Closed-loop brain-computer interfaces can be used to bridge, modulate, or repair damaged connections within the brain to restore functional deficits. Towards this goal, we demonstrate that small artificial spiking neural networks can be bidirectional...
This study aims to enhance the accuracy of pneumonia diagnosis from x-ray images by developing a model that integrates Vision Transformer (ViT) and Graph Convolutional Networks (GCN) for improved feature extraction and diagnostic performance. The ViT...
A neural network-shaped composite fusing α-MnO and nitrogen-doped graphene (N@Gr/α-MnO) was synthesized a hydrothermal method. The resulting composite demonstrates enhanced electrocatalytic activity for hydrogen peroxide (HO) compared with each sing...
In this paper, we present a predictive model based on artificial neural network (ANN) to evaluate principal physicochemical properties of a set of anti-inflammatory drugs based on chosen topological indices. The molecular descriptors were calculated ...
Environmental geochemistry and health
Jul 20, 2025
Groundwater is a vital source of drinking water in Bangladesh, with tubewells commonly used, particularly in schools. This study assessed the quality of tubewell water in the southwest region, focusing on iron (Fe), arsenic (As), pH, electrical condu...
Current methods for detecting soybean fungal contamination are often destructive, time-consuming, and labor-intensive. This study proposed an efficient approach by fusing visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral i...
Plant peptide-protein interactions (PepPI) play a crucial role in plant growth, development, immune regulation, and environmental adaptation. However, existing computational methods still face several challenges in PepPI prediction. First, most metho...
Cardiovascular illnesses continue to be a predominant cause of mortality globally, underscoring the necessity for prompt and precise diagnosis to mitigate consequences and healthcare expenditures. This work presents a complete hybrid methodology that...
Accurate and efficient analysis of Electroencephalogram (EEG) signals is crucial for applications like neurological diagnosis and Brain-Computer Interfaces (BCI). Traditional methods often fall short in capturing the intricate temporal dynamics inher...
Lymphoma poses a critical health challenge worldwide, demanding computer aided solutions towards diagnosis, treatment, and research to significantly enhance patient outcomes and combat this pervasive disease. Accurate classification of lymphoma subty...
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