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http://dx.doi.org/10.1007/s00429-019-02020-6 | DOI Listing |
Sensors (Basel)
November 2024
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
The underwater imaging process is often hindered by high noise levels, blurring, and color distortion due to light scattering, absorption, and suspended particles in the water. To address the challenges of image enhancement in complex underwater environments, this paper proposes an underwater image color correction and detail enhancement model based on an improved Cycle-consistent Generative Adversarial Network (CycleGAN), named LPIPS-MAFA CycleGAN (LM-CycleGAN). The model integrates a Multi-scale Adaptive Fusion Attention (MAFA) mechanism into the generator architecture to enhance its ability to perceive image details.
View Article and Find Full Text PDFWater Res X
December 2024
School of Environment, Tsinghua University, Beijing 100084, China.
Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand compared to overall water usage, accurately predicting STWDF poses significant challenges. This study introduces an innovative network architecture-the multi-scale correction module neural network, built upon Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) enhanced with Attention mechanisms-for simultaneous STWDF with a temporal resolution of one hour over a week for 10 DMAs located in a single city in northern Italy.
View Article and Find Full Text PDFNeural Netw
February 2025
Department of Data Science and Artificial Intelligence, Hong Kong Polytechnic University, Hong Kong. Electronic address:
Intelligent Transportation Systems (ITS) are essential for modern urban development, with urban flow prediction being a key component. Accurate flow prediction optimizes routes and resource allocation, benefiting residents, businesses, and the environment. However, few methods address the spatial-temporal heterogeneity of urban flows.
View Article and Find Full Text PDFPhys Rev Lett
November 2024
School of Physics, Peking University, Beijing 100871, China.
We propose to measure the energy correlator in quarkonium production, which tracks the energy deposited in the calorimeter at the χ-angular distance away from the identified quarkonium. The observable eliminates the need for jets while sustaining the perturbative predictive power. Analyzing the power correction to the energy correlator, we demonstrate that the novel observable supplies a unique gateway to probing the hadronization, especially when cosχ≳0 in the quarkonium rest frame, where the perturbative emissions are depleted due to the dead-cone effects.
View Article and Find Full Text PDFPLoS Comput Biol
November 2024
Frankfurt Institute for Advanced Studies (FIAS), Frankfurt am Main, Germany.
Understanding how multicellular organisms reliably orchestrate cell-fate decisions is a central challenge in developmental biology, particularly in early mammalian development, where tissue-level differentiation arises from seemingly cell-autonomous mechanisms. In this study, we present a multi-scale, spatial-stochastic simulation framework for mouse embryogenesis, focusing on inner cell mass (ICM) differentiation into epiblast (EPI) and primitive endoderm (PRE) at the blastocyst stage. Our framework models key regulatory and tissue-scale interactions in a biophysically realistic fashion, capturing the inherent stochasticity of intracellular gene expression and intercellular signaling, while efficiently simulating these processes by advancing event-driven simulation techniques.
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