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Enhanced removal of phosphonates from aqueous solution using PMS/UV/hydrated zirconium oxide process

Chinese Chemical Letters 2023年第4期34卷 384-389页

作者： Shunlong Pan Xi Nie Xinrui Guo Hao Hu Biming Liu Yongjun Zhang School of Environmental Science and Engineering Nanjing Tech UniversityNanjing 210009China College of Environment Hohai UniversityNanjing 210098China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Traditional treatment processes cannot completely remove phosphonates in circulating cooling water by one-step method. Herein, we designed peroxymonosulfate/UV irradiation/hydrated zirconium oxide(PMS/UV/HZO) coupling process to enhance the phosphonates removal. In particular, nitrilotrismethylenephosphonic acid(NTMP) removal efficiency by PMS/UV/HZO process was much higher than that of PMS/UV process, UV/HZO process and other processes in comparison experiments. Specifically,almost 97.2% NTMP in water was degraded, and the total phosphorous(TP) reduced from 9.3 mg/L to 0.26 mg/L at pH 7 within 180 min. TP removal efficiency still reached above 90% after 5 cycles adsorptiondesorption of HZO. Moreover, Cl^(-), NO_(3)-and SO_(4)^(2-)ions all had negligible effect on NTMP removal. During the process, NTMP was first destroyed to form phosphates and other intermediates by the reactive oxygen species(ROS), then phosphates were in situ immobilized via HZO adsorption. Sulfate radical(SO_(4)^(·-))has been confirmed to be the major ROS in the reaction system by quenching experiment and electron paramagnetic resonance(EPR) characterization. And the excellent selective adsorption capacity of HZO for phosphate produced was attributed to the strong inner-sphere coordination between H_(2)PO_(4)-/HPO_(4)^(2-)and Zr-OH on the surface of HZO. These results suggest that PMS/UV/HZO process is a promising technique for enhanced phosphonates decontamination.

关键词： Phosphonates Peroxymonosulfate UV ROS Adsorption

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An inverse design method for supercritical airfoil based on conditional generative models

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Chinese Journal of Aeronautics 2022年第3期35卷 62-74页

作者： Jing WANG Runze LI Cheng HE Haixin CHEN Ran CHENG Chen ZHAI Miao ZHANG Shanghai Aircraft Design and Research Institute Shanghai 200436China School of Aerospace Engineering Tsinghua UniversityBeijing 100084China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

Inverse design has long been an efficient and powerful design tool in the aircraft *** this paper,a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learning.A Conditional Variational Auto Encoder(CVAE)and an integrated generative network CVAE-GAN that combines the CVAE with the Wasserstein Generative Adversarial Networks(WGAN),are conducted as generative *** are used to generate target wall Mach distributions for the inverse design that matches specified features,such as locations of suction peak,shock and aft *** and quantitative results show that both adopted generative models can generate diverse and realistic wall Mach number distributions satisfying the given *** CVAE-GAN model outperforms the CVAE model and achieves better reconstruction accuracies for all the samples in the ***,a deep neural network for nonlinear mapping is adopted to obtain the airfoil shape corresponding to the target wall Mach number *** performances of the designed deep neural network are fully demonstrated and a smoothness measurement is proposed to quantify small oscillations in the airfoil surface,proving the authenticity and accuracy of the generated airfoil shapes.

关键词： Conditional Variational AutoEncoder(CVAE) Deep learning Generative Adversarial Networks(GAN) Generative models Inverse design Supercritical airfoil

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DeepHBSP:A Deep Learning Framework for Predicting Human Blood-Secretory Proteins Using Transfer Learning

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Journal of Computer science & Technology 2021年第2期36卷 234-247页

作者： Wei Du Yu Sun Hui-Min Bao Liang Chen Ying Li Yan-Chun Liang Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and TechnologyJilin UniversityChangchun 130012China Department of Computer Science College of EngineeringShantou UniversityShantou 515063China Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Zhuhai 519041China

The identification of blood-secretory proteins and the detection of protein biomarkers in the blood have an important clinical application *** methods for predicting blood-secretory proteins are mainly based on traditional machine learning algorithms,and heavily rely on annotated protein *** traditional machine learning algorithms,deep learning algorithms can automatically learn better feature representations from raw data,and are expected to be more promising to predict blood-secretory *** present a novel deep learning model(DeepHBSP)combined with transfer learning by integrating a binary classification network and a ranking network to identify blood-secretory proteins from the amino acid sequence information *** loss function of DeepHBSP in the training step is designed to apply descriptive loss and compactness loss to the binary classification network and the ranking network,*** feature extraction subnetwork of DeepHBSP is composed of a multi-lane capsule ***,transfer learning is used to train a highly accurate generalized model with small samples of blood-secretory *** main contributions of this study are as follows:1)a novel deep learning architecture by integrating a binary classification network and a ranking network is proposed,superior to existing traditional machine learning algorithms and other state-of-the-art deep learning architectures for biological sequence analysis;2)the proposed model for blood-secretory protein prediction uses only amino acid sequences,overcoming the heavy dependence of existing methods on annotated protein features;3)the blood-secretory proteins predicted by our model are statistically significant compared with existing blood-based biomarkers of cancer.

关键词： blood-secretory protein deep learning capsule network transfer learning

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Adaptive Edge Finite Element Method and Numerical Design for Metasurface Cloak

SSRN

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SSRN 2023年

作者： Yang, Wei Wang, Tiancheng Mao, Jiangqiong Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

Metasurfaces are a type of metamaterial that have two-dimensional structures. In comparison to traditional metamaterials, metasurfaces have several advantages such as being lightweight, easily controllable, and simple to design. This paper outlines the phase matching principle and constitutive parameter theory of electromagnetic (EM) metasurfaces, as well as the constitutive parameter analysis and model equations for metasurface cloaks. Due to the singularity of metasurface cloaks, an adaptive edge finite element method (AEFEM) is developed in this paper. Additionally, the convergence theory of time-harmonic Maxwell’s equations for metasurface cloak is established under the T-coercivity assumption. The numerical simulations of arc-shaped metasurface cloaks have confirmed the accuracy of our model and numerical theory. Furthermore, we have utilized our numerical method to design a triangular-shaped metasurface cloak with fewer singularities. © 2023, The Authors. All rights reserved.

关键词： Maxwell equations

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Removing microplastics from aquatic environments:A critical review

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Environmental science and Ecotechnology 2023年第1期13卷 37-53页

作者： Yusheng Pan Shu-Hong Gao Chang Ge Qun Gao Sijing Huang Yuanyuan Kang Gaoyang Luo Ziqi Zhang Lu Fan Yongming Zhu Ai-Jie Wang School of Chemistry and Chemical Engineering Harbin Institute of TechnologyHarbin150090China State Key Laboratory of Urban Water Resource and Environment School of Civil&Environmental EngineeringHarbin Institute of Technology ShenzhenShenzhen518055China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Department of Ocean Science and Engineering Southern University of Science and TechnologyShenzhenChina Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) GuangzhouChina Key Laboratory of Environmental Biotechnology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing100085China

As one of the typical emerging contaminants,microplastics exist widely in the environment because of their small size and recalcitrance,which has caused various ecological *** paper summarizes current adsorption and removal technologies of microplastics in typical aquatic environments,including natural freshwater,marine,drinking water treatment plants(DWTPs),and wastewater treatment plants(WWTPs),and includes abiotic and biotic degradation technologies as one of the removal ***,numerous studies have shown that enrichment technologies have been widely used to remove microplastics in natural freshwater environments,DWTPs,and *** removal of microplastics via WWTPs is critical to reduce the release to the natural environment as a key connection point to prevent the transfer of microplastics from society to natural water *** technology has outstanding pre-degradation effects on microplastics,and the isolated microbial strains or enriched communities can degrade up to 50%or more of pre-processed ***,more research focusing on microplastic degradation could be carried out by combining physical and chemical pretreatment with subsequent microbial *** addition,the current recovery technologies of microplastics are introduced in this *** is incredibly challenging because of the small size and dispersibility of microplastics,and the related technologies still need further *** paper will provide theoretical support and advice for preventing and controlling the ecological risks mediated by microplastics in the aquatic environment and share recommendations for future research on the removal and recovery of microplastics in various aquatic environments,including natural aquatic environments,DWTPs,and WWTPs.

关键词： Aquatic environment Enrichment and removal Microplastics Wastewater treatment plants

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A Simple Building Block with Noncovalently Conformational Locks towards Constructing Low-Cost and High-Performance Nonfused Ring Electron Acceptors

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Chinese Journal of Polymer science 2023年第4期41卷 556-563,I0008页

作者： Xiao-Bin Gu Jin-Hua Gao Zi-Yang Han Yu-Hao Shi Ya-Nan Wei Yin-Cheng Zhang Qian Peng Zhi-Xiang Wei Xin Zhang Hui Huang College of Materials Science and Opto-Electronic Technology Center of Materials Science and Optoelectronics EngineeringCAS Center for Excellence in Topological Quantum ComputationCAS Key Laboratory of Vacuum PhysicsUniversity of Chinese Academy of SciencesBeijing100049China School of Chemical Sciences University of Chinese Academy of SciencesBeijing100049China CAS Key Laboratory of Nanosystem and Hierarchical Fabrication CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing100190China

Nonfused ring electron acceptors(NFREAs)have attracted much attention due to their concise synthetic routes and low ***,developing high-performance NFREAs with simple structure remains a great *** this work,a simple building block(POBT)with noncovalently conformational locks(No CLs)was designed and ***-crystal X-ray study indicated the presence of S…O NOCLs in POBT,thus enabling it to possess a coplanar conformation comparable to that of fused-ring *** novel NFREAs based on CPT and POBT were developed,namely TT-CPT and TT-POBT,***,TT-POBT possessed a smaller Stokes shift and a reduced reorganization energy compared with TT-CPT,indicating the introduction of S…O No CLs can enhance the molecular rigidity even if simplifying the molecular *** a result,the TT-POBT-based PSC device afforded an impressive power conversion efficiency of 11.15%,much higher than that of TT-CPT counterpart(7.03%),mainly resulting from the tighterπ-πstacking,improved and balanced charge transport,and more favorable film *** work demonstrates the potential of the simple building block POBT with No CLs towards constructing low-cost and highperformance NFREAs.

关键词： Polymer solar cells Nonfused ring electron acceptors Simple building block Noncovalent conformation locks Reorganization energy

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Enhancing Nested Named Entity Recognition in Chinese EMRs: A Collaborative Approach

Enhancing Nested Named Entity Recognition in Chinese EMRs: A...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Yue, Hongtao Feng, Xiaoyue Xu, Hanchi Chu, Haoxuan Wang, Yushi Guan, Renchu Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Changchun China First Hospital Jilin University Cardiovascular Center Changchun China

ISBN: (纸本)9798350386226

Named entity recognition (NER) in electronic medical records (EMRs) is critical for identifying medical entities, constructing medical knowledge graphs, and supporting clinical decision-making. However, the scarcity of EMR datasets and the challenges posed by the complexity of Chinese medical texts hinder progress in this area. To address these issues, we introduce CMR-NER, a nested named entity recognition model that enhances entity prediction by integrating multiple features and considering a global view of entity boundaries. Leveraging the robust generalization capabilities of the large language model, CMR-NER involves collaboration with medical experts to ensure accuracy and reduce annotation costs. Additionally, we present HF-NER, a high-quality dataset specifically curated for Chinese EMR entity recognition focusing on heart failure. This dataset, constructed through a methodology combining ChatGPT's capabilities and expert validation, is a significant contribution to the field. It facilitates a comprehensive evaluation of CMR-NER. Experimental results demonstrate that our approach achieves comparable or superior performance to existing methods, underscoring its effectiveness in this challenging domain. © 2024 IEEE.

关键词： Electronic health record

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Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions:progress in efficacy and geographic equality

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National science Review 2024年第2期11卷 103-113页

作者： Tao Xue Ruohan Wang Meng Wang Yanying Wang Dan Tong Xia Meng Conghong Huang Siqi Ai Fangzhou Li Jingyuan Cao Mingkun Tong Xueqiu Ni Hengyi Liu Jianyu Deng Hong Lu Wei Wan Jicheng Gong Shiqiu Zhang Tong Zhu Institute of Reproductive and Child Health National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics Ministry of Education Key Laboratory of Epidemiology of Major Diseases(PKU) School of Public Health Peking University Health Science Centre State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health Peking University Advanced Institute of Information Technology Peking University Department of Epidemiology and Environmental Health School of Public Health and Health ProfessionsUniversity at Buffalo State Key Joint Laboratory of Environment Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking University Department of Earth System Science Tsinghua University School of Public Health Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of HealthFudan University College of Land Management Nanjing Agricultural University National&Local Joint Engineering Research Center for Rural Land Resources Use and Consolidation Clean Air Asia

Clean air actions （CAAs） in China have been linked to considerable benefits in public ***,whether the beneficial effects of CAAs are equally distributed geographically is *** high-resolution maps of the distributions of major air pollutants (fine particulate matter[PM2.5]and ozone[O3]) and population,we aimed to track spatiotemporal changes in health impacts from,and geographic inequality embedded in,the reduced exposures to PM2.5and O3from 2013 to *** used a method established by the Global Burden of Diseases *** analyzing the changes in loss of life expectancy（LLE） attributable to PM2.5and O3,we calculated the gain of life expectancy （GLE） to quantify the health benefits of the air-quality ***,we assessed the geographic inequality embedded in the GLE using the Gini index （GI）.Based on risk assessments of PM2.5and O3,during the first stage of CAAs（2013 to 2017）,the mean GLE was 1.87 *** of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed （GI 0.44）.During the second stage of CAAs（2017 to 2020）,the mean GLE increased to 3.94 months and geographic inequality decreased （GI 0.18）.According to our assessments,CAAs were enhanced,from the first to second stages,in terms of not only preventing premature mortality but also ameliorating health *** enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5and *** findings will contribute to optimizing future CAAs.

关键词： clean air action public health inequality fine particulate matter ozone

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Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms 13

Last-X-Generation Archiving Strategy for Multi-Objective Evo...

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13th IEEE Congress on Evolutionary computation, CEC 2024

作者： Shu, Tianye Nan, Yang Shang, Ke Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Southern University of Science and Technology Shenzhen518055 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

ISBN: (纸本)9798350308365

For evolutionary multi-objective optimization algorithms (EMOAs), an external archive can be utilized for saving good solutions found throughout the evolutionary process. Recent studies showed that a solution set selected from an external archive is usually superior to the final population. That is, the incorporation of an external archive improves the performance of EMOAs. However, the computation time for maintaining an external archive is long, especially when the archive size is large. To solve this issue, a simple archiving strategy is to save all solutions generated in the last several generations. In this paper, we examine this archiving strategy for three representative EMOAs on artificial test problems (Minus-DTLZ and WFG) and real-world problems (RE). Our results show that archiving the last several generations clearly improves the performance of EMOAs without severely increasing the computation time. © 2024 IEEE.

关键词： Optimization algorithms

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2.5D ASF-UNet: Adjacent Slice Spatial Feature Fusion Model for WMH Segmentation from 3D MR Brain Image

2.5D ASF-UNet: Adjacent Slice Spatial Feature Fusion Model f...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Huang, Lan Sun, Yinglu Zhao, Ziqi Guo, Chunjie Wang, Yan College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun China The First Hospital of Jilin University Department of Radiology Changchun China

ISBN: (纸本)9798350386226

Segmenting brain white matter hyperintensities (WMH) from 3D Magnetic Resonance (MR) images is crucial for the diagnosis, treatment, and prognosis of Multiple Sclerosis (MS). Unlike common 2D images, this task is more challenging and time-consuming. Classical deep learning methods for 3D image segmentation face two main challenges: 1) Pure 3D networks have more parameters and are prone to overfitting. 2) When using 2D networks to segment slices of 3D images, the lack of 3D structural information results in suboptimal segmentation after reconstruction. To address these difficulties, we propose the 2.5D ASF-UNet, which employs the 2.5D workflow and uses adjacent slices as the input for 2D segmentation network ASF-UNet. In ASF-UNet, separate down-sampling paths are used for the adjacent slices, and the Local Spatial Attention Module (LSAM) is designed to more effectively integrate 3D spatial information into the 2D network. Additionally, the Conv-Spectral-Block (CSB) is designed to extract and integrate local and global features. It allows the model to capture global spatial structures while preserving detailed information. Experimental results on MICCAI MSSEG 2016 and Local MS datasets show that 2.5D ASF-UNet achieve better segmentation performance than other deep learning methods. © 2024 IEEE.

关键词： Image segmentation

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