Modeling the complex nonlinear dynamics of Brushless DC motors has been a prominent research focus over the past two decades, driven by their superior advantages and widespread industrial applications. Despite extensive efforts, achieving high-effici...
Journal of chemical information and modeling
Nov 20, 2025
Recommending optimal reaction conditions remains a core challenge in AI-driven chemistry due to the limited representation of condition features and the sparsity of labeled data. We propose a collaborative filtering framework that encodes reaction co...
Journal of chemical information and modeling
Nov 20, 2025
Drug-induced osteotoxicity refers to the detrimental effects of certain drugs on bone metabolism, density, and structure, posing serious safety concerns in clinical practice, drug development, and environmental health. Although previous studies have ...
Inferring gene regulatory networks (GRNs) is essential for understanding biological regulation. Although numerous deep learning approaches have been developed for GRN inference, most require large amounts of labeled data. We present Meta-TGLink, a st...
Endometrial cancer (EC) is the most common gynecologic malignancy, with a steadily increasing incidence worldwide. Abnormal vaginal bleeding, a hallmark symptom, enables early diagnosis, which is critical for improving clinical outcomes. Pelvic magne...
Macroalgae play a key role in the structure of benthic communities and provide essential ecological services; their responsiveness to stress positions them as indicators of ecosystem health. Traditional manual monitoring methods are resource-demandin...
Reservoir computers (RCs) are a class of recurrent neural networks that incorporate brain-inspired principles and provide an efficient alternative to deep learning. With fixed random internal connections and trained output weights, they simplify lear...
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...
Partial discharge (PD) detection in power transformers is critical for preventing insulation failures in modern power grids, yet remains challenging due to signal complexity and environmental noise. Existing methods struggle with accurate PD classifi...
International journal of neural systems
Nov 19, 2025
This research looks at the use of long-short-term memory (LSTM) networks to predict psychosis, in patients within the schizophrenia spectrum, based on Heart Rate Variability (HRV) data acquired from wearable devices. Our primary objective is to test ...
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