Abstract: Graph Neural Networks (GNNs) have gained popularity as an efficient choice for learning on graph-structured data. However, most methods are node or graph-centered, often overlooking valuable ...
Abstract: The data-driven methods based on the graph convolution architecture provide a promising direction for accelerating power flow (PF) calculation. These methods directly predict operational ...
The influence of IR (insulin resistance) on the response of patients with hypertension to intensive systolic blood pressure treatment in terms of cognitive performance remains unclear, as does which ...
Graphene has always fascinated scientists and engineers due to its massive strength, conductivity and flexibility. Traditionally, the goal has been to produce perfect graphene sheets with flawless ...
From time to time, commentators opine that emerging technology will make some traditional features of war obsolete. These predictions are almost invariably premature. The use of antitank weapons in ...
The code runs under Python 3.9.20 and Pytorch 2.3.1+cu121. Create a PyTorch environment and install required packages, such as "numpy", "pandas", "scikit-learn ...
Brain organoids are valuable models for studying neurological diseases. However, they mature slowly, limiting their utility for conditions that develop over decades. Until now, stimulation methods ...
ABSTRACT: This research investigates the impact of the road network topological structure on facility location modeling. We create four types of road networks, i.e., the radial, the grid, the ring, ...
We recently upgraded our Feign client from version 12.5 to 13.5 and have encountered an issue post-upgrade. Specifically, the method public ResponseInterceptor enrich ...
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