Adaptation Heroes

Pura Vida | Build a Space Biology Superhero

Awards & Nominations

Adaptation Heroes has received the following awards and nominations. Way to go!

Global Nominee

Hybrid Humans

High-Level Project Summary

Using a genetic algorithm, our team developed a game for mobiles, with the intention to make people aware of the risks of travel to outer space. The game also provides information about scientific studies carried out on organisms in order to reduce risks in the future. Interactively, the player will choose, among different organisms, the one that best adapts to the problem that the hostile outer space presents to the user.

Link to Final Project

https://github.com/Allen-RR/Adaptation_Heroes

Link to Project "Demo"

https://youtu.be/gDbqM1IZw5w

Detailed Project Description

We all want to travel through space and discover other universes, but do we know the risks of leaving planet Earth?

Our bodies just aren't ready to survive out there.

Scientists continually investigate the health implications of astronauts and living beings they send into space.

We propose an interactive and playful way to publicize research on biological organisms, while learning about the challenges and risks that, as human beings, we are exposed to in space.

Based on a genetic algorithm, we developed a game where you can merge with different organisms that have a unique characteristic to survive in interplanetary travel.

In this simple way you can access the technological and scientific knowledge that is so important for the development of humans in the future.

PITCH:

https://youtu.be/ZcOk7dlSRuE

PROTOTIPE FIGMA APP FINAL:

https://www.figma.com/proto/SgpZGPe0wGOSqKd8bFNPgY/NASA-Challenge?node-id=0%3A1&scaling=min-zoom&page-id=0%3A1&starting-point-node-id=5%3A2617

Apk application:

https://github.com/Allen-RR/Adaptation_Heroes/blob/main/HybridHuman.apk

Genetic algorithm code:

https://github.com/Allen-RR/Adaptation_Heroes/blob/main/Adaptation_HeroesAPP/app/src/main/java/dev/hardsoft/adaptationheroes/GeneticAlgorithm.java

App flow

https://youtube.com/shorts/0i64-LsvmdU?feature=share

Fig 1. Figma frames for the application.

Genetic Algorithm

With the numerous challenges present in space exploration, the discovery of information about this topic can have the capability to be diverse and dynamic.

For this challenge, and with the use of a game platform to inform, we present a solution using a genetic algorithm that allows the users to build a "Space Biology Superhero" by combining findings of research and studies on different types of organisms against the multiples risk of space exploration.

This genetic algorithm is used to find the best, or an approximate solution, for a combination of scores associated with a research and an organism. The process iterates over a collection of game cards with a score chosen by the user. A group of the cards forms different improved individuals that together creates a population.

For each individual in a population, a score of its cards is calculated representing the score for this specific individual. These values are stored in the case of the best and worst for the organism in a population, used to form a probability of the next generation of individuals having parents with a good or not so favorable score, simulating the processes of selection and crossover. For the process of mutation, we hope to implement it in future work.

Finally for the algorithm, the steps are repeated for each of the new generations of individuals, giving as an output at the end the best and optimized individual, the associated score and its related research cards.

In this challenge we use a set of assumed variables (similar to how this type of variables tend to work in global search heuristics), namely the genes distribution from parents to the next generation. In a future work, we would like to do more research about the distribution of genes in real life and how this could help improve our work and the information and research done in biology using computer science.

This method's inspiration on biology evolution and process as mutation, crossover and selection was an approach of great interest to us because of its thematic. We hope to bring information and understanding about space travel stresses and the adaptability that some organisms can have against those problems.

Fig 2. Genetic algorithm pseudocode diagram.

Development in Android Studio with Java and control version in Git

The development of the HybridHuman application was done in the Android Studio integrated development environment (IDE). Together with the Java and XML languages for the integration of the interfaces.

It was carried out using the figma designs. Which were used to couple the interfaces to the application.

In addition, the Git version control and the GitHub repository were used to be able to develop the application together with all the developers.

Fig 3. Image of the IDE Android Studio and the app development.

Space Agency Data

The article on the risks caught our attention and from here we started

https://www.nasa.gov/hrp/5-hazards-of-human-spaceflight

From here we get the information of each organism that we investigated

https://genelab-data.ndc.nasa.gov/genelab/projects

Risk and challenges general information for the game "risk metric":

https://humanresearchroadmap.nasa.gov/risks/

Papers

Bloomberg, J. J., Reschke, M. F., Clement, G. R., Mulavara, A. P., & Taylor, L. C. (2015). Risk of impaired control of spacecraft/associated systems and decreased mobility due to vestibular/sensorimotor alterations associated with space flight (No. JSC-CN-34446).

https://ntrs.nasa.gov/api/citations/20150018603/downloads/20150018603.pdf

Mhatre, S. D., Iyer, J., Petereit, J., Dolling-Boreham, R. M., Tyryshkina, A., Paul, A. M., ... & Bhattacharya, S. (2022). Artificial gravity partially protects space-induced neurological deficits in Drosophila melanogaster. Cell Reports, 40(10), 111279.

https://www.cell.com/action/showPdf?pii=S2211-1247%2822%2901099-3

Santucci, D., Kawano, F., Ohira, T., Terada, M., Nakai, N., Francia, N., ... & Ohira, Y. (2012). Evaluation of gene, protein and neurotrophin expression in the brain of mice exposed to space environment for 91 days. PloS one, 7(7), e40112.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392276/

Hackathon Journey

The challenge caught our attention from the beginning because one of our developers told us about the genetic algorithm (from the hand of John Henry Holland, one of the most promising lines of artificial intelligence emerged, that of genetic algorithms).

With this in mind, we thought about how to excite game users to wisely cooperate with other organisms to achieve survival in space.

We were surprised by all the risks that exist, and for which a solution must be found, to go into outer space.

We enjoy developing an app that brings this valuable information closer to people and also makes known the efforts that NASA is making to get us safely into space.