In the context of global economic austerity in the post epidemic era, housing, as one of the basic human needs, has become particularly important for accurate prediction of house prices. BP neural network is widely used in prediction tasks, but their...
Journal of chemical information and modeling
Sep 16, 2025
Designing novel high-performance donor and acceptor molecules is essential for improving the power conversion efficiency (PCE) of organic solar cells (OSCs). However, conventional experimental methods for developing new materials are often time-consu...
Journal of chemical information and modeling
Sep 16, 2025
Combination therapy presents a transformative approach to treating complex diseases such as cancer by mitigating toxicity and resistance challenges inherent to monotherapy. A critical gap in current computational methods, however, lies in their inabi...
The detection of sweat metabolites is crucial for health monitoring, disease screening, and personalized medicine. Traditional methods encounter challenges like low metabolite concentrations, complex biological matrices, and difficulty in achieving m...
The absolute positioning accuracy of industrial robots is much lower than that of repetitive. In this paper, an error compensation algorithm for industrial robots is proposed, which included the kinematic parameter calibration based on the enhanced D...
Analyzing the electroencephalography (EEG) signals of epilepsy patients can monitor the condition, detect and intervene in epileptic seizures in time. To enhance the lives of these patients, it is necessary to develop accurate methods to detect epile...
Journal of chemical information and modeling
Sep 15, 2025
Today, machine learning models are employed extensively to predict the physicochemical and biological properties of molecules. Their performance is typically evaluated on in-distribution (ID) data, i.e., data originating from the same distribution as...
Journal of chemical information and modeling
Sep 15, 2025
This study introduces MolAI, a robust deep learning model designed for data-driven molecular descriptor generation. Utilizing a vast training data set of 221 million unique compounds, MolAI employs an autoencoder neural machine translation model to g...
Real-time monitoring of phytoplankton in freshwater systems is critical for early detection of harmful algal blooms (HABs) to enable efficient response by water management agencies. This manuscript presents an image processing pipeline developed to a...
Halonitromethanes (HNMs) were high-toxicity nitrogenous disinfection byproducts generated by amino acids (AAs) during UV/monochloramine (UV/NHCl) disinfection in bromide-containing water. HNM concentrations fell over time, highlighting disinfection t...
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