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Atherosclerotic plaque classification in carotid ultrasound images using machine learning and explainable deep learning

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Intelligent Medicine 2024年第2期4卷 83-95页

作者： soni singh Pankaj k.Jain Neeraj sharma Mausumi Pohit sudipta Roy school of Vocational studies and Applied sciences Gautam Buddha UniversityGreater NoidaUttar PradeshIndia Artificial Intelligence and Data science Jio Institute Navi MumbaiMaharashtraIndia school of Biomedical Engineering Indian Institute of TechnologyVaranasiUttar PradeshIndia

Objective The incidence of cardiovascular diseases(CVD)is rising rapidly *** forms of CVD,such as stroke and heart attack,are more common among patients with certain *** development is a major factor underlying cardiovascular events,such as heart attack and stroke,and its early detection may prevent such *** imaging of carotid arteries is a useful method for diagnosis of atherosclerotic plaques;however,an automated method to classify atherosclerotic plaques for evaluation of early-stage CVD is ***,we propose an automated method for classification of high-risk atherosclerotic plaque ultrasound *** Five deep learning(DL)models(VGG16,ResNet-50,GoogLeNet,XceptionNet,and squeezeNet)were used for automated classification and the results compared with those of a machine learning(ML)-based technique,involving extraction of 23 texture features from ultrasound images and classification using a support Vector Machine *** enhance model interpretability,output gradient-weighted convolutional activation maps(GradCAMs)were generated and overlayed on original *** A series of indices,including accuracy,sensitivity,specificity,F1-score,Cohen-kappa index,and area under the curve values,were calculated to evaluate model *** output images allowed visualization of the most significant ultrasound image *** GoogLeNet model yielded the highest accuracy(98.20%).Conclusion ML models may be also suitable for applications requiring low computational ***,DL models could be more completely automated than ML models.

关键词： Explainable deep learning Carotid artery Classification VGG 16 ResNet-50 GoogLeNet XceptionNet squeezeNet

C-phycocyanin shows neuroprotective effect against rotenone-induced Parkinson’s disease in mice

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Asian Pacific Journal of Tropical Biomedicine 2024年第7期14卷 279-287页

作者： Hritik Rathod Ritu M.soni Jigna s.shah Department of Pharmacology Institute of Pharmacy Nirma UniversityAhmedabadGujaratIndia

Objective:To investigate the neuroprotective effect of C-phycocyanin in a mouse model of rotenone-induced Parkinson’s ***:C-phycocyanin(50 mg/kg,i.p.,daily)was administered to rotenone(30 mg/kg,p.o.,daily)treated mice for 28 *** studies(Y-maze,rotarod,round beam walk,and wire-hang tests)were carried out to assess neurobehavioral *** and malondialdehyde were determined in both serum and striatal *** proteins(AkT,AMPk,NF-κB,BDNF,and alpha-synuclein)in the striatum were estimated using *** analyses(hematoxylin and eosin stainning as well as Nissl staining)were carried out to assess structural abnormalities in the ***:C-phycocyanin significantly increased BDNF levels and decreased alpha-synuclein *** also slightly upregulated AMPk and AkT levels without significant difference compared with the rotenone ***,rotenone-induced elevated oxidative stress and structural abnormalities in the striatum were markedly mitigated by ***:C-phycocyanin might have potential neuroprotective effects against Parkinson’s *** studies are warranted to verify its efficacy and to understand the molecular mechanisms behind the neuroprotective effects of C-phycocyanin in Parkinson’s disease.

关键词： Parkinson’s disease C-phycocyanin Alphasynuclein BDNF Oxidative stress Rotenone

Comparative measurement of CO_(2),CH_(4)and CO at two traffic interjunctions having inflated vehicular flow in Delhi

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Journal of Environmental sciences 2024年第7期141卷 314-329页

作者： komal Daya soni khem singh shankar G.Aggarwal CsIR-National Physical Laboratory Dr.K.S.Krishnan MargNew Delhi 110012India Academy of scientific&Innovative Research(AcsIR) Ghaziabad 201002India

Vehicular emissions are considered one of the major anthropogenic sources of greenhouse gases and poor air quality in metropolitan *** study aims to see the correlation of CO_(2),CH_(4),and CO through monitoring over a period from December 2020 to October 2021 covering three seasons’winter,summer,and monsoon at two different traffic locations of Delhi having different traffic volumes,road patterns,and traffic *** annual average morning concentration of CO_(2),CH_(4)and CO was found(533±105),(7.3±3.1),(10.7±3.0)ppm at Najafgarh and(480±70),(5.2±1.8),(7.8±2.8)ppm at Rajendra Place,respectively.A relationship between concentration of all three gases and meteorological parameters such as temperature,humidity,wind speed and wind direction has also been investigated using Pearson correlation coefficient and pollution rose diagram.A comparable pattern in concentration was observed for all three gases in spatial(location)and temporal(diurnal)*** concentration trend of CO_(2)in different seasons is winter>summer>monsoon,while in the case of CH_(4)winter=summer>monsoon but not any seasonal trend was noted in CO *** is observed that CO_(2)has a good relation with CO(a tracer for vehicular emission)in terms of diurnal variation,whereas,CH_(4)does not represent a relation with CO and CO_(2)diurnally,suggesting that vehicles are the source of CO_(2)but not much contributing to other greenhouse gases like CH_(4).

关键词： Vehicular emission Greenhouse gases Harmful pollutants Meteorological parameters

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等离子体处理对牛仔织物的影响

国际纺织导报 2021年第6期49卷 23-25页

作者： s.k.soni 黄嘉磊(译) 罗艳(校) Jawaharlal Darda工程技术学院(印度) 不详

等离子体技术因其环境友好且应用广泛而被认为是一项面向未来的技术。等离子体技术在纺织工业中的应用包括纺织纤维的退浆、功能化和表面改性。等离子体技术适用于改变材料的化学结构及表面形貌。研究了常压等离子体处理对靛蓝染色牛仔... 详细信息

等离子体技术因其环境友好且应用广泛而被认为是一项面向未来的技术。等离子体技术在纺织工业中的应用包括纺织纤维的退浆、功能化和表面改性。等离子体技术适用于改变材料的化学结构及表面形貌。研究了常压等离子体处理对靛蓝染色牛仔织物各项性能的影响。同时还探讨了工艺参数(暴露时间和电极间距)的影响。采用FAsT评价系统测试了未处理和经等离子体处理的牛仔织物的各项性能。通过国际照明委员会的Lab比色系统,评估了经等离子体处理的织物的脱色效果。结果表明,织物性能受等离子体处理工艺参数的影响。随着等离子体处理暴露时间的延长,牛仔织物的剪切刚度降低。在低负荷下,织物受力后压缩增大,同时抗弯刚度增大。织物的成形性随着等离子体处理暴露时间的延长而提高。扫描电子显微镜(sEM)图像清楚地显示出大气等离子体对纤维进行了表面改性。

关键词：等离子体处理牛仔织物暴露时间电极间距表面改性

Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

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Journal of Magnesium and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan sekar s.k.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnesium Research Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till *** corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical *** intrinsic high electrochemical nature of Mg limits their utilization in diverse *** scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion *** present review enlightens the influence of grain size(Gs),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg ***,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are ***,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are ***,the individual role of Gs,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and *** challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is *** review is presented from basic concrete background to advanced corrosion mechanisms with an aim of creating interest among the readers like students,researchers and industry experts from various research ***,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of knowledge,(ii)foster research and development,(iii)make breakthrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

关键词： Corrosion Bio corrosion Magnesium alloys Magnesium composites Magnesium implants.

Enhancing Multicriteria-Based Recommendations by Alleviating scalability and sparsity Issues Using Collaborative Denoising Autoencoder

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Computers, Materials & Continua 2024年第2期78卷 2269-2286页

作者： s.Abinaya k.Uttej kumar school of Computer science&Engineering Vellore Institute of TechnologyChennaiTamilnadu600127India

A Recommender system(Rs)is a crucial part of several firms,particularly those involved in *** conventional Rs,a user may only offer a single rating for an item-that is insufficient to perceive consumer ***,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’*** the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested ***,the cost of these computations increases nonlinearly as the number of items and users *** triumph over the issues,a novel expanded stacked autoencoder(EsAE)with kernel Fuzzy C-Means Clustering(kFCM)technique is proposed with two *** the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the EsAE approach and users are clustered using the kFCM *** the next phase of online,the top-N recommendation prediction is made by the EsAE approach involving only the most similar user from multiple *** the EsAE_kFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation *** experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the EsAE_kFCM model constantly outperforms conventional Rs algorithms on a variety of assessment measures.

关键词： Recommender systems multicriteria rating collaborative filtering sparsity issue scalability issue stacked-autoencoder kernel Fuzzy C-Means Clustering

Emission colour tuning in kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of Rare Earths 2024年第1期42卷 57-65,I0002页

作者： Janani k Gayathri E Vijayatha V Ramasubramanian s Thiyagarajan P Department of science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of Physics Anna UniversityChennaiIndia

kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped kYbF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped kGdF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using UV light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped kYbF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： Rare earths Energy transfer upconversion Downshifting Colour coordinates

Juxtapose of system Performance for Food Calorie Estimation Using IoT and Web-based Indagation

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Journal of Harbin Institute of Technology(New series) 2024年第1期31卷 54-63页

作者： Anusuya s sharmila k Department of Computer science VISTASChennai 600117India Department of Computer science Dr.MGR Janaki College for WomenChennai 600028India

A rudimentary aspect of human life is the health of an individual,and most commonly the wellbeing is impacted in a colossal manner through the consumption of food. The intake of calories therefore is a crucial aspect that must be meticulously monitored. Various health gremlins can be largely circumvented when there is a substantial balance in the number of calories ingested versus the quantity of calories *** food calorie estimation is a popular domain of research in recent times and is meticulously analyzed through various image processing and machine learning techniques. However,the need to scrutinize and evaluate the calorie estimation through various platforms and algorithmic approaches aids in providing a deeper insight on the bottlenecks involved,and in improvising the bariatric health of an individual. This paper pivots on comprehending a juxtaposed approach of food calorie estimation through the use of employing Convolution Neural Network(CNN)incorporated in Internet of Things(IoT),and using the Django framework in Python,along with query rule-based training to analyze the subsequent actions to be followed post the consumption of food calories in the constructed webpage. The comparative analysis of the food calorie estimate implemented in both platforms is analyzed for the swiftness of identification,error rate and classification accuracy to appropriately determine the optimal method of use. The simulation results for IoT are carried out using the Raspberry Pi4B model,while the Anaconda prompt is used to run the server holding the web page.

关键词： food calorie estimation convolution neural network Django framework internet of things raspberry Pi

5G Resource Allocation Using Feature selection and Greylag Goose Optimization Algorithm

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Computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel Ali Alhussan s.k.Towfek Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer science and Intelligent systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of k-Nearest Neighbors(kNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test