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Setting Time of Cement01:12

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The setting time of cement refers to the process of cement paste transitioning from a plastic state to a solid state. This process is crucial in construction as it dictates the timeframe for concrete placement, compaction, and finishing. The onset of this solidification is termed the initial set, indicating when the paste becomes unworkable. The final set is when the paste has solidified completely, and further handling or manipulation can no longer affect its shape. The cement strength is...
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When analyzing the behavior of structures, engineers often rely on the concept of equilibrium. This refers to the state where all forces and moments acting on a system balance each other, resulting in no net movement or rotation. In many cases, equilibrium can be described by a set of standard equations. However, in some situations, alternative sets of equilibrium equations must be used to describe the system's behavior accurately.
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Setting Benchmarks for the New User: Training on the Robotic Simulator.

Shayan M Dioun1, Nicole D Fleming1, Mark F Munsell2

  • 1Department of Gynecologic Oncology and Reproductive Medicine.

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|December 28, 2017
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Summary

Robotic simulator scores accurately reflect gynecologic surgeon experience. Most trainees achieved benchmark scores after repeated practice, suggesting its utility in fellowship training.

Keywords:
GynecologyOncology Robotic surgerySimulator curriculumSurgical simulationSurgical training

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Area of Science:

  • Surgical Education
  • Medical Simulation
  • Robotic Surgery

Background:

  • Limited data exist on robotic simulator impact on fellowship training.
  • Assessing simulator score validity for experienced robotic surgeons is crucial.
  • Developing a standardized simulator curriculum for gynecologic oncology is needed.

Purpose of the Study:

  • To determine if robotic simulator scores correlate with gynecologic surgeon experience.
  • To establish benchmark scores using experienced surgeons.
  • To develop and evaluate a simulator-based curriculum for gynecologic oncology fellows.

Main Methods:

  • Participants were divided into beginner (0-50 cases) and experienced (>50 cases) robotic surgery groups.
  • Baseline module scores were established by participants completing 9 modules thrice.
  • Benchmark scores were defined by the median scores of experienced surgeons; trainees repeated modules to reach benchmarks.

Main Results:

  • Experienced surgeons consistently scored higher than beginners across all modules.
  • Significant differences in scores were observed in Energy Switching 1 and Suture Sponge 2 modules.
  • Over 75% of trainees met proficiency benchmarks in 8 of 9 modules after a median of 3-6 attempts.

Conclusions:

  • Robotic simulator scores effectively differentiate surgeon experience levels.
  • The developed curriculum enabled most trainees to achieve proficiency benchmarks through repetition.
  • Further research is required to validate the correlation between simulator performance and actual surgical outcomes.