Package mathspec Error: `amsmath' must be loaded earlier than `mathspec'
Repost it with a minimal working example for the amsmath must be loaded earlier than mathspec problem
How to change background colour in texworks I am using texworks for the first time, I want to change the background of the editor from dark to white, as the code is not visible in dark background. I am using texworks in Manjaro Linux on GNOME desktop environment. Please help me. I have something like this:  &lt;div class="content"&gt;     &lt;a href="#"&gt;A&lt;/a&gt; &lt;/div&gt; &lt;div class="content"&gt;     &lt;a href="#"&gt;B&lt;/a&gt; &lt;/div&gt; &lt;div class="content"&gt;     &lt;a href="#"&gt;C&lt;/a&gt; &lt;/div&gt;   When one of these links is clicked, I want to perform the .hide() function on the links that are not clicked. I understand jQuery has the :not selector, but I can't figure out how to use it in this case because it is necessary that I select the links using $(".content a")  I want to do something like  $(".content a").click(function() {     $(".content a:not(this)").hide("slow"); });   but I can't figure out how to use the :not selector properly in this case. Why was Count Dooku not given the title "Darth"? I don't know the exact significance of the word "Darth" in the Sith world, but I think it was a word of honor for powerful Sith. That's why Anakin was given this word in his new name.  All powerful Sith in canon had this word in their names: Darth Plagueis, Darth Bane, Darth Sidious, Darth Vader, Darth Maul, etc. As such name similarity can't be names given by their parents, I can assume they were given such words in names as a honor.   Now, look at Count Dooku... he was a powerful Sith too. So, why wasn't he given this title?    Darth word to address Dooku hasn't been used in the movies, as far as I know. If you are claiming that Darth and Lord words are same, give citations because my vocabulary rejects it. EM algorithm gaussian mixtures- derivation I'm trying to make sense of a derivation I'm following from the lecture notes of Stanford's ML course.  Specifically the notes are here:   I'm particular I'm interested in the step where they are optimizing the lower bound of the log-likelihood by finding the derivative of that function w.r.t the mean (top of page 7). I'm a bit stuck on going from line 1 to line 2 in that sequence.  To copy here (using abbreviated notation for space):  $$ \nabla \mu_s \sum_{i=1}^{m}\sum_{j=1}^{k} w_j^{(i)}\log\frac{\alpha_j \exp\psi_{j}^{(i)}\phi_j}{w_j^{(i)}}  \qquad(1) $$ $$ \nabla \mu_s \sum_{i=1}^{m}\sum_{j=1}^{k} w_j^{(i)}\psi_{j}^{(i)}\qquad(2) $$ where $\psi_{j}^{(i)} =-\frac{1}{2}(x^{(i)}-\mu_j)^T\Sigma^{-1}_{j}(x^{(i)}-\mu_j)$ and $\alpha_j=\frac{1}{(2\pi)^{n/2}|\Sigma_j|^{1/2}}$.  The quantity $\mu_s$ is the mean (of a multivariate gaussian distribution) for class $s$.    In short, I'm not sure how they get from (1) to (2).  From just changing the log of (1) I see:  $$ \nabla \mu_s \sum_{i=1}^{m}\sum_{j=1}^{k} w_j^{(i)}\log \left(\alpha_j \exp\psi_{j}^{(i)}\phi_j\right) - w_j^{(i)}\log w_j^{(i)} \qquad(1) $$  To get to their form (2) my impression is that they take pre-emptively discard terms that would contain derivatives of $w_j^{(i)}$ (w.r.t. $\mu_s$).  At least if you assume that much, you get to (2).  However, as they show earlier in that PDF,  $$ w_j^{(i)} = p(z^{(i)}=j | x^{(i)}) =\frac{p(x^{(i)}|z^{(i)}=j)p(z^{(i)}=j) }{\sum_j p(x^{(i)},z^{(i)}=j) } $$ i.e. this quantity is the posterior distribution of the class labels.  Intuitively, it seems like $\partial w_j^{(i)}/ \partial \mu_s$ should be non-zero.  After all, changing the location of the mean $\mu_s$ would change your posterior probability for a particular class given the same data.  (Right?).  Just from a mechanical point of view, $\partial w_j^{(i)}/\partial \mu_j$ would seemingly have some non-zero terms since $p(x^{(i)}|z^{(i)}=j) \sim \mathcal{N}(\mu_j, \Sigma_j)$.  If I work through the algebra, I get  $$ \frac{\partial w_j^{(i)}}{\partial \mu_j} = w_j^{(i)}(1-w_j^{(i)})\frac{\partial \psi^{(i)}_{j}}{\partial \mu_j} $$  What am I missing here?  If I take the log-likelihood (without even thinking about EM algorithm),    $$ \ell = \sum_{i=1}^{m}\log \sum_{j=1}^{k}p(x^{(i)}|z^{(i)}=j)p(z^{(i)}=j) $$ and differentiate w.r.t $\mu_s$, I correctly get  $$ \mu_s^* = \frac{\sum_{i=1}^{m}w_s^{(i)}x^{(i)}}{\sum_{i=1}^{m}w_s^{(i)}} $$  so I'm comfortable with the eventual result, just not the intermediate steps. I have been trying to achieve a true mesh displacement on meshes for quite some time, without ever getting it to work.  If I understand it correctly, this experimental feature would allow me to easily displace the vertices of a mesh - or to create new mesh vertexes where needed - to get a displaced mesh in the result, based off an image, but without using a bump map (simpler, faster?).   This all sounds very exciting in theory, but I am having a really hard time finding examples or tutorials that are both recent and whose links function. So I think there is the need for a question here which will call upon detailed and recent answers to bridge that gap.  I'll start with a simple ico sphere:    Then, , I will change the Feature Set to the Experimental one:    I then add a pink granite image to the mesh:    Mark Seams, Unwrap, add image in the UV Editor:      and finally, in the Object Data panel, change the Displacement method from Bump to True as explained :    no result yet:    if I click "Use Subdivision" this is what I get (so I won't click it right now):    Looking into the Node Editor, nothing seems to have changed with the Displacement of the mesh:    so I tried to replicate the node setup seen in  of  (Linear isn't an option, Clip, Single and Repeat are):    ... but the result is a white ICO Sphere, similar to Image 1.  So, can the "Experimental Feature Set" be used to create actual displacement, and modify a mesh?  This is what I'm trying to obtain - but with the image of the texture actually displaying on the mesh (image from ):    .blend file: Need help with a question regarding the Big Oh In class we are currently covering upper/lower bounds, big Oh and omega and the like. I am pretty good on the "typical" functions one would do, but at a complete loss at "general" statements. This ons function, for example:  $$\forall f\in\mathcal{F}: \lfloor \sqrt{\lfloor f(n)\rfloor }\rfloor \in O(\sqrt{f(n)}).$$  the domain F by the same is all natural numbers that return a real positive number when inputted. My first instinct with something like this is to remove the floors, the general strategy I though to solve this is remove the outer floor, then get rid of the square root, and then the inner floor. But I have no idea how to go about this or if this is even the right way to do it.  Help please? Thanks in advance. Help finding this set Lets define the following:  Let A be a set. A is innumerable if and only if there exists a bijective function from A to $\mathbb{N}$  Proof that there exists an innumerable set $B \subseteq \mathcal P \left({\mathbb{N}}\right)$ such that it has the following properties:  1) $X\cap Y =\emptyset$ for all $X,Y \in B$ such that $X \neq Y$  2) $\mathbb{N}= \bigcup B$  3) All elements of B are innumerable.  Any help is appreciated. I don´t know how to find this set ... Is there a way to install fonts on wine?   I'm looking to install fonts so i can use them to render text differently on various apps. Specifically myriad. How do I get a selected vertex and it's corresponding uv vertex?  A vertex I can get with  bpy.context.active_object.data.vertices[0]   A uv vertex I can get with  bpy.context.active_object.data.uv_layers['UVMap'].data[0]   But the index is not the same for uv and mesh vertex. Visualization for Euclidean Algorithm Labels and nesting gather and align I have nested gather and align according to  \begin{gather}        \sum\limits_{i=1}^n i + \text{expression} = \dfrac{n(n-1)}{2} \label{l1}\\        \begin{align}             a+\text{expression}&amp;=b \\ %\label{l2} doesnt work             c&amp;=d+\text{expression} \\             e+\text{long expression}&amp;=f-\text{expression}        \end{align}  \end{gather}   to get an output looking like this:   The problem is that it is not possible to label all equations separately. The problem is identical to that discussed in , except  that in my problem the first line needs to be centered.  Thanks for any help. How can I separate multiple quote blocks? I have a series of quotes which I want to display in two separate quote blocks.  &gt; Are questions about Microsoft Word Online on-topic here? I don't &gt; really see any posted here, but perhaps I am not searching correctly. &gt; - mweiss &gt;  &gt; Yes, they are. We even have a specific tag: [tag:word-online]. -ale &gt;  &gt; Thanks! I'm sorry I missed that tag. -mweiss   When I try to add these to my post, they display as a single combined quote.     Are questions about Microsoft Word Online on-topic here? I don't   really see any posted here, but perhaps I am not searching correctly.   - mweiss      Yes, they are. We even have a specific tag: . -ale      Thanks! I'm sorry I missed that tag. -mweiss   How can I separate quotes so that they aren't combined into a single quote block? I have a Windows Server 2012 R2 Domain.  Yesterday, a computer’s (running Windows 10 Pro) network drive stopped working.  After further investigation (gpresult /h) it appears ALL group policy objects are failing with the reason Inaccessible, Empty, or Disabled.  I have confirmed that all the GPOs still exist and are enabled on both (redundant and local) domain controllers.  Furthermore, there are 20 other machines on the same domain and LAN with absolutely no problems.  However, there is one other computer that I tested which presented with the same problem!  Does that mean the problem is with the servers?  gpresult /r reports that one client is getting GPOs from local DC1, and the other from DC2.  So it is not a problem related to a specific DC.  gpupdate /force fixed nothing (though it claimed that policies were applied).   I tried deleting the registry entries for local policies (following this guide ) and rebooting - same problem.    I found this support page from Microsoft (), but it claims it only applies to Windows 7 or earlier clients.  All my machines (both server and client) are running 64-bit versions and are fully updated.  I have rebooted all of them just to be sure. Basic mathematical induction regarding inequalities "'void' type not allowed here" error (Java) Prevent Windows 7 from sleep + power button hook I'm used to not shutdown Windows but to sleeping it. I set up power button (PB) action to do it. When I want to shutdown I must go to start -> Shutdown. That's OK.  Now I think of a mechanism that will be hooked up to a PB. Should be started after I press PB but before OS will go to sleep. Something that will check few conditions (i.e. running backup, running AV scan, ...) and if true (something is running) prevent go to sleep.  Optionally: It would be nice to start the same "mechanism" before restart and shutdown (invoked not only from Start menu, but also by other software (i.e. installers) but with option to allow some sources (i.e. UPS software)  Generally: How to run something after PowerButton but before Sleeping. How to code (C#.NET, vbs, batch (preferred)) sleep prevention (cancellation). Where can I safely store my stuff? How to sort two lists (which reference each other) in the exact same way Why is this limit $\lim_{n \to \infty}(1 + \frac{1}{n})^n$ equal to $e$? I dont get it, if I look at $$\lim \limits_{n \to \infty}\left(1 + \frac{1}{n}\right)^n = e$$    It seems like it should be $1$ because $1 \over n$ is almost zero and $1^\infty$ is still $1$ How do I translate an ISO 8601 datetime string into a Python datetime object?