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

Equation of Motion: General Plane motion01:22

Equation of Motion: General Plane motion

569
In the context of a rigid body's movement within a general plane, it is important to understand that this motion is typically triggered by external forces or couple moments exerted onto it. This principle can be explained through Newton's second law, which stipulates the translational motion of the body's center of mass along each axis.
Moreover, the body's center of mass experiences a rotational effect as a result of these couple moments. This rotation can be articulated as the...
569
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

557
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
557
Equation of Motion: General Plane motion - Problem Solving01:16

Equation of Motion: General Plane motion - Problem Solving

502
Consider a lawn roller with a mass of 100 kg, a radius of 0.2 meters, and a radius of gyration of 0.15 meters. A force of 200 N is applied to this roller, angled at 60 degrees from the horizontal plane. What will be the angular acceleration of the lawn roller?
The friction between the roller and the ground is characterized by two coefficients. The static friction coefficient is 0.15, while the kinetic friction coefficient is 0.1. These values are crucial in understanding the interaction between...
502
Projectile Motion: Example01:18

Projectile Motion: Example

12.7K
The theory of projectile motion is very useful for players of several sports to improve their performance. For example, a javelin thrower needs to throw their javelin in such a way that it travels as far as possible. The javelin thrower takes a short run-up to increase the initial speed of the javelin. The range of a projectile is at its maximum at a 45° angle so javelin throwers try to angle their throw as close to 45° as possible.
When we speak of the range (R) of a projectile on...
12.7K
Simple Harmonic Motion and Uniform Circular Motion01:42

Simple Harmonic Motion and Uniform Circular Motion

5.6K
While simple harmonic motion and uniform circular motion may be two separate concepts, they correlate and interlink with each other. Simple harmonic motion is an oscillatory motion in a system where the net force can be described by Hooke's law, while uniform circular motion is the motion of an object in a circular path at constant speed.
There is an easy way to produce simple harmonic motion by using uniform circular motion. For instance, consider a ball attached to a uniformly rotating...
5.6K
Torque Free Motion01:15

Torque Free Motion

808
The torque-free motion refers to the movement of a rigid body in space when no external torques are acting upon it. This type of motion can be observed in environments where there are no external forces or frictions, like in outer space. For example, a rotation of Mars in space is a torque-free motion. Mars is an axisymmetric object, meaning it has an axis of symmetry along which it rotates, designated as the z-axis. The rotating frame of reference is defined such that the center of mass of...
808

You might also read

Related Articles

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

Sort by
Same author

Delayed Cardiovascular Response to Acute Hypotension in Heart Failure Patients Compared to Healthy Adults.

International journal of vascular medicine·2026
Same author

Decoding fibrosis: Transcriptomic and clinical insights via AI-derived collagen deposition phenotypes in MASLD.

Hepatology (Baltimore, Md.)·2026
Same author

Modulation of Oncogenic KRAS Signaling by Branched Actin-driven Cell Membrane Protrusions.

Research square·2026
Same author

Integrating new fruit and vegetable growth parameters in SWAT models for improved simulations.

Frontiers in plant science·2026
Same author

Volumetric Cyclic Immunofluorescence for 3D Spatial Profiling of Immune Structures in Human FFPE Tissue.

bioRxiv : the preprint server for biology·2026
Same author

Accuracy of Diagnosis in Myeloproliferative Neoplasms With Splanchnic Vein Thrombosis (MPN-SVT).

American journal of hematology·2026

Related Experiment Video

Updated: Jan 28, 2026

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence
14:55

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence

Published on: March 5, 2022

4.4K

Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion

Felix Y Zhou1, Carlos Ruiz-Puig1, Richard P Owen1

  • 1Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom.

Elife
|February 27, 2019
PubMed
Summary
This summary is machine-generated.

A new computational tool, Motion Sensing Superpixels (MOSES), quantifies cell motion and interactions. This framework aids in understanding tissue homeostasis and disease development from time-lapse imaging data.

Keywords:
boundary formationcollective motioncomputational biologydevelopmental biologydynamic graphshumanmotion analysismotion mapssuperpixelssystems biology

More Related Videos

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

1.2K
Visualizing Motion Patterns in Acupuncture Manipulation
08:18

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

9.2K

Related Experiment Videos

Last Updated: Jan 28, 2026

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence
14:55

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence

Published on: March 5, 2022

4.4K
Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

1.2K
Visualizing Motion Patterns in Acupuncture Manipulation
08:18

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

9.2K

Area of Science:

  • Cell biology
  • Biophysics
  • Computational biology

Background:

  • Cell-cell interactions and motion are crucial for tissue homeostasis.
  • Defects in cellular dynamics are linked to various diseases.
  • Current tools for analyzing cell motion in time-lapse data are limited.

Purpose of the Study:

  • To introduce Motion Sensing Superpixels (MOSES), a novel computational framework.
  • To enable quantitative measurement and characterization of biological motion.
  • To overcome limitations in existing methods for analyzing complex cellular dynamics.

Main Methods:

  • Development of a computational framework utilizing a superpixel 'mesh' formulation.
  • Application of MOSES to analyze published time-lapse datasets.
  • Utilizing MOSES for single-cell tracking and population quantification.

Main Results:

  • MOSES demonstrated effective single-cell tracking.
  • MOSES provided more advanced population quantification than Particle Image Velocimetry.
  • MOSES successfully mapped interactions between esophageal cells relevant to cancer development.

Conclusions:

  • MOSES is a powerful tool for unbiased analysis of cellular dynamics.
  • The framework facilitates systematic analysis from high-content time-lapse imaging.
  • MOSES requires minimal prior knowledge and assumptions for its application.