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

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

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

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...

Floating Electricity Generator for Omnidirectional Droplet Vibration Harvesting

Floating Electricity Generator for Omnidirectional Droplet Vibration Harvesting

Floating Omnidirectional Droplet Vibration Generator: Breakthrough Research Academic Background With the widespread application of Internet of Things (IoT) devices in marine environmental monitoring, how to provide stable power to these devices without relying on the power grid has become an urgent issue. Traditional renewable energy sources such a...

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

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

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

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

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

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...

Deep Bayesian Active Learning Using In-Memory Computing Hardware

With the rapid development of artificial intelligence (AI) technologies, deep learning has made significant progress in complex tasks. However, the success of deep learning largely relies on massive amounts of labeled data, and the data labeling process is not only time-consuming and labor-intensive but also requires specialized domain knowledge, m...