For pixel art lovers:
Open-source ESP32-P4-based wi-fi connected pixel art player, part of the Makapix Club project (https://makapix.club/).
Link to firmware repo: https://github.com/fabkury/p3a
9 karma · joined March 24, 2018
Open-source ESP32-P4-based wi-fi connected pixel art player, part of the Makapix Club project (https://makapix.club/).
Link to firmware repo: https://github.com/fabkury/p3a
- Makers: Get art that looks awesome on low-res, download firmware
- Pixel artists: Reach real-world displays, gain points and badges
- Everyone: Enjoy free art & community, even if you don't own a display
At high level, the project seeks to combine an MQTT broker for live updates (new posts), a lightweight free & ad-free social media experience (comments and likes only), a self-hosted approach to storing the artworks, and MCU firmware to turn any display into a web-connected pixel art player.
Join us! It is a lot to build and this is all just for fun & love.
----
[Sorry for reposting, the Discord link was broken! Now it's fixed!]
This is for:
- Makers: Get art that looks awesome on low-res, download firmware
- Pixel artists: Reach real-world displays, gain points and badges
- Everyone: Enjoy free art & community, even if you don't own a display
At high level, the project seeks to combine an MQTT broker for live updates (new posts), a lightweight free & ad-free social media experience (comments and likes only), a self-hosted approach to storing the artworks, and MCU firmware to turn any display into a web-connected pixel art player.
Join us! It is a lot to build and this is all just for fun & love.
What it actually does is schedule (distribute) the desired muscle groups across days according to your specification of:
- volume: # sets to do on each workout day of that muscle group
- frequency: # days between workout days of that muscle group
I am afraid I do not have a website or write-up but the code is here: https://github.com/fabkury/caltre. I have been actually using this script for years and it has made my gym scheduling effortless. I can just focus on the "meta parameters", e.g.:
INPUT:
muscle group,`X sets per training day`,`train every X
days`
back,9,4
chest,9,4
quads,8,4
biceps,7,3
shoulder,6,4
abdominal,4,2
calf,4,5
anterior forearm,5,6
posterior forearm,5,6
day 1:
chest 9
biceps 7
day 2:
quads 8
abdominal 4
day 3:
back 9
calf 4
anterior forearm 5
day 4:
biceps 7
shoulder 6
abdominal 4
day 5:
chest 9
posterior forearm 5
day 6:
quads 8
abdominal 4
day 7:
back 9
biceps 7
day 8:
shoulder 6
abdominal 4
calf 4
day 9:
chest 9
anterior forearm 5
day X:
...
As starting point, I used the lat/lon of the population center of each census block group as provided by Census.gov. In Brazil the closest geographical equivalent is the setor censitário (census sector). I used Haversine distance (great circle distance between lat/lon's) to narrow the search space to the 5 closest hospitals, from the hospital database by the American Hospital Association, and the Brazilian CNES registry (Cadastro Nacional de Estabelecimentos de Saúde). From those 5 closest candidates, I then asked the HERE API for the true driving time to their address. Many many API calls.
We plotted average driving time against variables from the census block group provided by the American Community Survey to show how values change as driving distances change. Mostly just to demonstrate the kind of analyses possible. I presented the work at the NLM Informatics Training confereces, e.g. with many pictures of maps: https://github.com/fabkury/drithop/raw/master/Kury%20-%20dri... . Source code (but not data) are in the GitHub repo `drithop`. The maps are self-contained HTML files and interactive using OpenStreetMap.
Remote: Yes, but prefers in-person.
Willing to relocate: No.
Technologies: OHDSI, OMOP CDM, SNOMED, LOINC, CMS VRDC, claims data, EHR data, R, SQL, SAS, HL7 FHIR
Résumé/CV: https://1drv.ms/b/s!Auk_d44Mzjh_vIMOa1eAN2qaEzkWuw?e=0gDqOz
Email: fab at kury.dev
---
Healthcare data scientist. Has comprehensive background in manipulating health data, and building analyses, datasets, and other assets. Also experienced in publishing as a researcher in Biomedical Informatics.
Remote: Yes
Willing to relocate: No
Technologies: R, SQL, SAS, OHDSI OMOP Common Data Model, NDC, ATC, SNOMED, LOINC, ICD, Medicare claims, electronic health records
Résumé/CV: https://1drv.ms/b/s!Auk_d44Mzjh_vIE-sX5eL4OC2oNacg?e=lrhW4N
Email: fab at kury.dev
I am not an expert, but if something gives you a reward _partially randomly_ -- e.g., the one cool (or otherwise captivating) post on Facebook that sometimes comes out of the 200 you scrolled through -- this kind of reinforcement produces the behaviors most resistant to extinction.
See "Effects of different types of simple schedules" on https://en.wikipedia.org/wiki/Reinforcement.
Regeneron (NASDAQ: REGN) is a leading biotechnology company that invents life-transforming medicines for people with serious diseases. The Regeneron Genetics Center (RGC) is a wholly-owned subsidiary of the Company, whose goals are to apply large scale human genetics to identify new drug targets and to guide the development of therapeutics programs and precision medicine.
The position will be responsible for conducting analyses involving clinical and phenotypic data for genetics studies as well as clinical development and commercial programs. Responsibilities will include curating, cleaning, and analyzing large-scale phenotypic datasets, including de-identified EHR extracts from external collaborators, targeted clinical datasets in selected cohorts, and internal datasets from clinical trials and other human subject research.
https://careers.regeneron.com/job/REGEA002619399BR5080/Senio...
The hiring manager is my boss and you'd become my colleague, my peer. Feel free to ask me anything. You can reach me at 2020_03_09@kury.dev.