From Feeblemind's spell description,     On a failed save, the creature’s Intelligence and Charisma scores become 1.   The spell's effects are listed as "Instantaneous", which leads me to my question:  Does this prevent the effects of items like Ioun Stones which add to the score, or Headbands of Intellect which set the score to 19, from going into effect, or does the spell have an ongoing magic that keeps the stats at 1 until the save is made or the Feeblemind is removed through on of the listed spells?  If it does not prevent the intelligence/charisma stats from being raised through items, are the listed effects (being unable to speak/cast spells) caused by the low scores or a separate part of the spell's effects?
The description of the  says:     Your Intelligence score is 19 while you wear this headband. It has no   effect on you if your Intelligence is already 19 or higher.   The  spell description says that my Intelligence score becomes 1 on a failed save:     [...] On a failed save, the creature's Intelligence and Charisma   scores become 1. The creature can't cast spells, activate magic items,   understand language, or communicate in any intelligible way. [...]   If I am affected by Feeblemind and I am wearing the Headband of Intellect, would I have an Intelligence score of 19 or 1?   Also, what about the other effects like not being able to cast, activate magic items, understand languages or communicate in any way? Those seem Intelligence-related, but are mentioned additionally to the reduction.   If the Intelligence score becomes 19, are the other effects still active?
When training a neural network using the back-propagation algorithm, the gradient descent method is used to determine the weight updates. My question is: Rather than using gradient descent method to slowly locate the minimum point with respect to a certain weight, why don't we just set the derivative $\frac{d(\text{Error})}{dw}=0$, and find the value of weight $w$ which minimizes the error? Also, why are we sure that the error function in back-propagation will be a minimum? Can't it turn out the error function is a maximum instead? Is there a specific property of the squashing functions that guarantees that a network with any number of hidden nodes with arbitrary weights and input vectors will always give an error function that has some minima? Totally bounded, complete $\implies$ compact In computer science we discuss an abstract machine called a "deterministic finite automaton". The standard initialism for this term is "DFA". This makes sense in the singular usage of the initialism.  However, the pluralization of the word "automaton" is "automata". One speaks of "an automaton" or "many automata". Consequently, it seems intuitive to form an initialism of the phrase "deterministic finite automata" as "DFA".   This does not seem correct, as "DFA" could be either plural or singular. On the other hand, "DFAs" also does not seem correct because it would seem to expand to "deterministic finite automatons", a phrase which no self-respecting computer scientist would ever utter.   This appears to be a duplicate of the question here   But that question was never clearly resolved. What to do? Why {are you / you are} making noise? I always get confused between these two sentences:     Why are you making noise?      Why you are making noise?   Could anyone put light in the differences between the two? There was a book (it actually had a second book as well) where a guy gets paid with a group of others to go to a planet that is enclosed in a metallic sphere.   There are many species in this planet. I don't recall if they actually met the races in the first or the second book but there an incident where an alien in the first book ate fruit from a tree that removed any signs of gender from it. In windows we have an option to view recently opened media files as my recent documents, I was  wondering does there exists something like that in Ubuntu?  via terminal or via GUI? Truncated 200GB table but disk space not released SQL Azure and Full-Text Catalogs, Indexes and Searching divides, not divides and cardinalities In group theory it happens very often that you want to say: "The order of $H$ divides / does not divide the order of $G$." But the length of | is then always the same:  $ |H| | |G| $ produces |H|||G|  which is not ideal at all. (The negation \nmid has just this length too.) The length of "divides" should be longer than the "cardinality length". I could use   $ |H| \big| |G|$  but then there is no good way to say "does not divide" with the same length. Also, \big| is no solution when the expression has to be used in subscripts.   I thought it was just me, but I asked other group theorists, and nobody had a solution. I hope there is one.  I am seeking a division sign which is a little longer than the usual | , allows negation (with the same length) and proportionally correct use in subscripts (also under \sum etc.). It does not look professional if the "order sign" has the same length as the "divides" sign. (And what about combinations with absolute values, norms - although personally I don't use them as often as group orders.) How to make beveled 90 degree corners on a curve better? Greets  This is exercise 15.d chapter 3 of Stein &amp; Shakarchi's "Complex Analysis", they hint: "Use the maximum modulus principle", but I didn't see how to do the exercise with this hint rightaway, instead I knew how to do it with the Casorati-Weiestrass Theorem, here is my answer:  Define $g(z)=f(1/z)$ for $z\neq{0}$,then by the hypothesis we must have that for any $\epsilon&gt;0$ $g(D_{\epsilon&gt;0}(0)-\{0\})$ is not dense in $\mathbb{C}$, then the singularity at $0$ of $g$ is not essential, this implies $f$ must be a polynomial, but if $f$ is a non-constant polynomial, it is easy to see that its real part must be unbounded, so $f$ must be constant.  I would like to know an answer with the the maximum modulus principle.  Thanks Where's the Rainbow Jetpack gone in Jetpack Joyride? How do you unit test private methods? When we're dealing with problems in electrostatics (especially when we use Gauss' law) we often refer to the density of electric , which is inversely proportional to the radius in the case of a single point charge (all field lines are directed radially).   My question may sound dumb, despite the fact that this concept is quite intuitive, but if you think about it there is actually an infinite amount of field lines which we can draw everywhere (one through every point), so speaking of an area where field lines are more "dense" or "sparse" doesn't make much sense to me.  With this in mind, why can we still use such a concept? Why does it really work? I'm just trying to review basic terminal commands. Having said that, how do I create a text file using the terminal only? "Baggage" versus "luggage" Conditional clause (then) In this first instance the main clause only stands alone if you  omit (then).  But in the other example it clearly has a main clause. So would this be classed as an embedded main clause as it only works as a independent clause if it's adjusted and or if it's joined with a dependent clause.  If I have enough money, then I will buy a new car.  If it rains, the picnic will be cancelled.  The picnic will be cancelled if it rains. Links to the Wayback Machine are broken in chat transcript is an example of the bug. It looks like this in regular chat:  That link points to: http://web.archive.org/web/20080409050311/http://personalpages.manchester.ac.uk/staff/daryn.lehoux/Tropes.pdf  In the transcript, it looks like this:  That link points to: http://web.archive.org/web/20080409050311/%3Ca%20href=  ... which doesn't work so well! Could this be fixed? I'm not sure if this impacts links to elsewhere. Calculate relative time in C# Given a specific DateTime value, how do I display relative time, like:   2 hours ago 3 days ago a month ago Transforming the dummy values to be able to take logs I have a panel data model with double-log functional form. I have 4 variables, one of which is a dummy. What is the best way to transform the values of 0 for my dummy to be able to take natural logs (since you can't take logs from zero)? I have found 2 options so far, but I dont know which is the best (or perhaps there is a 3rd option).  1) Transform all the values of 0 into a very small value (0.00000000001) and then take the logs. I'm not sure this wouldn't still change the outcome of my model quite a bit. 2) Change the values of 0 into 1 and the dummy values of 1 into e (the base of natural logarithm). The log of this newly defined dummy then takes on the values of zero and one and the interpretation of my betas would remain the same.