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Related Concept Videos

Sound Intensity00:58

Sound Intensity

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The loudness of a sound source is related to how energetically the source is vibrating, consequently making the molecules of the propagation medium vibrate. To measure the loudness of a source, the physical quantity of interest is the intensity. This is defined as the energy emitted per unit of time per unit of area perpendicular to the sound wave's propagation direction. Since the total energy is greater if the source vibrates for a longer duration and over a larger area, dividing the...
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Sound Intensity Level00:53

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Humans perceive sound by hearing. The human ear helps sound waves reach the brain, which then interprets the waves and creates the perception of hearing. The loudness of the environment in which a person is located determines whether they can distinguish between different sound sources.
The human ear can perceive an extensive range of sound intensity, necessitating the use of the logarithmic scale to define a physical quantity—the intensity level. It is a ratio of two intensities and...
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Interdisciplinary Care: The Health Care Team-I01:21

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An interdisciplinary team includes many healthcare professionals working together and utilizing their skills, knowledge, and expertise to provide holistic and quality patient care.
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An interdisciplinary team includes many healthcare professionals working together and utilizing their skills, knowledge, and expertise to provide holistic and quality patient care. Here are a few more healthcare professionals.
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The energy transport per unit area per unit time, or the Poynting vector, gives the energy flux of an electromagnetic wave at any specific time. For a plane electromagnetic wave with E0 and B0 as the peak electric and magnetic fields and traveling along the x-axis, the time-varying energy flux can be given by the following equation:
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Continuing care describes the variety of health, personal, and social services provided over a prolonged period. The need for continuing care is increasing because people are living longer. Many people do not have families or others to care for them. Continuing care is mainly for patients who are disabled, functionally dependent, or suffering from a terminal disease. It is available within institutional settings or in homes. Examples include nursing centers or facilities, assisted living,...
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Updated: Jan 31, 2026

Hemodynamic Precision in the Neonatal Intensive Care Unit using Targeted Neonatal Echocardiography
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Explanatory models in neonatal intensive care: a tutorial.

Willem W L van Meurs1, Timothy A J Antonius2,3

  • 11Cardiovascular and Respiratory Physiology Group, Faculty of Science and Technology, University of Twente, Enschede, The Netherlands.

Advances in Simulation (London, England)
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Summary
This summary is machine-generated.

Explanatory models (EMs) offer an intuitive way to understand complex physiology for fragile patients. This educational technology aids clinical reasoning and communication, particularly in neonatal intensive care.

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Area of Science:

  • Medical Education
  • Clinical Physiology
  • Computational Medicine

Background:

  • Acute care providers face challenges with complex patient physiology and information overload from traditional educational tools.
  • Causal chain explanations have limitations in complex physiological systems.
  • A new educational technology is introduced to simplify understanding and reasoning in clinical settings.

Purpose of the Study:

  • To introduce a novel concept and educational technology for intuitive understanding of complex physiology.
  • To facilitate clinical reasoning and communication among healthcare providers.
  • To explore the utility of explanatory models in medical education.

Main Methods:

  • Developed an explanatory model (EM) representing physiological processes, interventions, and pathologies.
  • Adapted a conceptual model of the neonatal cardiorespiratory system for Transposition of the Great Arteries (TGA).
  • Implemented the model in interactive, animated software for educational use.

Main Results:

  • The software illustrates relationships between interventions and monitored variables in neonates with TGA.
  • Learners can explore clinical scenarios and the effects of therapeutic interventions.
  • The explanatory model provides insights into complex physiological interdependencies.

Conclusions:

  • Explanatory models show potential as mental models for clinical practice.
  • These models may aid clinical decision-making in neonatal intensive care and other fields.
  • The developed educational technology offers a promising approach to complex physiological understanding.