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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1033-1050页

作者： T.I.TOLUWALOJU C.k.THEIN D.HALIM Department of Mechanical Materials and Manufacturing EngineeringUniversity of Nottingham Ningbo ChinaNingbo 315100Zhejiang ProvinceChina Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute University of Nottingham Ningbo ChinaNingbo 315048Zhejiang ProvinceChina

The levered-dual response(LEDAR)Coulomb-damped system attains near resonant vibration isolation by differential preloads/offsets in linear *** takes the advantages of both the preloads/offsets in linear springs and the guiderail friction for realizing different levels of vibration *** isolation capacities are investigated on the strategies with both the horizontal and vertical guiderails,with the horizontal rail only,and without *** compressive preloads generally result in the consumption of most of the initial excitation energy so as to overcome the potential *** isolation onsets at the frequency ratio of 1∓0.095 on the left-hand side(LHS)and the right-hand side(RHS)of the lever are relative to the load plate *** observed near resonant isolation thus makes the LEDAR system a candidate for the isolation of the mechanical systems about resonance while opening a path for simultaneous harvesterisolation functions and passive functions at extreme frequencies.

关键词： lever ratio Coulomb damping preload tension/compression isolation band/depth offset potential

Advancements in nanotechnology for the delivery of phytochemicals

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Journal of Integrative Medicine 2024年第4期22卷 385-398页

作者： Divya Chauhan Pavan k.Yadav Nazneen Sultana Arun Agarwal Saurabh Verma Manish k.Chourasia Jiaur R.Gayen Division of Pharmaceutics and Pharmacokinetics Central Drug Research InstituteCouncil of Scientific and Industrial ResearchLucknow 226031Uttar PradeshIndia Academy of Scientific and Innovative Research Ghaziabad 201002Uttar PradeshIndia

Phytosomes(phytophospholipid complex) are dosage forms that have recently been introduced to increase the stability and therapeutic effect of herbal medicine. Currently, bioactive herbs and the phytochemicals they contain are considered to be the best remedies for chronic diseases. One promising approach to increase the efficacy of plant-based therapies is to improve the stability and bioavailability of their bio-active ingredients. Phytosomes employ phospholipids as their active ingredients, and use their amphiphilic properties to solubilize and protect herbal extracts. The unique properties of phospholipids in drug delivery and their use in herbal medicines to improve bioavailability results in significantly enhanced health benefits. The introduction of phytosome nanotechnology can alter and revolutionize the current state of drug delivery. The goal of this review is to explain the application of phytosomes, their future prospects in drug delivery, and their advantages over conventional formulations.

关键词： Phytochemical Bioavailability Drug delivery system Phytosome Plant extracts

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

Physical properties and maximum allowable mass-radius relation of complexity-free compact stellar objects within modified f(R,T)gravity formalism

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Chinese Physics C 2024年第7期48卷 273-288页

作者： M.k.Jasim S.k.Maurya Abdelghani Errehymy Ali khalid Jassim kottakkaran Sooppy Nisar Abdel-Haleem Abdel-Aty Department of Mathematical and Physical Sciences College of Arts and SciencesUniversity of NizwaNizwa 616Sultanate of Oman Astrophysics Research Centre School of MathematicsStatistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X54001Durban 4000South Africa Electrical Engineering Department College of EngineeringMustansiriyah UniversityBaghdadIraq Department of Mathematics College of Science and Humanities in AlkharjPrince Sattam bin Abdulaziz UniversityAl KharjSaudi Arabia Department of Physics College of SciencesUniversity of BishaP.O.Box 344Bisha 61922Saudi Arabia

This paper investigates the physical properties and predicted radii of compact stars generated by the Tolman-IV complexity-free model within the background of modified gravity theory,particularly the f(R,T)-gravity theory,under complexity formalism for a spherically symmetric spacetime proposed by ***[Phys Rev D 97:044010,2018].By solving the resulting set of differential equations,we obtain the explicit forms of the energy-momentum(EM)tensor components,including the density,radial pressure,and tangential *** influence of the parameterχon various physical properties of the star is thoroughly *** model undergoes a series of rigorous tests to determine its physical *** findings indicate that the model exhibits regularity,stability,and a surface with vanishing *** boundary of this surface is determined by carefully selecting the parameter *** complexity method employed in f(R,T)gravity offers an interesting approach for developing astrophysical models that are consistent with observable events as demonstrated by recent *** this regard,we use observational data from the GW190814 event,detected by the LIGO and Virgo observatories,to investigate the validity of the Tolman-IV model in f(R,T)*** analysis includes comparing the model's predictions with the observed characteristics of the compact object involved in the *** addition,data from two-millisecond pulsars,PSR J1614-2230 and PSR J0952-0607,are incorporated to further constrain the theoretical ***,we present a diagram depicting the relationship between the total mass and radius of the compact object candidates for different values ofχ.

关键词： complexity modified gravity compact Stars

Gastric cystica profunda:Another indication for minimally invasive endoscopic resection techniques?

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World Journal of Gastroenterology 2024年第27期30卷 3278-3283页

作者： Harjot k Bedi Douglas Motomura Neal Shahidi Department of Medicine University of British ColumbiaVancouver V6Z 2K5BCCanada

Gastric cancer presents a significant global health burden,as it is the fifth most common malignancy and fourth leading cause of cancer mortality *** in incidence rates across regions underscores the multifactorial etiology of this *** overall 5-year survival rate remains low despite advances in its diagnosis and *** surgical gastrectomy was previously standard-of-care,endoscopic resection techniques,including endoscopic mucosal resection and endoscopic submucosal dissection(ESD)have emerged as effective alternatives for early *** to surgical resection,endoscopic resection techniques have comparable 5-year survival rates,reduced treatment-related adverse events,shorter hospital stays and lower *** also enables en bloc resection,thus affording organ-sparing curative endoscopic resection for early *** this editorial,we comment on the recent publication by Geng et al regarding gastric cystica profunda(GCP).GCP is a rare gastric pseudotumour with the potential for malignant *** presents a diagnostic challenge due to its nonspecific clinical manifestations and varied endoscopic *** are several gaps in the literature regarding the diagnosis and management of GCP which warrants further research to standardize patient *** in endoscopic resection techniques offer promising avenues for GCP and early gastric cancers.

关键词： Early gastric cancer Endoscopy Endoscopic submucosal dissection Gastric cystica profunda

Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 977-997页

作者： Mustufa Haider Abidi Hisham Alkhalefah Mohamed k.Aboudaif Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box-800Riyadh11421Saudi Arabia

The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for ***,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient *** methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful ***,this paper proposes a crossover-based Multilayer Perceptron(CMLP)*** collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of *** an attack is detected,healthcare professionals are promptly alerted to prevent data *** paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are *** results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient *** the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and ***,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.

关键词： Smart healthcare systems multilayer perceptron cybersecurity adversarial attack detection Healthcare 4.0

Enhanced quantum resources via two distant atom-cavity systems under the influence of atomic dissipation

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Communications in Theoretical Physics 2024年第2期76卷 62-73页

作者： M Setodeh kheirabady M k Tavassoly M Rafeie E Ghasemian Laser and Optics Group Faculty of PhysicsYazd UniversityYazd 89195-741Iran Department of Electrical Engineering Faculty of Intelligent Systems Engineering and Data SciencePersian Gulf UniversityBushehrIran

Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key quantum resources may be protected and even enhanced by the implementation of some special hybrid open quantum systems. Here, we aim to show how a dissipative atom-cavity-system can be accomplished to generate enhanced quantum *** do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atoms interacting with a single-mode cavity field. In practical applications, a classical laser field may be applied to drive each atomic subsystem. After driving the system, a Bell-state measurement is performed on the output of the system to quantify the entanglement and coherence. The obtained results reveal that the remote entanglement and coherence between the atoms existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglement between two atoms inside each dissipative cavity attenuates due to the presence of unwanted environmental ***, the local coherence may show the same behavior as the remote ***, the system provides the steady state entanglement in various interaction regimes,particularly in the strong atom-cavity coupling and with relatively large detuning. More interestingly, our numerical analyses demonstrate that the system may show a memory effect due to the fact that the death and revival of the entanglement take place during the interaction. Our proposed model may find potential applications for the implementation of long distance quantum networks. In particular, it facilitates the distribution of quantum resources between the nodes of large-scale quantum networks for secure communication.

关键词： remote entanglement and coherence atomic dissipation steady state entanglement Bell-statemeasurement

Predictive active control of building structures using LQR and artificial intelligence

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 489-502页

作者： Nirmal S.Mehta Vishisht Bhaiya k.A.Patel Ehsan Noroozinejad Farsangi Department of Civil Engineering SVNIT SuratGujarat 395007India Urban Transformations Research Centre Western Sydney UniversityNSWAustralia

This study presents a neural network-based model for predicting linear quadratic regulator(LQR)weighting matrices for achieving a target response *** on the expected weighting matrices,the LQR algorithm is used to determine the various responses of the *** responses are determined by numerically analyzing the governing equation of motion using the state-space *** training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQR weighting *** study the effectiveness of an LQR-based neural network(LQRNN),the actual percentage reduction in the responses obtained from using LQRNN is compared with the target percentage ***,to investigate the efficacy of an active control system using LQRNN,the controlled responses of a system are compared to the corresponding uncontrolled *** trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage *** on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using ***,the LQRNN algorithm can replace conventional LQR control with the use of an active control system.

关键词： active control system linear quadratic regulator artificial neural networks state-space approach response effectiveness factor resilience

Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 932-945页

作者： Bin Yang Yaguo Lei Xiang Li Naipeng Li Asoke k.Nandi the key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System the School of Mechanical EngineeringXi’an Jiaotong UniveristyXi’an 710049 the Hunan Provincial key Labortory of Health Maintenance for Mechanical Equipment Hunan Univeristy of Science and TechnologyXiangtan 411201China the key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an Jiaotong UniveristyXi’an 710049China the Department of Electronic and Electrical Engineering Brunel University LondonUxbridge UB83PHUK

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source ***,in engineering scenarios,achieving such high-quality label annotation is difficult and *** incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled *** overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three ***,a residual network with dual classifiers is to learn features from cross-domain ***,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source *** the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised ***,the adaptation trajectories are designed for sample distributions across *** ensures that the target domain samples are only adapted with the pure-labeled *** LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related *** results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

关键词： Deep transfer learning domain adaptation incorrect label annotation intelligent fault diagnosis rotating machines