If $G_1,\cdots,G_n,\cdots$ are metrizable topological groups, then $G= \prod_{n\in \mathbb N} G_n$ is also a topological group.
Is the topological product $\Pi \{G_\alpha: \alpha < \kappa\} $ a topological group?
I connected an external screen to my laptop, but my desktop didn't automagically extend to it, as it used to do about a year ago (older version of Ubuntu).  I went to the display settings. The screen was listed there (correct resolution, brand name, etc.). But when i put the switch on 'on' and click 'apply', i get this error:   Failed to apply configuration: %s  GDBus.Error:org.freedesktop.DBus.Error.UnknownMethod: No such interface `org.gnome.SettingsDaemon.XRANDR_2' on object at path /org/gnome/SettingsDaemon/XRANDR   It's been like this for a few months now, but i'd really like to be able to use an external screen/beamer again.  Any ideas?  Thanks. I took some shots recently and I noticed that I'm getting a lot of little black dots in my images.  I cleaned my lens thoroughly with the Nikon camelhair brush and retook the pictures but once again, the dots appear.  I'm shooting with a Nikon D7000 and using a starter lens. I've attached an example (notice the black spots on the chairs, on the ceiling, etc). Interesting tab on StackOverflow One day I directed to SO and was met with the awesome Interesting page, which I really like. But when I travel away from it, I have to re-enter the query string to get it back. Is there a plan to make this tab visible so I can click to it anytime? I have recently installed Ubuntu 14.04 LTS on my laptop Sony Vaio VPCEA16FG. I have been getting system freezes (everything including display, mouse, keyboard stops working and I have to do a restart with the power switch) and there are random popups of "System program problem Detected"  On startup my screen is all splashed with black and white pixels and a System program problem detected message.  My video card info:    01:00.0 VGA compatible controller: Advanced Micro Devices, Inc. [AMD/ATI] Madison [Mobility Radeon HD 5650/5750 / 6530M/6550M Dilemma: Present Perfect Or Perfect Continuous? Instantiate TinyMCE via JS ( rather than PHP/wp_editor ) Star rating in AJAX with Ruby On Rails Holomorphic function has at most countably zeros I just installed the lastest version of . I works fine but in order to use it, I have to enter the following in the terminal: cd ugene-1.11.5/ then execute ./ugene -ui to launch UGENE GUI.   This takes too long. I would like to build a .desktop file for UGENE to be used in Ubuntu 12.04 so that I can simply open it from the unity launcher.  Not sure if this is helpful but the website says: By default ugene script launches the command-line version of UGENE.  Here's what I have (not sure if it's right):  [Desktop Entry] Version=1.0 Name=my Unipro UGENE GenericName=Integrated Bioinformatics Suite Comment=Unipro UGENE is a cross-platform visual environment for DNA and protein sequence analysis. MimeType=text/english;text/plain;text/x-makefile;text/x-c++hdr;text/x-c++src;text/x-chdr;text/x-csrc;text/x-java;text/x-moc;text/x-pascal;text/x-tcl;text/x-tex;application/x-shellscript;text/x-c;text/x-c++; Exec=/home/samuel/ugene-1.11.5 ./ugene -ui -c %F Icon=/usr/share/icons/hicolor/scalable/apps/ugene.svg Type=Application Terminal=true Categories=Utility;Development; StartupWMClass=UGENE   I added the launcher named my Unipro UGENE to my unity bar and tried opening it but it doesn't appear. I must be missing something. I don't know what the StartWMCClass field is suppose to be nor do I know whether I entered the correct MimeType. Prove that the average of iid Gaussian random variables is Gaussian Given $x_1, \ldots, x_N$, independent and all distributed as a   Gaussian with mean $\mu$ and variance $\sigma^2$. Then, the average   $$\bar{x} = \frac{1}{N}\sum_{i=1}^Nx_i$$ is distributed as a Gaussian   with mean $\mu$ and variance $\frac{\sigma^2}{N}.$   This is a very well-known result. Anyway, I'm looking around to find a proof for this and I'm not having luck. transpose columns to rows I'm trying to find an anime movie I watched when I was younger; I believe I first watched it in 90/91. The story revolved around the recruitment and training of a group that would pilot a mecha that was similar to Voltron in that each pilot controlled a portion of the mecha that would merge into a bigger mecha. Points that I remember:   Started on Earth Program was government funded One of the pilots was related to the creator of the program, I think a female Mecha had chain weapon and a sword that was summoned from it's superhero-like chest icon. Killing blow was an m or w shape Ended with father/creator of mecha? being kidnapped by the aliens and used as human shield to deter attack on alien vessel How to show hidden files in Nautilus 3.20.3 Ubuntu 16.10? How to show hidden files in Nautilus 3.20.3 Ubuntu 16.10? vertical alignment of a turned cell I know using turn command and a sample code like this:  \usepackage{rotating}  \begin{turn}{90} Supervised Learning \end{turn}}   we can rotate a text inside a cell, however, I couldn't find a way to vertically center this rotated text. Any suggestions is appreciated.  Here is the sample MWE:  \begin{table}[]     \centering     \begin{tabular}{|&gt;{\centering\arraybackslash}m{0.5cm}|c|&gt;{\centering\arraybackslash}m{8cm}|}         \hline         \multicolumn{2}{|c|}{Classification} &amp; References \\ \hline         %\multirow{2}{*}{{\begin{turn}{90}Supervised Learning\end{turn}}}            \multirow{2}{*}{\rotatebox[origin=c]{90}{Supervised Learning}}  \end{tabular}     \caption{A Classification}     \label{tab:Machine_Learning_models} \end{table} NIST randomness test p values I have a binary sequence of length $2^{20}$. I am using the NIST statistical test, assess.   What should be taken for ./assess and  How many bitstreams? in this test? In the final Analysis report, what p-values should be there to pass this test? How to write a unit-test / test class for trigger? How do I write a unit-test / test class for a trigger?  What are my options?   Inline with the trigger?  New Class? Regression Proof that the point of averages (x,y) lies on the estimated regression line How do you show that the point of averages (x,y) lies on the estimated regression line? Can I play a save from the non-GOTY edition of Red Dead Redemption in the GOTY edition? My friend is able to lend me Red Dead Redemption. However it's the vanilla edition, so I'm going to end up buying the GOTY edition anyway. Here is a question now: If I were to play Red Dead Redemption, non-GOTY edition, have a save from it, and then buy the GOTY edition, will I be able to play on the save I made while playing the non-GOTY edition? Random forest regression not predicting higher than training data I've noticed that when building random forest regression models, at least in R, the predicted value never exceeds the maximum value of the target variable seen in the training data. As an example, see the code below. I'm building a regression model to predict mpg based on the mtcars data. I build OLS and random forest models, and use them to predict mpg for a hypothetical car that should have very good fuel economy. The OLS predicts a high mpg, as expected, but random forest does not. I've noticed this in more complex models too. Why is this?   &gt; library(datasets) &gt; library(randomForest) &gt;  &gt; data(mtcars) &gt; max(mtcars$mpg) [1] 33.9 &gt;  &gt; set.seed(2) &gt; fit1 &lt;- lm(mpg~., data=mtcars) #OLS fit &gt; fit2 &lt;- randomForest(mpg~., data=mtcars) #random forest fit &gt;  &gt; #Hypothetical car that should have very high mpg &gt; hypCar &lt;- data.frame(cyl=4, disp=50, hp=40, drat=5.5, wt=1, qsec=24, vs=1, am=1, gear=4, carb=1) &gt;  &gt; predict(fit1, hypCar) #OLS predicts higher mpg than max(mtcars$mpg)       1  37.2441  &gt; predict(fit2, hypCar) #RF does not predict higher mpg than max(mtcars$mpg)        1  30.78899 CentOS 7 DVD ISO vs Everything ISO different