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   https://doi.org/10.1109/RAPID60772.2024.10647010  

   Willis, Andrew; Zhang, Jincheng; Louisos, Dustin; Hofmann, Tino; Touma, Jimmy E (August 2024, IEEE)
2. Revisiting flat band superconductivity: Dependence on minimal quantum metric and band touchings

   https://doi.org/10.1103/PhysRevB.106.014518  

   Huhtinen, Kukka-Emilia; Herzog-Arbeitman, Jonah; Chew, Aaron; Bernevig, Bogdan A.; Törmä, Päivi (July 2022, Physical Review B)
3. The ABoVE L-band and P-band airborne synthetic aperture radar surveys

   https://doi.org/10.5194/essd-16-2605-2024  

   Miller, Charles E; Griffith, Peter C; Hoy, Elizabeth; Pinto, Naiara S; Lou, Yunling; Hensley, Scott; Chapman, Bruce D; Baltzer, Jennifer; Bakian-Dogaheh, Kazem; Bolton, W Robert; et al (January 2024, Earth System Science Data)

   Abstract. Permafrost-affected ecosystems of the Arctic–boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P-band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the ∼80 SAR flight lines and how they fit into the ABoVE experimental design (Miller et al., 2023; https://doi.org/10.3334/ORNLDAAC/2150). The Supplement provides hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including boreal forest canopy structure from TomoSAR data over Delta Junction, AK, and the Boreal Ecosystem Research and Monitoring Sites (BERMS) area in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band airborne SAR data (https://uavsar.jpl.nasa.gov/cgi-bin/data.pl). 

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4. Experimental band flip and band closure in guided-mode resonant optical lattices

   https://doi.org/10.1364/OL.463350  

   Razmjooei, Nasrin; Magnusson, Robert (June 2022, Optics Letters)

   We demonstrate band flip in one-dimensional dielectric photonic lattices presenting numerical and experimental results. In periodic optical lattices supporting leaky Bloch modes, there exists a second stop band where one band edge experiences radiation loss resulting in guided-mode resonance (GMR), while the other band edge becomes a nonleaky bound state in the continuum (BIC). To illustrate the band flip, band structures for two different lattices are provided by calculating zero-order reflectance with respect to wavelength and incident angle. We then provide three photonic lattices, each with a different fill factor, consisting of photoresist gratings on Si₃N₄sublayers with glass substrates. The designs are fabricated using laser interferometric lithography. The lattice parameters are characterized and verified with an atomic force microscope. The band transition under fill-factor variation is accomplished experimentally. The measured data are compared to simulation results and show good agreement. 

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5. Cross-Layer Band Selection and Routing Design for Diverse Band-Aware DSA Networks

   https://doi.org/10.1109/GLOBECOM42002.2020.9322500  

   Upadhyaya, Pratheek S.; Shah, Vijay K.; Reed, Jeffrey H. (December 2020, GLOBECOM 2020 - 2020 IEEE Global Communications Conference, 2020)

   As several new spectrum bands are opening up for shared use, a new paradigm of Diverse Band-aware Dynamic Spectrum Access (d-DSA) has emerged. d-DSA equips a secondary device with software defined radios (SDRs) and utilize whitespaces (or idle channels) in multiple bands, including but not limited to TV, LTE, Citizen Broadband Radio Service (CBRS), unlicensed ISM. In this paper, we propose a decentralized, online multi-agent reinforcement learning based cross-layer BAnd selection and Routing Design (BARD) for such d-DSA networks. BARD not only harnesses whitespaces in multiple spectrum bands, but also accounts for unique electro-magnetic characteristics of those bands to maximize the desired quality of service (QoS) requirements of heterogeneous message packets; while also ensuring no harmful interference to the primary users in the utilized band. Our extensive experiments demonstrate that BARD outperforms the baseline dDSAaR algorithm in terms of message delivery ratio, however, at a relatively higher network latency, for varying number of primary and secondary users. Furthermore, BARD greatly outperforms its single-band DSA variants in terms of both the metrics in all considered scenarios. 

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