Classification of plastic materials based on spectroscopic data is a very crucial task in a variety of applications, including automated recycling, environmental monitoring, quality control in manufacturing, quality control of products, and analysis ...
The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challenging due to ...
Surface defect detection of organic jujubes is critical for quality assessment. However, conventional machine vision lacks adaptability to polymorphic defects, while deep learning methods face a trade-off-deep architectures are computationally intens...
The complexity of stock price fluctuations stems from its multi-scale characteristics, nonlinear dynamic characteristics, and fractal structure. To better capture the fractal characteristics of stock prices, this paper creatively proposes a predictio...
Epilepsy affects around 50 million people globally, causing significant burdens. While many methods predict seizures, current models struggle with handling spatiotemporal features and balancing accuracy with computational efficiency.This paper introd...
This paper addresses the challenges of dynamic environments and multimodal data fusion in multimodal transport path optimization for smart ports by proposing a GL-SSL Model that integrates Graph Neural Networks (GCN), Long Short-Term Memory (LSTM), a...
Journal of chemical information and modeling
Dec 1, 2025
Reliable prediction of compound potency and the ADME profile is crucial in drug discovery. With the recent surge of AI and deep learning frameworks, it remains unclear whether these modern techniques offer statistically significant improvement over t...
Journal of agricultural and food chemistry
Dec 1, 2025
Isoxazoline pesticides, such as fluxametamide, while effective against parasites and pests, pose a severe environmental threat due to their high toxicity to honeybees - critical pollinators essential for ecosystem health and food security. Existing p...
In this study, we developed an image-recognition-based deep-learning method for accurately predicting the DSSP (define secondary structures of proteins) parameters from a circular dichroism (CD) spectrum. Focusing on the inherently high image-recogni...
BACKGROUND: Protein function research helps in understanding the complex biological processes that occur within cells. However, the intricate nature of protein structures and functions, along with the rapid growth of protein sequence data, presents a...
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