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Understanding the local structure and thermophysical behavior of Mg-La liquid alloys via machine learning potential

International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 439-449页

作者： Jia Zhao Taixi Feng Guimin Lu National Engineering Research Center for Integrated Utilization of Salt Lake Resource East China University of Science and TechnologyShanghai 200237China Joint International Laboratory for Potassium and Lithium Strategic Resources East China University of Science and TechnologyShanghai 200237China

The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.

关键词： magnesium-lanthanum liquid alloys local structure macroscopic properties thermodynamic behavior deep potential mo-lecular dynamic simulation

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Multifaceted Disparities Associated with Translator Earnings: A Quantitative Study of Upwork Profiles

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Journal of Social Computing 2024年第1期5卷 88-100页

作者： Tyler Horan data Analytics and Computational Social science program University of Massachusetts AmherstAmherstMA 01003USA

This study aims to quantitatively explore the multifaceted determinants that influence earnings in the translation *** a dataset comprising 45000 translator profiles,the study focusses on delineating disparities correlated with demographic variables such as age,gender,home country wealth,and language *** study uses a random forest regression model to delineate the complex interaction between gender,the economic standing of a translator’s domicile country,age,and linguistic proficiency,as they relate to *** findings substantiate and,in many ways,extend existing qualitative and anecdotal evidence that has shaped the discourse in this *** rigorous empirical framework employed here can be replicated or adapted to study other sectors within the gig economy,thus contributing to a more comprehensive understanding of labour dynamics in the digital age.

关键词： translation online employment gig economy intercultural communication

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Assessing the corrosion protection property of coatings loaded with corrosion inhibitors using the real-time atmospheric corrosion monitoring technique

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 119-126页

作者： Xiaoxue Wang Lulu Jin Jinke Wang Rongqiao Wang Xiuchun Liu Kai Gao Jingli Sun Yong Yuan Lingwei Ma Hongchang Qian Dawei Zhang School of Energy and Power Engineering Beihang UniversityBeijing 100191China Beijing Institute of Space Long March Vehicle Beijing 100076China National Materials Corrosion and Protection data Center University of Science and Technology BeijingBeijing 100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China Shanghai Spaceflight Precision Machinery Institute Shanghai 201600China

The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal ***,limited studies have applied ACM to the corrosion protection properties of organic *** study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over *** with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in *** the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy *** trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface *** alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic *** with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.

关键词： atmospheric corrosion monitoring technology corrosion inhibitor coating carbon steel corrosion protection

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A Bayesian-based approach for extracting the pion charge radius from electron-electron scattering data

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Chinese Physics C 2021年第8期45卷 12-27页

作者： Alam A Hidayat Bens Pardamean Bioinformatics and data science Research Center Bina Nusantara UniversityJakarta 11480Indonesia Computer science Department BINUS Graduate Program-Master of Computer ScienceBina Nusantara UniversityJakarta 11480Indonesia

In this study,we utilize a potentially versatile Bayesian parameter approach to compute the value of the pion charge radius and quantify its uncertainty from several experimental e^(+)e^(-) datasets for the pion vector form *** employ dispersion relations to model the pion vector form factor to extract the *** model selection is used to determine the order of polynomial appearing in the form factor formulation that can be supported by the data,adapting the computation of Bayes evidence and Bayesian effective complexity based on Occam's *** findings indicate that five out of six used datasets favor the nine-parameter model for radius extraction,and accordingly,we average the radii from the *** some inconsistencies with the most updated radius values,our approach may serve as a more intuitive method of addressing parameter estimations in dispersion theory.

关键词： Bayesian complexity dispersion hadron pion

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Decreased levels of phosphorylated synuclein in plasma are correlated with poststroke cognitive impairment

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Neural Regeneration Research 2025年第9期20卷 2598-2610页

作者： Yi Wang Yuning Li Yakun Gu Wei Ma Yuying Guan Mengyuan Guo Qianqian Shao Xunming Ji Jia Liu Department of Clinical Laboratory Beijing Bo’ai HospitalChina Rehabilitation Research CenterCapital Medical UniversityBeijingChina Beijing Institute of Brain Disorders Laboratory of Brain DisordersMinistry of Science and TechnologyCollaborative Innovation Center for Brain DisordersBeijing Advanced Innovation Center for Big Data-based Precision MedicineCapital Medical UniversityBeijingChina Department of Neurosurgery Xuanwu HospitalCapital Medical UniversityBeijingChina

Poststro ke cognitive impairment is a major secondary effect of ischemic stroke in many patients;however,few options are available for the early diagnosis and treatment of this *** aims of this study were to(1)determine the specific relationship between hypoxic andα-synuclein during the occur of poststroke cognitive impairment and(2)assess whether the serum phosphorylatedα-synuclein level can be used as a biomarker for poststro ke cognitive *** found that the phosphorylatedα-synuclein level was significantly increased and showed pathological aggregation around the cerebral infa rct area in a mouse model of ischemic *** addition,neuronalα-synuclein phosphorylation and aggregation were observed in the brain tissue of mice subjected to chronic hypoxia,suggesting that hypoxia is the underlying cause ofα-synuclein-mediated pathology in the brains of mice with ischemic *** phosphorylatedα-synuclein levels in patients with ischemic stroke were significantly lower than those in healt hy subjects,and were positively correlated with cognition levels in patients with ischemic ***,a decrease in serum high-density lipoprotein levels in stroke patie nts was significantly correlated with a decrease in phosphorylatedα-synuclein *** ischemic stroke mice did not show significant cognitive impairment or disrupted lipid metabolism 14 days after injury,some of them exhibited decreased cognitive function and reduced phosphorylatedα-synuclein *** together,our results suggest that serum phosphorylatedα-synuclein is a potential biomarker for poststroke cognitive impairment.

关键词： biomarker high-density lipoprotein ischemic stroke phosphorylatedα-synuclein poststroke cognitive impairment

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Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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Computer Modeling in Engineering & sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and data science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics Engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia Department of Computer science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia Department of Computer science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

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Existence and Global Exponential Stability of Pseudo Almost Periodic Solutions of a General Delayed BAM Neural Networks

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Journal of Systems science & Complexity 2018年第3期31卷 608-620页

作者： DUAN Lian School of Mathematics and Big data Anhui University of Science and Technology

This paper studies a class of general BAM neural networks with multiple delays. Em- ploying the exponential dichotomy theory and fixed point method, together with constructing suitable Lyapunov functionals, easily verifiable delay-independent criteria are established to ensure the exis- tence and global exponential stability of pseudo almost periodic solutions, which not only generalize but also complement some existing ones. These theoretical results are also supported with numerical simulations.

关键词： General BAM neural network global exponential stability pseudo almost periodic solu-tion

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MashReDroid: enabling end-user creation of Android mashups based on record and replay

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science China(Information sciences) 2020年第10期63卷 54-73页

作者： Jiahuan ZHENG Liwei SHEN Xin PENG Hongchi ZENG Wenyun ZHAO School of Computer science Fudan University Shanghai Key Laboratory of data science Fudan University

To allow end users to combine different apps for accomplishing various goals, it is desired that they can create mashups of mobile apps in an on-demand fashion. The end user creation of mobile mashups,however, is complicated by the fact that many apps do not expose interfaces for mashup and the lack of user friendly interfaces for end user programming. In this paper, we propose MashReDroid, an end user programming approach for the creation of Android mashups that incorporates the behaviors of backend apps into the execution of a host app. MashReDroid automatically transforms Android apps into mashup enabled apps. It then allows end users to create mashups by recording the interactions between host apps and backend apps and run mashups by replaying the interactions. Our evaluation shows that MashReDroid supports a variety of real scenarios and users can easily create and use mashups with a very low overhead.

关键词： end user programming human computer interaction Android mashup app transformation

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On the Pathwise Uniqueness of Solutions of One-dimensional Reflected Stochastic Differential Equations with Jumps

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 149-163页

作者： Hua Zhang School of Statistics and data science&Key Laboratory of data science in Finance and Economics Jiangxi University of Finance and EconomicsNanchang330013China

In this paper, we are concerned with the problem of the pathwise uniqueness of one-dimensional reflected stochastic differential equations with jumps under the assumption of non-Lipschitz continuous coefficients whose... 详细信息

关键词： reflected diffusion processes with jumps pathwise uniqueness local time Meyer It?'s formula

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False Negative Sample Detection for Graph Contrastive Learning

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Tsinghua science and Technology 2024年第2期29卷 529-542页

作者： Binbin Zhang Li Wang College of data science Taiyuan University of TechnologyJinzhong 030600China

Recently,self-supervised learning has shown great potential in Graph Neural Networks (GNNs) through contrastive learning,which aims to learn discriminative features for each node without label information. The key to graph contrastive learning is data augmentation. The anchor node regards its augmented samples as positive samples,and the rest of the samples are regarded as negative samples,some of which may be positive samples. We call these mislabeled samples as “false negative” samples,which will seriously affect the final learning effect. Since such semantically similar samples are ubiquitous in the graph,the problem of false negative samples is very significant. To address this issue,the paper proposes a novel model,False negative sample Detection for Graph Contrastive Learning (FD4GCL),which uses attribute and structure-aware to detect false negative samples. Experimental results on seven datasets show that FD4GCL outperforms the state-of-the-art baselines and even exceeds several supervised methods.

关键词： graph representation learning contrastive learning false negative sample detection

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