Let $R$ be a commutative ring with 1.      a) Suppose $R$ has no nonzero nilpotent elements (that is, $a^n=0$ implies $a=0$). If $f(X)=a_0+a_1X+\cdots+a_nX^n$ in $R\left[X\right]$ is a zero-divisor, prove that there is an element $b\ne0$ in $R$ such that $ba_0=ba_1=\cdots=ba_n=0$.      b) Do part a) dropping the assumption that $R$ has no nonzero nilpotent elements.   There is a question in the picture about rings... I can't do it. Can you help me please?  There are some solutions in  but I did not understand. This question was marked as duplicate.  Do  a) and b) have difference answer? In a) R has no nonzero nilpotents, but in b) dropping the assumption that R has no nonzero nilpotent elements I thought a) and b) have different solutions.   If in a) if R has no nonzero nilpotent elements, will you use this property in proof of a) ? and in b) there is no such a condition, so  what i can do ? Could you clarify a) and b) ? thank you for your helping ...
Let $R$ be commutative ring with no (nonzero) nilpotents. If $f(x) = a_0+a_1x+\cdots+a_nx^n$ is a zero divisor in $R[x]$, how do I show there's an element $b \ne 0$ in $R$ such that $ba_0=ba_1=\cdots=ba_n=0$?
Do 'learn by heart' & 'learn by rote' mean the same? Here in India, both the phrases learning by heart and learning by rote are taken to have the same meaning, i.e., blind memorisation without true understanding.    However, some sources say that to learn something by heart implies that one knows something so well that it has been thoroughly internalised and imbibed.    So is it wrong to conflate the two? A Book for abstract Algebra I am self learning abstract algebra. I am using the book Algebra by Serge Lang. The book has different definitions for some algebraic structures. (For example, according to that book rings are defined to have multiplicative identities. Also modules are defined slightly differently....etc) Given that I like the book, is it OK to keep reading this book or should I get another one?  Thank you How do I correct an HSA distribution when I was refunded by a health provider? Difference between get "off of" and "off" Mobile chat "you have been suspended" notification is too ambiguous Earlier today, I was suspended from chat due to an inappropriate message (I totally deserved it, but that's not the point). I looked at my phone, and this is all that it told me:    ...which confused me because chat was still moving as normal. I didn't realize that I had been suspended until I checked on my computer to see what the heck was going on.  To me, "This room is read-only" sounds like some sort of database lockup or something related specifically to the room, not the user. It doesn't give any feedback to indicate that the room will be "read-only" for 30 minutes, and doesn't mention that all other rooms are also "read-only". Even a message saying just "You have been suspended from chat" would be more helpful. I see ads to other SE sites regularly on the sidebar of SO. Are these questions chosen by hand, or algorithmically? The reason I ask is that there was an ad pointing to  on Seasoned Advice. I'm all for a good laugh I suppose, but is this the kind of question that should be highlighted?  It's obviously a thriving community, but if this were my first exposure to that community, and I saw that the highest-rated answer -- from the user with the highest reputation -- was (and I paraphrase only lightly):  &quot;Why yes, there is tool that can cut cherry tomatoes in half.  It's fantastic for the job.  It's called a freakin' KNIFE!&quot;  would I ever want to visit again, let alone ask a question over there? First impressions count for a lot, and that one missed the mark IMHO. If the selection method is algorithmic, I suppose there's no reliable way to detect sarcasm in a highly-rated answer, but if it's manual, weeeellllllllll ... :) Why does $\sum_{k=1}^{\infty}\frac{{\sin(k)}}{k}={\frac{\pi-1}{2}}$? Inspired by  (and far more straightforward, I am guessing), Mathematica tells us that $$\sum_{k=1}^{\infty}\dfrac{{\sin(k)}}{k}$$ converges to $\dfrac{\pi-1}{2}$.   Presumably, this can be derived from the similarity of the Leibniz expansion of $\pi$ $$4\sum_{k=1}^{\infty}\dfrac{(-1)^{k+1}}{2k-1}$$to the expansion of $\sin(x)$ as $$\sum_{k=0}^{\infty}\dfrac{(-1)^k}{(2k+1)!}x^{2k+1},$$ but I can't see how...  Could someone please explain how $\dfrac{\pi-1}{2}$ is arrived at? I'tm trying to show in SQLcmd window the results of these queries:  SELECT SYSDATETIME() AS "date";  PRINT 'EXTRAÍDO POR:' SELECT SUSER_NAME() AS "Owner"  PRINT 'PASSWORD SETTINGS'; exec xp_loginconfig;  PRINT 'PASSWORD SETTINGS'; select * from sys.sql_logins;   And using this command in SQLcmd:  sqlcmd -S myServer -i inputpath -s, -o outputPath(like C:\log.xls) -e   So the sqlcmd output the file and does not show nothing in sqlcmd screen. How can i print these "Print" commands in the sqlcmd screen? (command promt).  When I run it on SSMS works well, like:  (1 row affected) OWNER:  (1 row affected) PASSWORD SETTINGS  (8 rows affected) PASSWORD SETTINGS  I would like to show in the prompt command this, like in the SSMS.  Thanks! Evaluate the sum $\sum_{k=1}^n {n \choose k-1} {n \choose k}$ Evaluate the summation of: $$ \sum_{k=1}^n {n \choose k-1} {n \choose k} $$ I have been trying to solve this problem by translating C(n, k-1) into C(n, k), because I know that: $$ \sum_{k=1}^n {n \choose k}^2={2n \choose n} $$ However, I haven't been having any luck. Am I on the right track? What am I doing wrong? What are attention mechanisms exactly? Attention mechanisms have been used in various Deep Learning papers in the last few years. Ilya Sutskever, head of research at Open AI, has enthusiastically praised them:    Eugenio Culurciello at Purdue University has claimed that RNNs and LSTMs should be abandoned in favor of purely attention-based neural networks:    This seems an exaggeration, but it's undeniable that purely attention-based models have done quite well in sequence modeling tasks: we all know about the aptly named paper from Google,   However, what exactly are attention-based models? I've yet to find a clear explanation of such models. Suppose I want to forecast the new values of a multivariate time series, given its historical values. It's quite clear how to do that with an RNN having LSTM cells. How would I do the same with an attention-based model? Find the Unit Vector of a Three Dimensional Vector Control 220V AC line using MCU Make locking posts more granular Set an alias on Bourne shell I am using a scrtipt with instruction 'SH -c command', where command is an alias from bash, this alias can not be interpreted into Bourne shell. ¿Do you have any idea for set this alias into Bourne shell and getting that it works in the new shell? Thanks everyone ! biblatex, biber, is it possible to \printbibliography between two years? With biblatex and Biber, is it possible to print all the bibliography (\printbibliography) from (let's say) 2003 to 2008 in one section? And then in another section print all the bibliography from 2009 to 2016? Where can I find medicine? I know it is possible to be stung by bees in Animal Crossing: New Leaf.   I learned that the hard way when I was trying to find my furniture tree. Now, I have an eye swollen shut and all of my towns people are making fun of me. They're all being kind enough to inform me that I need Medicine, but they seem to be enjoying themselves at my expense too much to tell me where to actually find the Medicine.  Where can i get medicine? I'd really like it if my townspeople stopped making fun of me. This question is here just to avoid you choosing the wrong Ubuntu version number.  So, this is not about:     nor about   nor   nor   nor   nor .   So in the answer below a simple guide as to what Ubuntu version is good for you, independent of future releases! The square root of a prime number is irrational If $p$ is a prime number, then $\sqrt{p}$ is irrational.  I know that this question has been asked but I just want to make sure that my method is clear. My method is as follows:  Let us assume that the square root of the prime number $p$ is rational. Hence we can write $\sqrt{p} = \frac{a}{b}$. (In their lowest form.) Then $p = \frac{a^2}{b^2}$, and so $p b^2 = a^2$. Hence $p$ divides $a^2$, so $p$ divides $a$. Substitute $a$ by $pk$. Find out that $p$ divides $b$. Hence this is a contradiction as they should be relatively prime, i.e., gcd$(a,b)=1$. C# Lambda expressions: Why should I use them? I have quickly read over the  documentation.  This kind of example has helped me to understand better, though:   delegate int del(int i); del myDelegate = x =&gt; x * x; int j = myDelegate(5); //j = 25   Still, I don't understand why it's such an innovation. It's just a method that dies when the "method variable" ends, right? Why should I use this instead of a real method? Linear Discriminant Analysis for $p=1$ I'm studying 'Introduction to Statistical Learning' by James, Witten, Hastie, Tibshirani.   In page 139, of their book, they began by introducing Bayes' Theorem $p_k(X)=P(Y=k|X=x) = \dfrac{\pi_kf_k(x)}{\sum_{l=1}^k \pi_l f_l(x)}$. $\pi$ is not mathematical constant, but denotes the prior probability. Nothing is strange in this equation.   The book claims that it wants to obtain an estimate for $f_k(x)$ that it can plug into the equation given above. To estimate $f_k(x)$, it assumes that is normal. In the one dimensional setting, $f_k(x)=\dfrac{1}{\sqrt{2\pi}\sigma}\exp(-\dfrac{1}{2\sigma^2}(x-\mu_k)^2)$, where $\mu_k$ and $\sigma^2_k$ are the mean and variance for the $k$th class. It is assumed that $\sigma^2_1 = \sigma^2_2 = \cdots = \sigma^2_K$. (I began to get confused from the last statement.)   Plugging $f_k$ into $p_x$, you have this quite messy equation (1) :   $$p_x(k)=\dfrac{\pi_k \frac{1}{\sqrt{2\pi}\sigma}\exp(-\frac{1}{2\sigma^2}(x-\mu_k)^2)}{\sum_{l=1}^K \pi_l \frac{1}{\sqrt{2\pi}\sigma}\exp(-\frac{1}{2\sigma^2}(x-\mu_l)^2)}. $$  Again, no surprises here since it is just substitution.     The Bayes' Classifier involves assigning an observation to the class for which equation (1) is the largest. Taking the log of Equation (1) and rearranging terms, it is not hard to show that this is equivalent to assigning the observation to the class for which the following is the largest:  $$\delta_k(x)=x \cdot \dfrac{\mu_k}{\sigma^2} - \dfrac{\mu_k^2}{2\sigma^2} + \log(\pi_k) $$  Question: I do not understand where this came from, and what it means. I tried doing the log of equation and it doesn't become this. Are we taking the derivative somewhere here, since this is the largest observation?