 2 scattering.
Journal Article
Overshooting, critical Higgs inflation and second order gravitational wave signatures
The self coupling λ of the Higgs boson in the Standard Model may show critical behavior, i.e. the Higgs potential may have a point at an energy scale ∼1017-18 GeV where both the first and second derivatives (almost) vanish. In this case the Higgs boson can serve as inflaton even if its nonminimal coupling to the curvature scalar is only O(10), thereby alleviating concerns about the perturbative unitarity of the theory. We find that just before the Higgs as inflaton enters the flat region of the potential the usual slow-roll conditions are violated. This leads to “overshooting” behavior, which in turn strongly enhances scalar curvature perturbations because of the excitation of entropic (non-adiabatic) perturbations. For appropriate choice of the free parameters these large perturbations occur at length scales relevant for the formation of primordial black holes. Even if these perturbations are not quite large enough to trigger copious black hole formation, they source second order tensor perturbations, i.e. primordial gravitational waves; the corresponding energy density can be detected by the proposed space-based gravitational wave detectors DECIGO and BBO.
Journal Article
PPARs： diverse regulators in energy metabolism and metabolic diseases
The nuclear receptor PPARs are fundamentally important for energy homeostasis. Through their distinct yet overlapping functions and tissue distribution, the PPARs regulate many aspects of energy metabolism at the transcriptional level. Functional impairment or dysregulation of these receptors leads to a variety of metabolic diseases, while their ligands offer many metabolic benefits. Studies of these receptors have advanced our knowledge of the transcriptional basis of energy metabolism and helped us understand the pathogenic mechanisms of metabolic syndrome.
Journal Article
General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian
The combination of deep learning and ab initio calculation has shown great promise in revolutionizing future scientific research, but how to design neural network models incorporating a priori knowledge and symmetry requirements is a key challenging subject. Here we propose an E(3)-equivariant deep-learning framework to represent density functional theory (DFT) Hamiltonian as a function of material structure, which can naturally preserve the Euclidean symmetry even in the presence of spin–orbit coupling. Our DeepH-E3 method enables efficient electronic structure calculation at ab initio accuracy by learning from DFT data of small-sized structures, making the routine study of large-scale supercells (>10
4
atoms) feasible. The method can reach sub-meV prediction accuracy at high training efficiency, showing state-of-the-art performance in our experiments. The work is not only of general significance to deep-learning method development but also creates opportunities for materials research, such as building a Moiré-twisted material database.
Fundamental symmetries are crucial to the deep-learning modeling of physical systems. Here the authors use equivariant neural networks preserving the Euclidean symmetries to accelerate electronic structure calculations by orders of magnitude keeping sub-meV accuracy.
Journal Article
Thermal gravitational waves during reheating
A
bstract
In this work, we revisit the generation of stochastic gravitational waves (GWs) from interactions in the thermal plasma. We extend the existing literature by incorporating the reheating phase into the thermal history. Our results show that the amplitude of the GW spectrum can be significantly enhanced because the temperature during reheating can be much higher than the reheating temperature. Furthermore, since the temperature evolution during reheating differs from that of free radiation, the peak frequency of the spectrum can also shift. Additionally, the morphology of the spectrum can present characteristic features. We also compute the contribution of the integrated GW spectrum to the effective number of neutrino species, ∆
N
eff
, which can be substantially larger.
Journal Article
Probing dark matter particles at CEPC
A
bstract
We investigate the capability of the future electron collider CEPC in probing the parameter space of several dark matter models, including millicharged dark matter models,
Z
′
portal dark matter models, and effective dark matter operators. In our analysis, the monophoton final state is used as the primary channel to detect dark matter models at CEPC. To maximize the signal to background significance, we study the energy and angular distributions of the monophoton channel arising from dark matter models and from the standard model to design a set of detector cuts. For the
Z
′
portal dark matter, we also analyze the
Z
′
boson visible decay channel which is found to be complementary to the monophoton channel in certain parameter space. The CEPC reach in the parameter space of dark matter models is also put in comparison with Xenon1T. We find that CEPC has the unprecedented sensitivity to certain parameter space for the dark matter models considered; for example, CEPC can improve the limits on millicharge by one order of magnitude than previous collider experiments for
O
1
−
100
GeV dark matter.
Journal Article
Applications of deep-learning approaches in horticultural research: a review
Deep learning is known as a promising multifunctional tool for processing images and other big data. By assimilating large amounts of heterogeneous data, deep-learning technology provides reliable prediction results for complex and uncertain phenomena. Recently, it has been increasingly used by horticultural researchers to make sense of the large datasets produced during planting and postharvest processes. In this paper, we provided a brief introduction to deep-learning approaches and reviewed 71 recent research works in which deep-learning technologies were applied in the horticultural domain for variety recognition, yield estimation, quality detection, stress phenotyping detection, growth monitoring, and other tasks. We described in detail the application scenarios reported in the relevant literature, along with the applied models and frameworks, the used data, and the overall performance results. Finally, we discussed the current challenges and future trends of deep learning in horticultural research. The aim of this review is to assist researchers and provide guidance for them to fully understand the strengths and possible weaknesses when applying deep learning in horticultural sectors. We also hope that this review will encourage researchers to explore some significant examples of deep learning in horticultural science and will promote the advancement of intelligent horticulture.
Journal Article
Exosomal circRNA-100338 promotes hepatocellular carcinoma metastasis via enhancing invasiveness and angiogenesis
Background
Exosomes play crucial roles in regulating the crosstalk between normal and cancer cells in the tumor microenvironment, and in regulating cancer proliferation, migration and invasion through their cargo molecules.
Methods
We analyzed the pro-invasiveness of exosomal circRNA-100,338 in HCC using the transwell invasion assay. The co-culture of human umbilical vein endothelial cells (HUVEC) and exosomes derived from HCC cell lines were used to evaluate the impact of HCC derived exosomes on HUVEC. Nude mice models were used to validate the findings in vitro. Clinically, quantitative RT-PCR was used to quantify the expression of serum exosomal circRNA-100,338 in HCC patients at both pre-surgery within one week and post-surgery within three weeks.
Results
We aim to investigate the pro-invasive role of exosomal circRNA-100,338 in HCC metastasis. We for the first time demonstrated that circRNA-100,338 was highly expressed in both highly metastatic HCC cells and their secreted exosomes. The transwell invasion assay showed that the overexpression or knockdown of exosomal circRNA-100,338 significantly enhanced or reduced the invasive abilities of HCC cells. Subsequently, in vitro and in vivo assays showed that exosomal circRNA-100,338 affected the cell proliferation, angiogenesis, permeability, and vasculogenic mimicry (VM) formation ability of human umbilical vein endothelial cells (HUVEC), and tumor metastasis. Furthermore, we also observed that the persistent high expression of exosomal circRNA-100,338 in serum of HCC patients who underwent curative hepatectomy may be a risk indicator of pulmonary metastasis and poor survival.
Conclusions
Our findings indicated that metastatic ability of HCC cells could be enhanced by transferring exosomal circRNA-100,338 to recipient HUVECs, which could affect proangiogenic activity by regulating angiogenesis.
Journal Article