I accidentally changed ownership of sudo to current administrative user
Set myself as owner of /etc with chown command now getting all kinds of errors
I've looked at the resumes of the type of candidates that get into computer science PhD programs at the top few universities (e.g. Stanford, MIT etc.) and a lot of them seem to have multiple publications (2-4) done during their undergraduate years. Is this representative of the entire pool? Or is this just a self-selected group that puts their resumes online.  I currently have one first-author workshop paper (5 pages), and I wonder how this might affect my chances at entry into these top universities. Say, I'm given a filename like libasound.so.2. Is there a way to query the package manager to correlate the filename with its corresponding package?  I'm interested to get answers for any package manager, but my primary focus is on apt and yum. To quantize a scalar field theory with the action:  $$S=\int \mathrm d^Dx\mathscr{L}(\phi,\partial_\mu\phi)=\int \mathrm dx^0L(\phi,\partial_0\phi)$$  we promote $\phi(\vec{x})$ and $\pi=\frac{\delta L}{\delta(\partial_0\phi)}=\pi(\vec{x})$ to be field operator at fixed time $x^0$ (with the canonical commutation relation $[\phi(\vec{x}),\pi(\vec{y})]=\delta^{D-1}(\vec{x}-\vec{y})$), then we use the classical equation of motion to find $\phi$ and $\pi$ at all time.  What principles lie behind this? Why can we assume that the field operators satisfy the classical equation of motion?    By example if we have a classical theory with $S=\int \,\mathrm dtL(\phi,\partial_t\phi)$, momentum $\pi=\frac{\delta L}{\delta(\partial_t\phi)}$ hamiltonian $H=\pi\phi-L$, the classical equation of motion is:  $$\frac{\mathrm d\phi}{\mathrm dt}=\frac{\delta L}{\delta(\partial_t\phi)}$$  When we do the canonical quantization, we promote $[\phi,\pi]=\delta(\vec{x}-\vec{y})$ and the equation of motion for $\phi$ is $$\frac{\mathrm d\phi}{\mathrm dt}=i[H,\phi]$$  Why should $i[H,\phi]$ has the same form as $\frac{\delta L}{\delta(\partial_t\phi)}$? This fact comes from where? I would like AUCTeX (that is, Emacs with auctex loaded) to suggest more LaTeX macros when using completion (M-Tab or C-Ret) than it does by default. I would like to have macros from packages I have downloaded on CTAN and macros I have written. I would also like it if it would complete \section or other macros that can be accessed via C-c C-s, C-c C-e etc.  Solution: I could not make the code quoted by  work. i get an error on loading emacs but did not looked much further in because I ca bear the nuisance of appending a few lines to my files.  The link given by Ben ( contains a working solution, thus I accept his answer. I had come across this page in my researchs but somehow messed up things. What eventually worked for me was using TeX-auto-generate TEX AUTO to create a bunch of .el files in the ~/.emacs.d/auctex/auto direcoty. Note that this directory must be created beforhand. For some reasons TeX-macro-private did not achieve the wanted result. Case insensitive regular expression without re.compile? I want to show that $$\log N&lt;\sum_{n=1}^{N}\frac{1}{n}&lt;1+\log N.$$ But I don't know how to show this. Chat gives me really, really specific time gap notifications My question is related to my previous asked one:   I have about 300 shapekeys and want to set the random value for all of them . How to do it using scripting? Voting to Close after Accidentally Voting to Leave Open When reviewing on SO, I accidentally pushed the "Leave Open" button on a post that clearly should've been closed. I pushed the back button and saw that in the review panel my vote to keep open had been locked and it said:     PhpMyCoder voted to leave open 1 minute ago   So I clicked on the question heading to go to its page and I clicked the close link on the question page and voted to close for the relevant reason. However, when I returned to the review page (and did a hard refresh) it still said:     PhpMyCoder voted to leave open 2 minutes ago   Is it possible to vote to leave open and vote to close at the same time? I assume not. In which case, I'd say this is a bug because it should've updated to say:     OtherUser and PhpMyCoder voted to close 2 minutes ago I have the formula $x! + y! = z!$ and I'm looking for positive integers that make it true. Upon  inspection it seems that x = y = 1 and z = 2 is the only solution. The problem is how to show it.   From the definition of the factorial function we know $x! = x(x-1)(x-2)...(2)(1)$  So we can do something like this:  $$ [x(x-1)(x-2)...(2)(1)] + [y(y-1)(y-2)...(2)(1)] = [z(z-1)(z-2)...(2)(1)]$$   we can then factor all of the common terms out on the LHS.  $$ [...(2)(1)][x(x-1)(x-2)... + y(y-1)(y-2)...] = [z(z-1)(z-2)...(2)(1)]$$ and divide the common terms out of the right hand side  $$[x(x-1)(x-2)...] + [y(y-1)(y-2)...] = [z(z-1)(z-2)...]$$  I'm stuck on how to proceed and how to make a clearer argument that there is only the one solution (if indeed there is only the one solution).   If anybody can provide a hint as to how to proceed I would appreciate it. Uk visa refused as self employed Why can't energy be created or destroyed? How exactly does a "random effects model" in econometrics relate to mixed models outside of econometrics? I used to think that "random effects model" in econometrics corresponds to a "mixed model with random intercept" outside of econometrics, but now I am not sure. Does it?  Econometrics uses terms like "fixed effects" and "random effects" somewhat differently from the literature on mixed models, and this causes a notorious confusion. Let us consider a simple situation where $y$ linearly depends on $x$ but with a different intercept in different groups of measurements:  $$y_{it} = \beta x_{it} + u_i + \epsilon_{it}.$$  Here each unit/group $i$ is observed at different timepoints $t$. Econometricians call it "panel data".    In mixed models terminology, we can treat $u_i$ as  a fixed effect or as a random effect (in this case, it's random intercept). Treating it as fixed means fitting $\hat \beta$ and $\hat u_i$ to minimize squared error (i.e. running OLS regression with dummy group variables). Treating it as random means that we additionally assume that $u_i\sim\mathcal N(u_0,\sigma^2_u)$ and use maximum likelihood to fit $u_0$ and $\sigma^2_u$ instead of fitting each $u_i$ on its own. This leads to the "partial pooling" effect, where the estimates $\hat u_i$ get shrunk toward their mean $\hat u_0$.  R formula when treating group as fixed:    y ~ x + group R formula when treating group as random:   y ~ x + (1|group)  In econometrics terminology, we can treat this whole model as a fixed effects model or as a random effects model. The first option is equivalent to the fixed effect above (but econometrics has its own way of estimating $\beta$ in this case, called "within" estimator). I used to think that the second option is equivalent to the random effect above; e.g. @JiebiaoWang in his highly upvoted answer to  says that      In econometrics, the random-effects model may only refer to random intercept model as in biostatistics    Okay --- let us test if this understanding is correct. Here is some random data generated by @ChristophHanck in his answer to  (I put  for those who do not use R):    @Christoph does two fits using econometrics approaches:    fe &lt;- plm(stackY~stackX, data = paneldata, model = "within") re &lt;- plm(stackY~stackX, data = paneldata, model = "random")   The first one yields the estimate of beta equal to -1.0451, the second one 0.77031 (yes, positive!). I tried to reproduce it with lm and lmer:  l1 = lm(stackY ~ stackX + as.factor(unit), data = paneldata) l2 = lmer(stackY ~ stackX + (1|as.factor(unit)), data = paneldata)   The first one yields -1.045 in perfect agreement with the within estimator above. Cool. But the second yields -1.026, which is miles away from the random effects estimator. Heh? What is going on? In fact, what is  plm even doing, when called with model = "random"?  Whatever it is doing, can one somehow understand it via the mixed models perspective?  And what is the intuition behind whatever it is doing? I read in a couple of econometrics places that random effects estimator is a weighted average between the fixed effects estimator and the "between" estimator which is more or less regression slope if we do not include group identity in the model at all (this estimate is strongly positive in this case, around 4.) E.g. @Andy :     The random effects estimator then uses a matrix weighted average of the within and between variation of your data. [...] This makes random effects more efficient[.]   Why? Why would we want this weighted average? And in particular, why would we want it instead of running a mixed model? How many keys does the Playfair Cipher have? How prove $p!|(a+1)$ if $p!|a^p+1$ Incompatible Software for next OSX? I understand the move past Snow Leopard meant losing Rosetta, and compatibility with any PPC apps.   Since there are some apps that can't be replaced (for example, old years of TurboTax that I might need to reference) I have a drive to boot Snow Leopard, and one for Yosemite. I was considering the jump to El Capitan, when I saw the question  which got me wondering the question -     Before installing a next generation OS, is there any way to find, in   advance, which apps I have that would be orphaned by the move?   Edit, the answer below from Jean Valjean was what I needed. One app concerning me appeared as follows:    It might be tedious to search many apps, but at least this gives me a chance to view the top ones that will cause me grief. The rules for the monk ability Tongue of the Sun and Moon state:     Starting at 13th level, you learn to touch the ki of other minds so that you understand all spoken languages. Moreover, any creature that can understand a language can understand what you say.   PHB, pp.79   The text says that this ability is something you learn to do, not something that simply happens to you, so it's not necessarily always on. Further, it seems logical to say that this is something you would do actively. That is, you could choose not to touch someone's mind, thereby excluding them from understanding you. You could also choose not to understand someone yourself, just in case they're telling , or using a subliminal trigger.  Assuming you can choose not to touch someone's mind, let's reason further. Suppose you're speaking and don't know that there is someone listening in nearby. Would they understand you, i.e. is the default that you are or aren't touching someone's mind? Similarly, if you are speaking to a large group of people, would you have to focus on all of them at once for them to understand you? Would this take effort? Is there a range?  My questions are:   Can you exclude some characters from understanding you while allowing others to do so? Can you decide not to understand someone who is speaking?   Basically, these boil down to: Can you choose not to touch someone's mind?  Then, assuming that the answer to the above is yes:   Do you have to know someone is listening in order for them to understand you? Is there a limit to the number of people you can affect? A range? Where is .bashrc? I am currently writing an essay on artificial moral agents, and I need to explain the difference between ethics and morals. However, I am finding it really hard to find a good book or research paper which contains a citable definition.   Could someone point me in the right direction? Prove that the normalisation of $A=k[X,Y]/(Y^2-X^2-X^3)$ is $k[t]$ where $t=Y/X$ (Reid, Exercise 4.5) This is a problem about finding the normalisation of a quotient polynomial ring. So I have to find the integral closure of the ring in its field of fractions. The problem statement is as follows:     Let $A=k[X,Y]/(Y^2-X^2-X^3)$. Prove that the normalisation of $A$ is $k[t]$ where $t=Y/X$.   Can I do this by showing that the field of fractions $\text{Frac} A$ of $A$ is equal to $k[t]$, and subsequently showing that the field of fractions is normal? (This could be done by showing that $k[t]$ is a UFD?)  I am lost at calculating/determining $\text{Frac}A$, or similarly proving that $k[t]=\text{Frac}A$. Also, how do I show that it is normal?  I hope you can help!