Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Parallel-axis Theorem01:06

Parallel-axis Theorem

8.7K
The parallel-axis theorem provides a convenient and quick method of finding the moment of inertia of an object about an axis parallel to the axis passing through its center of mass. Consider a thin rod as an example. There is a striking similarity between the process of finding the moment of inertia of a thin rod about an axis through its middle, where the center of mass lies, and about an axis through its end using the conventional method. In the conventional method, the concept of linear mass...
8.7K
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.6K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
1.6K
Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

1.2K
In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position...
1.2K
Parallel Processing01:20

Parallel Processing

921
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
921
Linearization and Approximation01:26

Linearization and Approximation

213
Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...
213
Parallel-Axis Theorem for an Area01:12

Parallel-Axis Theorem for an Area

3.4K
The moment of inertia is a fundamental concept in mechanical engineering that plays a significant role in designing rotationally symmetric objects such as flywheels, gears, and other mechanical systems. In this context, we will discuss the moment of inertia of a flywheel rotating about its centroidal axis and how it relates to the moment of inertia about an axis parallel to it.
For a flywheel approximated as a solid disc, consider an infinitesimal differential element with an arbitrary distance...
3.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A knowledge-guided deep learning framework for quantitative nucleic acid testing.

Briefings in bioinformatics·2026
Same author

DyMamba: dynamic Mamba for microscopy image semantic segmentation.

Bioinformatics (Oxford, England)·2026
Same author

Earthworm-Inspired Self-Powered Multistimuli Neuromorphic Vision Skin with Homogeneous Ion Heterogel Arrays.

ACS applied materials & interfaces·2026
Same author

A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.

Bioinformatics (Oxford, England)·2026
Same author

Corrective osteotomy for distal radius malunion using 3D-printed patient-specific guides and spacers: a retrospective comparative study.

BMC musculoskeletal disorders·2026
Same author

MSFSNet: Multi-Source Few-Shot Adaptation Network for Cross-Subject Depression Recognition from EEG Signals.

IEEE journal of biomedical and health informatics·2026
Same journal

A Transparent, Microfluidic Lab On A Chip For Multi-Modal Cell Culture Monitoring For Neurotoxicity Research.

IEEE transactions on nanobioscience·2026
Same journal

Investigating Effect of Dimensional Variance on Separation of Glomerular Ultrafiltrate in a Microfluidic Environment.

IEEE transactions on nanobioscience·2026
Same journal

Green synthesis of multifunctional ZnFe<sub>2</sub>O<sub>4</sub>-MWCNT-Cellulose acetate nanocomposite for peroxidase enzyme immobilization.

IEEE transactions on nanobioscience·2026
Same journal

IoT-Enabled SnOâ‚‚-Based Humidity Sensor for Real-Time Monitoring in Neonatal Incubators.

IEEE transactions on nanobioscience·2026
Same journal

Electrokinetic and Antibiofilm Effects of Silver Nanoparticles Combined with Imipenem Against multidrug-resistant of Klebsiella pneumoniae.

IEEE transactions on nanobioscience·2026
Same journal

Bio-inspired Optofluidic Molecular Communication with Photothermally Actuated Microrobot Swarms.

IEEE transactions on nanobioscience·2026
See all related articles

Related Experiment Video

Updated: Apr 17, 2026

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
06:18

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions

Published on: April 5, 2024

1.8K

BSIRT: a block-iterative SIRT parallel algorithm using curvilinear projection model.

Fa Zhang, Jingrong Zhang, Albert Lawrence

    IEEE Transactions on Nanobioscience
    |February 14, 2015
    PubMed
    Summary
    This summary is machine-generated.

    A new algorithm, Block-iterative SIRT (BSIRT), enhances large-field electron tomography reconstruction. BSIRT improves image quality and processing speed for detailed structural analysis.

    More Related Videos

    Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects
    06:36

    Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

    Published on: October 18, 2024

    1.6K
    Near Infrared Optical Projection Tomography for Assessments of &#946;-cell Mass Distribution in Diabetes Research
    15:18

    Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

    Published on: January 12, 2013

    17.0K

    Related Experiment Videos

    Last Updated: Apr 17, 2026

    Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
    06:18

    Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions

    Published on: April 5, 2024

    1.8K
    Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects
    06:36

    Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

    Published on: October 18, 2024

    1.6K
    Near Infrared Optical Projection Tomography for Assessments of &#946;-cell Mass Distribution in Diabetes Research
    15:18

    Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

    Published on: January 12, 2013

    17.0K

    Area of Science:

    • Electron Microscopy
    • Image Reconstruction
    • Computational Science

    Background:

    • Large-field high-resolution electron tomography (ET) is crucial for visualizing detailed cellular mechanisms.
    • Increasing field size in ET leads to critical reconstruction distortions and processing time challenges.
    • Existing curvilinear projection models improve ET quality but increase computational complexity.

    Purpose of the Study:

    • To develop a parallel algorithm for large-field electron tomography reconstruction using curvilinear projection.
    • To enhance both the quality and speed of ET reconstruction processes.

    Main Methods:

    • Proposed a novel Block-iterative SIRT parallel algorithm with curvilinear projection (BSIRT).
    • Implemented BSIRT on a GPU platform utilizing block-iterative methods, scope-based data decomposition, and page-based data transfer.
    • Focused on parallelizing iterative reconstruction for large-field ET.

    Main Results:

    • BSIRT demonstrated improved reconstruction quality in large-field ET.
    • The BSIRT algorithm significantly accelerated the reconstruction process.
    • Experimental results validated the effectiveness of the developed parallelization techniques.

    Conclusions:

    • BSIRT offers an effective solution for accelerating and improving large-field electron tomography reconstruction.
    • The parallelization strategy on GPU addresses the computational demands of curvilinear projection models.
    • This advancement facilitates more detailed and efficient structural analysis in electron tomography.