Applied Spectroscopy Reviews is a peer-reviewed scientific journal that focuses on the application of spectroscopic techniques in various fields. It publishes reviews on the latest developments, advancements, and applications of spectroscopy in areas such as chemistry, biology, materials science, and environmental science, among others. The journal aims to provide a platform for researchers to share detailed insights into how spectroscopic methods are being utilized to solve complex problems or advance knowledge in different disciplines.
"Area code stubs" typically refer to placeholder or incomplete entries related to telephone area codes in databases, software, or telecommunications systems. These stubs may indicate that information regarding a specific area code has not been fully populated or updated in a given context. In telecommunications, area codes are numerical prefixes that designate specific geographic regions for phone numbers.
In this example, posts have tags. When a post is deleted, we check to see if there are now any empty tags, and now we want to delete any empty tags that the post deletion may have created.
If we are creating and deleting posts concurrently, a naive implementation might wrongly delete the tags of a newly created post.
This could be due to a concurrency issue of the following types.
Failure case 1:which would result in the new post incorrectly not having the
- thread 2: delete old post
- thread 2: find all tags with 0 posts. Finds
tag0from the deleted old post which is now empty. - thread 1: create new post, which we want to have tag
tag0 - thread 1: try to create a new tag
tag0, but don't because it already exists, this is done using SQLite'sINSERT OR IGNORE INTOor PostgreSQL'sINSERT ... ON CONFLICT DO NOTHING - thread 1: assign
tag0to the new post by adding an entry to the join table - thread 2: delete all tags with 0 posts. It still sees from its previous search that
tag0is empty, and deletes it, which then cascades into the join table
tag0.Failure case 2:which leads to a foreign key failure, because the tag does not exist anymore when the assignment happens.
- thread 2: delete old post
- thread 2: find all tags with 0 posts
- thread 1: create new post
- thread 1: try to create a new tag
tag0, but don't because it already exists - thread 2: delete all tags with 0 posts. It still sees from its previous search that
tag0is empty, and deletes it - thread 1: assign
tag0to the new post
Failure case 3:which leads to a foreign key failure, because the tag does not exist anymore when the assignment happens.
- thread 2: delete old post
- thread 1: create new post, which we want to have tag
tag0 - thread 1: try to create a new tag
tag0, and succeed because it wasn't present - thread 2: find all tags with 0 posts, finds the tag that was just created
- thread 2: delete all tags with 0 posts, deleting the new tag
- thread 1: assign
tag0to the new post
Sample executions:All executions use 2 threads.
node --unhandled-rejections=strict ./parallel_create_delete_empty_tag.js p 9 1000 'READ COMMITTED': PostgreSQL, 9 tags, DELETE/CREATE thetag0test tag 1000 times, useREAD COMMITTEDExecution often fails, although not always. The failure is always:because the:error: insert or update on table "PostTag" violates foreign key constraint "PostTag_tagId_fkey"tries to insert a tag that was deleted in the other thread, as it didn't have any corresponding posts, so this is the foreign key failure.INSERT INTO "PostTag"node --unhandled-rejections=strict ./parallel_create_delete_empty_tag.js p 9 1000 'READ COMMITTED' 'FOR UPDATE': do aSELECT ... FOR UPDATEbefore trying toINSERT.This is likely correct and the fastest correct method according to our quick benchmarking, about 20% faster thanREPEATABLE READ.node --unhandled-rejections=strict ./parallel_create_delete_empty_tag.js p 9 1000 'REPEATABLE READ': repeatable readWe've never observed any failures with this level. This should likely fix the foreign key issue according to the PostgreSQL docs, since:- the
DELETE "Post"commit cannot start to be seen only in the middle of the thread 1 transaction - and then if DELETE happened, the thread 1 transaction will detect it, ROLLBACK, and re-run. TODO how does it detect the need rollback? Is it because of the foreign key? It is very hard to be sure about this kind of thing, just can't find the information. Related: postgreSQL serialization failure.
- the
node --unhandled-rejections=strict ./parallel_create_delete_empty_tag.js p 9 1000 'SERIALIZABLE': serializablenode --unhandled-rejections=strict ./parallel_create_delete_empty_tag.js p 9 1000 'NONE': magic value, don't use any transaction. Can blow up of course, since even less restrictions thanREAD COMMITTED
Some theoretical notes:
stackoverflow.com/questions/10935850/when-to-use-select-for-update from SELECT FOR UPDATE also talks about a similar example, and has relevant answers.
Often just called collimated light due to the collimator being the main procedure to obtain it.
However, you move very far away from the source, e.g. the Sun, you also get essentially parallel light.
sqlite3 ':memory:' 'WITH t (i) AS (VALUES (-1), (-1), (-2)) SELECT *, row_number() over () FROM t'-1|1
-1|2
-2|3With a possible output:
partition by:sqlite3 ':memory:' 'WITH t (i) AS (VALUES (-1), (-1), (-2)) SELECT *, row_number() over ( partition by i ) FROM t'-2|1
-1|1
-1|2rm -f tmp.sqlite
sqlite3 tmp.sqlite "create table t (id integer, val integer)"
sqlite3 tmp.sqlite <<EOF
insert into t values
(0, 0),
(1, 5),
(2, 10),
(3, 14),
(4, 15),
(5, 16),
(6, 20),
(7, 25),
(8, 29),
(9, 30),
(10, 30),
(11, 31),
(12, 35),
(13, 40)
EOFShow how many neighbours each column has with Output:
val between val - 2 and val + 2 inclusive:sqlite3 tmp.sqlite <<EOF
SELECT id, val, COUNT(*) OVER (
ORDER BY val RANGE BETWEEN 2 PRECEDING AND 2 FOLLOWING
) FROM t;
EOF0|0|1
1|5|1
2|10|1
3|14|3
4|15|3
5|16|3
6|20|1
7|25|1
8|29|4
9|30|4
10|30|4
11|31|4
12|35|1
13|40|1val - 1 and val + 1 inclusive instead:sqlite3 tmp.sqlite <<EOF
SELECT id, val, COUNT(*) OVER (
ORDER BY val RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING
) FROM t;
EOF0|0|1
1|5|1
2|10|1
3|14|2
4|15|3
5|16|2
6|20|1
7|25|1
8|29|3
9|30|4
10|30|4
11|31|3
12|35|1
13|40|1There seems to be no analogue to HAVING for window functions, so we can just settle for a subquery for once, e.g.:which outputs:
sqlite3 tmp.sqlite <<EOF
SELECT * FROM (
SELECT id, val, COUNT(*) OVER (
ORDER BY val RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING
) as c FROM t
) WHERE c > 2
EOF4|15|3
8|29|3
9|30|4
10|30|4
11|31|3- youtu.be/29aTqLvRia8?t=714 GlobalFoundries seems to be one of the leaders at the time. E.g. quantum computing company PsiQuantum uses them. Part of this was from acquiring IBM's microelectronics division in 2014.
- youtu.be/t0yj4hBDUsc?t=566 mentions the paper Deep learning with coherent nanophotonic circuits
- youtu.be/t0yj4hBDUsc?t=440 block diagram
- youtu.be/t0yj4hBDUsc?t=456 Lightmatter lightmatter.co/ seems to be using an in-silicon Mach-Zehnder interferometer to do analog matrix multiplication with light. It is an actual analog computer element!
Silicon Photonics for Extreme Computing by Keren Bergman (2017)
Source. stackoverflow.com/questions/17046204/how-to-find-the-boundaries-of-groups-of-contiguous-sequential-numbers/17046749#17046749 just works, even in SQLite which supports all quoting types known to man including
[] for compatibility with insane RDBMSs!Here's a slightly saner version:
rm -f tmp.sqlite
sqlite3 tmp.sqlite "create table mytable (id integer primary key autoincrement, number integer, status integer)"
sqlite3 tmp.sqlite <<EOF
insert into mytable(number, status) values
(100,0),
(101,0),
(102,0),
(103,0),
(104,1),
(105,1),
(106,0),
(107,0),
(1014,0),
(1015,0),
(1016,1),
(1017,0)
EOF
sqlite3 tmp.sqlite <<EOF
SELECT
MIN(id) AS "id",
MIN(number) AS "from",
MAX(number) AS "to"
FROM (
SELECT ROW_NUMBER() OVER (ORDER BY number) - number AS grp, id, number
FROM mytable
WHERE status = 0
)
GROUP BY grp
ORDER BY MIN(number)
EOFoutput:
1|100|103
7|106|107
9|1014|1015
12|1017|1017To get only groups of length greater than 1:
sqlite3 tmp.sqlite <<EOF
SELECT "id", "from", "to", "to" - "from" + 1 as "len" FROM (
SELECT
MIN("id") AS "id",
MIN(number) AS "from",
MAX(number) AS "to"
FROM (
SELECT ROW_NUMBER() OVER (ORDER BY "number") - "number" AS "grp", "id", "number"
FROM "mytable"
WHERE "status" = 0
)
GROUP BY "grp"
ORDER BY MIN("number")
) WHERE "len" > 1
EOFOutput:
1|100|103|4
7|106|107|2
9|1014|1015|2Determines what can or cannot happen when multiple queries are running in parallel.
See Section "SQL transaction isolation level" for the most common context under which this is discussed: SQL.
www.youtube.com/watch?v=6DxlkxA82FM COVID-19 Symposium: Entry of Coronavirus into Cells | Dr. Paul Bates
Some are named after the encoded protein. Others that are not as clean are just orfXXX for open reading frame XXX.
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 3. Visual Studio Code extension installation.
Figure 4. Visual Studio Code extension tree navigation.
Figure 5. Web editor. You can also edit articles on the Web editor without installing anything locally.Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.Video 4. OurBigBook Visual Studio Code extension editing and navigation demo. Source. 
- Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact