nograpes

It is domain-specific, but the domain is rather large. In the vast majority of life science fields, LaTeX is not accepted for journal articles, even in fields where you might expect it. In medical informatics, for example, direct LaTeX upload is uncommon, which you might not expect for an informatics journal.

What would an updated version of Session Restore look like? I mean, what would be your vision for a new version?

They aren't real books. This is a joke.

The purpose of the definition is not to evaluate individual aging, but the aging of populations. The probability of death neatly summarizes all the risks that the population experiences at different ages. Although the probability for a single person is difficult to measure, and can vary wildly with varying behaviour, the probability is easy to measure at the population level. By summarizing over the whole population, you can see the risks that are common to all humans, rather than just particular populations.

So smokers or people who jump from planes may not be older compared to those who don't. We don't have a single, reliable instrument that can measure individual level aging.

I think the folk definition of aging is actually aligns quite closely with the probability of death definition.

Consider the phrase "He looks like he aged 20 years, but it has only been 5 years since I last saw him." Everybody understands this to mean that he looks like his health has declined in 5 years the way most people's health would decline in 20 years.

If you replace "health has declined" with "probability of death has increased", then it means roughly the same thing. It is true that the folk understanding of "health has declined" could be based on several proxies such as skin texture, baldness, etc. I think what the probability of death definition does is bring some precision to what you mean when you say "health has declined".

The article does not mention it, but the cited journal article says that:

"Survivorship (on a log scale) is depicted by the shaded areas."

Notably, the journal article shades the area underneath the line that is labeled 'survival' in the linked article.

The author defined aging in terms of the probability of death. I found this definition helpful rather than confusing. You noted that we age and die at a constant rate; how would you define aging if not in terms of the probability of death?

There are some problems with the definition. Humans have very high relative probability of death during their first five years, but this quickly declines and then starts to rise again. This means that humans "age" backwards for the first part of their life, which is not particularly intuitive or helpful. However, the definition is helpful in the context of understanding how our aging compares to aging in other animals.

I wonder if there is a way to calculate the denominator for each of those? The proportion would be a much more compelling argument.

Has anyone got mouse wheel support working on a PuTTy terminal? I've compiled htop from source against ncurses 6 on Ubuntu, but no luck.

I know it sounds like I'm asking a lot for a PuTTy window... but mouse clicks have (amazingly) worked even on a very old version of htop. Just wondering if anyone has done it before pursuing it further.

In English, we have several similar words that are derived from this French meaning (putrid is an example). Both words are related to Latin "putere" meaning "to stink". The ultimate root of these words is the Proto-Indo-European root word *pu- "to rot, stink" [1].

It is not clear if the current meaning of the term pee-yoo is derived from this Indo-European root. The first Oxford English Dictionary entry is in 1604, where it shows up with several different spellings: pue, peuh, peugh, pyoo, and pew [2]. The "stretching" of the word into two syllables must have happened sometime later.

[1] http://www.etymonline.com/index.php?term=putrid

[2] http://www.grammarphobia.com/blog/2010/08/on-the-scent.html

Like this:

  db<-data.frame(replicate(44,1:5))
  likertcat <- as.ordered(c("Not at all", "To a small extent", "To some extent",
                 "To a moderate extent", "To a large extent"))
  db[ ,9:44] <- lapply(db[,9:44], function(x) likertcat[x])