Graph convolutional networks (GCNs) gain increasing attention on graph data learning tasks in recent years. However, in many applications, graph may come with an incomplete form where attributes of graph nodes are par...
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In the development of linear quadratic regulator(LQR) algorithms, the Riccati equation approach offers two important characteristics——it is recursive and readily meets the existence condition. However, these attribu...
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In the development of linear quadratic regulator(LQR) algorithms, the Riccati equation approach offers two important characteristics——it is recursive and readily meets the existence condition. However, these attributes are applicable only to transformed singular systems, and the efficiency of the regulator may be undermined if constraints are violated in nonsingular versions. To address this gap, we introduce a direct approach to the LQR problem for linear singular systems, avoiding the need for any transformations and eliminating the need for regularity assumptions. To achieve this goal, we begin by formulating a quadratic cost function to derive the LQR algorithm through a penalized and weighted regression framework and then connect it to a constrained minimization problem using the Bellman's criterion. Then, we employ a dynamic programming strategy in a backward approach within a finite horizon to develop an LQR algorithm for the original system. To accomplish this, we address the stability and convergence analysis under the reachability and observability assumptions of a hypothetical system constructed by the pencil of augmented matrices and connected using the Hamiltonian diagonalization technique.
Autonomous aerial vehicle (AAV)-assisted mobile edge computing (MEC) and data collection (DC) have been popular research issues. Different from existing works that consider MEC and DC scenarios separately, this articl...
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As an emerging privacy-preservation machine learning framework,Federated Learning(FL)facilitates different clients to train a shared model collaboratively through exchanging and aggregating model parameters while raw ...
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As an emerging privacy-preservation machine learning framework,Federated Learning(FL)facilitates different clients to train a shared model collaboratively through exchanging and aggregating model parameters while raw data are kept local and *** this learning framework is applied to Deep Reinforcement Learning(DRL),the resultant Federated Reinforcement Learning(FRL)can circumvent the heavy data sampling required in conventional DRL and benefit from diversified training data,besides privacy preservation offered by *** FRL implementations presuppose that clients have compatible tasks which a single global model can *** practice,however,clients usually have incompatible(different but still similar)personalized tasks,which we called task *** may severely hinder the implementation of FRL for practical *** this paper,we propose a Federated Meta Reinforcement Learning(FMRL)framework by integrating Model-Agnostic Meta-Learning(MAML)and ***,we innovatively utilize Proximal Policy Optimization(PPO)to fulfil multi-step local training with a single round of ***,considering the sensitivity of learning rate selection in FRL,we reconstruct the aggregation optimizer with the Federated version of Adam(Fed-Adam)on the server *** experiments demonstrate that,in different environments,FMRL outperforms other FL methods with high training efficiency brought by Fed-Adam.
Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product *** efforts of digital twinning neglect the decisive consumer feedback in...
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Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product *** efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital *** work mines real-world consumer feedbacks through social media topics,which is significant to product *** specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a *** primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset ***,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse *** this end,this work combines deep learning and survival analysis to predict the prevalent time of *** propose a specialized deep survival model which consists of two *** first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network ***,a specific loss function different from regular survival models is proposed to achieve a more reasonable *** experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.
The first-principles calculations are performed to examine structural,mechanical,and electronic properties at large strain for a monolayer C_(4)N_(4),which has been predicted as an anchoring promising material to atte...
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The first-principles calculations are performed to examine structural,mechanical,and electronic properties at large strain for a monolayer C_(4)N_(4),which has been predicted as an anchoring promising material to attenuate shuttle effect in Li–S batteries stemming from its large absorption energy and low diffusion energy *** results show that the ideal strengths of C_(4)N_(4)under tension and pure shear deformation conditions reach 13.9 GPa and 12.5 GPa when the strains are 0.07 and 0.28,*** folded five-membered rings and diverse bonding modes between carbon and nitrogen atoms enhance the ability to resist plastic deformation of C_(4)N_(4).The orderly bond-rearranging behaviors under the weak tensile loading path along the[100]direction cause the impressive semiconductor–metal transition and inverse semiconductor–metal *** present results enrich the knowledge of the structure and electronic properties of C_(4)N_(4)under deformations and shed light on exploring other two-dimensional materials under diverse loading conditions.
Brain tumor classification is crucial for personalized treatment *** deep learning-based Artificial Intelligence(AI)models can automatically analyze tumor images,fine details of small tumor regions may be overlooked d...
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Brain tumor classification is crucial for personalized treatment *** deep learning-based Artificial Intelligence(AI)models can automatically analyze tumor images,fine details of small tumor regions may be overlooked during global feature ***,we propose a brain tumor Magnetic Resonance Imaging(MRI)classification model based on a global-local parallel dual-branch *** global branch employs ResNet50 with a Multi-Head Self-Attention(MHSA)to capture global contextual information from whole brain images,while the local branch utilizes VGG16 to extract fine-grained features from segmented brain tumor *** features from both branches are processed through designed attention-enhanced feature fusion module to filter and integrate important ***,to address sample imbalance in the dataset,we introduce a category attention block to improve the recognition of minority *** results indicate that our method achieved a classification accuracy of 98.04%and a micro-average Area Under the Curve(AUC)of 0.989 in the classification of three types of brain tumors,surpassing several existing pre-trained Convolutional Neural Network(CNN)***,feature interpretability analysis validated the effectiveness of the proposed *** suggests that the method holds significant potential for brain tumor image classification.
Nanocatalytic therapy shows great potential for therapeutic ***,therapeutic efficiency is often limited by unsatisfactory enzyme activity and lack of the coordination of immune ***,engineering nanozymes activity enhan...
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Nanocatalytic therapy shows great potential for therapeutic ***,therapeutic efficiency is often limited by unsatisfactory enzyme activity and lack of the coordination of immune ***,engineering nanozymes activity enhancement while activating immune system will be an effective strategy to achieve efficient tumor ***,we synthesize a DSPE-PEG-FA modified manganese dioxide-based dual-atom nanozyme(MDF),on which iridium and platinum atoms are *** obtained MDF can simultaneously mimic four enzyme activities of catalase,oxidase,peroxidase,and glutathione oxidase,set off a reactive oxygen species(ROS)storm,cause tumor cell *** enzyme activity of MDF can be enhanced by its own photothermal ***,MDF can consume intracellular glutathione and release Mn^(2+),which can prevent generated ROS from consumption and further activate cyclic guanosine monophosphate-adenosine monophosphate synthase-stimulator of interferon genes(cGAS-STING)pathway and promote the secretion of type I interferon,which will help promote dendritic cells maturation,present antigens to T lymphocytes to help kill tumor ***,MDF shows excellent tumor suppressive *** work provides a new paradigm for the field of nanozymes and offers a new reference for involvement of cGAS-STING pathway activation in tumor catalytic therapy.
In recent decades, Ghost Imaging (GI) has emerged as a focal point of research attention among scholars. The imaging quality of GI remains a challenge despite extensive research. In this study, we propose a new model ...
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A self-standing dual-electric field synergistic[TiO2/polyvinylidene fluoride(PVDF)]//[g-C3N4 tube/PVDF]Janus nanofibres(named as[TP]//[CTP]JNs)S-scheme heterostructure piezoelectric photocatalyst is de-signed and cons...
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A self-standing dual-electric field synergistic[TiO2/polyvinylidene fluoride(PVDF)]//[g-C3N4 tube/PVDF]Janus nanofibres(named as[TP]//[CTP]JNs)S-scheme heterostructure piezoelectric photocatalyst is de-signed and constructed via conjugative ***-fields of built-in electric fields supplied by S-scheme heterostructure and piezoelectric field formed by PVDF jointly boost separation and transfer of photo-induced *** a case study,piezoelectric photocatalytic efficiency of[TP]//[CTP]JNs for tetracycline hydrochloride(TCH)under ultrasonic united with simulated sunlight illumination is 93.35％(40 min),which is 1.39 times of the photocatalytic efficiency(light illumination only)and 5.32 times of piezoelectric catalytic efficiency(applying ultrasonic only),proving the advantages of the synergistic ef-fect of piezoelectric catalysis and photocatalysis on contaminant *** dynamic behaviors of photocatalysis and photo-generated charges are deeply revealed through fs-TA and TRPL decay spectra,and the degradation pathways of antibiotics are reasonably speculated by combining LCMS spectra with Fukui *** the degradation ability,COMSOL simulation and DFT calculation,the structural advantage of Janus nanofibers is fully verified,and S-scheme charge transfer mechanism is confirmed by combining a series of sound ample experiments with theoretical ***,the construction mecha-nism of Janus nanofibers is proposed,and corresponding construction technique is established.
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