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Review of Artificial Neural Networks for Wind Turbine Fatigue Prediction

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Structural Durability & health Monitoring 2024年第6期18卷 707-737页

作者： Husam AlShannaq Aly Mousaad Aly Windstorm Impact Science and Engineering(WISE)Research LabLouisiana State UniversityBaton RougeLA 70803USA

Wind turbines have emerged as a prominent renewable energy source *** monitoring and detection methods are crucial to enhance their operational effectiveness,particularly in identifying fatigue-related *** review focuses on leveraging artificial neural networks(ANNs)for wind turbine monitoring and fatigue detection,aiming to provide a valuable reference for researchers in this domain and related *** various ANN techniques,including General Regression Neural Network(GRNN),Support Vector Machine(SVM),Cuckoo Search Neural Network(CSNN),Backpropagation Neural Network(BPNN),Particle Swarm Optimization Artificial Neural Network(PSO-ANN),Convolutional Neural Network(CNN),and nonlinear autoregressive networks with exogenous inputs(NARX),we investigate the impact of average wind speed on stress transfer function and fatigue damage in wind turbine *** findings indicate significant precision levels exhibited by GRNN and SVM,making them suitable for practical *** demonstrates superiority over BPNN and PSO-ANN in predicting blade fatigue life,showcasing enhanced accuracy,computational speed,precision,and convergence rate towards the global ***,CNN and NARX models display exceptional accuracy in classification *** results underscore the potential of ANNs in addressing challenges in wind turbine monitoring and fatigue ***,it’s important to acknowledge limitations such as data availability and model *** research should explore integrating real-time data and advanced optimization techniques to improve prediction accuracy and applicability in real-world *** summary,this review contributes to advancing the understanding of ANNs’efficacy in wind turbine monitoring and fatigue detection,offering insights and methodologies that can inform future research and practical applications in renewable energy systems.

关键词： Wind turbine fatigue prediction artificial neural network

A modular microfluidic platform to study how fluid shear stress alters estrogen receptor phenotype in ER+breast cancer cells

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Microsystems & Nanoengineering 2024年第1期10卷 287-299页

作者： Braulio Andrés Ortega Quesada Jonathan Cuccia Rachael Coates Blake Nassar Ethan Littlefield Elizabeth C.Martin Adam T.Melvin Cain Department of Chemical Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Chemical and Biological Engineering Clemson UniversityClemsonSC 29634USA Biological and Agricultural Engineering Louisiana State UniversityBaton RougeLA 70803USA Department Medicine Section Hematology and Medical OncologyTulane UniversityNew OrleansLA 70118USA

Metastatic breast cancer leads to poor prognoses and worse outcomes in patients due to its invasive behavior and poor response to *** is still unclear what biophysical and biochemical factors drive this more aggressive phenotype in metastatic cancer;however recent studies have suggested that exposure to fluid shear stress in the vasculature could cause *** this study a modular microfluidic platform capable of mimicking the magnitude of fluid shear stress(FSS)found in human vasculature was designed and *** device provides a platform to evaluate the effects of FSS on MCF-7 cell line,an estrogen receptor positive(ER+)breast cancer cell line,during circulation in the *** of the effects of FSS on MCF-7 cells was carried out utilizing two approaches:single cell analysis and bulk *** single cell analysis,cells were trapped in a microarray after exiting the serpentine channel and followed by immunostaining on the device(on-chip).Bulk analysis was performed after cells were collected in a microtube at the outlet of the microfluidic serpentine channel for western blotting(off-chip).It was found that cells exposed to an FSS magnitude of 10 dyn/cm^(2) with a residence time of 60 s enhanced expression of the proliferation marker Ki67 in the MCF-7 cell line at a single cell *** understand possible mechanisms for enhanced Ki67 expression,on-chip and off-chip analyses were performed for pro-growth and survival pathways ERK,AKT,and JAK/*** demonstrated that after shearing the cells phosphorylation of p-AKT,p-mTOR,and p-STAT3 were ***,there was no change in p-ERK1/*** is a mediator of ER rapid signaling,analysis of phosphorylated ERαwas carried out and no significant differences between sheared and non-sheared populations were *** together these results demonstrate that FSS can increase phosphorylation of proteins associated with a more aggressive phenotype in circulating cancer *** findin

关键词： fluid breast estrogen

PAL-BERT:An Improved Question Answering Model

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2729-2745页

作者： Wenfeng Zheng Siyu Lu Zhuohang Cai Ruiyang Wang Lei Wang Lirong Yin School of Automation University of Electronic Science and Technology of ChinaChengdu610054China Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA70803USA

In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant ***,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has ***,model training has become more costly and less *** enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language ***,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is ***,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the ***,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training *** with traditional models,PAL-BERT significantly improves the NLP task’s performance.

关键词： PAL-BERT question answering model pretraining language models ALBERT pruning model network pruning TextCNN BiLSTM

Controllable transitions among phase-matching conditions in a single nonlinear crystal

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Chinese Optics Letters 2024年第2期22卷 141-147页

作者：曾梓琦尤世欣杨子祥袁晨智由成龙金锐博 Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China Quantum Photonics Laboratory Department of Physics and AstronomyLouisiana State UniversityBaton RougeLouisiana 70803USA

Entangled photon pairs are crucial resources for quantum information processing *** the process of spontaneous parametric downconversion(SPDC),we can generate these photon pairs using bulk nonlinear ***,the crystal is designed to satisfy a specific type of phase-matching ***,we report controllable transitions among different types of phase matching in a single periodically poled potassium titanyl phosphate *** carefully selecting pump conditions,we can satisfy different phase-matching *** allows us to observe first-order Type-II,fifth-order Type-I,third-order Type-0,and fifth-order Type-II *** temperature-dependent spectra of our source were also analyzed in ***,we discussed the possibility of observing more than nine SPDCs in this *** work not only deepens the understanding of the physics behind phase-matching conditions,but also offers the potential for a highly versatile entangled biphoton source for quantum information research.

关键词： spontaneous parametric downconversion nonlinear crystals phase-matching condition

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An intelligent impulsive noise mitigation with deep learning method

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International Journal of Mechanical System Dynamics 2024年第3期4卷 346-360页

作者： Guo Yang Yuwen Qian Zikun Wang Xiangwei Zhou Wen Wu The School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjingChina The Division of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLouisianaUSA

To enable message transmission among sensors and equipment,power line communication(PLC)is a widely adopted smart ***,due to the occurrence of impulsive noise(IN),reliable transmissions over PLC channels in the smart grid are ***,in this paper,we propose an adaptive noise mitigation scheme to clip the IN with the sliding window-based method,where the altitude of the received signal in the current time slots is obtained by computing the average altitude of signals in the previous and next time *** detect the states of IN and dynamically estimate the power threshold of signals for the IN mitigation scheme,we develop an intelligent algorithm based on the long short-term memory *** prevent the useful signals from being eliminated as IN signals,we propose the accelerated proximal gradient method(APGM)based on tone reservation to reduce the peak-to-average power ratio(PAPR)for the transmitting signals with low computational *** addition,the closed-form expression of the bit error rate(BER)is derived for the proposed sliding window-based IN mitigation scheme according to the probability density function of the *** results demonstrate that the proposed IN mitigation scheme achieves a better BER performance than the conventional IN mitigation *** addition,the APGM aided by IN mitigation can further improve BER performance due to the PAPR reduction.

关键词： impulsive noise deep learning smart grid

Adhesion of Technical Lignin-Based Non-Isocyanate Polyurethane Adhesives for Wood Bonding

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Journal of Renewable Materials 2024年第7期12卷 1187-1205页

作者： Jaewook Lee Byung-Dae Park Qinglin Wu Department of Wood and Paper Science Kyungpook National UniversityDaegu41566Korea School of Renewable Natural Resources Louisiana State UniversityBaton RougeLA70806USA

Lignin is the most abundant aromatic natural polymer,and receiving great attention in replacing various petro-leum-based *** aim of this study is to investigate the feasibility of technical lignin as a polyol for the synthesis of non-isocyanate polyurethane(NIPU)adhesives to substitute current polyurethane(PU)adhesives that have been synthesized with toxic isocyanate and *** hardwood kraft lignin(C-HKL)was extracted from black liquor from a pulp mill followed by acetone fractionation to obtain acetone soluble-HKL(AS-HKL).Then,C-HKL,AS-HKL,and softwood sodium lignosulfonate(LS)were used for the synthesis of technical lignin-based NIPU adhesives through carbonation and polyamination and silane as a *** adhesion per-formance was determined for *** spectra showed the formation of urethane bonds and the reaction between lignin and *** NIPU adhesives prepared with C-HKL showed the highest adhesion strength among the three lignin-based NIPU *** the silane addition level increased,the adhesion strength of NIPU adhesives increased whereas formaldehyde emission decreased for all NIPU adhesives *** results indicate that NIPU adhesives based on technical kraft lignin have a great potential as polyol for the synth-esis of bio-based NIPU adhesives for wood bonding.

关键词： Technical lignin non-isocyanate polyurethane wood adhesives adhesion strength formaldehyde emission

THE GLOBAL EXISTENCE OF STRONG SOLUTIONS FOR A NON-ISOTHERMAL IDEAL GAS SYSTEM

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Acta Mathematica Scientia 2024年第3期44卷 865-886页

作者：韩斌赖宁安 Andrei TARFULEA Department of Mathematics Hangzhou Dianzi UniversityHangzhou310018China School of Mathematical Sciences Zhejiang Normal UniversityJinhua321004China Department of Mathematics Louisiana State UniversityBaton Rouge70803USA

We investigate the global existence of strong solutions to a non-isothermal ideal gas model derived from an energy variational *** first show the global wellposedness in the Sobolev space H^(2)(R^(3)) for solutions near equilibrium through iterated energy-type bounds and a continuity *** then prove the global well-posedness in the critical Besov space B^(3/2)_(2,1) by showing that the linearized operator is a contraction mapping under the right circumstances.

关键词： thermal fluid equations energy-variational method well-posedness theory for PDE paraproduct calculus

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Geothermo-mechanical alterations due to heat energy extraction in enhanced geothermal systems: Overview and prospective directions

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Deep Underground Science and Engineering 2024年第3期3卷 256-268页

作者： Mary C.Ngoma Oladoyin Kolawole Olufemi Olorode John A.Reif Jr.Department of Civil and Environmental EngineeringNew Jersey Institute of TechnologyNewarkUSA Department of Petroleum Engineering Louisiana State UniversityBaton RougeUSA

Geothermal energy from deep underground (or geological) formations,with or without its combination with carbon capture and storage (CCS),can be a key technology to mitigate anthropogenic greenhouse gas emissions and meet the 2050 net‐zero carbon emission *** resources in low‐permeability and medium‐and high‐temperature reservoirs in sedimentary sequence require hydraulic stimulation for enhanced geothermal systems (EGS).However,fluid migration for geothermal energy in EGS or with potential CO_(2) storage in a CO_(2)‐EGS are both dependent on the in situ flow pathway network created by induced fluid *** thermo‐mechanical interactions can be complex and induce varying alterations in the mechanical response when the working fluid is water (in EGS) or supercritical CO_(2)(in CO_(2)‐EGS),which could impact the geothermal energy recovery from geological ***,there is a need for a deeper understanding of the heat extraction process in EGS and CO_(2)‐*** study presents a systematic review of the effects of changes in mechanical properties and behavior of deep underground rocks on the induced flow pathway and heat recovery in EGS reservoirs with or without CO_(2) storage in CO_(2) ‐***,we proposed waterless‐stimulated EGS as an alternative approach to improve heat energy extraction in ***,based on the results of our literature review and proposed ideas,we recommend promising areas of investigation that may provide more insights into understanding geothermo‐mechanics to further stimulate new research studies and accelerate the development of geothermal energy as a viable clean energy technology.

关键词： CO_(2)-EGS enhanced geothermal systems geomechanics geothermal energy underground thermal energy

维普期刊数据库博看期刊

DPAL-BERT:A Faster and Lighter Question Answering Model

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 771-786页

作者： Lirong Yin Lei Wang Zhuohang Cai Siyu Lu Ruiyang Wang Ahmed AlSanad Salman A.AlQahtani Xiaobing Chen Zhengtong Yin Xiaolu Li Wenfeng Zheng Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA 70803USA School of Automation University of Electronic Science and Technology of ChinaChengdu610054China College of Computer and Information Sciences King Saud UniversityRiyadh11574Saudi Arabia School of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA College of Resources and Environmental Engineering Guizhou UniversityGuiyang550025China School of Geographical Sciences Southwest UniversityChongqing400715China

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering ***,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced *** study aims to minimize the inference time of such models while maintaining computational *** also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and *** research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge *** experimental results showed that the distilled models greatly outperform models trained from *** addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the *** demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.

关键词： DPAL-BERT question answering systems knowledge distillation model compression BERT Bi-directional long short-term memory(BiLSTM) knowledge information transfer PAL-BERT training efficiency natural language processing