The Academic Minute

Can the light reflected from a leaf reveal the health of a tree?

Nathan Swenson, professor of biological sciences and the Gillen director of the Environmental Research Center at the University of Notre Dame, looks for clues in the canopy.

Faculty Bio

Nathan Swenson is a professor of biological sciences and the Gillen Director of the University of Notre Dame Environmental Research Center. The goal of the research conducted by his group is to leverage information regarding intra- and inter-specific variation in tree performance to understand and predict the past, present, and future distribution of forest biodiversity.

Transcript:

Forests often look healthy — right up until they aren’t. By the time trees show visible signs of drought, disease, or pest damage, it can already be too late to prevent widespread decline. So, one of the biggest challenges in ecology is detecting stress early enough to protect forest health. Field surveys give us detailed information, but they’re too slow and labor-intensive to cover large areas. Genomic tools can reveal the activity of genes involved in drought responses or defense against pathogens, but those approaches are costly and difficult to scale. In our recent research, we asked a different question: can the light reflected from a leaf reveal what’s happening inside it at the genetic level? Leaves reflect light in specific wavelengths depending on their chemistry and condition. We measured leaf reflectance and paired it with gene expression data for genes tied directly to water stress and plant defense. For hundreds of genes we analyzed, specific wavelengths of reflected light were strongly associated with gene activity. That means we may be able to detect early molecular responses to stress—before trees visibly decline. By linking reflected light to gene expression, we move closer to monitoring forest health at landscape scales, using airborne or satellite sensors that measure light reflectance from the canopies of trees to identify forest declines before they reach a tipping point.

Read More:

[Notre Dame News] - How light reflects on leaves may help researchers identify dying forests

University of Notre Dame Environmental Research Center

Swenson Lab

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Most Americans shouldn’t have to do their own taxes.

Ryan Wilson, Henry B. Tippie Chair in Accounting at the University of Iowa, examines why.

Faculty Bio:

Ryan J. Wilson is the Henry B. Tippie Chair in Accounting and the department executive officer in Accounting at the Tippie College of Business at the University of Iowa. Previously, he was director of the School of Accounting at the University of Oregon Lundquist College of Business. He earned his doctorate degree at the University of Washington. He’s received recognition for excellence in accounting instruction at both the University of Iowa and University of Oregon.

Transcript:

Today is April 15. Tax day. The end of a season when Americans sweat over their 1040 forms or pay someone else to sweat over their 1040s for them.

But it doesn’t have to be that way. An opt-in system called ReadyReturn, widely used in more than 30 countries, prepares taxes automatically for free, and most U.S. taxpayers can benefit from something like it.

For about half of American taxpayers who just have withholding taxes or 1099s, the government already has all the information needed to prepare the returns. This renders the tax preparation process unnecessary for most, as we’re only giving the government information it already has.

ReadyReturn is already used in countries like the UK, Denmark, Sweden, and Spain and the concept is simple. The government prepares your tax return for you using data it access through third parties such as banks or brokerages. The government mails you the return (or in some cases, texts it) and, if you agree with what the government says you owe, all you have to do is sign off.

And it’s free.

More complicated returns would still need to be completed by a professional. And if someone wants to do their own return even if they’re eligible for a ReadyReturn, they can still do that.

However, for many Americans who have relatively simple returns, especially older and younger taxpayers, the government already has all the information needed to prepare them. Therefore, there’s little point in taxpayers submitting W2s and other tax paperwork to the IRS. Imagine the relief of so many busy taxpayers knowing this archaic obligation is no more.

Adopting a ReadyReturn program would not make the annual tax return process more enjoyable. But it would least make it far less costly to millions of Americans in both time and money.

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How do emotions in a social media post influence who shares it?

Yifan Yu, assistant professor of information, risk, and operations management at the University of Texas at Austin’s McCombs School of Business, examines this.

Faculty Bio:

Yifan Yu’s research centers on (1) the economics of artificial intelligence and machine learning; (2) business analytics leveraging online unstructured data (i.e., text, images, videos, networks, behavioral sequences); and (3) data analytics to facilitate volunteerism, sustainable operation, and social justice. I apply machine/deep learning, network analysis, econometric/game-theoretical modeling, and lab/field experimental methods to tackle questions in these fields. He has published in numerous research journals and spent several years as a research analyst or applied scientist for tech companies such as Amazon and Tencent (WeChat). Before I started a career in academic research, I worked in management consulting firms, venture capital, and private equity companies. He also established an online platform company with two partners in 2015 and worked as an entrepreneur for two years.

Transcript:

Not all feelings travel the same way online.We analyzed nearly 400,000 articles shared on a large social network, tracking how each post spread among more than six million people. Rather than counting clicks, we mapped each “cascade” — its size, how deep it traveled from person to person, how wide it became at any level, and how “viral” it was through peer-to-peer sharing.Specific emotions predicted what happened. Content expressing anxiety, love, or surprise reached more people and penetrated deeper into networks. Anger, sadness, and even joy were tied to smaller, shallower cascades.Why? Emotions are social signals. Anxiety invites advice and coordination. Love affirms bonds. Surprise provokes curiosity. Anger and sadness often trigger caution or withdrawal. Joy tends to be self-contained — good news for the poster, less reason for others to pass along.These patterns can vary. The same emotion can travel differently by age and gender, and among close friends versus acquaintances. But our findings reveal a deeper truth: emotions shape the architecture of information flow. Some specific feelings pull people in and propel ideas outward. Understanding these dynamics gives us new insight into how influence, attention, and connection emerge in today’s social networks.

Read More:[Informs PubsOnLine] - Emotions in Online Content Diffusion

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We are still learning how best help children with autism early in life.

Andrey Vyshedskiy, lecturer at Boston University, examines the importance of early learning interventions.

Faculty Bio:

Dr. Andrey Vyshedskiy is a neuroscientist at Boston University. He has authored more than 100 original research article published in leading scientific journals, including The New England Journal of Medicine and Nature. His research focuses on child development, the neurological basis of imagination, and the evolution of human language. Dr. Vyshedskiy has founded multiple successful companies and led the development of several FDA-approved medical devices. Building on his research, ImagiRation has developed a novel therapy for children that has been shown to significantly improve language abilities. His most recent book, The Evolution of Language: How the Brain Evolved Syntactic Language from Early Mammals to Homo sapiens, was published in 2025.

Transcript:

In our new study of over 15,000 autistic children, we discovered that syntactic language learning rate drops much earlier in autism. This finding could have important implications for when and how we design early interventions.We analyzed years of parent-reported developmental data, focusing on Prefrontal Synthesis—a cognitive function that allows children to mentally combine images and understand complex language, such as syntactic sentences, spatial instructions, and narratives. For example, Prefrontal Synthesis lets a child picture “a cat under the sofa” and understand the difference between sentences “the dog chased the boy” and “the boy chased the dog.” Many autistic children struggle with these skills, and our study helps explain why.Using data from children aged 2 to 22, we found that autistic and neurotypical children showed similar Prefrontal Synthesis learning rates at age 2. However, autistic children’s progress began to decline sharply by around 2.3 years, while neurotypical children continued to learn robustly until about age 7, when the test reached its ceiling. Children with more severe autism showed this decline even earlier, suggesting that the critical period for acquiring PFS is significantly shortened in autism.Our findings are consistent with evidence of accelerated early prefrontal cortex development in autism, which may prematurely close the brain’s window for mastering syntactic language. These results underscore the importance of beginning interventions before age 3—well before the typical start of therapy around age 4, which is often delayed by diagnostic and waitlist barriers.

Read More:

[Springer Nature] - Age-Dependent Process Governs Executive Function Disability in Autistic Children

[Amazon] - The Evolution of Language: How the Brain Evolved Syntactic Language from Early Mammals to Homo sapiens

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Procrastination is everywhere, even in government.

Brian Alexander, associate professor of politics at Washington and Lee University, explains a mistake that was corrected hundreds of years later.

Brian Alexander, Ph.D., is associate professor of Politics at Washington and Lee University and director of the W&L Washington Term, an experiential learning program for undergraduates in Washington, DC. He is author of “Jefferson’s Manual of Parliamentary Practice,” (Arcadia Books 2025), “A Social Theory of Congress” (Rowman & Littlefield 2021), and “The Folkways of Congress” (Brookings Institution Press, 2026). He served as American Political Science Association Congressional Fellow and a research fellow at Monticello’s International Center for Jefferson Studies.

Like all academics, I am uniquely skilled at the art of procrastination. For me, a visit to my university’s library, when I should have been grading papers, led to a discovery about Thomas Jefferson and new ideas about his efforts to shape the rules – and the power – of the U.S. Congress.As vice president of the United States, Thomas Jefferson presided over the Senate. To improve its procedures, he wrote the book, A Manual of Parliamentary Practice, first published in 1801, and the basis for the rules of Congress ever since. Little known to history, Jefferson made handwritten notes in personal copies of the 1801 Manual, as in the rare example I found at my library.In 1812, based on those handwritten notes, Jefferson published a second edition of the Manual, marking his final word on the book. But Congress continued to use the 1801 edition -- effectively the wrong version. Now, in 2025, based on discoveries that started in a university library, the House of Representatives updated its “House Rules and Manual” to account for this centuries-old oversight.Will Jefferson’s additions fix what ails the modern Congress? Alas, probably not. But by adhering to Jefferson’s final word, we pay tribute to the importance he placed on rules for orderly debate. We also recognize Jefferson’s lifelong belief in the value of a strong legislature in representative democracy -- a concern that drives our politics to this day.

Read More:

[Arcadia Publishing] - Jefferson’s Manual of Parliamentary Practice

[The Hill] - Thomas Jefferson would expect much more of Congress today

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How should we regulate AI companions?

Clare Huntington, Barbara Aronstein Black Professor of Law at Columbia Law School, has a template.

Faculty Bio:

Clare Huntington ’96 is a nationally recognized expert in family law and poverty law. Her wide-ranging scholarship explores the institutions and empirical foundations of the legal system’s approach to relationships. Her research focuses on early childhood development, aging, the impact of AI on our affective lives, and the challenges facing nonmarital families because of the law’s myopic focus on marriage. Huntington has received five teaching awards, including, in 2025, the Willis L.M. Reese Prize for Excellence in Teaching.Huntington’s research has appeared in the Columbia Law Review, Harvard Law Review, Michigan Law Review, New York University Law Review, Stanford Law Review, and Yale Law Journal, among other academic journals. She is the author of Failure to Flourish: How Law Undermines Family Relationships and a co-editor of Social Parenthood in Comparative Perspective. She served as associate reporter for the American Law Institute’s Restatement of the Law, Children and the Law. Before entering academia, Huntington was an attorney adviser in the U.S. Justice Department’s Office of Legal Counsel and clerked for Justices Harry A. Blackmun and Stephen G. Breyer of the U.S. Supreme Court, Judge Merrick B. Garland of the U.S. Court of Appeals for the District of Columbia Circuit, and Judge Denise L. Cote of the U.S. District Court for the Southern District of New York.Huntington is a co-founder and co-chair of the University Seminar on Families and Inequality and an affiliated faculty member with the Center on Poverty and Social Policy at Columbia University and the Columbia Population Research Center.Huntington joined Columbia Law School as a professor of law on July 1, 2023. She was previously a visiting scholar in 2008 and Nathaniel Fensterstock Visiting Professor of Law in 2022. Prior to her appointment at Columbia Law, she was the Joseph M. McLaughlin Professor of Law at Fordham Law School. During her tenure there, she was associate dean for strategic initiatives and associate dean for research and was named Teacher of the Year in 2021. She was previously associate professor at the University of Colorado Law School.

Transcript:

Stories about AI companions are everywhere. Sometimes the stories are heart-breaking. Sometimes the stories are encouraging. And often we don’t know what to think of this new phenomenon. What we do know is that millions of people of all ages regularly use AI companions for friendship, sexual intimacy, mental health support, and much more.Just like a relationship with a human, a relationship with an AI companion brings both benefits and risks. Children are especially vulnerable to the risks, including addiction, abuse, and invasion of privacy. But unlike human relationships, there is very little regulation of AI companionship.I study family law, and my research shows that this area of the law offers lessons for sensible regulation.First, family law shows why the legal system should regulate AI companionship. Close relationships help children and adults flourish, but these relationships also bring vulnerability. Our legal system recognizes this, with a particular emphasis on protecting children.Second, family law shows how to regulate AI companionship. To give one example, family law steps in when a power imbalance in a relationship leads to abuse. This lesson should be applied to the power imbalance between technology companies and users of AI companions. To give another example: family law requires mental health experts to be trained and licensed. AI companions marketed for therapeutic purposes should face the same gatekeeping.Finally, family law offers a track record of overcoming political polarization. Family law can bring together lawmakers of all political stripes, especially if the shared goal is protecting children.

Read More:

[Minnesota Law Review] - AI Companions and the Lessons of Family Law

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How do we turn AI from an educational shortcut to a scaffold that helps students learn?

Rosie Dutt, Teaching Assistant Professor & Director of the Undergraduate Neuroscience Career Development at the University of North Carolina, explores this.

Dr. Dutt teaches interdisciplinary computational neuroscience courses, integrating engineering and data science concepts. Her background in communications, consulting, and entrepreneurship helps foster student success and alumni engagement through career development initiatives, connecting students with professional opportunities and strengthening alumni networks.

In higher education, AI is often framed as a shortcut or even a threat to learning. Yet, it can be more productively understood not as an authority replacing student thinking, but as a metacognitive scaffold—a designed tool that supports students in reflecting on their own reasoning. This approach asks students to actively articulate, justify, and evaluate how they use AI’s contributions, shifting AI’s role from doing the thinking for them to helping them think more deeply. The AI tool provides computational support while preserving student judgment, reducing technical friction and prompting reflection.I implemented this approach in an undergraduate computational neuroscience course with mixed majors, many of whom were new to coding. Students were explicitly asked to document their AI use and respond to structured reflection prompts. This transparency repositioned AI from a prohibited shortcut to a cognitive partner that strengthens learning.The data showed that 100% of students reported growth in computational skills, though only 30% used generative AI, mostly for debugging. More importantly, students gained insight into when AI was helpful and when it wasn’t, developing judgment and epistemic responsibility rather than just technical proficiency.This shift toward transparency (where students have permission but must document and reflect on AI use) creates ethical accountability and makes learning outcomes measurable, moving beyond the default impulse to ban AI outright.The key takeaway is that transparency and structured design around AI use beats prohibition. AI doesn’t replace thinking, it shows students what they are actually doing, helping them articulate and strengthen their reasoning. Ultimately, this framework offers a transferable way to integrate AI in education responsibly, supporting students as active thinkers rather than passive users.

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What’s the best way to support the mental health of college students?

Alexis Redding, faculty member at the Graduate School of Education at Harvard University, says the reality is complicated.

Alexis Redding is a developmental psychologist with more than twenty-five years of experience supporting young adults in college and the transition to the workforce. She is a faculty member at the Harvard Graduate School of Education where she co-leads the higher education program and directs a professional program on college student mental health. She is editor of a newly-released book from Harvard Education Press, Mental Health in College: What Research Tells Us About Supporting Students.

For decades, we have talked about the college mental health crisis. Each year, new data alert us to troubling rates of student distress and result in renewed calls for more resources. That framing has helped focus attention and investment in student support, but it has also had an unintended consequence: it has created a context in which we assume every student struggle is a crisis.The reality is more complicated. Most students experience stress, loneliness, academic anxiety, and imposter syndrome at some point during college. These are typical developmental challenges that I have documented in my archival research dating back to the 1940s. These are real struggles that need real support, but they are not unexpected—and they are not a crisis.The difficulty lies in distinguishing between these expected struggles from moments that do require clinical intervention. If every time a student says things are having a hard time we direct them to the counseling center, we risk pathologizing normal experiences and creating barriers for those who need that clinical care. Finding the right balance matters. While we do not want to overreact to a student who is struggling, we also do not want to underreact – the stakes are too high.My research points to a better approach. When typical struggles are normalized, students are more likely to seek support early and persist through challenges. So, how do we start? By making discussions about the expected challenges part of our dialogue about college. And sharing our own struggles too, so that students know that what they are going through is not unique and that they are not doing anything wrong. By normalizing what it typical, we can also better spot when a student is in crisis and ensure they do get the timely care they need.That is the work of creating a truly caring campus.

Read More:

[Harvard Education Press] - Mental Health in College

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LinkedIn

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Tornadoes do not only occur on Earth; they also happen in space. How do we predict them?

Chip Manchester, C. Robert Clauer Collegiate Research professor of Climate and Space Sciences and Engineering at the University of Michigan, looks into this.

Chip Manchester is a research professor of climate and space sciences and engineering at the University of Michigan. His research focuses on the movement of solar plasma and magnetic fields through the solar system.

On Earth, a combination of weather stations and computer simulations help scientists predict how dangerous storms form and where they will move. With the forecasts, local communities can take safety precautions to prepare for dangerous storms.Scientists do the same for space weather, which originates at the Sun first as the solar wind, a soup of charged particles and magnetic fields that flows from the Sun and fills the solar system. On top of this relatively calm breeze, there is extreme space weather, driven by solar eruptions called coronal mass ejections. CMEs, which leave the Sun at high speed and expand to enormous size comparable to the Sun-Earth distance. These ejections can travel from the Sun to Earth in less than two days, and if they possess southward-pointing magnetic fields, they can trigger geomagnetic storms. Such storms create beautiful aurorae but can also damage electric grids and disrupt GPS-navigation systems, such as the Google Maps app on your smart phone.Predicting when coronal mass ejections might hit Earth, as well as their shape, size, density and magnetic field orientation, can help people prepare for severe space weather. But mMy colleague collaborators noticed that some geomagnetic storms occur without predicted Earth-bound eruptions. To better understand the discrepancy, our modeling team joined the effort to created a computer simulation of a coronal mass ejection moving through the solar system. The simulation had a spatial resolution 30 times higher than standard models along the eruption’s path, which allowed us to see patterns in the solar wind too small for previous simulations, while simultaneously viewing the larger eruption.We found that several intense, tornado-like spirals in the magnetic field called flux ropes, separated from the larger eruption when it plowed through a slow stream in the solar wind. Some of these tornadoes had southward-pointing magnetic fields that could trigger geomagnetic storms, even though the magnetic fields in the nearby eruption were oppositely oriented. Our results demonstrate the need to watch how solar eruptions move through space and monitor for small, but concerning, events.But to directly see and make reliable forecasts of these flux ropes, we need to monitor the solar wind from several vantage points, and we currently rely on probes at a single location between the Earth and Sun called L1. To address this problem, the mission team, led by Mojtaba Akhavan-Tafti, is developing a constellation of four satellites, one of which will be propelled beyond L1 by a solar sail. This will help us look out for smaller storm systems that we might otherwise miss.

Read More:

[Michigan Engineering] - We need a solar sail probe to detect space tornadoes

[The Astrophysical Journal] - High-resolution Simulation of Coronal Mass Ejection–Corotating Interaction Region Interactions: Mesoscale Solar Wind Structure Formation Observable by the SWIFT Constellation

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Our understanding of alcohol addiction may need a re-write.

Andrea King, professor of psychiatry and behavioral neuroscience at the University of Chicago, tells us why.

Andrea King is a clinical and research psychologist with expertise in addictive disorders, including alcohol use disorder.

There is a long-held belief that many people drink large amounts of alcohol to self-medicate and reduce negative feelings. In other words, they seek alcohol and consume large quantities to take away the bad feelings and forget their troubles.

But new research conducted by my team challenges that notion and some leading theories on the development of addiction.

We followed a group of 232 people across the U.S. between the ages of 21 and 35. Half of the group met the criteria for alcohol use disorder, or alcoholism. Half of the group had also experienced depression in the past year.

These participants reported on their mood states on our smartphone app during a typical alcohol drinking episode. It turns out that people with alcohol use disorder and depression had the same high sensitivity to alcohol’s positive and rewarding effects as those without depression. And these pleasurable alcohol effects were much more pronounced than in lighter drinkers.

This calls into question the supposed “dark side of addiction,” as proposed in the predominant theory in our field – that people shift from drinking for pleasure to drinking to avoid withdrawal and negative mood. In this study, and in our longitudinal work, we see that drinking alcohol to intoxication is related more to heightened positive effects rather than a dampening of negative states.

Our findings suggest that we may be focusing on the wrong target when we treat people with both alcohol use disorder and depression. We often focus on resolving stress and symptoms of depression, but that is only one side of the coin if we don’t also address the heightened rewarding effects that they experience from alcohol. No matter what your emotional state, we see that alcohol still exerts a powerful force on the pleasure centers of the brain.

Read More:

* Press release: https://biologicalsciences.uchicago.edu/news/alcohol-depression-study

* New Study: https://psychiatryonline.org/doi/10.1176/appi.ajp.20240069

* Related research: https://www.uchicagomedicine.org/forefront/research-and-discoveries-articles/people-with-alcohol-use-disorder-impaired-after-heavy-drinking-despite-claims-of-higher-tolerance

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