Stable Post Tracker
Stable Post Tracker - Related Videos
05:48
How to Build a Dichoptic Presentation System That Includes an Eye Tracker
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Cited by 13 •
2017
We recently proposed a method that allows dichoptic visual stimulus presentation and binocular eye tracking simultaneously1. The key is the combination of an infrared eye tracker and the corresponding infrared-transparent mirrors. This manuscript provides an in depth protocol for initial setup and everyday operation.
12:39
A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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Cited by 8 •
2020
Using multimodal sensors is a promising way to understand the role of social interactions in educational settings. This paper describes a methodology for capturing joint visual attention from colocated dyads using mobile eye-trackers.
12:09
Generation of Stable Transgenic C. elegans Using Microinjection
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Cited by 93 •
2008
This video demonstrates the technique of microinjection into the gonad of C. elegans to create transgenic animals.
12:59
A System to Create Stable Nanoparticle Aerosols from Nanopowders
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Cited by 4 •
2016
We designed and developed an effective nanopowder aerosolization setup and operating protocol. The system generated nanoparticle aerosols with stable number concentrations and size distributions for long durations, requiring only small quantities of test material (min. 200 mg).
01:24
The Seemingly Stable Trade‐Off
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2026
The short-run Phillips curve shows the relationship between the inflation rate and the unemployment rate.During the 1960s, economists observed that this relationship seemed to hold consistently. When unemployment was low, inflation tended to be high, and when unemployment was high, inflation tended to be low.Policymakers at the time interpreted this relationship as a necessary trade-off between unemployment and inflation. They thought they could reduce unemployment only by allowing higher...
FAQs
A baseline records the system’s condition before an intervention, modification, or deployment, while a reference value provides a comparison point for later measurements. Reviewing subsequent results against these values helps determine whether an observed difference represents a sustained shift or a temporary fluctuation. This comparison supports more consistent judgments about system performance over time.
Repeated measurements reveal whether a change persists across planned time points rather than appearing only once. A single result may reflect short-term variation, but a pattern across observations provides stronger evidence about the system’s ongoing behavior. This temporal perspective is useful when assessing whether an engineered construct maintains its intended characteristics after modification or deployment.
The workflow can follow functional performance, structural condition, and viability, depending on which characteristics matter for the system under study. Examining these dimensions separately can show whether a construct remains operational while its structure changes, or whether structural preservation occurs alongside declining viability. Such distinctions help bioengineers identify the type of instability that requires attention.
First, define the intervention, modification, or deployment event and select the characteristics that will be monitored. Next, collect baseline or reference measurements, schedule observations at planned time points, and record results consistently. Finally, compare later measurements with the initial or reference values to identify persistent changes, short-term variation, and overall stability.
Researchers can apply the workflow when they need to evaluate how an engineered cell system, tissue, biomaterial, or related biological construct behaves after a defined change or deployment. It is particularly relevant for quality control and performance assessment, because monitoring over time can reveal whether the construct continues to meet expected functional, structural, or viability-related requirements.
The measurements provide evidence for judging whether a design performs consistently after intervention or deployment. Detecting persistent changes can guide design decisions, while identifying short-term variation can prevent premature conclusions about failure or improvement. Recording comparable observations across time also strengthens experimental reproducibility by making stability assessments more systematic and easier to evaluate.