If my level 7 druid casts  (choosing the Primal Beast form) on himself and then proceeds to use , do the effects of the spell carry over to the Wild Shape?
Assume you cast Barkskin in humanoid form:     You touch a willing creature. Until the spell ends, the target’s skin has a rough, bark-like appearance, and the target’s AC can’t be less than 16, regardless of what kind of arm or it is wearing.   It is clear that under the rules of Wild Shape "transforming doesn’t break your concentration on a spell you’ve already cast", but does the effect of the spell carry over to your new skin?
solve $T(n)=T(n-1)+T(\frac{n}{2})+n$ Using the recursion tree i tried solving this: $T(n)=T(n-1)+T(\frac{n}{2})+n$; the tree has two parts (branches) one that of $T(n-1)$ and other branch is of $T(\frac{n}{2})$. But as the term T(n-1) reach higher depth, I solved that part of the tree. Finally it resulted in O$(2^n)$ is it correct or is it $O(n^2)$? How can we solve it by substitution method? Finding empty directories recursively World edit wood rotation What units does the rotation argument expect when creating objects? I want to create a lamp in blender using python. I want to give the lamp some rotation. As per the  I can set the initial rotation using a tuple of numbers in the function call like this rotation=(0.0, 0.0, 0.0) this is the specifc documentation for the rotation parameter:  rotation: (float array of 3 items in [-inf, inf], (optional)) – Rotation, Rotation for the newly added object  What units is this parameter specified with? It does not seem to be in degrees or radian.  When I try with my example code here where I use rotation=(0, 1, 0) to get 1 degree on the y axis. I end up getting 57.296 degrees after running the code.  import bpy  bpy.ops.object.lamp_add(type='AREA', view_align=False, location=(0, 0, 0), rotation=(0, 1, 0), layers=(True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False)) How do I exactly find the zero divisors and units of a ring in the form of $\mathbb{Z}_n \times \mathbb{Z}_m$? For instance, how does one calculate zero divisors and units of $\mathbb{Z}_6 \times \mathbb{Z}_2$? I understand that a zero divisor is a non-zero element of $R$ such that $rs = 0$ for some other non-zero element $s$ in $R$. But I don't really quite understand how to apply that to a ring of the form $\mathbb{Z}_n \times \mathbb{Z}_m$. Also, the units of $\mathbb{Z}_6 \times \mathbb{Z}_2$ would be elements that send some element $s$ in $\mathbb{Z}_n \times \mathbb{Z}_m$ to the multiplicative identity, right? (which would be 1)? How do I apply these concepts to "product" rings? Thank you. Java: Difference between the setPreferredSize() and setSize() methods in components "There is/are more than one". What's the difference? While adding to an Answer to  question, I needed to use the above phrase, and I suddenly realised I was unsure whether to write "is" or "are".   There is more than one way to skin a cat. If there are more than one species of cat, we will flay each species differently.   I don't think that second example above sounds quite right to me (disregarding the meaning - sorry!), but in my original Answer I felt "is" would have been even worse.  Is "are" always wrong here? If so, what exactly is the rationale? If not, is there a case where it's unquestionably preferred – and why is that?    Note that in both the problematic Answer and my example attempting to mimic the same context more briefly, the writer doesn't know how many there are. There may be one, more, or even none.  Getting even more specific, the writer might have an opinion on how many there might be, and wish to convey his leanings by choice of verb form if language allows this to be done succinctly. What do the fields in ls -al output mean? The vertical line at the end of the cell where i used cell merge is missing. Finding $\int x^xdx$ I'm trying to find $\int x^x \, dx$, but the only thing I know how to do is this:  Let $u=x^x$.  $$\begin{align} \int x^x \, dx&amp;=\int u \, du\\[6pt] &amp;=\frac{u^2}{2}\\[6pt] &amp;=\dfrac{\left(x^x\right)^2}{2}\\[6pt] &amp;=\frac{x^{2x}}{2} \end{align}$$  But it's certain that this isn't the correct way to evaluate that, and the answer must be wrong. I am trying to classify using randomForest classification in GEE . However, I always get the error User memory limit exceeded, so I assume the number  of the feature are too large. Nevertheless, I saw many developers can classify even bigger dataset, so I am wondering if there is a better option there? The code can be accessed via  var fire= ee.FeatureCollection('users/spatola/recovery_rf_1712').map(function(feature){     var num = ee.Number.parse(feature.get('CLC_311'));     return feature.set('CLC_311', num);   }) var indices= ['EVI_mean','Dnbr','NBR2_mean','NBR2_min','NBR2_max','EVI_min','EVI_max']; var fire1=  fire.filter(ee.Filter.notNull(indices)); var fire2= fire1.select('Class_R','Dnbr','EVI_max','NBR2_max','imageId') var bands= ['NBR2_max', 'EVI_max']; var classProperty= 'Class_R'; var random= fire2.randomColumn('random'); var split_train= 0.8; var split_test= 0.2; var trainPartition= random.filter(ee.Filter.lt('random',split_train)); var testPartition= random.filter(ee.Filter.gte('random',split_test));  var RFtrained_c= ee.Classifier.smileRandomForest({  numberOfTrees: 100,  minLeafPopulation:2,  seed: 123,  }) .setOutputMode('CLASSIFICATION') .train({     features: trainPartition,     inputProperties: bands,     classProperty: classProperty,     }) print(RFtrained_c); var dict =  RFtrained_c.explain(); var test = testPartition.classify(RFtrained_c) print(test.first()) I need to make Windows 7 STOP disabling the wifi adapter when the wired LAN is connected Sounds of supersonic objects Would you, as a stationary observer, hear a sound in reverse when the source of the sound travels with twice the speed of sound? Of course, he wouldn't hear anything at all before the airplane passed by and the sound reaches him, but what about after? Does it reverse due to the Doppler effect? Modular arithmetic: division, fractions, solving linear congruences I want to ask a question about modular arithmetic. I know, that modular multiplicative inverse exists only if modulo and integer are relatively prime. I want to know, are there any ways of division in modular arithmetic, if modulo and integer aren't relatively prime? I tried to find info about that, but failed. Continuously Differentiable Curves in $\mathbb{R}^{d}$ and their Lebesgue Measure Show that the image of the curve $\Gamma\in\mathscr{C}^{1}\left([a,b]\to\mathbb{R}^{d}\right)$ has d-dimensional Lebesgue measure zero (of course, $d\geq2$).  This can be proved using the absolute continuity of $\Gamma'$ (since $[a,b]$ is compact and $\Gamma'$ is assumed continuous, hence in $L^{1}([a,b])$) together with the fundamental theorem of calculus to obtain an $\epsilon$-small cover of $\Gamma$ by balls.  But I am trying to prove this using more elementary means (i.e. without integration).  Intuitively, since $\Gamma$ is smooth, we ought to (for fine enough partitions) be able to cover $\Gamma$ by boxes which arise from its tangent line.  And by taking the partition of $[a,b]$ to be finer and finer, the "tangent box" cover ought to also get smaller and smaller.  More rigorously, the vector-version of the mean value theorem can be applied: $$|\Gamma(t_{i-1})-\Gamma(t_{i})|\leq(t_{i}-t_{i-1})|\Gamma'(t_{i}^{\star})|\leq M_{i}\Delta t$$ where $t_{i}^{\star}\in(t_{i-1},t_{i})$ and $M_{i}=\sup_{t\in[t_{i-1},t_{i}]}|\Gamma'(t)|$ which exists and is finite since $\Gamma'$ is continuous.  But to me, it's not quite clear how to rigorously construct a cover by boxes from here.  NOTE:  In the proof I mentioned (using integration), essentially you sum the left hand side over all partition intervals of uniform length $\delta$ (which depends on the $\Gamma'$), and "integrate" the right hand side.  Actually, to be more specific, for each $\epsilon&gt;0$ there exists a $\delta&gt;0$ such that $||P||&lt;\delta$ implies $\int_{t_{i-1}}^{t_{i}}|\Gamma'(t)|dt&lt;\epsilon$ (e.g. absolute continuity).  This allows you to define numbers $\epsilon_{i}=\sup_{t,\bar{t}\in[t_{i-1},t_{i}]}|\Gamma(t)-\Gamma(\bar{t})|\leq\epsilon$ so that $\sum_{i=1}^{\#P}\epsilon_{i}\leq||\Gamma'||_{L^{1}([a,b])}$.  Then you can use these $\epsilon_{i}$ to put balls at each point $\Gamma(t_{i})$ of radius (say) $2\epsilon_{i}$, thus giving you an $\epsilon$-small cover.  Again though, this is harder to establish without integration theory. How to force nginx to resolve DNS (of a dynamic hostname) everytime when doing proxy_pass? What is the sign of the work done on the system and by the system? What is the sign of the  done on the system and by the system?  My chemistry book says when work is done on the system, it is positive. When work is done by the system, it is negative.  My physics book says the opposite. It says that when work is done on the system, it is negative. When work is done by the system, it is positive.  Why do they differ? Obtaining consistent one-hot encoding of train / production data Most properties of a single binary operation can be easily read of from the operation's table. For example, given $$\begin{array}{c|ccccc} \cdot &amp; a &amp; b &amp; c &amp; d &amp; e\\\hline a     &amp; e &amp; d &amp; b &amp; a &amp; c\\ b     &amp; d &amp; c &amp; e &amp; b &amp; a\\ c     &amp; b &amp; e &amp; a &amp; c &amp; d\\ d     &amp; a &amp; b &amp; c &amp; d &amp; e\\ e     &amp; c &amp; a &amp; d &amp; e &amp; b \end{array}$$ it is easy to check that it is closed (no elements occur in the table which don't occur as row or column index), commutative (the table is symmetric), has a neutral element (the row and column of $d$ are copies of the index row/column), and has an inverse element for each element (there's a $d$ in each row and column). In other words, almost all important properties can immediately be seen. The only part missing is associativity.  Therefore my question: Is there a simple way to see directly from the operation's table (i.e. without doing explicitly all the calculations) if an operation is associative? It's clear to me by inspection that if we fix $\beta = \frac{1-\mu}{\mu} \alpha$ (thereby fixing the mean) and let $\alpha \rightarrow 0$, the Beta distribution approaches a Bernoulli($\mu$) distribution.  For example:  par(mfrow = c(1, 2),     oma = c(0, 0, 1.5, 0)) xx = seq(0, 1, length.out = 1000) mus = c(.2, .7) for (ii in 1:2) {   mu = mus[ii]   matplot(xx, sapply(10^(-1:-5), function(al)      pbeta(xx, al, (1-mu)/mu * al)),     type = 'l', lty = ii,     main = paste('Mean:', mu),     ylab = 'Cumulative Probability', xlab = 'x') } title('Beta Approaches Bernoulli', outer = TRUE)     That is, if $X \sim B(\alpha, \frac{1-\mu}{\mu} \alpha)$, its CDF $F_X(x; \alpha, \mu)$, satisfies  $$ \lim_{\alpha \rightarrow 0} F_X(x; \alpha, \mu) = 1 - \mu = F_Y(x) \quad \forall x \in (0, 1)$$  Where $Y \sim$ Bernoulli($\mu$), and the convergence is non-uniform. I tried to do a more formal proof of this but couldn't make any progress, even in simple cases (like $\mu = \frac12$). The  makes reference to the $\mu = \frac12$ case several times without proof. Perhaps I'm missing something easy about doing the integral, or some fact about the Beta/incomplete Beta function. Any help would be appreciated!