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Publications citing W&M HPC resources

2024
  1. Goodman, S., Zhang, S., Malik, A.A. et al. AidData’s Geospatial Global Chinese Development Finance Dataset. Sci Data 11, 529 (2024). https://doi.org/10.1038/s41597-024-03341-w
  2. St-Laurent, P., M.A.M Friedrichs, 2024, On the sensitivity of coastal hypoxia to its external physical forcings, Journal of Advances in Modeling Earth Systems, 16, e2023MS003845, https://doi.org/10.1029/2023MS003845
  3. Abelt C, Sweigart K. Twisted 8-Acyl-1-dialkyl-amino-naphthalenes Emit from a Planar Intramolecular Charge Transfer Excited State. Photochem. 2024; 4(1):1-13. https://doi.org/10.3390/photochem4010001
  4. Rex Kincaid, Cameron Curtis, and Logan Wolf, ``Analysis of Centralized and Distributed Air Traffic Management Systems via Mixed Integer Linear Programs,'' Proceedings of the 2023 MODSIM World Conference, Norfolk, VA, May 22-23, 2023, No. 3018 (9 pages) http://www.modsimworld.org/conference-papers/2023.
  5. T. Whyte, A. Stathopoulos, E. Romero, K. Orginos, "Optimizing Shift Selection in Multilevel Monte Carlo for Disconnected Diagrams in Lattice QCD”, Computer Physics Communications, Vol. 294, 2024, https://doi.org/10.1016/j.cpc.2023.108928.
  6. Ruby W. Neisser, John P. Davis, Megan E. Alfieri, Hayden Harkins, Andrew S. Petit, Daniel P. Tabor, and Nathanael M. Kidwell The Journal of Physical Chemistry A 2023 127 (50), 10540-10554
    DOI: 10.1021/acs.jpca.3c04472 https://doi.org/10.1021/acs.jpca.3c04472
  7. Allaire, C., Ammendola, R., Aschenauer, E.-C., Balandat, M., Battaglieri, M., Bernauer, J., Bondì, M., Branson, N., Britton, T., Butter, A., Chahrour, I., Chatagnon, P., Cisbani, E., Cline, E. W., Dash, S., Dean, C., Deconinck, W., Deshpande, A., Diefenthaler, M., … Zurita, P. (2024). Artificial Intelligence for the Electron Ion Collider (AI4EIC). In Computing and Software for Big Science (Vol. 8, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1007/s41781-024-00113-4
2023
  1. Cai, X., Shen, J., Zhang, Y., Qin, Q., and Linker, L. (2023). Sea-level rise impacts on tidal marshes and estuarine biogeochemical processes. Journal of Geophysical Research: Biogeosciences, 128, e2023JG007450. https://doi.org/10.1029/2023JG007450
  2. Huang, W., Ye, F., Zhang, Y., Du, J., Park, K., Yu, H.C., Wang, Z. (2023) Hydrodynamic responses of estuarine bays along the Texas-Louisiana coast during Hurricane Harvey, Ocean Modelling, 102302, https://doi.org/10.1016/j.ocemod.2023.102302
  3. Boyle, J. H., Strickler, S., Twyford, A. D., Ricono, A., Powell, A., Zhang, J., Xu, H., Smith, R., Dalgleish, H. J., Jander, G., Agrawal, A. A., & Puzey, J. R. (2023). Temporal matches between monarch butterfly and milkweed population changes over the past 25,000 years. In Current Biology (Vol. 33, Issue 17, pp. 3702-3710.e5). Elsevier BV. https://doi.org/10.1016/j.cub.2023.07.057
  4. Chiu C-M, Chuang LZ-H, Chuang W-L, Wu L-C, Huang C-J, Zhang YJ. Utilizing Numerical Models and GIS to Enhance Information Management for Oil Spill Emergency Response and Resource Allocation in the Taiwan Waters. Journal of Marine Science and Engineering. 2023; 11(11):2094. https://doi.org/10.3390/jmse11112094
  5. St-Laurent, P., M.A.M. Friedrichs (2023) Dataset: Numerical experiments on the sensitivity of Chesapeake Bay hypoxia to physical forcings and the associated code and input files, dataset (size 32 gigabytes), William & Mary ScholarWorks, https://doi.org/10.25773/q2kh-rd09
  6. St-Laurent, P. (2023) Dataset: A numerical simulation of the ocean, sea ice and ice shelves in the Amundsen Sea (Antarctica) over the period 2006-2022 and its associated code and input files, dataset (size 2.2 terabytes), William & Mary ScholarWorks, https://doi.org/10.25773/bt54-sj65
  7. "Analysis of Centralized and Distributed Air Traffic Management Systems via Mixed Integer Linear Programs," (with Cameron Curtis and Logan Wolf)
    Proceedings of the 2023 MODSIM World Conference, Norfolk, VA, May 22-23, 2023, No. 3018
    (9 pages) https://www.modsimworld.org/about/publications/2023
  8. Ye, F., Cui, L., Zhang, Y., Wang, Z., Moghimi, S., Myers, E., Seroka, G., Zundel, A., Mani, S., Kelley, J.G.W. (2023) A parallel Python-based tool for meshing watershed rivers at continental scale, Environmental Modelling & Software, 166, 105731. https://doi.org/10.1016/j.envsoft.2023.105731
  9. Zhang, Y. J., Fernandez-Montblanc, T., Pringle, W., Yu, H.-C., Cui, L., and Moghimi, S. (2023) Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0), Geoscientific Model Development, 16, 2565-2581. https://doi.org/10.5194/gmd-16-2565-2023
  10. Huang, W., Zhang, Y.J, Liu, Z., Yu, H.C., Liu, Y., Lamont, S., Zhang, Y., Hirpa, F., Li, T., Baker, B., Zhang, W., Patel, S., and Mori, N. (2023) Simulation of compound flooding in Japan using a nationwide model, Natural Hazards. https://doi.org/10.1007/s11069-023-05962-7
  11. Zhang, Y., Wu, C.H., Anderson, J., Liu, Y., Danilov, S., Wang, Q., and Wang, Q. (2023) Lake ice simulation using a 3D unstructured grid model. Ocean Dynamics, 73:219–230. https://doi.org/10.1007/s10236-023-01549-9
  12. Lv, Z.†, Nunez, K., Brewer, E.†, Runfola, D. 2023. pyShore: A deep learning toolkit for shoreline structure mapping with high-resolution orthographic imagery and convolutional neural networks. Computers & Geosciences. https://doi.org/10.1016/j.cageo.2022.105296
  13. Horemans, D.M.L., M.A.M. Friedrichs, P. St-Laurent, R.R. Hood, C.W. Brown, 2023. Forecasting Prorocentrum minimum blooms in the Chesapeake Bay using empirical habitat models. Front. Mar. Sci., 10, http://dx.doi.org/10.3389/fmars.2023.1127649
  14. Hinson, K.E., M.A.M. Friedrichs, R.G. Najjar, M. Herrmann, Z. Bian, G. Bhatt, P. St-Laurent, H. Tian, G. Shenk, 2023. Impacts and uncertainties of climate-induced changes in watershed inputs on estuarine hypoxia, Biogeosciences, 20, 1937-1961, http://dx.doi.org/10.5194/bg-20-1937-2023
  15. G. S. Chiu, M. Mitchell, J. Herman, C. Longo, and K. Davis, “Enhancing assessments of blue carbon stocks in marsh soils using Bayesian mixed-effects modeling with spatial autocorrelation — proof of concept using proxy data,” Frontiers in Marine Science, vol. 9. Frontiers Media SA, Jan. 12, 2023. http://dx.doi.org/10.3389/fmars.2022.1056404
 2022
  1. Q. Qin, J. Shen, T. D. Tuckey, X. Cai, and J. Xiong, “Using Forward and Backward Particle Tracking Approaches to Analyze Impacts of a Water Intake on Ichthyoplankton Mortality in the Appomattox River,” Journal of Marine Science and Engineering, vol. 10, no. 9. MDPI AG, p. 1299, Sep. 14, 2022. http://dx.doi.org/10.3390/jmse10091299
  2. Z. Lv, K. Nunez, E. Brewer, and D. Runfola, “pyShore: A deep learning toolkit for shoreline structure mapping with high-resolution orthographic imagery and convolutional neural networks,” Computers & Geosciences, vol. 171. Elsevier BV, p. 105296, Feb. 2023 [Online]. Available: http://dx.doi.org/10.1016/j.cageo.2022.105296
  3. L. S. Storch and S. L. Day, “Topological early warning signals: Quantifying varying routes to extinction in a spatially distributed population model,” Journal of Theoretical Biology, vol. 554. Elsevier BV, p. 111274, Dec. 2022 [Online]. Available: http://dx.doi.org/10.1016/j.jtbi.2022.111274
  4. J. R. Bradley and A. P. Blossom, “The Generation of Visually Credible Adversarial Examples with Genetic Algorithms,” ACM Transactions on Evolutionary Learning and Optimization. Association for Computing Machinery (ACM), Jan. 30, 2023 . Available: http://dx.doi.org/10.1145/3582276
  5. Allan, J.C., Zhang, J., O'Brien, F. and Gabel, L., 2022. "Umpqua River tsunami modeling: Toward improved maritime planning response." Oregon Department of Geology and Mineral Industries, Open-file-report O-22-07, Portland, Oregon, 76 pp.
  6. D. Runfola, H. Baier, L. Mills, M. Naughton‐Rockwell, and A. Stefanidis, “Deep learning fusion of satellite and social information to estimate human migratory flows,” Transactions in GIS, vol. 26, no. 6. Wiley, pp. 2495–2518, Jun. 27, 2022. http://dx.doi.org/10.1111/tgis.12953
  7. E. Brewer, J. Lin, and D. Runfola, “Susceptibility & defense of satellite image-trained convolutional networks to backdoor attacks,” Information Sciences, vol. 603. Elsevier BV, pp. 244–261, Jul. 2022 [Online]. Available: http://dx.doi.org/10.1016/j.ins.2022.05.004
  8. Ethan Brewer. "Deep Learning from Space: Methods & Applications in High-Resolution Satellite Imagery Analysis." W&M Ph.D. Thesis. ProQuest. 2022. https://www.proquest.com/docview/2720899084/4C3EB75C6A884DD8PQ
  9. Wang, H., Gong, D., Friedrichs, M., Harris, C., Miles, T., Yu, H.-C. and Zhang, Y., “A Cycle of Wind-Driven Canyon Upwelling and Downwelling at Wilmington Canyon and the Evolution of Canyon-Upwelled Dense Water on the MAB Shelf,” Frontiers in Marine Science, vol. 9. Frontiers Media SA, Jun. 16, 2022. http://dx.doi.org/10.3389/fmars.2022.866075
  10. Xiang Hu, Timo Hyart, Dmitry I. Pikulin, Enrico Rossi, “Quantum-metric-enabled exciton
    condensate in double twisted bilayer graphene”, Phys. Rev. B 105, L140506 (2022).
  11. S. Saporito and D. Maliniak, Using the areal unit segregation measure to identify racially ‘packed’ and ‘cracked’ legislative districts, Electoral Studies, vol. 80. Elsevier BV, p. 102526, Dec. 2022. Available: http://dx.doi.org/10.1016/j.electstud.2022.102526
  12. Cassidy D. Peterson, Michael J. Wilberg, Enric Cortés, Dean L. Courtney, and Robert J. Latour. Effects of unregulated international fishing on recovery potential of the sandbar shark within the southeastern United States. Canadian Journal of Fisheries and Aquatic Sciences. 79(9): 1497-1513. https://doi.org/10.1139/cjfas-2021-0345
  13. Flynn, E. R., Kuehl, S. A., Harris, C. K., & Fair, M. J. (2022). Sediment and terrestrial organic carbon budgets for the offshore Ayeyarwady Delta, Myanmar: Establishing a baseline for future change. In Marine Geology (Vol. 447, p. 106782). Elsevier BV. https://doi.org/10.1016/j.margeo.2022.106782
  14. Runfola, D., Baier, H., Mills, L., Naughton‐Rockwell, M., & Stefanidis, A. (2022). Deep learning fusion of satellite and social information to estimate human migratory flows. In Transactions in GIS. Wiley. https://doi.org/10.1111/tgis.12953
  15. Brewer, E., Lin, J., Runfola, D., Susceptibility & defense of satellite image-trained convolutional networks to backdoor attacks. In Information Sciences (Vol. 603, pp. 244–261). Elsevier BV. https://doi.org/10.1016/j.ins.2022.05.004
  16. Hannah J. Naldrett and Christopher J. Abelt, "Turn-on Fluorescence of a 6-Acyl-1-Benzoindole by Alcohols," Journal of Photochemistry and Photobiology A: Chemistry 2022, 114121
  17. Brewer, E., Lin, J., & Runfola, D. (2022). Susceptibility & defense of satellite image-trained convolutional networks to backdoor attacks. In Information Sciences (Vol. 603, pp. 244–261). Elsevier BV. https://doi.org/10.1016/j.ins.2022.05.004
  18. Frankel, L.T., M.A.M. Friedrichs, P. St-Laurent, A.J. Bever, R. N. Lipcius, G. Bhatt, G.W. Shenk, 2022. Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling. Science of the Total Environment (814) 152722, https://doi.org/10.1016/j.scitotenv.2021.152722
  19. Cai, X., Qin, Q., Shen, J. and Zhang, Y.J. (2022), Bifurcate responses of tidal range to sea-level rise in estuaries with marsh evolution. Limnol. Oceanogr. Lett, 7: 210-217. https://doi.org/10.1002/lol2.10256
  20. Huang, W., Zhang, Y., Wang, Z., Ye, F., Moghimi, S., Myers, E., Yu, H. (2022) Tidal simulation revisited.  Ocean Dynamics, 72:187-205. https://doi.org/10.1007/s10236-022-01498-9
  21. Wang, Z., Li, D., Xue, H., Thomas, A. C., Zhang, Y. J., & Chai, F. (2022). Freshwater transport in the Scotian Shelf and its impacts on the Gulf of Maine salinity. Journal of Geophysical Research: Oceans, 127, e2021JC017663. https://doi.org/10.1029/2021JC017663
  22. Karthik, N., & Narayanan, R. (2022). Parton physics of the large-N_c mesons. In Physical Review D (Vol. 106, Issue 1). American Physical Society (APS). https://doi.org/10.1103/physrevd.106.014503
  23. Smith, R. D., Puzey, J. R., & Conradi Smith, G. D. (2022). Population genetics of transposable element load: A mechanistic account of observed overdispersion. In R. M. Marsano (Ed.), PLOS ONE (Vol. 17, Issue 7, p. e0270839). Public Library of Science (PLoS). https://doi.org/10.1371/journal.pone.0270839
  24. Brianna N. Peterson, Megan E. Alfieri, David J. Hood, Christian D. Hettwer, Daniel V. Costantino, Daniel P. Tabor, and Nathanael M. Kidwell, Solvent-Mediated Charge Transfer Dynamics of a Model Brown Carbon Aerosol Chromophore: Photophysics of 1-Phenylpyrrole Induced by Water Solvation. The Journal of Physical Chemistry A 2022 126 (27), 4313-4325 DOI: 10.1021/acs.jpca.2c00585
  25. Longo, Christian, "Bayesian Spatial Model Development of Soil Core Organic Matter as a proxy for Blue Carbon Stocks within the Chesapeake Bay" (2022). Undergraduate Honors Theses. William & Mary. Paper 1824.
    https://scholarworks.wm.edu/honorstheses/1824
  26. A. C. Hyman, G. S. Chiu, M. C. Fabrizio, and R. N. Lipcius, “Spatiotemporal Modeling of Nursery Habitat Using Bayesian Inference: Environmental Drivers of Juvenile Blue Crab Abundance,” Frontiers in Marine Science, vol. 9. Frontiers Media SA, Mar. 17, 2022 [Online]. Available: http://dx.doi.org/10.3389/fmars.2022.834990
  27. Metzger, S., & Jones, B. (2022). Getting Time Right: Using Cox Models and Probabilities to Interpret Binary Panel Data. Political Analysis, 30(2), 151-166. doi:10.1017/pan.2021.14
  28. Eskridge, B., Krakauer, H., Shi, H., Zhang, S.  "Ab initio calculations in atoms, molecules, and solids, treating spin–orbit coupling and electron interaction on an equal footing". Journal of Chemical Physics, 156, 014107 (2022); https://aip.scitation.org/doi/10.1063/5.0075900
2021
  1. Dukhovskoy, D. S., Morey, S. L., Chassignet, E. P., Chen, X., Coles, V. J., Cui, L., Harris, C. K., Hetland, R., Hsu, T.-J., Manning, A. J., Stukel, M., Thyng, K., & Wang, J. (2021). Development of the CSOMIO Coupled Ocean-Oil-Sediment- Biology Model. In Frontiers in Marine Science (Vol. 8). Frontiers Media SA. https://doi.org/10.3389/fmars.2021.629299
  2. Brewer, E., Lin, J., Kemper, P., Hennin, J., & Runfola, D. (2021). Predicting road quality using high resolution satellite imagery: A transfer learning approach. In T. R. Gadekallu (Ed.), PLOS ONE (Vol. 16, Issue 7, p. e0253370). Public Library of Science (PLoS). https://doi.org/10.1371/journal.pone.0253370
  3. Runfola, D., Stefanidis, A., & Baier, H. (2021). Using satellite data and deep learning to estimate educational outcomes in data-sparse environments. In Remote Sensing Letters (Vol. 13, Issue 1, pp. 87–97). Informa UK Limited. https://doi.org/10.1080/2150704x.2021.1987575
  4. Bahgat, K., & Runfola, D. (2021). Toponym-assisted map georeferencing: Evaluating the use of toponyms for the digitization of map collections. In C. R. da Silva (Ed.), PLOS ONE (Vol. 16, Issue 11, p. e0260039). Public Library of Science (PLoS). https://doi.org/10.1371/journal.pone.0260039
  5. Qiong Wu, Adam Hare, Sirui Wang, Yuwei Tu, Zhenming Liu, Christopher G. Brinton, and Yanhua Li. 2021. BATS: A Spectral Biclustering Approach to Single Document Topic Modeling and Segmentation. ACM Trans. Intell. Syst. Technol. 12, 5, Article 54 (October 2021), 29 pages. https://doi.org/10.1145/3468268
  6. Scavia, D., I. Bertani, J.M. Testa, A.J. Bever, J.D. Blomquist, M.A.M. Friedrichs, L.C. Linker, B.D. Michael, R.R. Murphy, G.W. Shenk, 2021. Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay. Ecological Applications, 31(6), e02384, https://doi.org/10.1002/eap.2384
  7. Lopez, A.G., R.G. Najjar, M.A.M. Friedrichs, M.A. Hickner, D.H. Wardrop, 2021. Estuaries as filters for riverine microplastics: simulations in a large, coastal-plain estuary. Front. Mar. Sci., 8, https://doi.org/10.3389/fmars.2021.715924
  8. Kopera, K. M.; Tuckman, H.G.; Hoy, G.R.;  Wustholz, K.L. Origin of Kinetic Dispersion in Eosin-Sensitized TiO2: Insights from Single-Molecule Spectroscopy. J. Phys. Chem. C 2021, 125, 43, 23634–23645
  9. Karpie, J., Orginos, K., Radyushkin, A. et al. The continuum and leading twist limits of parton distribution functions in lattice QCD. J. High Energ. Phys. 2021, 24 (2021). https://doi.org/10.1007/JHEP11(2021)024
  10. Nunez, K. Zhang, Y., Bilkovic, D.M., Hershner, C. (2021) Coastal Setting Determines Tidal Marsh Sustainability with Accelerating Sea-level Rise. Ocean and Coastal Management, 214, 105898.
  11. Brewer E, Lin J, Kemper P, Hennin J, Runfola D (2021) Predicting road quality using high resolution satellite imagery: A transfer learning approach. PLoS ONE 16(7): e0253370. https://doi.org/10.1371/journal.pone.0253370
  12. Hinson, K.E., Friedrichs, M.A.M., St-Laurent, P., Da, F., & Najjar, R.G. (2021). Extent and causes of Chesapeake Bay warming. Journal of the American Water Resources Association, 1-21, https://doi.org/10.1111/1752-1688.12916.
  13. Karthik, N. (2021). Quark distribution inside a pion in many-flavor ( 2+1 )-dimensional QCD using lattice computations: UV listens to IR. Physical Review D, 103(7). https://doi.org/10.1103/physrevd.103.074512
  14. Turner, J. S., St-Laurent, P., Friedrichs, M. A. M., & Friedrichs, C. T. (2021). Effects of reduced shoreline erosion on Chesapeake Bay water clarity. Science of the Total Environment, 769, 145157. https://doi.org/10.1016/j.scitotenv.2021.145157 
  15. Moriarty, J.M., M.A.M. Friedrichs, C.K. Harris. 2021. Seabed resuspension on primary productivity and remineralization in the Chesapeake Bay: Implications for dissolved oxygen and ammonium. Estuaries and Coasts,44, pages103–122. https://doi.org/10.1007/s12237-020-00763-8
  16. Zhang, Y. J. (2021). Assessment of subgrid method in a finite-volume model. Computers & Mathematics with Applications, 81, 220–236. https://doi.org/10.1016/j.camwa.2020.05.002
  17. Huang, W., Ye, F., Zhang, Y. J., Park, K., Du, J., Moghimi, S., Myers, E., Pe’eri, S., Calzada, J. R., Yu, H. C., Nunez, K., & Liu, Z. (2021). Compounding factors for extreme flooding around Galveston Bay during Hurricane Harvey. Ocean Modelling, 158, 101735. https://doi.org/10.1016/j.ocemod.2020.101735
  18. Cui L, Harris CK and Tarpley DRN (2021) Formation of Oil-Particle-Aggregates: Numerical Model Formulation and Calibration. Front. Mar. Sci. 8:629476. doi: 10.3389/fmars.2021.629476
  19. Ye, F. and Huang, W. and Zhang, Y. J. and Moghimi, S. and Myers, E. and Pe'eri, S. and Yu, H.-C. (2021) A cross-scale study for compound flooding processes during Hurricane Florence, 21, 1703-1719, Natural Hazards and Earth System Sciences, https://nhess.copernicus.org/articles/21/1703/2021
  20. Cai, X., J. Shen, Y.J. Zhang, Q. Qin, Z. Wang, and H.V Wang. (2021) Impacts of Sea-Level Rise on Hypoxia and Phytoplankton Production in Chesapeake Bay: Model Prediction and Assessment. Journal of the American Water Resources Association 118. https://doi.org/10.1111/1752-1688.12921
  21. Bever, A.J., M.A.M. Friedrichs, P. St-Laurent. 2021. Real-time environmental forecasts of the Chesapeake Bay: Model setup, improvements, and online visualization. Environmental Modeling and Software 140. DOI: 10.1016/j.envsoft.2021.105036
  22. Thomas, Stuart and Monahan, Christopher, "Topology of the O(3) non-linear sigma model under the gradient flow" (2021). Undergraduate Honors Theses. Paper 1621.
    https://scholarworks.wm.edu/honorstheses/1621
  23. Dartiailh, M.C., Cuozzo, J.J., Elfeky, B.H. et al. Missing Shapiro steps in topologically trivial Josephson junction on InAs quantum well. Nat Commun 12, 78 (2021). https://doi.org/10.1038/s41467-020-20382-y
  24. Beckensteiner, J., A. Scheld, P. St-Laurent, M.A.M. Friedrichs, D. Kaplan, 2021, Environmentally-determined production frontiers and lease utilization in Virginia’s eastern oyster aquaculture industry, Aquaculture, https://doi.org/10.1016/j.aquaculture.2021.736883
  25. Chappie, Emily E., "Molecular Cluster Fragment Machine Learning Training Techniques to Predict Energetics of Brown Carbon Aerosol Clusters" (2021). Undergraduate Honors Theses. Paper 1622. https://scholarworks.wm.edu/honorstheses/1622
Oral/Poster Presentations:
  1. Huffman, M., Ward, E., Kay, J., Rhoden, A., & Stickle, A. (2021). 5-Phase Ice Simulations to Test the Effects of Embedded Low Viscosity Layers on Crater Formation. In Lunar and Planetary Science Conference (pp. 1663). 
  2. Chappie, E. E., Tabor, D. P. and Kidwell, N. M. (2021). Molecular Fragment Machine Learning Training Techniques to Predict Cluster Energetics and Frequencies in Brown Carbon Aerosol Clusters. In International Symposium on Molecular Spectroscopy
  3. Turner, J. S. (2021). Water clarity and suspended particle dynamics in the Chesapeake Bay: local effects of oyster aquaculture, regional effects of reduced shoreline erosion, and long-term trends in remotely sensed reflectance. Virginia Institute of Marine Science, William & Mary. Ph. D. Dissertation.
  4. Dan Yu, Joseph Zhang, Lars Nerger, Jason Yu, C. Chu, C. Terng (2021) Ensemble data assimilation in a 3D unstructured grid ocean model with application to typhoon study, American Geophysical Union Fall Meeting.
  5. Thomas, Stuart and Monahan, Christopher, "Topology of the O(3) non-linear sigma model under the gradient flow" (2021). Undergraduate Honors Theses. William & Mary. Paper 1621.
  6. Frankel, Luke, 2021. Quantifying the increased resiliency of Chesapeake Bay Hypoxia to environmental conditions: a benefit of nutrient reductions. VIMS MS thesis.
2020
  1. Angello, N.H.; Wiley, R.E.; Abelt, C.J.; Scheerer, J.R. Synthesis and Spectrophotometric Analysis of 1-Azafluorenone Derivatives. Molecules 2020, 25, 3358.
  2. Wang, C., Z. Liu, C.K. Harris, X. Wu, H. Wang, C. Bian, N. Bi, H. Duan, J. Xu. 2020. The impact of winter storms on sediment transport through a narrow strait, Bohai, China, Journal of Geophysical Research – Oceans. https://doi.org/10.1029/ 2020JC016069.
  3. Runfola, D.; Batra, G.; Anand, A.; Way, A.; Goodman, S. Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach. Sustainability 2020, 12, 3225.
  4. Runfola D, Anderson A, Baier H, Crittenden M, Dowker E, Fuhrig S, et al. (2020) geoBoundaries: A global database of political administrative boundaries. PLoS ONE 15(4): e0231866. https://doi.org/10.1371/journal.pone.0231866

  5. Goodman, S, BenYishay, A, Runfola, D. A convolutional neural network approach to predict non‐permissive environments from moderate‐resolution imagery. Transactions in GIS. 2020; 00: 1– 18. https://doi.org/10.1111/tgis.12661

  6. St-Laurent, P., M.A.M. Friedrichs, R.G. Najjar, E.H. Shadwick, H. Tian, Y. Yao, E.G. Stets (2020) Relative impacts of global changes and regional watershed changes on the inorganic carbon balance of the Chesapeake Bay, Biogeosciences, 17, 3779-3796. https://doi/10.5194/bg-17-3779-2020

  7. Kim, G.E., St-Laurent, P., Friedrichs, M.A.M. et al. Impacts of Water Clarity Variability on Temperature and Biogeochemistry in the Chesapeake Bay. Estuaries and Coasts, (2020).  https://doi.org/10.1007/s12237-020-00760-x

  8. Solis, J., & Waggoner, P. (2020). Measuring Media Freedom: An Item Response Theory Analysis of Existing Indicators. British Journal of Political Science, 1-20. https://doi/10.1017/S0007123420000101

  9. Nunez, K., Zhang, Y.J., Herman, J., Reay, W., and Hershner, C. (2020) A multi-scale approach for simulating tidal marsh evolution. Ocean Dynamics. https://doi.org/10.1007/s10236-020-01380-6

  10. Zhang, Y.J., Ye, F., Yu, H. et al. Simulating compound flooding events in a hurricane. Ocean Dynamics 70, 621–640 (2020). https://doi.org/10.1007/s10236-020-01351-x
  11. Liu, Z., Wang, H.V., Zhang, Y., Magnusson, L., Loftis, J.D., and Forrest, D. (2020) Cross-scale modeling of storm surge, tide, and inundation in Mid-Atlantic Bight and New York City during Hurricane Sandy, 2012, Estuarine, Coastal and Shelf Science, 233. https://doi.org/10.1016/j.ecss.2019.106544  
  12. Du, J., Park, K., Yu, X., Zhang, Y., Ye, F. (2020) Massive pollutants released to Galveston Bay during Hurricane Harvey: Understanding their retention and pathway using Lagrangian numerical simulations, Science of The Total Environment, 704. https://doi.org/10.1016/j.scitotenv.2019.135364
  13.  Ye, F., Zhang, Y., Yu, H., Sun, W., Moghimi, S., Myers, E.P., Nunez, K., Zhang, R., Wang, H.V., Roland, A., Martins, K., Bertin, X., Du, J., and Liu, Z. (2020) Simulating storm surge and compound flooding events with a creek-to-ocean model: importance of baroclinic effects, Ocean Modelling, 145.https://doi.org/10.1016/j.ocemod.2019.101526  
  14. Chiciak, A.; Vitali, E.; Zhang, S. Magnetic and Charge Orders in the Ground State of the Emery Model: Accurate Numerical Results. Phys. Rev. B 2020, 102 (21). https://doi.org/10.1103/physrevb.102.214512.
  15. Allan, J.C., Zhang, J., O'Brien, F. and Gabel, L., 2020. Coos Bay tsunami modeling: Toward improved maritime planning response. Oregon Department of Geology and Mineral Industries Open-file-report O-20-08, Portland, Oregon, 78 pp.
  16. Sufian, R. S.; Egerer, C.; Karpie, J.; Edwards, R. G.; Joó, B.; Ma, Y.-Q.; Orginos, K.; Qiu, J.-W.; Richards, D. G. Pion Valence Quark Distribution from Current-Current Correlation in Lattice QCD. Phys. Rev. D 2020, 102 (5). https://doi.org/10.1103/physrevd.102.054508.
  17. Ibrahim, M. A.; Kayiran, O.; Eckert, Y.; Loh, G. H.; Jog, A. Analyzing and Leveraging Shared L1 Caches in GPUs. In Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques; ACM, 2020. https://doi.org/10.1145/3410463.3414623.
  18. Liu, H.; Pai, S.; Jog, A. Why GPUs Are Slow at Executing NFAs and How to Make Them Faster. In Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems; ACM, 2020. https://doi.org/10.1145/3373376.3378471.
  19. Kadam, G.; Zhang, D.; Jog, A. BCoal: Bucketing-Based Memory Coalescing for Efficient and Secure GPUs. In 2020 IEEE International Symposium on High Performance Computer Architecture (HPCA); IEEE, 2020. https://doi.org/10.1109/hpca47549.2020.00053.
  20. Herrmann, M.; Najjar, R. G.; Da, F.; Friedman, J. R.; Friedrichs, M. A. M.; Goldberger, S.; Menendez, A.; Shadwick, E. H.; Stets, E. G.; St‐Laurent, P. Challenges in Quantifying Air‐Water Carbon Dioxide Flux Using Estuarine Water Quality Data: Case Study for Chesapeake Bay. J. Geophys. Res. Oceans 2020, 125 (7). https://doi.org/10.1029/2019jc015610.
  21. Crear, D.; Latour, R.; Friedrichs, M.; St-Laurent, P.; Weng, K. Climate sensitivity of a Shark Nursery Habitat to a Changing Climate. Mar. Ecol. Prog. Ser. 2020, 652, 123–136. https://doi.org/10.3354/meps13483.
  22. Crear, D. P.; Watkins, B. E.; Friedrichs, M. A. M.; St-Laurent, P.; Weng, K. C. Estimating Shifts in Phenology and Habitat Use of Cobia in Chesapeake Bay Under Climate Change. Front. Mar. Sci. 2020, 7. https://doi.org/10.3389/fmars.2020.579135.
  23. Cai, X.; Zhang, Y. J.; Shen, J.; Wang, H.; Wang, Z.; Qin, Q.; Ye, F. A Numerical Study of Hypoxia in Chesapeake Bay Using an Unstructured Grid Model: Validation and Sensitivity to Bathymetry Representation. J Am Water Resour Assoc 2020. https://doi.org/10.1111/1752-1688.12887.
  24. Chang, J.; Lee, G.; Harris, C. K.; Song, Y.; Figueroa, S. M.; Schieder, N. W.; Lagamayo, K. D. Sediment Transport Mechanisms in Altered Depositional Environments of the Anthropocene Nakdong Estuary: A Numerical Modeling Study. Marine Geology 2020, 430, 106364. https://doi.org/10.1016/j.margeo.2020.106364.
  25. Harris, C.; Syvitski, J.; Arango, H. G.; Meiburg, E. H.; Cohen, S.; Jenkins, C. J.; Birchler, J.; Hutton, E. W. H.; Kniskern, T. A.; Radhakrishnan, S.; Auad, G. Data-Driven, Multi-Model Workflow Suggests Strong Influence from Hurricanes on the Generation of Turbidity Currents in the Gulf of Mexico. JMSE 2020, 8 (8), 586. https://doi.org/10.3390/jmse8080586.
  26. Wang, C.; Liu, Z.; Harris, C. K.; Wu, X.; Wang, H.; Bian, C.; Bi, N.; Duan, H.; Xu, J. The Impact of Winter Storms on Sediment Transport Through a Narrow Strait, Bohai, China. J. Geophys. Res. Oceans 2020, 125 (6). https://doi.org/10.1029/2020jc016069.
  27. B. Joó, J. Karpie, K. Orginos, A. V. Radyushkin, D. G. Richards and S. Zafeiropoulos, Parton Distribution Functions from Ioffe Time Pseudodistributions from Lattice Calculations: Approaching the Physical Point, Phys. Rev. Lett. 125 (2020) 232003, [2004.01687].
  28. Da, F., Friedrichs, M.A.M., St-Laurent, P., Shadwick, E.H., Najjar, R.G., & Hinson, K. (2020). Mechanisms driving decadal change in the carbonate system of a coastal plain estuary. Journal of Geophysical Research: Oceans, 126(6), e2021JC017239. https://doi.org/10.1029/2021JC017239
  29. Allan, J.C., Zhang, J., O'Brien, F. and Gabel, L., 2020. Coos Bay tsunami modeling: Toward improved maritime planning response. Oregon Department of Geology and Mineral Industries open-file-report O-20-08, Portland, Oregon, 78 pp. https://www.oregongeology.org/pubs/ofr/p-O-20-08.htm
Oral/Poster Presentations:

  1. Turner, J.S., St-Laurent, P., Friedrichs, M.A.M., & Friedrichs, C.T. (2020) Water clarity impacts of sediment inputs from shoreline erosion in the Chesapeake Bay: a modeling study. June 8, 2020 at the Chesapeake Community Research Symposium, Annapolis, MD (Online due to COVID-19). 

  2. Turner, J. S., St-Laurent, P., Friedrichs, M. A. M., & Friedrichs, C. T. Shoreline erosion impacts on Chesapeake Bay water clarity: an analysis of effects on light attenuation using a coupled hydrodynamic-biogeochemical model. Ocean Sciences meeting in San Diego, CA in February 2020.

  3. Kopera, K.M., Tuckman, H.G., Wustholz, K.L. Investigating Electron Transfer Dynamics of Eosin \
    Y on TiO2 Using Single Molecule Spectroscopy and Monte Carlo Simulations. 29th Winter Inter-American Photochemical Society Conference, January 2020, Sarasota, FL.

  4. Hinson, K.E., Friedrichs, M.A.M., St-Laurent, P., Najjar, R.G., & Da, F. (2020) Drivers of warming in the Chesapeake Bay: a 35-year retrospective analysis. June 8, 2020 at the Chesapeake Community Research Symposium, Annapolis, MD (Online due to COVID-19).

  5. Hinson, K.E., Friedrichs, M.A.M., St-Laurent, P., Najjar, R.G. (2020) A thirty-year retrospective analysis of Chesapeake Bay warming, Abstract [CB34A-03] at 2020 Ocean Sciences Meeting, San Diego, CA, 16-21 Feb.

  6. Bever, A.J., M.C. Fabrizio, M.A.M. Friedrichs, and T.D. Tuckey. 2020. Estimating Habitat Suitability for Forage Fish in Chesapeake Bay: Does the Choice of the Hydrodynamic Model Matter? Chesapeake Research and Modeling Symposium. 8-10 Jun

  7.  Bever, A.J., M.A.M. Friedrichs, D. Da, K. Hudson, P. St-Laurent, and A. Morandi. 2020. Real-time Forecasts of Acidification and Hypoxia in the Chesapeake Bay: Model Setup and Online Visualization. Ocean Sciences. San Diego, CA 16-21 Feb\