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arXiv 2023年

作者： Chen, xuwen Shen, Shunlin zhang, Zhifei Department of Mathematics University of Rochester RochesterNY14627 United States School of Mathematical Sciences Peking University Beijing100871 China

We study the mean-field and semiclassical limit of the quantum many-body dynamics with a repulsive δ-type potential N3βV (Nβx) and a Coulomb potential, which leads to a macroscopic fluid equation, the Euler-Poisson equation with pressure. We prove quantitative strong convergence of the quantum mass and momentum densities up to the first blow up time of the limiting equation. The main ingredient is a functional inequality on the δ-type potential for the almost optimal case β ∈ (0, 1), for which we give an analysis of the singular correlation structure between particles. Copyright © 2023, The Authors. All rights reserved.

关键词： Poisson equation

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Anomaly Detection for Multivariate Time Series Based on Contrastive Learning and Autoformer

Anomaly Detection for Multivariate Time Series Based on Cont...

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International Conference on Computer Supported Cooperative Work in Design

作者： xuwen Shang Jue zhang Xingguo Jiang Hong Luo Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications Beijing China Department of Computer Science and Engineering Beihang University Beijing China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Nowadays, due to the increasingly complex and huge data flow, anomaly detection has become an important technology to ensure the high security and reliability of the systems. It helps identify unusual observations in the data, thereby protecting safety and reducing risk. However, in the field of multivariate temporal anomaly detection, there are still some difficulties in spatio-temporal correlation mining of variables, generalization ability in dealing with complex temporal sequences, and feature learning under different granularity. Therefore, we propose an unsupervised anomaly detection method for multivariate time series based on contrastive learning and Autoformer autoencoder. In order to fully explore the spatio-temporal correlation of time series data, this paper uses Graph Attention Network and Auto-Correlation to jointly learn spatio-temporal correlation, and obtain positive and negative pairs through time-domain and frequency-domain data augmentation. Finally, the Autoformer autoencoder is used for anomaly detection in a predictive manner. In the loss function section, a joint loss function is formed by introducing contrastive learning losses at the time step and time window granularity, combined with prediction loss, to improve the learning effect. This paper investigates the performance of the proposed method through experiments on the SMAP and MSL public datasets, and achieves better results than baseline methods.

关键词： Correlation Computational modeling Time series analysis Contrastive learning Computer architecture Stability analysis Safety

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WELL/ILL-POSEDNESS OF THE BOLTZMANN EQUATION WITH SOFT POTENTIAL

arXiv

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arXiv 2023年

We consider the Boltzmann equation with the soft potential and angular cutoff. Inspired by the methods from dispersive PDEs, we establish its sharp local well-posedness and ill-posedness in Hs Sobolev space. We find the well/ill-posedness separation at regularity s = d−21, strictly 21-derivative higher than the scaling-invariant index s = d−22, the usually expected separation point. Copyright © 2023, The Authors. All rights reserved.

关键词： Boltzmann equation

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Hydrogels for the removal of the methylene blue dye from wastewater: a review

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ENVIRONMENTAL CHEMISTRY LETTERS 2022年第4期20卷 2665-2685页

作者： Yang, Yinchuan Zhu, Qinlin Peng, xuwen Sun, Jingjing Li, Cong zhang, Xinmiao zhang, Hao Chen, Jiabin Zhou, Xuefei Zeng, Hongbo zhang, Yalei Tongji Univ Coll Environm Sci & Engn State Key Lab Pollut Control & Resources Reuse Shanghai 200092 Peoples R China Tongji Univ Shanghai Inst Pollut Control & Ecol Secur Shanghai 200092 Peoples R China Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G IH9 Canada Univ Shanghai Sci & Technol Coll Environm & Architecture Shanghai 200093 Peoples R China Sinopec Beijing Res Inst Chem Ind Environm Protect Res Inst Beijing 100013 Peoples R China

Water pollution is a major environmental issue with the rapid development of industry. Therefore, advanced technologies and materials are needed to remove pollutants from contaminated waters. The adsorption process displays many advantages such as high adaptability and removal efficiency for water sources of varying quality. Hydrogels have recently attracted attention due to their high adsorption capacity and structural stability, yet several issues remain to be explored, such as the number of reuse and engineering applications. Here, we review hydrogels for the removal of methylene blue from wastewater, with focus on hydrogel preparation and properties, adsorption performance and mechanisms, reusability and comparison with biological and chemical oxidation methods.

关键词： Hydrogel Methylene blue Adsorption Dye Wastewater treatment

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PEcnv: accurate and efficient detection of copy number variations of various lengths

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BRIEFINGS IN BIOINFORMATICS 2022年第5期23卷 bbac375-bbac375页

作者： Wang, xuwen Xu, Ying Liu, Ruoyu Lai, Xin Liu, Yuqian Wang, Shenjie zhang, Xuanping Wang, Jiayin Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian Peoples R China Xi An Jiao Tong Univ Sch Comp Sci & Technol Med Informat Xian Peoples R China

Copy number variation (CNV) is a class of key biomarkers in many complex traits and diseases. Detecting CNV from sequencing data is a substantial bioinformatics problem and a standard requirement in clinical practice. Although many proposed CNV detection approaches exist, the core statistical model at their foundation is weakened by two critical computational issues: (i) identifying the optimal setting on the sliding window and (ii) correcting for bias and noise. We designed a statistical process model to overcome these limitations by calculating regional read depths via an exponentially weighted moving average strategy. A one-run detection of CNVs of various lengths is then achieved by a dynamic sliding window, whose size is self-adopted according to the weighted averages. We also designed a novel bias/noise reduction model, accompanied by the moving average, which can handle complicated patterns and extend training data. This model, called PEcnv, accurately detects CNVs ranging from kb-scale to chromosome-arm level. The model performance was validated with simulation samples and real samples. Comparative analysis showed that PEcnv outperforms current popular approaches. Notably, PEcnv provided considerable advantages in detecting small CNVs (1 kb-1 Mb) in panel sequencing data. Thus, PEcnv fills the gap left by existing methods focusing on large CNVs. PEcnv may have broad applications in clinical testing where panel sequencing is the dominant strategy.

关键词： genomics sequencing data analysis variant detection copy number variation (CNV) exponentially weighted moving average clinical panel sequencing

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SHARP GLOBAL WELL-POSEDNESS AND SCATTERING OF THE BOLTZMANN EQUATION

arXiv

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arXiv 2023年

We consider the 3D Boltzmann equation for the Maxwellian particle and soft potential with an angular cutoff. We prove sharp global well-posedness with initial data small in the scaling-critical space. The solution also remains in L1 if the initial datum is in L1, even at such low regularity. The key to existence, uniqueness and regularity criteria is the new bilinear spacetime estimates for the gain term, the proof of which is based on novel techniques from nonlinear dispersive PDEs including the atomic U-V spaces, multi-linear frequency analysis, dispersive estimates, etc. To our knowledge, this is the first 3D sharp global result for the Boltzmann equation. Copyright © 2023, The Authors. All rights reserved.

关键词： Boltzmann equation

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Thermal-mechanical coupling in drilling high-performance CFRP: Scale-span modeling and experimental validation

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COMPOSITE STRUCTURES 2024年 331卷

作者： Liu, Yong Pan, Zitao zhang, Hao Jing, xuwen Zhou, Honggen Chen, Yong Jiangsu Univ Sci & Technol Coll Mech Engn Zhenjiang 212003 Peoples R China Yancheng Inst Technol Sch Automot Engn Yancheng 224051 Peoples R China

The focus of this study is to explore a scale -span thermal-mechanical coupling method for predicting the dynamic mechanical progressive failure behaviors and predicting thermal damage during the drilling process of Carbon Fiber Reinforced Plastic (CFRP). Initially, a thermal conduction constitutive model of drilling CFRP was developed based on the proposed thermal distribution ratio calculation method. Meanwhile, a dynamic spanscale progressive damage constitutive model for CFRP, incorporating modified micromechanics failure criterion with bilinear damage evolution laws, was proposed, and a bilinear cohesive model, including three damage modes, is employed to simulate interlaminar delamination. Subsequently, a user -defined material subroutine VUMAT was implemented on the ABAQUS/Explicit platform to simulate the thermal-mechanical coupling behaviors of drilling T700S-12K/YPH-23 CFRP using a twist drill bit. Finally, a comprehensive information monitoring platform for CFRP drilling experiments was established to validate the accuracy of the simulation results by considering drilling temperature, thrust force, and hole -wall morphology. The results demonstrate excellent agreement between the established thermal-mechanical coupling span -scale model and the experimental data. Furthermore, the simulation effectively captures the various damage behaviors and thermal conduction phenomenon, that occur during the intact drilling process.

关键词： CFRP Drilling Scale -span Thermal -mechanical coupling Progressive failure

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Combined Separated Oscillatory Fields Technique

Combined Separated Oscillatory Fields Technique

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European Frequency and Time Forum (EFTF)

作者： Fuyu Sun Chao Li xuwen Hu Shougang zhang National Time Service Center Chinese Academy of Sciences Xi'an China Key Laboratory of Time Reference and Applications Chinese Academy of Sciences Xi'an China

ISBN: (数字)9798350354270

ISBN: (纸本)9798350354287

Ramsey's method of separated oscillatory fields (SOFs) has been originally used in beam magnetic resonance apparatuses, which leads to the establishment of atomic definition of time interval and frequency. Since then, various versions of the SOFs technique have been widely used for precise measurement of different physical quantities. Here, we present an alternative method to generate atomic beam magnetic resonance signals by combining two Ramsey cavities with phase differences of 0 and 1t. It is found that the strength of the resonance signals generated using this combined SOFs technique is approximately twice that of the resonance signals produced by the conventional SOFs techniques. In addition to generating stronger resonance, the combined Ramsey method eliminates the Rabi background superimposed on the Ramsey interference pattern without increasing the Ramsey signal linewidth. Thus, this technique serves a promising tool for high-precision measurements.

关键词： Atomic measurements Time-frequency analysis Magnetic field measurement Atomic beams Magnetic resonance Europe Interference

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Recent advances in coacervation and underlying noncovalent molecular interaction mechanisms

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PROGRESS IN POLYMER SCIENCE 2024年 153卷

作者： Peng, Qiongyao Wang, Tao Yang, Diling Peng, xuwen zhang, Hao Zeng, Hongbo Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G1H9 Canada

Coacervation is a liquid-liquid phase separation phenomenon. It involves the formation of a dense coacervate phase, rich in concentrated materials, and a co-existing immiscible dilute supernatant. This phenomenon can occur either from a homogeneous aqueous solution (simple coacervation) or when two different macromolecular aqueous solutions (proteins, polymers, and colloids) are brought into contact (complex coacervation). Coacervation has historical significance as it may have played a role in the origin of life, concentrating nutritious materials through liquid-liquid phase separation. It also reveals the underlying mechanisms of many biological phenomena such as intracellular biomolecular condensates, extracellular matrices, squid beak's gradient properties, sessile organism's wet adhesion, Alzheimer's diseases, and more. Coacervation provides insights and inspires promising solutions in areas like artificial cells/tissues, gradient materials, gene/drug delivery, underwater adhesives, and beyond. The driving forces of coacervation are noncovalent molecular interactions, often referred to as 'chemistry beyond the molecule', including hydrophobic interaction, electrostatic interaction, hydrogen-bonding interaction, cation- zr interaction, zr - zr interaction, multivalency, etc. In this work, we have systematically reviewed the underlying noncovalent molecular interactions of simple coacervation and complex coacervation, respectively. We summarize commonly used materials and their corresponding molecular structures, dis cussing their applications. Some remaining challenge issues and perspectives for future studies are also presented. Understanding the underlying noncovalent molecular interactions of coacervation, alongside insights into molecular compositions and structures, can better guide the design of novel materials, elucidate various biological phenomena, and contribute to the development and optimization of relevant engineering technologies. (c) 2024 The Auth

关键词： Simple coacervation Complex coacervation Noncovalent molecular interactions Liquid-liquid phase separation LLPS

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A novel finer soil strength mapping framework based on machine learning and remote sensing images

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COMPUTERS & GEOSCIENCES 2024年 182卷

作者： Wang, Ruizhen Wan, Siyang Chen, Weitao Qin, xuwen zhang, Guo Wang, Lizhe China Univ Geosci Key Lab Geol Survey & Evaluat Minist Educ Wuhan 430074 Peoples R China China Univ Geosci Fac Comp Sci Wuhan 430074 Peoples R China China Geol Survey Basic Survey Dept 45 Fuwai St Beijing 100037 Peoples R China

Soil strength is an important factor for assessing the vehicle trafficability in the wilds and making reliable offroad path planning. Rating Cone index (RCI) has been widely used as an indicator of soil strength for mobility assessment. Currently, regional RCI are mainly obtained by using Soil Moisture Strength Prediction (SMSP) Model based on the Unified Soil Classification System (USCS) soil types and soil moisture at critical depth. However, USCS classification is inaccessible directly in most soil databases. And current soil moisture products are of coarse spatial resolution and only reliable in soil surface layer. It is costly to arrange ground survey for USCS soil type and the fine soil moisture in deeper layers cannot be obtained directly. To fill this gap, a novel framework is proposed to generate finer RCI-based soil strength map. To gain USCS soil classification in an un-surveyed study site, RF, GBDT, XGBoost and LCE ensemble learning models were trained with data from gSSURGO Database which contains USCS soil types and soil properties, and then make prediction on data from SoilGrids Database by using same properties. Then, to obtain the finer soil moisture of critical depth, these treebased models were constructed with ground observation data, Sentinel-2 images, topographical data and soil properties with higher spatial resolution. The SMSP model is finally used to generate the finer daily soil strength map for the study site. The proposed framework highly improved the resolution and reliability of existing soil strength map generating methods, and can provide detailed soil strength information.

关键词： Soil strength Rating cone index Machine learning Soil moisture

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