how to change logon screen for domain user in windows 7
How can I change the Windows 7 Logon Screen wallpaper?
What is the pythonic way to avoid default parameters that are empty lists? Sometimes it seems natural to have a default parameter which is an empty list. Yet . If for example, I have a function: def my_func(working_list=[]):     working_list.append(&quot;a&quot;)     print(working_list)  The first time it is called the default will work, but calls after that will update the existing list (with one &quot;a&quot; each call) and print the updated version. So, what is the pythonic way to get the behavior I desire (a fresh list on each call)? Does Perl have PHP-like dynamic variables? MAXDOP not working? I wanted to test out MAXDOP on my computer. So I set MAXDOP to 2 for a specific query. However, when I looked at my logical processors in Task Manager as I ran the query, it looked like they were all being used. I thought that it would only be using 2 logical processors if MAXDOP was set to 2? Does anyone know what is happening? Please see image below.  Another issue is, the DOP returned by the execution plan said 1. Now I know that setting MAXDOP does not mean SQL Server will actually use the number set. However, given that it seemed all my 4 logical processors were being used to process the query, it made it even more strange to see DOP 1.  This is the query I ran:   This was what happened as I ran it (i.e. it looks like all 4 logical processors are being used to run the query): This is a lake of approximately 13 ha with 81 sampled depth points in about 10 transect lines:    Previously in ARCgis with a 50 ha lake and about a 100 depth sampling points, I got decent output with the TopotoRaster tool. However, no such exact equivalent seems to exist with QGIS or open source software.  In QGIS, I got the interpolated raster below, using the TIN method in the Raster Interpolation plugin. However, this seemed to be a lucky outcome, when I tried to repeat, I got different results (unsatisfactory) in spite of not really varying any parameter.    These are more urban (constructed) tanks than lakes, therefore, they are fairly regular in their bed profile, hence the low point sampling density. Some articles seemed to suggest Inverse Distance Weighting (IDW) as the most suitable technique, yet I seemed to get the worst results with that (possibly owing to low point density).  Are there any heuristics which can be employed here considering the size of the lake, its regular profile and the point sampling density to arrive at which interpolation method is apt? (between Kriging, IDW, Bilinear, Cubic convolution, TIN or spline)  Or is it always a bit of trial and error? How can I install Ubuntu on a headless machine? I have a headless storage server with preconfigured Windows Home Server. How can I install Ubuntu without a display?  Do I have to build a custom install flash drive? If so, what would be the basic procedure? Is there a program (like unetbootin) to do this? It is will known that increasing cooling of a metal casting will lead to finer micro-structure which mean higher mechanical properties. If I have 2 molds one is thick copper die ,&amp; second is just thin-walled copper cup or mold cooled by water. which one of them excepted to cool the molten metal i.e. aluminium faster ?   by calculation it seems that copper die have higher cooling power as it has higher thermal diffusivity , but in real life it seems water have more cooling power. I am so confused. Given a $k$-manifold $M$, such that $\partial M$ is a $(k-1)$-manifold, there is a standard way in which $\partial M$ inherits the orientation of $M$. So if $M$ is oriented by the form field $\omega$, then $\omega_\partial=\omega(v_{\text{out}},v_1,\dots,v_{k-1})$ orients $\partial M$, where the $v_1,\dots,v_{k-1}$ are basis vectors for a tangent space on a point of the boundary, and $v_\text{out}$ is an outward pointing vector (see here: , which follows the exposition of Hubbard &amp; Hubbard).  In practice I find this very difficult to interpret. How can one find this $v_\text{out}$ in practice?   For instance, take $M$ to be defined by $z=x^2+y^2$ for $x\ge0$ (technically a manifold with boundary, in fact a half-paraboloid). It's a fact that $\partial M$ is defined by the parabola $z=y^2$. If $M$ is oriented by $dx\wedge dy$, how does this induce an orientation on the boundary (in fact we should obtain a 1-form that induces an orientation on the boundary)?   Note: I find the whole discussion of boundary orientation to be rather clumsy in its exposition. In the case of surfaces inducing orientations on boundary curves, I was originally taught to imagine that the normal vector that induces the surface orientation is me walking on the surface. This normal should walk along the boundary such that the surface lies to its left. OK - but how does this translate to the $v_{\text{out}}$ interpretation, so that we can generalize to other dimensions easily?)  Edit: An ideal answer would merge the intuitive approach with the rigorous approach, if possible. I would grateful to anybody who could help order my (at present confused) understanding! Can inductor voltage and capacitor current change abruptly? I understand that inductor current and capacitor voltage cannot change abruptly, but can inductor voltage and capacitor current change abruptly?  I have a feeling the answer is no but I cannot explain why. How do I set up a folder so that anything created in it inherits permissions? 14 months ago, an  supplement was published that discussed how the ranger described in the Player's Handbook was under powered. These rules reimagined the ranger's abilities, and suggested that an official version would be released later.     Finally, we come to implementation. If this iteration of the ranger, or a future revision of it, grades high enough, our plan is to present it as a revised ranger in a future D&amp;D sourcebook.   Does that Sourcebook exist yet? If not, have the devs given an update or told us their intentions? Limit of $L^p$ norm Could someone help me prove that given a finite measure space $(X, \mathcal{M}, \sigma)$ and a measurable function $f:X\to\mathbb{R}$ in $L^\infty$ and some $L^q$, $\displaystyle\lim_{p\to\infty}\|f\|_p=\|f\|_\infty$?    I don't know where to start. This looks like a question asked , but it isn't.  $$T(n)=\begin{cases} T (\sqrt{n}) + 1 \quad &amp; \text{ if } n&gt;1 \\  1 &amp; \text{ if }n=1\end{cases}$$  My professor gave this to me in class yesterday. This is where I'm stuck:   $$T(n) =  T(n^{1/2})+1 =  T(n^{1/4})+2 = T(n^{1/8})+3 = \dots =   T(n^{1/ 2 ^k})+k$$  Now this will continue till  $$n^{1/ 2 ^k}=1$$  How do I proceed ahead? If I take log on both sides, then RHS becomes zero. How do I solve the relation?  I don't want to use the Master theorem, I want to know where and why am I stuck. Detecting current iPhone input language how to read xml file from url using php Format timedelta to string How to implement a \tomorrow in latex I was asked how to implement a \tomorrow macro in TeX/LaTeX. While I could come up with a reasonably good solution, working for one document class, I don't see how that could be achieved in a document class agnostic way.  I found , but even though the date arithmetic may be of use, it assumes a specific format for the date (which also is wrong for the locale I reside in).  Does anyone have a reasonably portable solution? Is this even possible? Falsely accused witch befriends transforming dragon she was to be sacrificed to Story is in a medievalish setting and starts with a woman who has been falsely accused of being a witch being taken by 2 men to be sacrificed to a dragon.  She ends up befriending the (male) dragon, who is able to transform into various forms, including human, and can speak only the language of whatever form he is in. e.g. can speak English in human form, but can't in dragon form.  He needs to return to his dragon form every day at sunrise or he dies.  Contact with iron or steel causes him pain and prevents him from transforming.  Near the end of the book, he's been put in handcuffs by one of the two men from the start and the woman has to get the assistance of the other one (village blacksmith?) to remove them before sunrise, which they manage to do just in time.  I think I read it maybe 10 years ago.    I also remember it was a very short book, probably only about 100 pages. (Automatic Bike Project) amount of torque required to change gears? I am planning to build an electronically controlled automatic bike transmission for my senior design project. I'm personally more of an electrical guy, so dealing with the mechanics is somewhat new to me. I would have loved to use an off-the-shelf electronic derailleur, but alas, they are too cost prohibitive (the school has allotted a budget of $115 per student and we're a group of two, so we have $230 to spend). So I'm going to need to make my own like several other people have done.  I am planning on using the bike's current derailleurs and replacing the hand shifters with motors of some sort to pull on the cables. Of course, we're going to need a certain amount of torque to shift up (and much less for shifting down) and a holding torque to ensure that we don't accidentally slip down a gear.   I have not bought a bike yet, I'm looking at a Diamondback bike that I found on Craigslist (it looks like a hybrid bike). So I'm wondering if there are any average measurements for the required torque.  And of course, I'm sure there are many people more experienced in bicycling than I am. So if you have a better solution, please feel free to shout it out. I'm all ears. How to store lots of small text in a SQL Server database? Let $a=p_1^{x_1}p_2^{x_2}\cdots\cdot p_q^{x_q}$ and $b=p_1^{y_1}p_2^{y_2}\cdots p_r^{x_r}$ ,   say — Since gcd(a,b) is the largest common divisor of a and b and is divisible by any other common divisor of the two,   GCD$(a,b)=p_1^{\min(x_1,y_1)}p_2^{\min (x_2,y_2)} \cdots p_q^{\min (x_q,y_q)}$  LCM$(a,b)= p_1^{\max(x_1,y_1)}p_2^{\max(x_2,y_2)}\cdots p_r^{\max (x_r,y_r)}$  I understand GCD(a,b) has to divide both $a,b$. Therefore the exponent of any prime factor $p_i$ in GCD has to be in both $a,b$  — therefore $p_i^{\min(x_i, y_i)}$. But I'm muddled and anxious. Why does $\min$ appear in GREATEST common divisor? Why does $\max$ appear in LOWEST common multiple?