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The concept of mixing time is significant in producing a uniform concrete mix with the required strength. The mixing period starts once all components are in the mixer. Initially, the mixer is charged with 10% of the water, followed by the consistent addition of solids and then 80% of the water. The remaining water is added later, within the first quarter of the mixing period. The minimum mixing time varies according to the mixer's capacity; for example, mixers with up to 1 cubic yard...
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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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In operant conditioning, the timing of reinforcement is crucial. For animals like rats and cats, immediate reinforcement (within a few seconds) is much more effective than delayed reinforcement. For example, a food reward for a rat needs to follow within 30 seconds of pressing a bar to be effective. 
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Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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The human heart, despite its modest size and weight, is an organ of remarkable strength and endurance. Roughly the size of a fist, the heart weighs between 250 and 350 grams and is nestled within the mediastinum, the medial cavity of the thorax. It extends obliquely for about 12 to 14 cm, resting on the superior surface of the diaphragm. The heart is positioned anterior to the vertebral column and posterior to the sternum, with two-thirds of its mass lying to the left of the midsternal line.
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Related Experiment Video

Updated: Feb 5, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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A mixed-effects location scale model for time-to-event data: A smoking behavior application.

Delphine Courvoisier1, Theodore A Walls2, Boris Cheval1

  • 1Faculty of Medicine, University of Geneva, Switzerland.

Addictive Behaviors
|September 6, 2018
PubMed
Summary

Mixed-effects location scale models (MELS) reveal individual variability in smoking patterns. This statistical approach offers insights into nicotine dependence and can refine smoking cessation programs.

Keywords:
Longitudinal datamixed-effects location scale modelsrandom effectstime to first cigarette

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Area of Science:

  • Statistics
  • Psychology
  • Public Health

Background:

  • Mixed-effects location scale models (MELS) are valuable for analyzing within-person and between-person variability in time-to-event data.
  • Understanding nicotine dependence variability is crucial for optimizing smoking cessation interventions.

Purpose of the Study:

  • To extend MELS to time-to-event smoking data.
  • To analyze daily variations in time to first cigarette among smokers in cessation programs.

Main Methods:

  • Application of MELS to daily time-to-first-cigarette data over seven days.
  • Comparison of smoking patterns between groups asked to continue smoking versus those asked to quit.

Main Results:

  • Identified distinct patterns: stable smokers (smoked daily, later after waking) and variable smokers (missed days, smoked soon after waking).
  • Variable smoking patterns were strongly associated with the group asked to quit smoking.

Conclusions:

  • MELS can provide nuanced insights into individual smoking behaviors during cessation attempts.
  • The MELS framework is adaptable for analyzing other time-to-event outcomes in various cessation programs, such as relapse prediction.