Multi-Task Aquatic Toxicity Prediction Model Based on Multi-Level Features Fusion

Chemistry, Computational Chemistry, Environmental Chemistry, Engineering, Environmental Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Environmental and Public Health,
aquatic toxicity   deep learning   multi-task model   molecular fingerprints   molecular graph features  

Academic Background With the growing threat of organic compounds to environmental pollution, studying the toxic responses of different aquatic organisms to these compounds has become crucial. Such research not only helps assess the potential ecological impacts of pollutants on the overall aquatic ecosystem but also provides significant scientific f...

Flexible No-Drift Data Glove Using Ultrathin Silicon for the Metaverse

Chemistry, Nanoscience, Materials Science, Metallic Materials, Information Science, Semiconductors and Information Devices,
no-drift sensor   ultrathin silicon   data glove   human-machine interface   metaverse  

Academic Background With the rapid development of the Metaverse, human-machine interface (HMI) technology has become a key link between virtual space and human users. Among these, gesture recognition technology is particularly important in the Metaverse, especially the precise capture of finger movements. Traditional bending sensors used for gestur...

Deep-Learning-Enhanced Metal-Organic Framework E-Skin for Health Monitoring

Chemistry, Nanoscience, Materials Science, Information Science, Semiconductors and Information Devices, Artificial Intelligence, Life Sciences, Bioengineering,
E-skin   Metal-organic framework   Deep learning   Health monitoring   Motion detection   Biomolecular sensing   Artificial intelligence  

Deep Learning-Enhanced Metal-Organic Framework E-Skin for Health Monitoring Academic Background Electronic skin (e-skin) is a technology capable of sensing physiological and environmental stimuli, mimicking human skin functions. In recent years, the potential applications of e-skin in fields such as robotics, sports science, and healthcare monitori...

Investment Micro-Casting 3D-Printed Multi-Metamaterial for Programmable Multimodal Biomimetic Electronics

Chemistry, Nanoscience, Engineering, Electrical Engineering, Materials Science, Information Science, Electronic Information, Medicine, Life Sciences, Bioengineering,
3D printing   multi-metamaterial   biomimetic electronics   programmable   modal sensing  

Research on Multi-material Biomimetic Electronics Based on Investment Micro-casting 3D Printing Academic Background With the rapid development of biomimetic electronics, electronic skin (E-skin) and flexible sensors that mimic human perceptual functions have shown broad application prospects in robotics, medical devices, and human-computer interact...

An Inkjet-Printable Organic Electrochemical Transistor Array with Differentiated Ion Dynamics for Sweat Fingerprint Identification

An Inkjet-Printable Organic Electrochemical Transistor Array with Differentiated Ion Dynamics for Sweat Fingerprint Identification

Engineering, Electrical Engineering, Materials Science, Organic Polymeric Materials, Information Science, Artificial Intelligence, Medicine,
inkjet printing   organic electrochemical transistor   ion dynamics   sweat identification   artificial intelligence   health monitoring  

Sweat Fingerprint Identification Technology Based on Ion Dynamics: Research on Inkjet-Printed Organic Electrochemical Transistor Arrays Academic Background Sweat, as a non-invasive biomarker, contains rich physiological information that can reflect human health conditions, such as hydration balance and disease markers. However, sweat has complex co...

Resistive Memory-Based Zero-Shot Liquid State Machine for Multimodal Event Data Learning

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
resistive memory   zero-shot learning   liquid state machine   multimodal data   neuromorphic hardware   event-driven learning   brain-inspired computing  

Novel Resistive Memory-Driven Zero-Shot Multimodal Event Learning System: A Report on Hardware-Software Co-Design Academic Background The human brain is a complex spiking neural network (SNN) capable of zero-shot learning in multimodal signals with minimal power consumption, allowing generalization of existing knowledge to address new tasks. Howeve...

Efficient Scaling of Large Language Models with Mixture of Experts and 3D Analog In-Memory Computing

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
large language models   mixture of experts   3D in-memory computing   energy efficiency   hardware acceleration  

Efficient Scaling of Large Language Models with Mixture of Experts and 3D Analog In-Memory Computing Academic Background In recent years, large language models (LLMs) have demonstrated remarkable capabilities in natural language processing, text generation, and other fields. However, as the scale of these models continues to grow, the costs of trai...

Decoupled Peak Property Learning for Efficient and Interpretable Electronic Circular Dichroism Spectrum Prediction

Chemistry, Computational Chemistry, Information Science, Artificial Intelligence,
Electronic Circular Dichroism   Peak Property Learning   Deep Neural Network   Molecular Chirality   Spectrum Prediction  

Efficient and Interpretable Electronic Circular Dichroism Spectrum Prediction: Decoupled Peak Property Learning Academic Background Electronic Circular Dichroism (ECD) spectroscopy is a crucial tool for studying molecular chirality, particularly in asymmetric organic synthesis and the pharmaceutical industry, where it is used to distinguish the abs...

Multimodal Learning for Mapping Genotype–Phenotype Dynamics

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Cell Biology, Biochemistry, Bioengineering, Genetics,
multimodal learning   genotype-phenotype relationship   single-cell RNA sequencing   machine learning   cellular heterogeneity  

Multimodal Learning Reveals Genotype–Phenotype Dynamics Background The complex relationship between genotype and phenotype has long been a central question in biology. Genotype refers to the genetic information of an organism, while phenotype is the manifestation of this genetic information in a specific environment. Although Wilhelm Johannsen intr...

Leveraging Pharmacovigilance Data to Predict Population-Scale Toxicity Profiles of Checkpoint Inhibitor Immunotherapy

Information Science, Computer Science, Medicine, Oncology, Life Sciences, Immunology,
Pharmacovigilance   Checkpoint Inhibitors   Toxicity Prediction   Deep Learning   Cancer Immunotherapy   Population Analysis   Dynamic Graph Convolutional Network  

Predicting and Monitoring the Toxicity of Immune Checkpoint Inhibitors: Breakthrough Application of the DysPred Deep Learning Framework Academic Background Immune checkpoint inhibitors (ICIs) represent a major breakthrough in cancer immunotherapy in recent years, enhancing the body’s antitumor immune response by inhibiting immune checkpoint signali...