The porous structure in pomelo peel is believed to be responsible for the protection of its fruit from damage during the free falling from a *** quantitative understanding of the relationship between the deformation b...
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The porous structure in pomelo peel is believed to be responsible for the protection of its fruit from damage during the free falling from a *** quantitative understanding of the relationship between the deformation behavior and the porous structure could pave the way for the design of porous structures for efficient energy ***,a universal feature of pore distribution in pomelo peels along the radial direction is extracted from three varieties of pomelos,which shows strong correlation to the deformation behavior of the peels under *** by the porous design found in pomelo peels,porous polyether-ether-ketone(PEEK)cube is additively manufactured and possesses the highest ability to absorb energy during compression as compared to the non-pomelo-inspired geometries,which is further confirmed by the finite element *** nature-optimized porous structure revealed here could guide the design of lightweight and high-energy-dissipating materials/devices.
The single-photon absorption induced single event transient in the silicon-germanium heterojunction bipolar transistor is *** laser wavelength and bias condition have been proven to have significant impacts on the cha...
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The single-photon absorption induced single event transient in the silicon-germanium heterojunction bipolar transistor is *** laser wavelength and bias condition have been proven to have significant impacts on the characterization of the single event transient(SET) response of the device by two-dimensional(2-D) raster *** optical analytical calculation,the laser-induced charge distribution is well-embedded in the 3-D TCAD process simulation conducted to explore the underlying physical *** addition to the ion shunt effect,the excess electron injection from the emitter to the base could play a vital role in the SET peak amplitude and charge *** impact of the metal layer on the SPA experimental results is also determined by establishing a figure of merit that will help researchers estimate the laser-induced transient sensitivity of devices with metal layer blocking.
The methane combustion with hydrogen addition can effectively reduce carbon emissions in the iron and steel making industry,while the combustion mechanism is still poorly *** oxy-fuel combustion of methane with hydrog...
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The methane combustion with hydrogen addition can effectively reduce carbon emissions in the iron and steel making industry,while the combustion mechanism is still poorly *** oxy-fuel combustion of methane with hydrogen addition in a 0.8 MW oxy-natural gas combustion experimental furnace was numerically studied to investigate six different combustion *** results show that the 28-step chemical reaction mechanism is the optimal recommendation for the simulation balancing the numerical accuracy and computational *** the hydrogen enrichment increases in fuel,the highest flame temperature ***,the chemical reaction accelerates with enlarging the peak of the highest flame temperature and intermediate OH *** the hydrogen enrichment reaches 75 vol.%,the flame front is the farthest,and the flame high-temperature zone occupies the largest proportion corresponding to the most vigorous chemical reactions in the same oxygen supply.
Recently, Pareto Set Learning (PSL) has been proposed for learning the entire Pareto set using a neural network. PSL employs preference vectors to scalarize multiple objectives, facilitating the learning of mappings f...
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Drug-Drug Interaction (DDI) task plays a crucial role in clinical treatment and drug development. Recently, deep learning methods have been successfully applied for DDI prediction. However, training deep learning mode...
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ISBN:
(数字)9798350386226
ISBN:
(纸本)9798350386233
Drug-Drug Interaction (DDI) task plays a crucial role in clinical treatment and drug development. Recently, deep learning methods have been successfully applied for DDI prediction. However, training deep learning models always need large amount of data, while known DDIs are scarce. To address this challenge, a graph neural network-based DDI prediction model named PNESR-DDI is proposed, which compensates for the lack of DDIs by enriching drug representations. First, to obtain initial node representations that incorporate rich semantic information from the biomedical knowledge graph (KG), a link prediction pre-training method on external KG is proposed in the node embedding pre-training module. Then, considering the large scale of the KG, subgraph extraction for the target drug pairs is introduced to reduce noise and decrease computational complexity in the subgraph anchoring module. After that, the subgraph is updated, and node similarities are propagated in the subgraph reconstruction module. Based on the node similarity scores, the subgraph is pruned and reconstructed, which adjusts node representations to be more conducive to DDI prediction. Finally, the drug embeddings, subgraph representations, and drug fingerprint features are concatenated to predict DDIs. PNESRDDI is evaluated on two benchmark DDI datasets: DrugBank and TWOSIDES. Experiment results show that PNESR-DDI achieves better performance than baselines. Ablation results validate the effectiveness of the pre-training method and the adaptive subgraph reconstruction strategy.
As the mean-time-between-failures(MTBF)continues to decline with the increasing number of components on large-scale high performance computing(HPC)systems,program failures might occur during the execution period with ...
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As the mean-time-between-failures(MTBF)continues to decline with the increasing number of components on large-scale high performance computing(HPC)systems,program failures might occur during the execution period with high *** successful execution of the HPC programs has become an issue that the unprivileged users should be *** the user perspective,if the program failure cannot be detected and handled in time,it would waste resources and delay the progress of program ***,the unprivileged users are unable to perform program state checking due to execution control by the job management system as well as the limited ***,automated tools for supporting user-level failure detection and autorecovery of parallel programs in HPC systems are *** paper proposes an innovative method for the unprivileged user to achieve failure detection of job execution and automatic resubmission of failed *** state checker in our method is encapsulated as an independent job to reduce interference with the user *** addition,we propose a dual-checker mechanism to improve the robustness of our *** implement the proposed method as a tool named automatic re-launcher(ARL)and evaluate it on the Tianhe-2 *** results show that ARL can detect the execution failures effectively on Tianhe-2 *** addition,the communication and performance overhead caused by ARL is *** good scalability of ARL makes it applicable for large-scale HPC systems.
With the promotion of advanced communication technology, autonomous vehicle platoons (AVPs) develop rapidly due to their advantages in enhancing traffic efficiency, road safety and reducing fuel consumption. However, ...
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作者:
Li, YuanLu, XiaofenYao, XinSouthern University of Science and Technology
The Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China
School of Computer Science University of Birmingham Edgbaston BirminghamB15 2TT United Kingdom
Evolutionary algorithms (EAs) combined with constraint handling techniques (CHTs) are very effective in solving constrained optimization problems (COPs). Recently, negatively correlated search (NCS) has been shown to ...
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In this paper, we study two residual-based a posteriori error estimators for the C0 interior penalty method in solving the biharmonic equation in a polygonal domain under a concentrated load. The first estimator is de...
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Multifaceted user modeling aims to uncover fine-grained patterns and learn representations from user data, revealing their diverse interests and characteristics, such as profile, preference, and personality. Recent st...
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