Large-scale Testing
Large-scale Testing - Related Videos
02:41
pH Scale
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2020
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...
08:18
A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances
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Cited by 4 •
2020
We demonstrate algal toxicity testing for difficult substances (e.g., colored substances or nanomaterials) using a setup illuminated vertically with an LED.
07:17
Pilot Testing
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2023
Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University In any experiment researchers have the challenge of creating experiences for participants that are consistent (i.e., reliable) and authentic (i.e., valid). Yet there are many ways to manipulate any one variable. For example, if you want participants to feel sad, you can have them think of their own sad memory, watch a sad video, or read a sad story. Researchers must find the best way to...
08:46
Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
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Cited by 5 •
2016
For this study synchrotron radiation micro-tomography, a non-destructive three-dimensional imaging technique, is employed to investigate an entire microelectronic package with a cross-sectional area of 16 x 16 mm. Due to the synchrotron's high flux and brightness the sample was imaged in just 3 min with an 8.7 µm spatial resolution.
10:08
Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests
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Cited by 4 •
2017
This paper describes the assembly process and operation of a bench-scale photosynthetic bioreactor that can be used, in conjunction with other methods, to estimate pertinent kinetic growth parameters. This system continuously monitors the pH, light, and temperature using sensors, a data acquisition and control unit, and open-source data acquisition software.
FAQs
Larger sample sets improve the power to detect subtle genetic effects that may be difficult to observe in smaller groups. Testing many individuals also helps determine whether an apparent genotype–phenotype relationship is reproducible across a population rather than limited to a few observations. This makes findings more useful for disease-risk assessment, biological interpretation, and follow-up research.
Quality-control filters help separate meaningful measurements from technical error, while statistical methods evaluate whether observed associations could have arisen by chance. Together, these safeguards reduce the risk that unreliable measurements or coincidental patterns will be interpreted as biological signals. Their use is essential when many markers, variants, and samples are analyzed in parallel.
Analyzing broad sets of genetic markers or variants can reveal reproducible patterns across populations, including relationships between genotypes and phenotypes. The same strategy can expose biological diversity and support the search for variants associated with disease-related traits. Because the measurements span many samples, results can provide a stronger basis for identifying signals that merit further investigation.
A typical workflow begins with parallel measurement of many samples, markers, or variants through high-throughput genotyping or sequencing. Automated processing then organizes the resulting measurements, followed by quality-control filtering to remove technical problems. Statistical analysis evaluates patterns, associations, and the possibility of chance findings, producing results suitable for interpretation and experimental follow-up.
Researchers may choose this approach when they need to examine genotype–phenotype relationships across populations, search for disease-associated variants, or characterize genetic diversity. It is also relevant to genome-wide association studies and population-scale screening, where analyzing many measurements simultaneously provides the breadth needed to identify patterns that narrower testing might miss.
Results may identify reproducible associations, reveal biological diversity, and improve assessment of disease risk or subtle genetic effects. They can also generate evidence for follow-up experiments and clinical research rather than serving as an endpoint by themselves. Interpretation depends on the combination of measurement quality, statistical evaluation, sample size, and the consistency of signals across the analyzed population.