Is there a way to launch Terminator when right clicking "Open in Terminal" for Ubuntu 18.04?
Setting nautilus-open-terminal to launch Terminator rather than gnome-terminal
Continuous function from $(0, 1]$ onto $(0, 1)$? This question pertains to L1 &amp; L2 regularization parameters in Light GBM. As per official documentation:  reg_alpha (float, optional (default=0.)) – L1 regularization term on weights.  reg_lambda (float, optional (default=0.)) – L2 regularization term on weights  I have seen data scientists using both of these parameters at the same time, ideally either you use L1 or L2 not both together.   While reading about tuning LGBM parameters I cam across one such case: Kaggle official GBDT Specification and Optimization Workshop in Paris where Instructors are ML experts. And these experts have used positive values of both L1 &amp; L2 params in LGBM model. Link below (Ctrl+F 'search_spaces' to directly reach parameter grid in this long kernel)      I have seen same in XGBoost implementations.  My question is why use both at the same time in LGBM/XGBoost.  Thanks. I want to animate a character in a realistic but easy way. I was thinking that I could use videos of me performing the actions I want to have on my characters, however I can't find a way of placing the videos and make the character to follow my movements in an automated way, like motion tracking. How can I animate automatically using this technique? Are there any Plug-ins to work like this? Is this mehod actually more useful than standard animation techniques? Prove that $i^i$ is a real number According to WolframAlpha,  but I don't know how I can prove it. IndentationError: unindent does not match any outer indentation level How can I use Gmail (in Chrome) as the default email handler in Windows 8?  I used to use GmailNotifier in Windows 7, but that doesn't seem to work anymore. Clicking on a mailto: link simply opens Chrome with a blank page.  I am not interested in using the Mail app built into Windows 8. Is my proof that $U_{pq}$ is not cyclic if $p$ and $q$ are distinct odd primes correct? Prove that $U_{pq}$ is not cyclic if $p$ and $q$ are distinct odd primes.   I am a self taught person. I just learned this and tried this on my own and came up with this.  $x \equiv 1 \pmod{p}$ and $x \equiv -1 \pmod{q}$ has a solution $[a]_{pq}$, since $p$ and $q$ are relatively prime. Because $q$ is an odd prime, $[-1]_{pq}$ is not a solution, so $[a]_{pq}\neq [-1]_{pq}$. But $a^2 \equiv 1 \pmod{p}$ and $a^2 \equiv 1 \pmod{q}$, so $a^2 \equiv 1\pmod{pq}$ since $p$ and $q$ are relatively prime, and thus $[a]_{pq}$ has order 2.  Can someone please tell me if this proof this correct? Please help with proof as I learned it just now as a self taught person. I have  experience where empty spaces cause unwanted effects. It is not easy to trace the cause of these unwanted effects. In order to eliminate any doubt, I often overuse % as follows.   \usepackage% [% left=3cm, right=3cm% ]% {geometry}   or  \newcommand{\mycommand}% {% This is my command.% }   I got an extreme example that will break what Leo Liu said     In fact, only spaces which would be   output have to be removed by comment.   The following code does not produce output, but we cannot remove the % and leave a blank line between two elements of a list below.  \newpsstyle{gridstyle} { gridwidth=0.4pt, % griddots=0 }   Shortly speaking, where are the necessary places to be appended with % to remove unwanted spaces? Why does a window become a mirror at night? In day, when you look in the room through the window out, you can clearly see what happens outside. At night when it's dark outside but there's light inside you can look in the window but it becomes a mirror.  Why? UBUNTU 14.04 cheese booth not detect webcam Cheese Booth shows an error:     There was an error playing video from the webcam     I test if webcam works fine or not by opening google hangout, its works fine.    Please tell, what is the issue in cheese booth.  Note: Sometimes the cheese booth works fine but most of time not Random Gaussian Variables Is there a class in the standard library of .NET that gives me the functionality to create random variables that follow Gaussian distribution? Most games build on other games' successes and many are downright clones. Where is the limit of imitation before legal issues come into play? Is it down to literary or graphic work like characters and storyline that cause legal problems, or can someone actually claim to own gameplay mechanics?  There are so many similar clone games out there that the rules are probably very slack or nonexistent, but I'd like to hear the views of more experienced developers / designers. Probability of a player winning before another Given a 7 sided dice, 2 players roll it independantly simultaneously and when a player rolls a '6' he gets a prize.  What is the probability of the first player getting a prize before the second?  So my solution is to sum over all the turns j in which player 1 could win, and make the second player lose all these turns:  $$P(A) = \sum_{i=1}^{\infty}(6/7)^{j-1}*(1/7)*(6/7)^j = 0.461$$ My question is if my solution is correct, and if so, why is the probability so low? It seems to me that either player 1 wins before the 2nd or the other way around, and the probability of them playing forever is 0, so it should be 0.5? Broken APT on WSL 18.04 I am looking for tutorials, articles or books containing theory of  in context of mathematical physics. Please suggest. I have two independent groups: from one I have drawn a sample of size less than 30 due to its small population, while the second group has sample size 100.  Is it appropriate to use an independent samples t-test in this case? How to ignore accent in SQLite query (Android) How do I start skype in the system tray? What does 'super' do in Python? - difference between super().__init__() and explicit superclass __init__() What's the difference between:  class Child(SomeBaseClass):     def __init__(self):         super(Child, self).__init__()   and:  class Child(SomeBaseClass):     def __init__(self):         SomeBaseClass.__init__(self)   I've seen super being used quite a lot in classes with only single inheritance. I can see why you'd use it in multiple inheritance but am unclear as to what the advantages are of using it in this kind of situation. Why is the Earth so fat? I made a naive calculation of the height of Earth's equatorial bulge and found that it should be about 10km.  The true height is about 20km.  My question is: why is there this discrepancy?  The calculation I did was to imagine placing a ball down on the spinning Earth.  Wherever I place it, it shouldn't move.  The gravitational potential per unit mass of the ball is $hg$, with $h$ the height above the pole-to-center distance of the Earth (call that $R$) and $g$ gravitational acceleration.  Gravity wants to pull the ball towards the poles, away from the bulge.  It is balanced by the centrifugal force, which has a potential $-\omega^2R^2\sin^2\theta/2$ per unit mass, with $\omega$ Earth's angular velocity and $\theta$ the angle from the north pole.  This comes taking what in an inertial frame would be the ball's kinetic energy and making it a potential in the accelerating frame.  If the ball doesn't move, this potential must be constant, so  $$U = hg - \frac{(\omega R \sin\theta)^2}{2} = \textrm{const}$$  we might as well let the constant be zero and write  $$h = \frac{(\omega R \sin\theta)^2}{2g}$$  For the Earth,   $$R = 6.4*10^6m$$  $$\omega = \frac{2\pi}{24\ \textrm{hours}}$$  $$g = 9.8\ m/s^2$$  This gives 10.8 km when $\theta = \pi/2$, so the equatorial bulge should be roughly that large.    , the Earth is 42.72 km wider in diameter at the equator than pole-to-pole, meaning the bulge is about twice as large as I expected.  (Wikipedia cites diameter; I estimated radius.)  Where is the extra bulge coming from?  My simple calculation uses $g$ and $R$ as constants, but neither varies more than a percent or so.  It's true the Earth does not have uniform density, but it's not clear to me how this should affect the calculation, so long as the density distribution is still spherically-symmetric (or nearly so).  (Wikipedia also includes , without derivation, that agrees with mine.)