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Stability of water yield in watersheds

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Science China Earth Sciences 2024年第2期67卷 483-496页

作者： yu YAN Zhiyong LIU Xiaohong chen Liyan HUANG Center for Water Resources and Environment School of Civil EngineeringSun Yat-Sen UniversityGuangzhou510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai519082China

The hydrological system of a watershed is intricately influenced by both underlying characteristics and climate *** the variability in water yield is essential for effective water resources management and water security in the context of changing *** this study,we adopted the Budyko framework and leveraged simulations from the CMIP6 model to investigate the compensation effects of climate and underlying characteristics on watershed water *** on Taylor expansion and Budyko framework,we estimated the sensitivity of watershed water yield to climate and underlying characteristics(the first-and second-order partial derivatives).By combining external watershed characteristics(e.g.,water yield ratios and underlying characteristics)with internal sensitivity coefficients,this study further used vine copula and principal component analysis to quantify the stability of watershed water *** findings show:(1)Water-yield changes related to underlying characteristics could be offset by climate-related water-yield changes across all climate zones,maintaining the water yield ratio steady(i.e.,the compensation effects).(2)However,global watersheds will turn more sensitive to underlying characteristics and less sensitive to climate variation in the *** climate-and underlying-related sensitivities increase in watersheds with arid climates.(3)The stability of watershed water yield will gradually diminish in the *** 1901–1950to 2051–2100,the global stability of 280 watersheds drops from 0.054 to 0.021(i.e.,stability index identified by the joint probability).Particularly,the largest change in stability of water yield reaches-0.347±0.18 in arid *** semi-arid,semihumid,and humid regions,the changes are-0.039±0.010,-0.028±0.005,and-0.005±0.002,*** findings provide a reference for the future sustainable water resources development under climate change,highlighting the vulnerability of the water resources in ari

关键词： Hydrological system stability Compensation effects on water yield Sensitivities Budyko-Fu decomposition framework Global watersheds

MUS Model:A Deep Learning-Based Architecture for IoT Intrusion Detection

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Computers, Materials & Continua 2024年第7期80卷 875-896页

作者： yu Yan yu Yang Shen Fang Minna Gao Yiding chen College of Information Engineering University of Engineering of the Chinese People’s Armed Police Force(PAP)Xi’an710000China College of Missile Engineering Rocket Force Engineering UniversityXi’an710000China

In the face of the effective popularity of the Internet of Things(IoT),but the frequent occurrence of cybersecurity incidents,various cybersecurity protection means have been proposed and *** them,Intrusion Detection System(IDS)has been proven to be stable and ***,traditional intrusion detection methods have shortcomings such as lowdetection accuracy and inability to effectively identifymalicious *** address the above problems,this paper fully considers the superiority of deep learning models in processing highdimensional data,and reasonable data type conversion methods can extract deep features and detect classification using advanced computer vision techniques to improve classification *** TransformField(MTF)method is used to convert 1Dnetwork traffic data into 2D images,and then the converted 2D images are filtered by UnsharpMasking to enhance the image details by sharpening;to further improve the accuracy of data classification and detection,unlike using the existing high-performance baseline image classification models,a soft-voting integrated model,which integrates three deep learning models,MobileNet,VGGNet and ResNet,to finally obtain an effective IoT intrusion detection architecture:the MUS *** types of experiments are conducted on the publicly available intrusion detection dataset CICIDS2018 and the IoT network traffic dataset N_BaIoT,and the results demonstrate that the accuracy of attack traffic detection is greatly improved,which is not only applicable to the IoT intrusion detection environment,but also to different types of attacks and different network environments,which confirms the effectiveness of the work done.

关键词： Cyberspace security intrusion detection deep learning Markov Transition Fields(MTF) soft voting integration

Quantum vector DC magnetometry via selective phase accumulation

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Science China(Physics,Mechanics & Astronomy) 2024年第10期Mechanics & Astronomy) .卷 16-26页

作者： Min Zhuang Sijie chen Jiahao Huang Chaohong lee Institute of Quantum Precision Measurement State Key Laboratory of Radio Frequency Heterogeneous IntegrationCollege of Physics and Optoelectronic EngineeringShenzhen University Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (Guangdong) Laboratory of Quantum Engineering and Quantum Metrology School of Physics and AstronomySun Yat-sen University (Zhuhai Campus)

Precision measurement of magnetic fields is a crucial issue in both fundamental scientific research and practical sensing technology. The sensitive detection of a vector magnetic field poses a significant challenge in quantum magnetometry, particularly in estimating a vector DC magnetic field with high precision. Here, we propose a comprehensive protocol for quantum vector DC magnetometry, utilizing selective phase accumulation in both non-entangled and entangled quantum probes. Building upon the principles of Ramsey interferometry, our protocol enables the selective accumulation of phase for a specific magnetic field component by incorporating a meticulously designed pulse sequence. In the individual measurement scheme, we employ three individual quantum interferometries to independently estimate each of the three magnetic field components. Alternatively, in the simultaneous measurement scheme, the application of a pulse sequence along different directions enables the simultaneous estimation of all three magnetic field components using only one quantum interferometry. Notably, by employing an entangled state(such as the Greenberger-Horne-Zeilinger state) as the input state, the measurement precisions of all three components may reach the Heisenberg limit. This study not only establishes a general protocol for measuring vector magnetic fields using quantum probes, but also presents a viable pathway for achieving entanglement-enhanced multi-parameter estimation.

关键词： magnetometry quantum interferometry entanglement-enhanced quantum metrology

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Automated Identification of Ordered Phases for Simulation Studies of Block Copolymers

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Chinese Journal of Polymer Science 2024年第5期42卷 683-692,I0011页

作者： yu-chen Zhang Wei-Ling Huang Yi-Xin Liu State Key Laboratory of Molecule Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai200433China

In unit cell simulations,identification of ordered phases in block copolymers(BCPs)is a tedious and time-consuming task,impeding the advancement of more streamlined and potentially automated research *** this study,we propose a scattering-based automated identification strategy(SAIS)for characterization and identification of ordered phases of BCPs based on their computed scattering *** approach leverages the scattering theory of perfect crystals to efficiently compute the scattering patterns of periodic morphologies in a unit *** the first stage of the SAIS,phases are identified by comparing reflection conditions at a sequence of Miller *** confirm or refine the identification results of the first stage,the second stage of the SAIS introduces a tailored residual between the test phase and each of the known candidate ***,our strategy incorporates a variance-like criterion to distinguish background species,enabling its extension to multi-species BCP *** has been demonstrated that our strategy achieves exceptional accuracy and robustness while requiring minimal computational ***,the approach allows for real-time expansion and improvement to the candidate phase library,facilitating the development of automated research workflows for designing specific ordered structures and discovering new ordered phases in BCPs.

关键词： Block copolymer Phase identification Scattering function

Organic interfacial engineering of gold nanowires for selective glycerol electrooxidation

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Chinese Chemical Letters 2024年第3期35卷 502-507页

作者： Zhe Wang Qingling Hong Boqiang Miao Tianjiao Wang yu Ding Pujun Jin Pei chen yu chen Key Laboratory of Macromolecular Science of Shaanxi Province Key Laboratory of Applied Surface and Colloid Chemistry(Ministry of Education)Shaanxi Key Laboratory for Advanced Energy DevicesSchool of Materials Science and EngineeringShaanxi Normal UniversityXi'an 710062China

The selective electrochemical conversion of glycerol into value-added products is a green and sustainable strategy for the biomass *** this work,Au nanowires(Au-NW)modified with polyethyleneimine(PEI)molecule(Au-NW@PEI)is obtained by an up-bottom post-modification *** characterization,molecular dynamics simulation and density functional theory demonstrate that the loose-packed PEI monolayer firmly and uniformly distribute on the Au-NW surface due to the strong Au-N *** experiments and product analysis display that PEI modification significantly enhance the electro-activity of Au-NW for the glycerol electro-oxidation reaction(GEOR)due to the electronic ***,the steric hindrance and electrostatic effect of PEI layer make the optimizing adsorption of intermediates ***,the selectivity of C3 product glyceric acid over Au-NW@PEI is increased by nearly 20%.The work thus indicates that the rational design of metal-organic interface can effectively elevate the electro-activity and selectivity of Au nanostructures,which may have wide application in biomass development.

关键词： Glycerol electrooxidation reaction Organic interface engineering Gold-based nanomaterials Electrocatalysis Selectivity

Tunable quantum dots in monolithic Fabry-Perot microcavities for high-performance single-photon sources

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Light(Science & Applications) 2024年第2期13卷 325-332页

作者： Jiawei Yang Yan chen Zhixuan Rao Ziyang Zheng Changkun Song yujie chen Kaili Xiong Pingxing chen Chaofan Zhang Wei Wu Ying yu Siyuan yu State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information TechnologySun Yat-Sen UniversityGuangzhou 510006China Institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangsha 410073China College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha 410073China Hunan Key Laboratory of Quantum Information Mechanism and Technology National University of Defense TechnologyChangsha 410073 HunanChina Hefei National Laboratory Hefei 230088China

Cavity-enhanced single quantum dots(QDs)are the main approach towards ultra-high-performance solid-state quantum light sources for scalable photonic quantum ***,harnessing the Purcell effect requires precise spectral and spatial alignment of the QDs’emission with the cavity mode,which is challenging for most *** we have successfully integrated miniaturized Fabry-Perot microcavities with a piezoelectric actuator,and demonstrated a bright single-photon source derived from a deterministically coupled QD within this *** the cavity-membrane structures,we have achieved large spectral tunability via strain *** resonance,a high Purcell factor of~9 is *** source delivers single photons with simultaneous high extraction efficiency of 0.58,high purity of 0.956(2)and high indistinguishability of 0.922(4).Together with its compact footprint,our scheme facilitates the scalable integration of indistinguishable quantum light sources on-chip,therefore removing a major barrier to the development of solid-state quantum information platforms based on QDs.

关键词： quantum removing purity

On the thermodynamics of plasticity during quasi-isentropic compression of metallic glass

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Matter and Radiation at Extremes 2024年第2期9卷 74-89页

作者： Kaiguo chen Bo chen Yinan Cui yuying yu Jidong yu Huayun Geng Dongdong Kang Jianhua Wu Yao Shen Jiayu Dai College of Science National University of Defense TechnologyChangsha 410073People’s Republic of China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense TechnologyChangsha 410073People’s Republic of China Applied Mechanics Laboratory Department of Engineering MechanicsSchool of AerospaceTsinghua UniversityBeijing 100084People’s Republic of China Institute of Fluid Physics China Academy of Engineering PhysicsMianyangPeople’s Republic of China Department of Material Science and Technology Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

Entropy production in quasi-isentropic compression (QIC) is critically important for understanding the properties of materials under extremeconditions. However, the origin and accurate quantification of entropy in this situation remain long-standing challenges. In this work, a framework is established for the quantification of entropy production and partition, and their relation to microstructural change in QIC. Cu50Zr50is taken as a model material, and its compression is simulated by molecular dynamics. On the basis of atomistic simulation-informed physicalproperties and free energy, the thermodynamic path is recovered, and the entropy production and its relation to microstructural change aresuccessfully quantified by the proposed framework. Contrary to intuition, entropy production during QIC of metallic glasses is relativelyinsensitive to the strain rate ˙γ when ˙γ ranges from 7.5 × 10^(8) to 2 × 10^(9)/s, which are values reachable in QIC experiments, with a magnitudeof the order of 10^(−2)kB/atom per GPa. However, when ˙γ is extremely high (>2 × 10^(9)/s), a notable increase in entropy production rate with˙γ is observed. The Taylor–Quinney factor is found to vary with strain but not with strain rate in the simulated regime. It is demonstrated thatentropy production is dominated by the configurational part, compared with the vibrational part. In the rate-insensitive regime, the increase inconfigurational entropy exhibits a linear relation to the Shannon-entropic quantification of microstructural change, and a stretched exponential relation to the Taylor–Quinney factor. The quantification of entropy is expected to provide thermodynamic insights into the fundamentalrelation between microstructure evolution and plastic dissipation.

关键词： entropy metallic regime

Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation

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Journal of Magnesium and Alloys 2024年第1期12卷 186-196页

作者： Sujeong Byun Jinyeong yu Seho Cheon Seong Ho lee Sung Hyuk Park Taekyung lee School of Mechanical Engineering Pusan National UniversityBusan 46241South Korea School of Materials Science and Engineering Kyungpook National UniversityDaegu 41566South Korea

Mg alloys possess an inherent plastic anisotropy owing to the selective activation of deformation mechanisms depending on the loading *** characteristic results in a diverse range of flow curves that vary with a deformation *** study proposes a novel approach for accurately predicting an anisotropic deformation behavior of wrought Mg alloys using machine learning(ML)with data *** developed model combines four key strategies from data science:learning the entire flow curves,generative adversarial networks(GAN),algorithm-driven hyperparameter tuning,and gated recurrent unit(GRU)*** proposed model,namely GAN-aided GRU,was extensively evaluated for various predictive scenarios,such as interpolation,extrapolation,and a limited dataset *** model exhibited significant predictability and improved generalizability for estimating the anisotropic compressive behavior of ZK60 Mg alloys under 11 annealing conditions and for three loading *** GAN-aided GRU results were superior to those of previous ML models and constitutive *** superior performance was attributed to hyperparameter optimization,GAN-based data augmentation,and the inherent predictivity of the GRU for *** a first attempt to employ ML techniques other than artificial neural networks,this study proposes a novel perspective on predicting the anisotropic deformation behaviors of wrought Mg alloys.

关键词： Plastic anisotropy Compression Annealing Machine learning Data augmentation

Mechanism of selective laser trabeculoplasty:a systemic review

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International Journal of Ophthalmology(English edition) 2024年第5期17卷 963-968页

作者： yu-Feng chen Wen Zeng Department of Ophthalmology Zhongnan Hospital of Wuhan UniversityWuhan 430071Hubei ProvinceChina

Although selective laser trabeculoplasty(SLT)is a recognized method for the treatment of glaucoma,the exact changes in the target tissue and mechanism for its intraocular pressure lowing effect are still *** purpose of this review is to summarize the potential mechanisms of SLT on trabecular meshwork both in vivo and in vitro,so as to reveal the potential mechanism of *** may induce immune or inflammatory response in trabecular meshwork(TM)induced by possible oxidative damage etc,and remodel extracellular *** may also induce monocytes to aggregate in TM tissue,increase Schlemm’s canal(SC)cell conductivity,disintegrate cell junction and promote permeability through autocrine and paracrine *** provides a theoretical basis for SLT treatment in glaucoma.

关键词： mechanisms selective laser trabeculoplasty glaucoma trabecular meshwork