Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/S1359-6446(04)03203-9 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Design of a Wearable Exoskeleton Piano Practice Aid Based on Multi-Domain Mapping and Top-Down Process Model.
Biomimetics (Basel)
December 2024
School of Information Engineering, Quanzhou Ocean Institute, Quanzhou 362700, China.
This study designs and develops a wearable exoskeleton piano assistance system for individuals recovering from neurological injuries, aiming to help users regain the ability to perform complex tasks such as playing the piano. While soft robotic exoskeletons have proven effective in rehabilitation therapy and daily activity assistance, challenges remain in performing highly dexterous tasks due to structural complexity and insufficient motion accuracy. To address these issues, we developed a modular division method based on multi-domain mapping and a top-down process model.
View Article and Find Full Text PDFOpen Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement.
PLoS One
January 2025
Woodwell Climate Research Center, Falmouth, MA, United States of America.
Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs.
View Article and Find Full Text PDFL2G: Repurposing Language Models for Genomics Tasks.
bioRxiv
December 2024
Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Pre-trained language models have transformed the field of natural language processing (NLP), and their success has inspired efforts in genomics to develop domain-specific foundation models (FMs). However, creating high-quality genomic FMs from scratch is resource-intensive, requiring significant computational power and high-quality pre-training data. The success of large language models (LLMs) in NLP has largely been driven by industrial-scale efforts leveraging vast, diverse corpora and massive computing infrastructure.
View Article and Find Full Text PDFLarge scale Raman spectrum calculations in defective 2D materials using deep learning.
J Phys Condens Matter
January 2025
Département de Physique et Institut Courtois, Université de Montréal, Montréal, Canada.
Article Synopsis
- The authors present a new machine learning workflow designed to predict how defects affect the Raman response of 2D materials.
- By integrating various techniques, including machine-learned potentials and a density of states method, they can simulate large systems with tens of thousands of atoms.
- They validate their approach by applying it to isotopic graphene and defective hexagonal boron nitride, finding their predictions align well with experimental data, suggesting potential for further studies in solid-state physics.
Density-wave-like gap evolution in LaNiO under high pressure revealed by ultrafast optical spectroscopy.
Nat Commun
November 2024
Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, China.
Density wave (DW) order is believed to be correlated with superconductivity in the recently discovered high-temperature superconductor LaNiO. However, experimental investigations of its evolution under high pressure are still lacking. Here, we explore the quasiparticle dynamics in bilayer nickelate LaNiO single crystals using ultrafast optical pump-probe spectroscopy under high pressures up to 34.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!