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Related Concept Videos

Structural Classification of Joints01:20

Structural Classification of Joints

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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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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.
Synarthrosis
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Consider a truss structure with frictionless joints fixed to a wall and roller support. If a force of 150 N is applied to joint A, the forces in each member of the truss can be determined using the method of joints.
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Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
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The method of joints is a commonly used technique to analyze the forces in structural trusses. The method is based on the principle of equilibrium, which assumes that the truss members are connected by frictionless pins. The forces at each joint can be determined by considering the equilibrium of the forces acting on that joint. Consider a truss structure with two forces of 20 N and 10 N acting at joints C and D, respectively. The method of joints can be used to determine the forces FCB, FDC,...
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Predictive joint-action model: A hierarchical predictive approach to human cooperation.

Ana Pesquita1, Robert L Whitwell2, James T Enns2,3

  • 1Department of Psychology, University of British Columbia, Douglas Kenny Building, 2136 West Mall, Vancouver, B.C., V6T 1Z4, Canada. anapesquita@gmail.com.

Psychonomic Bulletin & Review
|November 10, 2017
PubMed
Summary

This study introduces the predictive joint-action model (PJAM), a hierarchical framework to understand human cooperative behavior. PJAM integrates predictive principles with empirical evidence to advance the science of joint action.

Keywords:
Interpersonal coordinationJoint-actionPredictionSocial cognition

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Area of Science:

  • Cognitive Science
  • Social Psychology
  • Neuroscience

Background:

  • Recent research highlights the perceptual, cognitive, and motor aspects of cooperative behavior.
  • The study of human cooperative behavior is emerging as a distinct field: joint-action.
  • Theoretical development in joint-action research lags behind empirical findings.

Purpose of the Study:

  • To propose a novel theoretical framework for the study of joint-action.
  • Introduce the predictive joint-action model (PJAM) as a hierarchical predictive framework.
  • To reconcile existing empirical evidence with a unified theoretical approach.

Main Methods:

  • Summarizing hierarchical predictive principles and their application to joint-action.
  • Juxtaposing PJAM's assumptions with current joint-action literature.
  • Evaluating the hierarchical predictive approach's success in explaining empirical data.

Main Results:

  • PJAM offers a structured approach to understanding the mechanisms of joint-action.
  • The model aligns with and explains a range of empirical findings in the field.
  • Hierarchical predictive principles provide a robust foundation for joint-action research.

Conclusions:

  • PJAM successfully accounts for the burgeoning empirical literature on joint-action.
  • The hierarchical predictive approach offers a promising avenue for future research.
  • The model has the capacity to generate novel, testable hypotheses for joint-action studies.