Snap-packaged Chromium can not read mounted volumes
Why can't Chromium suddenly access any partition except for /home?
Exporting QGIS project to Mapnik XML? Is it possible to export a QGIS project to Mapnik xml?   I'm using QGIS 2.4 and Quantumnik does not seem to work with that version. KKT points and nonlinear optimality (theory) I have some questions about Karush Kuhn Tucker conditions. I am not clear about the theory. There are plenty of theorems and I am confused with it. Let us say we have the following problem: We have a general problem, not a convex problem. $$\min f(x)\\g_{j}(x)\le 0,\forall j\in J\\h_{k}(x)=0,\forall k \in K. $$ I will solve it.....Lagrange function, verifying primal feasibility, dual feasibility and complementary slackness and I will get some KKT points. Now what is the conclusion?  If I get no KKT point, can I say that the problem has no solution or what is the conclusion? If I get only one KKT point, is it a local minimum or even a global minimum? If I get more KKT points, what is the conclusion? In which case I will verify SOSC condition? If I get more KKT points or even for one point is it necessary? And the conclusion is what? The KKT points which satisfies the SOSC condition are strick local minimum and the poins which does not satisfy it are not the solution of the problem?  I am so sorry for so many questions, but any help would be very appreciated. Thank you very much in advance. Why is the sum of two random variables a convolution? For long time I did not understand why the "sum" of two random variables is , whereas a mixture density function sum of $f(x)$ and $g(x)$ is $p\,f(x)+(1-p)g(x)$; the arithmetic sum and not their convolution. The exact phrase "the sum of two random variables" appears in google 146,000 times, and is elliptical as follows. If one considers an RV to yield a single value, then that single value can be added to another RV single value, which has nothing to do with convolution, at least not directly, all that is is a sum of two numbers. An RV outcome in statistics is however a collection of values and thus a more exact phrase would be something like "the set of coordinated sums of pairs of associated individual values from two RV's is their discrete convolution"...and can be approximated by the convolution of the density functions corresponding to those RV's. Even simpler language: 2 RV's of $n$-samples are in effect two n-dimensional vectors that add as their vector sum.           Please show the details of how the sum of two random variables are a convolution and a sum. "He is king" vs "He is a king." I'm reading a book and encountering the phrase "insert name is king" a lot. I'm wondering, what's the difference between them? When and why should I use "He is king" instead of "He is a king"?   Examples:        Tommen is king now   Yet if neither one is king, still, how could it be Lord Renly?   And he is a king, and you’re just a spy   Everyone else is a king or prince these days      Same with other words:        They elected him president.   They called him a thief. Find subexpression to minimize leafcount after replacment with temporary variable What do ref, val and out mean on method parameters? I'm looking for a clear, concise and accurate answer.    Ideally as the actual answer, although links to good explanations welcome.  This also applies to VB.Net, but the keywords are different - ByRef and ByVal. Showing that $A\cap B = A\setminus (A\setminus B)$ How does one show that $A\cap B = A\setminus (A\setminus B)$?  My thinking is that if $x\in A\setminus (A\setminus B)$ then this means that $x\in A$ and $x\notin A\setminus B$, which means that $x\in A$ and ($x\notin A$ and $x\in B$), but I don't see why the expression in parentheses should simplify to just $x\in B$. Any insight would be helpful.  Maybe $(x\in A^c$ and $x\in B)$, i.e, $x\in A^c\cap B$ is a possible simplification of the expression in parentheses, but still don't see why this simplifies to just $x\in B$. Possible Duplicates:             I heard a professor of mathematics explaining that the following conslusions are true.   $\textrm{False}\Rightarrow \textrm{True}$ $\textrm{False}\Rightarrow \textrm{False}$   Could someone please explain to me why both conclusions are true? I am especially interested in the first case. I'd like to hear two explanations if possible: One for mathematicians and one for non-mathematicians. :-) How can I export the "available software to download" to a file? Sometimes Ubuntu will show a popup like this:    (It looks weird because I'm using )  How can I export the list of packages/changes Ubuntu wants to install to a file? This is for debugging purposes - I think something in this update is breaking my system, and I want to be able to be able to figure out exactly where the break is coming from. Is it possible to experimentally show that observable universe is much larger than ~93B ly? Why don't we treat rubbish the same as spam? Why does the classical path give the dominant contribution in the path integral? Array slices in C# How do you do it? Given a byte array:  byte[] foo = new byte[4096];   How would I get the first x bytes of the array as a separate array? (Specifically, I need it as an IEnumerable&lt;byte&gt;)  This is for working with Sockets. I figure the easiest way would be array slicing, similar to Perls syntax:  @bar = @foo[0..40];   Which would return the first 41 elements into the @bar array. Is there something in C# that I'm just missing, or is there some other thing I should be doing?  LINQ is an option for me (.NET 3.5), if that helps any. How do I add swap after system installation? I did not create a swap partition during Ubuntu installation.  Later, I freed up some space and made a swap partition.  Now after each boot up, I am manually opening gparted to right-click the swap partition to turn on the 'swapon' option.  How can I automatically enable the swap partition at boot?  Also, if I had not created the swap partition, what are my other options? Jensen's Inequality implies convexity? Suppose $\phi$ is a real function on $\mathbb{R}$ such that $$\phi \Bigl(\int_0^1f(x)\,dx\Bigr)\leq \int_0^1 \phi(f)\,dx$$ for every real bounded measurable function $f$. Prove that $\phi$ is then convex.    This one is in Rudin's Real and Complex Analysis, page 74, and, to be quite honest, I am unsure what my first step to solve this problem should even be. To help think of a general methodology, I attempted this similar question, from page 71 of the same book:      Assume $\phi$ is a continuous real valued function on $(a,b)$ such that $$\phi\Bigl(\frac{x+y}{2}\Bigr)\leq\frac{\phi(x)+\phi(y)}{2}$$ for all $x, y\in (a,b).$ Prove that $\phi$ is then convex (the conclusion does not follow if continuity is omitted from the hypothesis).   I take it that the latter question is just a special case of the former (assuming $\phi$ is bounded on $(a,b)$), so I attempted to solve the latter problem first. My attempt was to note that \begin{align*} \phi\big(\lambda x + (1-\lambda)y\big) &amp;\leq \phi\Bigl(\frac{2\lambda x + 2(1-\lambda)y}{2}\Bigr) \\ &amp;\leq \frac{1}{2}\Bigl(\phi\bigl(2\lambda x\bigr)+\phi \bigl(2(1-\lambda)y\bigr)\Bigr) \\ &amp; \leq \phi\bigl(\lambda x\bigr)+\phi\bigl((1-\lambda)y\bigr) \end{align*} with the latter inequality justified simply by applying the hypothesis again twice to the previous expression.   From here, however, I am stuck; I cannot justify "popping out" the $\lambda$ and the $(1-\lambda)$ in the last inequality via some bound afforded by the hypothesis and/or the continuity of $\phi$. Adding an error on a dynamic referenced field Is there a way to add an error on a dynamically referenced field? Let's take this simple example:  opp.get('Name').addError('Invalid name');   This is not working, I'm looking for a similar minded way.  Thanks Interpretation of log transformed predictor and/or response How to allocate aligned memory only using the standard library? subequations and array in braces How to use a variable for a key in a JavaScript object literal?