Horror/Creepy TV series, cartoon, decades odd ago (likely cable/teletoon)
Narration cartoon about a town that has weird paranormal occurrences in it
Addons: Only some .zips will install Why is it that if I go to install an add-on from User Preferences > Add-ons > Install from File... and choose a *.ZIP, some add-ons will install, while others will return me to the User Preferences with nothing having happened (as far as I can tell)?  Is there a specific file structure required in the .ZIP? I get many add-ons from GitHub, using the Download Zip button, and even there installation of the actual Zip file only works some of the time. swap x and y axis on data generated plot Background: I'm giving a presentation to colleagues at work on hypothesis testing, and understand most of it fine but there's one aspect that I'm tying myself up in knots trying to understand as well as explain it to others.  This is what I think I know (please correct if wrong!)   Statistics that would be normal if variance was known, follow a $t$-distribution if the variance is unknown CLT (Central Limit Theorem): The sampling distribution of the sample mean is approximately normal for sufficiently large $n$ (could be $30$, could be up to $300$ for highly skewed distributions) The $t$-distribution can be considered Normal for degrees of freedom $&gt; 30$   You use the $z$-test if:   Population normal and variance known (for any sample size) Population normal, variance unknown and $n&gt;30$ (due to CLT) Population binomial, $np&gt;10$, $nq&gt;10$   You use the $t$-test if:   Population normal, variance unknown and $n&lt;30$ No knowledge about population or variance and $n&lt;30$, but sample data looks normal / passes tests etc so population can be assumed normal   So I'm left with:    For samples $&gt;30$ and $&lt;\approx 300$(?), no knowledge about population and variance known / unknown.   So my questions are:   At what sample size can you assume (where no knowledge about population distribution or variance) that the sampling distribution of the mean is normal (i.e. CLT has kicked in) when the sampling distribution looks non-normal? I know that some distributions need $n&gt;300$, but some resources seem to say use the $z$-test whenever $n&gt;30$... For the cases I'm unsure about, I presume I look at the data for normality. Now, if the sample data does looks normal do I use the $z$-test (since assume population normal, and since $n&gt;30$)? What about where the sample data for cases I'm uncertain about don't look normal? Are there any circumstances where you'd still use a $t$-test or $z$-test or do you always look to transform / use non-parametric tests? I know that, due to CLT, at some value of $n$ the sampling distribution of the mean will approximate to normal but the sample data won't tell me what that value of $n$ is; the sample data could be non-normal whilst the sample mean follows a normal / $t$.  Are there cases where you'd be transforming / using a non-parametric test when in fact the sampling distribution of the mean was normal / $t$ but you couldn't tell? Motion Tracking objects that go out of frame and re-enter later I am motion tracking a video in which the camera turns away from one scene and then shortly returns to it. However, the segments that went off-screen lose their track and do not continue tracking once the camera returns. I am wondering if there is a manual way to tell a segment where and when to continue looking for it's tracking target. Is this possible to do? Query standard input of lightning-input I want to query standard HTML textarea which is wrapped by lightning-textarea. How can I get it?  &lt;lightning-textarea name=&quot;secret_field&quot; label=&quot;Secret&quot; value={secretFieldValue}&gt;&lt;/lightning-textarea&gt; Can I update an early Airport Time Capsule? What is the best way to put a backdoor in an encryption system? How can you put a backdoor into an encryption algorithm? Are there any techniques that can be used to reduce the time it takes to break a key?  I am looking for practical examples encryption schemes that have backdoors, because they were designed to or new techniques exposed them. It is my understanding that you can use a lack of entropy and diffusion in block ciphers which will reduce the necessary time that it takes to break a key. This is especially true with s-boxes, which can be designed to not increase the strength of the key. As for one-way algorithms, using none-primes can make it easier to reverse keys. What are other decisions that can be made to make a broken encryption algorithm?   The goal is find examples that can be used for encryption pedagogy, by collecting a sample of weak ciphers to practice on. I just installed Ubuntu 14.04 on a Dell laptop with 1.7Ghz Pentium M and 1Gbyte memory.  Graphics are Intel® 852GM/855GM x86/MMX/SSE2, OS type is 32bit.  The whole system is VERY slow. When I launch the applications manager, for example, I need to wait in order to see the letters I typed appear!  It is as if the CPU was overloaded and no memory available, but I only have Firefox running.  How can I make the system run smoother? It used to have Windows XP installed and it worked fine. This came up in proving non-regularity of a certain language (powers of 2 over the ternary alphabet). Any clue to the above equation could help me move forward.  Edit: Of course, $x = 1, y = 1$ is a solution. I am looking for non-trivial solutions. Is $\lim\limits_{n\rightarrow\infty} n$ comparable to $\aleph_0$? For example, can we say: $\infty=\lim\limits_{n\rightarrow\infty} n &lt; \aleph_0$?  These are two different types of structures. The limit being like the length, extension, or just generic magnitude and the other being cardinality of a set. Can we compare magnitude to cardinality?  Intuitively, we can reach $\aleph_0$ by counting the natural numbers on the number line and in the process will be approaching $\infty$. Which leads me to believe $\infty\leq\aleph_0$. But I can't see why it should be a strict inequality. I feel like they should be of equal magnitude.  I saw on a recent comment that $2^\infty=\infty$, but are those infinities really the same? It seems not to me. Of course we (usually) have that  $2^{\aleph_0}=\aleph_1$ where ${\aleph_0}$ and $\aleph_1$ are clearly two very distinct infinities, countable vs uncountable at least. Maybe one might argue that as far as the concept of magnitude is concerned, all infinities are "equal". Open Finder window from current Terminal location? If I am in a specific path in a Terminal window, how can I open that same window in a new Finder window?   Note: This is the opposite of . Request of a domain with no virtualhost in apache ends to default virtualhost If I ask Apache for domain.com that has no Virtual Host setup in Apache configuration, Apache will show the default Virtual Host. How can I prevent this from happening or simply drop the connection? Empty set does not belong to empty set Herbert in his book "Elements of set theory" on page no 3 says that      we can form the set $ \{ \emptyset \} $ whose only member is $\emptyset $. Note that $ \{ \emptyset \} \neq  \emptyset $, because $ \emptyset \in \{ \emptyset \} $ but $\underline{ \emptyset \notin \emptyset} $·   By the last argument $\emptyset \notin \emptyset$, is he saying that empty set is not a member of or does not belong to empty set  OR  it is a typo and he wanted it to be $ \{\emptyset \} \notin \emptyset $, that set containing empty set is not a member of empty set mysql_insert_id alternative for postgresql is there an alternative for mysql_insert_id() php function for PostgreSQL? Most of the frameworks are solving the problem partially by finding the current value of the sequence used in the ID. However, there are times that the primary key is not a serial column.... I had an (extremely minor) identity crisis when I clicked on my username and saw a different identicon than I'd had previously. :)  According to , your identicon is based on a hash of your last known IP address.  Since a user's profile picture part of their identity, I would prefer if my profile picture only changed through deliberate action on my part.  Since the user's IP hash is already saved (the identicon has to be displayed to people even during the unthinkable periods when we're not actively browsing), I propose preserving the first one assigned to a user, and not updating it even if the user's IP address changes.  Are there any upsides to the current behavior that I haven't thought of? I have a query on profile like  profilename = [Select name from profile where id=:userinfo.getUserprofileid ].name  Now I have a check in  VF page  like  profilename  == 'System Administrator' . this works fine if the logged in user language is english. If the user language is different then profile name will be  'System admin' in that language . So how to prevent this beahviour?   Also  is there any particular field in profile which I can use  to identify the profile is system admin? so that I can have check on that field instead of checking for name which is causing the problem, for example I think modifyall filed is only checked for system admin. Often I need to recall the different \tracing commands; and a couple of times I stumbled on some webpages that worked fine for me; sadly, I didn't keep them, and my searches don't take me there anymore.   So I thought I'd ask about links to where one can read a list of \tracing commands?   For instance,  mentions:  \tracingall \tracingassigns \tracingcommands \tracinggroups \tracingifs \tracinglostchars \tracingmacros \tracingnesting \tracingonline \tracingoutput \tracingpages \tracingparagraphs \tracingrestores \tracingstats \tracingscantokens   .. but, I'm pretty sure there was something like \tracingboxes (and not so sure if there was something like \tracingglues); yet I cannot find any resources mentioning those. Should covariates that are not statistically significant be 'kept in' when creating a model? I have several covariates in my calculation for a model, and not all of them are statistically significant.  Should I remove those that are not?  This question discusses the phenomenon, but does not answer my question:   There is nothing in the answer to that question that suggests that non-significant covariates be taken out, though, so right now I am inclined to believe that they should stay in.  Before even reading that answer, I was thinking the same since a covariate can still explain some of the variance (and thus help the model) without necessarily explaining an amount beyond some threshold (the significance threshold, which I see as not applicable to covariates).  There is another question somewhere on CV for which the answer seems to imply that covariates should be kept in regardless of significance, but it is not clear on that.  (I want to link to that question, but I was not able to track it down again just now.)  So...   Should covariates that do not show as statistically significant be kept in the calculation for the model?  (I have edited this question to clarify that covariates are never in the model output by the calculation anyway.)  To add complication, what if the covariates are statistically significant for some subsets of the data (subsets which have to be processed separately).  I would default to keeping such a covariate, otherwise either different models would have to be used or you would have a statistically significant covariate missing in one of the cases.  If you also have an answer for this split case, though, please mention it. Error installing any module Number of lines in a file in Java I use huge data files, sometimes I only need to know the number of lines in these files, usually I open them up and read them line by line until I reach the end of the file  I was wondering if there is a smarter way to do that