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Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast scenarios: A Numerical modeling study

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Computer modeling in Engineering & sciences 2024年第9期140卷 2747-2777页

作者： Farman saifi mohd Javaid Abid Haleem s.m.Anas Department of mechanical Engineering Jamia Millia Islamia(A Central University)New Delhi110025India Department of Civil Engineering Jamia Millia Islamia(A Central University)New Delhi110025India

Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infras-tructure systems and networks capable of withstanding blast *** centered on high-profile facilities such as embassies and petrochemical plants,this concern now extends to a wider array of infrastructures and *** and scholars increasingly prioritize structural safety against explosions,particularly to prevent disproportionate collapse and damage to nearby *** has further amplified the reliance on oil and gas pipelines,making them vital for urban life and prime targets for terrorist ***,there is a growing imperative for computational engineering solutions to tackle blast loading on pipelines and mitigate associated risks to avert *** this study,an empty pipe model was successfully validated under contact blast conditions using Abaqus software,a powerful tool in mechanical engineering for simulating blast effects on buried *** a Eulerian-Lagrangian computational fluid dynamics approach,the investigation extended to above-surface and below-surface blasts at standoff distances of 25 and 50 *** descriptions in the numerical model relied on Abaqus’default mechanical *** analysis revealed varying pipe performance,with deformation decreasing as explosion-to-pipe distance *** explosion’s location relative to the pipe surface notably influenced deformation levels,a key finding highlighted in the ***,quantitative findings indicated varying ratios of plastic dissipation energy(PDE)for different blast scenarios compared to the contact blast(P0).specifically,P1(25 mm subsurface blast)and P2(50 mm subsurface blast)showed approximately 24.07%and 14.77%of P0’s PDE,respectively,while P3(25 mm above-surface blast)and P4(50 mm above-surface blast)exhibited lower PDE values,accounting for about 18.08%and 9.67%of P0’s PDE,***

关键词： Blast loading computational fluid dynamics computer modeling pipe networks response prediction structural safety

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In search of a pan-coronavirus vaccine:next-generation vaccine design and immune mechanisms

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Cellular & molecular Immunology 2024年第2期21卷 103-118页

作者： s.Cankat m.U.Demael L.swadling Division of Infection and Immunity Institute of Immunity and TransplantationUniversity College LondonPears BuildingLondon NW32PPUK

members of the coronaviridae family are endemic to human populations and have caused several epidemics and pandemics in recent *** this review,we will discuss the feasibility of and progress toward the ultimate goal of creating a pan-coronavirus vaccine that can protect against infection and disease by all members of the coronavirus *** will detail the unmet clinical need associated with the continued transmission of sARs-CoV-2,mERs-CoV and the four seasonal coronaviruses(HCoV-OC43,NL63,HKU1 and 229E)in humans and the potential for future zoonotic *** will highlight how first-generation sARs-CoV-2 vaccines and natural history studies have greatly increased our understanding of effective antiviral immunity to coronaviruses and have informed next-generation vaccine *** will then consider the ideal properties of a pan-coronavirus vaccine and propose a blueprint for the type of immunity that may offer ***,we will describe a subset of the diverse technologies and novel approaches being pursued with the goal of developing broadly or universally protective vaccines for coronaviruses.

关键词： Vaccine Coronavirus Cross-reactive immunity Cross-protection Universal

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Credit Card Fraud Detection Using Improved Deep Learning models

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Computers, materials & Continua 2024年第1期78卷 1049-1069页

作者： sumaya s.sulaiman Ibraheem Nadher sarab m.Hameed Computer science Department Al-Mustansiriya UniversityBaghdad10001Iraq Computer science Department University of BaghdadBaghdad10001Iraq Faculty of Basic Education Al-Mustansiriya UniversityBaghdad10001Iraq

Fraud of credit cards is a major issue for financial organizations and *** fraudulent actions become more complex,a demand for better fraud detection systems is *** learning approaches have shown promise in several fields,including detecting credit card ***,the efficacy of these models is heavily dependent on the careful selection of appropriate *** paper introduces models that integrate deep learning models with hyperparameter tuning techniques to learn the patterns and relationships within credit card transaction data,thereby improving fraud *** deep learning models:AutoEncoder(AE),Convolution Neural Network(CNN),and Long short-Term memory(LsTm)are proposed to investigate how hyperparameter adjustment impacts the efficacy of deep learning models used to identify credit card *** experiments conducted on a European credit card fraud dataset using different hyperparameters and three deep learning models demonstrate that the proposed models achieve a tradeoff between detection rate and precision,leading these models to be effective in accurately predicting credit card *** results demonstrate that LsTm significantly outperformed AE and CNN in terms of accuracy(99.2%),detection rate(93.3%),and area under the curve(96.3%).These proposed models have surpassed those of existing studies and are expected to make a significant contribution to the field of credit card fraud detection.

关键词： Card fraud detection hyperparameter tuning deep learning autoencoder convolution neural network long short-term memory resampling

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Factors influencing farmers’adoption of solar water-pumping systems in Gujarat

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Clean Energy 2024年第3期8卷 157-165页

作者： m sathish Kumar Y.A.Lad R.s.Pundir International Agribusiness management Institute Anand Agricultural UniversityAnand388110GujaratIndia Department of HRD&Pm International Agribusiness Management InstituteAnand Agricultural UniversityAnand388110GujaratIndia Department of Agribusiness Economics and Policies International Agribusiness Management InstituteAnand Agricultural UniversityAnand388110GujaratIndia

Agriculture has played an important role in the growth of the Indian *** and electricity are essential inputs for agriculture *** produces the third-largest amount of electricity in the world,behind China and the *** an incentive to increase production,most states provide free electricity to *** electricity has decreased groundwater levels and increased electricity *** objective of this study was to find out the factors that influenced farmers to adopt a solar water-pumping system in *** samples were randomly *** study examined the entire state of *** hundred and fifty farmers who adopted solar water-pumping systems were interviewed,including 50 banana farmers,50 cotton farmers and 50 groundnut *** data were collected through an *** adoption of solar water-pumping systems by farmers was identified using factor *** software was used to analyse the data *** this study,only two factors contributed to the variance of 59.469%.The adoption of solar water pumps by farmers was influenced by government policy and economic *** economic benefit variance of 33.20%was found,while a government policy variance was 26.27%.A solar water-pumping system has low initial costs,flexible credit policies motivate adoption,solar water-pumping systems can save electricity,and maintenance and repair costs are *** policy that includes solar water-pumping systems is motivated by awareness,subsidies for adoption and a fair price to sell energy *** are recommended to adopt a solar water-pumping system in conjunction with a drip irrigation system to receive additional *** successful scheme will be recommended to other states in India for implementation.

关键词： solar water-pumping system factor analysis banana cotton groundnut famers

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肥厚性心肌病:对比剂增强心血管mRI延迟强化定量分析

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国际医学放射学杂志 2011年第2期 169-169页

作者： C.J.Harrigan D.C.Peters C.m.Gibson B.J.maron W.J.manning m.s.maron 王鹤 PERFUsE Core Laboratories and Data Coordinating Center Beth Israel Deaconess Medical CenterHarvard Medical School

目的确定重复性最好的半自动灰阶阈值技术对大样本肥厚性心肌病(HCm)病人钆延迟强化(LGE)的定量。材料与方法研究由参与机构的内部审查委员会核准,所有

关键词： mRI 延迟强化肥厚性心肌病心血管灰阶定量分析

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A secure Framework for WsN-IoT Using Deep Learning for Enhanced Intrusion Detection

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Computers, materials and Continua 2024年第1期81卷 471-501页

作者： Kumar C.O. Gajendran s. marappan s. Zakariah m. Almazyad A.s. school of Computer science & Engineering Vellore Institute of Technology Chennai Campus Chennai 600127 India school of Electronics & Engineering Vellore Institute of Technology Chennai Campus Chennai 600127 India Department of Computer sciences and Engineering College of Applied Science King Saud University Riyadh 11543 Saudi Arabia Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia

The security of the wireless sensor network-Internet of Things (WsN-IoT) network is more challenging due to its randomness and self-organized nature. Intrusion detection is one of the key methodologies utilized to ensure the security of the network. Conventional intrusion detection mechanisms have issues such as higher misclassification rates, increased model complexity, insignificant feature extraction, increased training time, increased run time complexity, computation overhead, failure to identify new attacks, increased energy consumption, and a variety of other factors that limit the performance of the intrusion system model. In this research a security framework for WsN-IoT, through a deep learning technique is introduced using modified Fuzzy-Adaptive DenseNet (mF_AdaDenseNet) and is benchmarked with datasets like NsL-KDD, UNsWNB15, CIDDs-001, Edge IIoT, Bot IoT. In this, the optimal feature selection using Capturing Dingo Optimization (CDO) is devised to acquire relevant features by removing redundant features. The proposed mF_AdaDenseNet intrusion detection model offers significant benefits by utilizing optimal feature selection with the CDO algorithm. This results in enhanced Detection Capacity with minimal computation complexity, as well as a reduction in False Alarm Rate (FAR) due to the consideration of classification error in the fitness estimation. As a result, the combined CDO-based feature selection and mF_AdaDenseNet intrusion detection mechanism outperform other state-of-the-art techniques, achieving maximal Detection Capacity, precision, recall, and F-measure of 99.46%, 99.54%, 99.91%, and 99.68%, respectively, along with minimal FAR and mean Absolute Error (mAE) of 0.9% and 0.11. © 2024 The Authors.

关键词： accuracy Deep learning false alarm rate feature selection fuzzy rules intrusion detection wireless sensor networks

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Improving Generalization for Hyperspectral Image Classification: The Impact of Disjoint sampling on Deep models

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Computers, materials and Continua 2024年第1期81卷 503-532页

作者： Ahmad m. mazzara m. Distefano s. Khan A.m. Altuwaijri H.A. Department of Computer science National University of Computer and Emerging Sciences Chiniot 35400 Pakistan Institute of software Development and Engineering Innopolis University Innopolis 420500 Russian Federation Dipartimento di matematica e Informatica—mIFT University of Messina Messina 98121 Italy school of Computer science University of Hull Hull HU6 7RX United Kingdom Department of Geography College of Humanities and Social Sciences King Saud University Riyadh 11451 Saudi Arabia

Disjoint sampling is critical for rigorous and unbiased evaluation of state-of-the-art (sOTA) models e.g., Attention Graph and Vision Transformer. When training, validation, and test sets overlap or share data, it introduces a bias that inflates performance metrics and prevents accurate assessment of a model’s true ability to generalize to new examples. This paper presents an innovative disjoint sampling approach for training sOTA models for the Hyperspectral Image Classification (HsIC). By separating training, validation, and test data without overlap, the proposed method facilitates a fairer evaluation of how well a model can classify pixels it was not exposed to during training or validation. Experiments demonstrate the approach significantly improves a model’s generalization compared to alternatives that include training and validation data in test data (A trivial approach involves testing the model on the entire Hyperspectral dataset to generate the ground truth maps. This approach produces higher accuracy but ultimately results in low generalization performance). Disjoint sampling eliminates data leakage between sets and provides reliable metrics for benchmarking progress in HsIC. Disjoint sampling is critical for advancing sOTA models and their real-world application to large-scale land mapping with Hyperspectral sensors. Overall, with the disjoint test set, the performance of the deep models achieves 96.36% accuracy on Indian Pines data, 99.73% on Pavia University data, 98.29% on University of Houston data, 99.43% on Botswana data, and 99.88% on salinas data. © 2024 The Authors.

关键词： disjoint sampling Graph CNN Hyperspectral image classification spatial-spectral transformer

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Acceleration of solar wind particles due to inertial Alfvén waves

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Communications in Theoretical Physics 2024年第6期76卷 137-141页

作者： Kiran Batool Imran A Khan m shamir Abdul Kabir s Ayaz Theoretical Physics Department National Centre for PhysicsIslamabad 44000Pakistan Department of space sciences Institute of Space TechnologyIslamabad 44000Pakistan space and Astrophysics Research Lab(sARL) National Center of GIS and Space Applications(NCGSA)Islamabad 44000Pakistan salam Chair Department of PhysicsGC University LahoreKatchery RoadLahorePunjab 54000Pakistan Department of space science and CsPAR University of Alabama in HuntsvilleHuntsvilleAL 35899United States of America

Gaining an understanding of the effects and dynamics of the solar wind is crucial for the study of space weather,Earth's magnetosphere,spacecraft protection,the dynamics of the solar system,and various other *** show that Alfvén waves effectively transfer energy to resonant *** study demonstrates how inertial Alfvén waves deliver their energy to resonant plasma particles in different solar environments under certain *** analysis shows that inertial Alfvén waves experience more rapid damping with increasing parallel wavenumber,ambient magnetic field strength,and particle number density,coupled with a decrease in *** rate of energy transfer to resonant particles intensifies with higher temperatures and reduced parallel wavenumber and particle number *** with higher initial velocities actively participate in Landau damping,especially in regions with a stronger ambient magnetic field.

关键词： solar wind inertial Alfven waves resonant particles

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multiple scales method for analyzing a forced damped rotational pendulum oscillatorwithgallows

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Communications in Theoretical Physics 2024年第5期76卷 58-67页

作者： Haifa A Alyousef Alvaro H salas B m Alotaibi s A El-Tantawy Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of mathematics and statistics Universidad Nacional de ColombiaFIZMAKO Research GroupColombia Department of Physics Faculty of SciencePort Said UniversityPort Said 42521Egypt Research Center for Physics(RCP) Department of PhysicsFaculty of Science and ArtsAl-MikhwahAl-Baha UniversityAl-Baha 1988Saudi Arabia

This study reports the analytical solution for a generalized rotational pendulum system with gallows and periodic excited *** multiple scales method(msm)is applied to solve the proposed *** types of rotational pendulum oscillators are studied and talked about in *** include the forced damped rotating pendulum oscillator with gallows,the damped standard simple pendulum oscillator,and the damped rotating pendulum oscillator without *** msm first-order approximations for all the cases mentioned are derived in *** obtained results are illustrated with concrete numerical *** first-order msm approximations are compared to the fourth-order Runge-Kutta(RK4)numerical ***,the maximum error is estimated for the first-order approximations obtained through the msm,compared to the numerical approximations obtained by the RK4 ***,we conducted a comparative analysis of the outcomes obtained by the used method(msm)and He-msm to ascertain their respective levels of *** proposed method can be applied to analyze many strong nonlinear oscillatory equations.

关键词： rotational pendulum system multiple scales method approximate solution damped oscillations forced pendulum with gallows he-multiple scales method

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Transcriptional reprogramming during human osteoclast differentiation identifies regulators of osteoclast activity

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Bone Research 2024年第1期12卷 180-198页

作者： morten s.Hansen Kaja madsen maria Price Kent søe Yasunori Omata mario m.Zaiss Caroline m.Gorvin morten Frost Alexander Rauch molecular Endocrinology Laboratory(KmEB) Department of EndocrinologyOdense University HospitalDK-5000 Odense CDenmark Department of Clinical Research Faculty of Health SciencesUniversity of Southern DenmarkDK-5000 Odense CDenmark Clinical Cell Biology Pathology Research UnitDepartment of Clinical ResearchUniversity of Southern DenmarkDK-5000 Odense CDenmark Institute of metabolism and systems Research(ImsR)and Centre for Diabetes Endocrinology and Metabolism(CEDAM)University of BirminghamBirmingham B152TTUK Centre for membrane Proteins and Receptors(COmPARE) Universities of Birmingham and NottinghamBirmingham B152TTUK Department of molecular medicine University of Southern DenmarkDK-5000 Odense CDenmark Department of Orthopedic surgery Faculty of MedicineThe University of TokyoTokyo 113-8655Japan Department of Internal medicine 3 Rheumatology and ImmunologyFriedrich-Alexander-University Erlangen-Nürnberg(FAU)and Universitätsklinikum ErlangenD-91054 ErlangenGermany Deutsches Zentrum Immuntherapie(DZI) Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum ErlangenD-91054 ErlangenGermany steno Diabetes Center Odense Odense University HospitalDK-5000 Odense CDenmark

Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone *** novel antiosteoporotic therapeutics are needed,understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment *** study aimed to provide an overview of transcriptional reprogramming during human osteoclast *** were differentiated from CD14+monocytes from eight female *** sequencing during differentiation revealed 8980 differentially expressed genes grouped into eight temporal patterns conserved across *** patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density *** analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional *** donor-specific expression patterns revealed genes at the monocyte stage,such as filamin B(FLNB)and oxidized low-density lipoprotein receptor 1(OLR1,encoding LOX-1),that are predictive of the resorptive activity of mature *** expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation,and these receptors are associated with bone mineral density sNPs,suggesting that they play a pivotal role in osteoclast differentiation and *** regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1(C5AR1),somatostatin receptor 2(ssTR2),and free fatty acid receptor 4(FFAR4/GPR120).Activating C5AR1 enhanced osteoclast formation,while activating ssTR2 decreased the resorptive activity of mature osteoclasts,and activating FFAR4 decreased both the number and resorptive activity of mature *** conclus

关键词： osteoclast programming identif

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