There's one tweak of my phone I'm applying/removing through two some pretty simple shell scripts. But going to terminal emulator and typing the script names each time aside, the tweak actually makes on-screen keyboard unusable and may necessitate adb access to start deactivate.sh  Is there a way to launch the scripts from the home screen - just place them as icons, the way you can just double-click a .bat file on your desktop on Windows?
I'm using terminal-ide  which is basically a terminal for android with all sorts of utilities. One is able to create bash scripts for example. Is there a way to create an icon on the home screen that will launch one of these scripts?
Working in a group blender project What geometric object is given by this equation? What geometric object is given by this equation?  $x^2+y^2+z^2+2xy+2xz+2yz-x-y-z-6=0$  Maple says it's a hyperboloid of one sheet, but is there a way to show it without going the long way by using the principal axis theorem? When applying dropout in artificial neural networks, one needs to compensate for the fact that at training time a portion of the neurons were deactivated. To do so, there exist two common strategies:   scaling the activation at test time inverting the dropout during the training phase   The two strategies are summarized in the  below, taken from .  Which strategy is preferable, and why?    Scaling the activation at test time:    Inverting the dropout during the training phase: By definition $\aleph_1 = 2 ^{\aleph_0}$. And since $2 &lt; \aleph_0$, then $2^{\aleph_0} = {\aleph_1} \le \aleph_0 ^ {\aleph_0}$. However, I do not know what exactly $\aleph_0 ^ {\aleph_0}$ is or how I could compute it. Why is there no consistency in the plural forms of words ending on an "f" (e.g. safe, roof, dwarf, etc.)? The plural form of leaf is leaves, although according to  leafs is also correct. Dwarf can be pluralized as either dwarfs or dwarves. Conversely, the words roof and safe are pluralized as roofs and safes.  Is there any logic underpinning these variations? Is there a historical trend where words that were previously pluralized as -ves are now being increasingly pluralized as -fs? How to get the Runtime-Type of an Object dynamically (for Primitive Data Types and SObjects) Is it possible to get the Type of an Object (it's not an SObject)?  String s = 'test'; doSomething(s);  public static void doSomething(o Object) {     // need to find out if o is a string or an integer     type = IsThereAMethodToGetTheTypeOf(o) // ?     if(type='String') {         // do something for strings here ....     } else {         // do something else ....     } }   I think the Type class can't help me, because it has no way to get the type of an existing object instance, right? Any there any other way?  Since there is most likely no perfect solution possible within the current platform limitations, I posted an Idea on IdeaExchange here:   For SObject I have already this  public static string getType(SObject obj) {     if(obj==null) return '';     return obj.getSObjectType().getDescribe().getName()+''; } Why didn't Elizabeth get cursed? In Pirates of the Caribbean, whoever has the Aztec gold gets cursed.  But Elizabeth had the gold coin with her which Bootstrap gave to his son Will before he was tied to a cannon and dropped to the ocean floor.  Barbossa states that they were cursed because of Aztec gold.  Also in the fight between Jack and Barbossa, Jack takes a gold coin and he was also cursed.  Why didn't Elizabeth get affected? Or was she also cursed and nobody noticed? Do I need a swap partition? I have 4GB of RAM and I want to install Ubuntu. Do I need a to have a swap partition? Because my computer has 4GB RAM, I do not think it is necessary to have a swap partition. If I do need to have a swap partition, should it be a 4GB or an 8GB partition? How can I fix the non-stitched seam that is present after applying mirror modifier? Let $T:V\to V$ be a linear map, where $V$ is an inner product space. Given $T^2=\frac{T+T^*}{2}$, prove that $T$ is normal and that $T=T^2$. Let $T:V\to V$ be a linear map, where $V$ is a finite-dimensional inner product space. Given $T^2=\frac{T+T^{*}}{2}$, I would like to prove that $T$ is normal and that $T=T^2$. The first part, to prove that $T$ is normal, is quite easy: from $T^2=\frac{T+T^{*}}{2}$ we'll have $\,T^{*}=2T^2 - T$, and as $TT^{*} = 2T^3 -T^2 = T^{*}T$. Now, I need to prove that $T=T^*$, then $T = T^2$ is immediate. I have been thinking about this question for some days and I can't figure out in what technique to prove that $T = T^{*}$. From what I understand, the  states that there is a fundamental natural limit to how accurately we can measure velocity and momentum at the same time. It's not a limit on equipment but just a natural phenomenon.  However, isn't this just an observational limit? There is a definite velocity and momentum, we just don't know it. As in, we can only know so much about the universe, but the universe still has definite characteristics.  Considering this, how do a wide range of quantum mechanical phenomena work? For example, quantum tunneling - its based on the fact that the position of the object is indefinite. But the position is definite, we just don't know it definitely. Or the famous light slot experiment? The creation of more light slots due to uncertainty of the photon's positions?  What I am basically asking is why is a limit on the observer, affecting the phenomenon he is observing? Isn't that equivalent to saying  because we haven't seen Star X, it doesn't exist? It's limiting the definition of the universe to the limits of our observation! How can I install Sun/Oracle's proprietary Java JDK 6/7/8 or JRE? I want to install Oracle's JRE and to update to the latest version with the Software Updater when they released. Is there a Ubuntu package that is provided by Canonical or Oracle?  Before release Java 7, I followed  to install Java 6.  But it doesn't work for Java 7. There is no package sun-java7-xxx. How can you install Java 7? how long does the care take to reach the last pole algebra word problem There are 20 poles with a constant distance between each pole. A car takes 22 seconds to reach the 12th pole starting from the first pole, with a constant speed between each pole. how many seconds will it take to reach the last pole?   Is the answer 36 seconds?   since $\frac{22} {12}  = 1.83 $  $1.83 \times 20 = 36.67 $ "Parsing filters unsupported" error during extraction of RAR file I have received an .rar which I wish to unpack as it contains something rather important to me that I need to really have now. However even though I can view the contents of the .rar archive in the Archive Manager, I am unable to extract it due to this error:    The archive should contain two folders within it, each though contain at least 10 audio files as well as a PDF file each (I don't know what the contents exactly should be except for there should be audio files in there, and the content I have described is what I can see from the Archive Manager's view). So the only thing I am left with except the error is one of the folders and one of the audio files, but it says it has 0 bytes in it.  So how exactly do I fix this problem? I am running Ubuntu GNOME 16.04.1 with GNOME 3.20.  Information Update:  In reply to a comment requesting the output from the dpkg -l unrar unrar-free command:  Desired=Unknown/Install/Remove/Purge/Hold | Status=Not/Inst/Conf-files/Unpacked/halF-conf/Half-inst/trig-aWait/Trig-pend |/ Err?=(none)/Reinst-required (Status,Err: uppercase=bad) ||/ Name           Version      Architecture Description +++-==============-============-============-================================= un  unrar          &lt;none&gt;       &lt;none&gt;       (no description available) dpkg-query: no packages found matching unrar-free Key Derivation Functions vs. Password Hashing Schemes Key derivation functions, such as HKDF (standardized in ), are meant to stretch some initial keying material having enough entropy, like a Diffie-Hellman shared value, into one or more strong cryptographic secret keys.   Password-hashing schemes, such as the  winner , are meant to hash usually low-entropy passwords with the goal of making the hash digest inversion as costly as possible for an adversary with respect to CPU and memory consumption, as well as parallelization.  Is it exact to consider that password-hashing schemes are actually key derivation functions specialized for low-entropy inputs? Or is there any other essential difference of theoretical nature between these two types of cryptographic schemes? Equivalence between least squares and MLE in Gaussian model I am new to Machine Learning, and am trying to learn it on my own. Recently I was reading through  and had a basic question.   Slide 13 says that "Least Square Estimate is same as Maximum Likelihood Estimate under a Gaussian model". It seems like it is something simple, but I am unable to see this. Can someone please explain what is going on here? I am interested in seeing the Math.   I will later try to see the probabilistic viewpoint of Ridge and Lasso regression also, so if there are any suggestions that will help me, that will be much appreciated also. How to find max of amount of opportunity related to account? I have a below requirement : I need to find maximum amount on related opportunities and to display on account. Ex: suppose I have account A1 and A1 have 5 opportunities with amount o1=>100 o2=>500 o3=>300 o4=>1000 o5=>50 on my account i should have max_opportunity_amount =1000.  I have written below trigger ,but  I am not sure what to do further  trigger maxOppAmountonAcc on Opportunity(after insert){      map&lt;id,Opportunity&gt; oppMap = new map&lt;id,Opportunity&gt; ();     set&lt;Id&gt; oppId = new set&lt;Id&gt;();     for(Opportunity o : Trigger.new)     {         oppMap.put(o.accountId,o);         oppId.add(o.id);     }       List&lt;Account&gt; accList = new List&lt;Account&gt;();      for(Account a : [Select id ,MaxOppAmount__c,(select id,max(amount)  from opportunities) from Account where id in : oppMap.keyset()])     {      }  } what are the meanings of &quot;treated observation&quot; and &quot;non-treated observation&quot; in this context ?  Further, propensity score matching is a more robust method of matching that quantitative accounting researchers frequently use (Rosenbaum &amp; Rubin, 1983). With this technique, the researcher first estimates a logit or probit regression with the treatment effect as the dependent variable (i.e., S&amp;P 500 membership, continuing with our earlier example) and independent variables that are known determinants of the treatment (possibly economic performance, firm size, age, industry, etc. in our example). From this first-stage regression, the researcher obtains propensity scores. 6 The researcher then matches each treated observation to a non-treated observation based on the distance between their propensity scores (i.e., those observations with the closest propensity scores are matched). 7 Hoi et al. (2013) utilize propensity score matching in their study that links irresponsible CSR activities with tax aggressiveness. They first generate predicted propensity scores for each firm-year using a model of the determinants of a firm engaging in a high level of negative, irresponsible CSR activity. Then, they match a treatment firm (one with a high level of negative CSR activities) to a non-treatment firm (one with a low level of, or no, negative CSR activities) by matching observations with the closest propensity scores. Hoi et al. (2013) then re- test the relation between negative CSR activities and tax aggressiveness using this matched sample. These matching techniques help mitigate the researcher’s potential failure to consider certain firm characteristics that differ between treatment and non-treatment firms (Dhaliwal et al., 2012). When I shoot a ball vertically upward, its velocity is decreasing since  there is a downward acceleration of about $9.8\,\mathrm{ms}^{-2}$.   I have read that at the top most point, when $v = 0$, the acceleration is still $9.8\,\mathrm{ms}^{-2}$ in the downward direction where $v=0$. That is, the acceleration is still the same.  But at the highest point, the ball is stationary, so it is not even moving. How can it accelerate? Show that $d_2$ defined by $d_2(x,y)=\frac{|x-y|}{1+|x-y|}$ is a metric