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Author

Jun Lu

Bio: Jun Lu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Materials science. The author has an hindex of 135, co-authored 1526 publications receiving 99767 citations. Previous affiliations of Jun Lu include Drexel University & Argonne National Laboratory.


Papers
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Journal ArticleDOI
Haiwei Wu, Jianpeng Zhou, Jinyu Tian, Jun Lu, Yu Qiao 
TL;DR: This work designs a baseline detector, conducts a thorough analysis of the noise introduced by OSNs, and incorporates the modelled noise into a robust training framework, significantly improving the robustness of the image forgery detector.
Abstract: The increasing abuse of image editing software causes the authenticity of digital images questionable. Meanwhile, the widespread availability of online social networks (OSNs) makes them the dominant channels for transmitting forged images to report fake news, propagate rumors, etc. Unfortunately, various lossy operations, e.g., compression and resizing, adopted by OSNs impose great challenges for implementing the robust image forgery detection. To fight against the OSN-shared forgeries, in this work, a novel robust training scheme is proposed. Firstly, we design a baseline detector, which won the top ranking in a recent certificate forgery detection competition. Then we conduct a thorough analysis of the noise introduced by OSNs, and decouple it into two parts, i.e., predictable noise and unseen noise, which are modelled separately. The former simulates the noise introduced by the disclosed (known) operations of OSNs, while the latter is designed to not only complete the previous one, but also take into account the defects of the detector itself. We further incorporate the modelled noise into a robust training framework, significantly improving the robustness of the image forgery detector. Extensive experimental results are presented to validate the superiority of the proposed scheme compared with several state-of-the-art competitors, especially in the scenarios of detecting OSN-transmitted forgeries. Finally, to promote the future development of the image forgery detection, we build a public forgeries dataset based on four existing datasets through the uploading and downloading of four most popular OSNs. The data and code of this work are available at https://github.com/HighwayWu/ImageForensicsOSN.

26 citations

Journal ArticleDOI
TL;DR: In this article, the nanostructure and photoluminescence of polycrystalline Er-doped Y2O3 thin films, deposited by radicalenhanced atomic layer deposition (ALD), were investigated.
Abstract: The nanostructure and photoluminescence of polycrystalline Er-doped Y2O3 thin films, deposited by radical-enhanced atomic layer deposition (ALD), were investigated in this study. The controlled distribution of erbium separated by layers of Y2O3, with erbium concentrations varied from 6to14at.%, was confirmed by elemental electron energy loss spectroscopy (EELS) mapping of Er M4 and M5. This unique feature is characteristic of the alternating radical-enhanced ALD of Y2O3 and Er2O3. The results are also consistent with the extended x-ray absorption fine structure (EXAFS) modeling of the Er distribution in the Y2O3 thin films, where the EXAFS data were best fitted to a layer-like structure. X-ray diffraction (XRD) and selected-area electron diffraction (SAED) patterns revealed a preferential film growth in the [111] direction, showing a lattice contraction with increasing Er doping concentration, likely due to Er3+ of a smaller ionic radius replacing the slightly larger Y3+. Room-temperature photoluminescenc...

26 citations

Journal ArticleDOI
TL;DR: In this paper, a solution processed encapsulation method which facilitates phosphorus anchored inside multi-walled carbon nanotubes (MWCNTs) is proposed. But the method is limited to the case of lithium-ion batteries, where the phosphorus rings and chains are successfully encapsulated only inside MWCNTs.

26 citations

Journal ArticleDOI
Fumio Abe, M. G. Albrow1, D. Amidei2, J. Antos3  +396 moreInstitutions (30)
TL;DR: In this article, the authors have searched for new heavy, heavy, charged bosons through the decay of {ital W}{prime}{r_arrow}{ital e}{nu} in {ital pp}{ovr bar} collisions at {radical}{ital s}=1.8 TeV.
Abstract: We have searched for new, heavy, charged bosons {ital W}{prime} through the decay {ital W}{prime}{r_arrow}{ital e}{nu} in {ital pp}{ovr bar} collisions at {radical}{ital s}=1.8 TeV. The data used in the search represent 19.7 pb{sup --1}collected by the Collider Detector at Fermilab. Limits are placed on {sigma}{ital B}({ital pp}{ovr bar}{r_arrow}{ital W}{prime}{r_arrow}{ital e}{nu}) as a function of {ital M}{sub {ital W}{prime}}. Assuming standard couplings of the {ital W}{prime} to fermions, we establish the limit {ital M}{sub {ital W}{prime}}{gt}652 GeV/{ital c}{sup 2} (95% C.L.).

26 citations

Journal ArticleDOI
03 Apr 2020-ACS Nano
TL;DR: By tailoring the graphene layers, the junction structure described herein exhibits an atomic-scale tunable Schottky junction with an inherent built-in electric field, making it a perfect prototype to systematically comprehend interfacial electronic properties and transport mechanisms.
Abstract: Engineering tunable graphene-semiconductor interfaces while simultaneously preserving the superior properties of graphene is critical to graphene-based devices for electronic, optoelectronic, biomedical, and photoelectrochemical applications. Here, we demonstrate this challenge can be surmounted by constructing an interesting atomic Schottky junction via epitaxial growth of high-quality and uniform graphene on cubic SiC (3C-SiC). By tailoring the graphene layers, the junction structure described herein exhibits an atomic-scale tunable Schottky junction with an inherent built-in electric field, making it a perfect prototype to systematically comprehend interfacial electronic properties and transport mechanisms. As a proof-of-concept study, the atomic-scale-tuned Schottky junction is demonstrated to promote both the separation and transport of charge carriers in a typical photoelectrochemical system for solar-to-fuel conversion under low bias. Simultaneously, the as-grown monolayer graphene with an extremely high conductivity protects the surface of 3C-SiC from photocorrosion and energetically delivers charge carriers to the loaded cocatalyst, achieving a synergetic enhancement of the catalytic stability and efficiency.

26 citations


Cited by
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Journal ArticleDOI
04 Mar 2011-Cell
TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.

51,099 citations

Journal ArticleDOI
TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

34,830 citations

Journal ArticleDOI

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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations