Wikipedia:Reference desk/Archives/Science/2015 September 16

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September 16

When you die, what will happen to the microbes that live on your body?

Suppose you die today. What will happen to your body when you die on a microscopic level? Will your microbes still use you as a food source until you return to the soil? Will they find a new host? How did your microbes get on your body in the first place? Did they get on your body when you chewed your first solid food or fed on your mother's milk? Do everybody have the same set of microbes in their gastrointestinal tracts? 71.79.234.132 (talk) 01:19, 16 September 2015 (UTC)

Answers in order:

1. Decomposition
2. Some will eat you, some will die.
3. Not likely, since they will be six feet below potential new hosts, though they might colonize any insects or worms that find their way to you.
4. We are always covered in microbes at all times. Initial colonization will occur at birth through contact with unclean people and objects.
5. See above.
6. No. People typically have very similar sets of microbes to one another, but there is substantial variation from person to person.

See Human microbiota for more information. Someguy1221 (talk) 01:24, 16 September 2015 (UTC)

Before burials and cremations were invented, did dead human bodies just lie on the ground to be eaten by the scavengers? If they lie there long enough, can the microbiota spread to other human beings in the tribe? 71.79.234.132 (talk) 01:35, 16 September 2015 (UTC)

Any contact with a microbe carries a chance of being colonized by that microbe. However, actually determining the inter-relatedness of of different individuals' microbiota has not been possible until recently with the development of genome sequencing and especially metagenomics. So while it's certainly possible to be colonized from the microbes in a cadaver, there is no way to know whether this was ever a common occurrence. If you take a group of modern people, however, you can collect genomic sequences of their microbiota and construct a phylogenetic tree that, combined with information about each individual's life history, may allow you to determine how and when individuals were colonized. Someguy1221 (talk) 01:47, 16 September 2015 (UTC)

Just a quick note: cremation as we know it today is far newer than burial. A similar effect is produced by burning a dead body on a funeral pyre, but that's a much more primitive process, and your microbiota would have a lot better chance of contact with a live body than in the (hopefully) more sterile environment of a cremation facility. Nyttend (talk) 02:22, 16 September 2015 (UTC)

Torture

When a person is tortured using a skull splitter (as famously used on Cavaradossi in Act 2 of Puccini's Tosca), what are the physiological effects on the victim? 2601:646:8E01:9089:D010:57E9:169C:D80B (talk) 02:53, 16 September 2015 (UTC)

Surely this would vary from victim to victim? Not familiar with the opera or the device (and a Google search for "skull splitter" finds basically nothing except the Orkney Skull Splitter brand of beer), but lots of other types of torture will have radically different effects on different people, so we should be able to expect the same here. Nyttend (talk) 03:33, 16 September 2015 (UTC)

The OP is asking specifically about physiological effects which I don't think would vary THAT widely. When you put someone on a rack, their joints dislocate, that's the physiological effect, which would be pretty much the same person to person. However like the above, I am not at all familiar with a "skull splitter" so not too sure exactly how it works or what it does, apart from presumably, splitting one's skull, which sounds considerably unpleasant enough. Vespine (talk) 03:43, 16 September 2015 (UTC)

Trepanning came to mind as soon as I read "skull splitter". This no-longer-accepted medical procedure had at least one effect with wide variation in the results: some patients survived, and others didn't. This is why I was guessing that Cavaradossi might not have physiological effects similar to everyone else subjected to the same device. Nyttend (talk) 03:49, 16 September 2015 (UTC)

Trepanning is a still used procedure. Rmhermen (talk) 21:37, 16 September 2015 (UTC)

[un-indent] FYI, the "skull-splitter" was an iron or steel ring (usually with 2 sets of spikes, one on each side) which was gradually tightened around the victim's skull, squeezing it. (The head crusher was similar, but applied pressure from the top.) 2601:646:8E01:9089:D010:57E9:169C:D80B (talk) 04:38, 16 September 2015 (UTC)

So, what question are you asking that your imagination can not answer? It sounds pretty straight forward. Vespine (talk) 22:58, 16 September 2015 (UTC)

For one thing, whether the pain would become unbearable BEFORE significant brain damage occurs, or the other way around. 2601:646:8E01:9089:917A:B8AA:82B4:50AB (talk) 04:37, 17 September 2015 (UTC)

Here is a rare video clip of a similar process. ←Baseball Bugs ^{What's up, Doc?} carrots→ 01:40, 17 September 2015 (UTC)

Is Sexual Repression real?

Are there serious scientific studies about sexual repression? The Wikipedia article by the same name is not completely developed, so there seems to be nothing on the science behind this phenomenon, and I'm seriously doubting it exists as a medical condition. I don't get it. What's the difference between repression and self-denial/altruism? Could it be that the latter is voluntary and desirable while the former is involuntary and undesirable? 71.79.234.132 (talk) 04:04, 16 September 2015 (UTC)

The Wikipedia article on sexual repression is mostly dealing with people being prohibited from expressing their sexuality by cultural or legal standards, which would of course be a sociological and not psychological phenomenon. Looking for scientific use of the phrase is prone to bring up a lot of research and history related to discredited 19th century theories on sexuality (female hysteria and things of the sort). From a modern scientific perspective, it is recognized that there exist psychological conditions that cause a person to lose interest in sex. Such a loss of interest, which you might describe as sexual repression, is a common symptom of depression [1]. Anxiety disorders can also cause the condition vaginismus, which causes sex to become extremely painful for the female partner, and can lead to a loss of sexual interest. Someguy1221 (talk) 04:28, 16 September 2015 (UTC)

Then, is it still called "repression" if one prohibits oneself from engaging in certain behaviors by cultural and legal standards and feels perfectly happy and satisfied that way? Or does repression suggest the suppression is instantly bad? 71.79.234.132 (talk) 04:54, 16 September 2015 (UTC)

To my knowledge, "sexual repression" always has a negative connotation. A person who simply has no interest in sex would be called asexual. This is distinct from someone who has interest in sex but chooses not to partake, and is satisfied with that decision, would simply be practicing abstinence. Someguy1221 (talk) 09:36, 16 September 2015 (UTC)

There are indeed many scholarly studies about sexual repression. As said above, it is commonly viewed through the lens of cultural and legal systems more than as a medical disorder, though there is also some work from a more psychological or social-psychological angle. Here's one about sexual repression in Maoist China [2], here's one about how sexual repression changes through generations [3]. Here's a paper that discusses how masturbation was culturally repressed and seen as not only as a "sin" [4], but was (incorrectly) blamed for many real medical illnesses. Here's a book chapter [5] about sexual repression in Sambia culture. Many more articles are available via google scholar. You can ask at WP:REX if you would like a full copy and cannot otherwise find one. SemanticMantis (talk) 14:32, 16 September 2015 (UTC)

Graduate responsibility

Why is it that graduates are increasingly being given more responsibility in the workplace straight out of uni. For example, I've heard of uni graduates being given multi million pound projects to manage etc. 2A02:C7D:B917:9700:D8F6:4A2D:F9A7:DE4E (talk) 17:31, 16 September 2015 (UTC)

The Ref Desk isn't likely to be able to answer this in any event (open-ended "why" questions are notoriously difficult to reference), but the first step is to establish whether your premise is valid. Are recent grads being assigned more large-budget projects to manage now than they were 10 or 20 years ago? Your "I've heard" isn't actually evidence that there's anything to even investigate with respect to the "why". — Lomn 19:08, 16 September 2015 (UTC)

I agree with the above answer this isn't really a science ref desk question. However I don't really see any reason to strongly doubt it. If a grad gets "given" a multi-million pound project to manage, maybe they were an exceptional student, they had work placement as part of their curriculum already, they have good mentors and supervisors. Does this happen more now than in the past? I don't see why not? In my field of IT, certainly there is a constant demand to do more for less, more is demanded from everyone each year, there is less time given to "train" people, new employees are expected to "come up to speed" sooner and with less resources. That's just the very nature of capitalism. I don't see why more would not also be expected of people straight out of uni. Vespine (talk) 00:12, 17 September 2015 (UTC)

The original post seems to be referring to the business world, so my personal experience may not apply; however, my impression of academia in the US is that it has become significantly harder, not easier, for young people to receive large grants. Dragons flight (talk) 10:18, 17 September 2015 (UTC)

See complex question for the Wikipedia article on the problem with the question as asked, and why no one can actually answer it. Questions based on a premise that itself has not been established (like "When did you stop beating your wife?") cannot be answered in any meaningful way. --Jayron32 23:40, 16 September 2015 (UTC)

Ok, but remember not every complex question is also a loaded question. The former is hard and tricky, the latter is basically acting in bad faith. "Have you stopped beating your wife?" is acting in bad faith in a way that this question is not... SemanticMantis (talk) 01:30, 17 September 2015 (UTC)

Who says they are? ←Baseball Bugs ^{What's up, Doc?} carrots→ 01:36, 17 September 2015 (UTC)

Terahertz astronomy for detecting nucleic acids near Enceladus?

If life exists in the oceans of Enceladus, it may have a shared origin with Earth and would then contain RNA. Is it possible with current technology to get a yes-or-no answer about trace RNA in the plume by beaming terahertz maser pulses at the plume and reading back the resulting reflection/fluorescence by some sort of submillimeter astronomy? Wnt (talk) 19:40, 16 September 2015 (UTC)

I don't know, but these people [6] seem to think the idea has promise, even going one better, claiming detection of life bits that don't share a common origin with terrestrial life.

“ We propose a terahertz (far-infrared) circular dichroism-based life-detection technology that may provide a universal and unequivocal spectroscopic signature of living systems regardless of their genesis. ”

See also the 35 papers that cite that one [7]. This [8] seems like a nice somewhat recent overview, though at a skim I don't see anything about astrobiology. SemanticMantis (talk) 20:32, 16 September 2015 (UTC)

Is Anti-persistence forecast skill statistically significant sometimes?

Since PF is basically saying that weather systems will stop moving forever eventually you should approach where there's been 1.0 crossings of the average line on average and this should work better: If it's warmer than average now, forecast colder than average, if it's colder than average, forecast warmer. This would probably have some meteorological skill as you've got some extra information by knowing how long the average time between zero crossings is. Enough to be statistically significant in some or all cases? (Like certain climates or seasons of climates? It would probably work better if you only make forecasts when it reaches a local minima or maxima of temperature sigma level that breaches a certain rarity (1-sigma?) (1.5-sigmas?)). For any climate shouldn't there be a range of days in the future where a contrarian forecast beats both "regression towards the mean" (climatology) and "it'll stay the same forever" (persistence)? Forecasting primers seem to jump straight from persistence to either a list of clues that's longer than "after x days, switch to anti-persistence", or "use a weather map", which requires an artifact like a smartphone, telegraph or satellite reports, or paper (or at least using one in the last few days). They don't take this simplest idea to it's logical conclusion and exhaust all simpler methods than remembering a bunch of patterns. Really logically after twice the average number of days between average line crossings persistence should be better than climatology again (though not as good as before), after 3 times as long anti-persistence should be better than climatology again, after 4 times as long the persistence forecast is best and so on but the number of days between actual crossings of the average line is so variable in many (all?) climates that I'm not sure if even persistence II's skill (two half cycles) would be statistically significant above climatology. Sagittarian Milky Way (talk) 23:28, 16 September 2015 (UTC)

(This seems really rambly and hard to follow; can you focus and clarify a bit? For this question - "For any climate shouldn't there be a range of days in the future where a contrarian forecast beats both "regression towards the mean" (climatology) and "it'll stay the same forever" (persistence)? "

-- sure, that's technically possible, but conventional research over the past half century or so has determined that it can't be reliably determined. Chaos theory, lyapunov exponents and all that. I think you might get much better answers if you spend a little while to make a more clear question :) SemanticMantis (talk) 01:23, 17 September 2015 (UTC)

I'm not really sure what you mean, but I think what you are getting at is: If it is warm today, does that make it more likely that it will be cold at some point in the future? In general, the answer is usually no. The most skillful forecasts are usually somewhere between "the weather stays the same" and "the weather returns to the mean", but predicting "the weather goes to the opposite condition" is generally not an improvement on any time scale. To give an analogy, imagine that each day you pick a random number between -1 and 1 and write it down. The weather might be imagined as something like the average of the picks over the last several days. Sometimes the seven day average will go high, and sometimes low, but on average it returns towards zero. However, since each random pick is independent of what came before, there is nothing that forces low numbers to automatically follow high. Hence there is no more skill in predicting that low totals follow high totals than in predicting that tails should follow heads when flipping a fair coin. Dragons flight (talk) 13:24, 17 September 2015 (UTC)

(edit conflict) Sorry readers. Okay, let's say Weather Station A recorded -5, 0, 7, 10, 12, 14, and 13 degrees above those days' normals the last few days. So yesterday was a local maximum. A persistence forecast might be that "it'll be 13 above normal tomorrow (and forever)". That's probably a more accurate forecast for tomorrow than climatology ("it'll be 0 degrees above average forever") but it'll quickly get less accurate. Say that over tens of thousands of days of measurements at Station A, it's 10 days on average between cold spell and cold spell or warm spell and warm spell. So theoretically a persistence forecast should be worse than climatology for days 3 to 7 after a warmth peak and you could correct that by saying it will colder than average on those days. Can this system survive the onslaught of variability in time between fronts long enough for this idea to work? Maybe only day 5 or days 4-6 could be shown to be statistically better than climatology? Depending on climate and season maybe? Or maybe the time between fronts is so variable that you couldn't show a greater accuracy for anti-persistence for any lookahead time at all? I don't really believe you could find anything 10 days in the future or something when supercomputers and satellites can barely do anything there, but theoretically 1000 days from now should be more likely to be the same side of average as today in places where it's exactly a 10 days cycle if cycle lengths form a bell curve, right? It should always be most likely to still be the same side of average when it's a multiple of twice the average time between fronts, as it's more likely for a random front to be followed by the opposite kind of front. After the OP I realized that you can't just try to boost the accuracy of the anti-persistence days by only predicting above or below average and still test it's accuracy against climatology, for obvious reasons. You'd need to pick a number to compare it to climatology ("exactly average forever"). Maybe fit a curve that blends into an average-looking temperature curve, maybe by eyeball, but you'd need a number.

This is not a practical method sure, just a mathematical curiosity, but I've just always thought that if you're going to talk about brain dead nothing needed methods you might as well say whether there's a way to improve it while still staying brain dead and needing nothing. You could probably do better just looking at the newspaper weather map and imagining everything going east @ 0.2 USAs/day. Though it might be useful if you had no forecasting knowledge or access to forecasts or barometers but knew the average time between fronts in the climate you're in. Crash landing in the wilderness maybe? Sagittarian Milky Way (talk) 14:38, 17 September 2015 (UTC)

But if what Dragons flight says is true then this is good for nothing. Sagittarian Milky Way (talk) 14:41, 17 September 2015 (UTC)

Is it really always like roulette numbers, though? Like the polar vortex can only reach this far south when it's wavy, so if it's cold like heck it's more likely to be milder in about a week and cold like heck again in about 2 weeks. Sagittarian Milky Way (talk) 14:55, 17 September 2015 (UTC)

Right, weather is not like roulette. A zeroth-order approximation is that the weather where you are tomorrow will be similar to the weather today. A better approximation looks at larger structures, jet streams, pressure fronts, etc. I don't think "mean time between fronts" is very useful or even well defined for most places. It looks like you're interested in rubrics and educated guesses, rather than full-blown meteorology, global circulation models, and thinks like that. You might be interested in this fascinating little document from the NOAA newsletter about weather folklore - it provides some insight as to how you can do better than forecasting by persistence or regression to the mean, and discusses why some of these things work. Similar info at Weather_lore#True_lore.2C_and_why. So, the answer to your title question is surely "yes", and that's why we have both scientific methods as well as folk wisdom that do more than just make persistent forecasts. SemanticMantis (talk) 16:24, 17 September 2015 (UTC)

Sure, if you look at the weather 1000 miles upwind, one can often predict what is coming; however, that's not what I understood the question to be asking. If one only looks at the weather where you are standing then there is generally no skill in predicting contrary weather to the other side of the mean. Let's consider a specific example, seasonally adjusted daily mean temperature anomalies in New London, Wisconsin, USA. They have a 100+ year record daily temperature time series and are far enough North to be affected by polar vortex fluctuations (since Sagittarian Milky Way mentioned that). Suppose we have a model that:

$T(t+k)\approx {\bar {T}}+\alpha _{k}T(t)$

Where $T(t)$ is the mean temperature anomaly at time t, ${\bar {T}}$ is the mean temperature, and $\alpha _{k}$ is a proportionality factor that we can estimate. If we use only seasonally adjusted temperature anomalies, then ${\bar {T}}$ is zero by definition of the anomalies. So now we have a simple linear system and we can estimate $\alpha _{k}$ for various values of k.

Taking data for New London, I get the following:

k (days)	$\alpha _{k}$
0	1
1	0.72
2	0.46
3	0.32
4	0.25
5	0.20
6	0.17
7	0.14
8	0.12
9	0.11
10	0.11
15	0.07
20	0.05
30	0.04
45	0.02
60	0.01

A skillful forecast that weather of the opposite type was coming, would imply an $\alpha _{k}<0$ for some time offset k, but that's not generally what one sees. For offsets of a few days, it is productive to assume that the weather then will look like the weather today. Beyond a few days, the mean is a better estimate, but $\alpha _{k}$ remains positive suggesting a slight influence of the present. At no point for lags of 60 days or less is $\alpha _{k}<0$, as would be needed to predict contrary temperatures. A similar conclusion can be reached by looking at time-lagged autocorrelations or models that look at multiple days. As long as one is simply talking about only using weather observations from a single location, there is generally no added skill in predicting contrary weather to the other side of the mean. Dragons flight (talk) 09:58, 18 September 2015 (UTC)

Interesting. Thanks a lot. I guess it not reaching 0 could be explained by various slow-changing variations like El Niño and the amount of polar vortex waviness itself varying like it did last winter. Now I'm curious, is what a table like this would look like something many meteorology students think of if they managed to avoid encountering it for a while? And then they would write some code to find out or ask someone if they knew or look it up somewhere? Or maybe it's in every meteorology textbook? Sagittarian Milky Way (talk) 22:40, 18 September 2015 (UTC)