Plot – How to display axes when combined with show plots

The following code causes coordinate axes to not be displayed. I want to understand why that happens and how to fix it. Ideally, there is a way to set the image size and the axis parameters once and independent of the plot code.

g = graphic[{}, ImageSize -> {1920, 1080}];
g = show[g,
Table[
ParametricPlot[{(1 + t) Cos[a]Sin[a]}, {a, 0, 2 [Pi]},
PlotRange -> {{-2.1, 2.1}, {-1.2, 1.2}},
AxesStyle -> {{Black, AbsoluteThickness[5]}, {Black,
AbsoluteThickness[5]}}
PlotStyle -> {Black, AbsoluteThickness[12]}].
{t, 0, 1, 1/5}]];
Enlarge[g, .25]

First show the post in a loop based on the meta key in an array of multiple categories

I try to achieve the following.
The WordPress Topic Newspaper uses a custom block to display the four most recent multi-category posts specified in a TagDiv composer that came with the topic.

These blocks provide sorting options that are built into the topic as case or wp query arguments. These cases can then be applied to the blocks in which you set the number of posts, categories for displaying posts, and so on.

However, I need the latest post from a category (called Win Win Win) that, when set to this category, sets the custom field "wedstrijd" to "true" to appear as the first post of the four.

So if there is a contest, the first post is always this competitive post, the other three are filled with the latest entries from a range of categories.

Until the contest post is deleted, it should stay in the top position while adding other content, which will have a later release date. This competition category always has only one active published contribution.

I tried the following, but unfortunately I can only show the single post with the key wedstrijd to true. Someone out there who can help me with this?

The categories are set in the TagDiv composer of the site. These are 4,5,9,433.43,47,36,18,17,427,790,31648, where 31648 is the competition category. I've already tried to set the categories in the following query, but this does not work or overrides the settings in tagdiv composer.

                            case & # 39; winfirst & # 39 ;:
$ wp_query_args['meta_query'] = array (
& # 39; relation & # 39; => & # 39; OR & # 39 ;,
& # 39; # 39 & query_one; => array (
& # 39; key & # 39; => & # 39; wedstrijd & # 39 ;,
& # 39; compare & # 39; => & # 39; = & # 39 ;,
& # 39; value & # 39; => & # 39; 1 & # 39;
)
& # 39; # 39 & query_two; => array (
& # 39; key & # 39; => & # 39; wedstrijd & # 39 ;,
& # 39; compare & # 39; => & # 39; = & # 39 ;,
& # 39; value & # 39; => & # 39 ;,
)
);
$ wp_query_args['orderby'] = array ('query_one' => 'ASC', 'query_two' => 'DESC');

Probability – Show that additive Gaussian noise never increases frugality

To let $ mathbf {1} in mathbb {R} ^ d $ be that $ d $All-ones vector and leave $ n sim mathcal {N} (0, sigma ^ 2 I_ {d times d}) $, show that
$$ frac { | mathbf {1} + n | _1} { | mathbf {1} + n | _2} ge c sqrt {d} $$
with high probability $ d $for constant $ c $ (independent of $ sigma, d $).

In other words, prove that adding Gaussian noise never significantly improves frugality in the sense of $ ell_1 / ell_2 $ Relationship. Generalization to any dense vectors is of course welcome.

turing machines – How to show that B is semisetable at A

I'm preparing for my computational theory finale and came across exactly this problem:

B = {x | There is a prefix of x in A}.

Show that B is half decidable. In other words, you have to describe an algorithm M that when typing a string x half decides whether any prefix of x is in ON ("Half-decisions" means that it's okay if the algorithm goes through unprefixed strings ON). You assume that you have an algorithm MON that's half the decision ON,

Any help would be appreciated!

abstract algebra – show $ mathbb {C} [x,y]/ (xy-1) $ is an ideal principle

I have to show that $ A: = mathbb {C} [x,y]/ (xy-1) $ is an ideal area in principle

I know that $ A $ is isomorphic too $ mathbb {C}[t,t^{-1}]$ and that this is a subfield
from $ mathbb {C}

But I have to work with the canonical inclusion card $ i: mathbb {C}[x] hookrightarrow A $ from then point $ I cap Im (i) neq {0 } $ ideal for everyone $ I neq {0 } $, I have no idea why I need it.

html – "Is there a feature to upload a video to a database and show it to the end user or the like?"

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Network – Google 2-factor authentication does not show my location

I'm on my corporate proxy and use Google's 2-factor authentication to log in to my computer. When I get the notification on my phone, it says I'm trying to connect from Moscow (Russia) even though I'm in the US. In the past, this was not a problem – it was only a few weeks ago. So I'm worried about a MITM attack.

question: Is it normal for Google to show wrong 2-factor login paths behind a proxy?

Real analysis – Show that the a posteriori probability minimizes the quadratic error of a Bayesian problem

To let $ ( Omega, mathcal A, operatorname P) $ be a probability space, $ d in mathbb N $. $ X $ be a $ mathbb R ^ d $-valued random variable on $ ( Omega, mathcal A, operatorname P) $. $ Y $ be a $ left {0,1 right } $-valued random variable on $ ( Omega, mathcal A, operatorname P) $. $ eta $ be a version of $ operatorname P left[Y=1mid X=;cdot;right]$ and $ f: mathbb R ^ d to mathbb R $ Borel be measurable.

How can we show that? $ operatorname E left[left|eta(X)-Yright|^2right] le operatorname E left[left|f(X)-Yright|^2right]$?

If $ f $ is so limited $$ operator name E left[(f(X)-eta(X))(eta(X)-Y)mid Xright]= (f (X) – eta (X)) operatorname E left[eta(X)-Ymid Xright] day 1. $$ In that case, we can determine that $$ | f (X) -Y | ^ 2 = | f (X) – eta (X) | ^ 2 + 2 (f (X) – eta (X)) ( eta (X) -Y) + | eta (X) -Y | ^ 2 tag2 $$ and therefore begin {equation} begin {split} operator name E left[|f(X)-Y|^2mid Xright]& = | f (X) – eta (X) | ^ 2 + 2 (f (X) – eta (X)) underbrace {( eta (X) – operatorname E left[Ymid Xright])} _ {= : 0} + operatorname E left[|eta(X)-Y|^2mid Xright]\ & ge operatorname E left[|eta(X)-Y|^2mid Xright], end {split} tag3 end {equation} Building readiness we receive the claim.

How can we generalize this result?

It is clear that we must somehow evoke the monotone convergence.