Results 51 to 60 of about 50,928 (258)

MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis

FEBS Open Bio, EarlyView.
MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss, Ao Li, Eduardo H. Gilglioni, Mayank Bansal, Sumeet Pal Singh, Latifa Bakiri, Alessandra K. Cardozo, Esteban N. Gurzov   +7 more
wiley   +1 more source

Progressive Point Cloud Deconvolution Generation Network [PDF]

, 2020
In this paper, we propose an effective point cloud generation method, which can generate multi-resolution point clouds of the same shape from a latent vector. Specifically, we develop a novel progressive deconvolution network with the learning-based bilateral interpolation.
Le Hui, Rui Xu 0021, Jin Xie 0001, Jianjun Qian, Jian Yang 0003   +4 more
openaire   +2 more sources

Validity of a Wearable Digital Insole for Assessing Gait ON and OFF in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Gait impairment is a distinctive symptom of Parkinson's disease that negatively impact mobility. We assessed the validity of wearable digital insoles against a validated reference gait analysis system for measuring select gait characteristics in patients with Parkinson's disease. Methods A comparative analysis between digital insoles
Deborah A. Hall, Kimberly Kwei, Rolando J. Acosta, Bharatkumar Koyani, Erin Robertson, Pratyush Rai, Roland Barge, Emily Timm, Nicollette L. Purcell, Natasha Desai, Dhanesh Patel, Ana‐Maria Visoiu‐Knapp, Samuel Stuart, Rinol Alaj, Matthew F. Wipperman, Oren Levy, Joan A. O'Keefe   +16 more
wiley   +1 more source

Point-PNG: Conditional Pseudo-Negatives Generation for Point Cloud Pre-Training

IEEE Access
We propose Point-PNG, a novel self-supervised learning framework that generates conditional pseudo-negatives in the latent space to learn point cloud representations that are both discriminative and transformation-sensitive.
Sutharsan Mahendren, Saimunur Rahman, Piotr Koniusz, Tharindu Fernando, Sridha Sridharan, Clinton Fookes, Peyman Moghadam   +6 more
doaj   +1 more source

Automated Generation of Room Usage Semantics from Point Cloud Data

ISPRS International Journal of Geo-Information, 2023
Room usage semantics in models of large indoor environments such as public buildings and business complex are critical in many practical applications, such as health and safety regulations, compliance, and emergency response.
Guoray Cai, Yimu Pan
doaj   +1 more source

Disease Course After Anti‐CD20 Discontinuation in Secondary Progressive Multiple Sclerosis—A Multicenter Long‐Term Longitudinal Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To describe long‐term outcomes after anti‐CD20 discontinuation in selected patients with secondary progressive multiple sclerosis (SPMS) who remained without subsequent disease‐modifying therapy (DMT). Methods We retrospectively analyzed data from four centers in Austria and Switzerland.
Ferdinand Otto, Dariia Kliushnikova, Richard Friedrich Radlberger, Sinan Yasaroglu, Tobias Moser, Andrea Harrer, Kitty Kratzer, Wolfgang Hitzl, Christiane Gradl, Martin Schmidauer, Patrick Roth, Harald Hegen, Peter Wipfler   +12 more
wiley   +1 more source

Getting Topology and Point Cloud Generation to Mesh

CoRR, 2019
Sets & Partitions Workshop at NeurIPS ...
Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang 0001   +3 more
openaire   +2 more sources

PCGen: Point Cloud Generator for LiDAR Simulation

2023 IEEE International Conference on Robotics and Automation (ICRA), 2023
Data is a fundamental building block for LiDAR perception systems. Unfortunately, real-world data collection and annotation is extremely costly & laborious. Recently, real data based LiDAR simulators have shown tremendous potential to complement real data, due to their scalability and high-fidelity compared to graphics engine based methods.
Chenqi Li, Yuan Ren, Bingbing Liu
openaire   +2 more sources

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez, Alejandro F. Manchón‐Gordón, Antonio Vidal‐Crespo, Rafael Caballero‐Flores, Jhon J. Ipus, Clara F. Conde   +5 more
wiley   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source