Cool STEM News:

Scientists developed a clever way to detect Deepfakes by analyzing light reflections in the eyes | The Next Web (01:45)

• Deepfakes are always mentioned as a future technology that people are worried about. 
  • Deepfakes: artificial images and sounds put together with machine-learning algorithms to manipulate how a video looks and sounds. 
  • Main worry is that it can make it look like real people said/did something they didn’t.

• But what is not mentioned all that often, because we focus on the negative more, is the effort to counteract these “bad guy” technologies.

• Computer Scientists at the University of Buffalo developed a method to detect these Deepfake videos with a 94% accuracy. 
  • Note: Accuracy based on portrait style photos

• How? By utilizing light reflected in the eyes.
  • Analyzed the corneas, which generate reflective patterns when illuminated by light.
• Exposed to the same light type your corneas will reflect the same pattern.

• Deepfakes since they are GAN-synthesized (machine-learning algorithm) the images will fail to capture the light reflection properly and show inconsistencies.
  • GAN (Generative adversarial network): In my words, is a machine-learning algorithm that is trained on whether or not it fools the observer. 

• The researchers plan on working out the shortcomings found throughout the study:
  • Needs two eyes refracting light
  • One eye not visible it won’t work.
  • Only proven effective on portrait style images

New Clues Uncovered about Toxic Protein Structures in Neurodegenerative Diseases | GenEngNews (10:16)

• Transactive response DNA-binding protein-43 (TDP-43) is a soluble protein that interacts with nucleic acids. 
• The issue is that this protein forms large clumps, known as amyloid fibrils, which are associated with neurological diseases.
  • ALS, Alzheimer’s, sclerosis, dementia, and Huntington’s disease

• Scientists at the Case Western Reserve University School of Medicine, located in Ohio, were able to determine the structures of TDP-43.
  • Analyzed thousands of images of fibrils formed in the test tube by the key fragment of TDP-43.
  • Resolution close to individual atoms

• This understanding provides insight into how these toxic proteins clump and spread between nerve cells in the brain. 

• Qiuye Li, a graduate student and lead author hits the above point: “This is really an exciting development because it reveals a mechanism for the growth of these toxic aggregates. This, in turn, provides important clues as to how these aggregates may spread between the cells in affected brains.”

• Could pave the way for developing new therapeutics to treat neurological diseases.

Genetic Scalpel Invented for Microalgae to Efficiently Turn CO2 Into Biofuel | SciTechDaily (16:21)

• Researchers from the Qingdao Institute of BioEnergy and Bioprocess Technology (QIBEBT) have genetically modified an oil producing microalgae to create a more efficient genome.

• In the process, they created a gene scalpel that can trim microalgal genomes “rapidly and creatively.”

• This modified microalgae is considered a “minimal genome”: a genome stripped of all duplicated or apparently non-functional genes (“junk genes”).

• Normally this minimizing process is done in research on more simplistic organisms not something like an algae (e.g. eukaryotic organisms).
  • Eukaryote: any cell or organism that possesses a clearly defined nucleus. 

• Researchers were able to accomplish targeted deletion of genes for a type of algae called Nannochloropsis oceanica.
  • Single-Cell algae
  • Potential for production of biofuels, biomaterials, and other chemicals.

• Cut out two low-expression regions (LER) —  over 200 kilobases of the algae.
  • Kilobase: length of a DNA equal to 1,000 base pairs

• Going Forward: 
  • Researchers want to see if they can snip out still further LERs and other non-lethal regions.
  • Goal to craft a fully minimal microalgae that makes biofuels from CO2 with the highest efficiency.

• Other Benefits:
  • Model organism for further study of the molecular and biological function of every gene
  • Used as a building block for synthetic biologists for customized production of biomolecules such as biofuels or bioplastics

METL Tires Using NASA Tech Are Coming to Bikes | Gizmodo & New Atlas (24:21)

• Due to rovers exploring rough terrain on other planets, NASA had to develop a tire that was flexible enough & tough enough.

• Lead to the development of an airless titanium tire that’s flexible like rubber, but nearly indestructible. 
  • Nitinol: The metal alloy developed made of nickel and titanium. 
  • Exhibits the shape memory effect: when deformed it returns to its original manufactured shape without permanent damage.

• The first consumer-oriented application of airless shape memory alloy (SMA) tire technology will be developed by a startup called The Smart Tire Company.
  • Announced that it’s creating a metal bicycle tire using NASA’s Nitinol alloy that never needs to be inflated.

• The creators are hopeful to get these tires out to market by 2022.

• “Cyclists will not be able to wait to get their hands on these very cool-looking, space-age Metl tires that don’t go flat,” says Earl Cole, CEO of The Smart Tire Company. “The unique combination of these advanced materials, coupled with a next generation, eco-friendly design make for a revolutionary product.”

• Spin-offs from NASA:
  • Camera Phones: 1990s, JPL created a camera small enough to fit on a spacecraft (⅓ of all cameras contain this tech)
  • Scratch Resistant Lens: Developed the technique utilize in the process
  • Athletic Shoes
  • LEDs
  • CAT Scans
  • Freeze Dried Foods

Quest for prosthetic retinas progresses toward human trials, with a VR assist | TechCrunch (32:31)

• Latest advancement was accomplished by Diego Ghezzi, who holds the Medtronic Chair in Neuroengineering (LNE) at EPFL’s School of Engineering.
  • Located in Lausanne, Switzerland

• “Our system is designed to give blind people a form of artificial vision by using electrodes to stimulate their retinal cells,” says Ghezzi.

• Process from EPFL News:
  • Captures field of view image from an outside device (e.g. glasses)
  • Sends the data to a microcomputer placed in one of the eyeglasses.
  • Microcomputer turns the data into light signals which are transmitted to electrodes in the retinal implant.
  • Electrodes then stimulate the retina in such a way that the wearer sees a simplified, black-and-white version of the image.
  • Wearers must learn to interpret the many dots of light (10,500) in order to make out shapes and objects.

• Ghezzi gives an analogy as to what the wearer would see: “It’s like when you look at stars in the night sky – you can learn to recognize specific constellations. Blind patients would see something similar with our system.” 

• To test this somehow the researchers couldn’t just install a retinal implant on a human participant, so they went to a medium you may not have expected: VR.
• Simulated in a VR environment what a person with this retinal implant would see:
  • Dark except for little simulated “phosphors,” the pinpricks of light they expect to create by stimulating the retina.

• Primary finding: Most important factor was visual angle — the overall size of the area where the image appears. 

• This demonstration showed that the implant’s parameters are theoretically sound and the team can start working toward human trials.

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