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Response of ecosystem carbon storage to land use change from 1985 to 2050 in the Ningxia Section of Yellow River Basin,China

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Journal of Arid Land 2024年第1期16卷 110-130页

作者： LIN Yanmin HU Zhirui LI Wenhui CHEN Haonan WANG Fang NAN Xiongxiong YANG Xuelong ZHANG Wenjun College of Geographical Sciences and Planning Ningxia UniversityYinchuan 750021China China-arab Joint International Research Laboratory for Featured Resources and Environmental Governance in Arid Region Yinchuan 750021China Ningxia Land Resources Surveying and Monitoring Institute Yinchuan 750002China State Key Laboratory of Efficient Production of Forest Resources Yinchuan 750002China Ningxia Lingwu Baijitan National Nature Reserve Administration Yinchuan 751400China

Regional sustainable development necessitates a holistic understanding of spatiotemporal variations in ecosystem carbon storage(ECS),particularly in ecologically sensitive areas with arid and semi-arid *** this study,we calculated the ECS in the Ningxia Section of Yellow River Basin,China from 1985 to 2020 using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model based on land use *** further predicted the spatial distribution of ECS in 2050 under four land use scenarios:natural development scenario(NDS),ecological protection scenario(EPS),cultivated land protection scenario(CPS),and urban development scenario(UDS)using the patch-generating land use simulation(PLUS)model,and quantified the influences of natural and human factors on the spatial differentiation of ECS using the geographical detector(Geodetector).Results showed that the total ECS of the study area initially increased from 1985 until reaching a peak at 402.36×10^(6) t in 2010,followed by a decreasing trend to *** spatial distribution of ECS was characterized by high values in the eastern and southern parts of the study area,and low values in the western and northern *** 1985 and 2020,land use changes occurred mainly through the expansion of cultivated land,woodland,and construction land at the expense of unused *** total ECS in 2050 under different land use scenarios(ranked as EPS>CPS>NDS>UDS)would be lower than that in *** light was the largest contributor to the spatial differentiation of ECS,with soil type and annual mean temperature being the major natural driving *** of this study could provide guidance on the ecological construction and high-quality development in arid and semi-arid areas.

关键词： carbon storage land use change nighttime light Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model patch-generating land use simulation(PLUS)model geographical detector(Geodetector) Yellow River Basin

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Selective and Adaptive Incremental Transfer Learning with Multiple Datasets for Machine Fault Diagnosis

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Computers, Materials & Continua 2024年第1期78卷 1363-1379页

作者： Kwok Tai Chui Brij B.Gupta Varsha Arya Miguel Torres-Ruiz School of Science and Technology Hong Kong Metropolitan UniversityHong Kong999077China Department of Computer Science and Information Engineering Asia UniversityTaichung41354Taiwan Center for Advanced Information Technology Kyung Hee UniversitySeoul02447Korea Symbiosis Centre for Information Technology Symbiosis International UniversityPuneMaharashtra411042India Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon School of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Business Administration Asia UniversityTaichung41354Taiwan Center for Interdisciplinary Research University of Petroleum and Energy StudiesDehradun248007India Department of Computer Science&Engineering Chandigarh UniversityChandigarh160036India Centro de Investigación en Computación Instituto Politécnico NacionalUPALM-ZacatencoMexico City07320Mexico

The visions of Industry 4.0 and 5.0 have reinforced the industrial *** have also made artificial intelligence incorporated as a major *** machine faults has become a solid foundation for automatically recognizing machine failure,and thus timely maintenance can ensure safe *** learning is a promising solution that can enhance the machine fault diagnosis model by borrowing pre-trained knowledge from the source model and applying it to the target model,which typically involves two *** response to the availability of multiple datasets,this paper proposes using selective and adaptive incremental transfer learning(SA-ITL),which fuses three algorithms,namely,the hybrid selective algorithm,the transferability enhancement algorithm,and the incremental transfer learning *** is a selective algorithm that enables selecting and ordering appropriate datasets for transfer learning and selecting useful knowledge to avoid negative *** algorithm also adaptively adjusts the portion of training data to balance the learning rate and training *** proposed algorithm is evaluated and analyzed using ten benchmark *** with other algorithms from existing works,SA-ITL improves the accuracy of all *** studies present the accuracy enhancements of the SA-ITL,including the hybrid selective algorithm(1.22%-3.82%),transferability enhancement algorithm(1.91%-4.15%),and incremental transfer learning algorithm(0.605%-2.68%).These also show the benefits of enhancing the target model with heterogeneous image datasets that widen the range of domain selection between source and target domains.

关键词： Deep learning incremental learning machine fault diagnosis negative transfer transfer learning

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Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul Haq Fahim Arif Khursheed Aurangzeb Noor ul Ain Javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

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Magneto-Photo-Thermoelastic Excitation Rotating Semiconductor Medium Based on Moisture Diffusivity

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CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES 2024年第10期141卷 107-126页

作者： Lotfy, Khaled Mahdy, A. M. S. El-Bary, Alaa A. Elidy, E. S. Zagazig Univ Fac Sci Dept Math Zagazig 44519 Egypt Taibah Univ Fac Sci Math Dept Madinah 42353 Saudi Arabia Taif Univ Coll Sci Dept Math & Stat Taif 11099 Saudi Arabia arab Acad Sci Technol & Maritime Transport Alexandria 1029 Egypt

In this research, we focus on the free-surface deformation of a one-dimensional elastic semiconductor medium as a function of magnetic field and moisture diffusivity. The problem aims to analyze the interconnection between plasma and moisture diffusivity processes, as well as thermo-elastic waves. The study examines the photothermoelasticity transport process while considering the impact of moisture diffusivity. By employing Laplace's transformation technique, we derive the governing equations of the photo-thermo-elastic medium. These equations include the equations for carrier density, elastic waves, moisture transport, heat conduction, and constitutive relationships. Mechanical stresses, thermal conditions, and plasma boundary conditions are used to calculate the fundamental physical parameters in the Laplace domain. By employing numerical techniques, the Laplace transform is inverted to get complete time-domain solutions for the primary physical domains under study. Reference moisture, thermoelastic, and thermoelectric characteristics are employed in conjunction with a graphical analysis that takes into consideration the effects of applied forces on displacement, moisture concentration, carrier density, stress due to forces, and temperature distribution.

关键词： Moisture diffusivity semiconductor photothermoelastic rotation thermomechanical waves laplace transform MODEL HEAT

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Biorenewable materials for water remediation: The central role of cellulose in achieving sustainability

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Journal of Bioresources and Bioproducts 2024年第3期9卷 253-282页

作者： Kirti Mishra Samarjeet Singh Siwal Thandiwe Sithole Nirankar Singh Phil Hart Vijay Kumar Thakur Department of Chemistry M.M.Engineering CollegeMaharishi Markandeshwar(Deemed to be University)Haryana 133207India Department of Chemical Engineering University of JohannesburgDoornfontein 2088South Africa Biorefining and Advanced Materials Research Center Scotland’s Rural CollegeEdinburgh EH93JGUnited Kingdom Renewable and Sustainable Energy Research Centre Technology Innovation InstituteAbu Dhabi 9639United Arab Emirates School of Engineering University of Petroleum&Energy StudiesDehradun 248007India

As the population increases and manufacturing grows,greenhouse gas and other harmful emissions *** with chemicals such as dyes,pesticides,pharmaceuticals,oil,heavy metals or radionuclides,wastewater purification has become an urgent *** technologies exist that can remove these contaminants from wastewater sources,but they often demand high energy and/or high cost,and in some cases produce contaminant laden sludge that requires safe *** need for methods which are less capital intensive,less operationally costly and more environmentally friendly is ***-based materials have emerged as promising candidates for wastewater treatment due to their renewability,low cost,biodegradability,hydrophilicity,and antimicrobial *** this review article,we focussed on developing sustainable and biodegradable cellulose-based materials for wastewater *** article deals with cellulose-based materials’scope and their conversion into valuable products like hydrogel,aerogel,cellulose composites,and *** cellulose-based materials have no harmful environmental impact and are *** modified cellulose-based materials applying as membrane,adsorbent,sorbent,and beads to purify the wastewater were ***,the challenges and future prospects of cellulose-based materials for wastewater treatment were considered,emphasizing their potential to be sustainable and eco-friendly alternatives to traditional materials used in wastewater treatment.

关键词： Cellulose Wastewater treatment Hydrogel Nanocrystal Cellulose membrane

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Enhancing MXene-based supercapacitors:Role of synthesis and 3D architectures

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Journal of Energy Chemistry 2024年第4期91卷 1-26页

作者： Wen Siong Poh Wen Jie Yiang Wee-Jun Ong Pau Loke Show Chuan Yi Foo School of Energy and Chemical Engineering Xiamen University MalaysiaSelangor Darul EhsanMalaysia&College of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005FujianChina Kelip-kelip!Center of Excellence for Light Enabling Technologies Xiamen University MalaysiaSelangor Darul Ehsan 43900Malaysia Center of Excellence for NaNo Energy&Catalysis Technology(CONNECT) Xiamen University MalaysiaSelangor Darul Ehsan 43900Malaysia Department of Chemical Engineering Khalifa UniversityShakhbout Bin Sultan St-Zone 1Abu DhabiUnited Arab Emirates Zhejiang Provincial Key Laboratory for Subtropical Water Environment and Marine Biological Resources Protection Wenzhou UniversityWenzhou 325035ZhejiangChina Department of Chemical and Environmental Engineering Faculty of Science and EngineeringUniversity of Nottingham MalaysiaJalan Broga43500 SemenyihSelangor Darul EhsanMalaysia Department of Sustainable Engineering Saveetha School of EngineeringSIMATSChennai 602105India

MXene has been the limelight for studies on electrode active materials,aiming at developing supercapacitors with boosted energy density to meet the emerging influx of wearable and portable electronic *** its various desirable properties including intrinsic flexibility,high specific surface area,excellent metallic conductivity and unique abundance of surface functionalities,its full potential for electrochemical performance is hindered by the notorious restacking phenomenon of MXene *** to its two-dimensional(2D)nature and surface functional groups,inevitable Van der Waals interactions drive the agglomeration of nanosheets,ultimately reducing the exposure of electrochemically active sites to the electrolyte,as well as severely lengthening electrolyte ion transport *** a result,energy and power density deteriorate,limiting the application versatility of MXene-based *** 3D architectures using 2D nanosheets presents as a straightforward yet ingenious approach to mitigate the fatal flaws of ***,the sheer number of distinct methodologies reported,thus far,calls for a systematic review that unravels the rationale behind such 3D MXene structural ***,this review aims to serve this purpose while also scrutinizing the structure–property relationship to correlate such structural modifications to their ensuing electrochemical performance ***,the physicochemical properties of MXene play fundamental roles in determining the effective charge storage capabilities of 3D MXene-based *** largely depends on different MXene synthesis techniques and synthesis condition variations,hence,elucidated in this review as ***,the challenges and perspectives for achieving viable commercialization of MXene-based supercapacitor electrodes are highlighted.

关键词： MXene 3D architectures Synthesis design Supercapacitor Energy storage

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Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1981-2004页

作者： Shaik Mahaboob Basha Victor Hugo Cde Albuquerque Samia Allaoua Chelloug Mohamed Abd Elaziz Shaik Hashmitha Mohisin Suhail Parvaze Pathan Department of Electronics and Communication Engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Information Technology Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India Department of Veterinary Clinical Sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

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Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

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Computers, Materials & Continua 2023年第2期74卷 3333-3350页

作者： Akram Ali Alhadad Omar Tarawneh Reham R.Mostafa Hazem M.El-Bakry Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Computer Science Department Ibb UniversityIbbYemen SE Department Faculty of Computer Sciences and InformaticsAmman Arab UniversityAmman11953Jordan

COVID-19 is the common name of the disease caused by the novel coronavirus(2019-nCoV)that appeared in Wuhan,China in *** the infected people is the most important factor in the fight against the *** gold-standard test to diagnose COVID-19 is polymerase chain reaction(PCR),but it takes 5–6 h and,in the early stages of infection,may produce false-negative *** Computed Tomography(CT)images to diagnose patients infected with COVID-19 has become an urgent *** this study,we propose a residual attention deep support vector data description SVDD(RADSVDD)approach to diagnose *** is a novel approach combining residual attention with deep support vector data description(DSVDD)to classify the CT *** the best of our knowledge,we are the first to combine residual attention with DSVDD in general,and specifically in the diagnosis of *** attention with DSVDD naively may cause model *** in the proposed RADSVDD guides the network during training and enables quick learning,residual connectivity prevents vanishing *** approach consists of three models,each model is devoted to recognizing one certain disease and classifying other diseases as *** models learn in an end-to-end *** proposed approach attained high performance in classifying CT images into intact,COVID-19,and non-COVID-19 *** evaluate the proposed approach,we created a dataset from published datasets and had it assessed by an experienced *** proposed approach achieved high performance,with the normal model attained sensitivity(0.96–0.98),specificity(0.97–0.99),F1-score(0.97–0.98),and area under the receiver operator curve(AUC)0.99;the COVID-19 model attained sensitivity(0.97–0.98),specificity(0.97–0.99),F1-score(0.97–0.99),and AUC 0.99;and the non-COVID pneumoniamodel attained sensitivity(0.97–1),specificity(0.98–0.99),F1-score(0.97–0.99),and AUC 0.99.

关键词： Deep learning deep SVDD residual attention anomaly detection COVID-19 Coronavirus

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Exploring van der Waals materials with high anisotropy:geometrical and optical approaches

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Light(Science & Applications) 2024年第4期13卷 645-653页

作者： Aleksandr S.Slavich Georgy A.Ermolaev Mikhail K.Tatmyshevskiy Adilet N.Toksumakov Olga G.Matveeva Dmitriy V.Grudinin Kirill V.Voronin Arslan Mazitov Konstantin V.Kravtsov Alexander V.Syuy Dmitry M.Tsymbarenko Mikhail S.Mironov Sergey M.Novikov Ivan Kruglov Davit A.Ghazaryan Andrey A.Vyshnevyy Aleksey V.Arsenin Valentyn S.Volkov Kostya S.Novoselov Moscow Center for Advanced Studies Kulakova str.20Moscow 123592Russia. Emerging Technologies Research Center XPANCEOInternet CityEmmay TowerDubaiUnited Arab Emirates. Donostia International Physics Center(DIPC) Donostia/San-Sebastián 20018Spain. Institute of Materials Ecole Polytechnique Federale de Lausanne1015 LausanneSwitzerland. Department of Chemistry Lomonosov Moscow State UniversityMoscow 119991Russia. Laboratory of Advanced Functional Materials Yerevan State UniversityYerevan 0025Armenia. National Graphene Institute(NGI) University of ManchesterManchester M139PLUK. Department of Materials Science and Engineering National University of SingaporeSingapore 03-09 EASingapore. Institute for Functional Intelligent Materials National University of Singapore117544 SingaporeSingapore

The emergence of van der Waals(vdW)materials resulted in the discovery of their high optical,mechanical,and electronic anisotropic properties,immediately enabling countless novel phenomena and *** success inspired an intensive search for the highest possible anisotropic properties among vdW ***,the identification of the most promising among the huge family of vdW materials is a challenging quest requiring innovative ***,we suggest an easy-to-use method for such a survey based on the crystallographic geometrical perspective of vdW materials followed by their optical *** our approach,we found As2S3 as a highly anisotropic vdW *** demonstrates high in-plane optical anisotropy that is~20%larger than for rutile and over two times as large as calcite,high refractive index,and transparency in the visible range,overcoming the century-long record set by *** these benefits,As2S3 opens a pathway towards nextgeneration nanophotonics as demonstrated by an ultrathin true zero-order quarter-wave plate that combines classical and the Fabry–Pérot optical phase ***,our approach provides an effective and easy-to-use method to find vdW materials with the utmost anisotropic properties.

关键词： anisotropy anisotropic high

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Mapping the global research landscape on nonalcoholic fatty liver disease and insulin resistance:A visualization and bibliometric study

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World Journal of Hepatology 2024年第6期16卷 951-965页

作者： Sa'ed H Zyoud Omar E Hegazi Samer O Alalalmeh Muna Shakhshir Faris Abushamma Shadi Khilfeh Samah W Al-Jabi Department of Clinical and Community Pharmacy College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Clinical Research Center An-Najah National University HospitalNablus 44839Palestine College of Pharmacy and Health Sciences Ajman UniversityAjman 346United Arab Emirates Department of Nutrition An-Najah National University HospitalNablus 44839Palestine Department of Medicine College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Department of Urology An-Najah National University HospitalNablus 44839Palestine Department of Gastroenterology Hepatology and EndoscopyAn-Najah National University HospitalNablus 44839Palestine

BACKGROUND Nonalcoholic fatty liver disease(NAFLD)is a liver condition that is prevalent worldwide and associated with significant health risks and economic *** it has been linked to insulin resistance(IR),this study aimed to perform a bibliometric analysis and visually represent the scientific literature on IR and *** To map the research landscape to underscore critical areas of focus,influential studies,and future directions of NAFLD and *** This study conducted a bibliometric analysis of the literature on IR and NAFLD indexed in the SciVerse Scopus database from 1999 to *** search strategy used terms from the literature and medical subject headings,focusing on terms related to IR and *** software was used to visualize research trends,collaborations,and key thematic *** analysis examined publication type,annual research output,contributing countries and institutions,funding agencies,journal impact factors,citation patterns,and highly cited *** This analysis identified 23124 documents on NAFLD,revealing a significant increase in the number of publications between 1999 and *** search retrieved 715 papers on IR and NAFLD,including 573(80.14%)articles and 88(12.31%)*** most productive countries were China(n=134;18.74%),the United States(n=122;17.06%),Italy(n=97;13.57%),and Japan(n=41;5.73%).The leading institutions included the Universitàdegli Studi di Torino,Italy(n=29;4.06%),and the Consiglio Nazionale delle Ricerche,Italy(n=19;2.66%).The top funding agencies were the National Institute of Diabetes and Digestive and Kidney Diseases in the United States(n=48;6.71%),and the National Natural Science Foundation of China(n=37;5.17%).The most active journals in this field were Hepatology(27 publications),the Journal of Hepatology(17 publications),and the Journal of Clinical Endocrinology and Metabolism(13 publications).The main research hotspots were“therapeutic approaches for IR and NAFLD”and“inflamma

关键词： Nonalcoholic fatty liver disease Insulin resistance Bibliometric Visualization

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