Scanning transmission electron microscopy (STEM) provides structural analysis with sub-angstrom resolution. But the pixel-by-pixel scanning process is a limiting factor in acquiring high-speed data. Different strategies have been implemented to increase scanning speeds while at the same time minimizing beam damage via optimizing the scanning strategy. Here, we achieve the highest possible scanning speed by eliminating the image acquisition dead time induced by the beam flyback time combined with reducing the amount of scanning pixels via sparse imaging. A calibration procedure was developed to compensate for the hysteresis of the magnetic scan coils. A combination of sparse and serpentine scanning routines was tested for a crystalline thin film, gold nanoparticles, and in an in-situ liquid phase STEM experiment. Frame rates of 92, 23 and 5.8 s were achieved for images of a width of 128, 256, and 512 pixels, respectively. The methods described here can be applied to single-particle tracking and analysis of radiation sensitive materials.
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http://dx.doi.org/10.1038/s41598-021-02052-1 | DOI Listing |
J Am Coll Cardiol
November 2024
Elite Centre for Individualized Medicine in Arterial Disease, Odense University Hospital, Odense, Denmark; Department of Cardiothoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Background: Prospective data on the clinical course of the ascending thoracic aorta are lacking.
Objectives: This study sought to estimate growth rates of the ascending aorta and to evaluate occurrences of adverse aortic events (AAEs)-that is, thoracic aortic ruptures, type A aortic dissections, and thoracic aortic-related deaths.
Methods: In this prospective cohort study from the population-based, multicenter, randomized DANCAVAS (Danish Cardiovascular Screening trials) I and II, participants underwent cardiovascular risk assessments including electrocardiogram-gated, noncontrast computed tomography (CT) scans.
Am J Orthod Dentofacial Orthop
January 2025
Department of Orthodontics, Gulhane Faculty of Dental Medicine, University of Health Sciences, Ankara, Turkey.
Introduction: This study aimed to evaluate the stability of palatal rugae patterns after slow maxillary expansion (SME) treatment and the reliability of the rugae region as a reference region in digital superimposition.
Methods: The SME group comprised 21 subjects with Angle Class I or Class II dental malocclusion with unilateral or bilateral crossbite and constricted maxilla and were selected before the pubertal peak. Intraoral scans were captured via the intraoral scanner iTero Element software (version 1.
Sensors (Basel)
December 2024
Department of Intelligent Systems & Robotics, Chungbuk National University, Cheongju 28644, Republic of Korea.
Handheld LiDAR scanners, which typically consist of a LiDAR sensor, Inertial Measurement Unit, and processor, enable data capture while moving, offering flexibility for various applications, including indoor and outdoor 3D mapping in fields such as architecture and civil engineering. Unlike fixed LiDAR systems, handheld devices allow data collection from different angles, but this mobility introduces challenges in data quality, particularly when initial calibration between sensors is not precise. Accurate LiDAR-IMU calibration, essential for mapping accuracy in Simultaneous Localization and Mapping applications, involves precise alignment of the sensors' extrinsic parameters.
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December 2024
Division of Neurological Rehabilitiation, Instituto Nacional de Rehabilitacion Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico.
Stroke is a global health issue caused by reduced blood flow to the brain, which leads to severe motor disabilities. Measuring oxygen levels in the brain tissue is crucial for understanding the severity and evolution of stroke. While CT or fMRI scans are preferred for confirming a stroke due to their high sensitivity, Near-Infrared Spectroscopy (NIRS)-based systems could be an alternative for monitoring stroke evolution.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Faculty of Computer Science, Polish-Japanese Academy of Information Technology, 86 Koszykowa Street, 02-008 Warsaw, Poland.
Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans ( = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated.
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