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TCAS-PINN:Physics-informed neural networks with a novel temporal causality-based adaptive sampling method

Chinese Physics B 2024年第5期33卷 344-364页

作者：郭嘉王海峰古仕林侯臣平 college of science National University of Defense TechnologyChangsha 410073China

Physics-informed neural networks(PINNs)have become an attractive machine learning framework for obtaining solutions to partial differential equations(PDEs).PINNs embed initial,boundary,and PDE constraints into the loss function.The performance of PINNs is generally affected by both training and sampling.Specifically,training methods focus on how to overcome the training difficulties caused by the special PDE residual loss of PINNs,and sampling methods are concerned with the location and distribution of the sampling points upon which evaluations of PDE residual loss are accomplished.However,a common problem among these original PINNs is that they omit special temporal information utilization during the training or sampling stages when dealing with an important PDE category,namely,time-dependent PDEs,where temporal information plays a key role in the algorithms used.There is one method,called Causal PINN,that considers temporal causality at the training level but not special temporal utilization at the sampling level.Incorporating temporal knowledge into sampling remains to be studied.To fill this gap,we propose a novel temporal causality-based adaptive sampling method that dynamically determines the sampling ratio according to both PDE residual and temporal causality.By designing a sampling ratio determined by both residual loss and temporal causality to control the number and location of sampled points in each temporal sub-domain,we provide a practical solution by incorporating temporal information into sampling.Numerical experiments of several nonlinear time-dependent PDEs,including the Cahn–Hilliard,Korteweg–de Vries,Allen–Cahn and wave equations,show that our proposed sampling method can improve the performance.We demonstrate that using such a relatively simple sampling method can improve prediction performance by up to two orders of magnitude compared with the results from other methods,especially when points are limited.

关键词： partial differential equation physics-informed neural networks residual-based adaptive sampling temporal causality

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A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

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Computers, Materials & Continua 2024年第1期78卷 653-676页

作者： Haibo Li Yongbo Yu Zhenbo Zhao Xiaokang Tang college of Computer science and Technology Huaqiao UniversityXiamen361021China

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

关键词： Time series short-term prediction multi-granularity event alignment event matching

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Dynamic Analysis of the Multi-state Reliability System with Priority Repair Discipline

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 665-694页

作者： Aihemaitijiang YUMAIER Ehmet KASIM college of Mathematics and Systems science Xinjiang UniversityUrumqi 830046China

This paper considers a multi-state repairable system that is composed of two classes of components,one of which has a priority for repair.First,we investigate the well-posedenss of the system by applying the operator semigroup theory.Then,using Greiner’s idea and the spectral properties of the corresponding operator,we obtain that the time-dependent solution of the system converges strongly to its steady-state solution.

关键词： multi-state system C0-semigroup Dirichlet operator well-posedness asymptotic behavior

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Emulsifying property,antioxidant activity,and bitterness of soybean protein isolate hydrolysate obtained by Corolase PP under high hydrostatic pressure

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Food science and Human Wellness 2024年第3期13卷 1271-1278页

作者： Haining Guan Chunmei Feng Min Ren Xiaojun Xu Dengyong Liu Xiaoqin Diao college of Food science and Technology Bohai UniversityJinzhou 121013China

Enzymatic hydrolysis of proteins can enhance their emulsifying properties and antioxidant activities.However,the problem related to the hydrolysis of proteins was the generation of the bitter taste.Recently,high hydrostatic pressure(HHP)treatment has attracted much interest and has been used in several studies on protein modification.Hence,the study aimed to investigate the effects of enzymatic hydrolysis by Corolase PP under different pressure treatments(0.1,100,200,and 300 MPa for 1-5 h at 50℃)on the emulsifying property,antioxidant activity,and bitterness of soybean protein isolate hydrolysate(SPIH).As observed,the hydrolysate obtained at 200 MPa for 4 h had the highest emulsifying activity index(47.49 m^(2)/g)and emulsifying stability index(92.98%),and it had higher antioxidant activities(44.77%DPPH free radical scavenging activity,31.12%superoxide anion radical scavenging activity,and 61.50%copper ion chelating activity).At the same time,the enhancement of emulsion stability was related to the increase of zeta potential and the decrease of mean particle size.In addition,the hydrolysate obtained at 200 MPa for 4 h had a lower bitterness value and showed better palatability.This study has a broad application prospect in developing food ingredients and healthy foods.

关键词： Soybean protein isolate High hydrostatic pressure Emulsification Antioxidant Bitter taste

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Probiotic cocktails accelerate baicalin metabolism in the ileum to modulate intestinal health in broiler chickens

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Journal of Animal science and Biotechnology 2024年第2期15卷 779-794页

作者： Mingkun Gao Chaoyong Liao Jianyang Fu Zhonghua Ning Zengpeng Lv Yuming Guo State Key Laboratory of Animal Nutrition and Feeding College of Animal Science and TechnologyChina Agricultural UniversityBeijing 100193China National Engineering Laboratory for Animal Breeding College of Animal Science and TechnologyChina Agricultural UniversityBeijing 100193China

Background Baicalin and probiotic cocktails are promising feed additives with broad application prospects.While probiotic cocktails are known to enhance intestinal health,the potential synergistic impact of combining baicalin with probiotic cocktails on the gut health of broiler chickens remains largely unexplored.Therefore,this study aims to investigate the influence of the combined administration of baicalin and probiotic cocktails on the composition of ileal and cecal microbiota in broiler chickens to elucidate the underlying mechanisms responsible for the healthpromoting effects.Results A total of 3201-day-old male Arbor Acres broilers were divided into 4 groups,each with 8 replicates of 10 chicks per replicate.Over a period of 42 d,the birds were fed a basal diet or the same diet supplemented with 37.5 g/t baicalin(BC),1,000 g/t probiotic cocktails(PC),or a combination of both BC(37.5 g/t)and PC(1,000 g/t).The results demonstrated that BC+PC exhibited positive synergistic effects,enhancing intestinal morphology,immune function,and barrier function.This was evidenced by increased VH/CD ratio,sIgA levels,and upregulated expression of occludin and claudin-1(P<0.05).16S rRNA analysis indicated that PC potentiated the effects of BC,particularly in the ileum,where BC+PC significantly increased theα-diversity of the ileal microbiota,altered itsβ-diversity,and increased the relative abundance of Flavonifractor(P<0.05),a flavonoid-metabolizing bacterium.Furthermore,Flavonifractor positively correlated with chicken ileum crypt depth(P<0.05).While BC+PC had a limited effect on cecal microbiota structure,the PC group had a very similar microbial composition to BC+PC,suggesting that the effect of PC at the distal end of the gut overshadowed those of BC.Conclusions We demonstrated the synergistic enhancement of gut health regulation in broiler chickens by combining baicalin and probiotic cocktails.Probiotic cocktails enhanced the effects of baicalin and accelerated its metabolism in the ileum,thereby influencing the ileal

关键词： Baicalin Gut health Ileal microbiota Probiotic cocktails Synergistic effects

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Winter Wheat Yield Estimation Based on Sparrow Search Algorithm Combined with Random Forest:A Case Study in Henan Province,China

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Chinese Geographical science 2024年第2期34卷 342-356页

作者： SHI Xiaoliang CHEN Jiajun DING Hao YANG Yuanqi ZHANG Yan college of Geomatics Xi’an University of Science and TechnologyXi’an 710054China

Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790

关键词： winter wheat yield estimation sparrow search algorithm combined with random forest(SSA-RF) machine learning multi-source indicator optimal lead time Henan Province,China

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Independent and Combined Associations of Sleep Duration, Bedtime, and Polygenic Risk Score with the Risk of Hearing Loss among Middle-Aged and Old Chinese: The Dongfeng–Tongji Cohort Study

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Research 2024年第1期2023卷 721-733页

作者： Miao Liu Haiqing Zhang Zhichao Wang Tingting Mo Xuefeng Lai Yaling He Minghui Jiang Meian He Weijia Kong Tangchun Wu Xiaomin Zhang Department of Occupational and Environmental Health Ministry of Education Key Laboratory of Environment and Healthand State Key Laboratory of Environmental Health(Incubating)School of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubeiChina Department of Otorhinolaryngology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubeiChina Department of Epidemiology and Biostatistics School of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubeiChina

Evidence available on the independent and combined associations of sleep duration,bedtime,and genetic predisposition with hearing loss was lacking.The present study included 15,827 participants from the Dongfeng–Tongji cohort study.Genetic risk was characterized by polygenic risk score(PRS)based on 37 genetic loci related to hearing loss.We conducted multivariate logistic regression models to assess the odds ratio(OR)for hearing loss with sleep duration and bedtime,as well as the joint association and interaction with PRS.Results showed that hearing loss was independently associated with sleeping≥9 h/night compared to the recommended 7 to9:00 p.***.to 10:00 p.***.compared to those with bedtime>10:00 p.***.to 11:00 p.m.,with estimated ORs of 1.25,1.27,and 1.16,respectively.

关键词： Middle hearing fen

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Fully spin-polarized, valley-polarized and spin-valley-polarized electron beam splitters utilizing zero-line modes in a three-terminal device

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Chinese Physics B 2024年第6期33卷 596-603页

作者：吕小龙杨加恩谢航 college of science Guangxi University of Science and TechnologyLiuzhou 545006China college of Physics Chongqing UniversityChongqing 401331China Chongqing Key Laboratory for Strongly-Coupled Physics Chongqing UniversityChongqing 401331China

Topological zero-line modes(ZLMs) with spin and valley degrees of freedom give rise to spin, valley and spinvalley transport, which support a platform for exploring quantum transport physics and potential applications in spintronic/valleytronic devices. In this work, we investigate the beam-splitting behaviors of the charge current due to the ZLMs in a three-terminal system. We show that with certain combinations of ZLMs, the incident charge current along the interface between different topological phases can be divided into different polarized currents with unit transmittance in two outgoing terminals. As a result, fully spin-polarized, valley-polarized and spin-valley-polarized electron beam splitters are generated. The mechanism of these splitters is attributed to the cooperative effects of the distribution of the ZLMs and the intervalley and intravalley scatterings that are modulated by the wave-vector mismatch and group velocity mismatch. Interestingly, half-quantized transmittance of these scatterings is found in a fully spin-valley-polarized electron beam splitter.Furthermore, the results indicate that these splitters can be applicable to graphene, silicene, germanene and stanene due to their robustness against the spin–orbit coupling. Our findings offer a new way to understand the transport mechanism and investigate the promising applications of ZLMs.

关键词： topological zero-line modes spin polarization valley polarization quantum transport

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Expression Complementary Disentanglement Network for Facial Expression Recognition

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Chinese Journal of Electronics 2024年第3期33卷 742-752页

作者： Shanmin WANG Hui SHUAI Lei ZHU Qingshan LIU college of Computer science and Technology Nanjing University of Aeronautics and Astronautics college of Computer and Software Nanjing University of Information Science and Technology School of Information and Control Nanjing University of Information Science and Technology

Disentangling facial expressions from other disturbing facial attributes in face images is an essential topic for facial expression recognition.Previous methods only care about facial expression disentanglement(FED)itself,ignoring the negative effects of other facial attributes.Due to the annotations on limited facial attributes,it is difficult for existing FED solutions to disentangle all disturbance from the input face.To solve this issue,we propose an expression complementary disentanglement network(ECDNet).ECDNet proposes to finish the FED task during a face reconstruction process,so as to address all facial attributes during disentanglement.Different from traditional reconstruction models,ECDNet reconstructs face images by progressively generating and combining facial appearance and matching geometry.It designs the expression incentive(EIE) and expression inhibition(EIN) mechanisms,inducing the model to characterize the disentangled expression and complementary parts precisely.Facial geometry and appearance,generated in the reconstructed process,are dealt with to represent facial expressions and complementary parts,respectively.The combination of distinctive reconstruction model,EIE,and EIN mechanisms ensures the completeness and exactness of the FED task.Experimental results on RAF-DB,AffectNet,and CAER-S datasets have proven the effectiveness and superiority of ECDNet.

关键词： Geometry Image recognition Annotations Face recognition Task analysis Image reconstruction Facial features

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WebFLex:A Framework for Web Browsers-Based Peer-to-Peer Federated Learning Systems Using WebRTC

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Computers, Materials & Continua 2024年第3期78卷 4177-4204页

作者： Mai Alzamel Hamza Ali Rizvi Najwa Altwaijry Isra Al-Turaiki Department of Computer science College of Computer and Information SciencesKing Saud UniversityRiyadhKingdom of Saudi Arabia Department of Computer science and Engineering Punjab Engineering CollegeChandigarhIndia

Scalability and information personal privacy are vital for training and deploying large-scale deep learning models.Federated learning trains models on exclusive information by aggregating weights from various devices and taking advantage of the device-agnostic environment of web browsers.Nevertheless,relying on a main central server for internet browser-based federated systems can prohibit scalability and interfere with the training process as a result of growing client numbers.Additionally,information relating to the training dataset can possibly be extracted from the distributed weights,potentially reducing the privacy of the local data used for training.In this research paper,we aim to investigate the challenges of scalability and data privacy to increase the efficiency of distributed training models.As a result,we propose a web-federated learning exchange(WebFLex)framework,which intends to improve the decentralization of the federated learning process.WebFLex is additionally developed to secure distributed and scalable federated learning systems that operate in web browsers across heterogeneous devices.Furthermore,WebFLex utilizes peer-to-peer interactions and secure weight exchanges utilizing browser-to-browser web real-time communication(WebRTC),efficiently preventing the need for a main central server.WebFLex has actually been measured in various setups using the MNIST dataset.Experimental results show WebFLex’s ability to improve the scalability of federated learning systems,allowing a smooth increase in the number of participating devices without central data aggregation.In addition,WebFLex can maintain a durable federated learning procedure even when faced with device disconnections and network variability.Additionally,it improves data privacy by utilizing artificial noise,which accomplishes an appropriate balance between accuracy and privacy preservation.

关键词： Federated learning web browser privacy deep learning

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