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Refreshable memristor via dynamic allocation of ferro-ionic phase for neural reuse.
Nat Commun
January 2025
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Neural reuse can drive organisms to generalize knowledge across various tasks during learning. However, existing devices mostly focus on architectures rather than network functions, lacking the mimic capabilities of neural reuse. Here, we demonstrate a rational device designed based on ferroionic CuInPS, to accomplish the neural reuse function, enabled by dynamic allocation of the ferro-ionic phase.
View Article and Find Full Text PDFHistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration.
Comput Methods Programs Biomed
January 2025
Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano, Universitat Politècnica de València, Valencia, Spain; valgrAI: Valencian Graduate School and Research Network of Artificial Intelligence, Valencia, Spain.
Digital pathology is now a standard component of the pathology workflow, offering numerous benefits such as high-detail whole slide images and the capability for immediate case sharing between hospitals. Recent advances in deep learning-based methods for image analysis make them a potential aid in digital pathology. However, A significant challenge in developing computer-aided diagnostic systems for pathology is the lack of intuitive, open-source web applications for data annotation.
View Article and Find Full Text PDFA novel multi-user collaborative cognitive radio spectrum sensing model: Based on a CNN-LSTM model.
PLoS One
January 2025
School of Electronic Information Engineering, Inner Mongolia University, Hohhot, Inner Mongolia, China.
Cognitive Radio (CR) technology enables wireless devices to learn about their surrounding spectrum environment through sensing capabilities, thereby facilitating efficient spectrum utilization without interfering with the normal operation of licensed users. This study aims to enhance spectrum sensing in multi-user cooperative cognitive radio systems by leveraging a hybrid model that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. A novel multi-user cooperative spectrum sensing model is developed, utilizing CNN's local feature extraction capability and LSTM's advantage in handling sequential data to optimize sensing accuracy and efficiency.
View Article and Find Full Text PDFMVCL-DTI: Predicting Drug-Target Interactions Using a Multiview Contrastive Learning Model on a Heterogeneous Graph.
J Chem Inf Model
January 2025
School of Computer Science and Technology, Soochow University, Jiangsu 215006, China.
Accurate prediction of drug-target interactions (DTIs) is pivotal for accelerating the processes of drug discovery and drug repurposing. MVCL-DTI, a novel model leveraging heterogeneous graphs for predicting DTIs, tackles the challenge of synthesizing information from varied biological subnetworks. It integrates neighbor view, meta-path view, and diffusion view to capture semantic features and employs an attention-based contrastive learning approach, along with a multiview attention-weighted fusion module, to effectively integrate and adaptively weight the information from the different views.
View Article and Find Full Text PDFDipole-induced transitions from Schottky to Ohmic contact at Janus MoSiGeN/metal interfaces.
Nanoscale Horiz
January 2025
SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.
Janus MoSiGeN monolayers exhibit exceptional mechanical stability and high electron mobility, which make them a promising channel candidate for field-effect transistors (FETs). However, the high Schottky barrier at the contact interface would limit the carrier injection efficiency and degrade device performance. Herein, using density functional theory calculations and machine learning methods, we investigated the interfacial properties of the Janus MoSiGeN monolayer and metal electrode contacts.
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