How do I fix my package state after the installation process (dpkg) was interrupted?
E: dpkg was interrupted... run 'sudo dpkg --configure -a'
How to evaluate potential advisers on grounds other than their research/publications? I need to upload my signature in a PDF document, but I do not know how to edit the background of this image.   I wish to remove the bluish-tint background, and make it pure white.   Can anyone help me with this, please? Refused UK Visit visa for lack of sufficient funds - What more can I do? If $M^n$ is a compact topological manifold (not necessarily with additional structure), is there an upper bound on the number of charts needed to cover $M$ ? Does this bound depend on the dimension of $M$ ?  Thanks in advance...  Cheers "May I have a glass of water" vs. "Can I have a glass of water": which is better, "may I" or "can I", when asking for something? What is the correct sentence when asking for something like while flying asking for a glass of water :     May I have a glass of water     or      Can I have a glass of water Why no file-name in Inode information? I know that symlinks have a separated inode from the original file and that they only point for the inode containing the data. My question is, where is the hardlink name stored if there's no field in the inode structure refering to "name". I know that this could be a a relatively easy question, but as all hardlinks have the same inode number i assume that no inode is created when creating a hard link. We already had multiple questions about unbalanced data when using , , ,  and a number of other similar questions, what makes it a very popular topic! Unfortunately, each of the questions seems to be algorithm-specific and I didn't find any general guidelines for dealing with unbalanced data.  Quoting , dealing with unbalanced data     (...) heavily depends on the learning method. Most general purpose   approaches have one (or several) ways to deal with this.   But when exactly should we worry about unbalanced data? Which algorithms are mostly affected by it and which are able to deal with it? Which algorithms would need us to balance the data? I am aware that discussing each of the algorithms would be impossible on Q&amp;A site like this, I am rather looking for a general guidelines on when it could be a problem. I'm going thru a phone swap, and I now realize that I have multiple ID's   "codename" "codename@example.com" "realname@example.com"   I've tested all three, and they all have different login passwords. Not sure how I got here but I'd like to clean the mess up.  Is there any way to delete / remove / erase unwanted ID's so they don't exist anymore?  (Note: their existence creates total havoc with any type of ID edit...)  I see from  that I can't merge the apple ID's, but can I simply delete the unwanted ID's? Reconfiguring TexStudio after upgrade to OS X El Capitan Texstudio doesn't work for me anymore after updating to Mac OS X 10.11 El Capitan. I have the latest version of TexStudio installed (2.10.2). As pointed out by , this is due to a change in the places OS X allows files to be saved. When I started TexStudio, I received a message "PDFLatex could not be launched". In the settings, I had to change the folder of the compiler from user/texbin/ to /Library/Tex/texbin, as shown in the screenshot below:    Can anybody tell me if I have to make further changes in order to make TexStudio fully working (bibliography and the like), and if yes, which?   I hope TexStudio are very soon going to release an update (there is an issue for this on their issue queue.  Thank you for your help. This is my first post here, so please apologize any imprecisions. What is the need of exponential generating functions on combinatorial problems? I've been introduced in my last lectures. And for the following problem:     Having 3 different types of books $a,b,c$ in how many ways can we take four different books putting them in a shelf such that the book $a$ can only be taken at most $1$ time, $b$ can be taken at most $3$ times and $c$ can only be taken at most $2$ times?   The ordinary generating function for this problem is:  $\quad \quad \quad \quad \quad \quad \quad $  Looking at the exponential generating function of the same problem, the only part of interest is the coefficient of $x^4$, which is:  $$\left(\frac{ab^3}{1!3!}+\frac{b^3c}{3!1!}+\frac{ab^2c}{1!2!1!}+\frac{b^2c^2}{2!2!}+\frac{abc^2}{1!1!2!}\right)$$ And then multiply it by $4!/4!$. But why do I need an exponential generating function? Isn't only needed to take the coefficient of $x^4$, divide each term of it by $a_1!a_2!\dots a_n!$ with $a_n=\text{power of a,b,c,}\dots$ and then multiply it by $4!4!$? It's not clear why such complication is needed.  By complication I mean to expand that generating function with the factorials, I could expand the ordinary generating function and then artificially add the factorials. If  $$\sin A + \cos A + \tan A + \cot A + \sec A + \csc A = 7$$ then prove that  $$\sin 2A \quad\text{ is a root of }\quad x^2 - 44x - 36 = 0$$  I have no idea how to solve it. Plz help. How to install a dictionary (danish) in Texmaker How to calculate $5^{3^{1000}}\bmod 101$? I have a rather long footnote which breaks a listing in two parts, unnecessarily.  Since the listing is more important then the footnote I'd rather lake to have the footnote split.   Can I customize (one or all) footnotes to have a maximal length before they are continued on the next page? Or can I manually split a footnote in two to get the effect? Why use gradient descent with neural networks? When training a neural network using the back-propagation algorithm, the gradient descent method is used to determine the weight updates. My question is: Rather than using gradient descent method to slowly locate the minimum point with respect to a certain weight, why don't we just set the derivative $\frac{d(\text{Error})}{dw}=0$, and find the value of weight $w$ which minimizes the error? Also, why are we sure that the error function in back-propagation will be a minimum? Can't it turn out the error function is a maximum instead? Is there a specific property of the squashing functions that guarantees that a network with any number of hidden nodes with arbitrary weights and input vectors will always give an error function that has some minima? I've noticed this a few times on the Feed activity on the Android app, but never thought anything of it.  Why does this question (How To auto enable checkbox?) appear as "Unanswered" when there is an icon which denotes there are 5 answers, one of which has been marked as the answer?  Dragging down to refresh doesn't seem to clear the unanswered flag either.  Device: Nexus 5 Should import statements always be at the top of a module? states:  Imports are always put at the top of the file, just after any module comments and docstrings, and before module globals and constants.  However if the class/method/function that I am importing is only used in rare cases, surely it is more efficient to do the import when it is needed? Isn't this: class SomeClass(object):      def not_often_called(self)         from datetime import datetime         self.datetime = datetime.now()  more efficient than this? from datetime import datetime  class SomeClass(object):      def not_often_called(self)         self.datetime = datetime.now() How to extract the boundary of a raster image? I could have modifications ready for a specific question that was downvoted. I felt like the best thing to do was to delete the post first.  Is it possible to flag for moderator attention after you deleted the post ? I've been dealing with this problem for almost 2 hours now, with hardly any progress. I'm to prove the following inequality using induction   $$\sqrt[n+1]{n+1}&lt;\sqrt[n]{n}$$ where $n≥3$, $n∈\mathbb{N}$. How can this be done?