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Research Square 2021年

作者： Huang, Jing Ge, Zhongxi Huang, Yuqing Tang, Xuguang Shi, Zhan Lai, Peiyu Song, Zengjing Hao, Binfei Yang, Hong Ma, Mingguo Southwest University School of Geographical Sciences Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Karst Ecosystem Ministry of Education Chongqing400715 China Chongqing Engineering Research Center for Remote Sensing Big Data Application School of Geographical Sciences Southwest University Tiansheng Road No.2 Beibei District Chongqing400715 China Chongqing Key Laboratory of Karst Environment School of Geographical Sciences Southwest University Chongqing400715 China Department of Geography and Environmental Science University of Reading Whiteknights Reading BerkshireRG6 6AB United Kingdom Key Laboratory of Beibu Gulf Environment Change and Resource Use Ministry of Education Nanning Normal University Nanning530000 China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang524088 China

Backgrounds Vegetation dynamic plays a dominant role in the global carbon cycle and climate, especially in vulnerable karst ecosystem. Many studies have examined past several decades changes in vegetation greenness and the associated with climate drivers. Yet, few studies have analyzed the vegetation change in global karst regions particularly in the last decades when climate change and anthropogenic disturbance widely occurred. Methods In this study, we investigated the spatio-temporal variations of vegetation dynamic using the Seasonally Integrated Normalized Difference Vegetation Index (SINDVI) and examined their relationship to climate changes by correlation analysis, the ordinary least squares method investigate the variation trends and the Mann-Kendal test to detect the turning point from 2001 to 2020. Results As expected, there have greening trend in global karst SINDVI from 2001 to 2020, with significant increasing trend in China (range = 0.836, P © 2021, CC BY.

关键词： Temperature

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Deterministic two-photon controlled-Z gate with the two-photon quantum Rabi model

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Physical Review A 2025年第5期111卷 052601-052601页

作者： Jia-Cheng Tang Jin Zhao Haitao Yang Junlong Tian Pinghua Tang Shuai-Peng Wang Lucas Lamata Jie Peng Hunan Key Laboratory for Micro-Nano Energy Materials and Devices and School of Physics and Optoelectronics Xiangtan University Xiangtan Hunan 411105 China Beijing Academy of Quantum Information Sciences Beijing 100193 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou Zhejiang 310024 China School of Physics and Electronic Information Engineering Zhaotong University Zhaotong Yunnan 657000 China Department of Electronic Science College of Big Data and Information Engineering Guizhou University Guiyang Guizhou 550025 China Departamento de Física Atómica Molecular y Nuclear Universidad de Sevilla 41080 Sevilla Spain

We propose a scheme for realizing a deterministic two-photon controlled-Z (cz) gate based on variants of the two-photon quantum Rabi model, which is feasible within the framework of circuit QED. We begin by utilizing the two-photon interaction to implement the nonlinear sign gate and subsequently we construct the cz gate following the Knill-Laflamme-Milburn scheme [Nature (London) 409, 46 (2001)]. We consider three different regimes: the strong-coupling regime, the perturbative ultrastrong-coupling regime, and the large-detuning regime. Our results indicate that the cz gate operates fast with high fidelity. We also show that the photonic state in the waveguide can be input into the circuit QED system through a variable coupler and released after interaction with almost the same waveform except for a π-phase shift. Our scheme offers a suitable approach for achieving fast and deterministic two-photon quantum gates via light-matter interactions.

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A Novel L1 Gain Performance Based Multi-robot System Formulation Control Design Method

A Novel L1 Gain Performance Based Multi-robot System Formula...

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第32届中国控制与决策会议

作者： Xiongjun Wu Jialing Zhou Dequan Li Hongbo Zhao National Defense Key Laboratory of Science and Technology on Electromagnetic Scattering The 802 Institute of Shanghai Academy of Space Flight TechnologyThe Eighth Academy of China Aerospace Science and Technology Corporation School of Automation Nanjing University of Science and Technology School of Mathematics and Big Data Anhui University of Science and Technology School of Automation Science and Electrical Engineering Beihang University

The time-varying formations are usually required in practice for multi-agent systems to track the trajectories generated by multiple *** ability to maintain a stable formation property is helpful in terms of facilitating subsequent tasks such as collaborative detection,cooperative reconnaissance and performing other specific task like fetch and transport goods together as a ***,most of existing methods,on the other hand,are fragile to the measurement noises and network ***,it seems that few results are available that considering the internal and external control loop to arrive the consensus of position,the velocity and the attitude *** overcome these limitations,in this paper,we proposed a novel scheme and developed a novel L gain algorithm,where the integrated two loop robot control scheme is endowed with disturbance rejection ability,and it can maintain the formation structure during motion along a pre-determined or online generated geometric path,and to follow a timing law that dominates the rate of advancement of the *** conditions are established to guarantee the stability,the invariant set property,the L gain index,and also the initial tracking error bounding constraints,which are formulated and presented in terms of LMIs/BMIs and can be readily solved to obtain the *** simulations are carried out to validate the effectiveness of the proposed method,and the five robots as well as the three robots formulation cases are detail *** turns out that,in addition to providing a novel perspective of the formulation control problem with disturbance rejection ability,the approach adopted in this paper also paves the way to several extensions in relation to control of multi-agent systems in accordance with swarm intelligence principles,such as the collision avoidance,the delayed multi-agent system control,the incorporation of multiple simultaneous objectives and control design under communi

关键词： Formation Control L1 Gain Multi-agent Systems Disturbance Rejection Cooperative Detection

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Investigation of the Effect of Process Parameters on Energy Consumption in Incremental Sheet forming

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Procedia CIRP 2019年 80卷 50-55页

作者： Yanle Li Fuyuan Liu Changxu Xu Weidong Zhai Lirong Zhou Fangyi Li Jianfeng Li Key Laboratory of High Efficiency and Clean Mechanical Manufacture Ministry of Education School of Mechanical Engineering Shandong University Jinan 250061 China College of Big Data Statistics Guizhou University of Finance and Economics Guiyang 550000 China

The selection of machine tool and process parameters plays a crucial role in the energy consumption in manufacturing processes such as incremental sheet forming (ISF) process. The analysis of how the process parameters influence the energy required during ISF processes will not only provide opportunity to reduce the environmental consequences, but also reduce economic cost. To this end, an empirical power model is presented with the aim of understanding energy consumption composition during ISF performed on a milling machine. The effects of process variables (e.g., material strength, step down, sheet thickness, tool diameter, and feed rate) on the power, forming time, and energy required for ISF processes are experimentally investigated. In particular, experimental results are in-depth analyzed to understand energy required breakdown by a machine tool during the ISF. Further, the mechanism on how the process parameters affect the energy required for the sheet plastic deformation is revealed. Based on the analysis above, useful energy-saving suggestions on selecting process parameters are provided.

关键词： Energy consumption composition incremental sheet forming green manufacturing

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Discovery of Novel Mammalian target of rapamycin (mTOR) Inhibitors by Support Vector Machine

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IOP Conference Series: Earth and Environmental Science 2021年第3期692卷

作者： Panpan Wang Xiaobo Xu Yinghong Li Bo Li Qinglan Pei Pei Yu Chenxi Jing Meng Lu College of Chemistry and Pharmaceutical Engineering Huanghuai University Zhumadian China Chongqing Key Laboratory on Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications Chongqing China College of Life Sciences Chongqing Normal University Chongqing China

Mammalian target of rapamycin (mTOR) is a protein serine/threonine kinase playing the central downstream role in multiple mitogenic signalling pathways. As a c entral regulator of cell growth, proliferation, differentiation and survival, mTOR has b een reported to modulate proliferation and angiogenesis in neoplastic processes. Curre ntly, sirolimus and its analogues the only five mTOR inhibitors approved for clinical u se, which shows a great capacity in anticancer therapy. However, endocrine resistance in cancer therapy has been observed in sirolimus analogues, and the unavailability of n ew mTOR inhibitor besides similar structure of sirolimus analogues makes the resistan ce even worse. It is urgent to discovery new mTOR inhibitors as candidates for develo pment of effective anticancer drugs. In this study, support vector machine (SVM) as a virtual screening strategy was proposed. SVM models of mTOR inhibitors were constr ucted by training data published before 2012, and the ones published after 2012 as test set were used to verify according to cross validation. The selected model performed thi n false hit rates of 0.12% and 0.46% by screening PubChem and MDDR chemical libr aries respectively. As results, 9 novel novel scaffolds for mTOR were identified, and 6 of them have been reported their anticancer-related therapeutic capacity. In summary, SVM performed its ability to identify novel mTOR inhibitors, which can supply some candidates for mTOR anticancer drugs, and supply effective method for anticancer dru g discovery in future.

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HSCS:a hybrid shared cache scheduling scheme for multiprogrammed workloads

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Frontiers of Computer Science 2018年第6期12卷 1090-1104页

作者： Jingyu ZHANG Chentao WU Dingyu YANG Yuanyi CHEN Xiaodong MENG Liting XU Minyi GUO Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangsha 410004China School of Electronics and Information Shanghai Dianji UniversityShanghai 200240China

The traditional dynamic random-access memory (DRAM) storage medium can be integrated on chips via modern emerging 3D-stacking technology to architect a DRAM shared cache in multicore systems. Compared with static random-access memory (SRAM), DRAM is larger but slower. In the existing research, a lot of work has been devoted to improving the workload performance using SRAM and stacked DRAM together in shared cache systems, ranging from SRAM structure improvement to optimizing cache tags and data access. However, little attention has been paid to designing a shared cache scheduling scheme for multiprogrammed workloads with different memory footprints in multicore systems. Motivated by this, we propose a hybrid shared cache scheduling scheme that allows a multicore system to utilize SRAM and 3D-stacked DRAM efficiently, thus achieving better workload performance. This scheduling scheme employs (1) a cache monitor, which is used to collect cache statistics; (2) a cache evaluator, which is used to evaluate the cache information during the process of programs being executed; and (3) a cache switcher, which is used to self-adaptively choose SRAM or DRAM shared cache modules. A cache data migration policy is naturally developed to guarantee that the scheduling scheme works correctly. Extensive experiments are conducted to evaluate the workload performance of our proposed scheme. The experimental results showed that our method can improve the multiprogrammed workload performance by up to 25% compared with state-of-the-art methods (including conventional and DRAM cache systems).

关键词： multicore system shared cache workload performance

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Theory-screened Prussian blue analogues-based nanozymes for promoting diabetic wound healing via ferroptosis inhibition

Materials Today Bio

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Materials Today Bio 2025年 32卷 101839页

作者： Dong, Qingrong Shen, Xiaomei Fang, Ge Shi, Jia Zhu, Xiafeng Du, Jiangfeng Zhang, Hui Ge, Cuicui Department of Medical Imaging First Hospital of Shanxi Medical University Taiyuan030001 China State Key Laboratory of Radiation Medicine and Protection School of Radiation Medicine and Protection Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions Soochow University Suzhou215123 China College of Chemistry and Materials Jiangxi Normal University Nanchang330022 China Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province Taiyuan030001 China College of Pharmacy Academy of Medical Sciences Shanxi Medical University Jinzhong030619 China

Diabetes mellitus (DM) induced wound healing impairment remains a serious health problem, which can lead to limb amputation and even shorten life span. Inhibiting ferroptosis of endothelial cells has shown promise in promoting tissue repair and regeneration. However, a majority of known ferroptosis inhibitors belong to either antioxidants or iron-chelators but with poor pharmacological adherence and even serious side effects. Herein, we construct a series of Prussian blue analogues-based nanozymes as ferroptosis nano-inhibitors to simultaneously achieve highly efficient intracellular iron capture and antioxidant properties. Through computational and experimental methods, the optimized Prussian blue analogues (MPBs) with highest iron chelating efficiency and efficacy (CuPBs) are screened out and both the CuPBs and the post-chelated products have been demonstrated to exhibit reactive oxygen species (ROS)-scavenging activities. As expected, the CuPBs successfully inhibit ferroptosis in high glucose-cultured skin repair cells, thereby repairing their proliferation, migration and angiogenesis. Mechanistically, the CuPBs regulate ferroptosis by inhibiting iron accumulation and improving the antioxidant capacity of the Xc−-GPX4 system. Moreover, in a murine diabetic wound model, the CuPBs remarkably promote the wound healing by inhibiting ferroptosis and increasing the M2/M1 macrophage ratio, showing a 2-fold higher wound closure rate than deferoxamine (DFO). Collectively, our study presents a general design strategy on developing ferroptosis nano-inhibitors and provides a promising approach for treating ferroptosis-related diseases. © 2025 The Authors

关键词： Endothelial cells

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An automatic detection scheme of acute Stanford type A aortic dissection based on DCNNs in CTA images 19

An automatic detection scheme of acute Stanford type A aorti...

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4th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2019

作者： Xu, Xin He, Zhiqiang Niu, Kai Zhang, Yijie Tang, Hao Tan, Ling Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China Beijing University of Posts and Telecommunications Beijing China Guizhou Provincial Engineering Research Center for Livelihood Big Data Comprehensive Application China Department of Cardiovascular Surgery Second Xiangya Hospital Central South University Changsha Hunan China

ISBN: (纸本)9781450371711

As a severely life-threatening disease, acute Stanford type A aortic dissection brings patients with high potential of death. Computed Tomography Angiography (CTA) images become the effective diagnostic basis of aortic dissection. In this paper, we propose a scheme for automatic patient-level and site-level detection of aortic dissection based on Deep Convolutional Neural Networks (DCNNs) in order to relieve the burden on doctors and diagnose accurately and timely. Firstly, Mask R-CNN is adopted to precisely detect and segment the aorta from the original CTA images. Taking advantage of spatial continuity among CTA images, we put forward an area-wise screening method to remove a handful of unsatisfactory segmentation results. Then we process the segmented aorta images to extract the edges by Canny edge detector. Finally, two ResNets are employed in processed aorta images for aortic dissection detection. Specially, we can detect not only the ascending and descending aorta, but also the aortic arch, which may be the site of onset. We tested on over 3500 images, achieving an accuracy of 98.66% in slice-level detection, 96.51% in patient-level detection and 91.47% in site-level detection. © 2019 Association for Computing Machinery.

关键词： Deep neural networks

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A network security entity recognition method based on feature template and CNN-BiLSTM-CRF

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Frontiers of Information Technology & Electronic engineering 2019年第6期20卷 872-884页

作者： Ya QIN Guo-wei SHEN Wen-bo ZHAO Yan-ping CHEN Miao YU Xin JIN College of Computer Science and Technology Guizhou University Guiyang 550025 China Guizhou Provincial Key Laboratory of Public Big Data Guiyang 550025 China Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029 China

By network security threat intelligence analysis based on a security knowledge graph(SKG), multi-source threat intelligence data can be analyzed in a fine-grained manner. This has received extensive attention. It is difficult for traditional named entity recognition methods to identify mixed security entities in Chinese and English in the field of network security, and there are difficulties in accurately identifying network security entities because of insufficient features extracted. In this paper, we propose a novel FT-CNN-BiLSTM-CRF security entity recognition method based on a neural network CNN-BiLSTM-CRF model combined with a feature template(FT). The feature template is used to extract local context features, and a neural network model is used to automatically extract character features and text global features. Experimental results showed that our method can achieve an F-score of 86% on a large-scale network security dataset and outperforms other methods.

关键词： Network security entity Security knowledge graph (SKG) Entity recognition Feature template Neural network

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Daily CO_(2) Emission Reduction Indicates the Control of Activities to Contain COVID-19 in China

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The Innovation 2020年第3期1卷 24-36页

作者： Rong Wang Yuankang Xiong Xiaofan Xing Ruipu Yang Jiarong Li Yijing Wang Junji Cao Yves Balkanski Josep Peñuelas Philippe Ciais Didier Hauglustaine Jordi Sardans Jianmin Chen Jianmin Ma Tang Xu Haidong Kan Yan Zhang Tomohiro Oda Lidia Morawska Renhe Zhang Shu Tao Department of Environmental Science and Engineering Fudan UniversityShanghai 200438P.R.China Institute of Atmospheric Sciences Fudan UniversityShanghai 200438P.R.China Big Data Institute for Carbon Emission and Environmental Pollution Fudan UniversityShanghai 200438P.R.China Key Laboratory of Aerosol Chemistry and Physics Institute of Earth EnvironmentChinese Academy of SciencesXi'an 710075P.R.China Laboratoire des Sciences du Climat et de l’Environnement CEA CNRS UVSQ91190 Gif-sur-YvetteFrance CREAF Cerdanyola del Vallès08193 CataloniaSpain CSIC Global Ecology Unit CREAF-CSIC-UABBellaterra08193 CataloniaSpain College of Urban and Environmental Sciences Laboratory for Earth Surface ProcessesPeking University100871 BeijingP.R.China School of Public Health Key Laboratory of Public Health Safety of the Ministry of Education and National Health Commission Key Laboratory of Health Technology AssessmentFudan UniversityShanghai 200438P.R.China Universities Space Research Association ColumbiaMDUSA Global Modeling and Assimilation Office NASA Goddard Space Flight CenterGreenbeltMDUSA Queensland University of Technology 2 George StreetBrisbaneQLD 4001Australia Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092P.R.China

Lockdown measures are essential to containing the spread of coronavirus disease 2019(COVID-19),but they will slow down economic growth by reducing industrial and commercial ***,the benefits of activity control from containing the pandemic have not been examined and *** we use daily carbon dioxide(CO_(2))emission reduction in China estimated from statistical data for energy consumption and satellite data for nitrogen dioxide(NO_(2))measured by the Ozone Monitoring Instrument(OMI)as an indicator for reduced activities consecutive to a *** perform a correlation analysis to show that a 1%day-1 decrease in the rate of COVID-19 cases is associated with a reduction in daily CO_(2) emissions of 0.22%±0.02%using statistical data for energy consumption relative to emissions without COVID-19,or 0.20%±0.02%using satellite data for atmospheric column NO_(2).We estimate that swift action in China is effective in limiting the number of COVID-19 cases<100,000 with a reduction in CO_(2) emissions of up to 23%by the end of February 2020,whereas a 1-week delay would have required greater containment and a doubling of the emission reduction to meet the same *** analyzing the costs of health care and fatalities,we find that the benefits on public health due to reduced activities in China are 10-fold larger than the loss of gross domestic *** findings suggest an unprecedentedly high cost of maintaining activities and CO_(2) emissions during the COVID-19 pandemic and stress substantial benefits of containment in public health by taking early actions to reduce activities during the outbreak of COVID-19.

关键词： COVID-19 PANDEMIC CARBON EMISSION ENERGY CONSUMPTION SOCIAL CARBON COST CONTAINMENT EFFICACY PUBLIC HEALTH CORRELATION ANALYSIS INTEGRATED MODEL

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