Finding the right math for medical problems

The linked article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). However, even though the main audience for this magazine is professional mathematicians, I wrote it to be understandable even if you gloss over the math. And it involves the word “tortuosity”, which is just fun to say.

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A Nonparametric Swiss Army Knife for Medicine

For SIAM News:

The complexity of living things is frequently humbling for mathematicians. Even a single cell contains a plethora of processes and complicated interactions that tractable mathematical models cannot easily describe. Researchers have applied nonlinear dynamics, mechanical analogs, and numerous other techniques to understand biological systems, but the tradeoffs of modeling often err on the side of reductionism.

For this reason, Heather Harrington of the University of Oxford and her collaborators are turning to global mathematical methods and drawing on experimental data to identify the best techniques. Harrington described several of these methods during her invited talk at the 2021 SIAM Conference on Applications of Dynamical Systems, which took place virtually earlier this year.

“The way that we look at dynamical systems is usually in a small region of the parameter space,” Harrington said. This approach is helpful if one knows a lot about the model and its parameters, but it can be hard to extract detailed predictions from the model if the parameters in question range over large values. “In biology, we often don’t know if the system is very close to a value in parameter space because the variables or parameters are difficult to measure or the data is too messy,” she added.

[read the rest at SIAM News]

The danger of climate change may be its rate

As with many of my other contributions to SIAM News, the article “It’s Not the Heat, It’s the Rate: Rate-Inducted Tipping’s Relation to Climate Change” includes some mathematical equations, but I’ve tried to write the piece so you can understand it even if you gloss over that part. And this article in particular has some important concepts relating to the biggest issue facing humanity today: climate change.

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It’s Not the Heat, It’s the Rate

Rate-Inducted Tipping’s Relation to Climate Change

For SIAM News:

For many years, scientists have warned that the Atlantic meridional overturning circulation (AMOC)—the thermal cycle that drives currents in the Atlantic Ocean—is getting weaker [1]. Among other effects, the AMOC carries warm water to Ireland and the U.K. and returns cooler water from the north to southern regions. Instability in this circulation cycle could result in its complete collapse and cause widespread disruptions in temperature, changes in rain and snowfall patterns, and other natural disasters.

The potential loss of the AMOC represents a possible tipping point due to human-driven climate change. Global increases in temperature lead to warmer ocean water and melting polar ice, both of which decrease water density (see Figure 1). The subsequent lower-density water does not sink as much as it cools, thus disrupting the thermal cycle. When the AMOC collapsed in the prehistoric past, it jolted Earth’s climate and affected every ecosystem.

[Read the rest at SIAM News]

Teaching AI to “Do No Harm”

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Is There an Artificial Intelligence in the House?

For SIAM News:

Medical care routinely involves life-or-death decisions, the allocation of expensive or rare resources, and ongoing management of real people’s health. Mistakes can be costly or even deadly, and healthcare professionals—as human beings themselves—are prone to the same biases and bigotries as the general population.

For this reason, medical centers in many countries are beginning to incorporate artificial intelligence (AI) into their practices. After all, computers in the abstract are not subject to the same foibles as humanity. In practice, however, medical AI perpetuates many of the same biases that are present in the system, particularly in terms of disparities in diagnosis and treatment (see Figure 1).

“Everyone knows that biased data can lead to biased output,” Ravi Parikh, an oncologist at the University of Pennsylvania, said. “The issue in healthcare is that the decision points are such high stakes. When you talk about AI, you’re talking about how to deploy resources that could reduce morbidity, keep patients out of the hospital, and save someone’s life. That’s why bias in healthcare AI is arguably one of the most important and consequential aspects of AI.”

[ read the rest at SIAM News ]

Bicycles, networks, and biological homeostasis

The linked article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While this article contains equations, I wrote it to be understandable even if you gloss over the math.

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

Balancing Homeostasis and Health

For SIAM News:

Human beings are not bicycles. However, mechanistic metaphors for the human body abound. For instance, we compare athletes to finely-tuned machines and look for equations that are derived from mechanics to describe biological processes — even when the relationship is no better than an analogy.

However, the concept of homeostasis clearly exemplifies the breakdown of mechanistic models when one applies them to the human body. Homeostasis is the process by which an organism maintains a stable output regardless of input (within reasonable limits). The most familiar example is human body temperature, which stays within a remarkably small range of values regardless of whether one is sitting in a cold room or walking outside on a hot day.

“In a bicycle, you know what each part is for,” Michael Reed, a mathematician at Duke University, said. “We are not machines with fixed parts; we are a large pile of cooperating cells. The question is, how does this pile of cooperating cells accomplish various tasks?”

[ Read the rest at SIAM News ]

Coding complicity in police violence

Occasionally people (usually my fellow white men) yell at me to “stick to science!” Well, sticking to science is a luxury that white women and scientists of color can’t afford, and pretending scientists aren’t complicit in violence toward underrepresented groups preserves inequality. At the same time, some within the broad tent of STEM (science, technology, engineering, and mathematics) actively perpetuate problems. My latest piece for SIAM News discusses one particular example — the ways in which computer scientists and other developers of code have helped increase racial profiling and police brutality — but many of the points apply more broadly to STEM. (Bonus: look for the Rage Against the Machine lyrics.)

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When Software Harms, What You Reap Is What You Sow

For SIAM News:

As of July 2020, the CalGang database contained the names and personal details of nearly 90,000 people in the state of California who are suspected of being in gangs or associating with gang members. Despite its stated purpose to provide law enforcement agencies with accurate intelligence information, audits and independent investigations revealed that the database was riddled with errors, falsified material, racial profiling, and other serious problems.

Databases and algorithms are ubiquitous parts of our interconnected world, but CalGang illustrates a major way in which they can fail people. If a streaming service suggests a movie that you do not like, no real harm is done; but if your name appears in CalGang, you may face consequences like increased police harassment or harsher sentences if charged with a crime.

“[Most of] the people creating these technologies are not affected in negative ways,” Seny Kamara, a computer scientist at Brown University, said. “But if you’re a young Black male growing up in Chicago or New York or California, you know that you may end up as a false positive in a gang database, and that affects your life in a completely different way.”

[Read the rest at SIAM News]

Ecological stability far from equilibrium

toxic algae on Lake Erie, as seen by the Landsat 8 satellite

The linked article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While this article contains equations, I wrote it to be understandable even if you gloss over the math.

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

Ecological Transients and the Ghost of Equilibrium Past

For SIAM News:

The sight and smell of eutrophication—in the form of a layer of stinking green algae on a lake or pond—is likely familiar to many readers. The result is detrimental, even toxic, to other species that rely on the water, ranging from tiny animals to birds and even humans. For example, eutrophication on Lake Erie affects millions (see Figure 1). But the real culprit is actually the substance that feeds the algae: excess phosphorous that is produced by human activities like fertilizer runoff and leaky septic systems.

To manage eutrophication, one must know whether the affected body of water resides in a eutrophic stable state, or if its state is a long transient. The second case mimics stability because it can last a long time but is sustained by another source of phosphorous in the lakebed sediments. According to Tessa Francis, an ecologist at the University of Washington Puget Sound Institute, the wrong management choice has major consequences in terms of costs and trade-offs.

“You’re investing all of this social, political, and economic capital into management, but you’re getting no results from it,” Francis said. “If you gave the system a bigger smack by adding an alternative management strategy to tackle the phosphorus pool at the bottom of the lake, that would be more likely to get your lake back to the state you want. This is just one consequence of long transients in terms of how they affect management decisions.”

[Read the rest at SIAM NEWS]

The cost of “herd immunity” for COVID-19 is too high

My latest comic with Maki Naro is up at The Nib, the award-winning nonfiction comics site! This time we tackle the question of “herd immunity” for the COVID-19 pandemic, which has been suggested by a number of politicians as a strategy for beating the disease. As Maki and I describe, without a vaccine, this is less a strategy than a cynical throwing up of hands. Read on for an explanation of what “herd immunity” is and why it’s basically giving up.

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Waiting For Herd Immunity is Not the Answer

Panel from “Waiting for Herd Immunity is Not the Answer” at The Nib. Click to read the rest. [Credit: Maki Naro (art)/moi (words)]

P.S. Do you like this comic? If so, please pledge to Maki’s and my forthcoming comics collection Who Owns an Asteroid? (from Unbound), which will include many such nonfiction science comics in full color!

Sizing up the weirdest objects in the universe

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How big is a neutron star?

Astrophysicists are combining multiple methods to reveal the secrets of some of the weirdest objects in the universe.

For Symmetry Magazine:

Neutron stars are arguably the strangest objects in the cosmos. Born from the deaths of massive stars, they combine strong gravity with temperatures and densities higher than anything we can make in the lab.

While we’ve known about neutron stars for the better part of a century, astrophysicists still aren’t entirely sure how large they are. That uncertainty is related to two other unanswered questions: What’s in the middle of neutron stars, and how massive can they grow?

[read the rest at Symmetry Magazine]

Cold War treaties aren’t sufficient for the era of asteroid mining

Why did I, a physics/astronomy journalist, write about asteroids for a deep-sea mining trade magazine? Read on! Oh yes, and pledge to my book of science comics with Maki Naro, Who Owns an Asteroid?

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The World Is Not Ready for Asteroid Mining, But It Needs To Be

For Deep Sea Mining Observer:

Nothing is less “deep sea” than an asteroid, yet parallels exist between these two domains, particularly when it comes to resource extraction. Asteroids are debris left over from the formation of the Solar System roughly 4.5 billion years ago. Due to our shared origin, Earth and asteroids contain the same basic materials: water, carbon compounds,  metals, and so forth. The “metals and so forth” part has drawn the interest of nations and private companies, since many asteroids are potentially rich in gold, platinum, and rare-earth elements. Astronomers have identified 957,798 asteroids as of December 2019, of which about 10,000 are known to orbit close enough to our planet to be classified as near-Earth objects — with some reachable by spacecraft.

With no biosphere, ecosystem services, or local stakeholders, extracting materials from asteroids carries few of the environmental concerns present in terrestrial or ocean mining on Earth.

Both the deep ocean and outer space are governed by international law, with much of said law constructed during the Cold War. Interested parties often bring a certain Wild West mentality to resource extraction in both instances. However, space law lags behind terrestrial laws on a number of fronts, and recent moves by individual nations and companies should be seen as a wake-up call.

[read the rest at DSM Observer…]

Fighting racial gerrymandering with math

The linked article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While this article contains equations, I wrote it to be understandable even if you gloss over the math.

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

The Mathematical Fight for Voting Rights

For SIAM News:

State and local governments will redraw voting districts based on new information following completion of the 2020 U.S. Census. Ideally, this process ensures fair representation. In practice, however, districting often involves gerrymandering: the deliberate planning of districts to dilute the voting power of certain groups in favor of others, which violates the law.

Racial gerrymandering—drawing districts to limit the power of voters of color to select candidates they favor—is a particularly pernicious problem. Section 2 of the Voting Rights Act (VRA) of 1965 specifically prohibits this practice, but that has not stopped authorities from doing it anyway. “A number of court decisions have purposefully asked mathematicians, political scientists, and statisticians to use specific methods to try and understand racial gerrymandering,” Matt Barreto, a professor of political science and Chicana/o studies at the University of California, Los Angeles, said.

Barreto and his colleagues employ powerful statistical methods and draw on census and other public data to identify gerrymandered districts. Utilizing these tools, mathematicians can test proposed district maps or draw their own, designing them from the ground up to prevent voter dilution.

[Read the rest at SIAM News…]