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The Bright Single Pulse Emission from PSR B1133+16

Research in Astronomy and Astrophysics 2024年第4期24卷 253-261页

作者： Jun Tan zhi-Gang Wen Zhen wang xue-Feng Duan Hong-Guang wang Na wang Vishal Gajjar Jian-Ping Yuan Rai Yuen Wen-Ming Yan Jian-Ling Chen Wei Han Hui wang Cheng-Bing Lyu Ai-Jun Dong Maths and Information Technology School Yuncheng UniversityYuncheng 044000China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China Xinjiang Key Laboratory of Radio Astrophysics Urumqi 830011China School of Physics and Materials Science Guangzhou UniversityGuangzhou 510006China Space Science Laboratory University of CaliforniaBerkeley 94710USA Department of Physics and Electronic Engineering Yuncheng UniversityYuncheng 044000China School of Physics and Electronic Science Guizhou Normal UniversityGuiyang 550025China

We have conducted a comprehensive investigation into the bright single pulse emission from PSR B1133+16using the Giant Metrewave Radio *** time resolution data(61μs)were obtained at a center frequency of 322 MHz with a bandwidth of 32 MHz over a continuous observation period of 7.45 hr.A total of 1082 bright pulses were sporadically detected with peak flux densities ranging from 10 to 23 times stronger than the average pulse ***,no giant pulse-like emission with a relative pulse energy larger than 10 and extremely short duration was detected,indicating that these bright pulses cannot be categorized as giant pulse *** majority of these bright pulses are concentrated in pulse phases at both the leading and trailing windows of the average pulse profile,with an occurrence ratio of approximately *** pulse energy distribution for all individual pulses can be described by a combination of two Gaussian components and a cutoff power-law with an index of α=-*** updated nulling fraction of 15.35%±0.45% was determined from the energy *** emission of individual pulses follows a log-normal distribution in peak flux density *** is imperative that regular phase drifting in bright pulse sequence is identified in both the leading and trailing components for the first *** physical mechanisms are discussed in detail to provide insights into these observations.

关键词： (stars:)pulsars:general (stars:)pulsars:individual(PSR B1133+16) methods:observational methods:data analysis

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Interpretation and characterization of rate of penetration intelligent prediction model

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Petroleum Science 2024年第1期21卷 582-596页

作者： zhi-Jun Pei Xian-zhi Song Hai-Tao wang Yi-Qi Shi Shou-Ceng Tian Gen-Sheng Li College of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China State Key Laboratory of Petroleum Resources and Prospecting Beijing102249China Kunlun Digital Technology Co. Ltd.Beijing102206China

Accurate prediction of the rate of penetration(ROP)is significant for drilling *** the intelligent ROP prediction model based on fully connected neural networks(FNN)outperforms traditional ROP equations and machine learning algorithms,its lack of interpretability undermines its *** study proposes a novel interpretation and characterization method for the FNN ROP prediction model using the Rectified Linear Unit(ReLU)activation *** leveraging the derivative of the ReLU function,the FNN function calculation process is transformed into vector *** FNN model is linearly characterized through further simplification,enabling its interpretation and *** proposed method is applied in ROP prediction scenarios using drilling data from three vertical wells in the Tarim *** results demonstrate that the FNN ROP prediction model with ReLU as the activation function performs exceptionally *** relative activation frequency curve of hidden layer neurons aids in analyzing the overfitting of the FNN ROP model and determining drilling data *** the well sections with similar drilling data,averaging the weight parameters enables linear characterization of the FNN ROP prediction model,leading to the establishment of a corresponding linear representation ***,the quantitative analysis of each feature's influence on ROP facilitates the proposal of drilling parameter optimization schemes for the current well *** established linear characterization equation exhibits high precision,strong stability,and adaptability through the application and validation across multiple well sections.

关键词： Fully connected neural network Explainable artificial intelligence Rate of penetration ReLU active function Deep learning Machine learning

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The Consistency of LSE Estimators in Partial Linear Regression Models under Mixing Random Errors

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Acta Mathematica Sinica,English Series 2024年第5期40卷 1244-1272页

作者： Yun Bao YAO Yu Tan LÜ Chao LU Wei wang xue Jun wang School of Mathematical Sciences Anhui UniversityHefei 230601P.R.China School of Big Data and Artificial Intelligence Chizhou UniversityChizhou 247000P.R.China School of Big Data and Statistics Anhui UniversityHefei 230601P.R.China

In this paper,we consider the partial linear regression model y_(i)=x_(i)β^(*)+g(ti)+ε_(i),i=1,2,...,n,where(x_(i),ti)are known fixed design points,g(·)is an unknown function,andβ^(*)is an unknown parameter to be estimated,random errorsε_(i)are(α,β)-mix_(i)ng random *** p-th(p>1)mean consistency,strong consistency and complete consistency for least squares estimators ofβ^(*)and g(·)are investigated under some mild *** addition,a numerical simulation is carried out to study the finite sample performance of the theoretical ***,a real data analysis is provided to further verify the effect of the model.

关键词： (α,β)-mixing random variables partial linear regression model least squares estimator consistency

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Multimodal Machine Learning Guides Low Carbon Aeration Strategies in Urban Wastewater Treatment

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Engineering 2024年第5期36卷 51-62页

作者： Hong-Cheng wang Yu-Qi wang Xu wang Wan-Xin Yin Ting-Chao Yu Chen-Hao xue Ai-Jie wang State Key Laboratory of Urban Water Resource and Environment School of Civil and Environmental EngineeringHarbin Institute of Technology(Shenzhen)Shenzhen 518055China Key Laboratory of Drinking Water Safety and Distribution Technology of Zhejiang Province College of Civil Engineering and ArchitectureZhejiang UniversityHangzhou 310058China

The potential for reducing greenhouse gas(GHG)emissions and energy consumption in wastewater treatment can be realized through intelligent control,with machine learning(ML)and multimodality emerging as a promising ***,we introduce an ML technique based on multimodal strategies,focusing specifically on intelligent aeration control in wastewater treatment plants(WWTPs).The generalization of the multimodal strategy is demonstrated on eight ML *** results demonstrate that this multimodal strategy significantly enhances model indicators for ML in environmental science and the efficiency of aeration control,exhibiting exceptional performance and *** random forest with visual models achieves the highest accuracy in forecasting aeration quantity in multimodal models,with a mean absolute percentage error of 4.4%and a coefficient of determination of *** testing in a full-scale plant reveals that the multimodal model can reduce operation costs by 19.8%compared to traditional fuzzy control *** potential application of these strategies in critical water science domains is *** foster accessibility and promote widespread adoption,the multimodal ML models are freely available on GitHub,thereby eliminating technical barriers and encouraging the application of artificial intelligence in urban wastewater treatment.

关键词： Wastewater treatment Multimodal machine learning Deep learning Aeration control Interpretable machine learning

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A Multiscale Reliability-Based Design Optimization Method for Carbon-Fiber-Reinforced Composite Drive Shafts

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1975-1996页

作者： Huile Zhang Shikang Li Yurui Wu Pengpeng zhi Wei wang Zhonglai wang Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313001China Huzhou Key Laboratory of Green Energy Materials and Battery Cascade Utilization Huzhou CollegeHuzhou313000China SAIC Motor Corporation Limited Passenger Vehicle Co. Shanghai201804China School ofMechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu611731China

Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive ***,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance *** study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive ***,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python *** enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s *** Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process *** studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components.

关键词： Multiscale reliability-based design optimization carbon-fabric-reinforced composite drive shaft

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Pushing the frontiers: Chip-based detection based on micro-and nano-structures

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Chinese Chemical Letters 2024年第4期35卷 86-98页

作者： Meihui Liu Xinyuan Zhou Xiao Li Zhenjie xue Tie wang Tianjin Key Laboratory of Life and Health Detection Life and Health Intelligent Research InstituteTianjin University of TechnologyTianjin 300384China

Changes in trace substances in human metabolites, which are related to disease processes and health status, can serve as chemical markers for disease diagnosis and symptom monitoring. Real-time online detection is an inevitable trend for the future of health monitoring, and the construction of chips for detection faces major challenges. The response of sensors often fails to meet the requirements for chipbased detection of trace substances due to the low efficiency of interfacial heterogeneous reactions, necessitating a rational design approach for micro-and nano-structures to improve sensor performance with respect to sensitivity and detection limits. This review focuses on the influence of micro-and nanostructures that used in chip on sensing. Firstly, this review categorizes sensors into chemiresistors, electrochemical sensors, fluorescence sensors, and surface enhanced Raman scattering(SERS) sensors based on their sensing principle, which have significant applications in disease diagnosis. Subsequently, commencing from the application requirements in the field of sensing, this review focuses on the different structures of nanoparticle(NP) assemblies, including wire, layered, core-shell, hollow, concave and deformable structures. These structures change in the size, shape, and morphology of conventional structures to achieve characteristics such as ordered alignment, high specific surface area, space limitation,vertical diffusion, and swaying behavior with fluid, thereby addressing issues such as poor signal transmission efficiency, inadequate adsorption and capture capacity, and slow mass transfer speed during sensing. Finally, the design direction of micro-and nano-structures, and possible obstacles and solutions to promote chip-based detection have been discussed. It is hope that this article will inspire the exploration of interface micro-and nano-structures modulated sensing methods.

关键词： Chip-based detection Micro-and nano-structures Real-time online detection Sensing Health monitoring

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Light-driven sextuple theranostics:nanomedicine involving second near-infrared AIE-active Ir(Ⅲ)complex for prominent cancer treatment

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Science China Chemistry 2024年第7期67卷 2314-2324页

作者： xue Liu Jiangao Li Fei Zhang Dingyuan Yan Lei wang Dong wang Ben Zhong Tang Center for AIE Research Shenzhen Key Laboratory of Polymer Science and TechnologyGuangdong Research Center for Interfacial Engineering of Functional MaterialsCollege of Material Science and EngineeringShenzhen UniversityShenzhen 518060China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)Shenzhen 518172China

Light-driven cancer theranostics has shown inexhaustible and vigorous vitality by virtue of its high efficacy,prominent controllability and *** of an all-round theranostic material simultaneously affording both multimodal diagnosis imaging and synergistic phototherapy would be an appealing yet significantly challenging ***,a novel nanomedicine Ir@PPEG-MeEPO was ingeniously constructed by integrating beforehand1O2-charged amphiphilic polymer and well-tailored Ir(Ⅲ)complex IrDPTP,which was featured by second near-infrared(NIR-Ⅱ)aggregation-induced emission(AIE)tendency,efficient reactive oxygen species(ROS)generation,good photothermal conversion efficiency and high-performance hydrogen gas *** the best of our knowledge,IrDPTP held the longest emission wavelength among all reported AIE Ir(Ⅲ)***,Ir@PPEG-MeEPO was capable of controllably releasing ROS via triggered photothermal effect upon NIR irradiation,making it well-adapted to hypoxic environment of *** distinctive characteristics of Ir@PPEG-MeEPO endowed it with unprecedented performance on sextuple theranostics comprised of NIR-Ⅱfluorescence-photoacoustic-photothermal trimodal imaging and photodynamic-photothermal-hydrogen trimodal therapy,witnessed by the precise tumor diagnosis and complete tumor *** study would open up new perspectives for the exploration of superior nanomedicine for practical cancer theranostics.

关键词： aggregation-induced emission NIR-II emission cancer theranostics multimodal diagnosis imaging multimodal therapy

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Merging non-covalent and covalent crosslinking:En route to single chain nanoparticles

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Chinese Chemical Letters 2024年第6期35卷 307-311页

作者： Yifei Zhang Yuncong xue Laiwei Gao Rui Liao Feng wang Fei wang CAS Key Laboratory of Soft Matter Chemistry Department of Polymer Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China Department of Neurosurgical The First Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineHefei 230026China

Single-chain nanoparticles represent an emerging class of nanomaterials designed to mimic protein's folding *** covalent crosslinking toward the formation of single-chain nanoparticles encounters complex energy landscapes,leading to the potential occurrence of misfolding *** noncovalent crosslinking can circumvent this issue,the resulting single-chain nanoparticles exhibit lower structural stability compared to their covalently crosslinked *** this study,we present a novel approach for the synthesis of single-chain nanoparticles,achieved through the combination of non-covalent and covalent intramolecular *** grafted onto the linear polymer form intrachain non-covalent stacks aided by hydrogen bonds,leading to the formation of non-covalently crosslinked single-chain *** nanoparticles undergo conversion to covalently crosslinked nanostructures through subsequent photo-irradiation using[2+2]photocycloaddition,a process facilitated by the supramolecular confinement ***,the resulting single-chain nanoparticles demonstrate both intrachain folding efficiency and substantial stability,offering significant potential for advancing applications across diverse fields.

关键词： Single chain nanoparticles Intrachain folding Supramolecular confinement Cyanostilbenes [2+2]photocycloaddition

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Characteristic Study of Self-Powered Sensors Based on Native Protein Composite Film

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Energy & Environmental Materials 2024年第1期7卷 226-232页

作者： Jiehui xue Huijing Xiang Yanrong Zhang Jun Yang Xia Cao Zhonglin wang Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences School of Resources Environment and Materials School of Physics Science and Technology Center on Nanoenergy Research Guangxi University Center for Green Innovation School of Mathematics and Physics University of Science and Technology Beijing Research Centre of Information Technology Shenzhen Institute of Information Technology School of Chemistry and Biological Engineering University of Science and Technology Beijing School of Materials Science and Engineering Georgia Institute of Technology

Flexible electronic sensors composed of flexible film and conductive materials play an increasingly important role in wearable and internet information *** has received more and more attention and made some progress over the ***,it is still a great challenge to prepare biocompatible and highly transparent conductive *** white is a pure natural protein-rich material.

关键词： flexible sensors intelligent sensing natural protein-rich material triboelectric nanogenerators

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Heterogeneous body compositions and all-cause mortality in acute coronary syndrome patients:a ten-year retrospective cohort study

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Journal of Geriatric Cardiology 2024年第5期21卷 534-541页

作者： Guang-zhi LIAO Lin BAI Yu-Yang YE xue-Feng CHEN Xin-Ru HU Yong PENG Department of Cardiology West China HospitalSichuan UniversityChengduSichuanChina

BACKGROUND The association of different body components,including lean mass and body fat,with the risk of death in acute coronary syndrome(ACS)patients are *** We enrolled adults diagnosed with ACS at our center between January 2011 and December 2012 and obtained fol-low-up outcomes via telephone *** used restricted cubic splines(RCS)with the Cox proportional hazards model to analyze the associations between body mass index(BMI),predicted lean mass index(LMI),predicted body fat percentage(BF),and the value of LMI/BF with 10-year *** also examined the secondary outcome of death during *** During the maximum 10-year follow-up of 1398 patients,331 deaths(23.6%)occurred,and a U-shaped relationship was found between BMI and death risk(P_(nonlinearity)=0.03).After adjusting for age and history of diabetes,the overweight group(24≤BMI<28 kg/m^(2))had the lowest mortality(HR=0.53,95%CI:0.29-0.99).Predicted LMI and LMI/BF had an inverse linear relationship with a 10-year death risk(P_(nonlinearity)=0.24 and P_(nonlinearity)=0.38,respectively),while an increase in BF was associ-ated with increased mortality(P_(nonlinearity)=0.64).During hospitalization,31 deaths(2.2%)were recorded,and the associations of the indicators with in-hospital mortality were consistent with the long-term outcome *** Our study provides new insight into the“obesity paradox”in ACS patients,highlighting the importance of considering body composition *** LMI and BF may serve as useful tools for assessing nutritional status and predicting the prognosis of ACS,based on their linear associations with all-cause mortality.

关键词： patients mortality coronary

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