88 research outputs found

    The dominance of big teams in China's scientific output

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    Modern science is dominated by scientific productions from teams. A recent finding shows that teams with both large and small sizes are essential in research, prompting us to analyze the extent to which a country's scientific work is carried out by big/small teams. Here, using over 26 million publications from Web of Science, we find that China's research output is more dominated by big teams than the rest of the world, which is particularly the case in fields of natural science. Despite the global trend that more papers are done by big teams, China's drop in small team output is much steeper. As teams in China shift from small to large size, the team diversity that is essential for innovative works does not increase as much as that in other countries. Using the national average as the baseline, we find that the National Natural Science Foundation of China (NSFC) supports fewer small team works than the National Science Foundation of U.S. (NSF) does, implying that big teams are more preferred by grant agencies in China. Our finding provides new insights into the concern of originality and innovation in China, which urges a need to balance small and big teams

    The dominance of big teams in china’s scientific output

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    Modern science is dominated by scientific productions from teams. A recent finding shows that teams of both large and small sizes are essential in research, prompting us to analyze the extent to which a country’s scientific work is carried out by big or small teams. Here, using over 26 million publications from Web of Science, we find that China’s research output is more dominated by big teams than the rest of the world, which is particularly the case in fields of natural science. Despite the global trend that more papers are written by big teams, China’s drop in small team output is much steeper. As teams in China shift from small to large size, the team diversity that is essential for innovative work does not increase as much as that in other countries. Using the national average as the baseline, we find that the National Natural Science Foundation of China (NSFC) supports fewer small teams than the National Science Foundation (NSF) of the United States does, implying that big teams are preferred by grant agencies in China. Our finding provides new insights into the concern of originality and innovation in China, which indicates a need to balance small and big teams. © 2020 Linlin Liu, Jianfei Yu, Junming Huang, Feng Xia, and Tao Jia. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license

    How ChatGPT is Solving Vulnerability Management Problem

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    Recently, ChatGPT has attracted great attention from the code analysis domain. Prior works show that ChatGPT has the capabilities of processing foundational code analysis tasks, such as abstract syntax tree generation, which indicates the potential of using ChatGPT to comprehend code syntax and static behaviors. However, it is unclear whether ChatGPT can complete more complicated real-world vulnerability management tasks, such as the prediction of security relevance and patch correctness, which require an all-encompassing understanding of various aspects, including code syntax, program semantics, and related manual comments. In this paper, we explore ChatGPT's capabilities on 6 tasks involving the complete vulnerability management process with a large-scale dataset containing 78,445 samples. For each task, we compare ChatGPT against SOTA approaches, investigate the impact of different prompts, and explore the difficulties. The results suggest promising potential in leveraging ChatGPT to assist vulnerability management. One notable example is ChatGPT's proficiency in tasks like generating titles for software bug reports. Furthermore, our findings reveal the difficulties encountered by ChatGPT and shed light on promising future directions. For instance, directly providing random demonstration examples in the prompt cannot consistently guarantee good performance in vulnerability management. By contrast, leveraging ChatGPT in a self-heuristic way -- extracting expertise from demonstration examples itself and integrating the extracted expertise in the prompt is a promising research direction. Besides, ChatGPT may misunderstand and misuse the information in the prompt. Consequently, effectively guiding ChatGPT to focus on helpful information rather than the irrelevant content is still an open problem

    Green synthesis of biogenetic Te(0) nanoparticles by high tellurite tolerance fungus Mortierella sp. AB1 with antibacterial activity

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    Tellurite [Te(IV)] is a high-toxicity metalloid. In this study, a fungus with high Te(IV) resistance was isolated. Strain AB1 could efficiently reduce highly toxic Te(IV) to less toxic Te(0). The reduced products formed rod-shaped biogenetic Te(0) nanoparticles (Bio-TeNPs) intracellularly. Further TEM-element mapping, FTIR, and XPS analysis showed that the extracted Bio-TeNPs ranged from 100 to 500 nm and consisted of Te(0), proteins, lipids, aromatic compounds, and carbohydrates. Moreover, Bio-TeNPs exhibited excellent antibacterial ability against Shigella dysenteriae, Escherichia coli, Enterobacter sakazakii, and Salmonella typhimurium according to inhibition zone tests. Further growth and live/dead staining experiments showed that E. coli and S. typhimurium were significantly inhibited by Bio-TeNPs, and cells were broken or shriveled after treatment with Bio-TeNPs based on SEM observation. Additionally, the antioxidant and cytotoxicity tests showed that the Bio-TeNPs exhibited excellent antioxidant capacity with no cytotoxicity. All these results suggested that strain AB1 showed great potential in bioremediation and Bio-TeNPs were excellent antibacterial nanomaterials with no cytotoxicity.Peer reviewe

    UrbanGenoGAN: pioneering urban spatial planning using the synergistic integration of GAN, GA, and GIS

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    Introduction: Urban spatial planning is critical for the development of sustainable and livable cities. However, traditional planning methods often face challenges in handling complex planning scenarios and large-scale data.Methods: This paper introduces UrbanGenoGAN, a novel algorithm that integrates generative adversarial networks (GANs), genetic optimization algorithms (GOAs), and geographic information system (GIS) to address these challenges. Leveraging the generative power of GANs, the optimization capabilities of genetic algorithms, and the spatial analysis capabilities of GIS, UrbanGenoGAN is designed to generate optimized urban plans that cater to various urban planning challenges. Our methodology details the algorithm’s design and integration of its components, data collection and preprocessing, and the training and implementation processes.Results: Through rigorous evaluation metrics, comparative analysis with existing methodologies, and case studies, the proposed algorithm demonstrates significant improvement in urban planning outcomes. The research also explores the technical and practical considerations for implementing UrbanGenoGAN, including scalability, computational efficiency, data privacy, and ethical considerations.Discussion: The findings suggest that the integration of advanced machine learning and optimization techniques with spatial analysis offers a promising approach to enhancing decision-making in urban spatial planning. This work contributes to the growing field of AI applications in urban planning and paves the way for more efficient and sustainable urban development

    Electric-field-driven Non-volatile Multi-state Switching of Individual Skyrmions in a Multiferroic Heterostructure

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    Electrical manipulation of skyrmions attracts considerable attention for its rich physics and promising applications. To date, such a manipulation is realized mainly via spin-polarized current based on spin-transfer torque or spin-orbital torque effect. However, this scheme is energy-consuming and may produce massive Joule heating. To reduce energy dissipation and risk of heightened temperatures of skyrmion-based devices, an effective solution is to use electric field instead of current as stimulus. Here, we realize an electric-field manipulation of skyrmions in a nanostructured ferromagnetic/ferroelectrical heterostructure at room temperature via an inverse magneto-mechanical effect. Intriguingly, such a manipulation is non-volatile and exhibits a multi-state feature. Numerical simulations indicate that the electric-field manipulation of skyrmions originates from strain-mediated modification of effective magnetic anisotropy and Dzyaloshinskii-Moriya interaction. Our results open a direction for constructing low-energy-dissipation, non-volatile, and multi-state skyrmion-based spintronic devices.Comment: Accepted by Nature Communications 11, 3577 (2020

    Ppm1b negatively regulates necroptosis through dephosphorylating ​Rip3

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    该研究论文发现蛋白磷酸酶Ppm1b 通过去磷酸化RIP3负调控程序性细胞坏死(necroptosis),阐明了RIP3磷酸化状态的精确调控对于细胞和机体在生理和病理状态下的存活至关重要。The auto-phosphorylation of murine ​receptor-interacting protein 3 (​Rip3) on Thr 231 and Ser 232 in the necrosome is required to trigger necroptosis. However, how ​Rip3 phosphorylation is regulated is still largely unknown. Here we identified ​protein phosphatase 1B (​Ppm1b) as a ​Rip3 phosphatase and found that ​Ppm1b restricts necroptosis in two settings: spontaneous necroptosis caused by ​Rip3 auto-phosphorylation in resting cells, and ​tumour necrosis factor-α (​TNF)-induced necroptosis in cultured cells. We revealed that ​Ppm1b selectively suppresses necroptosis through the dephosphorylation of ​Rip3, which then prevents the recruitment of ​mixed lineage kinase domain-like protein (​Mlkl) to the necrosome. We further showed that ​Ppm1b deficiency (​Ppm1bd/d) in mice enhanced ​TNF-induced death in a ​Rip3-dependent manner, and the role of ​Ppm1b in inhibiting necroptosis was evidenced by elevated ​Rip3 phosphorylation and tissue damage in the caecum of ​TNF-treated ​Ppm1bd/d mice. These data indicate that ​Ppm1b negatively regulates necroptosis through dephosphorylating ​Rip3 in vitro and in vivo

    Adenovirus-mediated stromal cell-derived factor-1 alpha gene transfer improves cardiac structure and function after experimental myocardial infarction through angiogenic and antifibrotic actions

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    Stromal cell-derived factor 1α (SDF-1) is not only a major chemotactic factor, but also an inducer of angiogenesis. The effects of SDF-1α on the left ventricular remodeling in a rat myocardial infarction (MI) model were analyzed. Myocardial infarction was induced by ligation of the left coronary artery in rats. 0.5 × 1010 pfu/ml AdV-SDF-1 or 0.5 × 1010 pfu/ml Adv-LacZ were immediately injected into the infarcted myocardium, 120 μl cell-free PBS were injected into the infarcted region or the myocardial wall in control, and sham group, respectively. We found that AdV-SDF-1 group had higher LVSP and ±dP/dtmax, lower LVEDP compared to control or Adv-LacZ group. The number of c-Kit+ stem cells, and gene expression of SDF-1, VEGF and bFGF were obviously increased, which was associated with reduced infarct size, thicker left ventricle wall, greater vascular density and cardiocytes density in infarcted hearts of AdV-SDF-1 group. Furthermore, the expression of collagen type I and type III mRNA, and collagen accumulation in the infarcted area was lower, which was associated with decreased TGF-β1, TIMP-1 and TIMP-2 expression in AdV-SDF-1 group. Conclusion: SDF-1α could improve cardiac structure and function after Myocardial infarction through angiogenic and anti-fibrotic actions
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