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1. Poleward Disturbances in Thermospheric Winds During the 3–4 November 2021 Geomagnetic Storm

   https://doi.org/10.1029/2025JA034544  

   Wehmeyer, Jonna; Tomikawa, Yoshihiro; Nishiyama, Takanori; Ogawa, Yasunobu; Franco‐Diaz, Eframir (February 2026, Journal of Geophysical Research: Space Physics)

   Abstract This study focuses on ionosphere‐thermosphere coupling over North America during the 3–4 November 2021 strong geomagnetic storm (Kp 8−). We comprehensively analyze storm‐time ionospheric and thermospheric disturbances using data from ground‐based instruments at Poker Flat, Millstone Hill, and Urbana, as well as satellite observations and model data. Significant features of ionosphere‐thermosphere dynamics during the storm include (a) equatorward (−300 m/s) and poleward (50 m/s) surges at Millstone Hill (42.37 glat) and a poleward surge (75 m/s) at Urbana (40.13 glat) in the magnetic local time (MLT) post‐midnight sector, (b) ion velocities greater than −1,500 m/s at Poker Flat accompanied by a deep ionospheric trough moving to latitudes as low as 40 glat suggesting SAPS activity, (c) a widespread electron density depression in the morning hours due to an extended composition disturbance zone and (d) Large‐Scale Traveling Ionospheric Disturbances (LSTIDs) related to disturbances in equatorward winds in the post‐poleward wind interval. Results show that the equatorward and poleward surges were not accompanied by LSTIDs, which suggests that the extreme disturbances in meridional winds could have mainly been caused by SAPS forcing, due to ion drag and pressure gradients, rather than equatorward propagating Traveling Atmospheric Disturbances (TADs). Furthermore, the MLT location of Millstone Hill and Urbana indicates that during the disturbances both stations would have been located within the eastward backflow sector of the SAPS, which likely contributed to the complicated ion‐neutral dynamics. 

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2. Complex Connections: How Information Flow Networks Can Quantify Ecohydrological Interactions

   https://doi.org/10.33548/SCIENTIA1137  

   Goodwell, Allison; Kumar, Praveen (January 2024, Scientia)

   NA (Ed.)

   Ecohydrological systems comprised of soil, water and vegetation are intricately connected, and changes in one component can trigger feedback mechanisms throughout the network. Understanding how these complex interactions occur and propagate is challenging. To address this, Dr Allison Goodwell and Professor Praveen Kumar from the University of Illinois Urbana-Champaign have characterised information flow — a mathematical concept initially developed for communication systems — to better quantify and understand these interactions. Their research offers new insights into ecosystem responses, evolving precipitation patterns, and ecohydrological models, advancing our understanding of environmental dynamics. 

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3. Quantum Key Distribution for Critical Infrastructures: Towards Cyber-Physical Security for Hydropower and Dams

   https://doi.org/10.3390/s23249818  

   Green, Adrien; Lawrence, Jeremy; Siopsis, George; Peters, Nicholas A; Passian, Ali (December 2023, Sensors)

   Hydropower facilities are often remotely monitored or controlled from a centralized remote control room. Additionally, major component manufacturers monitor the performance of installed components, increasingly via public communication infrastructures. While these communications enable efficiencies and increased reliability, they also expand the cyber-attack surface. Communications may use the internet to remote control a facility’s control systems, or it may involve sending control commands over a network from a control room to a machine. The content could be encrypted and decrypted using a public key to protect the communicated information. These cryptographic encoding and decoding schemes become vulnerable as more advances are made in computer technologies, such as quantum computing. In contrast, quantum key distribution (QKD) and other quantum cryptographic protocols are not based upon a computational problem, and offer an alternative to symmetric cryptography in some scenarios. Although the underlying mechanism of quantum cryptogrpahic protocols such as QKD ensure that any attempt by an adversary to observe the quantum part of the protocol will result in a detectable signature as an increased error rate, potentially even preventing key generation, it serves as a warning for further investigation. In QKD, when the error rate is low enough and enough photons have been detected, a shared private key can be generated known only to the sender and receiver. We describe how this novel technology and its several modalities could benefit the critical infrastructures of dams or hydropower facilities. The presented discussions may be viewed as a precursor to a quantum cybersecurity roadmap for the identification of relevant threats and mitigation. 

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4. Spatially varying nanophotonic neural networks

   https://doi.org/10.1126/sciadv.adp0391  

   Wei, Kaixuan; Li, Xiao; Froech, Johannes; Chakravarthula, Praneeth; Whitehead, James; Tseng, Ethan; Majumdar, Arka; Heide, Felix (November 2024, Science Advances)

   The explosive growth in computation and energy cost of artificial intelligence has spurred interest in alternative computing modalities to conventional electronic processors. Photonic processors, which use photons instead of electrons, promise optical neural networks with ultralow latency and power consumption. However, existing optical neural networks, limited by their designs, have not achieved the recognition accuracy of modern electronic neural networks. In this work, we bridge this gap by embedding parallelized optical computation into flat camera optics that perform neural network computations during capture, before recording on the sensor. We leverage large kernels and propose a spatially varying convolutional network learned through a low-dimensional reparameterization. We instantiate this network inside the camera lens with a nanophotonic array with angle-dependent responses. Combined with a lightweight electronic back-end of about 2K parameters, our reconfigurable nanophotonic neural network achieves 72.76% accuracy on CIFAR-10, surpassing AlexNet (72.64%), and advancing optical neural networks into the deep learning era. 

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5. Mitigation of SARS-CoV-2 transmission at a large public university

   https://doi.org/10.1038/s41467-022-30833-3  

   Ranoa, Diana Rose; Holland, Robin L.; Alnaji, Fadi G.; Green, Kelsie J.; Wang, Leyi; Fredrickson, Richard L.; Wang, Tong; Wong, George N.; Uelmen, Johnny; Maslov, Sergei; et al (December 2022, Nature Communications)

   Abstract In Fall 2020, universities saw extensive transmission of SARS-CoV-2 among their populations, threatening health of the university and surrounding communities, and viability of in-person instruction. Here we report a case study at the University of Illinois at Urbana-Champaign, where a multimodal “SHIELD: Target, Test, and Tell” program, with other non-pharmaceutical interventions, was employed to keep classrooms and laboratories open. The program included epidemiological modeling and surveillance, fast/frequent testing using a novel low-cost and scalable saliva-based RT-qPCR assay for SARS-CoV-2 that bypasses RNA extraction, called covidSHIELD, and digital tools for communication and compliance. In Fall 2020, we performed >1,000,000 covidSHIELD tests, positivity rates remained low, we had zero COVID-19-related hospitalizations or deaths amongst our university community, and mortality in the surrounding Champaign County was reduced more than 4-fold relative to expected. This case study shows that fast/frequent testing and other interventions mitigated transmission of SARS-CoV-2 at a large public university. 

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