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Activation Energy01:26

Activation Energy

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Activation energy is the minimum amount of energy necessary for a chemical reaction to move forward. The higher the activation energy, the slower the rate of the reaction. However, adding heat to the reaction will increase the rate, since it causes molecules to move faster and increase the likelihood that molecules will collide. The collision and breaking of bonds represents the uphill phase of a reaction and generates the transition state. The transition state is an unstable high-energy state...
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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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For an ideal solution, the pH is defined as the negative logarithm of the hydrogen ion concentration. For a non-ideal solution, an accurate measurement of the pH must consider the negative logarithm of the hydrogen ion activity rather than concentration. In such a solution, the pH can be more accurately defined as the negative logarithm of a product of the hydrogen ion concentration and its activity coefficient.
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Gene transcription is regulated by the synergistic action of several proteins that form a complex at a gene regulatory site. This is observed in eukaryotes, where the regulation of gene expression is a complex process. Regulatory proteins in eukaryotes can broadly be classified into two types – regulators that bind directly to specific DNA sequences and co-regulators that associate with regulatory proteins but cannot directly bind to the DNA. These co-regulators are further divided into...
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Transcription activators are proteins that promote the transcription of genes from DNA to RNA. In most cases, these proteins contain two separate domains ‒ a domain that binds to DNA and a domain for activating transcription; however, in some cases, a single domain is responsible for both binding and activation of transcription, as seen in the glucocorticoid receptor and MyoD.
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Related Experiment Video

Updated: Jan 22, 2026

Measuring Granulocyte and Monocyte Phagocytosis and Oxidative Burst Activity in Human Blood
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Calibrating an agent-based model of longitudinal human activity patterns using the Consolidated Human Activity

Namdi Brandon1, Paul S Price2

  • 1United States Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, U.S. EPA, 109 T.W. Alexander Drive, Research Triangle Park, 27709, NC, USA. brandon.namdi@epa.gov.

Journal of Exposure Science & Environmental Epidemiology
|July 12, 2019
PubMed
Summary

This study introduces the Agent-Based Model of Human Activity Patterns (ABMHAP) software to simulate year-long human behavior. ABMHAP accurately captures individual activity variations for improved chemical exposure assessment.

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Area of Science:

  • Environmental Health
  • Computational Epidemiology
  • Human Behavior Modeling

Background:

  • Characterizing long-term human exposure to hazardous chemicals requires understanding longitudinal behavior patterns.
  • Traditional methods linking daily records from multiple individuals are challenging for obtaining individual longitudinal data.
  • Agent-based simulation modeling offers an alternative strategy for generating such patterns.

Purpose of the Study:

  • To calibrate and evaluate the Agent-Based Model of Human Activity Patterns (ABMHAP) software.
  • To assess ABMHAP's capability in simulating daily activities (sleeping, eating, commuting, working/schooling) for diverse populations.
  • To determine if ABMHAP can capture interindividual and intraindividual variations in human behavior.

Main Methods:

  • Utilized the U.S. Environmental Protection Agency's Consolidated Human Activity Database (CHAD) for calibration and evaluation.
  • Parameterized ABMHAP using longitudinal (multi-day) activity data from CHAD.
  • Evaluated ABMHAP predictions against single-day behavior data from CHAD for four population groups.

Main Results:

  • ABMHAP was successfully calibrated and evaluated using empirical data from CHAD.
  • The model demonstrated proficiency in simulating key daily activities across working adults, nonworking adults, school-age children, and preschool children.
  • Results confirmed ABMHAP's ability to capture both interindividual and intraindividual variations in human behavior patterns.

Conclusions:

  • The Agent-Based Model of Human Activity Patterns (ABMHAP) is a validated tool for generating year-long human activity patterns.
  • Simulating annual activity patterns with ABMHAP offers a novel approach for exposure assessors.
  • This simulation method may enhance the characterization of exposure-related behaviors beyond traditional survey limitations.