Yanny or Laurel? The Sound that Divided the Internet

One chaotic week in 2018, the internet was torn apart by one singular audio clip. Two syllables, repeated over and over, sparked worldwide confusion. I was a voice saying “Yanny” or “Laurel”. If you ask me, I heard Yanny on my first listen, but now I can easily switch between the two (unlike the dress mentioned in one of my previous posts). I am here once again to talk about how the same audio can be interpreted differently by ears around the world, the same way one picture of a dress can be interpreted differently by eyes around the world.

In my article about “The Dress,” I related the function of our visual system to a camera. I clarified that the eyes do not record everything like a camera, but use context and past experience to interpret visual cues. Similarly, our ears do not hear everything like a microphone. They interpret input based on frequencies and expectations, which can also change as we age.

Hearing isn’t always believing.

Sound waves are interpreted by entering the eardrum, travelling to the inner are, and activating hair cells. The auditory cortex in your brain constructs what you hear based on the activation patterns of your hair cells, past experiences, and the sensitivity of your ears, all of which can differ from each individual (Moore 2012).

When people hear different words in the audio clip, it is caused by the brain forming different perceptions of the same signal, not personal preference.

The Science Behind It

The audio clip contains a mixture of frequencies. When analyzed, it was found that there were frequencies at both the low range (400-500 Hz) and high range (2500-300 Hz) in the audio clip (Rosen 2018). People who hear “Laurel” tend to emphasize lower frequencies, while people who hear “Yanny” tend to emphasize high frequencies (Rosen 2018). This is similar to “The Dress,” where people who saw each color set had a different preference for color undertones.

Presbycusis is a phenomenon that causes people to lose sensitivity to upper ranges of audio frequency as they age, causing a physical variation in how people hear (Gates et. al., 2006). Since “Yanny” is encoded in high-frequency sounds, it is more likely for it to be heard by younger people (like me!).

Surveys have shown that it was more likely for older adults to hear “Laurel” due to its lower frequencies. These frequencies are more stable throughout one’s lifespan.

Why does the brain choose one word over the other?

Top-down processing is when the brain uses existing knowledge and experience to interpret sensory information, instead of letting the sensory information motivate the interpretation. This type of processing is important for interpreting ambiguous sounds such as this one (Hickok & Poeppel, 2007). If your brain is used to certain vowels or speech patterns, you may hear a specific word. For example, more American English speakers heard “Laurel” because the low-frequency format is common in American English, while listeners who spoke a language with a higher-frequency format were more likely to hear ‘Yanny’ (Samuel, 2011).

What does this reveal?

Our brain does not perceive all the senses the same way as everyone else! Hearing sounds that are ambiguous forces our brain to guess, and not all brains guess the same way.

References

Gates, G. A., & Mills, J. H. (2005). Presbycusis. The Lancet, 366(9491), 1111–1120. https://doi.org/10.1016/S0140-6736(05)67423-5

Hickok, G., & Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews Neuroscience, 8(5), 393–402. https://doi.org/10.1038/nrn2113

Moore, B. C. J. (2012). An introduction to the psychology of hearing (6th ed.). Brill.

Rosen, J. (2018). The science behind Yanny vs. Laurel: Why we hear what we hear. The Journal of the Acoustical Society of America, 144(1), 62. https://doi.org/10.1121/1.5052025

Samuel, A. G. (2011). Speech perception. Annual Review of Psychology, 62, 49–72. https://doi.org/10.1146/annurev.psych.121208.131643

 

 

 

The Dress that Broke the Internet

I’m sure everyone has heard of this dress before, right? If you are not familiar, the picture of this dress went viral a few years ago because everyone on the internet could not agree whether it was blue and black or white and gold in color. If you ask me, I would say I see white and gold. How is it possible that we all look at the same picture but see completely different colors?

Seeing isn’t always believing

But why is this true? Why is everyone seeing this picture differently? Instead of recording the world like a camera, our brain actively interprets what we see using light, context, and past experiences (Foster 2011).  I’m here to talk about the neuroscience behind perceptions and why different people see different colors in the same picture.

Battle of the Brain

Studies have shown that there are stark individual differences in how people see color (Lafer-Sousa  2015). For example, how I define “red” is not the same way you define “red.” One specific study looked at which wavelengths of light were recognized in people who looked at the picture of the dress. People who prefer a more illuminating light, like a blue sky, saw white and gold because they were recognizing shorter wavelengths of light. On the other hand, people who favor warm light see blue and black because they see the longer wavelengths of light (Lafer-Sousa 2015).

Can you see it both ways?

Now that you know that people see both color schemes, are you able to see the other one? Personally, I am only able to see white and gold. Other people can switch between white & gold and blue & black. The quality of being able to switch between your perceptions is called a multistable image. Most of the people who are able to switch between the two color schemes in this picture have a background in art, so they are well-experienced in different color perceptions (Lafer-Sousa 2017).

References

Foster, D. H. (2011). Color constancy. Vision Res, 51(7), 674–700. https://doi.org/10.1016/j.visres.2010.09.006

Lafer-Sousa, R., Hermann, K. L., & Conway, B. R. (2015). Striking individual differences in color perception uncovered by ‘the dress’ photograph. Current biology : CB, 25(13), R545–R546. https://doi.org/10.1016/j.cub.2015.04.053

Lafer-Sousa, R., & Conway, B. R. (2017). Journal of Vision, 17(2), 25. https://doi.org/10.1167/17.2.25

When I was first learning to bake, I always wondered what was so special about ready-made mixes. In my mind, cake really wasn’t that complicated. Most cake recipes that I found online always called for some combination of flour, sugar, eggs, salt, and butter. So, why was it that the boxed cake mix always resulted in the same, consistent success, while baking from scratch yielded uncertain results?

What is in Cake Mix?

Cake mix is a box of conveniently measured out dry ingredients. All the baker needs to do is add eggs, some kind of fat, like oil, and a liquid, like water or milk. But what exactly makes up those dry ingredients?

According to the Betty Crocker website, their yellow cake mix consists of quite recognizable ingredients, including flour, sugar, corn syrup, baking soda, and corn starch. These match the ingredients one could think of in a normal recipe. The flour makes up most of the cake, while the sugar and corn syrup are for sweetness. The baker would add in the water, eggs, and fat (vegetable oil) on their own, so the question lies in the rest of the ingredients. 

The Extra Additives

The rest of the ingredients of the Betty Crocker yellow cake mix make up less than 2% of the ingredients. However, they are extremely important to the stability of the cake. According to the label, these ingredients are monoglycerides, dicalcium phosphate, sodium stearoyl lactylate, xanthan gum, and cellulose gum. These ingredients are additives that help maintain the texture, stability, and shelf life of the mix. 

• • For instance, dicalcium phosphate is a tasteless, odorless additive that is usually included along with flour. It is meant to break up the ingredients evenly in the baking process and improve the consistency of the flour (Enax et al., 2022).
  • Additionally, sodium stearoyl lactate is an additive that is also used as a stabilizer and emulsifier in processed foods (FAO & WHO, 1996). As a stabilizer, its job is to make sure that the food’s texture and taste maintain their quality during extended times on the shelf. As an emulsifier, its job is to allow ingredients like oil and water to mix together.
  • Xanthan gum is also an ingredient commonly used in both food, polishes, and cleaners. Its job is to act as a stabilizer and thickener in convenience foods. More specifically, its job is to retain moisture in bakery goods and trapping gas in ready-made cake mixes so that they bake better (Katzbauer, 1997). 

These are just a few of the extra ingredients that make cake mixes as consistent and convenient as they are today. They hold the ingredients together, enhance the taste and texture of the cake, and ensure that the results are similar each time. So, while, yes, cake mix is essentially the same mixture of flour and sugar than one might expect to find in a regular cake, there is a bit of science involved to help make sure it’s a bit easier each time!

 

References

Betty Crocker (n.d.). Betty Crocker Favorites Super Moist Yellow Cake Mix, Holiday Baking, 13.25 oz https://www.bettycrocker.com/products/betty-crocker-baking-and-cake-mixes/yellow 

Enax, J., Meyer, F., Schulze Zur Wiesche, E., & Epple, M. (2022). On the Application of Calcium Phosphate Micro- and Nanoparticles as Food Additive. Nanomaterials (Basel, Switzerland), 12(22), 4075. https://doi.org/10.3390/nano12224075 

FAO & WHO. (1996). SODIUM STEAROYL-2-LACTYLATE. Joint FAO/WHO Expert Committee on Food Additives (JECFA) Monographs. https://www.fao.org/fileadmin/user_upload/jecfa_additives/docs/Monograph1/Additive-424.pdf 

Katzbauer, B. (1997). Properties and applications of xanthan gum. Polymer Degradation and Stability, Vol, 59, Iss. 1–3, https://doi.org/10.1016/S0141-3910(97)00180-8 

Maehasi, N (2020). My very best Vanilla Cake – stays moist 4 days! https://www.recipetineats.com/my-very-best-vanilla-cake/ 

Wildfire seasons are becoming longer and more intense, and the speed at which a fire is detected can determine how much damage it ultimately causes. To improve early detection, researchers and government agencies are turning to an unexpected tool: satellites equipped with advanced thermal sensors and AI-powered alert systems.

Modern Earth-observation satellites can detect tiny temperature changes on the planet’s surface- sometimes only a few degrees above normal. When a hotspot appears in a remote forest or grassland, the satellite sends the data to a processing center, where algorithms analyze the signal to determine whether it is likely to be a wildfire, a controlled burn, or simply a patch of warm ground. This automated screening filters out false alarms and helps firefighters focus on genuine threats.

One major advantage of satellite detection is coverage. Traditional lookout towers or reporting systems depend on someone nearby noticing smoke. Satellites, however, pass over the same region several times a day, and some specialized systems- like Europe’s Sentinel satellites or NASA’s FIRMS platform- can relay updates within minutes. In regions that are difficult to access by road, this can mean the difference between a quick response and a fire that grows out of control.

The technology is also becoming increasingly accessible. Fire agencies, environmental groups, and even school programs now use public satellite dashboards to monitor hotspots in real time. Students studying climate science can open a web browser and watch how temperature, drought, and vegetation patterns influence fire risk across entire continents.

Still, satellite monitoring has limitations. Heavy clouds, dense smoke, or short revisit times can delay detection. That’s why many regions combine satellite data with drones, ground sensors, and local reporting networks. Together, these tools create a layered system- one that aims to spot fires earlier, respond faster, and ultimately protect more people and ecosystems.

As climate patterns shift, the need for rapid wildfire detection is only growing. Satellite technology is becoming a crucial part of the solution, offering a high-tech way to monitor the planet and catch fires before they spread.

 

Works Cited

European Space Agency. “Sentinel-3: The Mission.” ESA, 2023, https://www.esa.int/Applications/Observing_the_Earth/Copernicus/Sentinel-3.

NASA. “FIRMS: Fire Information for Resource Management System.” NASA Earthdata, 2023, https://firms.modaps.eosdis.nasa.gov/.

NASA. “How NASA Detects Wildfires From Space.” NASA Earth Observatory, 2022, https://earthobservatory.nasa.gov/features/Wildfires.

Schroeder, Wilfrid, et al. “The New VIIRS 375 m Active Fire Detection Data Product.” Remote Sensing, vol. 6, no. 7, 2014, pp. 7125–7149. MDPI, https://doi.org/10.3390/rs6077125.

United States Forest Service. “Early Detection of Wildfires Using Satellite Data.” USDA Forest Service, 2021, https://www.fs.usda.gov/research/.

Artificial-intelligence technology is beginning to transform one of the oldest tools in science: the microscope. Researchers at institutions such as UCLA and Caltech are developing AI-powered microscopes capable of analyzing samples in real time, flagging unusual cells, and helping scientists diagnose diseases faster and more accurately.

These advanced systems work by capturing high-resolution images and sending them through trained deep-learning models. When a researcher places a slide under the lens, the AI quickly scans thousands of cells, highlighting features that may indicate infection, cancer, or other abnormalities. Instead of relying solely on painstaking manual examination, scientists can use the AI’s suggestions as a guide, focusing their attention where it matters most.

Early results have been promising. In several studies, AI-assisted microscopes identified harmful bacteria and subtle cellular changes at speeds that outperform traditional methods. Some algorithms were even able to detect patterns that are difficult for the human eye to notice, offering a powerful complement to expert analysis.

What makes this technology especially impactful is its potential beyond major research hospitals. Schools, community clinics, and field labs could all benefit from microscopes that combine affordable hardware with intelligent software. Students learning cell biology could see the AI outline abnormal cells as they appear, while clinicians in resource-limited areas could diagnose infections more quickly and with improved accuracy.

However, researchers emphasize that AI is not replacing human expertise. The algorithms must be trained carefully, and scientists still play a critical role in verifying results and preventing misclassification. The goal is not to remove humans from the process, but to strengthen diagnostic tools and make high-quality analysis more widely accessible.

As AI continues to advance, the role of the microscope is shifting from simple magnification to intelligent interpretation. This fusion of computation and biology has the potential to accelerate diagnosis, improve education, and bring powerful analytical tools to places that need them most.

 

Works Cited

Ozcan, Aydogan, and Yibo Zhang. “Artificial Intelligence–Powered Optical Microscopy and Its Applications.” ACS Photonics, vol. 6, no. 11, 2019, pp. 2729–2741. American Chemical Society, https://doi.org/10.1021/acsphotonics.9b01029.

Rivenson, Yair, et al. “Deep Learning Microscopy.” Optica, vol. 4, no. 11, 2017, pp. 1437–1443. Optical Society of America, https://doi.org/10.1364/OPTICA.4.001437.

Zhang, Yibo, et al. “Pathologist-Level Interpretation of Microscope Images Powered by Deep Learning.” Nature Biomedical Engineering, vol. 3, 2019, pp. 1207–1215. Nature Publishing Group, https://doi.org/10.1038/s41551-019-0362-y.

Caltech. “AI Microscope Can Help Diagnose Diseases in Real Time.” Caltech News, 3 May 2022, https://www.caltech.edu/about/news/ai-microscope-can-help-diagnose-diseases.

University of California, Los Angeles (UCLA). “UCLA Engineers Develop AI-Powered Microscope to Automatically Detect Bacteria.” UCLA Newsroom, 12 Mar. 2020, https://newsroom.ucla.edu/releases/ai-microscope-bacteria-detection.

Imagine putting on a headset, picking up a 3D-printed lab tool, and suddenly you’re in a virtual chemistry lab- pouring colorful liquids, watching reactions bubble and swirl, all without spilling a drop. That’s not science fiction anymore. At Arizona State University, researchers have created a “mixed-reality” chemistry lab that blends the real world with the digital one (Arizona State University, 2023).

In a recent experiment, students used a 3D-printed burette- a tool chemists use for titrations- that connected to a computer simulation. When students turned the real valve, the digital liquid moved in the virtual flask (Amador et al., 2020; Meteor Studio, n.d.). They could watch the chemical reaction happen on screen, just like in a real lab, but with no mess or danger.

The researchers wanted to see if this new kind of setup actually helped students learn chemistry better. The results were fascinating: students who already had some chemistry experience learned even more with the mixed-reality setup. But beginners, who were still figuring out the basics, did better with the simpler version on a regular computer screen (Johnson-Glenberg et al., 2023). That means the kind of tools we use to learn science might need to match where we are in our learning journey.

What makes this so exciting is how it could change the way chemistry is taught. Schools that don’t have full lab spaces or expensive equipment could still give students the experience of “doing chemistry,” not just reading about it (Arizona State University, 2023). You can twist a valve, watch molecules react, and understand what’s happening- all while sitting in a classroom or even at home.

It’s a powerful reminder that chemistry isn’t only about memorizing formulas or mixing real chemicals. It’s about understanding how things work- and technology is opening new ways to do that. Whether you’re a future scientist or just someone curious about how the world works, the chemistry classroom of tomorrow might not look like the one you know today. It might be part real, part virtual, and completely amazing.

 

Works Cited

Johnson-Glenberg, M. C., Yu, C. S. P., Liu, F., Amador, C., Bao, Y., Yu, S., & LiKamWa, R. (2023). Embodied mixed reality with passive haptics in STEM education: randomized control study with chemistry titration. Frontiers in Virtual Reality, 4:1047833. https://doi.org/10.3389/frvir.2023.1047833 

Amador, C., Liu, F. W., Johnson-Glenberg, M. C., & LiKamWa, R. (2020). Work-in-Progress: Titration Experiment — Virtual Reality Chemistry Lab with Haptic Burette. In D. Economou et al. (Eds.), Proceedings of the 6th International Conference of the Immersive Learning Research Network (iLRN 2020), 363-365. IEEE. https://doi.org/10.23919/iLRN47897.2020.9155209 

Arizona State University. (2023, October 13). A new class of chemistry experiments. ASU News. Retrieved from https://news.asu.edu/20231013-discoveries-new-class-chemistry-experiments 

Meteor Studio, Arizona State University. (n.d.). Mixed Reality Virtual Titration Experiment. Retrieved from https://meteor.ame.asu.edu/projects/titration/ 

 

Every system in our body is connected, and every process in it is affected by all others. When two processes affect each other in a bidirectional manner, they are called axes. Scientists have recently looked into the gut-skin-brain axis, or the connection between your gut and skin health and your psychological well-being.

It is commonly known that your gut has its own microbiome, consisting of bacteria that help us digest our food. Less people know that there is a similar microbiome on your skin. Right now, there are thousands of different species of bacteria, fungi, viruses, and other microorganisms living in symbiosis on the surface of your skin. The word microbe usually comes with a negative connotation, making you think of disease or parasites, but the microbes both on our skin and in our gut are vital to our health. Having an unbalanced gut microbiome, or being in dysbiosis, is often associated with various skin conditions, such as eczema, psoriasis, rosacea, or acne (Wiginton 2025).

The skin makes for a very harsh environment. It is dry and we are constantly shedding skin cells, which makes it a less than ideal place for a microbe to live. But many species have adapted to be able to handle life on the skin, and most have preferred locations on the body as well. Some bacteria prefer somewhere warm, such as the armpit or foot, whereas others thrive somewhere oily, like our face. These microbes actually work as part of our immune system. Our skin is our largest organ and prevents pathogens from entering our body. The microbes that thrive on our skin like the harsh environment, and help keep it so. Other harmful microbes often cannot survive in these conditions, and sometimes are even attacked by our skin’s microbes (Byrd et al. 2018).

The link between the gut microbiome and our psychological well-being has been well established as bidirectional, meaning they affect each other. Dysbiosis, or an imbalance, in the gut has been linked to depression, anxiety, and autism. On the other hand, stress can alter our gut microbiome and make us more susceptible for gastrointestinal disorders. Studies have even shown which bacteria, Cutibacterium, show the strongest link to our psychological well-being (Tyson-Carr et al. 2025).

Recently, proof has been found of a triple axis, the gut-skin-brain axis. Probiotics are living microorganisms in our gut and have been found to play a part in our immune system. These microbes in the gut help our immune cells distinguish between harmful and beneficial microorganisms. Bacteria in the gut also release molecules that have anti-inflammatory effects on the skin. Studies have shown that taking probiotics benefits your gut microbiome, which in turn benefits our immune system, creating a snowball effect that can be beneficial towards our skin health and psychological well-being. Probiotics have even been proven to improve some chronic inflammatory skin diseases, such as psoriasis by increasing certain microbe species in the gut (Abdi et al. 2024).

 

Wiginton, K. (2025). What Is the Skin Microbiome? WebMD. https://www.webmd.com/skin-problems-and-treatments/skin-microbiome

Byrd, A. L., Belkaid, Y., & Segre, J. A. (2018). The human skin microbiome. Nature Reviews Microbiology, 16(3), 143–155. https://www.nature.com/articles/nrmicro.2017.157

Tyson-Carr, J., Leng, J., Scott, M., Adams, S., Hoptroff, M., Murphy, B., Fallon, N., Paterson, S., Thomas, A., Giesbrecht, T., & Roberts, C. (2025). Body site-specific associations between human skin microbiome composition and psychological wellbeing. British Journal of Dermatology, 193(Supplement 2), ii6–ii14. https://academic.oup.com/bjd/article/193/Supplement_2/ii6/8140349

Abdi, A., Oroojzadeh, P., Valivand, N., Sambrani, R., Lotfi, H. (2024). Immunological aspects of probiotics for improving skin diseases: Influence on the Gut-Brain-Skin Axis. Biochemical and Biophysical Research Communications, 702. https://www.sciencedirect.com/science/article/pii/S0006291X24001682