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---
layout: post
title: Another test markdown
subtitle: Each post also has a subtitle
categories: markdown
tags: [test]
---

Put the math expression within <span>$</span>...\$:

\\(\LaTeX{}\\)

$\Pi$

$ a * b = c ^ b $

$ 2^{\frac{n-1}{3}} $

$ \int\_a^b f(x)\,dx. $

\\( \int\_a^b f(x)\,dx. \\)

$ \rho {\rm{FOD}} = \sum\limits{\sigma ,i} {(\delta _1 - \delta _2 n_i^\sigma )|\phi _i^\sigma ({\bf{r}})|^2} $

$$ \rho {\rm{FOD}} = \sum\limits{\sigma ,i} {(\delta _1 - \delta _2 n_i^\sigma )|\phi _i^\sigma ({\bf{r}})|^2} $$


:+1:
:bolivia:

\1. 21312  
\2. 21312  
\4. 4214  

{% highlight python wl linenos %}
import networkx as nx
from collections import Counter

diagrams = defaultdict(list)
particle_counts = defaultdict(Counter)

for (a, b), neighbors in common_neighbors.items():
    # Build up the graph of connections between the
    # common neighbors of a and b.
    g = nx.Graph()
    for i in neighbors:
        for j in set(nl.point_indices[
            nl.query_point_indices == i]).intersection(neighbors):
            g.add_edge(i, j)

    # Define the identifiers for a CNA diagram:
    # The first integer is 1 if the particles are bonded, otherwise 2
    # The second integer is the number of shared neighbors
    # The third integer is the number of bonds among shared neighbors
    # The fourth integer is an index, just to ensure uniqueness of diagrams
    diagram_type = 2-int(b in nl.point_indices[nl.query_point_indices == a])
    key = (diagram_type, len(neighbors), g.number_of_edges())
    # If we've seen any neighborhood graphs with this signature,
    # we explicitly check if the two graphs are identical to
    # determine whether to save this one. Otherwise, we add
    # the new graph immediately.
    if key in diagrams:
        isomorphs = [nx.is_isomorphic(g, h) for h in diagrams[key]]
        if any(isomorphs):
            idx = isomorphs.index(True)
        else:
            diagrams[key].append(g)
            idx = diagrams[key].index(g)
    else:
        diagrams[key].append(g)
        idx = diagrams[key].index(g)
    cna_signature = key + (idx,)
    particle_counts[a].update([cna_signature])
{% endhighlight %}


|:                        |:                  :|: $$O_3 + C_2H_2 \rightarrow $$         :|||:  $$O_3 + C_2H_4 \rightarrow $$ :|||:       :| 
|:  ^^ Method            :| ^^ $$\lambda^a$$  |    vdW |    TS |    cycloadd.           |  vdW  |  TS  |  cycloadd.           | ^^ MAE    |
|-------------------------|-------------------|--------|-------|------------------------|-------|------|----------------------|-----------|
| $$\lambda$$-tPBE        |   0.20            | -0.40  | 7.69  | -68.00                 | -1.86 | 4.87 | -57.57               | 1.29      |
|-------------------------|-------------------|--------|-------|------------------------|-------|------|----------------------|-----------|
| MC1H-PBE $$^b$$         |   0.25            | -1.08  | 3.66  | -70.97                 | -1.25 | 0.13 | -61.26               | 3.35      |
|-------------------------|-------------------|--------|-------|------------------------|-------|------|----------------------|-----------|
| Reference values $$^c$$ |   ---------       | -1.90  | 7.74  | -63.80                 | -1.94 | 3.37 | -57.15               | --------- |
|=========================|===================|========|=======|========================|=======|======|======================|===========|
| $$^a$$ The optimal mixing parameter.$$\~$$ $$^b$$ From Ref. .$$\~$$  $$^c$$ Best estimates from Ref. . ||||||||


|   1   |  2     |   3   |   4   |  5   |  6   |  7  |
| spancell1     ||   spancell2  || cell | spancell3 ||
|^^ spancell1   ||   spancell2  || cell | spancell3 ||
{:class="custom-table"}


|:-----:|:-----:|:-----:|:-----:|
| (0,0) | (0,1) | (0,2) | (0,3) |
|     (1,0)    || ^^    | (1,3) |


|:-----:|:-----:|:-----:|:-----:| ---- |
| (0,0) | (0,1) | (0,2) | (0,3) |      |
|     (1,0)    || ^^    | (1,3) |      |


|:-----:|:-----:|:-----:|:-----:| ---- |
| (0,0) | (0,1) | (0,2) | (0,3) |      |
|     (1,0)           ||| (1,3)       ||


|:-----:|:-----:|:-----:|:-----:| ---- |
| (0,0) | (0,1) | (0,2) | (0,3) |      |
|     (1,0)           ||| ^^    |      |

|:-----:|:-----:|:-----:|:-----:| ---- |
| (0,0) | (0,1) | (0,2) | (0,3) |      \
|     (1,0)           ||| ^^    |      |


# Table

| Stage | Direct Products | ATP Yields |
| ----: | --------------: | ---------: |
|Glycolysis | 2 ATP                   ||
|^^         | 2 NADH      | 3--5 ATP   |
|Pyruvaye oxidation | 2 NADH | 5 ATP   |
|Citric acid cycle  | 2 ATP           ||
|^^                 | 6 NADH | 15 ATP  |
|^^                 | 2 FADH | 3 ATP   |
| 30--32 ATP                         |||


9 \* 9

| 1 \* 1 = 1 |
| 1 \* 2 = 2 | 2 \* 2 = 4 |
| 1 \* 3 = 3 | 2 \* 3 = 6 | 3 \* 3 = 9  |
| 1 \* 3 = 3 | 2 \* 3 = 6 | 3 \* 4 = 12 | 4 \* 4 = 16 |

# Emoji
:+1:

# Mathjax

$\LaTeX{}$

# PlantUML

@startuml
Bob -> Alice : hello
@enduml

# Video

![](//www.youtube.com/watch?v=Ptk_1Dc2iPY)

![](https://avatars3.githubusercontent.com/hubot?v=3&amp;s=40)

[\[video link\]](//www.youtube.com/watch?v=Ptk_1Dc2iPY)

Tips:
* Use pipes {% raw %}(`|`){% endraw %} to delineate columns, and dashes to delineate the header row from the rest of the table.
* Spacing doesn't matter to the markdown processor, any extra white space is removed, but it can really help with readability.
The two markdown examples below both create this table.

Use pipes `{% raw %}(`|`){% endraw %}` to delineate columns, and dashes to delineate the header row from the rest of the table.