skip to main content

Search for: All records

Creators/Authors contains: "Luo, Bin"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.


    The Australia Telescope Large Area Survey (ATLAS) and the VLA survey in the XMM-LSS/VIDEO deep field provide deep (≈15 $\mu$ Jy beam−1) and high-resolution (≈4.5–8 arcsec) radio coverage of the three XMM-SERVS fields (W-CDF-S, ELAIS-S1, and XMM-LSS). These data cover a total sky area of 11.3 deg2 and contain ≈11 000 radio components. Furthermore, about 3 deg2 of the XMM-LSS field also has deeper MIGHTEE data that achieve a median RMS of 5.6 $\mu$ Jy beam−1 and detect more than 20 000 radio sources. We analyse all these radio data and find source counterparts at other wavebands utilizing deep optical and infrared (IR) surveys. The nature of these radio sources is studied using radio-band properties (spectral slope and morphology) and the IR–radio correlation. Radio AGNs are selected and compared with those selected using other methods (e.g. X-ray). We found 1656 new AGNs that were not selected using X-ray and/or MIR methods. We constrain the FIR-to-UV SEDs of radio AGNs using cigale and investigate the dependence of radio AGN fraction upon galaxy stellar mass and star formation rate.

  2. Free, publicly-accessible full text available January 1, 2024
  3. Free, publicly-accessible full text available January 1, 2024
  4. Free, publicly-accessible full text available July 1, 2023

    Observations of historical tsunami earthquakes reveal that ruptures of these earthquakes propagate slowly at shallow depth with longer duration, depletion in high-frequency radiation and larger discrepancy of Mw–Ms than ordinary megathrust earthquakes. They can effectively generate tsunami and lead to huge damage to regional populated areas near the coast. In this study, we use a recently developed dynamic earthquake simulator to explore tsunami earthquake generation from a physics-based modelling point of view. We build a shallow-dipping subduction zone model in which locally locked, unstable patches (asperities) are distributed on a conditionally stable subduction interface at shallow depth. The dynamic earthquake simulator captures both quasi-static and dynamic processes of earthquake cycles. We find that earthquakes can nucleate on these asperities and propagate into the surrounding conditionally stable zone at slow speeds, generating tsunami earthquakes. A high normal stress asperity, representing a subducted seamount, can act as an asperity in some events but as a barrier in other events over multiple earthquake cycles. Low normal stress asperities typically act as asperities in tsunami earthquakes. The degree of velocity-weakening in the conditionally stable zone, which may sustain rupture at different speeds or stop rupture, is critical for tsunami earthquake generation and affectsmore »its recurrence interval. Distributed asperities may rupture in isolated events separated by tens of years, or in a sequence of events separated by hours to days, or in one large event in a cascade fashion, demonstrating complex interactions among them. The recurrence interval on a high normal stress asperity is much larger than that on low normal stress asperities. These modelling results shed lights on the observations from historical tsunami earthquakes, including the 1994 and 2006 Java tsunami earthquakes and 2010 Mentawai tsunami earthquake.

    « less
  6. Abstract

    Definitive diagnosis to sudden cardiac death (SCD) is often challenging since the postmortem examination on SCD victims could hardly demonstrate an adequate cause of death. It is therefore important to uncover the inherited risk component to SCD. Signal transducer and activators of transcription 5 A (STAT5A) is a member of the STAT family and a transcription factor that is activated by many cell ligands and associated with various cardiovascular processes. In this study, we performed a systematic variant screening on the STAT5A to filter potential functional genetic variations. Based on the screening results, an insertion/deletion polymorphism (rs3833144) in 3’UTR of STAT5A was selected as the candidate variant. A total of 159 SCD cases and 668 SCD matched healthy controls was enrolled to perform a case-control study and evaluate the association between rs3833144 and SCD susceptibility in Chinese populations. Logistic regression analysis showed that the deletion allele of rs3833144 had significantly increased the SCD risk (odds ratio (OR) = 1.54; 95% confidence interval (CI) = 1.18–2.01; P = 0.000955). Further genotype-expression eQTL analysis showed that samples with deletion allele appeared to lower expression of STAT5A, and in silico prediction suggested the local 3 D structure changes of STAT5A mRNA caused by the variant. Onmore »the other hand, the bioinformatic analysis presented that promoters of RARA and PTGES3L-AARSD1 could interact with rs3833144, and eQTL analysis showed the higher expression of both genes in samples with deletion allele. Dual-luciferase activity assays also suggested the significant regulatory role of rs3833144 in gene transcription. Our current data thus suggested a possible involvement of rs3833144 to SCD predisposition in Chinese populations and rs3833144 with potential function roles may become a candidate marker for SCD diagnosis and prevention.

    « less
  7. Abstract Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE’s mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth's evolution.