needed to create some content types that have a field that creates a vote, as a poll. Have you tested the modules and Advanced Poll Pollfield but as yet there is not a production version-these contain some errors.  Someone has a solution in order to implement content types with polls?
I need a poll inside my content types.  Sometimes the users create an article and like to create a poll directly into the node they created. They don't want to create an extra poll with no connection to the original article.  So how can I get the poll functionality inside a different content type?
We found this skull on a beach in southwestern Sweden, and are curious as to what kind of animal it was. I know that the -f means --fix-broken from the manual and that it attempts to fix problems with the packages, but what exactly does? How it decides how to fix the packages or if they need fixing and the method of fixing? And why sometimes it fails? I would like to take control of my app on an iOS device (mostly an iPhone) from my MacBook Pro or Windows, doesn't matter which one.  I know that it can be accomplished via Veency, and that's exactly what I need - but I do NOT want to jailbreak my iPhone.  Is there a similar legal alternative?  If not - is it something I could develop perhaps, or will I run into some SDK limitations for such a thing? Nonlinear regression model linear in some parameters In a set of  that I stumbled upon online, the author discusses a nonlinear regression model, which is linear in some parameters, like this $$ y = \theta_1 + \theta_2\exp \left( {\theta_3x} \right) + \varepsilon $$ and suggests to first perform a nonlinear regression to estimate $\theta_3$, and then use OLS to estimate the other two parameters. I am not very experienced in regression modeling, so please forgive me if I ask a very simple question, but I don't understand how you can do this consistently without also estimating the other 2 parameters? Apparently, there is some trick involved, which I don't understand...  Another question is what happens to the ability to do inferences based on parameter estimates to the complete model if you do the regression in two stages like that?  Many thanks! About $\lim \left(1+\frac {x}{n}\right)^n$ I was wondering if it is possible to get a link to a rigorous proof that  $$\displaystyle \lim_{n\to\infty} \left(1+\frac {x}{n}\right)^n=\exp x$$ OpenSSL remains vulnerable after update to 14.04 Possible Duplicate:          I am a little bit confused about asking a question:     Can you please tell me my next work?   or     Could you please tell me my next work?   Which is more correct? How can I install an app given only its APK file? Usage of :- (colon dash) in bash I'm using an HP laptop running Windows 7 Home Edition.  The moment I reach the login screen the computer automatically types "ppppppppp" in the password place, luckily I have fingerprint login to counter that.  The moment I login, it keeps acting as if I'm typing 'p' repeatedly. I tried removing the button and cleaning under it but it was no use. I've tried restarting, uninstalling the keyboard driver, but it was no use.  I can't go to Control Panel because the moment I get there, it starts typing "pppppp" in the search field and I'm unable to find anything.  I'm typing this from my phone because going anywhere on my laptop seems impossible. I have been reading Geoff Cumming's 2008 paper  [~200 citations in Google Scholar] -- and  am confused by one of its central claims. This is one in the series of papers where Cumming argues against $p$-values and in favour of confidence intervals; my question, however, is not about this debate and only concerns one specific claim about $p$-values.   Let me quote from the abstract:     This article shows that, if an initial   experiment results in two-tailed $p= .05$, there is an $80\%$   chance the one-tailed $p$-value from a replication will fall in   the interval $(.00008, .44)$, a $10\%$ chance that $p &lt; .00008$,   and fully a $10\%$ chance that $p &gt; .44$. Remarkably, the   interval—termed a $p$ interval—is this wide however large   the sample size.   Cumming claims that this "$p$ interval", and in fact the whole distribution of $p$-values that one would obtain when replicating the original experiment (with the same fixed sample size), depend only on the original $p$-value $p_\mathrm{obt}$ and do not depend on the true effect size, power, sample size, or anything else:     [...] the probability distribution of $p$ can be derived without   knowing or assuming a value for $\delta$ (or power). [...] We do not assume any prior knowledge   about $\delta$, and we use only the information $M_\mathrm{diff}$ [observed between-group difference] gives about $\delta$ as   the basis for the calculation for a given $p_\mathrm{obt}$ of the distribution of   $p$ and of $p$ intervals.      $\quad\quad\quad$    I am confused by this because to me it seems that the distribution of $p$-values strongly depends on power, whereas the original $p_\mathrm{obt}$ on its own does not give any information about it. It might be that the true effect size is $\delta=0$ and then the distribution is uniform; or maybe the true effect size is huge and then we should expect mostly very small $p$-values. Of course one can start with assuming some prior over possible effect sizes and integrate over it, but Cumming seems to claim that this is not what he is doing.  Question: What exactly is going on here?    Note that this topic is related to this question:  with an excellent answer by @whuber. Cumming has a paper on this topic to:  -- but that one is clear and unproblematic.  I also note that Cumming's claim is repeated several times in the 2015 Nature Methods paper  that some of you might have come across (it already has ~100 citations in Google Scholar):     [...] there will be substantial variation in the $P$ value of repeated experiments. In reality, experiments are rarely repeated; we do not know how different the next $P$ might be. But it is likely that it could be very different. For example, regardless of the statistical power of an experiment, if a single replicate returns a $P$ value of $0.05$, there is an $80\%$ chance that a repeat experiment would return a $P$ value between $0$ and $0.44$ (and a $20\%$ change [sic] that $P$ would be even larger).   (Note, by the way, how, irrespective of whether Cumming's statement is correct or not, Nature Methods paper quotes it inaccurately: according to Cumming, it's only $10\%$ probability above $0.44$. And yes, the paper does say "20% change". Pfff.) What is the meaning of this "let there be light" joke? Is it supposed to be a HTML or an HTML VS10 debugger error: Test host process exited unexpectedly Evaluate $\lim_{x\rightarrow 0} \frac{\sin (6x)}{\sin(2x)}$ without L'Hopital Animating Dynamic Paint with noise texture How do I get breading to stick to pre-cooked chicken for pan frying? How to make a field NULL using MySQL GUI Tools? I'm using the MySQL Query Browser (part of the ) and need to change a field to NULL, but I can't figure out how to do it - if I delete the value it tries to update it to ''. Typing "NULL" makes it try to update to 'NULL' (a string).  I know I could just write a query to do it, but that defeats the entire purpose of the tool, no? Sarrus Rule with LaTeX Is there a way to create a new command with 9 arguments ({a_{11}},{a_{12}},{a_{13}},{a_{21}},{a_{22}},{a_{23}},{a_{31}},{a_{32}},{a_{33}}) that has as output a matrix with the Sarrus Rule? For instance: to obtain     just use the command that we will call sarrus:  \sarrus{-k}{k-1}{1}{0}{k-1}{k}{2}{0}{1}.   If it is possible i want to use the command sarrus in math mode just like matrix for istance. I would like to use Flash Player to show web contents but since today (12 Jan 2021) Adobe is blocking it. Is there a way to use it? I've tried Firefox, Chrome, Safari and Brave browsers.