The endolymphatic duct (ED) and the endolymphatic sac (ES) are the nonsensory components
of the endolymph-filled, closed, membranous labyrinth. The ED leads from the utricular …

This paper presents a new Network Intrusion Detection System (NIDS) based on Graph
Neural Networks (GNNs). GNNs are a relatively new sub-field of deep neural networks, which …

We conducted integrative somatic–germline analyses by deeply sequencing 864 cancer-associated
genes, complete genomes and transcriptomes for 300 mostly previously treated …

The cochlear implant is an electronic auditory prosthesis with a component that is surgically
inserted in the ear and coupled with a detachable component that is worn externally like a …

This paper investigates graph neural networks (GNNs) applied for self-supervised intrusion
and anomaly detection in computer networks. GNNs are a deep learning approach for graph-…

PURPOSE: To determine the computed tomographic (CT), magnetic resonance (MR)
imaging, and angiographic findings of papillary endolymphatic sac tumors. MATERIALS AND …

Background and Purpose Increasing evidence suggests systemic inflammation‐caused
skeletal muscle atrophy as a major clinical feature of cachexia. Triptolide obtained from …

The continuous strengthening of the security posture of Internet of Things (IoT) ecosystems
is vital due to the increasing number of interconnected devices and the volume of sensitive …

In this work, we applied a deep Convolutional Neural Network (CNN) with Xception model to
perform malware image classification. The Xception model is a recently developed special …

In this paper, we propose XG-BoT, an explainable deep graph neural network model for
botnet node detection. The proposed model comprises a botnet detector and an explainer for …