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Pharmacological potential of Manilkara zapota(L.)***(Sapodilla):a narrative review

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Journal of Traditional Chinese Medicine 2024年第2期44卷 403-407页

作者： Priyanka Sharma Aakash Deep Harish kumar Nitin Bansal Sanjiv kumar arun Davinder kumar Department of Pharmaceutical Sciences Chaudhary Bansi Lal UniversityBhiwani 127021India Department of Pharmaceutical Sciences Maharishi Dayanand UniversityRohtak 124001India

Herbal medicine is safe and effective in treating various *** herbal medicine plays a tremendous role in treatment of various diseases and accompanying complications,hence herbal medicine requires remarkable attention in further research for the development of numerous active formulations for treatment of health *** plant needs special consideration for development and research of unidentified compound and characterization of novel active molecules that overcome multiple pathological *** genus Manilkara contains 135 plants around the *** overview discusses all the virtues of most important and commonly used plant Manilkara zapota(L.)***(***),also known as *** has various traditional beneficial effects in treatment of various diseases and disorders dating back to prehistoric times and used in ancient traditional system of herbal medicine.

关键词： herbal medicine Manilkara zapota phytoconstituents pharmacological activity review

Secure and resilient improved image steganography using hybrid fuzzy neural network with fuzzy logic

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Journal of Safety Science and Resilience 2024年第1期5卷 91-101页

作者： Sachin Dhawan Hemanta kumar Bhuyan Subhendu kumar Pani vinayakumar Ravi Rashmi Gupta arun Rana Alanoud Al Mazroa Dorset College King George BlvdSurreyBritish ColumbiaCanada Department of Information Technology Vignan’s Foundation for ScienceTechnology and Research(Deemed to be University)Andhra PradeshIndia krupajal Computer Academy Biju Patnaik University of Technology(BPUT)Rourkela 751002India Center for Artificial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia NSUT East Campus(Formerly AIACTRDelhi 110031India(Affiliated to Guru Gobind Singh Inderaprastha University))Dwarka 110078India Department of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida 201310Uttar PradeshIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)P.O.Box 84428Riyadh 11671Saudi Arabia

The exponential growth in communication networks,data technology,advanced libraries,and mainly World Wide Web services has played a pivotal role in facilitating the retrieval of various types of information as ***,this progress has also led to security concerns related to the transmission of confidential ***,safeguarding these data during communication through insecure channels is crucial for obvious *** emergence of steganography offers a robust approach to concealing confidential information,such as images,audio tracks,text files,and video files,in suitable media carriers.A novel technique is envisioned based on back-propagation *** to the proposed method,a hybrid fuzzy neural network(HFNN)is applied to the output obtained from the least significant bit substitution of secret data using pixel value dif-ferences and exploiting the modification *** simulation and test results,it has been observed that the proposed methodology achieves secure steganography and superior visual *** the experiments,we observed that for the secret image of the cameraman,the PSNR&MSE values of the proposed technique are 61.963895 and 0.041361,respectively.

关键词： Image enhancement Image processing Steganography Deep learning Fuzzy neural combination

Machine learning for predicting the outcome of terminal ballistics events

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Defence Technology（防务技术） 2024年第1期31卷 14-26页

作者： Shannon Ryan Neeraj Mohan Sushma arun kumar Av Julian Berk Tahrima Hashem Santu Rana Svetha venkatesh Applied Artificial Intelligence Institute(A2I2) Deakin University75 Pigdons RdWaurn PondsVIC3216Australia

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal *** evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SvR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the v50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite *** achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release *** demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this *** extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is *** circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss *** physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when *** resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical *** with numerical analysis tools such as finite element solvers the ML models run orders of magnitude *** provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballist

关键词： Machine learning Artificial intelligence Physics-informed machine learning Terminal ballistics Armour

Stability Analysis of DC Microgrid Clusters Based on Step-by-step System Matrix Building Algorithm

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 900-912页

作者： k.Jithin N.Mayadevi R.Hari kumar v.P.Mini the Department of Electrical Engineering College of Engineering TrivandrumAPJ Abdul Kalam Technological University(APJAKTU)ThiruvananthapuramIndia

DC microgrids(DCMGs)are made up of a network of sources and loads that are connected by a number of power electronic converters(PECs).The increase in the number of these PECs instigates major concerns in system *** interconnecting the microgrids to form a cluster,the system stability must be *** paper proposes a novel stepby-step system matrix building(SMB)algorithm to update the system matrix of an existing DCMG cluster when a new microgrid is added to the cluster through a distribution *** stability of the individual DCMGs and the DCMG cluster is analyzed using the eigenvalue ***,the particle swarm optimization(PSO)algorithm is used to retune the controller gains if the newly formed cluster is not *** simulation of the DCMG cluster is carried out in MATLAB/Simulink environment to test the proposed *** results are also validated using the OP4510 real-time simulator(RTS).

关键词： Converter DC microgrid cluster eigenvalue interconnection particle swarm optimization system stability system matrix

Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition:application of the clique polynomial method and physics-informed neural networks

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Applied Mathematics and Mechanics(English Edition) 2024年第9期45卷 1613-1632页

作者： k.CHANDAN k.kARTHIk k.v.NAGARAJA B.C.PRASANNAkumarA R.S.varun kumar T.MUHAMMAD Amrita School of Artificial Intelligence Amrita Vishwa VidyapeethamBengaluru 560035KarnatakaIndia Department of Studies in Mathematics Davangere UniversityDavangere 577002KarnatakaIndia Computational Science Lab Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru 560035KarnatakaIndia Department of Pure and Applied Mathematics School of Mathematical SciencesSunway UniversityPetaling Jaya 47500Malaysia Department of Mathematics College of ScienceKing Khalid UniversityAbha 61413Saudi Arabia

The heat transfer through a concave permeable fin is analyzed by the local thermal non-equilibrium(LTNE)*** governing dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled,and then are nondimensionalized by suitable dimensionless ***,the obtained nondimensional equations are solved by the clique polynomial method(CPM).The effects of several dimensionless parameters on the fin's thermal profiles are shown by graphical ***,the current study implements deep neural structures to solve physics-governed coupled equations,and the best-suited hyperparameters are attained by comparison with various network *** results of the CPM and physicsinformed neural network(PINN)exhibit good agreement,signifying that both methods effectively solve the thermal modeling problem.

关键词： heat transfer fin porous fin local thermal non-equilibrium(LTNE)model physics-informed neural network(PINN)

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 409-430页

作者： Zhuoqun Xia Hangyu Hu Wenjing Li Qisheng Jiang Lan Pu Yicong Shu arun kumar Sangaiah School of Computer and Communication Engineering Changsha University of Science and TechnologyChangshaChina Hunan Province People’s Hospital(The First Affiliated Hospital of Hunan Normal University) ChangshaChina The First Affiliated Hospital of Guangxi Medical University NanningChina International Graduate Institute of AI National Yunlin University of Science and TechnologyYunlinChina Department of Electrical and Computer Engineering Lebanese American UniversityBayrutLebanon

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible *** research has failed to fully explore effective DR lesion information in fundus ***,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion ***,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis ***,the LLM generates a global attention map based on ***,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion *** paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

关键词： DDR dataset diabetic retinopathy lesion localization multi-level patch attention mechanism

Clinical profile and outcomes of hepatocellular carcinoma in primary Budd-Chiari syndrome

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World Journal of Gastrointestinal Oncology 2024年第3期16卷 699-715页

作者： Ankit Agarwal Sagnik Biswas Shekhar Swaroop Arnav Aggarwal Ayush Agarwal Gautam Jain Anshuman Elhence arun vaidya Amit Gupte Ravi Mohanka Ramesh kumar Ashwani kumar Mishra Shivanand Gamanagatti Shashi Bala Paul Subrat kumar Acharya Akash Shukla Shalimar Department of Gastroenterology and Human Nutrition All India Institute of Medical SciencesNew Delhi 110029DelhiIndia Department of Gastroenterology Seth Gordhandas Sunderdas Medical College and KEM HospitalMumbai 400012MaharashtraIndia Department of Gastroenterology Sir HN Reliance Foundation HospitalMumbai 400004India Department of Liver Transplant and HPB Sir HN Reliance Foundation HospitalMumbai 400004India Department of Gastroenterology All India Institute of Medical SciencesPatna 801507India Professor of Biostatistics National Drug Dependence Treatment Centre(NDDTC)All India Institute of Medical SciencesNew Delhi 110029India Department of Radiodiagnosis All India Institute of Medical SciencesNew Delhi 110029DelhiIndia

BACkGROUND There is scant literature on hepatocellular carcinoma(HCC)in patients with Budd-Chiari syndrome(BCS).AIM To assess the magnitude,clinical characteristics,feasibility,and outcomes of treatment in *** A total of 904 BCS patients from New Delhi,India and 1140 from Mumbai,India were *** prevalence and incidence of HCC were determined,and among patients with BCS-HCC,the viability and outcomes of interventional therapy were *** In the New Delhi cohort of 35 BCS-HCC patients,18 had HCC at index presentation(prevalence 1.99%),and 17 developed HCC over a follow-up of 4601 person-years,[incidence 0.36(0.22-0.57)per 100 person-years].BCS-HCC patients were older when compared to patients with BCS alone(P=0.001)and had a higher proportion of inferior vena cava block,cirrhosis,and long-segment vascular *** median alpha-fetoprotein level was higher in patients with BCS-HCC at first presentation than those who developed HCC at follow-up(13029 ng/mL vs 500 ng/mL,P=0.01).Of the 35 BCS-HCC,26(74.3%)underwent radiological interventions for BCS,and 22(62.8%)patients underwent treatment for HCC[transarterial chemoembolization in 18(81.8%),oral tyrosine kinase inhibitor in 3(13.6%),and transarterial radioembolization in 1(4.5%)].The median survival among patients who underwent interventions for HCC compared with those who did not was 3.5 years vs 3.1 mo(P=0.0001).In contrast to the New Delhi cohort,the Mumbai cohort of BCS-HCC patients were predominantly males,presented with a more advanced HCC[Barcelona Clinic Liver Cancer C and D],and 2 patients underwent liver *** HCC is not uncommon in patients with *** interventions and liver transplantation are feasible in select primary BCS-HCC patients and may improve outcomes.

关键词： Budd chiari syndrome Cancer Cirrhosis Thrombosis Liver varices Transarterial chemoembolization Hepatic venous outflow tract obstruction

Development,validation,and transportability of several machine-learned,non-exercise-based vO_(2max)prediction models for older adults

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Journal of Sport and Health Science 2024年第5期13卷 611-620页

作者： Benjamin T.Schumacher Michael J.LaMonte Andrea Z.LaCroix Eleanor M.Simonsick Steven P.Hooker Humberto Parada Jr. John Bellettiere arun kumar Herbert Wertheim School of Public Health and Human Longevity Science University of California San DiegoLa JollaCA 92093USA Department of Epidemiology and Environmental Health School of Public Health and Health ProfessionsUniversity at BuffaloState University of New YorkBuffaloNY 14214USA Translational Gerontology Branch Intramural Research ProgramNational Institute on AgingNational Institutes of HealthBaltimoreMD 21225USA College of Health and Human Services San Diego State UniversitySan DiegoCA 92182USA Division of Epidemiology and Biostatistics School of Public HealthSan Diego State UniversitySan DiegoCA 92182USA University of California San Diego Moores Cancer Center La JollaCA 92093USA Computer Science and Engineering and Halicioglu Data Science Institute University of California San DiegoLa JollaCA 92093USA

Background:There exist few maximal oxygen uptake(vO_(2max))non-exercise-based prediction equations,fewer using machine learning(ML),and none specifically for older *** direct measurement of vO_(2max)is infeasible in large epidemiologic cohort studies,we sought to develop,validate,compare,and assess the transportability of several ML vO_(2max)prediction ***:The Baltimore Longitudinal Study of Aging(BLSA)participants with valid vO2_(max)tests were included(n=1080).Least absolute shrinkage and selection operator,linear-and tree-boosted extreme gradient boosting,random forest,and support vector machine(SvM)algorithms were trained to predict vO_(2max)*** developed these algorithms for:(a)the overall BLSA,(b)by sex,(c)using all BLSA variables,and(d)variables common in aging ***,we quantified the associations between measured and predicted vO_(2max)and ***:The age was 69.0±10.4 years(mean±SD)and the measured vO_(2max)was 21.6±5.9 mL/kg/*** absolute shrinkage and selection operator,linear-and tree-boosted extreme gradient boosting,random forest,and support vector machine yielded root mean squared errors of 3.4 mL/kg/min,3.6 mL/kg/min,3.4 mL/kg/min,3.6 mL/kg/min,and 3.5 mL/kg/min,*** quartiles of measured vO_(2max)showed an inverse gradient in mortality *** vO_(2max)variables yielded similar effect estimates but were not robust to ***:Measured vO_(2max)is a strong predictor of *** ML can improve the accuracy of prediction as compared to simpler approaches but estimates of association with mortality remain sensitive to *** studies should seek to reproduce these results so that vO_(2max),an important vital sign,can be more broadly studied as a modifiable target for promoting functional resiliency and healthy aging.

关键词： Cardiorespiratory fitness Prediction algorithms Epidemiology Mortality

Spatial and Contextual Path Network for Image Inpainting

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Intelligent Automation & Soft Computing 2024年第2期39卷 115-133页

作者： Dengyong Zhang Yuting Zhao Feng Li arun kumar Sangaiah Hunan Provincial key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China International Graduate Institute of AI National Yunlin University of Science and TechnologyYunlinTaiwan Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Image inpainting is a kind of use known area of information technology to repair the loss or damage to the *** feature extraction is the core of image *** enough space for information and a larger receptive field is very important to realize high-precision image ***,in the process of feature extraction,it is difficult to meet the two requirements of obtaining sufficient spatial information and large receptive fields at the same *** order to obtain more spatial information and a larger receptive field at the same time,we put forward a kind of image restoration based on space path and context path *** the space path,we stack three convolution layers for 1/8 of the figure,the figure retained the rich spatial *** the context path,we use the global average pooling layer,where the accept field is the maximum of the backbone network,and the pooling module can provide global context information for the maximum accept *** order to better integrate the features extracted from the spatial and contextual paths,we study the fusion module of the two *** fusionmodule first path output of the space and context path,and then through themass normalization to balance the scale of the characteristics,finally the characteristics of the pool will be connected into a feature vector and calculate the weight *** of images in order to extract context information,we add attention to the context path refinement *** modules respectively from channel dimension and space dimension to weighted images,in order to obtain more effective *** show that our method is better than the existing technology in the quality and quantity of themethod,and further to expand our network to other inpainting networks,in order to achieve consistent performance improvements.

关键词： Image inpainting attention deep learning convolutional network