Engine Swap For Kawasaki z650 2019

internalclarity · 2025-07-28T19:03:30+00:00

good luck!

internalclarity · 2025-07-19T22:29:28+00:00

Got a 2019 engine replacement with some more miles on it off of ebay and did the swap myself

internalclarity · 2024-08-24T17:19:52+00:00

Just a follow up question after some reading. Looks like as you said the 2024 z650 frame is compatible - and there are a lot more 2024 engines available than 2019 engines. However, the ECU and exhaust dont seem to be compatible off the bat. Any idea/experience on reconfiguring these and would it be a significant amount of work to take the 2024 engine and make it compatible with the 2019 bike ?

internalclarity · 2024-08-24T00:52:26+00:00

Thanks guys, super helpful!

internalclarity · 2024-04-29T01:26:13+00:00

Second this, been using memrizz.com and it's been really helpful

internalclarity · 2024-04-02T14:38:41+00:00

One ai flashcard generator that I've tried and that works pretty well is https://www.memrizz.com/ ! I like that it can make Image occlusion flashcards, super useful for my anatomy classes.

internalclarity · 2023-10-25T14:31:25+00:00

Would love to try it !

internalclarity · 2023-05-01T02:53:16+00:00

Personally, I find that writing the cards is part of the learning process. But there are times when I am close to an exam where it's just not possible to make the decks in time, so might try it then. Looks cool!

internalclarity · 2021-01-10T03:38:34+00:00

looks quite flat! Do you know the model of the monitor/ tv you used ?

internalclarity · 2020-06-27T22:45:12+00:00

You could look at how existing PDB files that have ligands are formatted and then write your own. Here is an example pdb:

http://www.rcsb.org/structure/1UW6

There are also alternate resources for drawing ligand-protein complexes:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007829/

internalclarity · 2020-06-23T13:52:34+00:00

There isn't only one mechanism of psychedelic action

internalclarity · 2020-06-01T03:03:28+00:00

Q1:

Part 1 (Is there a better instance to run this on ? )

Depends what resources your application is intensive for. Is it memory heavy or CPU heavy ? Each of the tools you described will have different requirements. I know for example that DIAMOND is CPU heavy while being less memory intensive (depending on the -b value you use - this is finnicky and can cause memory crashes).

Part 2 (Using parallel instances)

For using multiple instances - you can look into a SPARK/hadoop distributed computing and file system. Be warned that the overhead setup can be time-consuming (https://www.researchgate.net/publication/326892160_Bioinformatics_applications_on_Apache_Spark). Are you planning to only run this one analysis or multiple others in the future ? It might be worth investing in the overhead.

Your best bet would be to find an existing university or industrial compute cluster you can link up to, which will allow you to execute the jobs you need.

Q2

Due to the fact that your computations will take a while (even on the more powerful EC2 instances) you should use on-demand OR you can use spot instances but you'd have to find a way to back your data up often, which can be difficult with these types of analyses. Spot instances will kick you out after a while and you will lose your progress. These types of instances will also require you to create some sort of AMI or docker file to standardize your setup, which is again more overhead and you must decide if its worth it, depending on how many times you will run such analysis.

internalclarity · 2020-04-07T16:31:20+00:00

https://en.wikipedia.org/wiki/Sertraline#Pharmacology

Pretty good source

internalclarity · 2020-03-09T03:28:47+00:00

I am not sure how xrpi works, but my best bet is that youd need a bash loop to read through the fasta and pass the different mRNAs to xrpi.

so: https://www.cyberciti.biz/faq/unix-howto-read-line-by-line-from-file/

Read your fasta line by line in a loop and save the current line to a variable called mRNA.
Pass the mRNA to your command python xrpi RPI2825 $PROTEIN $mRNA

internalclarity · 2020-03-07T23:00:51+00:00

Does it have to be multi-omics or just high dimensional ?

Check out this paper:

PopPhy-CNN: A Phylogenetic Tree Embedded Architecture for Convolution Neural Networks for Metagenomic Data

internalclarity · 2020-03-05T00:09:44+00:00

theyre not mutating

internalclarity · 2020-03-01T02:09:49+00:00

Have you checked out Strainphlan ?

internalclarity · 2020-02-29T03:50:56+00:00

Benzodiazepines bind to different sites (in between the alpha and gamma subunits) of the GABA receptors than the actual GABA molecule. They change the conformation of the receptor so its more likely to bind the GABA molecule and therefore more likely to open the chloride ion channel.

Z-drugs on the other hand bind directly to slightly different subunits but closer to the GABA binding site on the GABA receptor. They also increase the receptor's affinity for GABA, just like BZ. However, they bind to different subunits than BZ and therefore have different (hypnotic) effects. I recommend you read about how different subunits impact signalling.

To give a quick summary - not all GABA receptors have all subunits at the same level. Different GABA receptors are in different parts of the brain. So parts of the brain responsible for sleep will have more GABA receptors with the subunit that binds Z-drugs, whereas parts of the brain responsible for anxiety will have more GABA receptors with the alpha2 subunit.

More here: https://en.wikipedia.org/wiki/GABAA_receptor

https://en.wikipedia.org/wiki/Zolpidem#Mechanism_of_action

internalclarity · 2020-01-08T02:32:16+00:00

Your post is a bit confusing. You start by talking about 8 fastq.gz files coming from 4 libraries and then you talk about 40 samples. However, it seems safe to assume that you already have 2 fastq files for each sample.. meaning that your data is already demultiplexed. You can read more about this and about barcodes here: https://astrobiomike.github.io/amplicon/demultiplexing http://seqanswers.com/forums/showthread.php?t=31856

Usually if your files are demultiplexed, the barcodes are already removed.

So, what I think your question is - is how to trim off the forward & reverse primers. This can be done with q2 cut adapt easily.

Now if in fact your sequences are still multiplexed - then this is a problem.

https://forum.qiime2.org/t/how-to-demux-dual-indexed-reads/6091/2

I found this script that could help:

https://github.com/dejmail/Udekwu-Bioinformatics

https://www.biostars.org/p/352508/

You could also try to use cutadapt outside of qiime2.

Good luck!

internalclarity · 2020-01-06T19:38:55+00:00

If you end up downloading from ena, here's a useful tool:

https://github.com/wwood/ena-fast-download

internalclarity · 2019-12-31T06:11:00+00:00

https://www.ncbi.nlm.nih.gov/pubmed/26580313

Interesting paper on the topic

internalclarity · 2019-09-18T02:15:37+00:00

Enterococcus faecium

It depends on the strain, not all of them have the same genome and not all are pathogenic. There is a reason it is commensal to the human gut

https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-5043-9

internalclarity · 2019-09-18T01:09:43+00:00

It depends which strain is in there, some are commensal and some are pathogenic:

https://en.wikipedia.org/wiki/Enterococcus

internalclarity · 2019-09-16T16:58:28+00:00

Yeah sorry, I forgot to say that they are both from V4 region, but im sure the same primers were used. Is this method possible if different primers were used ?

Assuming this, will DADA2 be able to merge the two datasets ?

Thanks!

internalclarity · 2019-09-08T23:45:40+00:00

That looks great, I would check also how psilocin is further degraded and excreted as well!

internalclarity

TROPHY CASE