Mid Domain
Mid Domain - Related Videos
01:31
Ed through Mid-point Method
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2024
At point A, the price is $6 for 120 units. Moving to point B, the price increases to $9, resulting in a decrease in quantity demanded to 80 units. This translates to a 50 percent increase in price and a 33.33 percent decrease in quantity, leading to a price elasticity value of 33.33/50 or 0.67. Conversely, moving from point B to A, entails a 33.33 percent decline in price and a 50 percent increase in quantity. This yields a price elasticity of 50/33.33 or 1.5. This discrepancy arises from the...
02:26
Conservation of Protein Domains Over Different Proteins
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2020
Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms. A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
08:44
The Utility of Stage-specific Mid-to-late Drosophila Follicle Isolation
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Cited by 9 •
2013
Stage-specific isolation of mid-to-late Drosophila follicles is useful for a variety of purposes. Such follicles develop in culture, which allows for genetic and/or pharmacologic manipulations to be coupled with in vitro development assays and live imaging. Additionally, follicles can be used for molecular studies, such as isolating mRNA and protein.
09:39
In-situ Tapering of Chalcogenide Fiber for Mid-infrared Supercontinuum Generation
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Cited by 5 •
2013
We describe a method for in-situ tapering of As2S3 fibers to achieve efficient mid-infrared supercontinuum generation. By tapering while monitoring the supercontinuum’s spectrum, the spectral width can be maximized for a fiber taper. In-situ fiber tapering can be applied to optimize the performance of other fiber-based devices.
07:42
Nerve-sparing Mid-urethral Obstruction (NeMO) in Female Small Rodents
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Cited by 7 •
2017
Traditional modeling of partial bladder outlet obstruction in rodents is fraught with animal mortality. A denervation injury from dissection around the proximal urethra and bladder neck is also of major concern. We developed and evaluated a safe and reliable mid-urethral obstruction model, avoiding the shortcomings of the traditional model.
FAQs
Central accumulation arises from geometry rather than a biological advantage. When species ranges are placed randomly inside the same bounded domain, ranges near an edge have fewer allowable positions and are more likely to terminate at that boundary. Ranges positioned around the middle can overlap with ranges extending from either side, so the model predicts a richness maximum there. This gives biogeographers a spatial baseline.
The boundary defines where ranges may be placed and therefore sets the spatial context for the prediction. A geographic or environmental limit can produce a central peak solely through containment, so changing the defined limits changes the null expectation. Comparing predictions under different boundaries helps assess whether an observed richness pattern reflects spatial constraint or requires additional explanations such as latitude, habitat boundaries, competition, or historical processes.
An environmental explanation attributes higher richness to conditions that favor more species, whereas the mid-domain effect starts with random range placement and fixed limits. The resulting center peak can therefore appear without invoking stronger environmental conditions or biological interactions. This contrast lets researchers ask whether the observed pattern exceeds the richness pattern expected from boundaries alone.
First, they define geographic or environmental limits and represent species ranges as positions constrained within them. The model then produces a predicted richness pattern from the allowed overlap. Researchers compare that prediction with observed species richness across the same domain. Agreement supports spatial constraint as a possible contributor; departures indicate that other processes should be evaluated.
A mismatch does not identify one cause by itself. It shows that the boundary-based null expectation does not fully account for the observed distribution, prompting evaluation of latitude, habitat boundaries, competition, and historical processes. The comparison is therefore diagnostic rather than definitive: it separates a pattern explainable by spatial containment from one requiring additional biological or historical interpretation.
In biogeography, species richness often varies across geographic or environmental space. The mid-domain framework supplies a controlled baseline for interpreting that variation, especially when distributions occupy a defined domain. It helps prevent a central richness peak from being treated automatically as evidence of superior habitat or stronger interactions, and it places biological explanations alongside a spatial null model.