Led by Ph.D. student Robert J. Madden at Colorado State University, this extensive research sheds light on the enduring presence of dice and gambling within Native American cultures from the Late Pleistocene epoch, during the end of the last Ice Age. Madden’s team meticulously studied archaeological sites spanning Wyoming, Colorado, and New Mexico, where these artifacts unequivocally indicate the ancient manufacture and use of gaming implements long before similar devices appeared in the Old World.

The study’s central finding highlights that these earliest dice were not the familiar six-sided cubes but a more primitive form known as “binary lots.” These small bone pieces, ingeniously shaped as flat or slightly rounded ovals or rectangles, were crafted for tactile ease and designed to produce binary outcomes—much like a modern coin toss. Distinct markings and surface modifications on each side of these dice distinguished the “counting” face, ensuring reliable differentiation when tossed in groups to generate game scores.

Through this binary outcome mechanism, ancient Native Americans ingeniously employed randomization principles that hint at nascent forms of probabilistic thought. Madden explains that these artifacts were “simple, elegant tools” intentionally created for generating random results, demonstrating purposeful design rather than incidental byproducts of material craftsmanship.

To objectively identify dice within the vast archaeological record, Madden devised a novel attribute-based morphological test derived from an exhaustive comparative analysis of 293 sets of historic Native American dice documented in ethnographer Stewart Culin’s early 20th-century monograph Games of the North American Indians. This systematic approach involved a checklist of quantifiable physical features, setting a rigorous standard for dice identification independent of subjective interpretation.

Applying this framework to existing archaeological collections led to the identification of over 600 diagnostic and probable dice specimens spanning a temporal range from the Late Pleistocene through the post-European contact period. Many of these artifacts had been excavated and accessioned into museum repositories for decades but lacked definitive classification due to the absence of a formalized identification standard.

The research team conducted direct examinations of seminal dice artifacts housed in three key institutions—the Smithsonian Institution’s Division of Anthropology, the University of Wyoming Archaeological Repository, and the Denver Museum of Nature and Science—culminating in a comprehensive reevaluation of these critical cultural objects and their significance.

From a broader historical and intellectual standpoint, this discovery fundamentally challenges the prevailing academic consensus which held that dice games—reflecting humanity’s earliest interaction with randomness and precursor intellectual engagement with probability theory—originated exclusively in complex Old World societies roughly 5,500 years ago. Madden’s findings delineate a far older, geographically distinct lineage of probabilistic gaming.

Although not suggesting that Ice Age hunter-gatherers conceptualized formal probability theory, the research posits that these ancient groups engaged intuitively with random processes, employing repeatable, rule-governed games that leveraged consistent probabilistic patterns such as the law of large numbers. This sheds new light on the global evolution of probability and mathematical thinking, emphasizing indigenous contributions.

Furthermore, the archaeological record reveals the remarkable spatial and temporal persistence of dice use across at least 57 sites within a dozen states, encompassing diverse socio-cultural milieus and subsistence strategies. This continuity attests to the significant social and cultural functions of chance-based games among Native American populations over thousands of years.

Madden elucidates that such games provided structured, neutral arenas that facilitated intergroup interaction, the exchange of goods and knowledge, alliance formation, and strategies for managing uncertainty in complex social landscapes. In this sense, dice and gambling acted as sophisticated social technologies enabling cohesion and negotiation within and between indigenous communities.

The cultural importance and resilience of this gaming heritage persist into living Native American traditions today, underscoring an unbroken continuum of engagement with chance, competition, and communal connection spanning millennia. This enduring legacy situates Native American contributions as foundational to the human story of gaming and stochastic reasoning.

The study, titled “Probability in the Pleistocene: Origins and Antiquity of Native American Dice, Games of Chance, and Gambling,” promises to enrich anthropological, archaeological, and mathematical discourses alike, inviting a reevaluation of indigenous intellectual histories through a rigorous, evidentiary lens grounded in both material culture and probabilistic analysis.

As the research appears in the April 2, 2026 issue of American Antiquity, it heralds a significant advance in understanding how early humans across continents grappled with randomness, gaming, and structured social interaction—opening new avenues for interdisciplinary inquiry and expanding the scope of archaeological science.

Subject of Research: Origins and antiquity of Native American dice, games of chance, and gambling during the Late Pleistocene and Holocene periods.

Article Title: Probability in the Pleistocene: Origins and Antiquity of Native American Dice, Games of Chance, and Gambling

News Publication Date: March 23, 2026

Web References:
DOI: 10.1017/aaq.2025.10158

Image Credits: Photo courtesy of Robert Madden, featuring Late Pleistocene to Late Holocene prehistoric Native American dice from sites in Nebraska, Wyoming, Colorado, and New Mexico, courtesy of Smithsonian Institution and University of Wyoming collections.

Keywords: Native American archaeology, dice, games of chance, gambling, Late Pleistocene, probability theory, random processes, cultural anthropology, material culture, prehistoric gaming, social anthropology, mathematical history

Led by Ph.D. candidate Alexa Jayne, this pioneering study probes the nuanced dynamics between faculty self-disclosure of impostor feelings and student evaluations of teaching efficacy. The investigation reveals a complex interplay whereby students who are made aware of a professor’s professed impostor syndrome tend to marginally downgrade their assessment of that professor’s competence and employability, even when objective indicators of success are held constant. These findings provide critical insights for academic leaders and pedagogical strategists seeking to optimize faculty development and mentorship protocols.

Impostor syndrome is characterized by an enduring fear of being unmasked as a fraud, despite evidence of success and external validation. This psychological pattern is rampant in the high-stakes, feedback-rich environments of higher education, where faculty regularly face rigorous peer reviews, publication scrutiny, and tenure evaluations. Jayne’s research uniquely evaluates not only the internal experience of impostorism but also its external ramifications on how students, a vital stakeholder group, perceive and engage with faculty members.

In the experimental design, participants, who were university students, were exposed to two nearly identical vignettes describing a hypothetical tenured professor. In one scenario, the professor openly acknowledged experiencing impostor feelings—attributing personal success to external variables and fearing exposure as a fraud. In the control scenario, the same professor’s profile was presented without any reference to self-doubt. Subsequently, students rated the professor across dimensions including likeability, anticipated average class grades, salary estimations, and willingness to enroll in the course.

Strikingly, students who read the vignette featuring a professor’s disclosure of impostor syndrome perceived that professor as having less experience and earning a salary approximately $10,000 lower than their non-disclosing counterpart. This differentiation points to a tangible effect of such transparency on perceived professional stature. Nonetheless, the likeability scores remained consistently high across both conditions, indicating that vulnerability might enhance personal connection without necessarily translating into diminished interpersonal warmth.

These outcomes suggest a delicate balancing act for faculty members navigating the classroom environment. While authentic self-expression and approachability can foster trust and student engagement, overt expressions of insecurity must be carefully calibrated to avoid undermining perceived authority and expertise. Jayne underscores that confidence often remains conflated with competence in students’ minds, an association that educators must strategically address.

Further, the research hints at broader implications for diversity and inclusion within academia. Populations disproportionately affected by impostor syndrome—such as women and minorities in STEM fields—may face compounded challenges in faculty retention and advancement due to the societal conflation of confidence with professional aptitude. Thoughtfully structured interventions and mentorship frameworks are thus imperative for supporting these groups and normalizing discussions around impostor feelings without penalization.

Jayne’s work extends beyond the classroom to leadership paradigms across sectors, where deliberate vulnerability is increasingly championed as a trust-building mechanism. The study cautions that while openness can humanize leaders and foster team cohesion, it may inadvertently erode perceptions of competence if not communicated with contextual awareness.

This inquiry complements broader research initiatives led by Professor Bryan Dik at Colorado State University, whose scholarly focus centers on the intersection of meaningful work and its psychological tolls. Dik contextualizes these findings within what his team terms the ‘dark side’ of calling—the paradox wherein fulfilling work pursuits can engender adverse mental health outcomes and professional strain.

Looking forward, Jayne and Dik anticipate further exploration into how demographic variables modulate these dynamics and impact critical career milestones such as hiring and promotion, particularly for early-career faculty navigating already biased institutional landscapes. Their ongoing research aims to foster systemic support mechanisms that mitigate the negative repercussions of impostor syndrome and promote equitable academic environments.

Ultimately, this study offers a nuanced perspective on the psychological and perceptual undercurrents shaping faculty-student interactions. It challenges entrenched assumptions about the indispensability of unshakeable confidence in academia and advocates for a more empathetic and evidence-informed approach to faculty vulnerability. As universities grapple with retention and mentorship challenges, embracing this complexity may hold the key to nurturing resilient, authentic educators who thrive amid the rigorous demands of scholarly life.

Subject of Research: Faculty impostor syndrome and its impact on student perceptions of professor competence and teaching effectiveness.

Article Title: Conflating competence with confidence: Student perceptions of a professor with imposter phenomenon.

News Publication Date: 12-Nov-2025

Web References:
Scholarship of Teaching and Learning in Psychology – DOI: 10.1037/stl0000461

Keywords: Psychological science, Psychological theory, Behavioral psychology, Clinical psychology, Psychiatry, Social interaction, Human social behavior, Social psychology, Education research, Cognitive psychology

Air quality in America’s largest cities has steadily improved thanks to tighter regulations on key sources of particulate pollution. However, increased heat, wildfire smoke and other emerging global drivers of urban aerosol pollution are now combining to create a new set of challenges for public health officials tasked with protecting millions of people on the East Coast.

Research from Colorado State University published in npj Climate and Atmospheric Science begins to unpack and characterize these developing relationships against the backdrop of New York City. The research quantifies how existing particulate pollution from sources such as vehicle exhaust or consumer products are now combining with wildfire smoke –– transported from thousands of miles away –– to create secondary, often more toxic, pollution or contribute to the formation of ozone in hot weather.

Professor Delphine Farmer in the Department of Chemistry led the research with data collected from continuous on-the-ground readings at a site on Long Island during the summer of 2023.

“We did not set out to study air quality, wildfire and heat in that way, but smoke from fires in Canada arrived and, unfortunately, that is likely to be more and more common in the future,” Farmer said. “Cities on the West Coast have been dealing with these combined issues for a while, but the developing situation in New York is a good test case to understand how variables like the nearby natural forests and denser populations on the East Coast may contribute to these emerging drivers of air pollution in mega cities.”

Aerosol pollution consists of tiny particles of smoke or other compounds from many common sources such as cleaning solutions or cooking in restaurants. It can also occur naturally from the gases plants release every day. Hotter temperatures can cause plants to release more of those gases and speed the evaporation of some of those consumer products into particulate air pollution. Meanwhile, wildfire smoke particles absorb and react to those same gasses –– further amplifying both natural and man-made sources of pollution. Because these particles can enter the lungs, they may lead to heart disease, cancer and even dementia, making them a key focus area for health regulation.

Farmer said the situation in New York presented an opportunity to start to untangle the relationships between sources and their impacts overall. Her team found evidence that 90 percent of the aerosol pollution found over the city was indeed sensitive to at least one aspect of these global changes, such as high temperatures –– meaning effects from the pollutants were made worse during a heat wave, for example.

Some volatile chemical products such as paints and solvents are sensitive to these changes, and the team’s work shows that those sources are responsible for more than double the estimated contribution from cars to the city’s air pollution total in this category.

New York also has plenty of restaurants where the daily cooking and cleaning activities can contribute to overall pollution totals as well. However, the team found that while those emissions were also sensitive to the introduction of smoke or higher temperatures the effects were localized.

“We found that restaurants do have a big impact on their own local neighborhoods, but their associated aerosols are only a minor component of the total average load across the region,” Farmer said. “Still, any worsening of those conditions from the arrival of wildfire smoke –– for example –– could lead to environmental health inequality for those areas that health policy makers will need to consider.”

She added that context like that will help policy makers prioritize sources of pollution to target for both their overall contributions to the area’s air quality and their localized impact on public health.

Machine learning techniques aid research into urban air pollution

Emily Franklin led aerosol data collection on the ground and follow-up analysis for the project as a CSU postdoctoral fellow funded by the National Science Foundation. She has since taken a position as a research scientist at CSIRO, Australia’s national science agency.

Franklin said the team pulled measurements from many different instruments on the site and worked closely with fellow researchers from the universities of Minnesota, Columbia, Michigan and the University of California, Berkeley for the project. Together, these instruments generated thousands of individual indicators of aerosol composition, including characterization of hundreds of unique but unidentifiable compounds in the atmosphere. To take advantage of these complex measurements, she leveraged machine learning techniques.

“This was an incredibly rich and complex dataset. In a place like New York, you have compounds coming from trees in city parks, fires in Canada, construction sites miles away, and the barbecue joint up the road,” Franklin said. “Machine learning was a powerful tool allowing us to embrace this complexity and leverage it to better understand how all of these sources interact with the climate to make the air pollution experienced by the community.”

Funding for this project came from the National Oceanic and Atmospheric Administration as part of their AGES+ campaign, which is focused on improving air quality understanding through extensive, coast-to-coast observation using ground sites, research aircraft and satellite data.

The CSU team will now continue to study air quality in the region through the NSF funded GOTHAAM Campaign using a C-130 aircraft as a flying chemistry lab to measure atmospheric composition in real time across New York, New Jersey and Connecticut. That project focuses on volatile organic compounds –– a broad term for gases from car exhaust, industry, vegetation and consumer products that react in the atmosphere to form ground-level ozone, secondary organic aerosols and particulate matter.

Farmer said measurements taken from the plane will give the team a better sense of the chemistry happening in the region as they will be able to get readings over the ocean and at different altitudes. Ideally, they will be able to provide more information to the millions of residents in the broader region about their air quality and potential health risks from it.

“We worry about what we are breathing on the ground but in reality, the chemistry happening above us has a big impact on that. This research project will again help us understand key interactions better and improve our ability to predict potentially hazardous air quality conditions,” she said.

bu içeriği en az 2000 kelime olacak şekilde ve alt başlıklar ve madde içermiyecek şekilde ünlü bir science magazine için İngilizce olarak yeniden yaz. Teknik açıklamalar içersin ve viral olacak şekilde İngilizce yaz. Haber dışında başka bir şey içermesin. Haber içerisinde en az 12 paragraf ve her bir paragrafta da en az 50 kelime olsun. Cevapta sadece haber olsun. Ayrıca haberi yazdıktan sonra içerikten yararlanarak aşağıdaki başlıkların bilgisi var ise haberin altında doldur. Eğer yoksa bilgisi ilgili kısmı yazma.:
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Led by Professors Garret Miyake and Robert Paton, the research centers on a novel photoredox catalytic system that ingeniously mimics natural photosynthesis. Unlike conventional catalytic techniques that typically rely on high heat or harsh reagents, this system utilizes visible light photons to initiate and drive chemical reactions. By absorbing two photons sequentially, the catalyst accumulates sufficient energy to perform super-reducing reactions—processes that require breaking some of the most resilient bonds in organic molecules. This dual-photon mechanism circumvents the inherent energy limitations of single-photon systems, unlocking new reaction pathways previously inaccessible under mild conditions.

One of the most remarkable aspects of this discovery is its ability to effectively reduce aromatic hydrocarbons, or arenes, a notoriously challenging class of chemical compounds due to their stable, resonance-stabilized ring structures. These arenes, such as benzene rings commonly found in fossil fuels, serve as fundamental building blocks for an array of indispensable chemicals including plastics, pharmaceuticals, and agrochemicals. Traditionally, converting arenes into more functionalized compounds demands substantial energy input, often achieved through high-temperature catalysis or the use of aggressive reagents, resulting in considerable environmental burden. The CSU team’s light-based method offers a gentler yet highly efficient alternative with significant implications for both industrial chemistry and sustainability.

At the core of this catalytic process is its strategic use of proton-coupled electron transfer (PCET), a sophisticated mechanism that mitigates the challenge of back electron transfer, which typically quenches efficiency in photoredox catalysis. By coupling electron transfers with proton shifts, the catalyst stabilizes reactive intermediates and extends their lifetimes, facilitating effective bond cleavage and electron addition. This mechanistic innovation allows the catalyst to maintain its super-reducing power throughout the reaction, a critical factor in achieving the high efficiencies reported.

The implications of this technology extend well beyond the laboratory. By enabling efficient transformations at ambient temperatures, this photoredox methodology has the potential to substantially lower energy consumption across various chemical manufacturing sectors. Reduced dependency on high heat and pressure translates directly into lower carbon emissions and diminished production costs. Moreover, the ability to conduct these transformations under mild conditions alleviates the generation of harmful byproducts common in traditional processes, thereby contributing to reduced overall pollution and enhanced environmental compliance.

This research is set against the backdrop of the U.S. National Science Foundation’s Center for Sustainable Photoredox Catalysis (SuPRCat), a multi-institutional initiative directed by Miyake, aimed at revolutionizing chemical synthesis through the integration of synthetic chemistry and computational insights. The center’s concerted efforts focus on developing catalytic systems capable of addressing urgent sustainability challenges, including the efficient synthesis of ammonia fertilizers, remediation of persistent environmental pollutants like PFAS, and innovative pathways for the upcycling of polymers.

Katharine Covert, program director for the NSF Centers for Chemical Innovation, emphasizes the transformative impact of photoredox catalysis on pharmaceutical development and wider chemical industries. Through collaborative efforts within the SuPRCat framework, the deeper understanding of catalyst functionality has enabled the pioneering of less energy-intensive synthetic routes, exemplified by the CSU team’s reported breakthrough. The confluence of synthetic innovation and theoretical modeling underscores a new paradigm in catalysis design, promising continued advancement in green chemistry.

Beyond the technical merits, the researchers highlight an urgent call to action concerning the global chemical industry’s environmental footprint. Miyake underlines the pressing timeline humanity faces in transitioning towards sustainable technologies, asserting that innovative approaches like theirs are indispensable to averting irreversible ecological damage. The team’s collective expertise and interdisciplinary collaboration stand as a testament to the caliber required to meet such formidable challenges, heralding a future where chemical manufacturing harmonizes with environmental stewardship.

This pioneering study also featured contributions from notable researchers including University of Colorado Boulder Professor Niels Damrauer and CSU team members Amreen Bains, Brandon Portela, Alexander Green, Anna Wolff, and Ludovic Patin. Their combined expertise in organic synthesis, computational chemistry, and catalysis underpins the robustness and broad applicability of the developed system.

Looking ahead, the team is actively expanding this photoredox platform to tackle a wider array of chemical transformations crucial for sustainable development. Applications under exploration include the sustainable production of ammonia, a cornerstone fertilizer in global agriculture; strategic degradation of PFAS chemicals, which persist as pervasive environmental contaminants; and advanced chemical recycling methods aimed at mitigating plastic waste through polymer upcycling. These ambitious goals position the research at the interface of chemistry, environmental science, and societal needs, highlighting its broad relevance and transformative potential.

In conclusion, the CSU-led team’s research presents a landmark advancement in organic photoredox catalysis, offering a potent combination of energy efficiency, environmental sustainability, and chemical versatility. By leveraging the synergistic effects of proton-coupled electron transfer and innovative light absorption strategies, this new catalytic system sets a precedent for future developments in sustainable chemical manufacturing, inspiring hope for a more resilient and eco-conscious industrial future.

Subject of Research: Organic photoredox catalysis for sustainable chemical transformations

Article Title: Efficient super-reducing organic photoredox catalysis with proton-coupled electron transfer–mitigated back electron transfer

News Publication Date: 19-Jun-2025

Web References:

• DOI link to article
• CSU Center for Sustainable Photoredox Catalysis
• U.S. National Science Foundation Center for Sustainable Photoredox Catalysis at CSU
• Prof. Robert Paton contact

References:
Paton, R. S., Miyake, G. M., et al. (2025). Efficient super-reducing organic photoredox catalysis with proton-coupled electron transfer–mitigated back electron transfer. Science. DOI: 10.1126/science.adw1648.

Image Credits: Colorado State University College of Natural Sciences

Keywords

Catalysis, Sustainability, Chemistry, Photosynthesis, Chemical compounds, Organic chemistry, Hydrocarbons, Fossil fuels, Fertilizers, Pollution, Redox reactions, Organic reactions

Synthetic biology, a transformative discipline at the intersection of biology, engineering, and computer science, focuses on designing and assembling novel DNA sequences that function as biological circuits. Analogous to electronic switches that toggle power on or off, these genetic circuits allow scientists to control cellular processes with unprecedented accuracy. Until now, complex multicellular organisms like plants posed intricate challenges due to their differentiated tissues and developmental stages. The CSU team, spearheaded by Professors June Medford and Ashok Prasad, has overcome these hurdles, paving the way for functional genetic circuitry in plants.

The toggle switch functions by inserting engineered DNA sequences that respond to external stimuli, enabling researchers to activate or deactivate targeted genes at will. This modulation of gene expression holds tremendous promise for precision agriculture. For instance, regulating the timing of fruit ripening could greatly improve harvest efficiency and reduce waste. The ability to switch traits dynamically also offers solutions to enhance stress tolerance, nutritional content, and developmental processes, adapting crops in real-time to environmental cues.

One of the greatest challenges in implementing such synthetic genetic devices in plants arises from their multicellularity and complexity. Unlike bacteria, plants possess multiple cell types distributed in roots, stems, leaves, flowers, and fruits, each with distinct gene expression profiles and physiological roles. Successfully engineering a toggle that operates coherently throughout these diverse tissues required sophisticated design principles and engineering methodologies. The CSU group addressed this by creating synthetic plant DNA parts and employing advanced mathematical modeling to optimize the toggle circuit components before plant transformation.

By simulating various combinations of genetic elements in silico, the research team identified optimal circuits that maintain bistability — the ability to stably exist in either an ‘on’ or ‘off’ state until externally switched. This bistability is critical for a functional toggle switch, ensuring that the plant reliably retains its gene expression state without continuous stimulus. This predictive modeling shortened development time and increased efficiency, culminating in the transformation of mature plants with the synthetic toggles.

After inserting the engineered DNA into plants, the team carefully monitored gene expression changes over a twelve-day period, successfully demonstrating the switch’s ability to toggle gene activity systemically across different plant organs. This observation signified that the synthetic circuitry could influence complex plant developmental stages and physiological processes in a controlled manner, thus enabling dynamic manipulation of plant traits throughout the life cycle.

Professor June Medford highlights the interdisciplinary nature of this achievement. “Our collaboration combines deep biological knowledge with advanced algorithmic and engineering expertise,” she explained. “Integrating quantitative research and mathematical modeling allows us to decode complex biological signals and design precise genetic circuits. This project epitomizes the power of merging synthetic biology with computational techniques to push the boundaries of plant engineering.”

Such a technology portends vast opportunities for improving crop resilience amidst the escalating challenges posed by climate change. Professor Ashok Prasad emphasizes the real-world impact: “Farmers could soon be able to flip gene switches that enhance drought tolerance during dry spells or modulate growth rates and nutritional quality in crops such as pumpkins or tomatoes. This synthetic genetic toggle offers a new dimension of control that can adapt agriculture dynamically to unpredictable environmental stresses.”

Beyond immediate agricultural applications, this advancement also contributes fundamental knowledge to synthetic biology’s expansion into multicellular organisms. The research showcases that genetic circuits are not confined to microbes but can be effectively scaled and implemented in higher organisms with complex developmental architectures. This milestone serves as a gateway to more sophisticated biological programming, including multi-gene networks and responsive feedback systems within plants.

The implications extend to sustainable agriculture by minimizing reliance on chemical inputs through genetically programmable traits, potentially reducing pesticides and fertilizers. Synthetic toggles could also be harnessed to engineer plants with enhanced capabilities for carbon sequestration or biomass production for renewable materials. The versatility of these switches opens avenues across environmental science, agroecology, and bioenergy sectors.

Looking forward, the team envisions integration with machine learning and automated design frameworks to accelerate development cycles and discover novel genetic circuits with even greater functional complexity. This automation would democratize synthetic biology tools, enabling wider adoption among researchers and agricultural stakeholders. The marriage of quantitative modeling and experimental biology stands to revolutionize how plants are engineered to meet global societal and environmental needs.

In summary, the CSU researchers have demonstrated the first functional genetic toggle switch in full-grown plants, a feat that transcends previous limitations in synthetic biology. This technology lays the foundation for controlled, programmable plant traits that can be switched on demand, holding transformative potential for agriculture, biotechnology, and ecological stewardship in an era of climatic uncertainty.

Subject of Research: Genetic circuitry and synthetic biology implementation in full-grown plants.

Article Title: Genetic Toggle Switch in Plants

News Publication Date: 19-May-2025

Web References:

• https://pubs.acs.org/doi/full/10.1021/acssynbio.4c00777

References:

• ACS Synthetic Biology, DOI: 10.1021/acssynbio.4c00777

Image Credits: Colorado State University Walter Scott, Jr. College of Engineering

Keywords: Synthetic biology, Plant genetics, Genetic material, DNA synthesis, Genetic analysis, DNA structure, Agriculture, Food production, Sustainable agriculture, Mathematics, Modeling, Quantitative modeling, Applied mathematics, Electronic circuits, Plant sciences, Plant signaling, Plants, Protein design, Agricultural biotechnology