- Sep 2022
How Fast a Low Carbon Transition? Or: Is Vaclav Smil Wrong?
Title: How Fast a Low Carbon Transition? Or: Is Vaclav Smil Wrong? Author: Mark Trexler Date: May 21, 2022
!- for : comparison of green growth vs energy descent
- Jul 2022
New DNA technology is shaking up the family trees of many plants and animals.
One of Darwin's most compelling arguments in favour of evolution by means of natural selection was just how many different, apparently unrelated phenomena it explained. One of these was 'Classification' (what we now call taxonomy).
Darwin argued that, when the taxonomists of his day arranged species into hierarchical groups, those tree-like groupings were best explained by genealogical descent.
Now that biological evolution is accepted as a fact, genealogical descent has become the criterion taxonomists use to place species into hierarchical groups. Ironically, Darwin's explanation of taxonomy means it can no longer be used to justify his theory because modern taxonomy is, in effect, defined by his theory.
The strongest tool we have for identifying genealogical descent in species is modern DNA analysis. This has helped identify many mistakes in former, non-DNA-based taxonomic classifications. But DNA analysis can't be used in all cases… For example, we do not have access to DNA samples of the vast majority of extinct species.
- Jun 2021
Covid vaccine uptake has soared among minorities, but we can’t be complacent about hesitancy. (2021, April 25). Inews.Co.Uk. https://inews.co.uk/opinion/covid-vaccine-uptake-soared-minorities-cant-complacent-hesitancy-970503
- African Descent
- vaccine uptake
- Black British
- ethnic minorities
- vaccine hesitance
- Apr 2016
Effect of step size. The gradient tells us the direction in which the function has the steepest rate of increase, but it does not tell us how far along this direction we should step.
That's the reason why step size is an important factor in optimization algorithm. Too small step can cause the algorithm longer to converge. Too large step can cause that we change the parameters too much thus