Teaching Research Data Management with DataLad: A Multi-Year, Multi-Domain Effort

Multi-Year, Multi-Disciplinary Efforts in Scientific Research Data Management Education Research Background With the development of modern neuroscience, Research Data Management (RDM) has become an indispensable skill for scientists. However, despite the importance of research data management for scientific research, such technical skills are often...

High-speed High-power Free-space Optical Communication via Directly Modulated Watt-class Photonic-crystal Surface-emitting Lasers

High-speed High-power Free-space Optical Communication via Directly Modulated Watt-class Photonic-crystal Surface-emitting Lasers

High-Speed High-Power Free-Space Optical Communication: Direct Modulation of Watt-Level Photonic Crystal Surface-Emitting Lasers Background Introduction As a vital light source for optical communication, semiconductor lasers are widely used due to their small size, low cost, long lifespan, and high efficiency. For example, vertical-cavity surface-e...

Hyperspectral In-Memory Computing with Optical Frequency Combs and Programmable Optical Memories

Hyperspectral In-Memory Computing and Applications of Optical Frequency Comb and Programmable Optical Memory Introduction In recent years, breakthroughs in machine learning have driven revolutionary developments in various industries, including healthcare, finance, retail, automotive, and manufacturing. These transformations have led to a surge in ...

Cell Type Mapping of Inflammatory Muscle Diseases Highlights Selective Myofiber Vulnerability in Inclusion Body Myositis

Characterization of Heterogeneity in Muscle Fiber Types and Selective Susceptibility in Inclusion Body Myositis With advancing age, the incidence of inflammatory myopathies gradually increases, among which inclusion body myositis (IBM) is the most common type, currently lacking effective treatment methods. Unlike other inflammatory myopathies, IBM ...

k-emophone: a mobile and wearable dataset with in-situ emotion, stress, and attention labels

Scientific Data Report | K-emophone: A Mobile and Wearable Dataset with On-site Emotion, Stress, and Attention Labels Background With the proliferation of low-cost mobile and wearable sensors, numerous studies have leveraged these devices to track and analyze human mental health, productivity, and behavioral patterns. However, despite the developme...

Deep-Learning-Based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging

Deep-learning-based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging Research Background and Motivation A brain-computer interface (BCI) is a system that directly decodes and outputs brain activity information without relying on related neural pathways and muscles, thereby achieving communication...

An EEG Study on Artistic and Engineering Mindsets in Students in Creative Processes

A Study on EEG Activities in Artistic and Engineering Thinking during the Creative Process Background and Research Motivation Creativity is universally regarded as the ability to imagine new and valuable things. Researchers have identified two types of creative thinking: growth mindset and fixed mindset. Growth mindset creativity can improve skills...

Temporal Aggregation and Propagation Graph Neural Networks for Dynamic Representation

Temporal Aggregation and Propagation Graph Neural Networks (TAP-GNN) Background Introduction A temporal graph is a graph structure with dynamic interactions between nodes over continuous time, where the topology evolves over time. Such dynamic changes enable nodes to exhibit varying preferences at different times, which is critical for capturing us...

Graph-Based Non-Sampling for Knowledge Graph Enhanced Recommendation

Graph-Based Non-Sampling for Knowledge Graph Enhanced Recommendation

Graph-Based Sampling-Free Knowledge Graph Enhanced Recommendation In recent years, knowledge graph (KG) enhanced recommendation systems, aiming to address cold start problems and the interpretability of recommendation systems, have garnered substantial research interest. Existing recommendation systems typically focus on implicit feedback such as p...

Diffusion-based Deep Learning Method for Augmenting Ultrastructural Imaging and Volume Electron Microscopy

Diffusion-based Deep Learning Method for Augmenting Ultrastructural Imaging and Volume Electron Microscopy

Enhancing Super-Resolution Imaging and Volume Electron Microscopy with Deep Learning Algorithms Based on Diffusion Models Background Introduction Electron Microscopy (EM) as a high-resolution imaging tool has made significant breakthroughs in cell biology. Traditional EM techniques are primarily used for two-dimensional imaging, and although they h...