Learning JavaScript and doing some questions. I am trying to reverse a given string and I don't know why my logic is wrong as running through the debugger it looks like it's doing the swapping as intended.  Any help is really appreciated, I know it's simple but that means I'm missing something important.     function reverse(s) {   let i = 0;   let j = s.length - 1;    while (i &lt; j) {     let temp = s[j];     s[j] = s[i];     s[i] = temp;     i++;     j--;   }   return s; }  console.log(reverse("hello"));
Does javascript use immutable or mutable strings? Do I need a "string builder"?
Simplify result of $\int_0^{\infty} \frac{1}{1+x^n}dx$ It is quite easy to show that (by using residue theorem) $$\int_0^{\infty} \frac{1}{1+x^n}dx = \frac{2 \pi i^{1+2/n}}{n(e^{2 \pi i / n} - 1)} $$ for $$n \ge 2$$  Is there any possibility to simplify $$\frac{2 \pi i^{1+2/n}}{n(e^{2 \pi i / n} - 1)}$$ or it is best result?  Thanks in advance! Which word to use when we ask for help?  Some conditions:     We know that the person asked is able to do it. We don't know if the person asked is able to do it. The  contains a link to the new code of conduct,  . As of 2018-08-07T05:27:38+00, . Also, I cannot find any other link to the conduct yet, neither in the help center, nor in the site navigation, which is a bummer, given that we're invited to read the new CoC:     Really, please, take a moment to read the new Code of Conduct now. It’s not long, it’s not wordy-and-legalese-y and in our long held tradition, we feel that it does a good job of assuming that the vast majority of folks that use our sites always have the best intentions at heart.    Is the code of conduct not yet published?  Edit: As mentioned in the comments,  announces the conduct and links to , so maybe it's not public yet? How did the ending happen from Neil's perspective? I am trying to figure out the scene near the finale of Tenet where Neil unlocks the door and gets shot in the face. I can't really see the flow where he opens and holds the door and the protagonist walks in and fights the bad guy. Can you tell the series of events as Neil sees them happen till he gets shot? UPDATE If I am not wrong, I see it like this: Neil was running down towards the door, both the protagonist and his mate are inside with the door locked fighting the bad guy, then, he unlocks the door and walks in and stands behind the door. The protagonist's mate comes out of the room, then the protagonist, then he closes the room, then he look back to get shot in the face. But this doesn't make sense, if he wanted to unlock the door when he was running down, they were already in fighting the bad guy!!!!! I'm downloading GTA V. After 20gb / 100gb I paused my download for restarting my pc. Then download restarts from 0%.  Why this could happen? Can I restart my PC during downloads without losing progress? We work heavily with serialization and having to specify Serializable tag on every object we use is kind of a burden. Especially when it's a 3rd-party class that we can't really change.  The question is: since Serializable is an empty interface and Java provides robust serialization once you add  implements Serializable - why didn't they make everything serializable and that's it?    What am I missing? $ KC $ spaces imply $ US $ spaces , but vise versa is false. In the $ US $ space , each convergent sequence has unique limit.      In the $ KC $ space , every compact subset is closed.      It easy to show that $ KC $ spaces imply $ US $ spaces.   The example below show that $ US $ spaces do not imply $ KC $ spaces.      Let $ X = [ 0, 1 ] $ with the the usual topology and attach  a new point z whose neighborhood are open dense subsets of $ [ 0,1 ]$. Observe $ [ 0,1 ]$ is a compact non-closed  of $X$ and then $X$ is not a $KC$ space. However no sequence in $ [ 0,1 ]$ converge to $z$ and in particular  all convergent in $X$ have unique limits.   can you give me more details?   Why $X$ is not closed? Why no sequence in $ [ 0,1 ]$ converges to $z$ and in particular all convergent sequences in $X$ have unique limits ? Does there exist a matrix $\mathbf{A}\in\mathbb{R}^{3\times3}$ such that $\mathbf{A}^{2}=-\mathbf{I}$? Is it possible for a matrix $\mathbf{A}\in\mathbb{R}^{3\times3}$,  $$\mathbf{A}^2=-\mathbf{I}$$  I know that It is possible for $2\times2$ matrix, but is it possible for $3\times3$ matrix ? Disable two column mode for separate part I am writing a document using the report class in two column mode, but I need a \section to spread across both columns, but how can I set that?  Something like  \documentclass[10pt,danish,a4paper,twoside,twocolumn]{report} \input{preamble.tex} \begin{document}  % This section should spread over both columns \section{Name}  \lipsum[1-3] \end{document} Holomorphic functions: is it true that $f(\bar{z})=\overline {f(z)}$? 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? One or more of the following things happened to me on a Stack Exchange site:   My post(s) were wrongly deleted or locked by a moderator A moderator posted a wrong comment on one of my posts I was suspended, but did not do anything wrong I asked a meta question, but the question was closed and/or deleted A moderator discredited me in public ...   I think a moderator has abused their power, but I feel powerless against them.  What recourse do I have now? What can I do when I feel that a moderator has abused their power, and has been repeatedly unfair in their dealings with me? In iOS 7, when the phone is in Sleep mode and I receive a call, I don't see the "Decline" button. All I see is a green "Answer..." button that requires me to slide to the right to answer the call. Is there anyway we can change that? I know that there are buttons for "Remind Me Later, etc" but I want the "Decline" button.   It works fine when the phone is not in Sleep mode. How to do one-class text classification? I have to deal with a text classification problem. A web crawler crawls webpages of a certain domain and for each webpage I want to find out whether it belongs to only one specific class or not. That is, if I call this class Positive, each crawled webpage belongs either to class Positive or to class Non-Positive.  I already have a large training set of webpages for class Positive. But how to create a training set for class Non-Positive which is as representative as possible? I mean, I could basically use each and everything for that class. Can I just collect some arbitrary pages that definitely do not belong to class Positive? I'm sure the performance of a text classification algorithm (I prefer to make use of a Naive Bayes algorithm) highly depends on which webpages I choose for class Non-Positive.  So what shall I do? Can somebody please give me an advice? Thank you very much! Formula for calculating $\sum_{n=0}^{m}nr^n$ I want to know the general formula for $\sum_{n=0}^{m}nr^n$ for some constant r and how it is derived.  For example, when r = 2, the formula is given by: $\sum_{n=0}^{m}n2^n = 2(m2^m - 2^m +1)$ according to   Thanks! Why are there humans in the Star Wars Universe? I think the term "back and forth" gets thrown around a lot without much thought.  From Dictionary.com:         [fawrth, fohrth]      adverb    1.  onward or outward in place or space; forward: to come forth; go forth.   Wouldn't the term be more meaningful if "forth" was used first since you have to have a starting place before you can go "back"?  Examples:        I've been going back and forth from Houston to New York.   I've been going forth and back from Houston to New York.      Which is more correct? Real-life examples of common distributions Can a probability distribution value exceeding 1 be OK? How do I pipe terminal standard output (stdout) to the clipboard? For example,   Say I want to list the contents of a folder and directly paste them into a chat window for a friend to see.    I realize I could do ls &gt; filename.txt to create a file (filename.txt) with those contents; I'd then have to open or print the file and manually select and copy the text block (which can be annoying/tedious.)  I clearly could also select and copy the output of ls directly from within the terminal window.  It would be much faster/easier to simply pipe standard output to the clipboard.  What terminal command allows me to do this?