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Improving Molecular Design with Direct Inverse Analysis of QSAR/QSPR Model.
Mol Inform
January 2025
Department of Applied Chemistry, School of Science and Technology, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan.
Recent advances in machine learning have significantly impacted molecular design, notably the molecular generation method combining the chemical variational autoencoder (VAE) with Gaussian mixture regression (GMR). In this method, a mathematical model is constructed with X as the latent variable of the molecule and Y as the target properties and activities. Through direct inverse analysis of this model, it is possible to generate molecules with the desired target properties.
View Article and Find Full Text PDFScale-Consistent and Temporally Ensembled Unsupervised Domain Adaptation for Object Detection.
Sensors (Basel)
January 2025
School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.
Unsupervised Domain Adaptation for Object Detection (UDA-OD) aims to adapt a model trained on a labeled source domain to an unlabeled target domain, addressing challenges posed by domain shifts. However, existing methods often face significant challenges, particularly in detecting small objects and over-relying on classification confidence for pseudo-label selection, which often leads to inaccurate bounding box localization. To address these issues, we propose a novel UDA-OD framework that leverages scale consistency (SC) and Temporal Ensemble Pseudo-Label Selection (TEPLS) to enhance cross-domain robustness and detection performance.
View Article and Find Full Text PDFHierarchical Optimization Segmentation and Parameter Extraction of Street Trees Based on Topology Checking and Boundary Analysis from LiDAR Point Clouds.
Sensors (Basel)
January 2025
School of Geosciences, Yangtze University, Wuhan 430100, China.
Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process.
View Article and Find Full Text PDFOn the steroids extracted from soft corals against the NS3/4A protease of hepatitis C virus.
J Mol Graph Model
December 2024
Faculty of Chemistry and Center for Computational Science, Hanoi National University of Education, Hanoi, Viet Nam; Institute of Natural Sciences, Hanoi National University of Education, Hanoi, Viet Nam.
The Hepatitis C virus (HCV) causes a variety of liver diseases, making it a global health issue that affects millions of people in the world. The NS3/4A protease has been considered a common target for anti-HCV treatments using direct-acting antiviral agents and their derivatives. Of the natural products that have been proposed for novel therapeutic product alternatives, the soft coral compounds are found to contain steroids with various bioactive properties for effective HCV treatments.
View Article and Find Full Text PDFComparing Virtual Reality-Based and Traditional Physical Objective Structured Clinical Examination (OSCE) Stations for Clinical Competency Assessments: Randomized Controlled Trial.
J Med Internet Res
January 2025
Institute of Medical Teaching and Medical Education Research, University Hospital Würzburg, Würzburg, Germany.
Background: Objective structured clinical examinations (OSCEs) are a widely recognized and accepted method to assess clinical competencies but are often resource-intensive.
Objective: This study aimed to evaluate the feasibility and effectiveness of a virtual reality (VR)-based station (VRS) compared with a traditional physical station (PHS) in an already established curricular OSCE.
Methods: Fifth-year medical students participated in an OSCE consisting of 10 stations.
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