Earth is the only planet we know of where life exists.    This sentence is  from the commentary of Planet Earth.  Why it is  know of in this sentence? Can it be know about？  What’s the difference between know of and know about?
Is there a difference between "think of something" and "think about something"? I've also met "have heard of/about something".
Where can I find Ghost/Poison/Psychic type Pokémon? Anyone can optimized this code for better explanation and easy to understand? How can I find $f(0)$, $f'(0)$, and $f'(x)$ given that  $f(x+y)=f(x)+f(y)+x^2y+xy^2$  and  $\lim_{x\to0}\frac{f(x)}{x}=1$. For which $a \in \mathbb{C} -\ \{0,1\}$ does the equation $f(z) = f(az) $ has a non constant solution $f$ with $f$ being analytical in a neighborhood of $0$.  My attempt:  First, we can see that any such solution must satisfy:  $f(z)=f(a^kz)$ for all $k \in \mathbb{N} $.  If $|a|&lt;1$:  The series $z_{k} = a^k$ converges to 0 which is an accumulation point, and $f(z_i)=f(z_j)$ for all $i, j\in \mathbb{N} $. Thus $f$ must be constant.  If $|a|=1$:  For all $a \neq 1$ , $f$ must be constant on any circle around $0$, so again $f$ must be constant.  My quesions are:   Am I correct with my consclusions?   Also, I'm stuck in the case where $|a|&gt;1$. Any ideas?  Thanks Singular verb after two noun phrases joined by "and" that can be thought of as a single thing Meaning of probability notations $P(z;d,w)$ and $P(z|d,w)$ What is the difference in meaning between the notation $P(z;d,w)$ and $P(z|d,w)$ which are commonly used in many books and papers? I want to upgrade my disk from MBR to GPT, and I tried using Windows' MBR2GPT.EXE tool to do the job. I used Windows' DISKPART tool to identify the disk I want to convert. However, this happened:  C:\WINDOWS\system32&gt;MBR2GPT.EXE /convert /disk:0 /allowfullos  MBR2GPT will now attempt to convert disk 0. If conversion is successful the disk can only be booted in GPT mode. These changes cannot be undone!  MBR2GPT: Attempting to convert disk 0 MBR2GPT: Retrieving layout of disk MBR2GPT: Validating layout, disk sector size is: 512 bytes Disk layout validation failed for disk 0 MBR2GPT: Conversion failed   and the conversion failed. Using Diskpart again, I get the following output:  DISKPART&gt; list disk    Disk ###  Status         Size     Free     Dyn  Gpt   --------  -------------  -------  -------  ---  --- * Disk 0    Online          465 GB      0 B   Disk 1    Online         3841 MB   960 KB  DISKPART&gt; select disk 0  Disk 0 is now the selected disk.  DISKPART&gt; list partition    Partition ###  Type              Size     Offset   -------------  ----------------  -------  -------   Partition 1    Primary            100 MB  1024 KB   Partition 2    Primary            464 GB   101 MB   Partition 3    Recovery           813 MB   464 GB   Partition 4    Recovery           511 MB   465 GB   Looking at the partitions on disk 0, there are 2 primary partitions and 2 hidden ones, I read  that the partitions might have something to do with the conversion failing, so I believe this is the culprit. If anyone could offer help converting my disk, that would be greatly appreciated. Number of onto functions Why does locking the rear tires on a vehicle cause it to spin? are often used in motor-sports and stunt driving to turn around tight corners.  Essentially, the driver applies the handbrake as he enters the turn, in order to "kick out" the back end and slide the vehicle around the corner.  However, applying the handbrake hard enough to lock the rear wheels while traveling straight will cause the rear of the vehicle to "kick out".  Given enough speed, the vehicle will spin 180 degrees.  Why do sliding wheels on a car want to "get in front" of rolling wheels? Is there an intelligent way to left-align the parts right of &amp; of the two cases environments shown below (if x >= 0, otherwise, if y &lt; 0, otherwise). I wonder if there is a better way than using manual spaces:  \begin{align*}  u(x) &amp;=   \begin{cases}    0        &amp; \text{if } x \geq 0 \\    1        &amp; \text{otherwise}   \end{cases}   \\  \tau &amp;=   \begin{cases}    a+b+c+d  &amp; \text{if } y &lt; 0 \\    1        &amp; \text{otherwise}   \end{cases} \end{align*} Is there a SATA cable which can connect to multiple disks? I have a motherboard with just few SATA slots but have to put quite few hard disks in the box, so naturally I easily ran out of free slots.  I wonder if there are forked cables (I have no idea what would be the name for these cables) so I can connect multiple hard disks to a single SATA slot on the motherboard?  PS. Speed is not essential here as all disks contain archived data. How can I decode HTML characters in C#? I have email addresses encoded with HTML character entities. Is there anything in .NET that can convert them to plain strings? What's the relationship between initial eigenvalues and sums of squared loadings in factor analysis? On the one hand I read in a comment  that:     You can't speak of "eigenvalues" after rotation, even orthogonal   rotation. Perhaps you mean sum of squared loadings for a principal   component, after rotation. When rotation is oblique, this sum of   squares tells nothing about the amount of variance explained, because   components aren't orthogonal anymore. So, you shouldn't report any   percentage of variance explained.   On the other hand, I sometimes read in books people saying things like:     The eigenvalues associated with each factor represent the variance   explained by that particular factor; SPSS also displays the eigenvalue   in terms of the percentage of variance explained (so factor 1 explains   31.696% of total variance). The first few factors explain relatively large amounts of variance (especially factor 1), whereas subsequent   factors explain only small amounts of variance. SPSS then extracts all   factors with eigenvalues greater than 1, which leaves us with four   factors. The eigenvalues associated with these factors are again   displayed (and the percentage of variance explained) in the columns   labelled Extraction Sums of Squared Loadings.   That text is from Field (2013) Discovering statistics using IBM SPSS, and this diagram accompanies it.    I'm wondering     Who is correct about whether it's possible to speak of eigenvalues after rotation? Would it matter if it was an oblique or orthogonal rotation?   Why are the "initial eigenvalues" different from the "extraction sums of squared loadings"? Which is a better measure of total variation explained by the factors (or principal components or whatever method is used)? Should I say that the first four factors explain 50.317% of variation, or 40.477%? Limits of dead reckoning using MEMS sensors I'm trying to track body parts relative to a person's torso. I see quite a few questions about using MEMS accelerometers and gyros for dead reckoning, and they confirm my suspicions that various factors greatly limit their usefulness for these sorts of applications, but I'm seeking clarification of these limits:   What exactly are these limits?  Other answers have addressed why these limits exist. Naturally the specifications the parts in the system in question and what is considered "acceptable error" for the system will both change the exact limits, but is there a single order of magnitude in time, or distance that I can expect dead reckoning to work? I'm well aware that over long distances (a few yards or so) the error becomes too large for most practical purposes, but what about within a few feet?  What can I do to improve these limits?  I'm currently looking at using an accelerometer and a gyro. What other sensors can I add to the system to improve the error rate? I know over longer distances a GPS can be used, but I doubt any consumer electronics grade GPS has fine enough resolution to help in my case.  Additionally, a general consensus seems to the only way to improve these limits past the point of improved sensors is to provide a reference not subject to error. Some systems solve this using cameras and markers.  What kind of reference points can a portable/wearable device provide?   I've seen the usage of radio waves to measure long distances accurately, but I can't tell if such a system could be accurate on such small scale (in terms of distance measured) using "off-the-shelf" components. Why are my objects in all layers? I'm running CentOS 7.0 build 1503. I'm trying to search for commands I don't know the name of by searching the man descriptions for multiple keywords using AND (e.g. search for a command containing the both words "create" and "group" in the description).  So I came across the command apropos (which is an alias for man -k). The default behaviour when given multiple keywords is to return any command matching any of the keywords, which isn't what I want. According to the man page the option -a specifies using AND, to return matches only when all words match.  But this isn't what I'm seeing in practice, so I need some help here - e.g. using Centos 7, if I do:  apropos create user   I see a huge list of commands, seemingly matching any command with create or user in the description, as expected. Noting the list includes an entry for the command 'useradd (8) - create a new user...'.  If I do:  apropos -a create user   I only get 2 commands (environ and open). This is what I'm confused by - I would expect it to return the command 'useradd (8) - create a new user', because i can see from the previous search that command does contain those words in the description. Also the 2 returned commands don't obviously seem to be anything about creating users. What am I doing wrong? I'm sure it's something embarrassingly obvious, for that I apologise in advance.  Thanks This post is an expansion of  For many graduated sites (eg Physics), moderators do not want to apply the unilateral close vote in all cases--it is better to let some community votes pile on first.  We only use the unilateral in obvious cases then. This renders the CV queue useless to us. If we &quot;skip&quot; something, we can't get back to it. If we say &quot;do not close&quot;, it's removed from the queue and our community can't see it. If we use &quot;close&quot;, we are using a unilateral mod vote--we don't want to do that. What I propose is a set of &quot;next/previous&quot; buttons, that let us navigate the queues, looking for closeable questions, and coming back to the others later. Thoughts? Update and bounty reason Due to the recent Great Flag Overhaul, mods no longer see close flags in the flag queue. Which means that the only way to get to them is via the review queue 1 Shog's solution is ideal in this case; let mods view the close queue as a list. (In fact, a list similar to the old flag queue -- which shows a list of mods who have seen the post and what mod actions have already been taken -- would be great) On Physics, the majority of the flags that we get are VTC flags. And the community isn't always able to close things on their own, so we have to step in. However, powering through the close queue isn't an option; because &quot;skip&quot;ing a post2 leads to it being dumped into the void (I can't get back to it unless I have a link). Extremely inconvenient. Could the workflow here be improved? 1. The /tools listing for posts with outstanding close votes doesn't work because it doesn't list posts which have been flagged but not VTCd 2. which I may want to take a closer look at later; gotta be careful with the binding votes. How to pin Eclipse to the Unity launcher? For a finite set $S$ there are $\vert S\vert!$ orderings of its elements.  What is the cardinality of all orderings of $\mathbb{N}$?  What would $$\vert \mathbb{N}\vert!$$ mean?  Is it $\prod_{n\in\mathbb{N}} \aleph_0=\aleph_0^{\aleph_0}=\aleph_1$?   says the "equivalence classes of well-orderings of the natural numbers" has cardinality $\aleph_1$.  But I can't put together in my mind the connection between well-orderings of $\mathbb{N}$ and all orderings of $\mathbb{N}$.  (Are there non well-ordered orderings of $\mathbb{N}$?)  This leads to wondering what the cardinality of all orderings of $\mathbb{R}$ is.  (Actually my thought process went in the other direction, from $\mathbb{R}$ to $\mathbb{N}$.)  I think knowing the answer to the above question will teach how to determine what $$\vert \mathbb{R}\vert !$$ means, if anything.  I will be happy if you assume the continuum hypothesis to be true for the purposes of this question, but any level of completeness is welcome. Order of a product of subgroups. Prove that $o(HK) = \frac{o(H)o(K)}{o(H \cap K)}$.