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Frontiers of structural and Civil Engineering 2024年第8期18卷 1169-1194页

作者： Tang QIONG Ishan JHA Alireza BAHRAMI Haytham F.IsLEEM Rakesh kumar Pijush sAMUI school of Applied Technologies Qujing Normal UniversityQujing 655011China Department of Civil Engineering Indian Institute of Technology-BHUVaranasi 221005India Department of Building Engineering Energy Systems and Sustainability ScienceFaculty of Engineering and Sustainable DevelopmentUniversity of GävleGävle 80176Sweden Department of Civil Engineering National Institute of Technology-PatnaPatna 800005India

This study employs a hybrid approach,integrating finite element method(FEM)simulations with machine learning(ML)techniques to investigate the structural performance of double-skin tubular columns(DsTCs)reinforced with glass fiber-reinforced polymer(GFRP).The investigation involves a comprehensive examination of critical parameters,including aspect ratio,concrete strength,number of GFRP confinement layers,and dimensions of steel tubes used in DsTCs,through comparative analyses and parametric *** ensure the credibility of the findings,the results are rigorously validated against experimental data,establishing the precision and trustworthiness of the *** present research work examines the use of the columns with elliptical cross-sections and contributes valuable insights into the application of FEM and ML in the design and evaluation of structural systems within the field of structural engineering.

关键词： elliptical column fiber-reinforced polymer machine learning finite element method ABAQUs

Corrigendum to“Nitrosamines crisis in pharmaceuticals-Insights on toxicological implications,root causes and risk assessment:A systematic review”[***.14(2024)100919]

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Journal of Pharmaceutical Analysis 2024年第6期14卷 934-936页

作者： Hemanth P.R.Vikram Tegginamath Pramod kumar Gunjan kumar Narasimha M.Beeraka Rajashree Deka sheik Mohammed suhail sandeep Jat Namitha Bannimath Gayatiri Padmanabhan Ravandur s.Chandan Pramod kumar Bannimath Gurupadayya Department of Pharmaceutical Chemistry JSS College of Pharmacy MysuruJSS Academy of Higher Education and Research(JSSAHER)Mysuru570015India Xenone Healthcare Pvt.Ltd. New Delhi110076India Department of Pharmaceutics JSS College of Pharmacy MysuruJSS Academy of Higher Education and Research(JSSAHER)Mysuru570015India Department of Human Anatomy I.M.Sechenov First Moscow State Medical University(Sechenov University)Moscow119991Russian Federation Department of Pharmacology Raghavendra Institute of Pharmaceutical Education and Research(RIPER)Ananthapuramu515721India Herman B.Wells Center for Pediatric Research Department of PediatricsIndiana University School of MedicineIndianapolisIN46202USA Animal Physiology and Biochemistry Laboratory Department of ZoologyGauhati UniversityGuwahati781014India Department of Pharmacology JSS College of Pharmacy MysuruJSS Academy of Higher Education and Research(JSSAHER)Mysuru570015India Department of Pharmaceutical Analysis National Institute of Pharmaceutical Education and Research(NIPER)-GuwahatiChangsari781101India Department of Pharmacology University of GalwayGalwayH91 TK33Ireland

Original statement in the section 2:*** search Our primary screening of 180 articles yielded the relevant data for this *** selection A total of 180 articles spanning from 1960 to the present day,including original research,reviews,case reports and studies reporting nitrosamine impurities above the no-observed-adverse-effect levels(NOAEL)established by regulatory agencies,were initially *** the primary screening,we considered factors such as relevance,publication date,access to the full article text,and content.

关键词： statement initially spanning

Gas hydrate saturation from NGHP 02 LWD data in the Mahanadi Basin

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Energy Geoscience

Energy Geoscience 2024年第2期5卷 279-289页

作者： Uma shankar Pradeep kumar Yadav sneha Devi Udham singh Yadav Department of Geophysics Institute of ScienceBHUVaranasi221005India Oil and Natural Gas Corporation Ltd. Gas Hydrate Research&Technology Centre(GHRTC)Panvel410221Navi MumbaiIndia

During the Indian National Gas Hydrate Program(NGHP)Expedition 02,Logging-while-drilling(LWD)logs were acquired at three sites(NGHP-02-11,NGHP-02-12,and NGHP-02-13)across the Mahanadi Basin in area *** applied rock physics theory to available sonic velocity logs to know the distribution of gas hydrate at site NGHP-02-11 and *** physics modeling using sonic velocity at well location shows that gas hydrate is distributed mainly within the depth intervals of 150-265 m and 100 -215 mbsf at site NGHP-02-11 and NGHP-02-13,respectively,with an average saturation of about 4%of the pore space and the maximum concentration of about 40%of the pore space at 250 m depth at site NGHP-02-11,and at site NGHP-02-13 an average saturation of about 2%of the pore space and the maximum concentration of about 20%of the pore space at 246 m depth,as gas hydrate is distributed mainly within 100-246 mbsf at this *** of gas hydrate estimated from the electrical resistivity method using density derived porosity and electrical resistivity logs from Archie's empirical formula shows high saturation compared to that from the sonic ***,estimates of hydrate saturation based on sonic P-wave velocity may differ significantly from that based on resistivity,because gas and hydrate have higher resistivity than conductive pore fluid and sonic P-wave velocity shows strong effect on gas hydrate as a small amount of gas reduces the velocity significantly while increasing velocity due to the presence of *** site NGHP-02-11,gas hydrate saturation is in the range of 15%e30%,in two zones between 150-180 and 245-265 *** NGHP-02-012 shows a gas hydrate saturation of 20%e30%in the zone between 100 and 207 *** NGHP-02-13 shows a gas hydrate saturation up to 30%in the zone between 215 and 246 *** observations from rock physics modeling and Archie’s approximation show the gas hydrate concentrations are relatively low(space)at the sites of the

关键词： Mahanadi Basin Gas hydrate sonic log Effective medium modeling Electrical resistivity log Archie’s analysis Gas hydrate saturation

An Assisted Diagnosis of Alzheimer’s Disease Incorporating Attention Mechanisms Med-3D Transfer Modeling

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Computers, Materials & Continua 2024年第1期78卷 713-733页

作者： Yanmei Li Jinghong Tang Weiwu Ding Jian Luo Naveed Ahmad Rajesh kumar school of Artificial Intelligence Chongqing University of TechnologyChongqing400054China Computer school China West Normal UniversityNanchong637009China Department of Computer science Prince Sultan UniversityRiyadh11586Saudi Arabia Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313001China

Alzheimer’s disease(AD)is a complex,progressive neurodegenerative *** subtle and insidious onset of its pathogenesis makes early detection of a formidable challenge in both contemporary neuroscience and clinical *** this study,we introduce an advanced diagnostic methodology rooted in theMed-3D transfermodel and enhanced with an attention *** aim to improve the precision of AD diagnosis and facilitate its early ***,we employ a spatial normalization technique to address challenges like clarity degradation and unsaturation,which are commonly observed in imaging ***,an attention mechanism is incorporated to selectively focus on the salient features within the imaging *** upon this foundation,we present the novelMed-3D transfermodel,designed to further elucidate and amplify the intricate features associated *** proposedmodel has demonstrated promising results,achieving a classification accuracy of 92%.To emphasize the robustness and practicality of our approach,we introduce an adaptive‘hot-updating’auxiliary diagnostic *** system not only enables continuous model training and optimization but also provides a dynamic platform to meet the real-time diagnostic and therapeutic demands of AD.

关键词： Alzheimer’s disease channel attention Med-3D hot update

Improved neurological diagnoses and treatment strategies via automated human brain tissue segmentation from clinical magnetic resonance imaging

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Intelligent Medicine 2024年第3期4卷 161-169页

作者： Puranam Revanth kumar Rajesh kumar Jha P Akhendra kumar B Deevena Raju Department of Electronics and Communication Engineering Faculty of Science and TechnologyICFAI Foundation for Higher EducationHyderabadIndia Department of Data science&AI Faculty of Science and TechnologyICFAI Foundation for Higher EducationHyderabadIndia

Objective segmentation of medical images is a crucial process in various image analysis *** segmentation methods excel in accuracy when compared to manual segmentation in the context of medical image *** of the essential phases in the quantitative analysis of the brain is automated brain tissue segmentation using clinically obtained magnetic resonance imaging(MRI)*** allows for precise quantitative examination of the brain,which aids in diagnosis,identification,and classification of ***,the efficacy of the segmentation approach is crucial to disease diagnosis and treatment *** This study presented a hybrid optimization method for segmenting brain tissue in clinical MRI scans us-ing a fractional Henry horse herd gas optimization-based shepard convolutional neural network(FrHHGO-based shCNN).To segment the clinical brain MRI images into white matter(WM),grey matter(GM),and cerebrospinal fluid(CsF)tissues,the proposed framework was evaluated on the Lifespan Human Connectome Projects(HCP)*** hybrid optimization algorithm,FrHHGO,integrates the fractional Henry gas optimization(FHGO)and horse herd optimization(HHO)*** required 30 min,whereas testing and segmentation of brain tissues from an unseen image required an average of 12 *** Compared to the results obtained with no refinements,the skull stripping refinement showed significant *** the method included a preprocessing stage,it was flexible enough to enhance image quality,allowing for better results even with low-resolution *** precision of 93.2%,recall of 91.5%,Dice score of 91.1%,and F1-score of 90.5% were achieved using the proposed FrHHGO-based shCNN,which was superior to all other approaches.

关键词： Brain tissue segmentation Deep learning Magnetic resonance imaging Optimization technique shepard convolutional neural network

Testing the LCC hypothesis by considering environmental sustainability and economic development:Role of green energy and resource management

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Geoscience Frontiers 2024年第3期15卷 419-430页

作者： sunil Tiwari syed Ali Raza shiv kumar Gupta Irum shahzadi Mahendra Babu Kuruva Department of Tourism studies School of Business StudiesCentral University of KeralaIndia Department of Business Administration IQRA UniversityKarachi 75300Pakistan Centre for Mountain Tourism and Hospitality studies HNB Garhwal Central UniversitySrinagarUttarakhand 246174India Department of Production Engineering São Paulo State University(UNESP)BauruBrazil Department of Business Administration IQRA University Karachi-75300Pakistan Department of Business Management HNB Garhwal Central UniversitySrinagar GarhwalUttarakhand 246174India

This study aims to demystify the role of green energy and green technology in establishing the nexus between behavioural intentions of tourists,technologies,and digital payments by using Perceived value(PV),Compatibility(CO),Perceived Enjoyment(PE),and social Influence(sI)as a predictor variables,Trust(TR)and satisfaction(sA)as a mediating variables and Behavioural Intentions(BI)as an outcome *** the empirical estimation,we employ smart PLs-sEM,TAM(Technology Acceptance Model)and sPss and Tested the LCC *** findings suggest that green energy and perceived value have the highest positive impact on tourists’trust towards digital payments followed by compatibility,social influence and perceived ***,tourists’satisfaction and green technology is one of the important determinants of choosing any digital mode of payment,is mostly influence by perceived value,perceived enjoyment,compatibility and social ***,if we choose between trust and satisfaction,trust plays a significant role in exploring the behavioural intentions of tourists about green energy and green technology followed by tourists’*** addition,Tourists’trust and satisfaction are highly correlated and influence each *** study offers novel policy implications in terms of use of green technology and green energy in enhancing trust and satisfaction of tourists in order to deeper understanding of different dimensions of digital payments and M-wallets,and allowing them to explore the long-term value inherent of digital payments and M-wallets.

关键词： Digital payment Green technology Green energy Tourism LCC hypothesis

Multi-scale habitat influences sprainting and group size of a freshwater-obligate smooth-coated otter(Lutrogale perspicillata) in Tungabhadra Otter Conservation Reserve, India

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Ecological Processes 2024年第1期13卷 159-175页

作者： Ankit Moun P.Ramesh kumar M.Malathi Priya T.Ramesh Riddhika Kalle sálim Ali Centre for Ornithology and Natural History Deputy Conservator of Forests Bellary Territorial Forest Division Deputy Conservator of Forests Working Plan and Survey and Research WingBellary Territorial Forest Division Centre for Functional Biodiversity University of Kwa Zulu-Natal

Background The impact of changing land-use patterns and associated anthropogenic threats on scale-dependent habitat use of semi-aquatic mustelids in scent-marking and social behaviour can provide important insights into the habitat ecology of smooth-coated otters(Lutrogale perspicillata).Methods We sampled 180 stream segments(100–400 m) as spatial replicates of 60 1-km2 sites to record indirect evidence(i.e. spraints and mass latrine sites) and group sizes of smooth-coated otters along the Tungabhadra Otter Conservation Reserve(TOCR) during the dry season. To quantify habitat, we recorded stream characteristics, riparian vegetation, and anthropogenic disturbances at the local scale, and hydro-environmental characteristics and land uses at the landscape scale. Using Markovian-chain detection and occupancy models, we assessed the multi-scale habitat use of otters in their selection of suitable areas for scent-marking based on repeated presence-absence data on spraint/latrine locations along the TOCR. We further used linear regression techniques to explore relationships between the number of individuals in smooth-coated otter group and hydro-environmental characteristics, spraint/latrine encounter rate, anthropogenic pressure, land cover, topography, and *** At the local scale, the probability of spraint deposition and group size decreased with anthropogenic disturbance while the probability of spraint detections decreased with grass cover. At the landscape scale, the probability of otter site use for spraint deposition and group sizes increased in southeast flowing streams. spraint deposition increased with the proportion of sugarcane fields, whereas in contrast, group size decreased with proportion of sugarcane *** Our findings highlight the first empirical evidence on multi-scale habitat use of a southern Indian population of smooth-coated otters in an inland freshwater ecosystem surrounded by the scrub jungle–agriculture matrix. We sug

关键词： Presence-absence modelling Inland river Freshwater ecosystem semi-aquatic mammal smooth-coated otter

Energy characterization of forced ventilated Photovoltaic-DsF system in hot summer of composite climate

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Energy and Built Environment 2024年第5期5卷 704-718页

作者： sajan Preet sanjay Mathur Jyotirmay Mathur Manoj kumar sharma Amartya Chowdhury school of Built Environment University of ReadingUnited Kingdom Centre for Energy and Environment Malaviya National Institute of TechnologyJLN MargJaipur302017India

Performance of Photovoltaic-double skin façade(Photovoltaic-DsF)system in summer has been *** to high solar ingress,cooling requirement of a building significantly ***-DsF system provides a shield and controls the heat gain through fenestration in the interior *** the present article,mathematical correlations are developed for energy characterization of forced-ventilated Photovoltaic-DsF system in India’s hot summer zone *** Photovoltaic-DsF system has been installed and monitored for Jaipur’s summer months(May to July).L25 Orthogonal array of design parameters(air cavity thickness,air velocity,and PV panel’s transparency)and their respective levels have been developed using Taguchi design to perform *** on experimental results,multiple linear regression has been used to forecast solar heat gain coefficient,PVs electrical power and daylighting illuminance indoors as function of design *** statistical significance of mathematical relationships is sorted by variance analysis,which is found to be in good accord with field measurements(R2>0.90).The proposed correlations are pragmatic in designing Photovoltaic-DsF systems for hot summer *** Photovoltaic-DsF system with 30%transmittance and air velocity of 5 metres per second in 200 mm air cavity thickness achieved maximum energy performance in hot summers.

关键词： Photovoltaic double-skin façade Taguchi method Forced ventilation Net energy consumption Overall energy performance

Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni sanjay kumar sharma Mohammad Khalid Imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia school of Computer science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging subset of the Digital Database for screening Mammography(CBIs-DDsM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

Downwash airflow distribution pattern of hexa-copter unmanned aerial vehicles

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International Journal of Agricultural and Biological Engineering 2024年第4期17卷 24-34页

作者： Dengeru Yallappa Ramasamy Kavitha Allimuthu surendrakumar Kannan Balaji Balakrishnan suthakar Ayyasamy Paramasivam Mohan kumar Yathendranaik Ravi Narayananaik Ashoka kumar Kavan Department of Farm Machinery and Power Engineering Agricultural Engineering College and Research InstituteTamil Nadu Agricultural UniversityCoimbatore

In recent times,the use of vertical take-off and landing(VTOL)multi-rotor Unmanned Aerial Vehicle(UAVs)for spraying chemical pesticides against weeds and pests has recently become *** current aerial spray application research is primarily focused on examining the influence of UAV spraying parameters such as flight height,travel speed,rotor configuration,droplet size,payload and wind *** downwash airflow velocity generated by the UAV rotor propeller has a significant impact on the droplet deposition process.A test rig was developed to measure the downwash airflow pattern generated by the rotor propeller of a *** this investigation,a six-rotor electric autonomous UAV sprayer was used to investigate the parameters and distribution laws of downwash airflow *** downwash airflow velocity was measured using portable anemometers mounted on the test rig at radial positions viz.,0 m,0.5 m,1 m,1.5 m and 2 m,perpendicular to(X)and parallel to the UAV’s flight direction(Y).The experiment was conducted at three levels of hover height,viz.,1 m,2 m and 3 m(Z)and three levels of payload,viz.,0 kg,5 kg,and 10 *** special downwash airflow distribution pattern was analysed using the Python programming language(Version 3.7).Results show that the downwash airflow velocity generated by the radial position of the UAV rotor is evenly distributed on the rotating loop and the standard deviation of the downwash airflow velocity is less than 0.5 m/*** maximum downwash airflow velocity of 13.8 m/s was observed below the rotor at 10 kg payload capacity,1 m hover height(Z),and 0.5 m in the *** minimum downwash wind field of 0.3 m/s was observed at 0 kg pay load capacity,1 m height,and 2 m in the *** downwash airflow velocity along each position in the radial direction of the rotor increases initially and then *** downwash airflow distribution results helps in mounting of spray nozzle configuration to drone sprayer which helps to

关键词： downwash air payload rotor propeller flight height distribution analysis flight direction