I notice that the Android Stack Exchange app shows my SO  and  tags have upvote scores of 111 and 103 respectively but via my desktop browser it shows that I have 108 and 100 respectively. This difference has lasted for over 4 days, is there a lag or difference in the calculation? All other tags have correct scores and number of answers posted.
I checked yesterday and today the new homepage in the Android app. Very surprised I saw that I would almost reach a silver tag badge, that confused be because I always take a look on possible badges I can get. However I compared the score with the website and I got a total different results. See this two screenshots:
How long does mana from Burning-Tree Emissary stay around? Does mana added to your pool from  get destroyed when the card that added it is destroyed? What is the maximum number of Locations Discovered that one can achieve in Skyrim? I found this confusing when I use the neural network toolbox in Matlab. It divided the raw data set into three parts:   training set validation set test set   I notice in many training or learning algorithm, the data is often divided into 2 parts, the training set and the test set.  My questions are:   what is the difference between validation set and test set?  Is the validation set really specific to neural network? Or it is optional. To go further, is there a difference between validation and testing in context of machine learning? How fast does gravity propagate? A thought experiment: Imagine the Sun is suddenly removed. We wouldn't notice a difference for 8 minutes, because that's how long light takes to get from the Sun's surface to Earth.   However, what about the Sun's gravitational effect? If gravity propagates at the speed of light, for 8 minutes the Earth will continue to follow an orbit around nothing. If however, gravity is due to a distortion of spacetime, this distortion will cease to exist as soon as the mass is removed, thus the Earth will leave through the orbit tangent, so we could observe the Sun's disappearance more quickly.  What is the state of the research around such a thought experiment? Can this be inferred from observation? passive Vs active or omission of 'which is' What is the part of speech of 'regarded' in the following?     "a quality of beauty and intensity of emotion regarded as characteristic of poems"    Why isn't it "... [which is] regarded ..."?  And in another case:      "a small lizard with wide feet, found especially in warm countries"     And also:      "Words used to describe writing or speech style"    In all these examples, why shouldn't the verbs be in their passive form (e.g. which is found, words that are used)?   I am a ESL learner and I am very confused by these usages! I've noticed the text of the Hot Meta Posts box is not within its limits. I guess this would happen for any question with a word that's long enough: How to extend USB beyond the recommended maximum cable length of 5m? I'm planning to use USB port for an application(from a device to a PC) but the distance between the device and the PC will be around 15m. The recommended maximum USB cable length is 5m.  How can I buffer the data without loosing any information, safely? Would a USB hub work? Python function attributes - uses and abuses Not many are aware of this feature, but Python's functions (and methods) can have . Behold:  &gt;&gt;&gt; def foo(x): ...     pass ...      &gt;&gt;&gt; foo.score = 10 &gt;&gt;&gt; dir(foo) ['__call__', '__class__', '__delattr__', '__dict__', '__doc__', '__get__', '__getattribute__', '__hash__', '__init__', '__module__', '__name__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__str__', 'func_closure', 'func_code', 'func_defaults', 'func_dict', 'func_doc', 'func_globals', 'func_name', 'score'] &gt;&gt;&gt; foo.score 10 &gt;&gt;&gt; foo.score += 1 &gt;&gt;&gt; foo.score 11   What are the possible uses and abuses of this feature in Python ? One good use I'm aware of is 's usage of the docstring to associate a syntax rule with a method. But what about custom attributes ? Are there good reasons to use them ? Does herd behavior influence the SO sites? Are you influenced by existing votes? That is, if a question or answer has a large number of up votes, are you more likely to vote it up (and similar for down)?  The reason I'm putting this question is this: on these sites we see how other people vote before we do. This almost certainly influences us (see resources, below) - just as we can be influenced by our  (people often naturally pick the busy one).  This trend may also be further influenced by rep - do we give more weight to the answer of someone with 10K rep than someone with 10 - even if they both have e.g. zero votes?  And if this does happen, is it even a problem?  I'm not looking here for solutions - right now I'm just curious as to whether this is something you recognise.  Clarification edit: I'm referring to voting here. Example: if you see a question or answer with 20 plus votes, are you more likely to vote it up than if it has no votes, or a negative number vote?  Bounty: I've been so impressed at the quality of answers and comments here that I'm offering a small bounty to encourage more great responses and discussion.  Wrapped up: Bounty awarded to the answer that received the most votes. In light of the question, it only seemed appropriate...  Resources: How do I pipe terminal standard output (stdout) to the clipboard? For example,   Say I want to list the contents of a folder and directly paste them into a chat window for a friend to see.    I realize I could do ls &gt; filename.txt to create a file (filename.txt) with those contents; I'd then have to open or print the file and manually select and copy the text block (which can be annoying/tedious.)  I clearly could also select and copy the output of ls directly from within the terminal window.  It would be much faster/easier to simply pipe standard output to the clipboard.  What terminal command allows me to do this? Where is the itoa function in Linux? I'm looking for a single word, for someone who...   keeps seeing everything that is wrong with everybody else.  never seems to see the good of other people, only the bad things. points at others, as if he forgets he has weaknesses himself. does not brag about himself, he just seems to be dissatisfied with everyone else.   I prefer a word that is as unambiguous and clear-cut as possible. How do I set up a supply line? UMVUE of $e^{-\lambda}$ from poisson distribution Let $X_1,\ldots,X_n \sim$ Poisson$(\lambda)$. I wish to find UMVUE of $e^{-\lambda}$. Here $\overline{X}_n$ is complete and sufficient for $\lambda$ (hence for $e^{-\lambda}$??). Define $Y_i=1$ if $X_i=0,$ $Y_i=0$ otherwise. Clearly (I checked!) each $Y_i$ and hence $\overline{Y}_n$ is unbiased for $e^{-\lambda}$. Then I should be able to use the Lehmann Scheffe theorem to deduce the UMVUE. The estimator I get looks like $$\frac{1}{n} E\left\{\#X_i:X_i=0 \mid \sum_{i=1}^n X_i\right\}$$ whereas the correct answer is $$\left(\frac{n-1}{n}\right)^{\sum_{i=1}^n X_i}$$ I'd appreciate if anyone lets me know where I'm going wrong and guides me into the right path. Thank you. How can I determine if someone's SSH key contains an empty passphrase? Some of my Linux &amp; FreeBSD systems have dozens of users. Staff will use these "ssh gateway" nodes to SSH into other internal servers.  We're concerned that some of these people use an unencrypted private SSH key (A key without a . , because if a cracker ever gained access to their account on this machine, they could steal the private key and now have access to any machine which uses this same key. For security reasons, we require all users to encrypt their private SSH keys with a passphrase.  How can I tell if a private key is not-encrypted (e.g. Does not contain a passphrase)? Is there a different method to do this on an ASCII-armored key vs. a non-ASCII-armored key?  Update:  To clarify, assume I have superuser access on the machine and I can read everybody's private keys. I have a question related to modeling short time-series. It is not a question , but how. What method would you recommend for modeling (very) short time-series (say of length $T \leq 20$)? By "best" I mean here the most robust one, that is the least prone to errors due the fact of limited numbers of observations. With short series single observations could influence the forecast, so the method should provide a cautious estimate of errors and possible variability connected to the forecast. I am generally interested in univariate time-series but it would be also interesting to know about other methods. We have an instance of SQL Server 2008 installed on a customer server. The customer's IT department is in charge of the various backups of the machine.  The SQL Server log shows there is a full backup every day at 7 PM but we can't find evidence of any plan scheduled in SQL Server.  The technicians we contacted couldn't tell us if there was some sort of automatic backup, all they told is that the entire machine is being backup up.  Using a script I found in  I found out that the physical device name is a GUID and that this means that this is an external backup process:  USE [msdb] GO  SELECT      [bs].[database_name],      [bs].[backup_start_date],      [bs].[backup_finish_date],      [bs].Server_name,     [bs].user_name AS [BackupCreator] ,     [bmf].physical_device_name FROM msdb..backupset bs   INNER JOIN msdb..backupmediafamily bmf ON [bs].[media_set_id] = [bmf].[media_set_id]  ORDER BY [bs].[backup_start_date] DESC   This is a row from the above query:     db_name 2015-09-16 19:01:23.000   2015-09-16 19:01:28.000SERVER_NAME  NT AUTHORITY\SYSTEM{424F084A-F35D-4A66-8FC7-072268A89A77} 5   Moreover the backup start and finish date spans only for 5 seconds, so I guess it's clear it's not a job of sql server.  This is a line from the log:     2015-09-03 19:02:30.71 Backup   Database backed up.   Database: db_name, creation date(time): 2012/10/12(20:52:11), pages dumped: 3290021,   first LSN: 276028:152755:172, last LSN: 276028:152827:1, number of dump devices: 1,   device information:   (FILE=1, TYPE=VIRTUAL_DEVICE: {'{95380B0A-D50B-408F-B95F-1AB8975BA7F8}5'}).   This is an informational message only. No user action is required.   So, since they can't help us what can I do to track down the process responsible of the backups? We need this because we want to coordinate the backup in an ordered manner, and do the transaction log backups too in order to keep the log at a reasonable size (now we do shrink the log every week, and this is not the good way to go). I am trying to make a map where you have to make a village from scratch, and I need help. I'm trying to make a /clone command happen relative to where a mob that's named house is, and I cant figure it out. Any help? Proof that any simple connected graph has at least 2 non-cut vertices. I'm trying to prove that any simple connected graph with at least $3$ vertices ($|V| \ge 3$) has at least $2$ vertices whose removal will not lead to the increment of number of components. In other words, there are at least $2$ vertices that are non-cut vertices.  Attempt at solution:   I tried to prove it using induction by the number of vertices: $n - t \ge 2$, where $n$ is the number of vertices our graph has, and $t$ is a number of cut vertices.   Base  Let $n =3$, then the graph will look like this:  $О-О-О$  Clearly, it has one cut vertex (the middle one). So, $3-1 \ge 2$ holds.  Or it can be a full graph, then $3 - 0 \ge 2$ also holds. Assumption  Let $n = k$, and the formula holds, $k - t &gt;= 2$ Step  Prove for $n = k + 1$ If we add one vertex to the graph, it could either be a cut vertex or non-cut vertex. In case it is a cut vertex, we have $$\begin{align*}&amp;(k+1) - (t+1) \ge 2\\ &amp;k + 1 - t - t\ge 2\\ &amp;k\ge 2\end{align*}$$   In case it is not a cut vertex...and I'm stuck here, because anything can happen. The number of cut vertices might increase, might decrease, or stay the same.  I'm sure there is better and shorter proof to this, and I really hope someone could help me. Why can partial derivatives be exchanged? In the   post in this stack exchange, one of the answers to the questions of do partial derivatives commute is: Second order partial derivatives commute if f is $C^2$ (i.e. all the second partial derivatives exist and are continuous). This is sometimes called Schwarz's Theorem or Clairaut's Theorem. This theorem is in my textbooks, yet I cannot seem to find the proof in them. I have tried proving the theorem yet I have gotten stuck. So, what is the proof of Clairaut's Theorem, or why do partial derivatives commute? If the proof is too long, a link to the proof with an intuitive explanation will be sufficient.