I have 100 objects and I don't want to render them until frame 30. I want to set keyframes to the restrict rendering button in the outliner but I don't want to set it for every single object by myself.
Very basic question here, I am afraid.  I have hundreds of shattered pieces of a mesh and I am trying to animate their visibility over the scene.  How can I animate the visibility and render visibility parameter for one piece, then copy/transfer to all the others?
How to disable internet search results in start menu post Creators Update? It  to disable internet search results in start menu searches before the Windows 10 Creators Update, but I've just clean installed a new Windows 10 Pro image and that setting is gone. Is there some way to disable it through editing the registry/etc? Consider equations defined in $D_x = (0,\infty) \times (0,\infty)$  1) Find the maximal solution to  $$ \dot y = \frac{3t^2}{5y^4} $$ satisfying the initial value problem $y(1) = 2^{\frac{1}{5}}$  I have found the maximum solution to be $((0,\infty), (t^3+1)^\frac{1}{5})$  2) Find the maximal solution to   $$ \dot y = -\frac{2y}{5t}+\frac{3}{5y^4}$$  satisfying the IVP $y(1) = 2^{\frac{1}{5}}$.  (HINT: Use a transformation of the form $t^{\alpha}y(t)$.   I hope someone can explain how to use the transformation to find the maximal solution. How to draw neat polygons around scatterplot regions in ggplot2 Record Animation In BGE Generate a log of all the installs on a system (whether apt-get/yum/pip/npm/...) Short story about survivors on Earth after the atmosphere has frozen I was tasked to prove that when given 2 graphs $G$ and $\bar{G}$ (complement), at least one of them is a always a connected graph.  Well, I always post my attempt at solution, but here I'm totally stuck. I tried to do raw algebraic manipulations with # of components, circuit ranks, etc, but to no avail. So I really hope someone could give me a hint on how to approach this problem. Drawing arrows on an HTML page to visualize semantic links between textual spans I have an HTML page with some textual spans marked up something like this:  ... &lt;span id="T2" class="Protein"&gt;p50&lt;/span&gt; ... &lt;span id="T3" class="Protein"&gt;p65&lt;/span&gt; ... &lt;span id="T34" ids="T2 T3" class="Positive_regulation"&gt;recruitment&lt;/span&gt; ...   I.e. each span has an ID and refers to zero or more spans via their IDs.  I would like to visualize these references as arrows.  Two questions:   How can I map an ID of a span to the screen coordinates of the rendering of the span? How do I draw arrows going from one rendering to another?   The solution should work in Firefox, working in other browsers is a plus but not really necessary. The solution could use jQuery, or some other lightweight JavaScript library. Product of pairwise coprime integers divides $b$ if each integer divides $b$ Let $a_1....a_n$ be pairwise coprime.  That is $gcd(a_i, a_k) = 1$ for distinct $i,k$, I would like to show that if each $a_i$ divides $b$ then so does the product.  I can understand intuitively why it's true - just not sure how to formulate the proof exactly. I want to say if we consider the prime factorizations of each $a_i$, then no two prime factorizations share any prime numbers.   So the product of $a_1...a_n$ must appear in the prime factorization of $b$.  Is this correct?  Or at least if if the idea is correct, any way to formulate it more clearly? When one should use spacing line \quad or \, How does sudo handle $HOME differently since 19.10? [i] Susan married Ed. (RHD)   [ii] My sister got married last fall. (COCA)   Is there a passive implication in [ii]? That is, the families and so on arrange and perform the marriage ceremonies for two people, and through all this the two get married. Is this implied in the expression [ii], and not in [i]? Do we have name for these kind of "flat graphics" images? Navigation bar overlapped by status bar Undergraduate research field different from PhD field I am a Physics undergrad who is interested in pursuing a PhD in pure maths in the future (algebraic geometry/topology) but I am a bit unsure. My question is quite general, and I don't wish to provide more background for fear of bias in the answers.  My question: Is it is advisable/possible/unfavorable/favorable to apply for a PhD in a field, different from that in which you have done most of your undergraduate research?  My research (includes just reading and understanding papers, writing summaries until now, I havent published anything) mostly includes Quantum field theory, and gauge theory. Would the selection committee turn down an application to a pure maths field, if I have no research experience whatsoever?  I would also like to ask the question other way round. What if I concentrate my undergraduate research SOLELY on topics in pure maths such as algebraic geometry/topology and take other physics courses, would I be able to apply to a string theory PhD with a high chance of success?  Should I consider spending time on both of these (which is almost an impossible task), to improve my chances in both the areas or would research in one area, and grad level courses in the other suffice?  In brief: Should the PhD field you are applying to be the same as your undergraduate research area? Choosing between LM and GLM for a log-transformed response variable I'm trying to understand the philosophy behind using a Generalized Linear Model (GLM) vs a Linear Model (LM). I've created an example data set below where:  $$\log(y) = x + \varepsilon $$   The example does not have the error $\varepsilon$ as a function of the magnitude of $y$, so I would assume that a linear model of the log-transformed y would be the best. In the example below, this is indeed the case (I think) - since the AIC of the LM on the log-transformed data is lowest. The AIC of the Gamma distribution GLM with a log-link function has a lower sum of squares (SS), but the additional degrees of freedom result in a slightly higher AIC. I was surprised that the Gaussian distribution AIC is so much higher (even though the SS is the lowest of the models).   I am hoping to get some advice on when one should approach GLM models - i.e. is there something I should look for in my LM model fit residuals to tell me that another distribution is more appropriate? Also, how should one proceed in selecting an appropriate distribution family.   Many thanks in advance for your help.  [EDIT]: I have now adjusted the summary statistics so that the SS of the log-transformed linear model is comparable to the GLM models with the log-link function. A graph of the statistics is now shown.  Example  set.seed(1111) n &lt;- 1000 y &lt;- rnorm(n, mean=0, sd=1) y &lt;- exp(y) hist(y, n=20) hist(log(y), n=20)  x &lt;- log(y) - rnorm(n, mean=0, sd=1) hist(x, n=20)  df  &lt;- data.frame(y=y, x=x) df2 &lt;- data.frame(x=seq(from=min(df$x), to=max(df$x),,100))   #models mod.name &lt;- "LM" assign(mod.name, lm(y ~ x, df)) summary(get(mod.name)) plot(y ~ x, df) lines(predict(get(mod.name), newdata=df2) ~ df2$x, col=2)  mod.name &lt;- "LOG.LM" assign(mod.name, lm(log(y) ~ x, df)) summary(get(mod.name)) plot(y ~ x, df) lines(exp(predict(get(mod.name), newdata=df2)) ~ df2$x, col=2)  mod.name &lt;- "LOG.GAUSS.GLM" assign(mod.name, glm(y ~ x, df, family=gaussian(link="log"))) summary(get(mod.name)) plot(y ~ x, df) lines(predict(get(mod.name), newdata=df2, type="response") ~ df2$x, col=2)  mod.name &lt;- "LOG.GAMMA.GLM" assign(mod.name, glm(y ~ x, df, family=Gamma(link="log"))) summary(get(mod.name)) plot(y ~ x, df) lines(predict(get(mod.name), newdata=df2, type="response") ~ df2$x, col=2)  #Results model.names &lt;- list("LM", "LOG.LM", "LOG.GAUSS.GLM", "LOG.GAMMA.GLM")  plot(y ~ x, df, log="y", pch=".", cex=3, col=8) lines(predict(LM, newdata=df2) ~ df2$x, col=1, lwd=2) lines(exp(predict(LOG.LM, newdata=df2)) ~ df2$x, col=2, lwd=2) lines(predict(LOG.GAUSS.GLM, newdata=df2, type="response") ~ df2$x, col=3, lwd=2) lines(predict(LOG.GAMMA.GLM, newdata=df2, type="response") ~ df2$x, col=4, lwd=2) legend("topleft", legend=model.names, col=1:4, lwd=2, bty="n")   res.AIC &lt;- as.matrix(     data.frame(         LM=AIC(LM),         LOG.LM=AIC(LOG.LM),         LOG.GAUSS.GLM=AIC(LOG.GAUSS.GLM),         LOG.GAMMA.GLM=AIC(LOG.GAMMA.GLM)     ) )  res.SS &lt;- as.matrix(     data.frame(         LM=sum((predict(LM)-y)^2),         LOG.LM=sum((exp(predict(LOG.LM))-y)^2),         LOG.GAUSS.GLM=sum((predict(LOG.GAUSS.GLM, type="response")-y)^2),         LOG.GAMMA.GLM=sum((predict(LOG.GAMMA.GLM, type="response")-y)^2)     ) )  res.RMS &lt;- as.matrix(     data.frame(         LM=sqrt(mean((predict(LM)-y)^2)),         LOG.LM=sqrt(mean((exp(predict(LOG.LM))-y)^2)),         LOG.GAUSS.GLM=sqrt(mean((predict(LOG.GAUSS.GLM, type="response")-y)^2)),         LOG.GAMMA.GLM=sqrt(mean((predict(LOG.GAMMA.GLM, type="response")-y)^2))     ) )  png("stats.png", height=7, width=10, units="in", res=300) #x11(height=7, width=10) par(mar=c(10,5,2,1), mfcol=c(1,3), cex=1, ps=12) barplot(res.AIC, main="AIC", las=2) barplot(res.SS, main="SS", las=2) barplot(res.RMS, main="RMS", las=2) dev.off() What makes the number of neutrons the number of proton similar? What is a “protected” or "highly active" question? I have a Transcend Storejet external USB hard disk. This is not an SSD, but a mechanical disk with rotating plates. I have formatted the whole disk, without partitioning, as NTFS. I have used mkntfs tool under Linux.  When plugged into a Linux machine, the system sees a drive with two partitions (/dev/sdc /dev/sdc1 /dev/sdc2). However, as I know it is a partitionless disk, I can mount the whole device (mount -t ntfs /dev/sdc /mnt) and it works without any problems.  When plugged into a MS Windows XP machine, the systems sees a disk with two unformatted partitions, and it does not assign a drive letter to either the whole disk, nor to any of the partitions.  Would anyone know how to get MS Windows to mount my disk as a NTFS superfloppy?  I have already tried removing old USB mounting points and residual devices using 'DriveCleanup'. It did not help.  By the way, I also have an external Kingston USB SSD, also formatted as NTFS superfloppy, without partitioning. However, this one is recognized and mounted normally by MS Windows. What determines which frames are inertial frames? I understand that you can (in principle) measure whether "free particles" (no forces) experience accelerations in order to tell whether a frame is inertial. But fundamentally, what determines which frames are inertial (i.e. what principle selects in which frames free particles will not appear to accelerate)? I've been told that the cosmic microwaves determine the ultimate rest frame of the universe, but that doesn't make sense to me, since one can still ask why that frame is an inertial frame.  Also, I understand that there are no real inertial frames in general relativity, but it seems like there certainly exists approximate inertial frames and we can ask why those frames are approximately inertial and not others. For example, in the frame of a person riding a merry go round, free particles appear to greatly accelerate; while in the frame of someone standing next to the merry go round there are no such great accelerations. Why does the guy (or gal) on the merry go round see free particles accelerating while the other guy doesn't.   And if you're gonna tell me that it's "the rest of the stuff in the universe" that determines whether the person on the merry go round sees free particles accelerate, I'll ask how you know that all that stuff is not spinning.  I hope this question sort of makes sense, it's been bothering me for a while and my study of relativity (most of special relativity and just the outline of general relativity) hasn't really clarified it for me much.