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Classification of Bones01:18

Classification of Bones

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The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
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The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
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Structural Classification of Joints01:20

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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Relative Motion Analysis using Rotating Axes01:25

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
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Classification of Skeletal Muscle Fibers01:48

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Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
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Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
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Related Experiment Video

Updated: Sep 4, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

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Fault detection by skeleton extraction based on orientation field consistency.

Yang Li1, Baorong Zhong2, Xiaohong Xu1

  • 1School of Geosciences, Yangtze University, Wuhan, Hubei, China.

Plos One
|July 15, 2022
PubMed
Summary

This study introduces a novel fault detection method using orientation field consistency and skeleton extraction. The technique efficiently identifies geological faults in seismic data by analyzing orientation field patterns, simplifying the process and enhancing fault continuity.

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Area of Science:

  • Geophysics
  • Seismic Data Analysis
  • Image Processing

Background:

  • Stratigraphic discontinuities, or faults, are critical geological features.
  • Traditional fault detection methods can be influenced by non-structural factors and require extensive parameter tuning.
  • Efficient and automatic fault extraction from seismic data remains a challenge.

Purpose of the Study:

  • To propose an improved fault detection method using skeleton extraction based on orientation field consistency.
  • To enhance the efficiency and automation of fault detection in seismic data.
  • To reduce the impact of transverse non-structural factors on fault identification.

Main Methods:

  • Utilizing orientation field consistency to identify regions of stratigraphic discontinuity in seismic data.
  • Applying binarization and closing operations for fault area extraction and continuity enhancement.
  • Employing a skeleton extraction method based on longitudinal center points for fault line identification.

Main Results:

  • The proposed method effectively extracts discontinuous regions by exploiting lower orientation field consistency.
  • Fault areas are successfully extracted and continuity is improved through binarization and closing operations.
  • Skeleton extraction accurately identifies fault lines, highlighting longitudinal characteristics and suppressing transverse noise.

Conclusions:

  • The developed method simplifies the fault identification process by requiring fewer parameter adjustments compared to classical methods.
  • It demonstrates superior performance in suppressing transverse discontinuities and strengthening fault continuity.
  • This approach offers an efficient and automated solution for fault detection in seismic data analysis.