检索结果-南通市图书馆

International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 395-404页

作者： Ge Chu Chaohui Wang Zhewei Yang Lin Qin xin fan College of Materials Science&Engineering Guilin University of TechnologyGuilin 541004China Institute of Energy Innovation College of Materials Science and EngineeringTaiyuan University of TechnologyTaiyuan 030024China

The development of anode materials with high rate capability and long charge-discharge plateau is the key to improve per-formance of lithium-ion capacitors(LICs).Herein,the porous graphitic carbon(PGC-1300)derived from a new triply interpenetrated co-balt metal-organic framework(Co-MOF)was prepared through the facile and robust carbonization at 1300°C and washing by HCl solu-tion.The as-prepared PGC-1300 featured an optimized graphitization degree and porous framework,which not only contributes to high plateau capacity(105.0 mAh·g^(−1)below 0.2 V at 0.05 A·g^(−1)),but also supplies more convenient pathways for ions and increases the rate capability(128.5 mAh·g^(−1)at 3.2 A·g^(−1)).According to the kinetics analyses,it can be found that diffusion regulated surface induced capa-citive process and Li-ions intercalation process are coexisted for lithium-ion storage.Additionally,LIC PGC-1300//AC constructed with pre-lithiated PGC-1300 anode and activated carbon(AC)cathode exhibited an increased energy density of 102.8 Wh·kg^(−1),a power dens-ity of 6017.1 W·kg^(−1),together with the excellent cyclic stability(91.6%retention after 10000 cycles at 1.0 A·g^(−1)).

关键词： metal-organic framework porous graphitic carbon optimized plateau capacity kinetic analysis lithium-ion capacitor

Cross-Project Software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第2期78卷 1687-1711页

作者： xin fan Shuqing Zhang Kaisheng Wu Wei Zheng Yu Ge School of Software Nanchang Hangkong UniversityNanchang330063China Software Testing and Evaluation Center Nanchang Hangkong UniversityNanchang330063China

Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consider linear correlations between features(indicators)of the source and target projects.These models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target projects.As a result,the performance of such CPDP models is compromised.In this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as S-DCCA.Canonical Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the dataset.The redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss function.Finally,cross-project defect prediction is achieved through the application of the SMOTE data sampling technique.Area Under Curve(AUC)and F1 scores(F1)are used as evaluation metrics.This paper conducted experiments on 27 projects from four public datasets to validate the proposed method.The results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 score.This indicates that the proposed method exhibits favorable performance characteristics.

关键词： Cross-project defect prediction deep canonical correlation analysis feature similarity

Software Defect Prediction Method Based on Stable Learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 65-84页

作者： xin fan Jingen Mao Liangjue Lian Li Yu Wei Zheng Yun Ge College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing210012China School of Software Nanchang Hangkong UniversityNanchang330029China Software Testing and Evaluation Center Nanchang Hangkong UniversityNanchang330029China

The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor.In previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data distribution.However,target projects often lack sufficient data,which affects the performance of the transfer learning model.In addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model.To address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual networks.This method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code images.During the model training process,target project data are not required as prior knowledge.Following the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the data.This approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction performance.To evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE dataset.The experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction methods.Therefore,SDP-SL can effectively enhance within-and cross-project defect predictions.

关键词： Software defect prediction code visualization stable learning sample reweight residual network

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Neural Regeneration Research 2024年第12期19卷 2637-2648页

作者： Yi Guo Zhonghua Lin Zhen fan xin Tian Department of Neurology Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Sichuan Provincial Center for Mental Health Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Department of Geriatrics Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Department of Neurology Chongqing Key Laboratory of NeurologyThe First Affiliated Hospital of Chongqing Medical UniversityChongqingChina

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

关键词： electrophysiological techniques epilepsy functional brain network functional magnetic resonance imaging functional near-infrared spectroscopy machine leaning molecular imaging neuroimaging techniques structural brain network virtual epileptic models

Using ChatGPT to promote college students’participation in physical activities and its effect on mental health

在线全文

学校读者我要写书评

暂无评论

World Journal of Psychiatry 2024年第2期14卷 330-333页

作者： Yi-fan Zhang xin-Qiao Liu School of Education Tianjin UniversityTianjin 300350China

As one of the most famous large language models,ChatGPT has great potential for application in physical education.It can provide personalized exercise plans,a variety of exercise options,and interactive support.The integration of ChatGPT into the teaching process can promote college students’participation in physical activities and improve their mental health while expanding the traditional teaching environment and promoting the reform of traditional teaching methods.However,the application of ChatGPT faces challenges and obstacles in physical education.To make full use of ChatGPT in physical education,it can be combined with wearable devices and sports equipment to enhance the efficiency of interactions with users.Relevant policies are urgently needed to avoid the improper use of users’data.

关键词： ChatGPT College students Physical education Mental health

Bioinspired metal-organic framework nanozyme reinforced with thermosensitive hydrogel for regulating inflammatory responses in Parkinson’s disease

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2024年第2期17卷 858-865页

作者： Xiaowan fan Tao Zhang xin Ding Yushuo Gu Qing Li Wei Jiang Kelong fan Nanozyme Medical Center Academy of Medical ScienceZhengzhou UniversityZhengzhou 450001China Department Central-China Branch of National Center for Cardiovascular DiseasesHean Cardiovascular Disease CenterFuwai Central-China HospitalCentral China Fuwai Hospital of Zhengzhou UniversityZhengzhou 450046China Application Center for Precision Medicine the Second Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China CAS Engineering Laboratory for Nanozyme Key Laboratory of Protein and Peptide PharmaceuticalsInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 101408China Department of General Surgery Strategic Support Force Medical CenterBeijing 100101China Department of Anesthesiology Pain and Perioperative MedicineThe First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China

Parkinson’s disease(PD)is a prevalent neurodegenerative disorder accompanied by movement disorders and neuroinflammatory injury.Anti-inflammatory intervention to regulate oxidative stress in the brain is beneficial for managing PD.However,traditional natural antioxidants have failed to meet the clinical treatment demands due to insufficient activity and sustainability.Herein,Cu-doping zeolite imidazolate framework-8(ZIF-8)nanozyme is designed to simulate Cu/Zn superoxide dismutase(SOD)by biomimetic mineralization.The nanozyme composite is then integrated into thermosensitive hydrogel(poly(lactic-co-glycolic acid)-poly(ethylene glycol)-poly(lactic-co-glycolic acid)(PLGA-PEG-PLGA))to form an effective antioxidant system(Cu-ZIF@Hydrogel).The thermosensitive hydrogel incorporating nanozymes demonstrate distinct viscoelastic properties aimed at enhancing local nanozyme adhesion,prolonging nanozyme retention time,and modulating antioxidant activity,thus significantly improving the bioavailability of nanozymes.At the cellular and animal levels of PD,we find that Cu-ZIF@Hydrogel bypass the blood-brain barrier and efficiently accumulate in the nerve cells.Moreover,the Cu-ZIF@Hydrogel significantly alleviate the PD’s behavioral and pathological symptoms by reducing the neuroinflammatory levels in the lesion site.Therefore,the hydrogel-incorporating nanozyme system holds great potential as a simple and reliable avenue for managing PD.

关键词： bioinspired nanozyme thermosensitive hydrogel Parkinson’s disease oxidative stress neuroinflammatory

Zn-air batteries for electric vehicles

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Tungsten 2024年第1期6卷 164-173页

作者： Nai-Qi Meng Yu-xin fan Jing-Sheng Cai State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai 200438China College of Energy Soochow Institute for Energy and Materials InnovationS(SIEMIS)Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhou 215006China Institute of New Energy for Vehicles School of Materials Science and EngineeringTongji UniversityShanghai 201804China

The increasingly serious environmental challenges have gradually aroused people's interest in electric vehicles.Over the last decade,governments and automakers have collaborated on the manufacturing of electric vehicles with high performance.Cutting-edge battery technologies are pivotal for the performance of electric vehicles.Zn-air batteries are considered as potential power batteries for electric vehicles due to their high capacity.Zn-air battery researches can be classified into three categories:primary batteries,mechanically rechargeable batteries,and chemically rechargeable batteries.The majority of current studies aim at developing and improving chemically rechargeable and mechanically rechargeable Zn-air batteries.Researchers have tried to use catalytic materials design and device design for Zn-air batteries to make it possible for their applications in electric vehicles.This review will highlight the state-of-the-art in primary batteries,mechanically rechargeable batteries,and chemically rechargeable batteries,revealing the prospects of Zn-air batteries for electric vehicles.

关键词： Energy storage Electric vehicles Bifunctional oxygen catalysts Mechanically rechargeable Zn-air batteries Chemically rechargeable Zn-air batteries

Total Factor Productivity with Chinese Characteristics

在线全文

学校读者我要写书评

暂无评论

Social Sciences in China 2024年第1期45卷 54-70页

作者： fan xin Liu Wei School of Economics Renmin University of China

Although total factor productivity(TFP)is a common concept in mainstream Western economics,its origins are actually embedded in Marx's understanding of improving labor productivity.As an important element of labor productivity under socialized production conditions,TFP is further reflected in the category of"socially necessary labor time"in two distinct senses.Re-examining TFP from the perspective of Marxist political economy and incorporating it into the theoretical system of political economy of socialism with Chinese characteristics vividly illustrates the essence of"adhering to original principles,assimilating foreign concepts,and embracing a forward-looking vision"within political economy of socialism with Chinese characteristics.In practice,it is necessary to start with Marx's theory of productive labor and delineate the sectors involved in productive labor so that TFP and its fluctuations can be measured in a more relevant way.In the context of the new era and the new journey,as the key to achieving high-quality economic development in China,efforts are needed to increase TFP.This requires balancing economic factors such as the long term and short term,supply and demand,and gross quantity and structure,and promoting transformative changes in the quality,efficiency,and dynamism of economic development.

关键词： total factor productivity(TFP) technological progress technological effciency high-quality development

Dynamic response of buildings under debris flow impact

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Mountain Science 2024年第5期21卷 1581-1597页

作者： LIU Huan fan Xiaoyi TIAN Shujun DENG xin School of Mechanical and Electrical Engineering Southwest Petroleum UniversityChengdu 610500China School of Civil Engineering and Geomatics Southwest Petroleum UniversityChengdu 610500China Housing and Urban-Rural Development Bureau of Mingshan District Ya’an 625100China Engineering Safety Assessment and Protection Research Southwest Petroleum UniversityChengdu 610500China School of Civil Engineering and Architecture Southwest University of Science and TechnologyMianyang 621010China

This study employs the smoothed particle hydrodynamics–finite element method(SPH–FEM) coupling numerical method to investigate the impact of debris flow on reinforced concrete(RC)-frame buildings. The methodology considers the variables of debris flow depth and velocity and introduces the intensity index IDV(IDV = DV) to evaluate three different levels of debris flow impact intensity. The primary focus of this study is to investigate the dynamic response and failure mechanism of RC-frame buildings under debris flow impact, including structural failure patterns, impact force and column displacement. The results show that under a highintensity impact, a gradual collapse process of the RCframe building can be observed, and the damage mode of the frame column reflects shear failure or plastic hinge failure mechanism. First, the longitudinal infill walls are damaged owing to their low out-of-plane flexural capacity;the critical failure intensity index IDV value is approximately 7.5 m2/s. The structure cannot withstand debris flows with an intensity index IDV greater than 16 m2/s, and it is recommended that the peak impact force should not exceed 2100 k N. The impact damage ability of debris flow on buildings mostly originates from the impact force of the frontal debris flow, with the impact force of the debris flow body being approximately 42% lower than that of the debris flow head. Finally, a five-level classification system for evaluating the damage status of buildings is proposed based on the numerical simulation and investigation results of the disaster site.

关键词： SPH–FEM method Debris flow Buildings The intensity index Dynamic response

Grapevine-like high entropy oxide composites boost high-performance lithium sulfur batteries as bifunctional interlayers

在线全文

学校读者我要写书评

暂无评论

Green Energy & Environment 2024年第3期9卷 565-572页

作者： Huarong fan Yubing Si Yiming Zhang Fulong Zhu xin Wang Yongzhu Fu College of Chemistry and Center of Green Catalysis Zhengzhou UniversityZhengzhou450001China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu611731China

Lithium-sulfur batteries(LSBs)with high energy densities have been demonstrated the potential for energy-intensive demand applications.However,their commercial applicability is hampered by hysteretic electrode reaction kinetics and the shuttle effect of lithium polysulfides(LiPSs).In this work,an interlayer consisting of high-entropy metal oxide(Cu_(0.7)Fe_(0.6)Mn_(0.4)Ni_(0.6)Sn_(0.5))O_(4) grown on carbon nanofibers(HEO/CNFs)is designed for LSBs.The CNFs with highly porous networks provide transport pathways for Li^(+) and e^(-),as well as a physical sieve effect to limit LiPSs crossover.In particular,the grapevine-like HEO nanoparticles generate metal-sulfur bonds with LiPSs,efficiently anchoring active materials.The unique structure and function of the interlayer enable the LSBs with superior electrochemical performance,i.e.,the high specific capacity of 1381 mAh g^(-1) at 0.1 C and 561 mAh g^(-1) at 6 C.This work presents a facile strategy for exploiting high-performance LSBs.

关键词： Electrospun carbon nanofibers Grapevine-like morphology Hierarchical physical sieve effect High-entropy induced chemisorption Lithium-sulfur battery