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Assessing Body Temperature - Temporal Artery01:19

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Here is a stepwise guide to assessing the body temperature at the temporal artery using a temporal artery thermometer
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A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
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Peripheral thermosensation is the perception of external temperature. A change in temperature (on the surface of the skin and other tissues) is detected by a family of temperature-sensitive ion channels called Transient Receptor Potential, or TRP, receptors. These receptors are located on free nerve endings. Those detecting cold temperatures are closer to the surface of the skin than the nerve endings detecting warmth. These thermoTRP channels, while temperature selective, have relatively...
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The Collision Theory
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Novel Model Based on Artificial Neural Networks to Predict Short-Term Temperature Evolution in Museum Environment.

Alessandro Bile1, Hamed Tari1, Andreas Grinde2

  • 1Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, via A. Scarpa 16, 00161 Roma, Italy.

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|January 22, 2022
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Summary

Artificial Intelligence (AI) models accurately predicted short-term microclimate fluctuations in museums. This technology aids in preserving cultural heritage by preventing climate-induced artwork damage.

Keywords:
NARNARXartificial neural networkscultural heritage preservationforecastingnonlinear autoregressive neural networkstime series

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Area of Science:

  • Environmental Science
  • Computer Science
  • Conservation Science

Background:

  • Environmental microclimates significantly impact artwork preservation, posing risks of irreparable damage.
  • Fluctuations in temperature and humidity are critical factors affecting cultural heritage stability.
  • Proactive monitoring and prediction are essential for effective preventive conservation strategies.

Purpose of the Study:

  • To evaluate the efficacy of Artificial Intelligence (AI) techniques for predicting short-term microclimatic variations.
  • To apply Nonlinear Autoregressive (NAR) and Nonlinear Autoregressive with Exogenous (NARX) models to museum microclimate data.
  • To explore AI as a decision-support tool for mitigating climate-induced damage to artworks in cultural institutions.

Main Methods:

  • Time series analysis of microclimate data from Rosenborg Castle.
  • Application of Nonlinear Autoregressive (NAR) and Nonlinear Autoregressive with Exogenous (NARX) AI models.
  • Validation of predictive capabilities on small historical datasets.

Main Results:

  • Both NAR and NARX models demonstrated good adaptive capacity in predicting short-term microclimate values.
  • The AI models showed potential for accurate forecasting even with limited data.
  • Successful application of AI for microclimate prediction in a real-world museum setting.

Conclusions:

  • AI, specifically NAR and NARX models, offers a viable solution for very short-term forecasting of microclimate variables in museums.
  • The proposed AI models can serve as valuable decision-support tools for museum management.
  • Implementing AI-driven forecasting can enhance preventive conservation efforts and protect valuable artworks from climate-related deterioration.