Tag: Vectors

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Spreading

Tiger mosquito,
spreading northwards, adapting.
Deadly time capsules.

Many mosquito species struggle to survive at low temperatures, preventing their spread into cooler climates and thus limiting the spread of diseases carried by the mosquitoes. Yet new research by Medley et al (2019) suggests that some mosquito species may be able to adapt part of their reproductive cycle to survive cold winters.

The Asian tiger mosquito is a vector for a number of pathogens, including Zika and dengue viruses. The species first arrived in the USA in Texas in 1985 and today the current range extends as far north New Jersey.

How has this tropical and sub-tropical species managed to survive the temperate conditions?

The secret lies with a process called diapause – a type of animal dormancy where development is delayed in response to unsuitable environmental conditions such as cold winters.

In the Asian tiger mosquito, the length of day or night (photoperiodism) can induce egg diapause – as the days get shorter with the approach of winter eggs become dormant and only start developing again once the days start to lengthen and temperatures are likely to be more suitable for the species.

In the new study the researchers found that northern diapause eggs survive northern winters a lot better than southern diapause eggs, but both northern and southern diapause eggs survive southern winters the same as each other. The research demonstrates the species adapting to colder conditions as it expands northwards over a period of around 30 years. Not only have northern populations adapted to northern climes by producing more eggs but those eggs are adapted to survive the northern winters better too.

Original research: https://doi.org/10.1111/1365-2664.13480

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Low-rank Representation by Dr David Keyes

Vast sea of numbers,

Can you be described by few,

As bones define flesh?

 

Many data objects, such as matrices, which are traditionally described by providing a high precision number for every (row,column) entry, can be represented to usefully high precision by many fewer numbers. This so-called “data sparsity” holds for the mathematical descriptions of many physical and statistical phenomena whose effects or correlations decay smoothly with distance.

An apparently complex interaction or relationship is, with a special perspective, much simpler. In an extreme limit, we can lump the moon’s gravitational effect on the Earth by assuming that all of its distributed mass is concentrated at a single point. The potential to represent dense matrices by products of a small number of vectors (the number needed is called the “rank”) is analogous to this and leads to huge savings in memory and operations when manipulating such objects. The effect of the whole can be represented by a carefully defined abstraction. One version of this technique is called “skeletonization,” which suggests the Sciku above. For an example of this philosophy, see Yokota et al, 2014.

Original research:  https://doi.org/10.14529/jsfi140104

David Keyes directs the Extreme Computing Research Center at KAUST, where he was a founding dean in 2009. He inhabits the intersection of Mathematics, Computer Science, and applications, with a focus on colonizing emerging energy-efficient architectures for scientific computations. He is a Fellow of SIAM and AMS and has received the ACM Gordon Bell Prize and the IEEE Sidney Fernbach Award. As a lover of poetry, he is delighted to discover the Sciku community.

Enjoyed this sciku? Check out David’s other sciku: Algorithmic complexity.